2035 mvp appendix a 2007 model validation report by PolkTPO

Polk 2035 Mobility Vision Plan Appendices Prepared for:

Polk Transportation Planning Organization 330 West Church Street, Bartow, Florida 863-534-6486 / www.polktpo.com www.2035mobilityvisionplan.org

Prepared by:

URS Corporation 7650 W. Courtney Campbell Causeway, Tampa, Florida 813-286-1711 / www.urscorp.com Renaissance Planning Group 400 North Ashley Drive, Suite 1010, Tampa, FL 813-254-7741 / www.citiesthatwork.com Gannett Fleming, Inc. Westlake Corporate Center, 9119 Corporate Lake Drive, Suite 150, Tampa, FL 813-831-8870 / www.gannettfleming.com

Adopted December 7, 2010

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APPENDIX A 2007 Model Validation Report

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DRAFT REPORT Polk County 2007 Model Validation Report

Prepared for

Florida Department of Transportation – District 1 and

Polk County Transportation Planning Organization July 1, 2009 Prepared by

Financial ID No. 202075 1 12 03 Contract No. C8Q60 Work Authorization No. 1

Table of Contents Table of Contents ....................................................................................................................................................................... i 1. Introduction ..................................................................................................................................................................... 1 2. The Modeling Process..................................................................................................................................................... 4 The Application Manager ............................................................................................................................................... 4 The Scenairo Manager ..................................................................................................................................................... 6 3. The Model Network ........................................................................................................................................................ Traffic Count Data ........................................................................................................................................................... Screen Lines, Cut Lines, and Cordon Lines .................................................................................................................. Corridor Reports .............................................................................................................................................................. External Station Trips ....................................................................................................................................................... Through Trips ................................................................................................................................................................... Turn Prohibitors and Turn Penaltys .............................................................................................................................. Toll Links............................................................................................................................................................................ Transit Routes ...................................................................................................................................................................

6 20 21 22 23 26 27 27 28

4. The Trip Generation Model .......................................................................................................................................... Trip Rates .......................................................................................................................................................................... Socioeconomic Data ......................................................................................................................................................... Special Generators ............................................................................................................................................................ Person Trips / Household ..............................................................................................................................................

30 31 33 35 38

5. The Trip Distribution Process ...................................................................................................................................... Terminal Times.................................................................................................................................................................. Average Trip Length by Purpose .................................................................................................................................. Friction Factors .................................................................................................................................................................

40 40 41 43

6. The Transit Prep Process ............................................................................................................................................... 45 7. The Mode Choice Model ............................................................................................................................................... 49 “Tier A” Constants and Coefficients .............................................................................................................................. 51 The HBW Nest Flowcharts .............................................................................................................................................. 53 The HBNW Nest Flowcharts ........................................................................................................................................... 54 The NHB Nest Flowcharts ............................................................................................................................................... 55 Summary Reports ............................................................................................................................................................. 56 8. The Transit Assignment Process................................................................................................................................... 61 Estimate of Ridership ...................................................................................................................................................... 62 The Highway Assignment Process...................................................................................................................................... 63 10. The Post Processor ........................................................................................................................................................... 10.1 Screenline Performance ........................................................................................................................................... 10.2 Assignment Accuracy............................................................................................................................................... 10.3 The RMSE Report .....................................................................................................................................................

64 65 65 66

11. Future Model Updates ................................................................................................................................................... 69

III

1 Introduction The 2007 Model Validation is being conducted for the Florida Department of Transportation (FDOT) in cooperation with the Polk County Transportation Planning Organization (TPO). This report “TM-1: The Polk County Model Validation for 2007” provides an overview of the base year model structure and provides a summary of the data used within the model for the validation year. A companion report “TM-2 Technical Resource Guide for the 2007 model ” provides the model user with detailed instructions as to how to run the model, reviews model parameters, and describes what data is commonly changed by the user and where these data are located. The validation of the Polk County Base Year 2007 network was carried out within the CUBE/Voyager transportation planning environment developed by Citilabs Corp. As this is the first use of the CUBE/Voyager model within FDOT District One, the following historical perspective is offered:

FDOT District One

In the early 1980’s the series of Urban Transportation Planning Programs previously run on large ‘main-frame’ computers were converted to run on microcomputers using software such as: TRANPLAN, Micro-Trips, and Trips, etc. At this time the Florida DOT adopted a standardized model structure, called the “Florida Standard Urban Transportation Model Structure” -- or FSUTMS -- using TRANPLAN software. This served Florida well, into the early 1990s. In the last 10 years, however, changes in the level of analysis required of Florida’s travel demand forecast models and increasing federal regulations on travel forecasts have highlighted some issues with existing models. Additionally, Federal Transit Administration (FTA) oversight of forecasts related to the New Starts program over the past five years has provided a number of insights to “state of the practice” concepts for models. Indeed, it was found that many ideas initially considered good practice, in fact, have many bad or undesirable properties during forecasting. In response to these and other issues, in 2005, the FDOT and the Model Task Force agreed to adopt a new modeling system for FSUTMS. The platform chosen for this was CUBE/Voyager. This modeling system is designed to use an open script format (instead of FORTRAN code) and is being developed with Federal Transit Administration (FTA) model requirements in mind. 1

Since FTA requirements for New Starts/Small Starts is essentially an “investment grade” level-of-analysis, the FTA has extremely high review criteria (compared to highway modeling) to validate the project benefits and evaluate whether those benefits are sufficiently cost-effective. Indeed, looking toward the future, and based upon what is expected of future planning models, FDOT District One has decreed that all CUBE/Voyager models within The District will implement the “Tier A Transit” methodology. Back in 2006, the year 2000 “highway-only” TRANPLAN/FSUTMS models used in FDOT District One were converted into a CUBE model using script developed Sung-Ryong Han at Citilabs. The model (which we refer to as: 'Version 1') used a combination of CUBE/Voyager script and DOS/FORTRAN programs. In 2007, at the request of Jim Baxter (Senior Technical Analysis Coordinator at District One) changes were made to the model to incorporate a revised TOLL script and to incorporate HEVAL script written by Wongqiang Wu of FDOT Central Office. These models (which we refer to as: 'Version 2”) were believed to be the first 100% CUBE/Voyager script models in Florida. The Development of a CUBE-Voyager Transit Model, for FDOT Central Office, was begun by AECOM and DMJM Harris in 2007. This effort led to the development of “Tier B/C Transit” and "Tier A Transit" scripts scaled to large and small transit operations. The first scripts became available 10/2008 and were incorporated into the CUBE model for District One by Dan Macmurphy at Traf-OData Corp. Although these models were written in CUBE script, some DOS/FORTRAN programs (for AUTOCON, MODE and HEVAL) were retained from earlier models. Unfortunately, the model procedures also contained a number of problematic WINDOWS-DOS commands for copying and/or combining files. We refer to these models as “Version 3” 'Version 4 models retain DOS/FORTRAN programs for AUTOCON and MODE. But HEVAL reporting has been converted to CUBE/Voyager script and contains a number of new report features.

The Polk YR2007 Model’s CUBE application manager is shown below. The model shown, consists of a highway network with 8,195 roadway links (2,487 centerline miles) and 656 Traffic Analysis Zones serving a population of 558,990 with an employment base of 244,382. Transit services within the model are provided via 31 routes operated by The LAMTD, WHAT, and Polk County Transit.

2 The Modeling Process In the traditional travel demand forecasting process, forecasts of urban activity and descriptions of transportation networks are the primary inputs to a sequential demand model that normally consists of the following four stages: generation, distribution, mode choice, and assignment. As we progress from the TRANPLAN modeling environment into the CUBE/Voyager modeling environment a number of changes must occur within the standard procedures, program modules, datasets and definitions we use in travel demand forecasting. The model process uses long-used, standard, algorithms in conjunction with local factors (such as number of residential dwelling units, the size of employment work sites, and schools) to determine future travel demand. The predicted future traffic identifies roadway capacity deficiencies and the effectiveness of improvement strategies. Formerly, in TRANPLAN -- a command line oriented program structure would activate a number of batch file processes and procedures, which in turn, call a number of programs to run. The programs in the TRANPLAN package were are well documented, but lacked a graphical user interface. Additionally, most add-on programs (such as Trip Generation, Mode Choice and Highway Evaluation were not well documented. To understand how the model worked you needed to know the DOS batch file job control language, the TRANPLAN job control language and command structure, and you also had to know FORTRAN code. In CUBE/Voyager, a Windows based program – the model is run via a graphical user interface (GUI) whereby a mouse-click or a function key, when selected, would activate a “pop up” window or menu from which the user will choose options to run the model. All programs are part of the CUBE and are well documented. To understand how the model works you need to be able to understand the built-in application flowchart and the CUBE/Voyager job control language and command structure. All models utilize the application manager, CUBE scripts and built-in programs. The Polk TPO CUBE/Voyager model for 2007 is contained in a “catalogue file” called POLK. CAT. Upon opening this file, the user is presented with a “model window”, showing the Application Manager and the Scenario Manager that includes all of the highway and transit procedures required by the model. THE APPLICATION MANAGER The Application Manager, shown below, provides a flowchart of each step in the overall model application: From this interface the user may edit input files, view the model network, initiate a model run or view model output. . 4

New to the model process (at least for FDOT District One) is the inclusion of what is called the â&#x20AC;&#x153;Tier Aâ&#x20AC;? Transit methodology. These procedures are to be used for areas where transit is provided almost exclusively by line-haul bus routes running fixed scheduled service during the weekday. 5

THE SCENAIRO MANAGER A model “run” is initiated by activation of the Scenario Manager, as shown below:

Next, both “Model Users” and “Model Developers” are presented with the same series of menu screens. Menu screens 1 & 2 contain variables customarily changed by the model user, Menu screens 3 & 4 contain variables customarily changed only by model developers. Note the check boxes, so that the user only has to run the module(s) required. This is very helpful in reducing running time for select-link analysis (HASSIGN only) or select-corridor reporting (HEVAL only) are required, after the initial model run. Menu Screen 1

Menu Screen 2

(at this point the user will typically selects â&#x20AC;&#x153;runâ&#x20AC;? to begin the model process)

Menu Screen 3

Menu Screen 4

Upon beginning a model run, the user is presented with a Task Monitor, with a progress bar.

When complete, the user may choose any of the report boxes shown in the application manager. 11

One such report, RUN SUMMARY, from the Post Process step in the model, gives a report on the Highway Assignment: DATE: GEN: NET: DISTRIB: TPREP: MODE: TASSIGN: HASSIGN: HEVAL:

Wed 10/07/2009 12:23:09.48 12:23:11.11 12:23:25.29 12:24:11.73 12:29:47.71 12:33:10.32 12:33:51.51 12:36:58.00

