Temple Mobility Master Plan Appendix B

Appendix B

TABLE OF CONTENTS

List of Figures ............................................................................................................................................................. iii

List of Tables ................................................................................................................................................................ v

Introduction .................................................................................................................................................................. 1

Socioeconomic Conditions 3

Demographic Overview 3 Land Use 19 Key Findings 21

Safety Analysis........................................................................................................................................................... 23

Methodology 23

Data Sources 24

Results of Safety Analysis 24

Crash Rate Analysis 29

Intersection Analysis 34

Contributing Factors Analysis 35 Severity, Mode Split, and Active Transportation 40 Key Findings 43

Transportation Supply ............................................................................................................................................... 45 Master Thoroughfare Plan 45 Transportation Supply Gaps Analysis 46 Key Findings 55

Transportation Demand Modeling ............................................................................................................................ 56 Methods 56

Existing Conditions Analysis Results 57 Forecast Conditions 61 Future Capacity Deficiencies 61 Key Findings 63

Traffic Congestion and Level of Service .................................................................................................................. 65 Methodology and Data Sources 65

Existing Operational Performance Results 65 Future Operational Deficiencies Analysis 70

Transportation Demand Management 74 Methodology and Data Sources 74 Existing Programs and Policy 74 Key Findings 76

Transit ......................................................................................................................................................................... 78 System Overview 78 Methodology and Data Sources 81 Ridership Analysis 82 Key Findings 87

Active Transporation ................................................................................................................................................. 88

Existing Facilities 88 Bicycling Comfort 90 Active Transportation Demand 92 Planned Improvements 94 Key Findings 94

Gaps Analysis 96

Freight Network and Commodity Flows ................................................................................................................... 98 Existing Freight Network 98

Current Commodity Flows 99

Trading Partners 102

Infrastructure Asset Evaluation 105

Bridge Conditions 106 Pavement Conditions 107 Airport 110 Next Steps ................................................................................................................................................................ 112

LIST OF FIGURES

Figure 1: Study Area Map 2

Figure 2: The City of Temple and ETJ Total Population (2005 2019) 4

Figure 3: The City of Temple and ETJ Household Median Income (2005 2019) 4

Figure 4: Population and Employment Density by Block Group (2019) 5

Figure 5: Percent Change in Population and Employment by Block Group (2010 2019/2018) 6

Figure 6: Population and Employment by TAZ (2045) 7

Figure 7: Percent Change in Population and Employment from 2019 to 2045 by TAZ 8

Figure 8: City of Temple and ETJ Population Pyramid (2019 and 2045) ....................................................................... 9

Figure 9: Bell County Race and Ethnicity (2015 2019) .............................................................................................. 10

Figure 10: The City of Temple and ETJ Race and Ethnicity (2005 2019) 11

Figure 11: Bell County Labor Force (2015 2019) 12

Figure 12: Bell County Civilian Employment by Industry (2015 2019) 13

Figure 13: The City of Temple and ETJ Employment by Industry (2005 2019) 14

Figure 14: Bell County Household Median Income (2015 2019) 15

Figure 15: Bell County Households by Income Bracket (2015 2019) 16

Figure 16: Environmental Justice Zones 17

Figure 17: Housing and Transportation Costs as a Percent of the Area's Median Income 18

Figure 18: The City of Temple and ETJ Future Land Use Plan 19

Figure 19: City of Temple Zoning (2020) 21

Figure 20: Crash Summary by Severity by Year; 2016 2020 25

Figure 21: 5 Year Crash Counts by Corridor; 2016 2020 26

Figure 22: 5 Year Count of Persons Involved in Crashes by Corridor; 2016 2020 27

Figure 23: 5 Year Count of Fatalities by Corridor; 2016 2020 28

Figure 24: 5 Year Count of Serious Injuries by Corridor; 2016 2020 29

Figure 25: 5 Year Crash Rates by Segment; 2016 2020 31

Figure 26: 5 Year Rate of Fatalities by Segment; 2016 2020 32

Figure 27: 5 Year Rate of Serious Injuries; 2016 2020 33

Figure 28: Speed Related Crashes; non Interstate; 2016 2020 ................................................................................ 38

Figure 29: Failure to Yield Related Crashes; Angle Collisions; 2016 2020 ............................................................... 39

Figure 30: Failure to Yield Related Crashes; Opposite Direction Collisions; 2016 2020 40

Figure 31: Mode Split and Severity Outcomes; 2016 2020 41

Figure 32: Active Transportation Crashes by Severity; 2016 2020 42

Figure 33: FHWA Proven Safety Countermeasures 44

Figure 34: Temple 2020 Thoroughfare Plan 45

Figure 35: Snapshot of Traffic on Avenue H and 31st 46

Figure 36: Aerial View of Avenue H and 31st 47

Figure 37: Street view looking East 47

Figure 38: Total Crashes 2016 to 2020 by Injury ......................................................................................................... 48

Figure 39: Total Crashes Person Level Outcome 48

Figure 40: West Temple Commuters 50

Figure 41: North Pea Ridge 51

Figure 42: Residential developments along Hartrick Bluff 51

Figure 43: Improved Section of 31st Street 52

Figure 44: Unimproved Section of 31st Street 52

Figure 45: Central and Adams Ave. Corridor 53

Figure 46: Adams Street view 53

Figure 47: Central Ave Street view............................................................................................................................... 53

Figure 48: Industrial Boulevard .................................................................................................................................... 54

Figure 49: Martin Luther King Jr. Boulevard 54

Figure 50: Temple Subarea Level of Service 2015 Existing Conditions 60

Figure 51: Temple Subarea Level of Service 2045 Forecast Conditions 61

Figure 52: Existing Conditions TransModeler Network Loop 363 and 31st Street 66

Figure 53: Total Network Delay by Time Period 67

Figure 54: 2021 AM Peak Delay 68

Figure 55: 2021 PM Peak Delay 69

City of Temple Mobility Master Plan

Comprehensive System Assessment

Figure 56: 2021 Total VMT by Time Period 70

Figure 57: Future AM Intersection LOS Map 72

Figure 58: Future PM Intersection LOS Map ................................................................................................................ 73

Figure 59: The HOP Service Categories 79

Figure 60: The HOP Key Transfer Locations 80

Figure 61: Existing Fixed Transit Routes and Stops The HOP 81

Figure 62: Route 200 Ridership by Stop 83

Figure 63: Route 510 Ridership by Stop 83

Figure 64: Route 530 Ridership by Stop 84

Figure 65: Target Transit Riders Served 85

Figure 66: Population and Employment Served 86

Figure 67: Transit Market Served by Existing System 87

Figure 68: Sidewalk Condition in City of Temple 89

Figure 69: Existing Sidewalk and Hike & Bike Trails .................................................................................................... 89

Figure 70: LTS Scores in Study Area 92

Figure 71: Likely Active Transportation Demand 93

Figure 72: Existing and Planned Bicycle Facilities 94

Figure 73: Active Transportation Facilities in EJ Zones 95

Figure 74: Regional Overview of the City of Temple 98

Figure 75: Texas Rail and Freight Network Temple 99

Figure 76: Bell County Outbound Tonnage 103

Figure 77: Bell County Inbound Tonnage 103

Figure 78: Bell County Outbound Tonnage within Texas ........................................................................................... 104

Figure 79: Bell County Inbound Tonnage within Texas .............................................................................................. 104

Figure 80: Existing Rail Freight Offload Sites 105

Figure 81: Bridge Condition Map; All Bridges 107

Figure 82: PCI Breakdown 108

Figure 83: HPMS IRI Ratings Map 110

Figure 84: TPL Airport Master Plan Master Plan Concept 111

Comprehensive System Assessment

LIST OF TABLES

Table 1: Demographic Overview of the City of Temple MMP Study Area 3

Table 2: Future Land Use Distribution 20

Table 3: High Crash Count Corridors 26

Table 4: Count of Crashes Related to Intersections; 2016 2020 34

Table 5: Percentage of Crashes at or Related to Intersections; 2016 2020 34

Table 6: Top Crash Intersections; 2016 2020 35

Table 7: Top Ten Contributing Factors; 2016 2020 36

Table 8: Top Ten Contributing Factors with Fatalities or Severe Injuries; 2016 2020 ............................................... 36

Table 9: Contributing Factors for Active Transportation Crashes; 2016 2020 ........................................................... 43

Table 10: Lighting Conditions 49

Table 11: Surface Conditions 49

Table 12: Weather Conditions 49

Table 13: Temple Subarea Existing Traffic & Congestion Performance Measures 58

Table 14: Temple Subarea Existing Roadway Capacity Measures 59

Table 15: Temple Subarea Existing Level of Service (LOS) 59

Table 16: Total Number of Intersections with Unacceptable LOS 66

Table 17: Existing Conditions Top Intersections with High/Failing LOS for AM Peak Period 67

Table 18: Existing Conditions Top Intersections with High/Failing LOS for PM Peak Period 68

Table 19: Future Conditions Top Intersections with Failing LOS for AM Peak Period 71

Table 20: Future Conditions Top Intersections with Failing LOS for PM Peak Period 71

Table 21: Commute Mode Share for Temple 76

Table 22: Existing Fixed Transit Routes The HOP 78

Table 23: Sidewalk Coverage in City of Temple 89

Table 24: LTS Score and User Accommodation 91

Table 25: Summary of LTS Scores in Study Area 91

Table 26: Active Transportation Demand Input Factors 93

Table 27: Critical Active Transportation Network Gap locations 96

Table 28: Critical Roadway AT Network Gaps ............................................................................................................. 97

Table 29: 2015 Inbound/Outbound Cargo Tonnage from TX SAM V4 Model ............................................................ 100

Table 30: Truck Volumes and Percentages 101

Table 31: Top Inbound Trading Partners 102

Table 32: Top Outbound Trading Partners 102

Table 33: Status of System within Study Area 106

Table 34: Status of System Within Study Area Within NHS Network 106

Table 35: Mileage Distribution 108

Table 36: Functional Class Breakdown 109

INTRODUCTION

The comprehensive systems assessment for the Temple Mobility Master Plan (MMP) has been performed to ensure that the investments recommended by the plan are based on quantitative evaluation of the needs of the City of Temple. An early stage in the plan development used public and stakeholder input to draft a statement of vision for the City supported by broad goal statements, each with specific objectives. Quantifiable and measurable system performance measures were defined for each of the objectives and these performance measures were used to identify the areas of transportation needs within the City. This process of defining a vision statement with corresponding goals, objectives and performance measures is essential to a data driven and outcomes based decision making process for the MMP. The needs that drive the recommendations are determined by infrastructure or service gaps that are identified by comparing existing or future travel demand with the existing transportation system.

As part of the multimodal comprehensive system assessment for the Temple MMP, the transportation system existing conditions were analyzed. Each step in the analysis used the most recent data available for the subject matter as a surrogate for 2021 existing conditions. The analysis covers the incorporated City of Temple and its extraterritorial jurisdiction (ETJ) boundary (Figure 1). Consistent with the statement of the vision, the goals, and the objectives of the Temple MMP, an analysis of mobility, accessibility, connectivity, and other performance factors was performed for 10 categories:

• Current Socioeconomic Conditions

• Transportation Supply

• Transportation Demand

• Traffic Congestion and Level of Service (LOS)

• Safety

• Transit

• Active Transportation

• Freight Network and Industrial Flows

• Infrastructure Asset Evaluation

• Gap/Deficiencies Analysis

Analysis of the Existing Conditions provided a baseline for the transportation system performance assessment. This baseline was compared with forecasts and modeling of anticipated future conditions to show change in the system over time. The future conditions analysis provided in this assessment includes a review of socioeconomic forecasts, forecast conditions, capacity deficiencies analysis, operational deficiencies analysis, and provides initial recommendation for the development and testing of alternative solutions.

City of Temple Mobility Master Plan

Figure 1: Study Area Map

SOCIOECONOMIC CONDITIONS

An important step in identifying transportation needs in the study area is to capture, as much as possible, an in depth understanding of the existing population and employment trends occurring in the area. Land use patterns and demographic trends directly influence which modes of travel people use. In areas where development is spread out and land uses are separated, people are more likely to use personal automobiles and travel further distances throughout the day. In contrast, areas with dense, mixed use development typically have shorter trips and higher utilization of alternative modes of transportation, such as transit, bicycles, and walking. Likewise, the growth trends occurring in the study area have an impact on the performance of the transportation system over time and how users will interact with the system both now and in the future.

The analysis of needs for the existing transportation system and forecast years were supplemented where necessary and/or appropriate with public or stakeholder input derived from outreach and surveys of transportation system users. Population growth and density are important trends to understand when planning local transportation systems, as areas of higher population density are most functional when planned to be accessible by multiple transportation modes. By examining where people live within the study area, and where growth is occurring, decisions can be made of where multimodal facility investment could be best spent to help the greatest number of people.

The following sections discuss both current and projected population, employment and other socioeconomic metrics for the Temple MMP study area consisting of the City of Temple municipal boundary and the surrounding ETJ. Where it is useful for context or comparative purposes, data at the county or state level are also presented.

Population

The geographic distribution of population by socioeconomic cohort and the population growth trends in the study area are important factors used to interpret the demand on the multimodal transportation systems in the City. The density of population also affects how the various modes of transportation function to meet community needs. Examining where people live and where growth is occurring helps inform decisions on multimodal facility investment that helps the greatest number of Temple residents.

Table 1 provides an overview of the current and projected population and employment as well as the median age, income, and poverty level for the Temple MMP study area In 2019, the population of the City of Temple plus the ETJ was approximately 134,000 people, and in 2018, there were nearly 60,000 jobs located in the study area. The population is expected to grow by roughly 34% and employment by 66% over the next 25 years (2045).

City of Temple Mobility Master Plan

Temple MMP Study Area Population and Employment

Over the past decade, the City of Temple and its ETJ have seen a significant amount of population growth, particularly in the past five years, which has seen almost a 10% increase when compared to the average population from 2010 2014 (Figure 2). This parallels the 8% population growth seen from 2015 to 2019 within the county. Note that the Temple MMP study area contains almost 40% of the total population within Bell County

Figure 2: The City of Temple and ETJ Total Population (2005 2019)

135,000

130,000

125,000

120,000

115,000

Population Count ACS 5-Year Data Range

110,000

140,000 2005 - 2009 2010 - 2014 2015 - 2019

Source: ACS 5 YR (2019, 2014), IPUMS NHGIS ACS 5 YR (2009)

A similar upward trend in household median income can be seen in Figure 3, with significant increases over the second half of the past decade. Note that the household median income is almost $5,000 more within the Temple MMP study area when compared to Bell County.

Figure 3: The City of Temple and ETJ Household Median Income (2005 2019)

Householde Median Income (2021 Dollars)

City of Temple and ETJ Household Median Income (20052019)

61,000

60,500

60,000

59,500

59,000

58,500

58,000

The City of Temple and ETJ Total Population (2005 2019) 57,500

2005 - 2009 2010 - 2014 2015 - 2019

ACS 5 Year Data Range

Source: ACS 5 YR (2019, 2014), IPUMS NHGIS ACS 5 YR (2009)

City of Temple Mobility Master Plan

Figure 4 shows population and employment density (per square mile) within the Temple MMP study area. Population and employment are symbolized by gradient of yellow and blue, respectively, where darker colors indicate higher density. As expected, population and employment are concentrated near downtown Temple with lower density employment surrounding the City’s core.

Population growth in the City’s core has outpaced employment over the past decade. While Figure 4 illustrates the densities of subareas where people live and work, Figure 5 describes how these subareas are growing in terms of percent change over time.

Figure 4: Population and Employment Density by Block Group (2019)

Source: ACS 5 YR (2019), LEHD (2018), Decennial Census (2010), LEHD (2010)

• Low density population and employment growth on the outskirts of the City

• Moderate population and employment density just north of FM 93, an area that has seen a high rate of residential growth

• High population growth but only moderate employment growth in the northwestern suburbs of the City of Temple

• Major employment growth directly north of the City of Temple

• Employment growth south of FM 93 and in the vicinity of the US 190 interchange

Figure 5: Percent Change in Population and Employment by Block Group (2010 - 2019/2018)

Figure 6: Population and Employment by TAZ (2045)

Trends identified in the map include:

• Growth will expand into the ETJ.

• Population and employment will grow in parts of Temple adjacent to communities (e.g., Belton, Troy).

• Population will increase north of downtown.

• Population and employment within Loop 363 will increase.

• Employment will increase to the northwest of downtown, specifically around Loop 363.

• Employment will continue to grow along I 35

Temple Mobility Master Plan

Figure 6 shows population and employment density (per square mile) within the Temple MMP study area as projected for 2045 by traffic analysis zones (TAZ)

Source: American Community Survey (ACS) 5 YR (2019) + Projected populations use TexPACK V 2.4 KT

Figure 7 shows the percent change of population and employment growth (per square mile) within the Temple MMP study area from 2019 to 2045.

