Alternative Methods For Developing External Travel Survey
1. Report No.FHWA/TX-10/0-6583-12. Government Accession No.4. Title and SubtitleALTERNATIVE METHODS FOR DEVELOPING EXTERNALTRAVEL SURVEY DATA7. Author(s)Technical Report Documentation Page3. Recipient's Catalog No.5. Report DatePublished: October 20106. Performing Organization Code8. Performing Organization Report No.Stephen Farnsworth, Eric Talbot, Praprut Songchitruksa,Phillip Reeder, and David PearsonReport 0-6583-19. Performing Organization Name and Address10. Work Unit No. (TRAIS)Texas Transportation InstituteThe Texas A & M University SystemCollege Station, Texas 77843-313511. Contract or Grant No.Project Number 0-658312. Sponsoring Agency Name and Address13. Type of Report and Period CoveredTexas Department of TransportationResearch and Technology Implementation OfficeP.O. Box 5080Austin, Texas 78763-5080Final: March 2009 – February201014. Sponsoring Agency Code15. Supplementary NotesProject performed in cooperation with the Texas Department of Transportation and the Federal HighwayAdministration.Project Title: Methods for Developing External Travel Survey DataURL: http://tti.tamu.edu/documents/0-6583-1.pdf16. AbstractThe Texas Department of Transportation (TxDOT) has a comprehensive on-going travel surveyprogram that supports the travel demand models being developed for transportation planning efforts in urbanareas throughout Texas. One component of the survey program is the external travel survey. External travelsurveys provide data on travel movements into, out of, and through urban areas. In recent years, there hasbeen a heightened sensitivity to the methods used to collect external survey data as well as the type of datathat is collected. This research examines alternative methods for collecting data on external travelmovements and evaluates the potential for synthesizing/modeling external travel in lieu of conductingexternal surveys. The research will provide recommendations to TxDOT on the most viable methods toestimate external travel movements for use in travel demand models in urban areas in Texas.17. Key WordsExternal Survey, Transportation Planning, ExternalLocal, External Through, Trip Tables19. Security Classif.(of this report)UnclassifiedForm DOT F 1700.7 (8-72)18. Distribution StatementNo restrictions. This document is available to thepublic through NTIS:National Technical Information ServiceSpringfield, Virginia 22161http://www.ntis.gov20. Security Classif.(of this page)UnclassifiedReproduction of completed page authorized21. No. of Pages12622. Price
ALTERNATIVE METHODS FOR DEVELOPING EXTERNALTRAVEL SURVEY DATAbyStephen FarnsworthAssociate Research ScientistTexas Transportation InstituteEric TalbotGraduate Assistant ResearcherTexas Transportation InstitutePraprut SongchitruksaAssociate Research ScientistTexas Transportation InstitutePhillip ReederProgram Manager, Travel Forecasting ProgramTexas Transportation InstituteandDavid PearsonResearch ScientistTexas Transportation InstituteReport 0-6583-1Project 0-6583Project Title: Methods for Developing External Travel Survey DataPrepared in cooperation with theTexas Department of Transportationand theFederal Highway AdministrationPublished: October 2010TEXAS TRANSPORTATION INSTITUTEThe Texas A&M University SystemCollege Station, Texas 77843-3135
DISCLAIMERThe contents of this report reflect the views of the authors, who are responsiblefor the facts and the accuracy of the data presented herein. The contents do notnecessarily reflect the official view or policies of the FHWA or TxDOT. This report doesnot constitute a standard, specification, or regulation. The research supervisor in chargeof this project was Stephen Farnsworth.v
ACKNOWLEDGMENTSThis project was conducted in cooperation with the Texas Department ofTransportation (TxDOT) and the Federal Highway Administration (FHWA). Theresearch reported herein was performed by the Texas Transportation Institute (TTI). Mr.Bill Knowles, Director of the Traffic Analysis Section of the Transportation Planning andProgramming Division, served as the research project director.The authors would like to thank the members of the Project Monitoring Committeefor their advisement and guidance: Mr. Charlie Hall, Transportation Planning and Programming Division, TexasDepartment of Transportation;Ms. Janie Temple, Transportation Planning and Programming Division, TexasDepartment of Transportation;Mr. Greg Lancaster, Transportation Planning and Programming Division, TexasDepartment of Transportation;Mr. Paul Tiley, Transportation