C:\FSUTMS\D1\Polk.F\YR2007 ************************* VOLUME AND COUNT SUMMARY BY SCREENLINE *********************** Summary for SL= 1 VOL= 52,339 CNT= 53,451 VOL/CNT= 0.98 N=12 Summary for SL= 2 VOL= 124,515 CNT= 116,146 VOL/CNT= 1.07 N=14 Summary for SL= 3 VOL= 118,729 CNT= 107,961 VOL/CNT= 1.10 N=16 Summary for SL= 4 VOL= 64,742 CNT= 59,476 VOL/CNT= 1.09 N=6 Summary for SL= 5 VOL= 98,648 CNT= 90,927 VOL/CNT= 1.08 N=12 Summary for SL= 6 VOL= 175,719 CNT= 178,114 VOL/CNT= 0.99 N=20 Summary for SL= 7 VOL= 49,003 CNT= 47,550 VOL/CNT= 1.03 N=10 Summary for SL= 8 VOL= 149,441 CNT= 121,994 VOL/CNT= 1.22 N=16 Summary for SL= 9 VOL= 168,740 CNT= 156,884 VOL/CNT= 1.08 N=16 Summary for SL= 11 VOL= 199,580 CNT= 183,957 VOL/CNT= 1.08 N=16 Summary for SL= 13 VOL= 123,278 CNT= 111,246 VOL/CNT= 1.11 N=18 Summary for SL= 14 VOL= 83,157 CNT= 92,013 VOL/CNT= 0.90 N=14 Summary for SL= 15 VOL= 158,083 CNT= 172,116 VOL/CNT= 0.92 N=18 Summary for SL= 16 VOL= 121,399 CNT= 133,717 VOL/CNT= 0.91 N=8 Summary for SL= 17 VOL= 62,761 CNT= 51,278 VOL/CNT= 1.22 N=8 Summary for SL= 18 VOL= 62,442 CNT= 67,388 VOL/CNT= 0.93 N=8 Summary for SL= 19 VOL= 154,685 CNT= 179,007 VOL/CNT= 0.86 N=10 Summary for SL= 27 VOL= 471,042 CNT= 441,121 VOL/CNT= 1.07 N=22 Summary for SL= 37 VOL= 262,366 CNT= 313,794 VOL/CNT= 0.84 N=22 Summary for SL= 40 VOL= 815,152 CNT= 857,977 VOL/CNT= 0.95 N=20 Summary for SL= 57 VOL= 311,871 CNT= 289,512 VOL/CNT= 1.08 N=25 Summary for SL= 60 VOL= 176,461 CNT= 189,567 VOL/CNT= 0.93 N=18 Summary for SL= 71 VOL= 153,135 CNT= 144,024 VOL/CNT= 1.06 N=10 Summary for SL= 98 VOL= 209,784 CNT= 230,402 VOL/CNT= 0.91 N=12 Summary for SL= 99 VOL= 459,000 CNT= 472,090 VOL/CNT= 0.97 N=46 _________________________________________________________________________________________ Total VOL= 9,520,297 CNT= 9,789,138 VOL/CNT= 0.97 N=1,085

**************************** ROOT MEAN SQUARE ERROR SUMMARY ***************************** Percent RMSE for Volume Group 1 1- 5,000: 44.4% (<55.00% acceptable) N=348 Percent RMSE for Volume Group 2 5,000- 10,000: 33.9% (<45.00% acceptable) N=407 Percent RMSE for Volume Group 3 10,000- 20,000: 24.0% (<35.00% acceptable) N=240 Percent RMSE for Volume Group 4 20,000- 30,000: 18.7% (<27.00% acceptable) N=64 Percent RMSE for Volume Group 5 30,000- 40,000: 8.8% (<24.00% acceptable) N=10 Percent RMSE for Volume Group 6 40,000- 50,000: 7.4% (<22.00% acceptable) N=10 Percent RMSE for Volume Group 7 50,000- 60,000: 7.3% (<20.00% acceptable) N=2 12

Percent RMSE for Volume Group 8 60,000- 70,000: 4.6% (<18.00% acceptable) N=4 _______________________________________________________________________________________ Total 1-500,000: 28.1% (<39.00% acceptable) N=1,085

********************** VOLUME AND COUNT SUMMARY BY FACILITY TYPE *********************** Facility Type Summary for FT= 12 VOL= 1,036,805 CNT= 1,087,764 VOL/CNT= 0.95 N=24 Facility Type Summary for FT= 16 VOL= 169,540 CNT= 155,357 VOL/CNT= 1.09 N=8 Facility Type Summary for FT= 21 VOL= 826,552 CNT= 765,343 VOL/CNT= 1.08 N=64 Facility Type Summary for FT= 22 VOL= 308,941 CNT= 285,830 VOL/CNT= 1.08 N=26 Facility Type Summary for FT= 23 VOL= 1,004,974 CNT= 1,062,160 VOL/CNT= 0.95 N=86 Facility Type Summary for FT= 24 VOL= 1,277,158 CNT= 1,332,030 VOL/CNT= 0.96 N=85 Facility Type Summary for FT= 25 VOL= 1,021,433 CNT= 1,121,448 VOL/CNT= 0.91 N=73 Facility Type Summary for FT= 31 VOL= 100,174 CNT= 75,679 VOL/CNT= 1.32 N=12 Facility Type Summary for FT= 32 VOL= 271,685 CNT= 278,760 VOL/CNT= 0.97 N=40 Facility Type Summary for FT= 33 VOL= 113,879 CNT= 140,100 VOL/CNT= 0.81 N=18 Facility Type Summary for FT= 34 VOL= 22,152 CNT= 19,783 VOL/CNT= 1.12 N=2 Facility Type Summary for FT= 35 VOL= 389,923 CNT= 371,322 VOL/CNT= 1.05 N=76 Facility Type Summary for FT= 36 VOL= 96,957 CNT= 94,565 VOL/CNT= 1.03 N=22 Facility Type Summary for FT= 37 VOL= 18,241 CNT= 21,904 VOL/CNT= 0.83 N=2 Facility Type Summary for FT= 41 VOL= 202,463 CNT= 262,343 VOL/CNT= 0.77 N=28 Facility Type Summary for FT= 42 VOL= 1,112,516 CNT= 1,072,710 VOL/CNT= 1.04 N=182 Facility Type Summary for FT= 43 VOL= 801,302 CNT= 863,016 VOL/CNT= 0.93 N=166 Facility Type Summary for FT= 44 VOL= 20,768 CNT= 20,373 VOL/CNT= 1.02 N=10 Facility Type Summary for FT= 45 VOL= 152,887 CNT= 172,256 VOL/CNT= 0.89 N=38 Facility Type Summary for FT= 46 VOL= 173,388 CNT= 215,569 VOL/CNT= 0.80 N=84 Facility Type Summary for FT= 47 VOL= 31,778 CNT= 34,477 VOL/CNT= 0.92 N=8 Facility Type Summary for FT= 62 VOL= 42,406 CNT= 29,675 VOL/CNT= 1.43 N=4 Facility Type Summary for FT= 64 VOL= 4,723 CNT= 6,075 VOL/CNT= 0.78 N=1 Facility Type Summary for FT= 65 VOL= 7,781 CNT= 11,087 VOL/CNT= 0.70 N=1 Facility Type Summary for FT= 92 VOL= 33,063 CNT= 30,218 VOL/CNT= 1.09 N=3 Facility Type Summary for FT= 93 VOL= 240,976 CNT= 225,272 VOL/CNT= 1.07 N=19 Facility Type Summary for FT= 99 VOL= 37,832 CNT= 34,022 VOL/CNT= 1.11 N=3 _________________________________________________________________________________________ Total VOL= 9,520,297 CNT= 9,789,138 VOL/CNT= 0.97 N=1,085

************************* VOLUME AND COUNT SUMMARY BY AREA TYPE ************************ Area Type Summary for AT= 12 VOL= 90,195 CNT= 94,000 VOL/CNT= 0.96 N=11 Area Type Summary for AT= 13 VOL= 140,472 CNT= 105,545 VOL/CNT= 1.33 N=14 Area Type Summary for AT= 14 VOL= 23,364 CNT= 17,425 VOL/CNT= 1.34 N=2 Area Type Summary for AT= 21 VOL= 250,422 CNT= 235,644 VOL/CNT= 1.06 N=24 Area Type Summary for AT= 31 VOL= 5,591,877 CNT= 5,721,803 VOL/CNT= 0.98 N=707 Area Type Summary for AT= 32 VOL= 336,183 CNT= 335,954 VOL/CNT= 1.00 N=21 Area Type Summary for AT= 33 VOL= 705,707 CNT= 676,604 VOL/CNT= 1.04 N=66 Area Type Summary for AT= 42 VOL= 2,209,742 CNT= 2,417,233 VOL/CNT= 0.91 N=186 Area Type Summary for AT= 51 VOL= 13,118 CNT= 13,061 VOL/CNT= 1.00 N=4 Area Type Summary for AT= 52 VOL= 159,216 CNT= 171,869 VOL/CNT= 0.93 N=50 _________________________________________________________________________________________ Total VOL= 9,520,297 CNT= 9,789,138 VOL/CNT= 0.97 N=1,085 ******************************************************************************************************************************** 13

* * * Overall Summary * * * ******************************************************************************************************************************** Total Number of Links: Total Centerline Miles: Total Lane Miles: Total Directional Miles: Total VMT using Volumes: Total VMT using Counts: Total VMT Volume over Counts: Total VHT using Volumes: Total VHT using Counts: Total VHT Volume over Counts: Total Volumes All Links: Total VMT All Links: Total VHT All Links: Original Speed (MPH): Congested Speed (MPH): __________________________

8,126 2,612.69 3,425.07 2,653.26 4,497,932 4,605,283 0.98 139,557 139,716 1.00 52,885,343 16,966,220 547,393 35.66 33.66

(Links (Links (Links (Links (Links (Links

With With With With With With

Counts) Counts) Counts) Counts) Counts) Counts)

YR2007 Cube/Voyager model estimates for transit travel, compared to reported transit ridership, are shown on the following page.

ESTIMATE OF AVERAGE WEEKDAY RIDERSHP BY ROUTE 2007 Daily 2009 Ridership CUBE/Voyager Estimate from Ridership PAX/HR PolkTPO.A Model

2007 Daily 2009 Ridership CUBE/Voyager Estimate from Ridership PAX/HR PolkTPO.A Model

LAMTD

WHAT

Shuttle

117

267

Northside

232

E. Main/Combee

256

231

Lakeland/WinterHaven

269

130

Lakeland/WinterHaven

247

130

Haines City

101

Grove Park/Crystal Lake

296

139

PCC/Hospital

Edgewod

106

298

22x

Bartow Express to Lakeland

285

157

107

22X

Bartow Express to Winter Haven

170

Eagle Ridge/Winter Haven

305

421

Southside

179

327

Cleveland Heights

S Florida Ave

545

573

Southwest

167

Medulla Loop

Westside

119

137

South

1,599

1,256

Ariana/Beacon

298

Central Ave

220

106

W Memorial

414

551

Kathleen/Providence

190

362

N US98/Duff Rd

599

890

N Florida Ave

513

525

Lakeside Village

197

Kathleen/Mall Hill Rd

170

Kidron/Flightline

Subtotal

4,270

Subtotal

78.6%

Polk County Transit 25

Bartow/Fort Meade

Frostproot to Eagle Ridge Mall

23.8

111

5.6

3.5

5,080

Subtotal

192

119.0%

Total

6,061

6,369 105.1%

In the following sections of the report, we discuss each of the eight steps contained in the CUBE/Voyager model Application Manager for 2007:

3 The Model Network In CUBE a Highway Network consisting of links and nodes depicting roadway characteristics (Area Type, Facility Type, and Directional Lanes) is part of the model’s Application Manager. As with the 2000 TRANPLAN model, The highway network module, written in CUBE script, shown below, also updates the model network with: • • • • • •

Speeds and Capacity from the SPDCAP file. Drive Time, Walk Time and Distances Calculates link directionality (one-way vs. two-way) Updates the Count field. Assigns attributes to Toll Links Builds a free-flow travel time matrix

For the 2007 model validation, data received from District One on Urban and Transitioning areas, was used to update Area Type Codes. Facility Type and Directional Lanes were updated using data from the Polk County TPO and The District concerning: roadway improvements, traffic signal location. Recent aerial photography was also used by Traf-OData staff to supplement these data as well as to check roadway alignment and for the adjustment of centroid links. The following illustrations show characteristics of the model network. 16

2007 NETWORK FACILITY TYPE

2007 NETWORK DIRECTIONAL LANES

2007 NETWORK AREA TYPE

TRAFFIC COUNT DATA The validation of any travel demand model relies upon the existence of extensive base year traffic count data. The volume-to-count ratio (V/c) generated by the model is used to measure the ability of a travel demand highway assignment model to simulate known traffic conditions. Traffic counts are needed for a variety of different roadway categories distributed throughout the study area in order to validate highway assignment performance among screen lines and/or cut lines, facility types, area types, and lane configurations. The FSUTMS standard is for the model to assign trips to the highway network for peak-season weekday average The model network daily traffic (PSWADT). contains 1085 links (red) with count data.

New to CUBE for the 2007 model, count data are retained with the link data in the network. The count source, the count location identifier, the average annual daily traffic (AADT), and the model output conversion factor (MOCF) for each count, collected from various sources, were entered into the network database. The AADT is converted to peak-season weekday average daily traffic (PSWADT) based on the MOCF and the count field is filled in with the appropriate valued depending on the directionality of the link. Traffic count data for the study area came from three sources. 1. The 2007 Florida Traffic Information CD from FDOT. 2. Count data from the Polk TPO were used to supplement for counts located on nonstate roads. 3. The Florida Turnpike Enterprise was also asked to provide counts.