Figure 7: Percent Change in Population and Employment from 2019 to 2045 by TAZ

Source: American Community Survey (ACS) 5 YR (2019) + Projected populations use TexPACK V 2.4 KT

Trends identified in the map include:

• High percentage of growth in population along Loop 363 and south of SH 190.

• An increase in employment in the northwest portion of the study area, surrounding Pendleton.

• Low to moderate population growth rate near existing residential development

• A moderate to high percent change in employment in most TAZs.

• Low change for both population and employment around Belton Lake on all sides except to the west near Fort Hood.

City of Temple Mobility Master Plan

Temple MMP Study Area Age & Sex

The 2019 study area population was relatively young, with a median age of 38, and the overall age distribution was comparable to that of the United States as a whole. Figure 8 compares 2019 and 2045 population by age cohort, with shaded areas representing growth and red outlines representing decline that is expected to occur if the City continues to grow at the current rate. Looking closer at Figure 8, three distinct patterns emerge:

1. A small but growing elderly population (65 years and older)

2. A growing middle aged population (25 39 years old).

3. A declining older adult population (40 54 years old)

As is the reality in most U.S. cities, the elderly population is growing, which is shown by the projected growth in almost all age groups 65 and over. There is also expected growth shown in the bars representing age groups between 25 and 39. Contrastingly, there is expected to be significant decline in older adults ages 40 to 54. The consistency in the City’s young population is represented by the largely unchanging structure of the lower portion of the chart. Contextualizing age and transit users, the American Public Transportation Association (APTA) has found that 79% of transit riders fall within the 25 to 54 age range (Clark, 2017) A large portion of the population (43%) within the Temple MMP study area falls within the highest transit users prime age range. Looking into the future, this age group declines by roughly 3% a majority of which occurs within the older adult category.

Figure 8: City of Temple and ETJ Population Pyramid (2019 and 2045)

Source: ACS 5 YR (2019), Decennial Census (2010)

City of Temple Mobility Master Plan

Bell County Race & Ethnicity

Bell County has experienced a steady increase in population from 2014 to 2019, which is reflected in Figure 9 by the growth in the three major race and ethnic groups (i.e., White, Black, or African American, and Hispanic or Latino) within the county. The growth of non white populations shown is relative to the overall population growth of the county and has remained at roughly 55% for the past 5 years. When considering mobility, the American Public Transportation Association has discovered White or Caucasian riders consist of the largest single group of transit users (40%) within race and ethnicity category and within communities of color, Black or African American populations are the second largest users (24%) (Clark, 2017)

Figure 9: Bell County Race and Ethnicity (2015 - 2019)

Bell County Race and Ethnicity (2015 2019)

180,000

160,000

140,000

Population Count

120,000

100,000

80,000

60,000

40,000

20,000

0

White alone* Black or African American alone*

* Not Hispanic or Latino

American Indian and Alaska Native alone*

Asian alone* Native Hawaiian and Other Pacific Islander alone*

Race and Ethnicity

2015 2016 2017 2018 2019

Some other race alone* Two or more races*

Hispanic or Latino

Source: ACS 1 YR (2015 2019)

City of Temple Mobility Master Plan

Temple MMP Study Area Race and Ethnicity

Figure 10 uses ACS 5 Year estimates to assess the trends in race and ethnicity within the Temple MMP study area boundary. The distribution of race and ethnicity in Temple closely resembles the demographics of the county. The majority (64%) of the study area is White (non Hispanic or Latino), followed by a moderate (21%) Hispanic or Latino population, and a relatively small (11%) Black or African American population.

Figure 10: The City of Temple and ETJ Race and Ethnicity (2005 2019)

The City of Temple and ETJ Race and Ethnicity (20052019)

90,000

80,000

70,000

60,000

50,000

40,000

30,000

20,000

10,000

0

White alone* Black or African American alone*

American Indian and Alaska Native alone*

Population Count Race and Ethnicity

Asian alone* Native Hawaiian and Other Pacific Islander alone*

Some other race alone* Two or more races* Hispanic or Latino

2005 - 2009 2010 - 2014 2015 - 2019

* Not Hispanic or Latino

City of Temple Mobility Master Plan

Source: ACS 5 YR (2019, 2014), IPUMS NHGIS ACS 5 YR (2009)

Employment

Bell County Employment

Total employment in the county has been on the rise for the past five years with an overall growth of 10%. 1 Total employment in the county is primarily driven by civilian workers, which comprise roughly 90% of the labor force. Figure 11 demonstrates a yearly increase across the civilian labor force, while the Armed Forces saw significant decreases (32%) from 2015 to 2018 and is currently at approximately 20,000 people (4% lower than 2015).

Figure 11: Bell County Labor Force (2015 2019)

Bell County Labor Force (2015 2019)

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000

# of People Employed 16 Years and Older Year

2015 2016 2017 2018 2019

Civilian labor force Armed Forces

Source: ACS 1 YR (2015 2019)

Figure 12 shows the breakdown of the civilian labor force by industry between 2015 2019. The top four industries within the county are:

• Educational services, and health care, and social assistance

• Retail trade

• Public administration

• Professional, scientific, & management, and administrative & waste management services

City of Temple Mobility Master Plan

Figure 12: Bell County Civilian Employment by Industry (2015 - 2019)

Bell County Employment by Industry (2015 2019)

Public Administration

Other Services (Except Public Administration)

Arts, Entertainment, and Food Services

Educational Services and Health Care

Professional, Scientific, and Administrative…

Finance, Insurance, and Real Estate

Industry

Information

Transportation, Warehousing, and Utilities

Retail Trade

Wholesale trade

Manufacturing

Construction

Agriculture, Forestry, etc.

0 40,000 80,000 120,000 160,000 200,000

# of Civilian Employed Population 16 Year and Older

2015 2016 2017 2018 2019

Source: ACS 1 YR (2015 2019)

Temple MMP Study Area Employment

Overall, the MMP study area employment by industry ( Figure 13) mirrors the county, with concentrations in education, retail trade, and professional services. Notably, the City has a higher concentration in manufacturing, which can be attributed to these major employers (> 500 employees) (Temple EDC, 2020):

• Baylor Scott & White Health

• McLane Company, Inc.

• BNSF Railway Company

• Wilsonart International

• H E B Retail Distribution Center

• Walmart Distribution Center

• Performance Food Group

Figure 13: The City of Temple and ETJ Employment by Industry (2005-2019)

The City of Temple and ETJ Employment by Industry (2005-2019)

Public Administration

Other Services (Except Public Administration)

Arts, Entertainment, and Food Services

Educational Services and Health Care

Professional, Scientific, and Administrative Services

Finance, Insurance, and Real Estate

Industry

Information

Transportation, Warehousing, and Utilities

Retail Trade

Wholesale trade

Manufacturing

Construction

Agriculture, Forestry, etc.

0 10,000 20,000 30,000 40,000 50,000 60,000

2005 - 2009 2010 - 2014 2015 - 2019

Source: ACS 5 YR (2019, 2014), IPUMS NHGIS ACS 5 YR (2009)

City of Temple Mobility Master Plan

Household Income

Household Income data was not readily available for the more detailed study area. As a reference ACS data was pulled for Bell County. Bell County’s median household income has fluctuated slightly over the past five years and closely mirrors trends demonstrated in the Temple MMP study area. There was a 5% increase between 2015 and 2016 which has since then leveled out to approximately $56,800 (Figure 14)

Figure 14: Bell County Household Median Income (2015 2019)

Bell County Household Median Income (2015 - 2019)

$57,500.00

$57,000.00

$56,500.00

$56,000.00

$55,500.00

$55,000.00

$54,500.00

$54,000.00

$58,000.00 2015

Household Median Income (2021 Dollars) Year

$53,500.00

Source: ACS 1 YR (2015 2019)

City of Temple Mobility Master Plan

Figure 15 shows which income brackets have seen the most growth over the past 5 years (2015-2019). Recall that Bell County had seen the most growth between 2015 and 2016, which has since leveled out to the current household median income of approximately $56,000. The growth in the median income in 2016 was influenced by the $75,000 $99,999 (37% increase) income bracket and the those whose income is over $200,000 (39% increase), indicated by the increase in households within those income backets shown in DARK YELLOW. Note that in the following year (2016 2017), growth primarily occurred within lower income brackets; specifically, households that made $100,000 $199,999 (30% increase), $50,000 $74,999 (8% increase), and $25,000 $49,999 (3% increase). Increases in these lower income brackets contributed to the decline of the median income in 2017. Similarly, we see a 14% increase in the $75,000 $99,999 income bracket and 10% increase in the $100,000 $199,999 bracket, which supplemented the growth of the median income between 2017 and 2018. And recently there was a surge in the over $200,000 income bracket; however, there was still a dip in the household median income that year suggesting external factors related to the economy and job market within the region

The trends discussed above demonstrate how the median income increased over time, however, the largest grouping of households within a single bracket (~26%) falls within the $25,000 $49,999 income bracket.

Figure 15: Bell County Households by Income Bracket (2015 2019)

Bell County Housholds by Income Bracket (2015 2019)

City of Temple Mobility Master Plan

Source: ACS 1 YR (2015 2019)

Equity and Environmental Justice

The City continuously works to provide equitable improvements throughout the community by distributing projects throughout all locations in Temple. To help continue this focus and plan for equitable distribution of recommendations in the MMP a review of the Environmental Justice Communities of Concern (EJCOC) was conducted.

It is critical that EJCOC zones be considered when evaluating how the City is growing. The Killeen Temple Metropolitan Planning Organization (KTMPO) considered the following three criteria when identifying these communities. To qualify as an EJCOC zone, the area must meet one or more of the following criteria (KTMPO, 2020):

• Census tracts with fifty percent or more of the population categorized as Low to Moderate Income by HUD.

• Census tracts with fifty percent or more of the population identifies as minority (Black; Asian or Pacific Islander, American Indian, Eskimo or Aleut; Other Race).

• Census tracts with twenty five percent or more persons of Hispanic or Latino descent.

Figure 16: Environmental Justice Zones

Source: ACS 5 YR (2019), KTMPO (2020)

Figure 16 uses KTMPO’s EJCOC zones and the previously identified high population and employment density areas to identify additional threats to these communities. There are several instances shown below where a high population and employment density area is located near an EJCOC zone. These areas should

City of Temple Mobility Master Plan

be considered when planning transportation projects to ensure that existing communities are not displaced due to proposed investments

Precautionary methods should also be considered when planning in the northwest region of Temple (bounded by FM 1237, TX 317, TX 36, and I 35). This area is mostly farmland; however, it also contains the H E B Distribution Center and is just west of a high density employment area. Similar concerns can be made about the region along US 190 / I 14, southeast of downtown Temple. This area has experienced a moderate amount of population and employment growth.

City of Temple Cost of Living

Using the Center for Neighborhood Technology’s (CNT) Housing and Transportation’s Affordability Index metric on housing and transportation cost, Figure 17 assesses the overall affordability of the study area. CNT has determined that places where housing and transportation costs are greater than 45% of the area’s median income should be considered unaffordable. Looking closer at Figure 17, most of downtown Temple falls within or close to this cutoff (light green). Surrounding areas are considered unaffordable based of their combined housing and transportation costs, which are shown by the darker colors. Specifically, areas south of Temple and near Morgan’s Point Resort. Housing costs in Temple are relatively low and range from 20 35% of the area’s median income. Transportation costs become gradually higher as people live farther away from downtown this increase is expected due to longer commute times and distance.

Figure 17: Housing and Transportation Costs as a Percent of the Area's Median Income

Source: Center for Neighborhood Technology (2017)

City of Temple Mobility Master Plan

Land Use

Future Land Use Plan

The section uses the City of Temple’s future land use plan as described in the 2020 Comprehensive Plan. Figure 18 illustrates how the City plans to grow over the next decade.

During previous development of the comprehensive plan, these land uses were determined using community feedback, recommendations from the Comprehensive Plan Advisory Committee, Planning and Zoning Commission, and the City Council.

Figure 18: The City of Temple and ETJ Future Land Use Plan

Source: City of Temple (2020)

Currently, the City of Temple future land use plans indicates 42% as Industrial, 26% as Rural/Estate, and 17% as Residential and Neighborhood Services. This differs from the original land use distribution outlined in the 2020 Comprehensive Plan, with 5% of land being allocated to Industrial uses, 61% as Rural/Estate, and 17% as Residential and Neighborhood Services. Table 2 shows the future land use by total acres and percentage of land use

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Table 2: Future Land Use Distribution

Future Land Use Category

Total Acres % of MMP Study Area

Industrial 60,091 42% Rural/Estate 37,065 26%

Residential and Neighborhood Services 24,493 17%

Employment Mixed-Use 6,557 5% Corridor Mixed-Use 6,471 4%

Regional Commercial 2,177 2% Business Park 2,083 1%

Temple Medical & Education District 1,988 1%

Urban Residential 1,803 1% Parks and Open Space 1,758 1%

Downtown Transition 191 0%

Downtown Core 80 0%

Total 144,757 100%

Source: City of Temple (2020)

Zoning

Figure 19: City of Temple Zoning (2020)

Source: City of Temple (2020)

Figure 19 shows the current (2020) zoning for the City of Temple. The top five zoning categories consist of over 75% of the land within the City limits:

• Agricultural (AG) 38%

• Light Industrial (LI) 18%

• Single Family Dwelling 1(SF 1) 8%

• Single Family Dwelling 2 (SF 2) 7%

• General Retail (GR) 6%

The current zoning aligns with the future land use plan for the incorporated City of Temple and the ETJ boundary, with most of the land being allocated to agricultural, industrial, and housing uses

Key Findings

The assessment of the existing and projected demographic data and future land use will be used to identify locations within the study area that should be a key focus for transportation investment. Key findings from this analysis include:

• Existing employment in Temple is concentrated in education, retail trade, and professional services, and manufacturing.

• The population is expected to grow by roughly 34% (45,861) and employment by 66% (39,020) over the next 25 years (2019 2045)

• Population and employment are expected to increase throughout the study area, with a higher percentage increase around Loop 363 and to the north of Temple.

• Employment is expected to increase along I 35 and generally throughout the study area.

• Temple has a small but growing elderly population (65 years and older), a declining older adult population (40 54 years old), and a growing middle aged population (25 39 years old).

• The current household median income for Bell County is approximately $56,000.

• Areas in the northwest region of Temple (bounded by FM 1237, TX 317, TX 36, and I 35), the region along US 190 / I-14, and southeast of downtown Temple may be considered a vulnerable area due to their transportation and housing costs

• Housing costs in Temple are relatively low and range from 20 35% of the area’s median income.

• Areas considered unaffordable based off their combined housing and transportation costs include areas south of Temple and near Morgan’s Point Resort.

• There is anticipated growth in goods and freight movement in the region. Future land use for Temple allocates 42% to industrial and 26% to rural/estate uses. Consideration of planning for freight movement and infrastructure that supports truck traffic will be critical to support this growth.

SAFETY ANALYSIS

Transportation safety data analysis provides planners, policy makers, and the public with a better understanding of where critical safety issues exist in the transportation system and what factors may be contributing to Temple MMP study area crashes and crash rates. As such, safety data analysis is a critical component of regional transportation planning.

The technical crash analysis presented in the following section reviews historical crash data within the City of Temple and surrounding ETJ over a five year period. The review of crash data encompasses an assessment of key transportation safety issues for both motorized and non motorized users. The Temple MMP development process uses concepts and progam initiatives articulated in federal and state policy documents.

At the federal level, the Highway Safety Improvement Program (HSIP) requires a data driven, strategic approach that focuses on system safety performance to improve highway safety on all public roads. The federal HSIP also requires a state level Strategic Highway Safety Plan (SHSP) that defines the state safety goals and describes a program of strategies to improve safety in order to achieve a significant reduction in traffic fatalities and serious injuries on all public roads.

The 2017 update to the Texas SHSP acknowledged a steady increase in roadway fatalities, particularly in urban areas, since 2012, despite efforts to improve roadway user behavior and upgrade roadway conditions. The SHSP maintains a vision of moving to zero deaths on roadways, and represents a multidiscipline collaboration aspiring to make Texas travel safer by reducing crashes, fatalities, and injuries by focusing on seven key emphasis areas, including distracted driving, impaired driving, intersection safety, older road users, pedestrian safety, roadway and lane departures, and speeding.

The Temple MMP seeks to use the tools and metrics outlined in the HSIP and to achieve the goal of significantly reducing and eventually eliminating vehicle related fatalities in the Temple MMP study area, supporting the Texas SHSP goals.

Methodology

The analysis detailed in this section is conducted to support the City of Temple’s expected contributions to the vision expressed in the SHSP as a member of the Killeen Temple Metropolitan Planning Organization (KTMPO), and to support an effective data driven process for prioritizing transportation safety improvements in the region and at the local level. Crash counts and crash rates are examined by individual year in comparison to statewide data and as a 5 year rolling average for comparison to federal FAST Act Roadway Safety Performance Measures (PM1) and Texas statewide safety performance targets.

