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.

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

Methods

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

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.

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

Existing Conditions Analysis Results

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.