Planning and Programming Division, TexasDepartment of Transportation;Mr. Eduardo Calvo, El Paso District, Texas Department of Transportation.The authors would like to provide special thanks to Duncan Stewart, Frank Espinosa,and Sylvia Medina of TxDOT’s Research and Technology Implementation (RTI)Division for their assistance in this project.The authors would like to thank the following individuals from TTI for theirassistance: Mr. Ed Hard – project administration assistance,Ms. Debbie Spillane – literature review assistance,Mr. Jason Beesinger – data analysis assistance,Mr. Gary Lobaugh – review and formatting assistance,Mr. Justin Malnar – contract assistance, andEditors in TTI’s Communications Division.vi
TABLE OF CONTENTSList of Figures . xList of Tables . xiChapter 1. Introduction . 1Project Purpose . 1Overview of Travel Surveys in Texas . 1Legal Challenges and Foundations . 4Understanding the Problem. 6External Local and External Through Trip Apportionment . 8Non-Commercial and Commercial Vehicle Trip Allocation . 8Non-Resident Travel . 8Average Trip Lengths . 8Survey Expanded Trip Tables . 8Methods to Estimate External Data . 9Developing Synthetic External Models . 9Data from Other Surveys . 10Statewide Model Data Extrapolation . 10Chapter 2. Alternative Approaches to Collecting External Travel Survey Data . 13Methods for Collecting New Travel Data . 13Methods for Developing New Estimates Using Existing Data . 16Estimating External-External (E-E) Trip Matrices . 16Estimating Internal-External (I-E/E-I) Trip Matrices . 17Method for Developing New Estimates Using State Planning Data . 18Chapter 3. Analysis of Traffic Control Plans. 19Analytical Procedure . 22Overview of Modeling Tools . 22Operational Assumptions . 23Old TCP for 4-Lane Undivided Roadways. 23New TCP for 4-Lane Undivided Road without Shoulder . 23New TCP for 4-Lane Undivided Road with Shoulder . 24Simulation Setup of TCPs in VISSIM . 25Experimental Design for the Simulation Analysis. 28Design of Simulation Scenarios . 30Data Collection and Measures of Effectiveness . 30Results . 32Impacts of Old TCPs . 32Impact of New TCPS on Roads without Adequate Shoulders . 33Impact of New TCPS on Roads with Adequate Shoulders. 36Probability of Exceeding Bay Capacity . 37Survey Efficiency. 38Summary . 39Chapter 4. Alternative Methods – Use of Other Travel Survey Data . 43Household Surveys . 43Work Place Surveys . 44Commercial Vehicle Surveys . 44vii
Average Trip Length Estimates . 45Summary . 46Chapter 5. Alternative Methods – Statewide Analysis Model. 47Statewide Analysis Model Application . 47Development of the Austin and Corpus Christi External Matrices . 48Comparison of UABs to External Survey Locations . 49Development of External Local and External Through Trip Matrices . 49Statewide Analysis Model Results. 49Summary . 53Chapter 6. Alternative Methods – Logit Models . 55Overview of Previous Research . 55Model Overview . 59Model Data Sources . 62Model Approach . 63Model I Development and Evaluation . 65Candidate Predictor Variables . 65Variable Definitions . 65Interaction Score Variables . 70Route Validity Variable . 70Average Turns Variable . 71“Is Commercial Vehicle” Variable . 71Variables Not Selected as Candidate Predictor Variables . 71Data Sources for Predictor Variables . 72Preliminary Variable Selection . 73Diagnostics . 76Final Variable Selection . 78Model Refinement . 80Model Evaluation . 81Model II Development and Evaluation . 82Candidate Predictor Variables . 83Discussion of Candidate Predictor Variables . 85Measures of Separation between External Stations . 85Route Validity Variable . 86Variables Not Selected as Candidate Predictor Variables . 86Data Sources for Predictor Variables . 87Preliminary Variable Selection . 87Final Variable Selection . 89Model Refinement . 90Model Evaluation . 91Model Results and Sample Applications . 92Selected Results . 94Summary . 105Chapter 7. Summary, Recommendations, and Conclusions . 107Summary of Alternative Methods . 107Other Survey Types . 107EULA Application in SAM . 108viii
Logit Model . 108Additional Methods to Consider . 108Internet-Based Travel Surveys . 108Postcard Surveys . 108GPS Enabled Cellular Phone Data . 109Recommendations . 109Conclusions . 109References . 111ix