Crashes by severity are also calculated to examine propensity for harm in the case of a crash, as are types of crashes (opposing direction, same direction, angle, etc.). Vehicle vs. pedestrian and vehcile vs. bicycle crashes are calculated to identify risks to these vulnerable modes. A review of contributing factors was also performed to gain insight on operational vulnerabilities and inform strategy development. Crash hotspots, and top crash intersections and segments are delineated to identify location specific safety needs.

In addition to identifying issues that need to be addressed, the results of this analysis can be used to inform the development of need and purpose for safety strategies and help to improve design elements in future transportation projects, as well as inform the assessment and scoring of proposed projects by providing data driven benchmarks for safety performance measures. Reviewing operational safety patterns in comparison to other existing conditions analyses such as traffic and transportation demand also provides the City of Temple with a benchmark and tools to assess and compare progress in contributing to PM1 statewide targets as well as gauge progress towards improving transportation safety at the local level

City of Temple Mobility Master Plan

Data Sources

The data used in this analysis was obtained from the Crash Records Information System (CRIS) and covers the most recent five year period (2016 2020) of data available. CRIS is maintained by the Texas Department of Transportation (TxDOT) and is a georeferenced database that contains a collection of records regarding motor vehicle traffic crashes as submitted by law enforcement officers through a standardized crash report. 2 These reports are processed to exclude personal information but include other crash details relevant to analysis, such as:

• Crash severity

• Contributing factors

• Location

The summaries and figures in this analysis provide illustrations to better understand regional crash trends in the study area, including:

• Total crashes

• Crashes by severity

• Crash rates

• Crashes involving pedestrians or bicyclists (active transportation crashes)

Data obtained from CRIS was queried for all of Bell County at the crash, unit, and person level in order to support the review of various integral statistics used in roadway safety analysis. The data was processed in Microsoft excel to create summary tables of various statistics. Geographic Information System (GIS) programs were used to geocode the data, refine available data to calculate metrics for the Temple MMP study area, review locations, generate heatmaps to review density, and generate figures to illustrate the analysis in the following sections.

Control sections and roadway centerlines with estimates of vehicle miles traveled were obtained from TxDOT’s open GIS portal. 3

Results of Safety Analysis

In the City of Temple and the surrounding ETJ there were a total of 9,001 crashes between 2016 and 2020 as represented in the CRIS data. Of these crashes 63 were fatal crashes, 212 resulted in suspected serious injury, 1,226 were reported as suspected minor injury, 1,541 as possible injury, 5,590 no injury or property damage only crahses, and 369 crashes reported with unkown severity.

Figure 20 represents these findings by year and shows an overall downward trend in total crashes over the last five years.

3 TxDOT Open Data Portal (arcgis.com)

City of Temple Mobility Master Plan

Crash Count

600

400

200

0

800 1,000 1,200 1,400 1,600 1,800 2,000 2016 2017 2018 2019 2020

Fatal injury Suspected serious injury Suspected minor injury

Possible injury Not injured Unknown

Source: CRIS, 2016 2020

Figure 21 shows the number of all crashes in the study area by corridor over the 5 year period. A number of key summary processes informed the effective use and identification of characteristics represented in the data. In further sections of this analysis, raw counts were reviewed in proportion to the volume of traffic along each segment in order to better understand where the transportation system might be experiencing higher crash incident rates.Though I 35 is shown to have a high crash count over the five year period, the volume of traffic on the interstate raises the statistical likelyhood of crashes happening in a given time period. Table 3 identifies corridors with the highest crash counts.

Figure 20: Crash Summary by Severity by Year; 2016 - 2020

Figure 21: 5 Year Crash Counts by Corridor; 2016 - 2020

Source: CRIS, 2016 2020

Source: CRIS, 2016 2020

A few additional segments of the transportation system were identified as having high crash counts including FM 2305 from FM 317 to I 35, having 240 crashes, 0 fatalities, and 2 serious injuries. The southwest portion of the HK Dodgen Loop had 214 crashes, 2 fatalities, and 6 serious injuries. The north section of I 35 had 242 crashes with 3 fatalities and 11 serious injuries.

Number of Fatalities and Serious Injuries by Corridor: 2016 - 2020

A deeper dive into the severity of outcomes at the segment and corridor level produced results that revealed which corridors had the highest count for fatalities and serious injuries Figure 22 shows which corridors had the highest number of persons involved in crashes. Figure 23 shows the corridors that experienced the highest count of fatalities and Figure 24 on the succeeding page shows the count of serious injuries by corridor. SH 317 had 5 fatalities and 4 serious injuries for the 142 crashes that happened along the corridor.

Figure 22: 5 Year Count of Persons Involved in Crashes by Corridor; 2016 2020

Source: CRIS, 2016 2020

City of Temple Mobility Master Plan

Corridors are represented in Figure 23 with 3 fatalities each including FM 436, SH 95, a southeast portion of US 190, SH 36 in the northwest part of the study area, and the northern portion of I 35

Figure 23: 5 Year Count of Fatalities by Corridor; 2016 2020

Source: CRIS, 2016 2020

City of Temple Mobility Master Plan

Figure 24 shows the 5 Year serious injury count. As evidenced by its dark coloring on the map, S. 31st street is represented as having the highest count of serious injuries, while I 35, SH 53, and SH 36 have between 8 and 12 serious injuries, respectively.

24: 5 Year Count of Serious Injuries by Corridor ; 2016 2020

Crash Rate Analysis

Source: CRIS, 2016 2020

Gross crash counts, especially where interstates are present, can yield somewhat misleading results as traffic volumes and statistical likelyhood of crashes are interlinked. For example, 100 crashes a year, while undesireable on an interstate with an average daily traffic count of around 19,000 vehicles, is proportionaly less alarming than a local road with 100 crashes and a smaller volume of traffic. Normalizing the crash counts by volume of traffic helps refine the crash analysis to a point where locations experiencing disproportionate crash rates and severe outcomes are highlighted. To perform this analysis, vehicle miles traveled by segment were used to generate crash rates, rate of fatalities, and rate of injuries. The rates used in this analysis are expressed in terms of million vehicle miles (MVM) traveled. The equation used for the calculation is as follows:

Figure

Where:

R = Accident rate of the section in accidents per million vehicle miles of travel (ACC/MVM)

A = Total number of accidents on the roadway section for the analysis period

T = Time period of the study ( in years or fraction of years)

V = Average Annual Daily Traffic (AADT) during the study period

L = Length of the section in miles

All Crashes

Figure 25 shows the crash rates by segment and helps highlight a few key locations with the highest rate of crashes. A few locations, due to segment length and low volume of traffic are shown to have a disproportionate rate of crashes. A small segment of Old Cedar Creek Road near the intersection with 317 has two crashes over the 5 year period and a low volume of approximately 100 average daily traffic (ADT) count, which in turn yields a high crash rate. Similar results are seen with a small segment of Woodland Trail just south of FM 2305 with three crashes, and High Crest Drive to the west off of FM 439 also with three crashes. Two segments between W. Adams Avenue and W. Central Avenue in central Temple are shown as well. In these cases, N. 29th St. has 42 crashes and 27th St had 16 crashes. Segments were then screened to review where the rate of fatalities was highest. This review as well as the review of serious injury rates revealed a better understanding of where localized rates of severe outcomes were occurring. The person level data, rather than the crash level data informed both fatal and serious injury rates.

Source: CRIS, 2016 2020

Mobility Master Plan

Figure 25: 5 Year Crash Rates by Segment; 2016 2020

Fatal Crashes

Figure 26 shows the locations of these segments. To the west, Nolan Loop,which connects FM 439 to FM 93 had 2 crashes and 1 fatality. S. Cedar Road, off of FM 2305 had 9 crashes and 1 fatality. In the southeast portion of the study area, Reads Lake Road had 2 crashes and 1 fatality.

In the central portion of the study area, S. 57th Street, just north of I 35 had 1 crash with 1 fatality. S. 49th Street to the south of I 35 had 2 crashes and 1 fatality, while N. 25th Street between W. Adams Avenue and W. Central Avenue had 44 crashes with 1 fatality and 1 serious injury.

Figure 26: 5 Year Rate of Fatalities by Segment; 2016 2020

Source: CRIS, 2016 2020

Serious Injury Crashes

The review of serious injury rates highlighted the nine segments (Figure 27) with rates of 3 or higher. West of I 35, Executive Drive, just north of W. Adams Avenue had 1 crash which resulted in serious injury. Draper Drive, just off of Airport Road had 4 crashes and 1 serious injury. To the north, Hart Road had 7 crashes and 1 serious injury, while to the east, Dairy Road had 1 crash with 1 serious injury. 5

In the central portion of the study area, N. 21st Street had 17 crashes and 2 serious injuries. S. 7th Street had 6 crashes and 2 serious injuries, while N. 7th Street had 19 crashes and 1 serious injury. E. Jackson Street, just south of Jackson Park, had 1 crash with serious injury.

Figure 27: 5 Year Rate of Serious Injuries; 2016 2020

Source: CRIS, 2016 2020

5 Crash rates are calculated per 100 million VMT per segment. Short segments with a low traffic volume will have high rates if any crashes are present. This occurs because there is a relatively high number of crashes proportionate to the length and volume of the segment.

of Temple Mobility Master Plan

Table 6 identifes which intersections represent the highest counts for intersection or intersection related crashes.

Table 6: Top Crash Intersections; 2016 2020

Top Intersections

Crash Count

Fatal injury Suspected serious injury Suspected minor injury Possible injury Not injured Unknown

S. 31st St & 190 276 1 6 52 100 642 24 I 35 & S. Loop 363 266 0 4 50 75 628 19 W. Central Ave & S. 3rd St. 196 1 8 29 74 468 20 I-35 & W. Adams interchange 180 0 6 40 87 423 18 Airport Rd/W. Central Ave & S. 31st St. 172 1 1 40 53 466 8

I-35 & W. H. K. Dodgen Loop 102 2 2 26 24 235 14 SH 317 & W. Adams Ave. 84 1 1 24 27 183 6 S.E. H.K. Dodgen & S. 1st St. 73 0 0 16 30 170 5 Airport Rd./W. Central Ave & S. 25th St. 38 0 1 4 17 90 4 E. Adams Ave. & Loop 363 37 0 3 6 9 86 2 Airport Rd./W. Central Ave & S. 29th St. 34 0 0 2 9 92 2

Source: CRIS, 2016 2020

Contributing Factors Analysis

Understanding factors that contribute to crashes, especially those resulting in serious injuries or fatalities, can add depth to a comprehensive crash analysis and inform the development of strategies. Identifying the top contributing factors allows the City of Temple and its planning partners to incorporate proven safety countermeasures and crash modification factors into the design and prioritization of future roadway investments to address or mitigate these contributing factors.

Of the top ten contributing factors, the top two (in terms of total crashes) involved speeding, while three others involved failing to yield the right of way. A portion of data entries were noted as having “No Data” or “Other” in the contributing factors fields, though the crash data did have other factors noted including events such as distracted or inattentive, swerving or veering or improper changing of lanes.

Table 7 shows the top ten contributing factors by total count. Though it is important to focus on contributing factors that result in fatal and severe outcomes, reviewing all crash types will help highlight the propensity of certain types of crashes in the system and allow for a more systemic approach to projects addressing risk and severity reduction

City of Temple Mobility Master Plan

Table

7: Top Ten Contributing Factors; 2016 2020 Top Ten CF by Gross Count

Crash Count

Speeding 2,263

Failed to yield 1,376

Erratic driving 915

Distracted driving 698 Disregard traffic control 423

Improper turning 291 Under influence 230 Animal on road 126 No data 1,983 Other 301

Source: CRIS, 2016 2020

Of the crashes represented in Table 7, where the contributing factor was disregarding a form of traffic control, nearly 94% occurred at intersections. Similarly, just over 78% of failure to yield crashes were at intersections and just over 64% of crashes with a form of improper turning were also at intersections. A similar review of contributing factors was performed using only the sum of fatalities and severe injuries to index the top factors. Table 8 shows the resulting top contributing factors where there were fatal or severe injury outcomes.

Table 8: Top Ten Contributing Factors with Fatalities or Severe Injuries; 2016 2020 Top Ten Contributing Factors by Fatal and Severe Outcomes Person Count

Speeding 151 No data 98

Erratic driving 80

Failed to yield 66 Other 38 Under influence 36

Disregard traffic control 34

Distracted driving 19

Improper turning 7 Ill driver 7

Source: CRIS, 2016 2020

A smaller yet significant portion of fatal and severe injury crashes, ranging between 40% and 44%, respectively, resulted from failure to yield or disregarding a traffic control at intersections. A comparison was then performed between the top contributing factors and collision types. An analysis was conducted of the interrelation of contributing factors and collision types. This comparison shows that speeding and failure to yield were the top two contributing factors for crashes in the study area When comparing the type of collision with contributing factor it was found that single vehicle or same direction collisions were the top collision type for speed related contributing factors. Angle collisions and opposite direction collisions were the top collision types where failure to yield was the contributing factor.

This comparison of interrelation helps illuminate system level factors leading to safety incidents and can inform the selection and development of appropriate crash modification factors and proven safety countermeasures to reduce likelihood and severity of these incidents.

Speed Related Crashes

Heat maps were generated for each of the identified conditions in order to understand where problem areas might be. For speed related crashes, I 35 was removed from the heat map to facilitate the review of surface level hot spots. Figure 28 illustrates the location of speed related crashes. Contiguous portions along S. 31st Street are among the highest level of occurences. Portions of W. Adams Avenue and W. Central Avenue have high rates of speed related crashes, specifically at or near intersections with 31st Street, 25th Street and 3rd Street. Additional speed related crash locations occur along FM 2305 as well as Airport Road. A few key intersections along Loop 363 with high concentrations of speed related crashes are at I 35 and at SH 53. High concentrations of speed related crashes also occur along US 190 at 57th Street, S. 31st Street, at the 290 interchange as well as at Little River Road.

Figure 28: Speed Related Crashes; non-Interstate; 2016 2020

Source: CRIS, 2016 2020

Failure to Yield Related Crashes

For crashes where a failure to yield was the main contributing factor, two different types of collisions were identified and mapped, including angle collisions and opposite direction collisions. Figure 29 shows intersections along S. 31st Street similar to locations that appeared in the speed related crash analysis as well as along W. Adams and W. Central Avenues. Additional hotspot locations appear along the northwest portion of Loop 363 at intersections with Industrial Boulevard as well as at Lucius McCelvey Drive. S E HK Dodgen and US 190 appear to have a high concentration of crashes where there was a failure to yield as do intersections at S. 5th Street just south of US 190 and at Midway Drive and FM 817.

Figure 29: Failure to Yield Related Crashes; Angle Collisions; 2016 2020

Source: CRIS, 2016 2020

An additional heat map was generated for crashes with failure to yield as the contributing factor where the collision type involved the vehicles as being in opposing directions. These locations are represented in Figure 30. S. 31st Street has a few hotspots occuring between Forest Trail and Azalea Drive as well as at US 190. Additional hot spots on S. 31st Street are seen at FM 93 and at W. H Avenue. FM 93 has another hot spot at SH 95. 2305 has hot spots at S. Kegley Drive, Hilliard Road, and at Morgans Point Road.

Severity, Mode Split, and Active Transportation

One of the most important steps in planning for the future of active transportation in a city is to determine the city’s specific modal needs so that these needs can be addressed accordingly. One type of needs identification comes in the form of a identifying the mode split in the safety analysis, which involves examining how safe the transportation system is for active transportation users. People traveling in a vehicle that has been engineered with crumple zones, seatbelts, and airbags are inherently buffered from more severe outcomes in the event of a crash. Conversely, persons traveling in various means outside a motorized vehicle are inherently more susceptible or vulnerable to severe outcomes. This type of analysis can pinpoint current safety issues and challenges, allowing the region to implement measures to mitigate or prevent crashes over time to address the existing and future safety needs of active transportation users. Over the 5 year period there were 197 active transportation users affected by 186 crashes. Of those, there were 12 fatalities, 30 serious injuries and 62 minor injuries.

For each type of roadway user a higher proportion of active transportation users had severe outcomes in proportion to their involvement in a crash. Figure 31 shows the resulting distribution of mode split and severity outcomes.

Figure 30: Failure to Yield Related Crashes; Opposite Direction Collisions; 2016 2020

Source: CRIS, 2016 2020

Source: CRIS, 2016 2020

Figure 32 shows the location and severity of crashes involving active transportation users. Segments along S. 31st Street have a number of clustered occurences with two fatatlities just north of US 190 and a number of severe injuries south of Canyon Creek Drive and near the intersection of W. Avenue J. Two serious injuries adjacent to S. 31st Street are on W. Avenue R and on W. Avenue T. A number of active transportation crashes occurred on US 190 near and at I-35 with 3 fatalities. A few other contiguous active transportation crashes occurred on S. 1st Street between W. Avenue J and W. Avenue F with one fatality and two serious injuries. A number of active transportation crashes have occurred along SH 53 through Temple with 3 fatalities and 1 serious injury.