Lastly, there should be an adequate number of counts to cover the entire model network. The Polk County 2007 model network contains 8,126 links with 1,085 counts, (approximately 15%) as illustrated above.

SCREEN LINES, CUT LINES, CORDON LINES Screen Lines, Cut Lines and Cordon Lines are drawn across a model network to measure travel flows, as an aggregate volume-to-count ratio, between sub-areas within the model. Screen lines and/or cut lines typically follow natural features, major transportation facilities, or political boundaries. Cordon Lines are typically used to measure flow into and out of a Central Business District. The starting point for developing screen lines and/or cut lines for the Polk County 2007 model was to review what was already present in the Polk County 2000 model. When a potential location was missing a count, a nearby count location that was a reasonable substitute was used. In addition, an external cordon line was used. Screen line maps for measuring north/south and east/west traffic flow are depicted in the following illustrations: 21

The Polk County 2007 model has, for the first time, a set of screen lines to measure flow along the entire length of a major corridor. These facilities, that may need special attention in the future, and which may be a priority concern to FDOT District One and/or the Polk County TPO are: • US 27, • SR 37, • Interstate 4 Eastbound • Interstate 4-Westbound • The Polk Parkway; • SR 60; • US 17; • US 98 These screen lines give the modeler the ability to graphically portray model volumes and counts based on accuracy guidelines contained in the FSUTMS Task C update. An example of which is shown below: 2007 CORRIDOR REPORTS US 27 CORRIDOR 40,000.00 35,000.00

25,000.00

Volume

20,000.00

-20%

15,000.00

+20%

10,000.00 5,000.00

52 1

0 52 1

52 0 16

52 0

51 2 16

7 51 2

50 5 16

50 5

01 4 16

STATION

6 01 4

01 2 16

01 0 16

01 0

00 9 16

00 9

00 8 16

00 8

00 8 16

5 00 8

00 8

0.00 16

PSWADT

30,000.00

EXTERNAL TRIPS Development of a model requires that volumes be assigned to roadways that exit the model study area at what we call â&#x20AC;&#x153;external stationsâ&#x20AC;?. . There are 26 external zones in the Polk County 2007 model, numbered 630 through 656, as depicted in the illustration to the right. In the table which follows, details as to the source of external station volume, the location, directionality of the link as used in the 2007 model.

EXTERNAL STATION VOLUMES External Station Volume Zone 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656

Name SR 37 SR 674 CR 640 W CR 676 SR 60 W Old Mulberry Rd Medulla Rd Sheppard Rd Rice Rd US 92 W I-4 W Knights Station Rd Deeson Rd US 98 N SR 471 SR 33 US 27 N US 192 Champions Gate Blvd I-4 E W Lake Wilson Rd US 92 NE CR 580 / Cypress Pkwy SR 60 E CR 64 US 27 US 17

Dir S W W W W W W W W W W W W W N N N N E E N E E N S S E

2007 2007 Source ID Description AADT MOCF PSWT FDOT 160136 SR 37 SOUTHWEST OF SR 674/WIMAUMA RD BREWSTER 2,600 0.94 2,766 FDOT 160080 SR 674/WIMAUMA RD, W OF SR 37, BREWSTER 1,700 0.94 1,809 TPO 465 CR 640 (PINECREST ROAD) EAST OF HILLSBOROUGH COUNTY LINE 6,623 0.92 7,219 TPO 192 CR 676 (NICHOLS ROAD) EAST OF HILLSBOROUGH COUNTY LINE 1,074 0.92 1,171 FDOT 105508 SR 60, WEST OF POLK COUNTY LINE 19,100 0.92 20,761 TOD 3,928 TOD 543 TOD 13,000 TOD 5,000 FDOT 10564 9,700 0.92 10,543 FDOT 100084 SR 400/I-4, EAST OF PARK ROAD EXCHANGE 116,000 0.94 123,404 TPO 162 CR 582 (KNIGHTS STATION RD) EAST OF HILLSBOROUGH COUNTY LINE 4,714 0.92 5,138 TPO 481 DEESON RD W/O TILLMAN RD 1,748 0.92 1,905 FDOT 161003 SR 35/700/US 98 NW OF SR 471 N OF LAKELAND 8,100 0.92 8,804 FDOT 160134 SR 471 NORTH OF SR 35/700/US 98, NORTH OF LAKELAND 2,400 0.92 2,609 FDOT 111000 ON SR-33 0.181 MI. S OF C-561 (RV) 7,300 0.92 7,935 FDOT 110310 US-27, 0.78 MI. S OF CR-474 (GREENSWAMP RD.)(RCLP) 37,500 0.91 41,208 FDOT 11210000 44,000 0.92 47,826 TPO 1047 CHAMPIONS GATE ACCESS ROAD (CR 532 EXTENSION) NORTH OF CR 53 14,281 0.92 15,566 FDOT 106111 100,000 0.94 106,383 TPO 258 LAKE WILSON ROAD SOUTH OF OSCEOLA CR 532 8,008 0.92 8,729 FDOT 160125 SR 600/US 17/92, NORTHEAST OF CR 54, LOUGHMAN 8,600 0.92 9,348 TPO 205 CYPRESS PARKWAY WEST OF OSCEOLA COUNTY LINE 8,559 0.92 9,329 FDOT 160019 SR 60, EAST OF CR 630/INDIAN LAKE ESTATES 7,200 0.92 7,826 TPO 172 CR 64 (ARBUCKLE ROAD) NORTH OF HIGHLANDS COUNTY LINE 1,863 0.92 2,031 FDOT 160020 SR 25/US 27 NORTH OF HIGHLANDS/POLK COUNTY LINE 18,600 0.91 20,440 FDOT 160052 SR 35/US 17, 0.2 MI N OF HARDEE/POLK COUNTY LINE 8,500 0.91 9,341

Source: HWYNET_07A.NET

Vehicle trips at external stations may also be divided into two categories: External Productions and/or External Attractions. In the first travel demand forecast models (developed in the 1960’s) the assumption was that the urban area being modeled existed in “space”. That is to say the model was separated from any other urban areas Therefore, all trips at external stations (other than EE trips) were assumed to be trips with a destination in the urban core. As urban areas grew closer, and transportation facilities improved, more and more of the trips at external stations were actually vehicles leaving the model, attracted to employment opportunities outside of the model study area. These trips are referred to as “external attractions”. In Polk County, for 2007, this is particularly true for trips in NE Polk destined to Disney World and other large employment centers in neighboring Osceola County. To that end, the external trip table has been modified to allow for productions and attractions, as indicated in the following table:

External Station Volume Zone 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656

Source: HWYNET_07A.NET

Through Trips Dir S W W W W W W W W W W W W W N N N N E E N E E N S S E

2007 PSWT 2,766 1,809 7,219 1,171 20,761 3,928 543 13,000 5,000 10,543 123,404 5,138 1,905 8,804 2,609 7,935 41,208 47,826 15,566 106,383 8,729 9,348 9,329 7,826 2,031 20,440 9,341

Zone 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656

From

2,301

Total

4,602

22,222 22,222 44,444

250 250

500 500

12,193 12,193 24,386 12,500 12,500 25,000 26,222 26,222 52,444

2301

4,602

3093

6,186

EETABLE_07A.MAT

Calculation by Percent A or P ie Zone Trips Prods Attrs Prods % Attrs % 630 2,766 2,766 100% 0% 631 1,809 1,809 100% 0% 632 7,219 7,219 100% 0% 633 1,171 1,171 100% 0% 634 16,159 9,675 12,000 60% 40% 635 3,928 3,928 100% 0% 636 543 543 100% 0% 637 13,000 13,000 100% 0% 638 5,000 5,000 100% 0% 639 10,543 10,543 100% 0% 640 78,960 51,054 45,000 65% 35% 641 5,138 5,138 100% 0% 642 1,905 1,905 100% 0% 643 8,304 8,304 100% 0% 644 2,109 2,109 100% 0% 645 7,935 4,818 6,000 61% 39% 646 16,822 1,500 25,000 9% 91% 647 22,826 1,500 35,000 7% 93% 648 15,566 1,000 20,000 6% 94% 649 53,939 23,381 57,800 43% 57% 650 8,729 1,000 12,000 11% 89% 651 9,348 1,000 14,000 11% 89% 652 9,329 6,189 5,000 66% 34% 653 3,224 2,156 2,200 67% 33% 654 2,031 2,031 100% 0% 655 14,254 9,723 7,800 68% 32% 656 9,341 9,341 100% 0% INTEXT_07A.DBF SPECGEN_07A.DBF

THROUGH TRIPS

SR 37

SR 674

CR 640 W

CR 672

SR 60 W

Old Mulberry Rd

Medulla Rd

Sheppard Rd

Rice Rd

US 92 W

I-4 W

Knights Station Rd

Deeson Rd

US 98 N

SR 471

SR 33

US 27 N

US 192

Champions Gate Blvd

I-4 E

W Lake Wilson Rd

US 92 NE

CR 580 / Cypress Pkwy

Vehicle trips at external stations may also be divided into two categories: IE or EE. IE trips are those trips that either have an origin or a destination outside of the study area. EE trips travel through the study area. For 2007 we began model validation by applying the same percentage of “through trips” used for the 2000 validation.. As shown on the following illustration, we began model validation with 26,722 through trips in I-4. There were also a significant number of through trips coded on SR 60, US 92 and US 27.

EETRIPS

630

631

632

633

634

635

636

637

638

639

640

641

642

643

644

645

646

647

648

649

650

651

652

SR 37

630

SR 674

631

CR 640 W

632

CR 676

633

SR 60 W

634

Old Mulberry Rd

635

Medulla Rd

636

Sheppard Rd

637

Rice Rd

638

US 92 W

639

I-4 W

640

1,500

Knights Station Rd

641

Deeson Rd

642

US 98 N

643

250

SR 471

644

250

SR 33

645

US 27 N

646

US 192

647

1,500

0 11,000

Champions Gate Blvd

648

I-4 E

649

0 20,722

W Lake Wilson Rd

650

US 92 NE

651

CR 580 / Cypress Pkwy

652

SR 60 E

653

2,301

CR 64

654

US 27

655

US 17

656

Dir

Location

Source: EETABLE_A07.MAT

0 20,722

0 11,000

1,193

1,900

TURN PROHIBITORS AND TURN PENALTY Model networks may contain turn prohibitions to control the flow of vehicles at intersections or time penalties allow for the adjustment of travel times on specific links. A typical use for a turn prohibition would be for coding a right-in, right-out, entrance -- typically found at high activity shopping centers on major roadways. Another use for a time penalty would be to reduce traffic flow along a bridge or similar structure with reduced clearances. Also, new for 2007, intersections along I-4 and the Polk Parkway were “enhanced” as illustrated. This coding resulted in the coding of fewer turn prohibitions. The model’s TURN_07A.PEN file contains 24 prohibitions, where movement is not allowed, and only 2 turn penalty’s (to control traffic flow in the NE portion of the County). TOLL LINKS The TOLLLINK_07A.DBF file contains toll price and service times at each toll plaza. These data are converted into travel time costs during the highway assignment process. The Polk County 2007 model includes 10 toll facilities along the Polk County Parkway, as indicated below: TOLL TOLLTYPE A B PLZADESC 1 1 4585 4586 EB EXT AIRPORT RD 1 1 4385 4384 WB ENT AIRPORT RD 2 1 4287 4288 EB EXT WARING RD 2 1 4450 4451 WB ENT WARING RD 3 1 4114 4115 EB EXT HARDEN BLVD 3 1 4386 4387 WB ENT HARDEN BLVD 4 1 4292 4293 EB EXT S FLORIDA AV 4 1 4394 4395 WB ENT S FLORIDA AV 5 1 4388 4389 WB ML WESTERN BARRIER 5 1 4391 2118 EB ML WESTERN BARRIER 6 1 4308 4294 WB EXT LAKELAND HIGHLANDS 6 1 4392 4393 EB ENT LAKELAND HIGHLANDS 7 1 4404 4405 WB ML CENTRAL BARRIER 7 1 4412 4413 EB ML CENTRAL BARRIER 8 1 4378 4379 EB EXT SR 540 8 1 4382 4383 WB ENT SR 540 9 1 4425 4426 NB ENT CR 546 9 1 4427 4428 SB EXT CR 546 10 1 4446 4447 SB ML EASTERN BARRIER 10 1 4449 4448 NB ML EASTERN BARRIER