LIST OF FIGURESFigure 1. Travel Survey Regions in Texas. 2Figure 2. External Survey on Low-volume Roadway. . 4Figure 3. Old TxDOT External Station TCP. . 19Figure 4. New TxDOT External Station TCP (without shoulders). . 20Figure 5. New TxDOT External Station TCP (with shoulders). 21Figure 6. Example of VAP Scripts for Controlling Routing Decisions. 23Figure 7. Overview of the Simulated Segment. . 25Figure 8. Detailed Diagram of the Survey Station in the Simulation. . 26Figure 9. Simulated Operation of Old TxDOT TCPs. . 26Figure 10. Simulated Operation of New TCP on Road without Shoulders. . 27Figure 11. Simulated Operation of New TCP on Road with Shoulders. . 27Figure 12. Impacts of Volume on Delay under Old TCP. . 33Figure 13. Best Case Scenario for New TCP on Roads without Shoulders. . 35Figure 14. Worst Case Scenario for New TCP on Roads without Shoulders. . 35Figure 15. SAM Urban Area Boundaries. . 48Figure 16. Interaction of Two Logit Models. . 59Figure 17. Local Route Validity Example. . 71Figure 18. Forward Selection Results for Model I. . 76Figure 19. Model I-a Diagnostics. . 77Figure 20. Step Test Plot for PINTTHj. . 80Figure 21. Illustration of Through Route Validity Variable. . 86Figure 22. Forward Selection Results for Model II. . 88Figure 23. Step Rest Results for Model II. . 90x
LIST OF TABLESTable 1. Survey Data Element Functions in the Modeling Process. . 7Table 2. External VMT Examples from Selected Texas Cities. . 9Table 3. Factors Influencing the Operations of the TCPs. . 29Table 4. Varied Factors for TCP Simulations. 29Table 5. Experimental Setup. . 30Table 6. Simulation Performance Measures. . 31Table 7. Selected Scenarios for Delay Comparison. 34Table 8. Probability of Exceeding Survey Bay Capacity for One Platoon. . 38Table 9. Completed Surveys* – New TCP on Roads with Adequate Shoulders. 39Table 10. Surveyor Utilization – New TCPs on Roads with Adequate Shoulder. . 39Table 11. Comparison of Impacts from Old versus New TCPs. . 41Table 12. Resident External Travel Estimates. . 43Table 13. Visitor External Travel Estimates. . 44Table 14. Commercial Vehicle External Local Travel Estimates. 45Table 15. Non-Commercial Vehicle External Local Trip Length Comparisons. . 45Table 16. Commercial Vehicle External Local Trip Length Comparisons. . 46Table 17. Summary of Survey and SAM Results. . 50Table 18. Summary of Unexpanded Austin Survey Data and SAM Results. 50Table 19. Summary of Expanded Austin Survey Data and SAM Results. . 51Table 20. Summary of Unexpanded Corpus Christi Survey Data and SAM Results. . 52Table 21. Summary of Expanded Corpus Christi Survey Data and SAM Results. . 52Table 22. Variables for Previous Stage One Models. . 56Table 23. Variables Considered for Previous Combined Models. 57Table 24. Variables for Previous Stage Two Models. . 58Table 25. Logit Model I. . 60Table 26. Logit Model II. . 61Table 27. Equations for Developing Through Trip Tables. . 62Table 28. Summary of External Surveys in Texas. . 63Table 29. Candidate Variable Definitions for Model I. . 65Table 30. Interaction Score Definition. 69Table 31. Forward Selection Results for Model I. . 75Table 32. Model I-a. 76Table 33. Parameter Estimate Change after Removing External Station 1213. . 78Table 34. Study Area Groups. 79Table 35. Parameter Estimate Changes when Removing Study Area Groups (percent). . 79Table 36. Model I-b . 80Table 37. Model I-c. 81Table 38. Cross Classification of Observations for Group 1. . 81Table 39. Cross Classification of Observations for Group 2. . 82Table 40. Cross Classification of Observations for Group 3. . 82Table 41. Cross Classification of Observations for Group 4. . 82Table 42. Variable Definitions for Model II. . 83Table 43. Forward Selection Results for Model II. . 88Table 44. Model II-a. . 89xi
Table 45. Relative Change in Parameter Estimates after Removing Study Area Groups. 89Table 46. Model II-b. . 89Table 47. Model II-c. . 90Table 48. Cross Classification of Observations for Group 1. . 91Table 49. Cross Classification of Observations for Group 2. . 91Table 50. Cross Classification of Observations for Group 3. . 91Table 51. Cross Classification of Observations for Group 4. . 92Table 52. Final Model I Equations. . 93Table 53. Final Model II Equations. . 94Table 54. Wichita Falls Commercial Vehicle Through Trip Table. . 95Table 55. Wichita Falls Non-Commercial Vehicle Through Trip Table. . 96Table 56. Amarillo Commercial Vehicle Through Trip Table. . 97Table 57. Amarillo Non-Commercial Vehicle Through Trip Table. . 98Table 58. Austin Commercial Vehicle Through Trip Table. . 99Table 59. Austin Non-Commercial Vehicle Through Trip Table. 100Table 60. Wichita Falls Comparison of Trip Estimates. . 101Table 61. Amarillo Comparison of Trip Estimates. 102Table 62. Austin Comparison of Trip Estimates. . 103Table 63. Comparison of Trip Estimates for all Study Areas Reviewed. . 104Table 64. Percent Difference for Modeled Through Trips. . 105Table 65. Overview of Current and Alternative Methods. . 107xii