Figure 31: Mode Split and Severity Outcomes; 2016 2020

Source: CRIS, 2016 2020

Active transportation crashes were reviewed for contributing factors. These factors are identified in Table 9. Other than crashes with no data or “other” noted for contributing factors, the top 4 contributing factors noted in the data were distracted driving, failure to yield, erratic driving, and speeding.

Figure 32: Active Transportation Crashes by Severity; 2016 2020

Table 9: Contributing Factors for Active Transportation Crashes; 2016 2020

Contributing Factors from Crashes involving Active Transportation Users Instance Count

Distracted driving 31

Failed to yield 27

Erratic driving 13 Speeding 10 Disregard traffic control 4 Under influence 3

Improper passing 2 Fatigued 2 Impaired visibility 2 Improper parking 2 Improper turning 1 Road rage 1 No data 91

Other 16

Source: CRIS, 2016 2020

Key Findings

This assessment of key transportation safety issues for both motorized and non motorized users will be used to inform the future development of safety strategies for Temple Key findings from this analysis include:

• Speeding is the top contributing factor for all crashes and for those that result in a fatality or serious injury.

• Distracted Driving is the highest contributing factor for crashes involving active transportation in Temple

• Vulnerable users, i.e., Pedestrians and Bicyclists are at a high risk

• Single vehicle or same direction collisions were the top collision type for speed related contributing factors

Strategies developed using proven safety countermeasures can contribute to achieving a significant reduction in traffic fatalities and serious injuries on all public roads. The development of recommendations for safety improvements that will occur later in the planning process will use best practices from FHWA. FHWA has set out a variety of proven safety countermeasures, shown in Figure 33. Further detail can be found on FHWA’s safety page. 6 Additional information on CMFs can be found on the CMF Clearinghouse. 7

6 https://safety.fhwa.dot.gov/provencountermeasures/fhwasa18029/ 7 http://www.cmfclearinghouse.org/

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Figure 33: FHWA Proven Safety Countermeasures 8

TRANSPORTATION SUPPLY

Analyzing the need for new roadways and additional capacity on existing roadways represents one component of the comprehensive needs assessment. Other considerations such as the quality and availability of transit services and non motorized infrastructure, the safety of all modes and for all users, the resiliency of the transportation system in the case of a natural disaster or security threat, and the efficiency of the existing transportation system are also important considerations when assessing the transportation needs of the community over the long term.

Master Thoroughfare Plan

The current City of Temple Master Thoroughfare Plan (MTP) was approved on October 15th, 2020. The MTP classifies roads into classifications and plans for future expansions. The City uses a functional street classification system to plan and design street improvements. Under this system It established six road classifications: highways, major arterials, minor arterials, community collector, and neighborhood collector. Primary consideration in planning and designing streets has typically been the roadway’s vehicle capacity, represented by roadway width and number of traffic lanes. Figure 34 provides the latest thoroughfare plan map.

34: Temple 2020 Thoroughfare Plan

City of Temple Mobility Master Plan

Figure

Source: City of Temple

Transportation Supply Gaps Analysis

The City of Temple is situated along the major north south Interstate Highway (IH) 35 that runs through Texas connecting several major cities within the state. The interstate and interchanges in the City of Temple continue to be improved to add capacity and accommodate not only through traffic, but also local traffic and freight travel. H. K. Dodgen Loop provides a bypass loop around the City connecting several of its major corridors, such as SH 190, Airport Road, Industrial Parkway, SH 317, Adams Ave, Avenue H, 31st Street, 3rd Street, 1st Street, Central Avenue Typically, travelers will encounter the most traffic on these facilities in the City and during the peak travel periods. However, there are several areas of concern highlighted in this section that will be built upon as the development of the plan continues. A description of these known traffic concerns in the City of Temple are presented in the following sections:

• Intersection of Avenue H and 31st Street

• West Temple Commuters Congestion along FM 2305

• Underdeveloped roads

• Congestion along 31st Street

• Downtown Temple One Ways

• Potential Under Utilized Roadway Capacity

Intersection of Avenue H and 31st Street

The intersection of Avenue H and 31st Street is a signal controlled intersection situation just west of downtown that experiences heavy travel activity during peak AM and PM periods causing periodic congestion and delay, as well as safety concerns. Avenue H is an east west facility separated by a tree lined median with two travel lanes in each direction and protected left turn lanes. 31st Street is a four lane undivided north south corridor with protected left turn lanes at the intersection. The project team preformed a desktop analysis as well as a field visit to the intersection to learn more about the characteristics that may be impacting traffic and safety. The team found the following concerns:

Congestion and Delay Figure 35 provides a snapshot of a typical Monday afternoon commute. As displayed in the screenshot traffic appears to back up along Avenue H in both directions as well as northbound traffic on 31st Street.

Geometry of the Intersection The intersection is an atypical uniquely situation with possible confusion for motorist turning off 31st Street onto Avenue H. Protected left turns on Avenue H are separated from the two travel lanes by pedestrian island that can appear to be the travel lane turning traffic are intended to follow. This has potential for wrong way driving as well as rear end/angle crashes. Figure 36 provides a closer look at the configuration.

Figure 35: Snapshot of Traffic on Avenue H and 31st

Source: Google Maps

Proximity of Driveway and Roadway Access near Intersection

There are several access points within 25 feet of the intersection. Mama Dog Creek runs parallel along 31st Street on the north side of Avenue H and there are several private driveways along Avenue H on the west side of 31st Street that can lead to abrupt turn movements and vehicle conflict points

Inconsistent Sidewalk Infrastructure and Multimodal Connectivity – The intersection has several recently updated sidewalk improvements along Avenue H on the north side and partially on the south side. However, there are no sidewalks along 31st Street. In addition, there are no sidewalks on the southeast side of Avenue H. As displayed in Figure 37 the sidewalk stops within a few feet after the intersection. The intersection also lacks a complete set of pedestrian signals and striped crosswalks. This can lead to pedestrian conflicts with motorist and unexpected challenges to crossing the street.

Intersection Crash Analysis

The data used in this analysis was obtained from the Crash Records Information System (CRIS) and covers the most recent five year period (2016 2020) of data available. This is the same data set used in the full crash analysis performed for the existing conditions review. CRIS is maintained by the Texas Department of Transportation (TxDOT) and is a database that contains a collection of records regarding motor vehicle traffic crashes as submitted by law enforcement officers through a standardized crash report. These reports are processed to exclude personal information but include other crash details relevant to analysis, such as:

• Crash severity;

• Contributing factors; and,

• Location.

City of Temple Mobility Master Plan

Figure 36: Aerial View of Avenue H and 31st

Figure 37: Street view looking East

Source: Google Maps

Source: Google Maps

For the data gathered over the indicated period, there were a total of 40 crashes involving 130 persons at the intersection of W. Avenue H and S. 31st St. Figure 38 and Figure 39 shows the totals of each person level outcome. There were no fatalities or serious injuries reported in these crashes, however there were 15 suspected minor injuries.

Figure 38: Total Crashes 2016 to 2020 by Injury

Fatal

Figure 39: Total Crashes Person Level Outcome

Person Unknown Injury Count

Person Not Injured Count

Person Possible Injury Count

Person Suspected Minor Injury Count

Person Suspected Serious Injury Count

Person Death Count

Source: CRIS, 2016 2020

Source: CRIS, 2016 2020

A review of the crashes by direction of approach indicates that most of these crashes occurred in favorable conditions. Table 10 through Table 12 show summaries of crash counts by type of operating condition present at the time of the crash.

Table

Table

Table

West Temple Commuter - Congestion along FM 2305

West Temple commuters traveling to Temple in the morning and then returning from Temple in the evening are limited to three possible routes. The only options available are FM 2305 (West Adams), Airport Road (HWY 36), and I 35. Of the options, the most direct and most often utilized route is FM 2305 which leads to excessive congestion along FM 2305 between HWY 317 and Loop 363. The area continues to grow substantially, which will likely exacerbate the issue. Also, it should be noted that numerous commuters from North Belton make use of these same routes. Figure 40 shows the area of west temple commuter patterns

City of Temple Mobility Master Plan

Figure 40: West Temple Commuters

New Development Using Roads that are still at County Road Standards

Recent growth has, in instances, motivated improvement of arterials; however, many new developments are still using several access routes that are at county road standards. This occurs in several areas of development around Temple. Examples include North Pea Ridge, South Pea Ridge, Hartrick Bluff and Little River Road south of Blackland. Shown below in Figure 41 are examples of the described issue along North Pea Ridge (2) which is currently at county road standards. North Pea Ridge is bordered by new subdivisions and arterials that have recently received improvements.

Figure 41: North Pea Ridge

Figure 42 are examples of new residential developments along Hartrick Bluff which utilize Hartrick Bluff for access. Hartrick Bluff in these sections is still at county road standards.

Figure 42: Residential developments along Hartrick Bluff

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Congestion along 31st Street - South of Azalea Drive

Improvements to 31st Street have been made near the intersection of Loop 363; however, these improvements extend only as far as Azalea Drive where 31st Street reduces in width by several lanes. Congestion often exists from Azalea to Canyon Creek. In this section are numerous commercial establishments including Wal Mart, McDonald’s, Bank of America, Wells Fargo, ExtraCo, Aldi Grocery Store, Walgreens, Sam’s Club, and others. Figure 43 shows a street view of an improved section of 31st Street. Figure 44 shows the street view of an unimproved section of 31st Street.

Figure 43: Improved Section of 31st Street

Figure 44: Unimproved Section of 31st Street

Congestion at Intersection of I-35 and Loop 363 Frontage Roads

Drivers accessing I 35 from the Loop 363 frontage roads at the southern intersection of the Loop and I 35 often experience congestion. Drivers along I 35 frontage roads intending to make a U Turn do not have a Texas Turn Around available to do so and must make a complete circuit around the intersection. Space constraints make fly overs at this intersection unlikely

City of Temple Mobility Master Plan

Source: Google Maps

Source: Google Maps

Downtown Temple One-Ways – Central and Adams Ave. Corridor

Central and Adams Avenue run east-west connecting downtown to I-35. Both corridors experience heavy travel during peak periods leading people in and out of downtown, with motorists often traveling at higher than posted speed limits causing congestion and safety concerns. A study was completed in 2019 on the Central Adams Corridor that provides a plan to transition a portion of the one way pair of Central and Adams to two way roadways (Figure 45) As described in the study, existing conditions along the length of Adams from downtown to I 35 are a mixture of unconnected sidewalks, large curb cuts for vehicular access, expansive asphalt and concrete, overhead utilities, and large billboard and other signage. This haphazard and uncontrolled development is stressful for both pedestrians and vehicles traveling from downtown. Figure 46 shows street view for existing Adams Avenue. Figure 47 shows street view of existing Central

Figure 45: Central and Adams Ave. Corridor

City of Temple Mobility Master Plan

Figure 46: Adams Street view

Source: Google Maps

Figure 47: Central Ave Street view

Source: Google Maps

Potential Under-Utilized Roadway Capacity – Industrial Blvd Cut-Off

Formerly Industrial Boulevard crossed I-35 as noted on the accompanying satellite imagery in Figure 48 Industrial Boulevard now has been rerouted to join N 3rd Street at a new crossing approximately 1,000 feet north leading to a portion of Industrial Boulevard on the east side of I 35 to experience significantly reduced use. Industrial Boulevard on the east side of IH 35 is currently four lanes with a shared center turn lane.

Figure 48: Industrial Boulevard

Potential Under Utilized Roadway Capacity – Martin Luther King

Martin Luther King, Jr Boulevard, as shown below is a four lane roadway just east of downtown Temple. The four lane section of roadway begins at its intersection with French Avenue and extends south several miles to its intersection with Loop 363. Figure 49 shows a screenshot of Martin Luther King Jr. Boulevard.

Figure 49: Martin Luther King Jr Boulevard

Source:

City of Temple Mobility Master Plan

Google Maps

Key Findings

The areas of traffic concern highlighted in this section are:

• Intersection of Avenue H and 31st Street

• West Temple Commuters Congestion along FM 2305

• Underdeveloped Roads

• Congestion along 31st Street

• Downtown Temple One Ways

• Potential Under Utilized Roadway Capacity

These areas will continue to be reference and evaluated during the planning process.

City of Temple Mobility Master Plan

TRANSPORTATION DEMAND MODELING

The existing conditions roadway deficiencies analysis provides policy makers and the public with a better understanding of how the roadway network is currently performing. The Killeen-Temple Metropolitan Planning Organization’s regional travel demand model (KTMPO Model) was used to examine the existing roadway network to evaluate roadway performance measures and to perform a capacity deficiencies analysis. The existing transportation system of the KTMPO Model represents the year 2015 and provides the best comparison available in the KTMPO Model to what would be considered existing conditions.

Methods

The following section identifies the data sources and describes the methods and tools used to complete the existing roadway assessment.

Killeen-Temple MPO Travel Demand Model

The latest KTMPO Model was produced in 2017 within TxDOT’s TexPACK model interface. The KTMPO Model is a person trip based model that reports volumes and metrics at the daily level. The model covers the entirety of Bell County, as well as portions of Lampasas and Coryell Counties. KTMPO Model outputs from the 2015 base year were used as part of the existing conditions analysis to highlight areas with deficiencies. The 2015 base year scenario outputs provided performance measures that identify areas of strain within the region.

Travel Demand Model Review

The KTMPO Model is a validated model that was calibrated to 2015 travel conditions during its development. Since the KTMPO Model covers the entirety of Bell County, well beyond the boundaries of Temple, it was necessary to review the quality of validation for the specific Temple area to ensure the model adequately replicated traffic at this more detailed level.

The KTMPO Model was reviewed throughout the Temple region to determine if the model showed an acceptable ability to replicate existing transportation system conditions and travel behavior. To accomplish this, 2015 KTMPO Model traffic volumes were compared to historical traffic counts throughout the region to assess the model’s ability to reproduce reasonable estimations of traffic volumes. It was found that the Temple region was largely successful in providing a sound representation of 2015 traffic based on this comparison. As part of this review, roadway characteristics such as functional class and number of lanes were reviewed to ensure the 2015 KTMPO Model was developed with reasonable assumptions that best represented the transportation system.

Temple Subarea

Since the KTMPO Model covers the entirety of Bell County, a subarea of the model was extracted to uniquely express the performance of the Temple study area independently from the rest of Bell County. The Temple Subarea was extracted from the KTMPO Model using TransCAD’s subarea tools by selecting KTMPO Model traffic analysis zones (TAZs) that best related to the Temple MMP study area boundary.

The design of the KTMPO Model TAZs were largely based on Census boundaries and were structured to capture similar land uses throughout the area. Due to the limitations of TAZ design, the Temple Subarea extracted from the KTMPO Model does not match the ETJ precisely, but the Temple Subarea does provide a reasonable depiction of what could be expected from the ETJ. This Temple Subarea was used to perform the existing roadway demand assessment.

Travel Demand Model Outputs

Travel demand forecasting quantifies the existing interaction between supply and demand on the transportation system. The supply of transportation is represented by the characteristics of the roadway network (e.g., roadway classification, roadway capacity, etc.), while the demand for transportation is created

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by the separation and intensity of urban activities. The service characteristics of the roadway and land use are direct inputs to the travel demand model.

The Temple Subarea estimated travel demand for the 2015 base year and produced a defined roadway network that contained performance measures such as Vehicle Miles Traveled (VMT), Vehicle Hours Traveled (VHT), Vehicle Hours of Delay, Volume to Capacity (V/C) ratio, and Travel Time Index (TTI). These measures helped in quantifying system deficiencies to gain a full perspective of the existing roadway system’s performance.

Segment level analysis was also conducted to visualize congestion level of service (LOS) on the Temple Subarea roadway network. LOS is an indicator of congestion on a scale from A to F, where A represents free flow traffic and F represents severe congestion. LOS was derived from KTMPO Model V/C ratios. The following ranges were used to generate roadway segment LOS values and are based on TxDOT’s Transportation Planning and Programming (TPP) division resources:

• LOS A: Less than 0.33

• LOS B: 0.33 to 0.55

• LOS C: 0.55 to 0.75

• LOS D: 0.75 to 0.90

• LOS E: 0.90 to 1.00

• LOS F: Greater than 1.00

Outputs for this assessment were analyzed for the full 24 hour period, as that is what was possible through use of the KTMPO Model.

Existing Conditions Analysis Results

The following sections detail findings from analyses based on the KTMPO Model to create a robust understanding of existing roadway conditions.