PLZALNSMIN PLZALNSMAX CARTOLL SVCMINUTES SVCSECONDS DECELCODE ACCELCODE EXACTCHGLN AVILANES 3 3 0.25 0 5 1 1 1 0 3 3 0.25 0 5 1 1 1 0 2 2 0.50 0 10 1 1 1 0 2 2 0.50 0 10 1 1 1 0 3 3 0.50 0 7 1 1 1 0 3 3 0.50 0 7 1 1 1 0 3 3 0.50 0 7 1 1 1 0 3 3 0.50 0 7 1 1 1 0 4 4 1.00 0 5 1 1 1 0 4 4 1.00 0 5 1 1 1 0 2 2 0.25 0 20 1 1 1 0 2 2 0.25 0 20 1 1 1 0 4 4 1.00 0 10 1 1 1 0 4 4 1.00 0 10 1 1 1 0 4 4 0.50 0 2 1 1 1 0 4 4 0.50 0 2 1 1 1 0 2 2 0.25 0 1 1 1 1 0 2 2 0.25 0 1 1 1 1 0 3 3 1.00 0 1 1 1 1 0 3 3 1.00 0 1 1 1 1 0

The last process undertaken during the NETWORK setup is to provide a matrix of free-flow travel times for subsequent processing during the DISTRIBUTION step. These times are contained in the FREESKIM_A07.MAT file. TRANSIT ROUTES IN THE MODEL NETWORK One of the processes undertaken during the NETWORK process is to link the TROUTE_07A.LIN file to the Highway Network. For 2007, the Polk County model contains a total of 31 line-haul bus-transit routes. Service providers are: The Citrus Connection (LAMTD), The Winter Haven Area Transit (WHAT), and Polk County Transit. Although transit routes are not processed until the Transit Prep Module, the CUBE visual editor enables the user to make highway network and transit network edits simultaneously, providing a form of automated assistance when splitting links, etc. As a general rule, transit routes contained in TROUTE_07A.LIN, a portion of which is shown below, are coded as large loops (outbound then inbound). ;;<<PT>><<LINE>>;; ; Created-11/2008-Traf-O-Data Corp. LINE NAME="LAMTD 10", LONGNAME="LAMTD #10 Shuttle", ONEWAY=T, TIMEFAC=1, CIRCULAR=T, HEADWAY[1]=60, HEADWAY[2]=60, MODE=21, OPERATOR=1, N=2849, 2886, 2909, 2922, 2949, 2968, 2976, 2986, 2983, 2984, 2982, 2981, 2990, 2999, 3008, 4786, 4787, 4788, 4789, 4790, 4835, 4834, 2995, 2938, 2929, 4850, 2864, 2870, 2863, 2816, 4847, 5863, 2690, 2669, 2633, 2635, 2636, 2637, 2692, 2694, 2695, 4823, 2696, 2697, 2710, 2711, 4824, 2730, 2745, 2775, 2777, 4801, 2802, 2801, 2800, 2797, 2799, 2798, 2793, 2820, 2849 LINE NAME="LAMTD 11", LONGNAME="LAMTD #11 Main/Combee", ONEWAY=T, TIMEFAC=1, CIRCULAR=F, HEADWAY[1]=60, HEADWAY[2]=60, MODE=21, OPERATOR=1, N=2849, 2820, 2793, 2798, 2799, 2797, 2800, 2801, 2802, 2824, 2855, 2832, 5769, 5768, 2825, 2819, 4825, 2812, 2822, 5036, 4828, 2874, 2867, 2692, 2637, 2636, 2635, 2633, 2669, 2690, 5863, 2729, 2731, 5850, 4884, 2736, 2737, 2766, 4888, 4887, 5864, 2342, 4901, 2343, 4894, 4895, 2557, 4907, 4917, 4904, 4905, 4916, 5867, 2557, 2591, 4908, 2666, 2767, 2847, 5870, 3065, 5871, 3185, 4900, 3187, 3212, 3216, 3138, 3119, 3061, 3018, 2869, 2806, 2805, 5851, 5854, 5855, 5853, 5852, 5850, 2731, 2729, 5863, 2690, 2693, 2692, 2694, 2695,

For example, when route 10, above, is processed in the network editor, a graphical representation of the route on the highway network is presented to the user, as shown below: 28

4 The Trip Generation Model The trip generation module process estimates the number of trips bound to, or destined from, each Traffic Analysis Zone. The total number of trips produced for a given zone is determined by multiplying the appropriate trip generation rate by the number of occupied dwelling units in each market segment and then summing the market segment totals together. Before an adequate understanding of trip generation can be achieved, the user must be familiar with several key definitions. A trip is composed of two trip ends: a production end and an attraction end. A production is defined as the home end of a home-based trip or the origin of a nonhome-based trip. An attraction is the nonhome end of a home-based trip or the destination of a nonhome-based trip. Trips produced at homes are attracted to areas of employment, education, recreation, shopping and other activities to satisfy the reason for making the trip. Nonhome-based trips have both trip ends at locations other than the traveler’s residence. (An example of a nonhome-based trip is a person traveling from an office to a shopping center.) The desired end product in trip generation analysis is an accurate identification and quantification of trip ends beginning and ending in each traffic analysis zone within a transportation study area. Thus, two sets of trip ends are identified: those produced by each zone and those attracted to each zone. Later in the FSUTMS model chain during the trip distribution module, these trip ends are paired. Each production-attraction pair forms one trip. Trip generation modeling would be easier to grasp if the models were simply required to estimate the total number of trip ends. The Instutute of Transportation Engineers (ITE) Trip Generation manual, for example, provides rates and equations to estimate total trip ends by land use category. Trip generation in a modeling context, however, must estimate the number of trip ends within several trip purpose categories. This complication is necessary because trip purpose is critical to the accurate prediction of travel behavior in steps following trip generation. FSUTMS uses seven trip purposes: • • • • • • •

Home-Based Work (HBW) Home-Based Shop (HBSH) Home-Based Social/Recreational (HBSR) Home-Based Other (HBO) Nonhome-Based (NHB) Truck-Taxi (TT) Internal-External (IE) 30

A trip’s purpose is important in determining trip length during the trip distribution module. For example, people generally do not travel as far on a shopping trip as they would commuting to work. Trip purpose also plays a significant part during the modal choice module. When estimating transit use, the propensity to use public transit and carpools is higher for work trips than for other trip purposes. When converting person-trips to vehicle-trips in the modal choice module, average vehicle occupancies differ by trip purpose. For example, people commonly drive alone to work although they rarely drive alone to the beach or other recreational activities. In the traffic assignment module, trip purpose has been used in some specialized models to help indicate time-of-day travel estimates. Modeling analysis for toll roads and high-occupancy vehicle facilities often focuses on work trips, which predominate during peak hours. Most trip generation models can be categorized into one of three different types:

• Regression analysis which relates trip ends to the land use and socioeconomic characteristics of the traffic analysis zones in the study area. Regression analysis is usually based on data from origindestination surveys which have been aggregated to traffic analysis zones. • Cross-classification which classifies trip ends by characteristics of the households or dwelling units in the study area. Cross-classification uses origin-destination data at the dwelling unit level and is referred to as a disaggregate technique. • Trip rate analysis which relates trip ends to factors such as land use, floor area, or employment. The trip rate method is also a disaggregate technique. The FSUTMS trip generation model does not use the regression approach but instead uses a combination of the other two techniques listed above. The cross-classification technique is used to generate home-based trip productions for the HBW, HBSH, HBSR and HBO trip purposes. TRIP RATES

The rate is determined by a cross-classification of households are based upon combinations of the following: •

Type of dwelling unit - single-family, multi-family or hotel/motel

•

Auto ownership - 0, 1 or 2+ autos per dwelling unit

•

Persons per dwelling unit - 1, 2, 3, 4, or 5+ persons per dwelling unit 31

Classification rates are contained in two tables: DUWEIGHTS.DBF and GRATES.DBF which follow:

Home Based Work Number of Number of Persons in Autos Household 1 2 3 4 5+ Available 0.29 0.59 0.87 1.17 1.46 0 0.30 0.92 1.28 1.53 1.72 1 0.95 1.55 1.91 2.16 2.36 2+

Dwelling Unit Type SingleFamily Multifamily

0 1 2+

Hotel/Motel Units

Dwelling Unit Type SingleFamily

0 1 2+

Hotel/Motel Units Source:

0 1 2+

0.10

0.58

0.85

1.05

1.21

0.34 1.13

0.82 1.62

1.10 1.89

1.30 2.09

1.46 2.25

Multifamily

0.82

0.56

0.39

0.29

Hotel/Motel Units

Home Based Social/Recreational Number of Number of Persons in 1 2 3 4 5+ Autos 0.06 0.11 0.29 0.73 1.81 0 0.34 0.49 0.73 1.06 1.55 1 0.58 0.76 1.00 1.32 1.74 2+

Multifamily

Home Based Shop Number of Number of Persons in Dwelling Autos Household 1 2 3 4 5+ Unit Type Available 0.25 0.48 0.73 0.97 1.21 0 Single0.28 0.82 1.12 1.35 1.52 1 Family 0.28 0.82 1.13 1.36 1.53 2+ 0.36

0.54

0.65

0.73

0.78

0.61 0.39

0.79 0.53

0.90 0.61

0.98 0.67

1.03 0.72

0.27

1.12

1.72

2.15

2.49

Home Based Other Dwelling Number of Number of Persons in 1 2 3 4 5+ Unit Type Autos 0.08 0.49 1.59 3.59 6.77 0 Single0.37 1.18 2.33 3.78 5.51 1 Family 0.28 1.01 2.15 3.66 5.53 2+ 0 1 2+

0.10

0.18

0.30

0.52

0.88

0.43 0.47

0.54 0.60

0.69 0.75

0.89 0.95

1.15 1.19

Multifamily

0.51

1.42

2.32

3.34

5.06

Hotel/Motel Units

0.15

0.78

2.04

4.04

6.83

0.32 0.53

1.15 1.46

2.43 2.62

4.11 3.99

6.19 5.51

0.44

1.03

1.81

2.83

3.77

Average Persons Per One-Person Dwelling Unit Households 0.00-1.12 0.89 1.13-1.37 0.65 1.38-1.62 0.65 1.63-1.87 0.36 1.88-2.12 0.34 2.13-2.37 0.28 2.38-2.62 0.24 2.63-2.87 0.19 2.88-3.12 0.15 3.13-3.37 0.17 3.38-3.62 0.14 3.63-3.87 0.13 3.88-4.12 0.04 4.13-4.37 0.02 4.38-4.62 0.01 4.63-5.99 0.00 0.00 6.00+ * Persons per dwelling unit

Percent of Households Per PPDU* Category Two-Person Three-Person Four-Person Households Households Households 0.11 0.00 0.00 0.25 0.02 0.09 0.25 0.05 0.02 0.53 0.06 0.03 0.45 0.11 0.06 0.42 0.13 0.10 0.39 0.15 0.12 0.34 0.19 0.16 0.32 0.20 0.18 0.26 0.17 0.14 0.27 0.18 0.18 0.23 0.23 0.12 0.16 0.17 0.24 0.15 0.14 0.21 0.15 0.13 0.17 0.05 0.07 0.14 0.00 0.02 0.05

Five-Person + Households 0.00 0.00 0.02 0.02 0.04 0.07 0.09 0.13 0.15 0.25 0.24 0.29 0.39 0.48 0.54 0.74 0.93

Source: C:\FSUTMS\D1\POLK.V4\PARAMETERS\DUWEIGHTS.DBF

C:\FSUTMS\D1\POLK.V4\PARAMETERS\MC_GRATES.DBF

Trip generation also requires trip rates for the remaining three FSUTMS trip purposes: NHB, TT and IE as follows: â&#x20AC;˘

Non-Home Based Trips (Productions and Attractions) = 3.54 * (Commercial Employment) + 1.71 * (Service Employment) +0.37 * (Dwelling Units)

â&#x20AC;˘

Truck/Taxi Trips (Productions and Attractions): Truck Trips = 0.45 * (Total Employment)

The INTEXT_07A.DBF file contains internal-external (IE) trips for each external zone. The FSUTMS trip generation model reads this file as IE trip productions and then estimates the number of IE trip attractions for each internal traffic analysis zone based on the relative number of home-based and nonhome-based attractions in each given TAZ.