CHAPTER 1. INTRODUCTIONThe importance of well developed transportation networks is often overlooked by thepublic. However, the reality is that transportation networks are crucial to the long-termeconomic vitality of the United States. The ability to effectively and efficiently movepeople and goods around the country has a direct correlation to the quality of people’slives. As transportation systems have developed on national, state, and local levels,methods to measure how effectively the networks are performing have also been devised.In addition to measuring the operational characteristics of highway systems, particularinterest has been devoted to planning for future growth and development.Adding capacity to transportation networks, whether it is adding lanes to existingroadways or building new roads altogether, is an expensive process. Right-of-wayacquisition, utility relocation, and design/engineering work all contribute to the everincreasing cost of expanding transportation systems. Urbanized areas typically havemany more transportation improvement projects identified than they have the funding toactually undertake. As a result, processes have been developed to help planners and cityofficials prioritize which projects provide the greatest benefit at the local and/or regionallevel. An accepted and widely implemented practice is the use of travel demand models(TDM) to forecast and estimate traffic and development patterns. Travel surveys serve asthe primary inputs for TDMs in Texas. Having good travel survey data results in moreaccurate estimates for use in travel demand models, thus resulting in better informationfor decision makers to utilize in managing transportation system investments.PROJECT PURPOSEThe Texas Department of Transportation (TxDOT) administers a robust travel surveyprogram that collects travel data in all of the urbanized areas in the state. The travelsurvey program includes household, workplace, commercial vehicle, and external travelsurveys. Data extracted from these surveys serve as inputs to TDMs used by TxDOT intransportation planning and policy analyses. The purpose of this project was to examinealternative methods for collecting data on external travel movements and evaluate thepotential for synthesizing external travel data in lieu of conducting external travelsurveys.This project examined experiences and results for highways within and outside Texas,both from existing information and through case studies of selected Texas highways. Theresearch used cause and effect relationships between various policies, actions, andpractices and the resulting functionality over the life cycle of highways.OVERVIEW OF TRAVEL SURVEYS IN TEXASOrigin-destination travel surveys were first used in Texas in the 1950s to develop triptables of zone to zone trip movements. In the 1960s, they served as the foundation forearly travel models used in transportation planning and programming. Essentially nonew large travel surveys were performed during the 1970s and early 1980s. By the mid1
1980s, there was a push to revive travel survey data collection efforts using small sampletechniques. In 1989–1990, TxDOT initiated several major travel surveys in urban areasto provide information to update their travel demand models. This effort has sinceevolved into TxDOT’s current-day travel survey program (TSP) that represents one of themost comprehensive continuing data collection efforts in the nation.The Transportation Planning and Programming (TPP) Division of TxDOT funds andmanages the TSP, which collects data on travel in all major urban areas in the state ofTexas. The TSP coordinates the conduct of travel surveys on a recurring basis in all of thestate’s 25 Metropolitan Planning Organizations (MPOs). The TSP consolidates the MPOsinto 14 travel survey regions in order to combine areas with similar travel characteristicsand survey them in a systematic and efficient manner. Figure 1 shows the travel surveyregions in Texas.Figure 1. Travel Survey Regions in Texas.2
The TSP includes household, workplace, commercial vehicle, and exter
Sep 05, 2008 · program that supports the travel demand models being developed for transportation planning efforts in urban areas throughout Texas. One component of the survey program is the external travel survey. External travel surveys provide data on travel movements into, ou
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