Regional Trends from KTMPO Model

Performance measure information on existing conditions from the KTMPO Model outputs were analyzed for the 2015 base year to emphasize potential issues on the Temple Subarea’s existing roadway infrastructure. Outputs were calculated to represent performance trends at a system and per capita level. The following measures were used to better understand the state of the Temple Subarea transportation network:

• Vehicle Miles Traveled (VMT) The amount of roadway miles traveled by vehicles within a specified segment for the 24-hour period travel time.

o This measure provides a sense of the overall level of vehicular traffic in the region and on individual roadways.

• Vehicle Hours Traveled (VHT) Calculated from speed and miles traveled, VHT represents the number of hours traveled by vehicles within a specified segment for the 24 hour period travel time.

o This measure provides insight into the quality of service that the region’s roadways provide, and feeds into other delay measures.

• Vehicle Hours of Delay This represents additional hours spent in traffic due to congestion on the roadway network.

o This measure indicates the amount of extra time it takes travelers to reach conditions compared to free flow conditions.

• Travel Time Index (TTI) The ratio of travel time on a congested network required to make the same trip at free flow speeds.

o For example, a TTI of 1.2 indicates that a 10 minute free flow trip would take 12 minutes on a congested network.

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Table 13: Temple Subarea Existing Traffic & Congestion Performance Measures presents the performance measures for the existing 2015 base year of the KTMPO Model for the Temple MMP Study area. The table is meant to quantify existing traffic and congestion and to provide a baseline for eventual evaluation of future conditions of the Temple Subarea. As the experience of congestion is subjective by region, the congestion described in these metrics are instead in contrast to a non real free flow network simulation, meaning they are the “existing” or real as modeled conditions.

Table 13: Temple Subarea Existing Traffic & Congestion Performance Measures Measure

2015 - Existing Conditions* Interstate Arterials Total

Daily VMT 995,974 1,736,162 2,732,137 per person 28

Daily VHT 18,876 47,877 66,753 per person 0.68

Annual Weekday Vehicle Hours of Delay 9,370 15,451 24,821 per person 0.25 Travel Time Index (TTI) 1.06 1.03 1.04 *2015 was used to evaluate current conditions because it is the most recent year available in the KTMPO Model.

Source: KTMPO Model

The 2015 “existing conditions,” data in Table 13 shows the average daily VMT per capita is 28 for the Temple Subarea. The KTMPO Model indicates that there are low levels of congestion in the 2015 existing conditions for the Temple Subarea. The reported average annual weekday vehicle hours of delay for the Temple Subarea are equivalent to 15 minutes per person. The TTI indicates slight congestion for 2015 existing conditions, with slightly more congestion occurring on interstate roadways than arterial roadways. The TTI measure suggests trips traveling on the network under congested conditions will take roughly 4% more time compared to the normal free flow travel time for the same trip.

Existing Deficiencies Analysis

The KTMPO Model estimates roadway capacities based on number of lanes, functional classification, and other model inputs. These estimated capacities and the output KTMPO Model volumes were used in evaluating the 2015 roadway system deficiencies of the Temple Subarea. The estimated volumes and capacities were used to calculate a V/C Ratio to generate equivalent LOS values (refer to Travel Demand Model Outputs section regarding LOS methods) and is defined below.

Volume Capacity (V/C) Ratio is the ratio of traffic flow to maximum allowable traffic flow on a roadway segment, where a ratio of 1 represents a segment at full capacity and higher values indicate more severe congestion. This measure is used to isolate specific locations where vehicular demand outstrips capacity of a roadway section.

Table 14 displays Temple Subarea capacity measures. The 2015 average V/C ratio suggests that, on average, the existing roadway network is below capacity and operates at an acceptable LOS. The 2015 average V/C ratio of 0.39 falls within LOS B, which indicates low congestion in the Temple Subarea. Roughly 9% of the total roadway miles within the Temple Subarea are reported as being congested in 2015.

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Table 14: Temple Subarea Existing Roadway Capacity Measures Measure

2015 – Existing Conditions*

Interstate Arterials Total

Average V/C Ratio 0.60 0.37 0.39

% of Roadway Miles with Heavy Congestion 9%

*2015 was used to evaluate current conditions because it is the most recent year available in the KTMPO Model.

Source: KTMPO Model

Table 15 presents LOS totals for the Temple Subarea roadway segments by LOS categories A D (low to moderate congestion acceptable LOS) and LOS categories E F (high to severe congestion failing LOS). LOS measures show that out of 511 roadway miles in the Temple Subarea, 464 roadway miles (91%) are categorized as having an acceptable LOS of LOS A D. A total of 47 roadway miles (9%) are categorized as having a failing LOS of LOS E F.

Table 15: Temple Subarea Existing Level of Service (LOS) Measure

2015 Existing Conditions*

Roadway Miles

% of Total

LOS A-D 464 91%

LOS E-F 47 9%

Total 511 100%

*2015 was used to evaluate current conditions because it is the most recent year available in the KTMPO Model.

Source: KTMPO Model

Figure 50 displays the 2015 roadway network LOS values of the Temple Subarea as reported by the KTMPO Model. This figure helps illustrate existing roadway system deficiencies within the Temple Subarea. The KTMPO model estimates severe LOS conditions along some of the major roadway facilities. Figure 50 shows that existing Temple Subarea LOS is strained along highways around major urban areas. Contiguous LOS scores of E and F, suggesting heavy congestion and are seen in the following roadways:

• Highway 36 west of the City of Temple

• Highway 317

• I 35 from north of the City of Temple to the City of Belton

• Highway 363 west of the City of Temple

• US 190 south of the City of Temple

• Highway 95 south of the City of Temple

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Source: KTMPO Model

The following summarize key findings from the roadway needs analysis:

• Existing 2015 KTMPO Model outputs show that the regional study area and per capita level of congestion measures are at an acceptable level. Overall, the Temple Subarea region roadway system is experiencing mostly low to moderate congestion.

• LOS measures derived from the KTMPO Model V/C ratios further these claims, displaying only 9% of roadway miles in the Temple Subarea study area being categorized as the LOS E F category.

The KTMPO Model performance measures identified in this memo will be used to evaluate the 2045 No Build Scenario, as well as any other alternative future or emerging trends scenarios.

Figure 50: Temple Subarea Level-of-Service 2015 Existing Conditions

Forecast Conditions

Figure 51 displays the LOS for the roadway network based on 2045 projections.

Figure 51: Temple Subarea Level of Service 2045 Forecast Conditions

Future Capacity Deficiencies

Source: KTMPO Model

The following list identifies potential future capacity deficiencies taking into account planned improvements and the forecast model reported LOS. The streets and intersections below are described by their current design and forecasted impacts Recommendations are made for each location listed. Several of the intersections that would be of concern are included in the roadways already identified.

Roadways

W.

• LOS F

• Roadway Improvements:

o S. 31st Street: 4 Lane, with a 5th turn lane on Northbound traffic curb & gutter section o W. Avenue D: 2 Lane curb & gutter section

• Major Traffic Generators: o Hospital, school, commercial and retail businesses along 31st Street.

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o Used as alternate route to avoid Central/Adams/N. 31st Street intersections

• Notes: W. Avenue D @ S. 31st Street is a non signalized intersection that experiences traffic backups during peak traffic periods. The lack of signalization during the peak hours results in traffic backups leading to the LOS F classification. The roadway is currently identified as a neighborhood collector in the Thoroughfare Plan.

• Recommendation: Identify this roadway as a Community Collector in the Thoroughfare Plan and perform a warrant study to determine if this intersection warrants a traffic signal.

W. Avenue T from W. 37th Street to S. 31st Street

• LOS F

• Roadway Improvements:

o S. 31st Street: 5 Lane curb & gutter section

o W. Avenue T: 2 Lane curb & gutter section

• Major Traffic Generators:

o Hospital, school, neighborhood, commercial and retail businesses along 31st Street.

• Notes: W. Avenue T @ S. 31st Street is a non signalized intersection that experiences traffic backups during peak traffic periods. The lack of signalization during the peak hours results in traffic backups leading to the LOS F classification. It is a straight aligned roadway that connects 31st Street to 57th Street. New development (retail and multifamily) and fast food restaurants has resulted in increased traffic at this intersection. The roadway is currently not designated in the Thoroughfare Plan.

• Recommendation: Identify this roadway as a Community Collector in the Thoroughfare Plan and perform a warrant study to determine if this intersection warrants a traffic signal.

Scott Blvd from S. 57th Street to S. 51st Street

• LOS F

• Roadway Improvements:

o S. 31st Street to S. 37th Street: 4 Lane curb & gutter section.

o S. 37th Street to S. 57th Street: 2 Lane with 10 foot striped shoulders curb & gutter section.

• Major Traffic Generators:

o Hospital, neighborhood, commercial and retail businesses along 31st Street.

• Notes: Scott Boulevard experiences traffic issues due to Baylor Scott & White Hospital, retail, restaurants, and multifamily elements near 31st Street and Scott Intersection as well as business and retail elements near 57th and Scott. This activity, accompanied by the large neighborhood in the middle, results in a roadway that experience significant traffic most of the day. This roadway also provides a way to bypass the S. 31st Street/Loop 363 intersection and ultimately the I 35/Loop 363 Intersection. The roadway is currently designated as a Neighborhood Collector in the Thoroughfare Plan.

• Recommendation: Identify this roadway as a Community Collector in the Thoroughfare Plan and evaluate striping options to accommodate more traffic capacity, while trying to maintain a neighborhood element between 37th Street and 57th Street. Recommend intersection enhancements at 57th and Scott.

Market Loop from Cottonwood Lane to S. 31st Street

• LOS F

• Roadway Improvements:

o 2 Lane curb & gutter section

• Major Traffic Generators:

o Hospital, neighborhood, commercial and retail businesses along 31st Street.

• Notes: Market Loop experiences traffic issues due to Baylor Scott & White Children’s Hospital, retail, restaurants, as well as the neighborhood that is located south of Loop 363 and west of S.

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31st Street. This roadway also provides a bypass of the 31st/Loop 363 intersection. This also is a direct route to access Thornton Lane and Midway Drive via Cottonwood Lane from 31st Street. The roadway is currently designated as a Neighborhood Collector in the Thoroughfare Plan.

• Recommendation: Identify this roadway as a Community Collector in the Thoroughfare Plan and evaluate striping options to accommodate more traffic capacity, while trying to maintain a neighborhood element.

Hartrick Bluff Road from FM 93 to City Limits

• LOS F

• 2-lane Roadway: o County roadway section.

• Major Traffic Generators:

o New residential developments

o Direct connection between FM 93 and FM 436

• Notes: Hartrick Bluff Road a direct route/cut thru from FM 93 to FM 436. There are large sections of unimproved land along this route. Future residential development will increase the burden on this roadway, that is currently at a LOS F. The roadway is currently designated as a Community Collector in the Thoroughfare Plan.

• Recommendation: This roadway could potentially be identified as a Minor Arterial based on future development along the route.

Intersections

W. Avenue T @ N. 31st Street

• LOS F

• Reference W. Avenue T from W. 37th Street to S. 31st Street.

• Notes: W. Avenue T @ S. 31st Street is a non signalized intersection that experiences traffic backups during peak traffic periods. The lack of signalization during the peak hours results in traffic backups leading to the LOS F classification. The roadway is currently identified as a neighborhood collector in the Thoroughfare Plan.

• Recommendation: Identify this roadway as a Community Collector in the Thoroughfare Plan and perform a warrant study to determine if this intersection warrants a traffic signal.

S. 57th Street @ Scott Blvd.

• LOS F

• Reference Scott Blvd from S. 57th Street to S. 51st Street

• Notes: Scott @ 57th Street is a signalized intersection that experiences traffic backups during peak traffic periods. Expansion (1 lane minimum) on 57th Street would aide in the current flow of this intersection. The current radius at the corners is tight and the number of lanes on 57th Street slow down turning movements at this intersection.

• Recommendation: Evaluate an additional lane on 57th Street to enhance safe turning movements at this intersection.

Key Findings

• As expected, major roadways such as interstates and state highways are expected to see high levels of congestion and delay in the future.

• Many connections on the west side of town, near Loop 363 are forecasted as failing in 2045.

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• Educational facilities within the City of Temple are expected to continue to be one of the largest activity generators in the community. Level of service around these institutions is typically congested, especially during peak hours.

• Industrial will likely continue to expand in Temple, especially to the north. Evaluating impacts of current delay and the freight network on future LOS to identify potential routing recommendations.

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TRAFFIC CONGESTION AND LEVEL OF SERVICE

In support of the Temple Master Transportation Plan, mesoscopic models were developed to analyze operational performance of the existing roadway network using Transmodeler (version 6) software. TransModeler is a mesoscopic tool for conducting large scale, detailed traffic simulations using origin destination data. Measures of effectiveness from the TransModeler simulations were used to establish baseline operations for future comparison.

Methodology and Data Sources

The following information provides a summary of the operational analysis used for establishing baseline conditions using TransModeler. The study methodology is as follows:

1. Acquired data from the KTMPO travel demand model performed using the 2015 base year including:

a. Existing roadway geometry

b. Roadway functional class information

c. Speed limits

d. Daily origin destination (O D) metrics reflecting 2015 weekday trip patterns, beginning, ending, or passing through Temple

2. Acquired signal timing data from the City of Temple for all signalized intersection within the City limits.

3. Used historical ADT from the TxDOT Statewide Traffic Analysis and Reporting System (STARS) to develop AM and PM peak hour factors that were then applied to the daily O D data to provide 2015 AM peak hour and PM peak hour O D matrices.

4. Determined 2021 baseline AM peak hour and PM peak hour O-D matrices using 2021 existing volume counts and traffic growth rates determined from historical traffic counts obtained from STARS. A growth rate of 2.0% was applied over a six year period.

5. Developed a simulation network of Temple’s transportation system using Caliper TransModeler Version 6.0™ to model existing traffic conditions of the roadway network.

6. Analyzed existing conditions using TransModeler to compile intersection turning movement counts, intersection level of service, and delay.

7. Compared output produced in step 6 with existing peak hour counts taken in 2019 pre pandemic conditions to evaluate the validity of the traffic demand model data using a square error (% RSME) test.

8. Calibrated the baseline model using the results of Step 7 and to reflect more realistic field conditions.

9. In accordance with the 2010 Highway Capacity Manual (HCM), reviewed the results of the baseline simulation model runs to evaluate the quality of traffic flow.

By developing a baseline condition, the resulting model will allow operational and capacity issues to be identified and support review and comparative analysis of the effects of modified lane configurations, traffic control, and any additional mitigations made to the roadway network on the systems operational performance for the upcoming future conditions.

Existing Operational Performance Results

Measures of effectiveness (MOEs) were output from the TransModeler simulation runs to evaluate operational performance of the AM and PM peak hours in the baseline conditions. These MOEs include intersection level of service (LOS), total network delay, total vehicle miles traveled (VMT), segment delay, and segment volume. Figure 52 provides an example of a simulation run displaying traffic backup along 31st Street at the Loop 363 interchange.

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Source: TransModeler V6

Intersection LOS is a qualitative measure describing operational conditions within the traffic stream, based on service measures such as speed, travel time, freedom to maneuver, traffic interruptions, comfort, and convenience. It ranges from LOS A (best) to LOS F (worst). LOS thresholds for intersections are based on control delay and are defined in the Highway Capacity Manual; TransModeler implements HCM 2010 methodologies to calculate LOS at intersections. The number of intersections with unacceptable LOS, represented by LOS E and LOS F, is shown in Table 16 A total of 81 intersections in the Temple MMP study were analyzed. Table

Source: TransModeler V6

A comparison of total network delay was made for the AM and PM peak hours. Delay is a measure of additional travel time experienced by travelers at speeds less than the free flow speed (expressed in minutes). Total network delay sums the delay for all vehicles within the simulation and all vehicles which could not enter the network during the analysis period.

Total Network Delay Baseline Conditions

As shown in Figure 53 the PM peak hour experiences higher total network delay than the AM peak hour, which is typical in many urban areas. This comparison is confirmed by the visual observation of the model which sees congestion propagate throughout the study area. Within the network, 31st street experienced

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Figure 52: Existing Conditions TransModeler Network - Loop 363 and 31st Street

the highest average delay in the PM peak hour, followed closely by the couplet formed by Adams and Central Aves Table 17 and Table 18 show the top intersections with high delay or failing level of service (LOS) for the AM and PM peak periods.