After NHB and TT attractions are calculated, FSUTMS sets the number of trip productions in each zone equal to the number of trip attractions for these two purposes. Internal-external productions are typically set to zero for all internal TAZs.1

As with the previous Polk County model (2000 validation) trip attractions were calculated for each zone, as follows: •

Home Based Work (HBW Attractions) =1.8 * (Total Employment) + 0.5 * (Dwelling Units)

•

Home Based Shopping (HBSH Attractions)=6.1 * (Commercial)

•

Home Based Social/Recreational (HBSR Attractions) = 0.5 * (Commercial) + 0.5 * (Service) + 1.61 * (Dwelling Units)

•

Home Based Other (HBO Attractions) = 1.5 * (Commercial) + 1.5 * (Service) + 0.3 * (Dwelling Units) + 1.5 * (School)

These data are contained in the ATTRATES.DBF file within the model, as shown below:

Purpose Home-Based Work Home-Based Shop Home-Based Social/Recreational Home-Based Other Non-Home-Based Truck-Taxi

1 2 3 4 5 6

Employment Industrial Commercial Service 0.00 0.00 0.00 0.00 6.10 0.00 0.00 0.50 0.50 0.00 1.50 1.50 0.00 3.54 1.71 0.00 0.00 0.00

Total 1.80 0.00 0.00 0.00 0.00 0.45

Dwelling School Units Enrollment 0.50 0.00 0.00 0.00 1.61 0.00 0.30 1.50 0.37 0.00 0.30 0.00

Source: C:\FSUTMS\D1\POLK.V4\PARAMETERS\ATTRATES.DBF

The trip generation model also allows the user to correct for non-standard trip making characteristics via a “special generators” file, where rates and distributions among trip purposes for the productions and attractions are entered that over-ride the standard. The Trip Generation Application, written in CUBE script, replaces the FORTRAN code used by earlier versions of the Polk County model.

1 Documentation And Procedural Updates To The Florida Standard Urban Transportation Model Structure,Final technical report No. 3: FSUTMS trip generation model,FDOT Central Office, Systems Planning, June 1997 33

The FSUTMS / CUBE program steps, which are basically is self-explanatory: • • • •

Set up program variables; Run Trip Generation; Creates a matrix of person-trips by trip purpose, and; Includes the External-to-External trip matrix file, for subsequent processing.

The reader is encouraged to refer to the companion document: “TM-2 Polk County Model Technical Guide for 2007” for additional detail. Like most standard FSUTMS models, the Polk County model uses trip rates developed based upon auto availability per household and the number of persons in each household. Trip production rates for home-based work, home-based shop, home-based social/recreation, and home-based other purposes are provided in the table below. Trip rates are based on data collected during the 2000 North Florida Travel Survey.

SOCIOECONOMIC DATA 2007 Socioeconomic Data

Polk County

Single Family Dwelling Units Multi Family Dwelling Units Hotel / Motel Units

195,886 71,238 11,744 278,868

Single Family Dwelling Population Multi Family Dwelling Population Hotel / Motel Population

458,589 113,459 21,456 593,504

Industrial Emp Commercial Emp Service Emp

76,727 53,952 115,272 245,951

School Enrollment

99,389

In FSUTMS / CUBE socioeconomic data with respect to the number of households, population and employment are contained in the ZONEDATA_07A.DBF file. These data, prepared by the Polk County TPO prior to the development of the model were checked for reasonableness by Traf-O-Data’s “SE_CHECK” program. This is a procedure, similar to the old FSUTM / TRANPLAN “LUCHECK” program that looks for common illogical data issues such as: . Zones have SFVNP less than SFV. Percent of zones with SFPOP & SFVNP=0 (>60% unusual) Zones have MFVNP less than MFV. Percent of zones with MFPOP & MFVNP=0 (>60% unusual) Zones have DU's but no SFPOP. Zones have DU's but no MFPOP. Zones have SFPOP but no DU's. Zones have MFPOP but no DU's. Zones have SFPOP/DU's <1. Zones have SFPOP/DU's >8. Zones have MFPOP/DU's <1. Zones have MFPOP/DU's >8. Zones have SFauto not equal to 100. Zones have MFauto not equal to 100. Zones have Hotel units with no population. Zones have hotel population but no hotel units. Zones have hotel units but no occupancy rate. Zones have students but no service employment. Zones have hotel units but no service employment.

A number of adjustments were made to the data to correct for errors encountered during the model validation and for issues identified The changes, which have been approved by the TPO in 2009, corrected an undercount of multi-family dwelling units in mobile home communities The illustration to the right shows the distribution of population in Polk County based on the 2007 database. 35

The following illustration show dwelling units per acre.

The following illustration indicates employment centers.

SPECIAL GENERATOR TABLE A number of adjustments were made to the Polk County 2000 FSUTMS trip generation model during validation. Several special generator adjustments were conducted during validation. This included numerous iterations of adjusting the relationship between attractions and productions at external zones. The rationale for these adjustments was to account for routine home-based and nonhome-based trips generated within Polk County that have a trip attraction outside of the County. A good example of this situation would be residents of Northeast Polk County who may live near Haines City, but work in Orlando or Kissimmee. In the absence of external attractors at these external zones, all home-based work trips produced in these areas would be attracted to zones within the Polk County 2000 model study area, resulting trip volumes significantly in excess of counts on screen lines and/or cut lines. Other adjustments included the addition of special attractors to incorporate trip rates from the University of South Florida/Polk Percent Trips by Purpose ZONE 446 479 516 534 634 640 645 646 647 648 649 650 651 652 653 655

P/A A P A P A + A + A + A + A + A + A + A + A + A + A + A +

Employment

Person Trips HBW HBSH HBSR HBO NHB Total Commercial Service School DU's Description 3,000 25 20 20 5 30 0 0 0 0 0 Lucerene Park adj 10,000 20 20 20 20 30 0 0 0 0 0 RV Resorts adj 5,000 25 20 20 5 30 0 0 0 0 0 Ridgewood Lakes adj 13,000 20 10 10 20 40 0 0 0 0 0 E Loughman adj 12,000 25 20 20 5 30 0 0 0 0 0 SR 60 (W) 45,000 25 20 20 5 30 0 0 0 0 0 I-4 (W) 6,000 25 20 20 5 30 0 0 0 0 0 SR 33 (N) 25,000 15 25 15 10 35 0 0 0 0 0 US 27 (N) 35,000 25 20 20 5 30 0 0 0 0 0 US 192 (E) 20,000 25 20 20 5 30 0 0 0 0 0 Champions Gate (NE) 57,800 25 20 20 5 30 0 0 0 0 0 I-4 (NE) 12,000 25 20 20 5 30 0 0 0 0 0 LakeWilsonRd (NE) 14,000 25 20 20 5 30 0 0 0 0 0 US 17/92 (NE) 5,000 25 20 20 5 30 0 0 0 0 0 CR 580 (E) 2,200 25 20 20 5 30 0 0 0 0 0 SR 60 (E) 7,800 25 20 20 5 30 0 0 0 0 0 US 17/27/92 (S)

Source: C:\FSUTMS\D1\POLK.V4\YR2007\INPUT\SPECGEN.DBF

As detailed in TM-2 Technical Resource Guide for the 2007 model, statistics were continually summarized to assess model validity during the switch from TRANPLAN (FORTRAN) to CUBE (CUBE script) for 2000.

One way to determine the reasonableness of trip generation model is to compare overall trip making rates per household with the pervious Polk County model and to make comparisons with other areas inside and outside Florida:

COMPARISON OF PERSON TRIPS / HOUSEHOLD Polk 2000 Purpose Home-Based Work Home-Based Shop Home-Based Socrec. Home-Based Other Non Home-Based Truck-Taxi Internal-External TOTAL

2000 Productions % by Productions 306,724 16% 191,858 10% 181,741 9% 479,319 25% 24% 477,391 8% 160,005 8% 153,026 1,950,064 100.00%

2007 Productions % by Productions 313,869 15% 206,228 10% 195,443 10% 450,034 22% 24% 484,541 9% 190,809 9% 187,803 2,028,727 100.00%

Person Trips / Household Person Year Trip/HH Region Vancouver, 1985 5.83 SMC 2007 6.20 SMC 2000 7.02 Polk 7.16 2007 Northern NJ 1986 7.75 Austin, TX 7.99 1986 LC 2000 8.07 TBRPM6.1 1999 8.12 Reno, NV 8.58 1987 Dallas-Ft. W 1984 8.68 Polk 2000 8.71 CFRPM 2000 8.89 Phoenix, AZ 1989 8.98 9.05 St. Louis, M 1990 Charlotte, N 1985 9.29 Atlanta, GA 9.81 1991 10.08 Nashua, NH 1990 10.11 Twin Cities, 1990 10.72 Pittsburg, PA 1990 12.20 Puget Sound 1989 San Diego, C 1986 14.30 Sources: (black) FHWA Model Validation & Reasonableness Checking Manual and (blue) FSUTMS Models in Florida.

5 The Trip Distribution Process TRIP DISTRIBUTION relies on a â&#x20AC;&#x153;Gravity Modelâ&#x20AC;? (which parallels Newton's gravitational law) to distribute trips. All trips starting in a TAZ are attracted to all other TAZ, proportional to the number of attractions and inversely proportional to the distance. In travel demand forecast models, the measure of separation is generally accepted as the zone-to-zone travel time via the specified transportation network. However, because people as social beings do not order their lives according to exact physical laws, optional adjustments may be employed to adjust the gravitational concept to fit the travel characteristics of the urban area being studied. The trip productions and attractions by trip purpose are obtained from the Trip Generation module. Travel times are obtained from tables generated by the Highway module. These travel times are then used to look up friction factors, which are locally calibrated values relating travel time. Friction factors control the probability of making a certain length trip, for a certain trip purpose. For instance, going to work is relatively insensitive to how long the trip is while shopping depends much more on travel time in selecting possible destinations. These factors are developed based on observed trip lengths for the local population and come from Census and survey data. Friction factors from the Polk County 2000 model were initially used for 2007. TERMINAL TIMES Terminal times represent the time involved at either end of a trip to travel from an origin to a vehicle or from the vehicle to a final destination. More specifically, this accounts for the time necessary to walk to or from the vehicle used for any given trip. Table 5. 2 lists the terminal times by area type used in the Polk County 2000 model. The purpose of the K-factor file is to adjust the distribution of trips by purpose between either a pair of zones or groups of zones in the urban area. K-factors are also known as socioeconomic adjustment factors because they can be used to decrease or increase the impedance between areas of like or dissimilar characteristics such as income and auto availability. K-factors may also be used to increase the impedance between rural and urban 40

sections of a study area or between multiple urban areas contained in the same model. K-factors are generally used only when trip distribution errors remain after testing a variety of other model adjustment methods. Appropriate situations for K-factors include models with either a significant coverage of rural development or multiple urban areas separated by some distance. K-factors have also been used to prevent illogical distributions of trips to or from lower income areas, but many modelers believe that the use Kfactors in that situation may yield unpredictable and illogical results in future year models, with land use changes. The Trip Distribution module, written in 100% CUBE script, replaces the TRANPLAN program controls used by earlier versions of the Polk County model. The program steps, which are basically is self-explanatory: • Set up program variables; • Run Trip Distribution; • Apply Auto Occupancy Factors to convert person-trips into vehicle-trips; • Assign trips to the network • Builds a congested-flow travel time matrix

AVERAGE TRIP LENGTH BY PURPOSE Calibration of the Trip Distribution step is accomplished via a comparison of average trip lengths generated by the 2007 Polk County model with data from household travel time surveys. Alternatively, data from other Florida models of comparable size are used, as shown in the following table:

Average Trip Length--Previous Models 1990 2000 2007 polk polk polk HBW 21.54 18.59 21.10 HBSH 20.24 18.95 16.40 HBSR 17.82 16.01 15.90 HBO 14.76 15.76 15.00 NHB 15.31 13.77 15.60 TT 14.65 16.00 14.90 IE 49.50 32.33 63.80

HBW HBSH HBSR HBO NHB TT IE

CTPP Travel Time to Work 1990 2000 Manatee Sarasota Charlotte Average

19.3 20.6 19.2 19.70

23.3 25.4 23.6 24.10

Average Trip Length--sorted by Population 2000 2000 2000 2000 2000 2005 2000 polk highlands st. johns lc smc juats cfrpm

2006 cfrpm

2000 tbrpm

21.4 17.0 16.6 17.2 16.1 15.4 41.9

21.8 16.3 13.9 15.9 15.2 15.9 68.1

15.4 14.3 13.6 12.9 11.0 11.9 24.4

17.0 13.9 15.2 13.1 12.7 10.7 29.8

19.0 16.2 15.1 14.6 15.7 15.7 51.4

17.1 14.0 15.1 15.1 13.7 15.6 26.2

21.10 16.40 15.90 15.00 15.60 14.90 63.80

22.1 16.2 16.5 18.4 18.6 15.9 37.0

22.2 21.4 17.2 17.5 16.1 15.7 39.2

99,768 128,066 511,250 532,044 858,783 1,334,613 1,551,023 1,551,023 2,554,238

Average Trip Length--Peer Cities 2000 2000 2000 polk lc smc HBW HBSH HBSR HBO NHB TT IE

19.0 16.2 15.1 14.6 15.7 15.7 51.4

17.1 14.0 15.1 15.1 13.7 15.6 26.2

21.10 16.40 15.90 15.00 15.60 14.90 63.80

Avg 19.1 15.5 15.4 14.9 15.0 15.4 47.1

FRICTION FACTORS Beginning with the friction factors used in the Polk County 2000 model, calibration by trip purpose was undertaken until the desired travel time distribution curves were obtained. (the 2007 factors are shown below). As a check, a comparison was made of HomeBased Work Trip frequency distribution curve between the 2000 model and the 2007 model. The reader is asked to review “TM-2 Technical Resource Guide for the 2007 model” for additional data.

FRICTION FACTORS MINUTE_M HBWFF HBSHFF HBSRFF HBOFF NHBFF TTFF IEFF 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 3 2662 859737 5976 57080 137382 4953 107380 4 2662 859737 5976 57080 137382 4899 96580 5 2632 842568 5900 56165 135035 4846 86865 6 2539 791818 5671 53434 127957 4741 75001 7 2414 725675 5365 49828 118631 3364 62071 8 2292 662906 5065 46344 109694 2571 48083 9 2168 602409 4765 42920 100978 2096 38413 10 1922 488594 4171 36291 84244 1833 29831 11 1676 385383 3587 30003 68586 1622 24474 12 1431 293097 3013 24093 54107 1412 20194 13 1247 231167 2591 19920 44052 1254 16987 14 1066 175956 2178 16007 34785 1096 13784 15 884 127152 1771 12335 26270 991 11651 16 764 98848 1509 10083 21113 886 9521 17 644 73418 1249 7945 16324 781 7394 18 547 55387 1044 6340 12800 677 5271 19 475 43435 894 5213 10359 572 3681 20 404 32887 749 4172 8135 488 2624 21 334 23613 607 3201 6109 415 2096 22 275 16841 489 2439 4557 363 1886 23 240 13279 421 2018 3712 311 1675 24 216 11048 374 1741 3173 285 1517 25 199 9659 344 1564 2817 259 1254 26 181 8159 308 1366 2443 233 1149 27 170 7275 287 1247 2212 207 991 28 158 6445 266 1130 1989 196 834 29 147 5648 244 1018 1774 181 729 30 134 4864 222 900 1552 165 520

HBW TRIP LENGTH FREQUENCY CURVE HBW Trip Length Frequency 7 6

Percent of Trips

5 4 3 2 1

Minutes 2000

2007

The last process undertaken during the TRIP DISTRIBUTION process is to provide a matrix of congested travel times for subsequent processing during the MODE CHOICE step. Travel times are contained in the CONGSKIM_A07.MAT file, a portion of which is shown below;

6 The Transit Prep Process The “Tier A Transit” methodology developed by AECOM for FDOT in 2008 is the “new standard” for FSUTMS. As such, it has been incorporated, for the first time, into the 2007 Polk County model, so we will provide a more detailed explanation of the processes incorporated into the model, in sections 6, 7 and 8. The "Tier A Transit" CUBE scripts which first became available 10/2008 were incorporated into the Polk County model for FDOT District One by Traf-O-Data Corp. in 2009.

The Transit Prep module, contains 30 program steps in two modules to prepare model prior to Mode Choice. Integral to the building of a transit network is the availability of access to transit. A critical component to this is identifying the zones that are within an acceptable walking distance to a transit stop. Walk access is generally provided from centroid nodes to stops nodes. Transit path building involves the generation of zoneto-zone transit paths, transit skims, transit fares, and station matrices. These files are built for each of the transit modes during each of the periods occurring in the model. The Polk County 2007 model is a multipath/single-period transit model that currently only has one mode, local bus.

The first module “Transit Prep” does the following: • Set up program variables; • Calculates transit speeds by mode; • Applies AUTOCON to build peak and off-peak access connections;

The module constructs separate peakperiod (AM) and midday (MD) transit restrained highway skims as an input to represent congested zone-to-zone travel times. Transit accessibility to transit stations coded within the NODE file was managed by the program which generates walk access links from origins and destinations to the transit network. Transit path building involves the generation of transit path matrices, fares, skims and station-to-station interchanges. Most of the effort in validating the transit accessibility and path building focused on ensuring that the transit network was up to date and accurately reflected base year conditions. In addition, walk access links were checked in order to ensure adequate connectivity.

The second module “Transit Path” does the following: • Set up program variables; • Calculates transit travel time skims, by mode; • Checks for/removes illogical paths, and; • Prepares Station Access data. Calibration of transit path building generally includes iterative adjustments to the following parameters: • Maximum transfers; • Maximum travel times; • Wait times; • Transfer times; • Minimum and maximum wait penalties; • Run time factors; • Transfer penalties, and; • Maximum fare. Please refer to the FSUTMS Transit Model Application Guide developed for FDOT by AECOMM in 2008. Travelers’ choices of public transportation services are dependent on the physical and operating characteristics, are how the traveler accesses the service. The model represents these characteristics by means of the trans network, which includes the transit lines, modes, operators, fares, speeds, and access connectors. Transit Line - Includes all of the individual routes of public transportation vehicles. Line coding represents the routing, stop locations and frequency. The mode, operator, and route name are also identified, as well as any line-specific travel time adjustments. Stop locations are commonly identified to the nearest roadway intersections in the highway network. Time of day can be used to represent 47

frequency. Different frequencies can be reflected as headway. The headway of a transit route is the time gap between two consecutive runs at a specific point. Two headways are used for each line by default, one for the peak period and another for the off-peak period. Zero is used for the headway if the line does not conduct service during that time period. Modes - For regions with more than one transit service, modes represent the transit choices available. These characteristics of each transit service should be represented in the network to reflect how they appear to the traveler. The most important characteristic is travel time. For example, rail systems are typically faster than local buses that stop regularly due to traffic congestion and passenger loading/unloading. Different mode numbers are used to reflect different transit services. The mode number is then assigned to identify each transit route. Default mode definitions can be used for a single transit agency; additional modes can be defined if two or more transit agencies exist within the region. Operators – Operators are the agencies responsible for providing transit services. Separate operators should be defined for each fare system the transit agency offers. If several fare systems are offered, then multiple operators should be defined. Fares – Fares are fees paid by travelers to use public transportation. The fees may be boarding fares that are assessed upon boarding the transit service, or transfer fares that are assessed upon boarding a subsequent transit service on a trip. Transfer fares are generally lower than boarding fares. Speeds - For those transit vehicles that operate in mixed-flow traffic, transit vehicle travel times are a function of auto travel time. The travel times for vehicles that operate on exclusive right-of-way (for example, fixed-guide way and bus-only lanes) are calculated using equations of motion. In Florida, facility type, area type, and mode categorize auto-transit time relationships. Transit travel times are computed on a link-by-link basis in the transit model. By default, all transit speeds are set to equal the auto speeds in the model. The user may change these values to define peak and off-peak period transit modes. Access Connectors - Occurs between a travelers’ origin and the first transit vehicle boarding. From a modeling context, it occurs between the origin zone (i.e., centroid) and the transit network. It is represented by connectors between centroids and transit stops. Transit is accessed by one of three ways: by walking, park-and-riding, or being dropped off by someone. Walk-access is walking between the origin and the first transit vehicle. Transit service must be within ½ mile (network distance) of the centroid. Park-n-ride (PNR) access and drop-off (or kiss-n-ride (KNR) access) occurs when a car is used from the origin to the first transit boarding. For PNR trips, the access trip portion is assumed to terminate at a formal or informal PNR lot. KNR trips can terminate at various locations, but it is assumed that the KNR trips terminate only at locations where PNR trips terminate. This assumption allows for easier model maintenance and is based in part on a lack of sufficient information about KNR travel patterns.

7 The Mode Choice Model The Mode Choice module, contains 27 program steps (not including iterative steps taken during model calibration) to prepare model prior to Transit Assignment.

The module accomplishes the following tasks: • Set up program variables; • Applies auto ownership by TAZ; • Calculates HOV time savings; • Uses utility and choice coefficients to Prepares mode share; • Runs user benefits • Creates Summit Reporting database • Optionally, iterates to match survey utilization • Optionally, re-writes utility coefficients • Prepares trip tables for assignment

The FSUTMS mode choice model is a behavioral model that is used to predict a traveler’s choice of one alternative (mode of transportation) from a set of alternatives (all forms of transportation available).

The probability of a mode being chosen is 49

given by exercising the following formula:

A better way to describe the MODE CHOICE model used for “Tier A Transit” is that it groups transportation alternatives into “levels” (or “nests”) hence the name “nested-logit model”. • • •

Choices at the top level are: AUTO and TRANSIT. Choices at the second level are: LOV, HOV, and WALK, PNR, KNR Choices at the third level are: 1-PASS, 2-PASS, LOCAL, PREMIUM.

The nested logit mode choice model works by computing the utility for each of the lower level choices. This utility represents the total economic “cost” in terms of travel time to travel a given mode. This “cost” is typically constructed as a linear function of the different components of time and cost

The utility for an upper level choice is computed by taking the log sum of the lower level nests. For example, the utility for the auto nest is computed from the utilities for LOV, 1-PASS, 2-PASS modes as follows: Uauto= NCauto * Ln(exp(Uda) + exp(Usr2) + exp(Usr3) Where: Uauto NCauto Ln (expUda) exp(Uda) exp(Usr2) exp(Usr3)

= Utility for auto = Nest coefficient for auto = Natural log = Exponental function = Utility for drive-alone 1 auto = Utility for shared-ride 2 auto = Utility for shared-ride 3+ auto

The total market is divided into zero-car, one-car, and two-car households for HBW and HBNW purposes. No market segmentation is done for the NHB trip purpose.2 The “Tier A Transit” mode choice model evaluates three auto sub-modes (LOV, HOV2 and HOV3+) and three transit sub-modes, by mode of access (WALK , PNR and KNR)

TIER A CONSTANTS AND COEFFICIENTS The “Tier A Transit” mode choice model uses two files to obtain the necessary parameters to achieve calibration. One is a file of “constants”: \PARAMETERS\MC_CONSTANTS.DBF (below, left) that indicates mode share from household surveys (the lower nest). The other file \PARAMETERS\TRAN_COEF.DBF that provides utility constants for the nested logit model. Discussion of the utility equations might be more easily understood by looking at the graphics on the following pages These illustrations show the nesting structures of the mode choice model used in the “Tier A Transit”. Notice how each box, representing a mode of access, has a representative share, all of which add up to 100%.