Figure 53: Total Network Delay by Time Period

5,000

Total Network Delay (hours)

4,000

3,000

2,000

1,000

0

AM Peak Hour PM Peak Hour

Source: TransModeler V6

Table 17: Existing Conditions Top Intersections with High/Failing LOS for AM Peak Period Intersection LOS Delay (sec/veh)

31st St & Loop 363 Frontage E 56 Adams Ave & Apache Dr E 65

FM 2305, Hilliard Rd & Old Waco Rd E 73 Adams Ave & 25th St F 87

31st St & Loop 363 Frontage F 100 I-35 Frontage & Central Ave F 103 31st St & Ave H F 112

31st St & Scott Blvd F 121 Adams Ave & I 35 Frontage F 151 Adams Ave & Central Ave F 196 31st St & Ave M F 224

Source: TransModeler V6

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Table 18: Existing Conditions Top Intersections with High/Failing LOS for PM Peak Period Intersection LOS Delay

(sec/veh)

31st St, Magnolia Blvd & Marlandwood Rd E 61

I 35 Frontage & 57th St E 65

Adams Ave & Central Ave F 241

I-35 Frontage & Central Ave F 99

Adams Ave & 25th St F 231

FM 2305, Hilliard Rd & Old Waco Rd F 192

31st St & Ave H F 116

31st St & Ave M F 262

Adams Ave & I-35 Frontage F 177

Adams Ave & Apache Dr F 102

31st St & Loop 363 Frontage F 140

Source: TransModeler V6

Figure 54 and Figure 55 on the following pages show total network delay by time period.

Figure 54: 2021 AM Peak Delay

Source: TransModeler V6

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Source: TransModeler V6

In addition to total network delay, total vehicle miles traveled (VMT) was compared across scenarios. Because the OD matrix is consistent for each of the options, a higher VMT indicates that more traffic is being served during the analysis period or that vehicles travel along longer routes. VMT for the AM and PM peak hours are presented in Figure 56

Figure 55: 2021 PM Peak Delay

As shown in Figure 56 the AM and PM peak hour exhibit similar VMT, with the PM peak hour being slightly higher which is most likely due to the combination of higher demand and added delay in the PM peak hour.

Figure 56: 2021 Total VMT by Time Period

Total Vehicle Miles Traveled (mi)

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000

AM Peak Hour PM Peak Hour

Source: TransModeler V6

The results of the analyses indicate that within the City of Temple a total of 12 intersections in the AM peak hour and 14 intersections in the PM peak hour are currently operating at an unacceptable level of service.

Total network delay and vehicle miles traveled were also compiled for the AM and PM peak hours and it was observed that the PM peak hour experiences more delay and congestion than the AM peak hour. This is consistent with the typical traffic patterns in most urban areas as trips between home and work as well as trips between home, work, and commercial developments tend to occur more in the PM peak hour.

These baseline conditions were then used to identify operational and capacity issues and review the effects of modified lane configurations, traffic control, and any additional mitigations made to the roadway network for the future operational deficiency analysis

Future Operational Deficiencies Analysis

Using the TransModeler V6 model to forecast future conditions, a total of 207 intersections were analyzed for the future year. These projections indicate 24 total failing intersections in the AM with 11 LOS E and 13 LOS F gradings. Projections for the PM show 38 total failing intersections with 12 LOS E and 26 LOS F gradings. Table 19 and Table 20 show intersections with a LOS F in the future forecast assuming the existing network and planned improvements are the only changes to the network. Future intersection LOS for AM and PM are shown in Figure 57 and Figure 58

It should be noted that commuters from western areas of Bell County are channelized to the same three routes: SH 36, Adams Avenue, and I-35 based on the existing plus committed network. Additionally, locations where the roadway or intersection is shared with a TxDOT facility, coordination with that agency will need to occur as the City does not own the right of way.

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Table 19: Future Conditions Top Intersections with Failing LOS for AM Peak Period

Intersection

LOS Delay (sec/veh)

Hillyard Rd, FM 2305 & Old Waco Rd F 363 31st St & I-35 Frontage F 253 Loop 363, Young Ave & FM 438 F 205

I-35 Frontage & Nugent Ave F 196 57th St & I-35 Frontage F 140 Central Ave & I-35 Frontage F 131 31st St & Ave M F 122

Midway Dr, Charter Oak Dr & Kegley Rd F 114

FM 2305 & Kegley Rd F 110 Central Ave & 31st St F 84

Nugent Ave & Eberhardt Rd F 84 Kings Trail & FM 93 F 67 Young Ave & Shell Ave F 57

Source: TransModeler V6

Table 20: Future Conditions Top Intersections with Failing LOS for PM Peak Period

Intersection

Hillyard Rd, FM 2305 & Old Waco Rd

LOS Delay (sec/veh)

F 432

Central Ave & I-35 Frontage F 274

Industrial Blvd & Cearley Rd F 242 Loop 363, Young Ave & FM 438 F 236

US 190 / Loop 363 & 1st St Connector F 184 Kings Trail & FM 93 F 182

57th St & I-35 Frontage F 159 31st St & I-35 Frontage F 145

FM 2305 & Kegley Rd F 141 Young Ave & Shell Ave F 134 31st St & Ave M F 133

I-35 Frontage & Nugent Ave F 133 Industrial Blvd & Loop 363 F 132 57th St & Loop 363 Frontage F 128

Midway Dr, Charter Oak Dr & Kegley Rd F 124

Loop 363 Frontage & SH 36 F 102

Adams Ave & 31st St F 101 Central Ave & 31st St F 101

Adams Ave & I 35 Frontage F 93

Old Howard Rd, SH 36 & Hillyard Rd F 90

57th St & Scott Blvd F 86

Cearley Rd, SH 53 & Twin Oaks Dr F 85

Loop 363 Frontage & SH 36 F 84

FM 2305 & Pea Ridge Rd F 82

Loop 363 Frontage & Wendland Rd F 81 Loop 363 & Industrial Blvd F 65

Source: TransModeler V6

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Figure 57: Future AM Intersection LOS Map

Source: TransModeler V6

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Figure 58: Future PM Intersection LOS Map

Source: TransModeler V6

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TRANSPORTATION DEMAND MANAGEMENT

A review of current and past efforts to pursue Transportation Demand Management strategies in Temple was undertaken as part of the review of existing conditions for the Temple MMP. The purpose of the review was to gain an understanding of the current knowledge of and support for Transportation Demand Management by the City of Temple’s elected officials and staff and the leaders of other partner agencies.

Methodology and Data Sources

A description of the existing conditions for TDM in the City of Temple and the surrounding area was developed by reviewing transportation planning documents of the City, KTMPO and other area agencies that might have initiated TDM activities in the past or are currently considering doing so. After a review of documents was complete, members from the ATG team provided a presentation to the Temple MMP Steering Committee stating the results of the review and asking the committee if any current or past activities had been missed. The ATG team also identified “Commute Mode Share” within the City of Temple as the perfromance measure to be used to establish the current state of TDM activity and to measure the potential future benefit of of new TDM programs activitites

Existing Programs and Policy

The review of documents produced examples of interest in TDM on the part of the City of Temple and the KTMPO but there was no evidence of past efforts to establish formal TDM programs and no evidence of current efforts underway.

Interest in TDM was expressed in the City of Temple’s Comprehensive Plan 2020. One of the stated principles of the plan is as follows:

2.2.7. Evaluate opportunities to invest in transportation demand management and smart city technologies to improve transportation efficiency.

Transportation Demand Management (TDM) is an overarching term for strategies that increase the overall efficiency of a transportation system with a priority focus on encouraging a reduction of single occupant vehicles trips (i.e., through an improved multi-modal transportation system) and through shifting of trips outside of peak periods. For a growing city the size of Temple, a greater focus may be to establish a proactive set of land use policies which reduce the need for travel through transportation efficient land uses (e.g., neighborhood services near residential areas, higher intensity mixed-use activity centers, etc.) and a focus on maximizing the use of smart city technologies to improve transportation efficiency. Some of these smart city technologies may include real time weather monitoring systems to enhance traffic safety, intelligent and adaptive traffic control devices which react to changing traffic patterns and public safety emergency needs, effective parking management, enhanced transit services, and other strategies emerging in published research. 9

While the statement of principle in the comprehensve plan acknowledges the value and potential role of TDM in Temple, the comprehensive plan does not identify any actions to intiate any TDM programs within the City.

The 2045 Metropolitan Transportation Plan develped by KTMPO provides the following statement acklowledging KTMPO staff activities to explore TDM:

9 City of Temple Comprehensive Plan 2020, Chapter 5, page 145.

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Staff is working to obtain more information to educate and inform the public about air quality issues such as Ozone and will work with the Policy Board to consider participation in this program. Program participation will include collaboration and support of the KTMPO member entities to identify measures for consideration to lower Ozone concentrations. These measures may include transportation demand management programs such as ridesharing, carpooling, telecommuting, transit, and bike/pedestrian travel 10

Members of the Temple MMP Steering Committee acknowledged the consideration of TDM strategies as part of a past air qulity program of the MPO, but said that effort had not been continued.

Consideration of TDM by KTMPO was also evident in their Congestion Management Process where there was acknowledgment of the value of improving the safety and desirablity of facilities for walking and bicyling in the statement:

Non motorized improvement strategies typically involve improving or creating new infrastructure that more effectively facilitates the use of active transportation. Active transportation includes modes such as walking or biking. Encouraging and facilitating active transportation can help reduce the number of trips made by single occupancy vehicles, thus reducing congestion on roadways. According to the National Travel Household Survey (2009), about half of all trips in metropolitan areas are three miles or less and about 28% of all trips are one mile or less. These distances can easily be made by bicycle or on foot, but 65% of trips one mile or less are made by automobile. Capacity improvements for non motorized transportation often have no effect on motorized transportation capacity but can decrease the demand for motorized transportation. Non motorized improvements can also improve safety conditions and reduce conflicts for people who currently already use active transportation. 11

KTMPO’s Congestion Management Process also identifies a set of “Non Infrastructure Improvements” that can be part of a toolbox for management of congestion including: rideshare programs, flexible work hours, telecommuting, satefllite offices, land use management, commuter choice tax benefits, HOV Toll savings, parking management, and driver education. 12

Existing Mode Share

To provide an indication of the current level of mode use for commuting, the ATG team assembled Table 21 showing the shares for 2018 and 2015. The US Census Bureau American Community Survey, the source used for the estimate of mode shares, tends to somewhat overstate the use of modes that are most heavily used because the survey asks commuters what mode they most often use. The results indicate that commuting in the City of Temple is highly car oriented with 82.9% driving alone and 10.9% carpooling. A comparison with the 2015 results suggests a small shift from driving alone to carpooling has occurred but the overall share using a car has remained about the same. Bicyling and walking to work have decreased slightly but working at home has increased slightly.

10

KTMPO, 2045 Metropolitan Transportation Plan, Environment & Quality of Life Air Quality, page 174. 11

KTMPO, Congestion management Plan 2016 Update

12

KTMPO, Congestion management Process I 2016 Update, Pages 4 5 to 4 7.

City of Temple Mobility Master Plan

Table 21: Commute Mode Share for Temple

Usual Commute Mode

2018

Share 2015 share

Drove Alone 82.9% 83.5% Carpooled 10.9% 9.9% Public Transit 0.5% 0.5% Taxi 0.0% 0.0% Motorcycle 0.2% 0.2%

Bicycle 0.3% 0.5% Walked 1.3% 1.7%

Worked at Home 3.4% 3.2% Other 0.5% 0.5%

Total 100.0% 100.0%

Source: US Census Bureau American Community Survey

Two recent trends that might lead to significant changes are the effect of the COVID 19 pandemic on working from home and the widespread availability of ride hailing companies like Uber and Lyft. During the COVID-19 pandemic, working from home increased dramatically out of necessity, but recent polls indicate that most workers would like to continuing working from home at least some of the time. Over the past year, most workers and their employers have invested in home furniture, computer and telecommunications technology and procedures to support collaboration and monitoring. One recent poll suggested that at least 16% of employees in the US will remain at home workers long after the pandemic is over. 13

The second major change was a rather sudden appearance and proliferation of ride hailing companies. Revenue from app based ride hailing services rose from $3.7 billion in 2015 to $14.7 billion in 2019. 14 While taxi service in most smaller cities like Temple was viewed as limited in availability and expensive, ride hailing companies have increased the speed of getting a ride and at significant reduction in cost.

Key Findings

The City of Temple has explicitly stated interest in promoting the use of TDM strategies and programs as part of an overall program of mobility and traveler safety. Because there are currently no City or regional TDM programs in place, the ATG Team will undertake a review of possible TDM strategies as part of the Temple Mobility Master Plan recommendations. The ATG team will use a three step process:

1. Gauge the level of support for TDM measures and develop a prioritized list of measures to consider

2. Assess the potential trip reduction benefits of the highest priority measures.

3. Formulate a process for developing a TDM program over time

Special attention will be given to how the recent changes in working at home and the availability of ridehailing services might change the receptivity of worker and employers to TDM programs. Part of the process

13 How Much Will Remote Work Continue After the Pandemic?, Kristen Senz, Harvard Business School Working Knowledge, August 2020.

14 https://www.businessofapps.com/data/ride hailing app market/ (Sources: Grand View Research, Lyft, Statista, Uber)

City of Temple Mobility Master Plan

will be developing a target Commute Mode Share and evaluating how reaching that target might affect other parts of the Temple MMP

City of Temple Mobility Master Plan

TRANSIT

This section explores the existing conditions of fixed route bus transit in the Temple MMP study area by examining each transit route’s ridership by stop, as well as by identifying how much of the underlying transit market is served by the routes. Because transit in the Temple MMP study area is part of an interconnected regional system, it is necessary to look at the breadth of transit service from the regional system level down to individual transit stop characteristics and performance.

Operating under the Hill Country Transit District, a transit agency called The HOP provides all fixed route services in the study area. The HOP currently runs nine different fixed bus routes in the communities of Temple, Belton, Harker Heights, Killeen, and Copperas Cove. Table 22 lists the existing fixed routes and the cities they serve.

Table 22: Existing Fixed Transit Routes The HOP

Route Name City Served

Route 2 Texas A&M/Lake Rd./Rancier Ave. Killeen

Route 4 Killeen Mall/Walmart/Scott & White Clinic Killeen

Route 35 – Harker Heights Loop Harker Heights

Route 65 Copperas Cove Loop Copperas Cove

Route 100 Metroplex/CTC/Copperas Cove Killeen

Route 200 Harker Heights/Nolanville/Belton/Temple Connector Killeen

Route 510 – VA Hospital/Temple College/Temple Mall/Walmart Temple

Route 530 Adams Ave/Temple HS/Social Security Office Temple

Route 610 Belton Loop Belton

Source: The HOP

System Overview

The HOP is a regional public transit system that started in the 1960s as a volunteer transit service that evolved to serve a nine county area. The HOP is a coverage based, hub and spoke system serving multiple cities through the largely rural service area. There are two major transfer stations in Killeen and Temple that serve as the major ‘hubs’ and are connected in a linear pattern by two main routes.

HOP Mission Statement

“To build, refine, and operate a safe, dependable, and effective transportation network that provides mobility, improves the quality of life, and stimulates economic development through the provision of rural, urban fixed route, and ADA complementary paratransit service for citizens and visitors of the Central Texas area.”

The HOP’s routes fall into the falling service categories:

• Express Service

o 200 Express Route Connector

• Bi directional Service

o 100 Metroplex Copperas Cove

• Loop Routes

o 2 Lake Rd/Rancier Ave

o 4 Killeen Mall/Walmart

City of Temple Mobility Master Plan

o 35 Harker Heights Loop

o 65 Copperas Cove Loop

o 610 Belton Loop

• Hybrid routes have both loop and bi directional service: o 510 South

o 530 East/West Crosstown

Figure 59 Highlights The HOP’s service cateogries.

Figure 59: The HOP Service Categories

City of Temple Mobility Master Plan

All of the HOP routes apart from the 200 Express route operate with headways of 60 minutes. The 200 Express operates with trips every two hours. While service span varies by route, most routes run from approximately 6:00 a.m. to 6:00 p.m. Timed transfers are critical for passengers to successfully navigate and use the system. The following is a list of all the key transfer locations and which routes transfer at each location. Schedules have been designed to foster a seamless transfer.

• Transfer between Routes 2 and 4 at 4th St and Ave C (Killeen Transfer Station)

• Transfer between Routes 100 and 4 at Texas Workforce commission

• Transfer between Routes 4, 35, and 200 at S&W clinic

• Transfer between Routes 100 and 65 at Walmart

• Transfer between Routes 510 and 530 at Adams & Main (Temple Transfer Station)

• Transfer between Routes 200 and 510 at Temple College

• Transfer between Routes 200 and 610 at Liberty Park

Figure 60 displays The HOP’s key transfer locations. Figure 61 maps these routes, as well as their existing stops, across the study area.

Figure 60: The HOP Key Transfer Locations

Source: The HOP

City of Temple Mobility Master Plan

Methodology and Data Sources

In order to map existing transit ridership by stop, the project team obtained ridership counts from The HOP that reflected ridership activity across the fixed route transit system spanning one week in spring of 2019. The total ridership activity (the sum of boardings and alightings) for each stop over the course of the week was mapped in GIS using a heat map visualization. This process depicted which stops along each route had the highest and lowest ridership activity. These heat maps are shown in the Results subsection below.

To identify how much of the market is currently served by fixed route transit, the project team looked at the total population, total employment, and Target Transit Riders (TTR) currently within the service area. To do this, the project team conducted a buffer analysis in GIS using the existing bus stops and demographic/employment data from the US Census Bureau’s 2019 American Community Survey (ACS) and 2018 Longitudinal Employer Household Dynamics program (LEHD) First, the project team used data on several demographic groups to sum the total TTR population in each block group in the study area. The demographic groups included in TTR population are:

• Population with disabilities

• Population with limited English proficiency

• Population of minorites

• Population aged 65 and older

Figure 61: Existing Fixed Transit Routes and Stops The HOP

Source: The HOP

• Population aged 17 or younger

• Population in poverty

These group were included because they are more likely to create demand for transit service. Next, the project team generated a quarter mile buffer around the existing bus stops in the transit system to represent the assumed maximum distance that most people would be willing to travel by foot or assistive mobility device to reach a transit system access point (bus stop or transfer station). Populations that fall within this buffer are considered to be served by the transit system and populations that fall outside the buffer are considered to be unserved. To estimate the number of TTR served by the existing fixed route transit system, the project team calculated the area (in square miles) of each block group and the area (in square miles) of the buffer to identy what percentage of each block group was covered by the quarter mile buffer. These percentages were then applied to the total TTR population to estimate how many TTRs are served in each block group. For example, if the quarter mile buffer covered 50% of a given block group, then the project team estimated that 50% of that block group’s TTR population are currently served by transit. The project team used this same process to calculate the total population served and total employment served.

Ridership Analysis

Transit ridership across the nation took a large hit during the initial onset of the COVID-19 pandemic. Ridership declined drastically in some locations across the country. For example, Houston Metro reported its total ridership was 53.6% lower in December 2020 than compared to the same month 2019 15 . DART saw a 55% decrease 16 in overall ridership from March to June in 2020 alone. The HOP faced similar hardship, with ridership declining by similar numbers. Although transit is expected to recover, the length of time it will take to reach pre COVID ridership numbers is unknown.

Total Ridership by Existing Routes and Stops

Mapping ridership by stop revealed patterns of the geographic distribution of ridership activity in the study area. The majority of stops that experienced the highest ridership activtity were transfer stations and other major destinations, such as medical facilities, supermarkets, and higher education facilities. Figure 62 through Figure 64 map ridership by stop for each route.

Figure 62 reveals that Route 200’s highest ridership activity occurs at the two extremeties of the route, at the Baylor Scott & White Clinic on Scott & White Drive between Harker Heights and Belton and at Avenue U at 3rd Street in the City of Temple. Confederate/Liberty Park in Belton and the Baylor Scott & White Medical Center in the City of Temple also both experience relatively high ridership for this route

Figure 63 shows that the Temple Transfer Station, the Walmart on Private Drive, and Avenue U at 3rd Street by the VA hospital have the highest levels of ridership for Route 510 in the City of Temple.

15 Source: TTI, April 2021, https://comptroller.texas.gov/economy/fiscal notes/2021/apr/transit.php

16 Source: Community Impact, July 2020, https://communityimpact.com/dallas fort worth/richardson/coronavirus/2020/07/08/dart officials report 55 hit to ridership since march/

City of Temple Mobility Master Plan

Figure 62: Route 200 Ridership by Stop

Figure 63: Route 510 Ridership by Stop

Source: The HOP

Source: The HOP

City of Temple Mobility Master Plan

Figure 64 reveals that the Temple Transfer Station in downtown Temple has the highest ridership activity of Route 530, followed by Adams Avenue at 23rd Street.

Figure 64: Route 530 Ridership by Stop

City of Temple Mobility Master Plan

Source: The HOP

Transit Market

Figure 65 and Figure 66 show the results of the buffer analysis to assest the amount of transit market served by the existing fixed route system.

Figure 65 compares the levels of TTR in each block group to the quarter mile buffer the project team generated around the existing transit stops. The map illustrates that there are block groups with high levels of TTR around Temple and west central Bell County south and east of Killeen/Harker Heights that fall outside of the existing system’s service area.

Figure 65: Target Transit Riders Served

City of Temple Mobility Master Plan

Source: The HOP

Figure 66: Population and Employment Served

Source: The HOP

Figure 66 illustrates the levels of total population and employment in the study area in comparison to the quarter mile buffer the project team generated around the existing transit stops. The map shows that areas of both high population and employment are being served in Belton, Harker Heights, and south Killeen. However, there are still many block groups with medium to high levels of population and employment that are not currently served by the fixed route transit system.Figure 67 illustrates the percentages of TTR, total population, and total employment that are currently served by the fixed route transit system.

City of Temple Mobility Master Plan

Future Plans

The Hill Country Transit District (HCTD) Service Provision Options Report completed in May of 2021 evaluated four future transit options for how HCTD could organize itself. Two scenarios were carried forward with implementation plans established by the HCTD Board. These scenarios focus on internal operations and not future routes or service operations. Additional information can be found in the Report.

Key Findings

Key Findings from the overview of the existing transit network and available ridership data include:

• The existing fixed route transit system in the study area is estimated to serve just over a third of the total population in the study area and just under half of all employment.

• The highest levels of ridership activity tend to occur at major destinations such as transfer stations, medical facilities, supermarkets, and higher education facilities.

• All of the HOP routes apart from the 200 Express route operate with headways of 60 minutes.

• There are block groups with high levels of TTR around Temple and west central Bell County south and east of Killeen/Harker Heights that fall outside of the existing system’s service area.

• The data analysis and feedback garnered through this study indicated that there is a transit service gap between central/east Temple and employment opportunities in the Industrial Park.

• Although current plans for future growth in transit service are modest, Hill Country Transit has offered to work with the study team on alternative future scenarios.

City of Temple Mobility Master Plan

Figure 67: Transit Market Served by Existing System

ACTIVE TRANSPORATION

Active transportation infrastructure is an important component to a balanced transportation system that supports mobility. Active transportation is a general term that covers non-motorized modes of travel such as walking, biking, and wheeling. Pedestrian and bicycle supportive infrastructure helps provide facilities that enable travelers to choose non motorized travel throughout the Temple MMP study area and provides key accessibility connections to people with mobility challenges. Accessibility and connectivity for people who walk and bike or use other active transportation modes is a primary goal of the previous Temple Comprehensive Plan 2020 and therefore is expected to play a major role in the Temple MMP as well.

To gain a better understanding of the current conditions for walking, biking, or using a mobility device in the study area, this memo aims to answer three questions:

1. How does it feel to walk or bike in Temple right now?

2. Where are people in Temple likely to walk or bike?

3. Where are barriers to walking and biking in Temple?

Answers to these questions are gathered through a range of analysis and data which are described in more detail in the sections below.

Existing Facilities

Sidewalks

The City of Temple’s sidewalk network is predominantly located in the central core of Temple between I 35 to the west and SH 363 to the east. The street network in this area is gridded with relatively short block lengths between each street. Short block lengths and a well connected street network can promote increased walking trips if paired with a sidewalk network in good condition and with proper connectivity.

Within the City of Temple, there are 173 miles of existing sidewalk. Roadways throughout the City of Temple that should typically have sidewalks on both sides were measured to arrive at 1,122 miles of total potential sidewalk (including the existing infrastructure) in the City of Temple (Table 23). This means that over 84% of roadways that should typically have sidewalk currently lack this transportation resource. To get a better sense of the overall condition of existing sidewalks within the City of Temple municipal boundary, sidewalk data from the City’s GIS database and Google Street view imagery were analyzed to determine the proportion of sidewalk in each of the six sidewalk condition rankings. Results are displayed in Figure 68 below. 40% of existing sidewalk is in good condition or better, much of which is located outside of the core of Temple in neighborhoods to the west and south. These occurrences may have more recent developments with newer sidewalk; however, based on what is depicted in the most recent Google Street view imagery, 6% of sidewalk is in Fair condition while another 40% is in Poor or Very Poor condition. Fair, Poor, and Very Poor sidewalks are concentrated in the gridded central portion of Temple. 14% of existing sidewalk did not have a reported condition ranking.

City of Temple Mobility Master Plan

Table 23: Sidewalk Coverage in City of Temple

Sidewalk Status Miles of Sidewalk % of Potential Sidewalk

Existing Sidewalk 173 15.4%

Missing Sidewalk 949 84.6%

Total Potential Sidewalk 1,122 100%

Hike & Bike Trails

Within the project study area, there are nearly 40 miles of off street hike & bike trails, including both paved and non paved trails. Currently, there are not any designated on street bicycle facilities, such as bike lanes or protected bike lanes, within the City of Temple. Existing sidewalks and hike & bike trails within the study area are shown in Figure 69

Figure 69: Existing Sidewalk and Hike & Bike Trails

Figure 68: Sidewalk Condition in City of Temple

EXCELLENT VERY GOOD GOOD FAIR POOR VERY POOR NO CONDITION

Source: City of Temple

City of Temple Mobility Master Plan

Bicycling Comfort

Using a bicycle is a healthy, efficient, and affordable way to reach daily activities. However, safe and comfortable facilities are needed for most people to choose cycling as a way of getting to their destination. A commonly used typology 17 within active transportation planning separates potential active transportation users into four categories of bicycle user types.

Strong and Fearless ~3%

These riders are a small portion of the population and are comfortable riding on roadways with limited or no bicycle specific facilities.

Enthused and Confident ~13%

These riders may feel comfortable riding where there is a designated lane for bicycles and on low volume roadways without bicycle facilities.

Interested but Concerned ~54%

While in a park or on a hike & bike trail these riders may feel safe and comfortable, but they have significant safety concerns while riding with traffic on the roadway. They would be interested in riding to accomplish daily needs more often if they felt safe and comfortable. This is generally the largest part of the population.

Not Interested ~30%

This portion of the population doesn’t have interest in riding to accomplish daily activities, but they may use hike & bike trials or ride for recreation on occasion.

Generally, surveys are conducted within a community to determine the distribution of the potential riding population into each of the four categories. Although a survey has not been completed in the study area or in the City of Temple, an average of four surveys conducted in major cities across the country have found that 3% of respondents fell into Strong and Fearless, 13% into Enthused and Confident, 54% into Interested but Concerned, and 30% into Not Interested. These percentages may shift should a similar survey be completed in Temple, but local preferences are likely to remain close to the average of the four surveys. The takeaway from these surveys and bicycle user type classification is that a large portion of the population (Interested but Concerned) may be able to use bicycles more often should safe and comfortable facilities be present along their route.

To better understand how cycling feels within the study area, a Bicycle Level of Traffic Stress (LTS) analysis was conducted to determine how each street feels to a person while cycling. The LTS produces a score ranging from 1 to 4, 1 being the most comfortable and 4 being the least. The LTS score also correlates to

17 Geller, Roger. Four Types of Cyclists

City of Temple Mobility Master Plan

the bicycle user types that feel comfortable using a given street (Table 24). As seen below, LTS scores of 1 and 2 can accommodate 70 100% of the potential riding population.

Table 24: LTS Score and User Accommodation LTS Score Users Accommodated Potential Riding Population Served

Typical Bicycle Facility Types 1 (Low Stress)

The LTS analysis (Table 25) found that a little over 40% of centerline roadway miles in the study area have low stress LTS scores of 1 and 2, with the majority of that being LTS 1. This is fed by the system of local streets with low speeds and volumes, particularly concentrated in the neighborhoods to the north and south of downtown Temple. The remaining 55% of roadways are ranked with LTS scores of 3 and 4, meaning that only up to about 16% of the potential riding population may feel comfortable accessing them in their current form. Outside of the Temple municipal boundary, there are many rural roadways with LTS 3 scores, and although volumes may be relatively low, potential speeds are not conducive to LTS 1 or 2 scores. Low stress streets in neighborhoods to the far south and west of the City of Temple are also fairly isolated and have limited connections to the greater street network.

Table 25: Summary of LTS Scores in Study Area

City of Temple Mobility Master Plan

Figure 70: LTS Scores in Study Area

Figure 70 shows the LTS scores for the street network in City of Temple and the greater study area.

Active Transportation Demand

Walking and biking trips often occur in places where it is comfortable and convenient to make them. People have a need or desire to reach a destination, and they get there in the most convenient, and comfortable way. In the study area, to understand where walking and biking trips might likely happen, an analysis using a grid of hexagons was completed. Hexagons were used as they provide a shape to which different input factors can be evenly attributed. The analysis used the input factors shown below in Table 26 If walking and biking facilities are comfortable and connected to key destinations in the areas identified in this analysis, it is likely that walking and biking trips may occur in those locations. This is not to say that walking and biking facilities should not be present outside of these higher demand areas, but that these areas may be a good place to examine current facilities and potentially make improvements.

Table 26: Active Transportation Demand Input Factors

Input Factor

Source

Population Density US Census Employment Density US Census

Bicycle and Pedestrian Crashes CRIS (TxDOT)

¼ Mile walkshed from Transit Stops Hill Country Transit District

¼ & 1 Mile walkshed from Schools City of Temple

¼ Mile Buffer from Major Parks City of Temple Environmental Justice Zones

KTMPO

Figure 71: Likely Active Transportation Demand

Source: Streetlight Data

Figure 71 shows areas with high concentrations of potential demand for walking and biking trips. The areas of higher demand are clustered near the central Temple area, especially along the gridded street network south of E. Adams Avenue. Areas with moderate demand are also scattered around the study area, especially where they are within proximity to parks or schools. There are pockets of moderate to high demand in areas west of I 35 and south US 190 near Smith.

City of Temple Mobility Master Plan

Planned Improvements

Planned and proposed bicycle facilities shown in Figure 72 were sourced from the KTMPO Future Bicycle & Pedestrian Plan for the Region.

Figure 72: Existing and Planned Bicycle Facilities

Key Findings

Supportive Network

The City of Temple’s central neighborhoods have a network of connected low stress streets that provide a good foundation for walking or cycling. Many of the outlying residential areas to the west and south also contain low stress local streets well suited for active tr ansportation. However, several high stress barriers exist that prohibit connectivity along the broader low stress network, which are discussed more below.

Barriers to Access

As mentioned above, major regional thoroughfares such as I 35 and Loop 363 limit crossing to only a handful of streets to access central Temple. For example, between the north and south interchanges of I 35 and Loop 363, there are five opportunities to cross I 35 from east to west, all of which are high stress roadways which limit the number of the potential riding population that would feel comfortable crossing. The

City of Temple Mobility Master Plan

Source: City of Temple and KTMPO

same may be true for those walking, as presence of sidewalks are spotty approaching those crossings. In central Temple, the same can be said for roadways like Adams Avenue and Central Avenue. These roadways separate Temple from north to south and signalized crossings are primarily on higher stress roadways. A similar effect is created by the railroad line running through Temple, which limits roadway crossings to stressful streets shared with motor vehicles.

Equity Concerns

When comparing high areas of demand and existing walking and biking facilities, it’s apparent that there are gaps in areas that are also identified Environmental Justice Communities (EJ Zones). EJ Zones are identified as areas where more than half of the population is low to moderate income according to the U. S. Department of Housing and Urban Development (HUD), or more than half of the population identifies as a minority (Black; Asian or Pacific Islander, American Indian, Eskimo or Aleut; Other Race), or where a quarter or more of the population is of Hispanic or Latino decent.

Figure 73: Active Transportation Facilities in EJ Zones

Source: City of Temple and ACS 5 YR (2019), KTMPO

As seen to the right in Figure 73, EJ Zones contain a significant portion of sidewalk in less than good condition, as well as limited hike & bike trails. These are also areas of higher demand.

City of Temple Mobility Master Plan

Gaps Analysis

General Connectivity Gaps

There is a gap in site connectivity from the roadway network and planned trail network to key employment centers and community amenities/businesses like the Veterans Administration Hospital (VA), Temple College and Baylor Scott & White Medical Center. The bicycle and pedestrian facilities typically end at the public right of way, making the last hundred foot connection to the 'front door' less comfortable for access. These are possibly private roadways.

Continuity between Park Trails and Planned On-Road Network

The planned connections for trails and on street bicycle facilities do an excellent job of connecting the network, turning a set of park trails into part of the active transportation network (where it is feasible). Because these are planning level connections, there is yet to be precise plans for their location and design, specifically at intersections/crossings. The gaps identified in Table 27 are areas where existing trail crossings could use further engineering and safety analysis, or future crossings should be considered carefully for optimal location and design that balances safety with usability.

Table 27: Critical Active Transportation Network Gap locations

Location Notes

Trail crossing across 1st Street at Temple College

Friar’s Creek Trail crossing across Canyon Creek Dr

Hickory Rd and Midway Dr

Signalized, but could benefit from high visibility features, traffic calming or other safety improvements.

Marked, but could benefit from high visibility features.

Signalized, but could benefit from high visibility features.