2 This methodology, recognized as having limited applicability to real-world travel characteristics and decision making processes, has been utilized since the very first models were conceived, around 1960, essentially due to computer memory and software limitations and limited availability of travel surveys. The TMIP process being undertaken by FHWA and FTA seek to improve this aspect of modeling for future generations. 51

TIER A TRANSIT: MC_CONSTANTS N1

HBW

HNBW

NHB

-999.990000

0.000000

DA AUTO0

NAME

0.660500

0.660530

0.569756

SR1PASS AUTO0

0.230600

0.230621

0.396549

0.108900

0.104479

0.032681

-999.990000

0.000000

W LKPRJ AUTO0

-999.990000

0.000000

PNRBUS AUTO0

-999.990000

0.000000

-999.990000

0.002978

-999.990000

TIER A TRANSIT: TRAN_COEFF HBW

HBNW

NHB

-0.025000

-0.012500

-0.025000

SR2PASS AUTO0

-0.025000

-0.012500

-0.025000

W ALKBUS AUTO0

-0.050000

-0.025000

-0.050000

-0.002500

-0.005000

-0.037500

-0.018750

-0.037500

-0.125000

-0.062500

-0.125000

PNRPRJ AUTO0

0.000000

0.000523

KNRBUS AUTO0

0.000000

KNRPRJ AUTO0

0.000000

-999.990000

0.000000

0.000000 CBDKNRBUS AUTO0

0.600000

0.300000

0.400000

-999.990000

0.000000

0.000000 CBDKNRPRJ AUTO0

0.800000

0.500000

-999.990000

0.000000

0.000000 FRINGEPNR AUTO0

0.200000

0.769400

0.769378

0.376048

DA AUTO1

0.000000

0.152300

0.152346

0.356571

SR1PASS AUTO1

0.000000

0.062200

0.062191

0.264244

SR2PASS AUTO1

0.012100

0.012085

0.002895

W ALKBUS AUTO1

-999.990000

0.000000

W LKPRJ AUTO1 PNRBUS AUTO1

0.000100

0.000406

0.000059

-999.990000

0.000000

PNRPRJ AUTO1

-999.990000

0.000389

0.000095

KNRBUS AUTO1

-999.990000

0.000000

KNRPRJ AUTO1

-999.990000

0.000000

0.000000 CBDKNRBUS AUTO1

-999.990000

0.000000

0.000000 CBDKNRPRJ AUTO1

-999.990000

0.000000

0.000000 FRINGEPNR AUTO1

0.777400

0.777356

0.380251

DA AUTO2

0.153600

0.153644

0.353765

SR1PASS AUTO2

0.062800

0.062826

0.264855

SR2PASS AUTO2

0.002800

0.002797

0.000935

W ALKBUS AUTO2

-999.990000

0.000000

W LKPRJ AUTO2

0.000100

0.000450

0.000055

PNRBUS AUTO2

-999.990000

0.000000

PNRPRJ AUTO2

-999.990000

0.000306

0.000072

KNRBUS AUTO2

-999.990000

0.000000

KNRPRJ AUTO2

-999.990000

0.000000

0.000000 CBDKNRBUS AUTO2

-999.990000

0.000000

0.000000 CBDKNRPRJ AUTO2

-999.990000

0.000000

0.000000 FRINGEPNR AUTO2

0.000000

CBDW ALK

0.000000

CBDPNR

0.000000

CBDKNR

NAME

IVTT IVTT for commuter rail OVT Cost Auto access time Number of transfers not used not used not used Transit access nest Transit nest Auto nest Auto access nest not used CBD constant walk paths CBD constant PNR paths CBD constant KNR paths not used

HOME-BASED WORK (HBW) MODE SHARE COEFFICIENTS HBW ALL TRIPS TOTAL 1.000000

100.00%

0.996100

99.61%

0.996700

99.67%

AUTO

TRANSIT

0.891100

0.108900

100.00%

0.983900

0.012200

99.61%

0.993800

0.002900

99.67%

TOTAL

LOV

HOV

WALK

PNR

KNR

0.891100

0.108900

0.000000

100.00%

TOTAL

B 1 13

0.769400

0.214500

0.012100

0.000100

0.000000

99.61%

0.777400

0.216400

0.002800

0.000100

0.000000

99.67%

1 PASS B

2 PASS B

LOCAL

PREMIUM

BUS

LOCAL B

0.660500

0.230600

0.108900

0.152300

0.062200

0.012100

0.153600

0.062800

0.002800

BUS

PREMIUM B

BUS

LOCAL B

BUS

PREMIUM B

BUS

TOTAL

100.00%

0.000100

22.67%

0.000100

21.93%

HOME BASED NON-WORK (HBNW) MODE SHARE COEFFICIENTS HBNW ALL TRIPS TOTAL 0.998608

99.86%

0.996795

99.68%

0.997379

99.74%

AUTO

TRANSIT

0.891151

0.107457

TOTAL 99.86%

0.983915

0.012880

99.68%

0.993826

0.003553

99.74%

LOV

HOV

WALK

PNR

KNR

0.891151

0.104479

0.000000

0.002978

99.86%

TOTAL

C 1 13

0.769378

0.214537

0.012085

0.000406

0.000389

99.68%

0.777356

0.216470

0.002797

0.000450

0.000306

99.74%

1 PASS C

2 PASS C

LOCAL

PREMIUM

BUS

LOCAL

BUS

PREMIUM BUS

LOCAL

PREMIUM BUS

TOTAL

BUS

0.002978

99.86%

0.660530

0.230621

0.104479

0.152346

0.062191

0.012085

0.000406

0.000389

22.74%

0.153644

0.062826

0.002797

0.000450

0.000306

22.00%

NON-HOME BASED (NHB) MODE SHARE COEFFICIENTS

NHB ALL TRIPS TOTAL 0.999509

99.95%

0.999912

99.99%

0.999933

99.99%

AUTO

TRANSIT

0.966305

0.033204

TOTAL 99.95%

0.996863

0.003049

99.99%

0.998871

0.001062

99.99%

LOV

HOV

WALK

PNR

KNR

0.966305

0.032681

0.000000

0.000523

99.95%

TOTAL

D 1 13

0.376048

0.620815

0.002895

0.000059

0.000095

99.99%

0.380251

0.618620

0.000935

0.000055

0.000072

99.99%

1 PASS D

2 PASS D

LOCAL

PREMIUM

BUS

LOCAL

BUS

PREMIUM BUS

LOCAL

PREMIUM BUS

TOTAL

BUS

0.000523

99.95%

0.569756

0.396549

0.032681

0.356571

0.264244

0.002895

0.000059

0.000095

62.39%

0.353765

0.264855

0.000935

0.000055

0.000072

61.97%

The final step in the mode choice application is placing the auto vehicle portion of the access-to-transit trip onto the highway trip table. Each auto-access trip is divided by the user defined auto-occupancy rate (contained in the scenario managerâ&#x20AC;&#x2122;s key field) is added from the origin zone to the parking zone. The following Mode Choice Summary, taken from the model file: MODESUM.TXT, lists input data and resulting mode share, by purpose.

MODE CHOICE SUMMARY PURPOSE HBW SKIMS/PERIOD PK Coefficients IVTT OVT AAT XFER COST DUM_CBD_WALK DUM_CBD_PNR DUM_CBD_KNR

Nesting Coeffcient NC_TRNAC NC_TRN NC_AUTOSR

-0.0250 -0.0500 -0.0375 -0.1250 -0.0025 0 0 0

0.5000 0.8000 0.2000

Constants Drive alone (0 car) -999.990 Drive alone (1 car) 0.7694 Drive alone (2 car) 0.7774 HOV2 (0 car) 0.6605 HOV2 (1 car) 0.1523 HOV2 (2 car) 0.1536 HOV3+ (0 car) 0.2306 HOV3+ (1 car) 0.0622 HOV3+ (2 car) 0.0628 Walk Bus (0 car) 0.1089 Walk Bus (1 car) 0.0121 Walk Bus (2 car) 0.0028 PNR Bus (0 car) -999.990 PNR Bus (1 car) 0.0001 PNR Bus (2 car) 0.0001 KNR Bus (0 car) -999.990 KNR Bus (1 car) -9.9000 KNR Bus (2 car) -9.9000

Parameters used in disutility calculations: Highway Operating Cost (cents/mi) 9.500 CTOLL Multiplier (toll to time) 0.027 Value of ZAPZERO 1.000 Auto Occupancy 3+ (HBW) 3.370 Auto Occupancy 3+ (HBO) 3.490 Auto Occupancy 3+ (NHB) 3.590 Inflation factor - Tolls 1.000 Inflation factor - Auto Op Cost 1.000 Inflation factor - Parking Cost 1.000 Inflation factor - Transit Fare 1.000 Auto Access Auto Occupancy Factor 1.200 Times reflected in minutes. Costs are in cents.

HBW - PK MODE XCHOICE RESULTS ************************************************************** Total Drive One Two+ Total MARKET SEGMENT Person Alone Pax Pax Auto ---------------------------------------Zero Car HHs 10300.1 0 10036.6 211.4 10248.0 One Car HHs 98367.0 69958.6 16820.0 10942.9 97721.5 Two+ Car HHs 205154.1 146591.0 34889.0 22576.8 204056.8

Walk Bus -----52.1 181.6 276.8

PNR Bus ------0 463.8 820.5

KNR Bus -----0 0 0

Total Transit ------52.1 645.5 1097.3

TOTAL

313821.1

216549.6

61745.6

33731.1

312026.3

510.5

1284.3

1794.9

Productions: CBD Exurban Other

2310.1 22244.5 289266.5

1586.0 15350.1 199613.5

487.7 4454.5 56803.4

222.2 2193.9 31315.0

2295.8 21998.5 287731.9

8.4 98.0 404.2

5.9 148.0 1130.5

0 0 0

14.3 246.0 1534.7

Attractions: CBD Exurban Other

13811.5 40665.8 259343.8

9325.0 28074.5 179150.2

2716.4 8072.3 50956.8

1421.9 4151.7 28157.5

13463.3 40298.5 258264.5

98.4 107.4 304.7

249.8 259.9 774.6

0 0 0

348.3 367.3 1079.3

255.27 0.50

642.17 0.50

0 0.50

897.43 0.50

364.8 144.1 1.6 0.0

1167.4 115.6 1.2 0.0

0 0 0 0

1532.3 259.8 2.8 0.0

Fare Revenue ($) Average Fare ($) Transfers: NONE ONE TWO THREE + Average Auto Occupancy

PURPOSE HBO SKIMS/PERIOD OP Coefficients IVTT OVT AAT XFER COST DUM_CBD_WALK DUM_CBD_PNR DUM_CBD_KNR

1.212

-0.0125 -0.0250 -0.0187 -0.0625 -0.0025 0 0 0

Nesting Coeffcient

NC_TRNAC NC_TRN NC_AUTOSR

0.3000 0.8000 0.2000

Constants Drive alone (0 car) -999.990 Drive alone (1 car) 0.3760 Drive alone (2 car) 0.3803 HOV2 (0 car) 0.5698 HOV2 (1 car) 0.3566 HOV2 (2 car) 0.3538 HOV3+ (0 car) 0.3965 HOV3+ (1 car) 0.2642 HOV3+ (2 car) 0.2649 Walk Bus (0 car) 0.0337 Walk Bus (1 car) 0.0029 Walk Bus (2 car) 0.0008 PNR Bus (0 car) -999.990 PNR Bus (1 car) 0.0001 PNR Bus (2 car) 0.0001 KNR Bus (0 car) -999.990 KNR Bus (1 car) -9.9000 KNR Bus (2 car) -9.9000 Parameters used in disutility calculations: Highway Operating Cost (cents/mi) 9.500 CTOLL Multiplier (toll to time) 0.027 Value of ZAPZERO 1.000 Auto Occupancy 3+ (HBW) 3.370 Auto Occupancy 3+ (HBO) 3.490 Auto Occupancy 3+ (NHB) 3.590 Inflation factor - Tolls 1.000 Inflation factor - Auto Op Cost 1.000 Inflation factor - Parking Cost 1.000 Inflation factor - Transit Fare 1.000 Auto Access Auto Occupancy Factor 1.200 Times reflected in minutes. Costs are in cents.