While not a physical gap, it is also important to make sure there is not a knowledge gap of the network and where it can connect. It will be important for Temple to coordinate between the Transportation and Parks and Recreation groups to create a signage and wayfinding system to clearly sign, mark and map the linkages between the two systems for seamless integration.

Critical Roadway Network Gaps

The Active Transportation Demand Analysis highlights an area in Temple where the Active Transportation Demand scores high and there are very few continuous North/South and East/West connections across the grid. The railroad is a significant barrier in this area and is likely forcing additional traffic to the few through cross streets. This reinforces the need for a balanced roadway approach to make sure active transportation modes are accommodated on the through streets. Locations of critical gaps are identified in Table 28

City of Temple Mobility Master Plan

Table 28: Critical Roadway AT Network Gaps Street From To Comments

S. 24th St Adams Ave/53 E Avenue N S. MLK Jr Dr E Avenue E King Circle or Trail Crossing

W. Avenue F S. MLK Jr Dr S. 25th St S 25th St W H Ave W Avenue E Includes RR crossing W Avenue E S 25th St S, 31 St

Tie into trail or sidepath on S. 31 St

Stratford Dr Hickory Rd

Waterford Park

S. 5th St Friars Creek Trail Temple College

W Adams Ave Hillard Rd N Kegley Rd

Safety Improvements to upgrade from sidewalk to trail with signage and crossings

W. Adams Ave Morgan’s Point Rd 317 Safety Improvements to upgrade from sidewalk to trail with signage and crossings

City of Temple Mobility Master Plan

FREIGHT NETWORK AND COMMODITY FLOWS

The City of Temple is in the northern part of Bell County, TX along Interstate 35. Figure 74 displays how the City is uniquely situated between five major metropolitan cities in Central Texas

Figure 74: Regional Overview of the City of Temple

Freight transportation continues to increase throughout Temple and is essential to the economy The location of Temple along Interstate 35 makes it an important part of the nation’s freight movement by truck as a part of the National Highway Freight Network. In addition, the City’s central proximity in the state allows for north south and east west rail corridors. Burlington Northern and Santa Fe (BNSF) and Union Pacific (UP) are the main railroad carriers in the City. The City was originally founded based on railroad activity to provide services for railroad equipment and passengers at major junction point.

Existing Freight Network

Combining the positive economic outlook, potential for growth in freight dependent industries, and the level of freight activity on the Temple MMP study area transportation system, the Temple MMP study area shows opportunity for freight growth in the future. It is critical that the study area freight system is designed and maintained to support anticipated development and corresponding increases in freight traffic.

City of Temple Mobility Master Plan

Figure 75 provides the Texas rail and freight network and how it relates to the City of Temple. As displayed, there is a high level of connectivity between the Texas Highway Freight Network in orange and the railroads in purple The City provides a central location point for both rail and trucking. One outcome of the strength and diversity of the region’s freight dependent industries is a substantial flow of commodities moving into and out of Temple and the surrounding area. Commodities moving into and out of Temple and the surrounding area are composed of a broad range of commodity types including items consumed within the region and industrial products and agricultural goods produced in the area for consumption elsewhere.

This memorandum uses the freight trip generation and origin destination data from the Texas Statewide Analysis Model (SAM V4), which was based on 2015 TRANSEARCH data, to measure existing (2015) commodity flows with origins or destinations in Temple and the surrounding area (represented by Bell County in SAM V4). The year 2015 was used to because it is the most recent year available in the SAM V4. The information summarized describes commodities moving into and out of the region in terms of quantity (tonnage), industry type, and geographic trading partner (origin or destination of the goods transported).

Current Commodity Flows

Based on the commodity flow information obtained from the Texas SAM V4, the City of Temple and its surrounding area were estimated to have transported over 12.7 million tons of cargo to trading partners

City of Temple Mobility Master Plan

Figure 75: Texas Rail and Freight Network - Temple

Source: TxDOT

throughout North America in 2015. Top outbound commodities include non-metallic minerals (8.67 million tons); secondary and miscellaneous cargo (1.2 million tons); clay, concrete and glass (0.7 million tons); petroleum products (0.41 million tons); and durable manufacturing (0.33 million tons). Table 29 inbound and outbound cargo tonnage.

Table 29: 2015 Inbound/Outbound Cargo Tonnage from TX SAM V4 Model

Commodity

Inbound Tonnage

Outbound Tonnage

Agriculture 644,324 284,535

Nonmetallic Minerals 3,929,843 8,669,133 Food 570,460 308,359 Consumer Manufacturing 10,996 2,506

Non-Durable Manufacturing 64,663 92,586 Lumber 161,006 180,052

Durable Manufacturing 372,879 334,880 Paper 73,789 34,259 Chemicals 224,602 305,353 Petroleum 1,745,512 407,373

Clay, Concrete, Glass 847,966 703,632

Primary Metal Product 140,323 202,892 Secondary and Misc. 404,129 1,199,857

Total 9,190,492 12,725,417

Source: SAMV4

During that same period, the area will receive over 9 million tons of cargo. Top inbound commodities include non metallic minerals (3.93 million tons); petroleum products (1.75 million tons); clay, concrete, and glass (0.85 million tons); agriculture products (0.64 million tons); and food (0.57 million tons).

Truck Movements

In addition, the existing freight movements of the Statewide Analysis Model Version 4 (SAMV4) were explored to provide a depiction of truck travel on roadways for the Temple region. The table below show the magnitude of truck flows on the model (SAMV4) roadways. As shown, I-35 is the dominant corridor for truck travel, though other roadways do show notable truck flows. We compared this information to Transearch tonnage and truck flows and saw an identical pattern regarding which roadways were being used by trucks.

Table 30 summarizes the roadways in the Temple Subarea with notable truck percentages according to the SAMV4.

City of Temple Mobility Master Plan

Table 30: Truck Volumes and Percentages

Roadway

I-35 (main)

From Limits To Limits

Average Volume

Average Percent Trucks

FM 1327 SH 53 59,400 27%

I-35 (main) SH 53 FM 93 95,200 21%

SH 36 SH 236 Moffat Rd 7,200 8% SH 36 SH 317 SL 363 26,300 7%

SH 36 / US 190 (main) US 95 Pritchard Rd 16,000 14%

SH 53 SL 363 N Mockingbird Rd 16,100 8%

SH 317 Stampede Rd FM 2601 12,100 15%

SH 317

FM 2601 FM 1237 11,400 15%

SH 317 FM 1237 SH 36 12,300 14%

SH 317 SH 36 FM 2483 7,200 8%

SL 336 (main) S I 35 US 95 24,000 9%

SL 336 SH 53 I 35 N 11,000 8% SL 336 (main) SH 36 I 35 S 20,000 8% Sparta Rd Approximately 4.15 miles W of FM 439 FM 439 1,100 9%

FM 93 Spring Valley Rd S Wheat Rd 2,300 15%

Source: SAMV4

City of Temple Mobility Master Plan

Trading Partners

The City of Temple and the surrounding area have a wide range of geographic trading partners across North America. Texas is by far the largest trading partner, with some counties shipping/receiving larger commodity tonnages than many states. Table 31 and Table 32 show the top inbound and outbound trading partners according to the Texas Statewide Travel Demand Model, as well as the top commodity traded between the Temple area and that location.

Table 31: Top Inbound Trading Partners

Trading Partner

2015 Cargo Tonnage

Top Commodity Traded

Harris County, TX 1,057,820 Petroleum

Bexar County, TX 414,772 Nonmetallic Minerals

Williamson County, TX 398,078 Nonmetallic Minerals

Oklahoma 309,641 Nonmetallic Minerals

Louisiana 296,482 Petroleum

Comal County, TX 288,926 Nonmetallic Minerals

Burnet County, TX 253,958 Nonmetallic Minerals

Jefferson County, TX 247,583 Petroleum

Dallas County, TX 212,168 Secondary and Misc. McLennan County, TX 199,385 Nonmetallic Minerals

Source: SAMV4

Table 32: Top Outbound Trading Partners

Trading Partner

2015 Cargo Tonnage

Harris County, TX 3,294,720

Top Commodity Traded

Nonmetallic Minerals

Travis County, TX 1,037,020 Nonmetallic Minerals

Dallas County, TX 776,568 Nonmetallic Minerals

Bexar County, TX 656,526 Nonmetallic Minerals

Tarrant County, TX 545,330 Nonmetallic Minerals

Williamson County, TX 416,058 Nonmetallic Minerals

Fort Bend County, TX 320,615 Nonmetallic Minerals

Montgomery County, TX 257,523 Nonmetallic Minerals

Collin County, TX 244,390 Nonmetallic Minerals Louisiana 224,327 Nonmetallic Minerals

Source: SAMV4

Figure 76 and Figure 77 and show the level of outbound and inbound tonnage for the Temple area across North America. Outside of Texas, Oklahoma, Louisiana, Kansas, Arkansas, and Illinois are the top trading partners for cargo inbound to Bell County. Bell County outbound cargo that travels beyond Texas is mainly destined to Oklahoma, Louisiana, California.

City of Temple Mobility Master Plan

Figure

76: Bell County Outbound Tonnage

Figure 77: Bell County Inbound Tonnage

Source: SAMV4

City of Temple Mobility Master Plan

Figure 78 and Figure 79 show the level of Inbound and Outbound tonnage of the Temple region across Texas. Within Texas, Harris, Williamson, Bexar, and Comal Counties are the top contributors to the inbound cargo to Bell County,. Bell County outbound cargo is mainly destined to Harris, Bexar, Travis, Dallas, and Tarrant Counties

Figure 78: Bell County Outbound Tonnage within Texas

Source: SAMV4

Figure 79: Bell County Inbound Tonnage within Texas

Source: SAMV4

City of Temple Mobility Master Plan

Infrastructure Asset Evaluation

Roadway network is critical to the movement of people and goods through various modes of transportation, within, from to, and through the Temple. The following section includes a review of bridge condition and pavement condition, including condition of sidewalks and bike facilities, where available; and provides an analysis of the City transportation system ‘state of good repair’. This analysis will provide discussion of and insight into the plans eventual recommendations on asset management policies, best practices, and regulatory requirements.

It is important to create an inventory of the region’s bridge and roadway conditions to promote the safe and efficient movement of people and goods throughout Temple. This allows regional and local decision makers to understand which facilities are in a state of good repair, which are in fair condition and require oversight, and which are in poor condition and must be prioritized for improvement. Having assets in poor condition has many potential negative impacts to network users (i.e., personal automobiles, transit vehicles, and freight). Poor conditions along roadways can cause wear and tear to vehicles; delays due to drivers having to maneuver around poor conditions or using unordinary routes due to conditions; and can also impact the attractiveness of local businesses as individuals and freight operators may have to avoid facilities with deficient accessibility. To create a robust inventory of existing network conditions, this analysis includes an evaluation of bridge and roadway pavement conditions.

Locations where rail freight is currently or can be delivered/offloaded are displayed in Figure 80

Figure 80: Existing Rail Freight Offload Sites

City of Temple Mobility Master Plan

Bridge Conditions

The bridge conditions analysis was based on the most up to date version of the Federal Highway Administration’s (FHWA) National Bridge Index (NBI). The NBI included location and condition information for 220 bridges within the Temple study area as of August 2021. It must be noted that bridges identified were limited to the NBI dataset, and some locally owned deficient bridges may not have been reported. The project team followed guidance provided in FHWA’s Computation Procedure for the Bridge Condition Measures and the Code of Federal Regulations (23 C.F.R 490.409) to determine the condition of each bridge asset.

The methodology for determining bridge condition included the calculation of a minimum component condition rating and application of the following scale based on this rating:

• Poor: minimum condition rating between 0 and 4 (indicates a bridge is structurally deficient)

• Fair: minimum condition rating between 5 and 6

• Good: minimum condition rating between 7 and 9

Out of the 220 bridges considered for the analysis, 95 were identified as fair, 120 as Good, and 5 poor Table 33 shows the breakdown of bridge condition for bridges in the Temple MMP study area, while Table 34 provides the status of bridges along the National Highway System (NHS). The location of bridges in the study area and their condition status can be viewed in Figure 81

Table 33: Status of System within Study Area

Structural Status Count

% of System

Bridges in Good Condition 120 54.55%

Bridges in Fair Condition 95 43.18% Bridges in Poor Condition 5 2.27%

Total 220 100.00%

Source: FHWA NBI

Table 34: Status of System Within Study Area Within NHS Network Condition

% of NHS Bridges by Condition*

Good Condition 46.09% Fair Condition 13.88% Poor Condition 0.72% *Percentages based on deck area

Source: FHWA NBI

City of Temple Mobility Master Plan

The five bridges identified as having conditions qualifying as poor are identified in the following locations:

• I 35 near Pepper Creak, 1.35 miles northeast of FM 93

• FM 817 near Riverside Trail 2.1 miles northeast of FM 93

• US 190 at the UP Railroad crossing

• I 35 (Both northbound and southbound lanes) at the BNSF crossing 1.98 miles north of SH 53 (Visual inspection through street view indicates that this location has been addressed through new construction since the latest NBI dataset was published.)

Pavement Conditions

The City of Temple recently completed the 2020 Pavement Management Report that reported on the overall roadway conditions for the roadways in the City. As highlighted in the report, the City maintains approximately 448 miles of paved roadways that requires a significant amount of investment to maintain, preserve, and extend the life of these roadways. The study used a Pavement Management System analysis to perform a quantitative performance score called the Pavement Condition Index (PCI) that represents the surface condition of the pavement on a scale of 0 to 100:

• PCI of 100 is a pavement in perfect condition

• PCI of 0 is a pavement that is failed

City of Temple Mobility Master Plan

Figure 81: Bridge Condition Map; All Bridges

Source: FHWA NBI

Figure

Figure

City of Temple Mobility Master Plan

Table 36: Functional Class Breakdown

Functional Class No. of Sections No. of Miles No. of Square Miles % by No. of Square Yards Weighted Average PCI

Arterial B 1,088 71.98 1,013,491 16.3% 79

Collector C 933 61.45 865,185 13.9% 70

Local E 5,034 308.99 4,350,537 69.8% 75

Total 7,055 442.42 6,229,213 100.0% 75

Source: 2020 Pavement Management Report

Through the Pavement Management Report, asphalt pavement budget scenarios were developed for arterials, collectors, and local roads. The scenarios provide a Pavement Condition Index (PCI) snapshot of the degradation of the roadways up to the year 2025. Additional information on financial impacts associated with pavement preservation can be found in the Report.

Additional Roadway pavement condition analysis for the Temple MMP study area was completed based on 2016 report data from FHWA’s Highway Performance Monitoring System (HPMS). HPMS data provided a condition rating based on the International Roughness Index (IRI) for roadways in the Temple MMP study area. This includes roadway segments found on the National Highway System (NHS), as well as various other roadways critical to the movement of people and goods in the study area. Based on guidance from the Code of Federal Regulations (23 C.F.R. 490.313), each roadway segment was categorized by condition according to the following IRI rating scale:

• Poor Condition: IRI > 170

• Fair Condition: IRI >= 95 and <= 170

• Good Condition: IRI <95

Figure 83 provides an overview of the IRI in the study area.

City of Temple Mobility Master Plan

Airport

Existing Conditions

The Draughon Miller Central Texas Regional Airport (TPL) is located in the northwest corner of the City of Temple, near the interchange of TX 36 and TX 317. Access to the airport is solely from Airport Rd/TX 36. Historically a US Army Air Forces Airfield, TPL now services general aviation and corporate aircraft operators. Its role is to connect Temple to regional and national markets to support the local economy. “The total operations breakdown includes 79.0 percent itinerant general aviation (GA); 14.1 percent military; and 6.9 percent local GA.” 18 In addition to the runway, and multiple hangers, landside facilities at the airport include the terminal building and paved parking lots.

Future Plans

The Airport Master Plan for TPL was developed in 2015, with short , intermediate and long term planning extending to 2026. The recommended Master Plan Concept from the Airport Master Plan is shown in Figure

Source: Author, “Airport Master Plan”, DATE, Page 17, LINK

City of Temple Mobility Master Plan

Figure 83: HPMS IRI Ratings Map

Source: HPMS

84. The plan focuses on recommended improvement on the actual site of the airport, including the design/construction of a Helicopter approach strip, hangers, and taxiways. Future connections and emerging technologies that would interface with the airport were not discussed in this plan. Connections regarding the following will be assessed during the recommendations phase of this study:

• General access

• Autonomous vehicles

• Transit

• Drones/helicopters

City of Temple Mobility Master Plan

Figure 84: TPL Airport Master Plan Master Plan Concept

Source: City of Temple Airport Master Plan

NEXT STEPS

The observations of the comprehensive system assessment and key findings will inform the next phase of the plan which uses a scenario analysis process to examine, test, and compare outcomes to the vision, goals and objectives developed with City staff, leadership, stakeholders, and the participating public. This information will then be used to develop recommendations for the Temple MMP.

City of Temple Mobility Master Plan