HBO - OP MODE XCHOICE RESULTS ************************************************************** Total Drive One Two+ Total MARKET SEGMENT Person Alone Pax Pax Auto ---------------------------------------Zero Car HHs 20786.9 0 16494.3 4143.0 20637.3 One Car HHs 193135.6 85031.3 66790.6 39466.3 191288.2 Two+ Car HHs 236065.3 104824.3 80403.5 49081.9 234309.7

Walk Bus -----149.6 612.5 550.4

PNR Bus ------0 1235.0 1205.1

KNR Bus -----0 0 0

Total Transit ------149.6 1847.5 1755.6

TOTAL

449987.7

189855.6

163688.3

92691.2

446235.1

1312.5

2440.1

3752.6

Productions: CBD Exurban Other

3203.3 32824.9 413959.5

1372.3 13914.7 174568.6

1220.3 12043.2 150424.8

574.4 6327.0 85789.8

3166.9 32284.9 410783.2

20.7 247.2 1044.6

15.7 292.8 2131.7

0 0 0

36.3 540.0 3176.3

Attractions: CBD Exurban Other

18987.0 56671.5 374329.2

7773.7 23733.0 158349.0

6831.8 20612.1 136244.5

3958.3 11522.5 77210.4

18563.8 55867.5 371803.8

162.8 277.3 872.4

260.5 526.6 1653.0

0 0 0

423.3 803.9 2525.4

656.26

1220.06

1876.32

Fare Revenue ($)

Average Fare ($) Transfers: NONE ONE TWO THREE + Average Auto Occupancy

PURPOSE NHB SKIMS/PERIOD OP Coefficients IVTT OVT AAT XFER COST DUM_CBD_WALK DUM_CBD_PNR DUM_CBD_KNR

-0.0250 -0.0500 -0.0375 -0.1250 -0.0050 0 0 0

Nesting Coeffcient NC_TRNAC NC_TRN NC_AUTOSR Constants Drive alone (0 car) Drive alone (1 car) Drive alone (2 car) HOV2 (0 car) HOV2 (1 car) HOV2 (2 car) HOV3+ (0 car) HOV3+ (1 car) HOV3+ (2 car) Walk Bus (0 car) Walk Bus (1 car) Walk Bus (2 car) PNR Bus (0 car) PNR Bus (1 car) PNR Bus (2 car) KNR Bus (0 car) KNR Bus (1 car) KNR Bus (2 car)

0.50

889.2 419.1 4.1 0.0

2206.6 230.2 3.2 0.1

0 0 0 0

3095.8 649.4 7.3 0.1

1.496

0.4000 0.8000 0.2000

0.4767 -999.990 -999.990 0.3002 -999.990 -999.990 0.2178 -999.990 -999.990 0.0052 -999.990 -999.990 -999.990 -999.990 -999.990 -999.990 -999.990 -999.990

MARKET SEGMENT -------------Zero Car HHs One Car HHs Two+ Car HHs

Total Person ------484495.7 1.0 1.0

Drive Alone -----233326.5 0 0

One Pax -----130461.9 0 0

Two+ Pax -----119503.2 0 0

Total Auto -----483291.7 0 0

Walk Bus -----1204.1 0 0

PNR Bus ------0 0 0

KNR Bus -----0 0 0

Total Transit ------1204.1 0 0

TOTAL

484495.7

233326.5

130461.9

119503.2

483291.7

1204.1

Productions: CBD Exurban Other

25103.7 90062.6 369329.5

12507.9 44387.0 176431.6

6886.9 24734.8 98840.2

5539.6 20581.5 93382.1

24934.4 89703.3 368653.9

169.3 359.3 675.5

0 0 0

169.3 359.3 675.5

Attractions: CBD Exurban Other

21926.5 79057.9 383511.4

11339.4 40266.8 181720.3

6229.8 22417.2 101814.9

4189.0 16016.2 99298.0

21758.2 78700.2 382833.3

168.3 357.6 678.1

0 0 0

168.3 357.6 678.1

Fare Revenue ($) Average Fare ($)

602.03 0.50

0 0.50

602.03 0.50

Transfers: NONE ONE TWO THREE +

1000.8 202.8 0.4 0.0

0 0 0 0

1000.8 202.8 0.4 0.0

Average Auto Occupancy

1.456

8 The Transit Assignment Process The Transit Assignment Module includes 12 steps, as illustrated below: • • • • • • •

Set up program variables; Loads Peak Period walk access to bus matrix, by mode; Loads Peak Period auto access to bus matrix, by mode; Loads Off Peak Period walk access to bus matrix, by mode; Loads Off Peak Period auto access to bus matrix, by mode; Loads auto access trips to highway trip table matrix, and; Prepares transit reports.

The transit assignment step in the Polk County 2007 model allocates trips to the transit network. Separate loads are conducted by mode and period as estimated by the mode choice model. HBW trips are assigned to the peak period network while HBNW and NHB trips are assigned to the midday network. Transit, evaluations were limited to how well the transit assignment matched against per-route ridership for each of the three transit operations in Polk County. As shown below, the model performed acceptably both on system-wide ridership and route ridership, but with just a few exceptions 61

ESTIMATE OF AVERAGE WEEKDAY RIDERSHP BY ROUTE 2007 Daily 2009 Ridership CUBE/Voyager Estimate from Ridership PAX/HR PolkTPO.A Model

2007 Daily 2009 Ridership CUBE/Voyager Estimate from Ridership PAX/HR PolkTPO.A Model

LAMTD

WHAT

Shuttle

117

267

Northside

232

E. Main/Combee

256

231

Lakeland/WinterHaven

269

130

Lakeland/WinterHaven

247

130

Haines City

101

Grove Park/Crystal Lake

296

139

PCC/Hospital

Edgewod

106

298

22x

Bartow Express to Winter Haven

Bartow Express to Lakeland

285

157

Eagle Ridge/Winter Haven

305

421

107

Southside

179

327

22X 30

Cleveland Heights

170

S Florida Ave

545

573

Southwest

167

Medulla Loop

Westside

119

137

South

Ariana/Beacon

298

Central Ave

220

106

W Memorial

414

551

Kathleen/Providence

190

362

N US98/Duff Rd

599

890

N Florida Ave

513

525

Lakeside Village

197

Kathleen/Mall Hill Rd

170

Kidron/Flightline

Subtotal

4,270

Subtotal

1,599

1,256 78.6%

Polk County Transit 25

Bartow/Fort Meade

Frostproot to Eagle Ridge Mall

23.8

111

5.6

3.5

5,080

Subtotal

192

119.0%

Total

6,061

6,369 105.1%

9 The Highway Assignment Model Process Trip Highway Assignment Module includes 2 steps, that: • • • •

Set up program variables; Loads trips, onto links with no toll; Loads trips onto links with toll parameters; Prepares for highway evaluation reports.

The purpose of highway assignment models is to load auto trips onto the highway network. This results in traffic estimates on individual links that ultimately attempt to simulate general vehicular travel throughout the study area. Validation of the highway assignment involved the adjustment of the speeds, capacities, penalties and other parameters related to trip distribution. Trips are loaded onto the network by means of an iterative equilibrium highway load program based on an all or nothing capacity restrained assignment. A series of statistical summaries are subsequently generated. The statistical summaries generated by “HASSIGN” are fairly limited with regards to model validation.

10 The Post Processor The Post Process which is 100% CUBE script, replaces the former HEVAL.EXE program., illustrated below, that:

The process includes 10 steps that: • • • • •

Set up program variables; Reports summary statistics, such as RMSE, VMT, VHT; Provides detailed reports and highway network summaries; Optionally, reports on corridor statistics; Provides detailed screen line summaries.

SCREENLINE PERFORMANCE Analyzing volume-to-count ratios along screen lines and/or cut lines allows for examining flows into, out of, and across geographic sub-areas and corridors. This constitutes a key component of highway assignment as well as assisting in the examination of trip distribution. There are 25 screen lines and/or cut lines in the Polk County 2000 model. Among these are cordons surrounding the various urban areas in the study area as well as an external cordon measuring trips coming into and going out of the study area. There are additional screen lines reporting volumes along I-4, US 27 ASSIGNMENT ACCURACY One of the most common uses of travel demand models is to forecast future traffic volumes in order to identify the impacts of growth over time and better plan to mitigate these impacts. A proper validation of the highway assignment is critical to the meaningful use of travel demand models. Key statistics analyzed as part of the validation process include the following: • • • • • •

Ratios of volume-over-count vehicle-miles traveled (VMT); Ratios of volume-over-count vehicle-hours traveled (VHT); Ratios of volume-over-count volumes; Volume-over-count ratios along screen lines and/or cut lines; Volume-over-count ratios on specific links; and Percent root mean square error.

FDOT standards allow for an accuracy of +/- 15 percent per category and +/- five percent area-wide. The Polk County 2007 model achieves this area-wide accuracy for volume-to count ratios at 0.98, for VMT, 0.99; for VHT 1.00

PERCENT ROOT MEAN SQUARED ERROR The percent root-mean-squared-error (RMSE) indicates whether the simulated network contains an acceptable level of assignment error. This is based on both the area-wide and volume group summaries. Accuracy is more stringent for higher volume facilities than for lower volume facilities. No RMSE category failed to meet established accuracy ranges with the Polk County 2007model.

The FSUTMS model update, Task C report, gives a number of validation criteria: Validation Check

Scale of Computation

Assigned VMT/Count VMT

Area

+/- 5%

Assigned VHT/Count VHT

Area

+/- 5%

Volume-Count Ratio

Screenlines

Facility Type, Area Type, No. of Lanes Facility Type, Area Type, Assigned VHT/Count VHT No. of Lanes

Assigned VMT/Count VMT

% Root Mean Square Error

Area

% Root Mean Square Error

Link Volume Groups

Level of Accuracy Vehicles per Day Level of Accuracy

+/- 20%

< 50K >

+/- 10%

+/- 20%

< 100K >

+/- 15%

< 20K >

+/- 25% +/- 35%-50%

+/- 100%

< 50K >

+/- 25%

Source: FSUTMS model update, Task C

The highway model evaluation summary provides the following details of the model:

DATE: GEN: NET: DISTRIB: TPREP: MODE: TASSIGN: HASSIGN: HEVAL:

Wed 10/07/2009 12:23:09.48 12:23:11.11 12:23:25.29 12:24:11.73 12:29:47.71 12:33:10.32 12:33:51.51 12:36:58.00

******************************************************************************************************************************** Total Number of Links: Total Centerline Miles: Total Lane Miles: Total Directional Miles: Total VMT using Volumes: Total VMT using Counts: Total VMT Volume over Counts: Total VHT using Volumes: Total VHT using Counts: Total VHT Volume over Counts: Total Volumes All Links: Total VMT All Links: Total VHT All Links: Original Speed (MPH): Congested Speed (MPH):

8,126 2,612.69 3,425.07 2,653.26 4,497,932 4,605,283 0.98 139,557 139,716 1.00 52,885,343 16,966,220 547,393 35.66 33.66

(Links (Links (Links (Links (Links (Links

With With With With With With

Counts) Counts) Counts) Counts) Counts) Counts)

11 FUTURE MODEL UPDATES A number of model enhancements could be considered during future model development efforts in Polk County. These could include the following: • Conducting external intercept and household travel diary surveys to provide updated local travel behavior characteristics to use in the travel demand model; • Considering and testing alternative trip generation structures either based on local survey statistics or borrowed parameters from other similar areas; • Adding capabilities within the external and trip generation models to allocate external trips among auto occupancy and truck categories for sensitivity testing; Implementation of Time-of-Day (TOD) modeling procedures. TOD applications are currently being studies by FDOT Systems Planning Office. We would recommend that TOD procedures begin with Trip Generation. Why? One example would be that a Shopping Mall may not generate ANY vehicle trips in the AM peak period, simply because most stores don’t open until 10:00AM but an office building will generate trips. Currently BOTH are coded the same: with just number of employees on site. Implementation of a special trip generation/distribution procedure may be warranted in the future. In District One the Lee/Collier model has a special procedure for distributing Southwest Florida International Airport trips based upon expected enplanements. A similar, special procedure, may be needed with the development of the Intermodal Logistics Center (ILC) with the CSX railway in central Polk County.