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This report is an archived publication and may contain dated technical, contact, and link information
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Publication Number:  FHWA-HRT-13-097    Date:  September 2014
Publication Number: FHWA-HRT-13-097
Date: September 2014

 

Analysis of Network and Non-Network Factors on Traveler Choice Toward Improving Modeling Accuracy for Better Transportation Decisionmaking

REFERENCES

  1. Raphael, S. and Rice, L. (2002). “Car Ownership, Employment, and Earnings,” Journal of Urban Economics 52(1), 109–130.

  2. Hiscock, R., Macintyre, S., Kearns, A., and Ellaway, A. (2002). “Means of Transport and Ontological Security: Do Cars Provide Psycho-Social Benefits to Their Users?” Transportation Research Part D: Transport and Environment, 7(2), 119–135.

  3. Cullinane, S. (2002). “The Relationship Between Car Ownership and Public Transport Provision: A Case Study of Hong Kong,” Transport Policy, 9(1), 29–39.

  4. Fujii, S. and Kitamura, R. (2000). “Evaluation of Trip-Inducing Effects of New Freeways Using a Structural Equations Model System of Commuters’ Time Use and Travel,” Transportation Research Part B, 34, 339–354.

  5. Handy, S. (2002). “Travel Behaviour-Land Use Interactions: An Overview and Assessment of the Research,” in Hani S. Mahmassani (ed.), In Perpetual Motion: Travel Behavior Research Opportunities and Application Challenges, Pergamon Press, Oxford, UK.

  6. Holtzclaw, J., Clear, R., Dittmar, H., Goldstein, D., and Haas, P. (2002) “Location Efficiency: Neighborhood and Socio-Economic Characteristics Determine Auto Ownership and Use—Studies in Chicago, Los Angeles, and San Francisco,” Transportation Planning and Technology, 25(1), 1–27.

  7. Lund, H. (2006). “Reasons for Living in a Transit Oriented Development, and Associated Transit Use,” Journal of the American Planning Association, 72(3), 357–366.

  8. Cao, X., Mokhtarian, P.L., and Handy, S. (2009) “Examining the Impacts of Residential Self-Selection on Travel Behaviour: A Focus on Empirical Findings,” Transport Reviews, 29(3), 359–395.

  9. Mokhtarian, P. and Cao, X. (2008). “Examining the Impacts of Residential Self-Selection on Travel Behavior: A Focus on Methodologies,” Transportation Research Part B, 42(3), 204–228.

  10. Zhou, B. and Kockelman, K. (2008) “Self-Selection in Home Choice: Use of Treatment Effects in Evaluating the Relationship Between the Built Environment and Travel Behavior,” Transportation Research Record 2077, 106–112, Transportation Research Board, Washington, DC.

  11. Frank, L., Saelens, B., Powell, K.E., and Chapman, J.E. (2007). “Stepping Towards Causation: Do Built Environments or Neighborhood and Travel Preferences Explain Physical Activity, Driving, and Obesity?” Social Sciences and Medicine, 65(9), 1898–1914.

  12. Bento, A., Cropper, M., Mobarak, A., and Vinha, K. (2005). “The Effects of Urban Spatial Structure on Travel Demand in the United States,” The Review of Economics and Statistics, 87(3), 466–478.

  13. Aditjandra, P.T., Cao, X., and Mulley, C. (2012). “Understating Neighbourhood Design Impact on Travel Behavior: An Application of Structural Equations Model to a British Metropolitan Data,” Transportation Research Part A, 46, 22–32.

  14. Cao, X., Mokhtarian, P.L., and Handy, S. (2007). “Do Changes in Neighborhood Characteristics Lead to Changes in Travel Behavior? A Structural Equations Modeling Approach,” Transportation, 34(5), 535–556.

  15. Newbold, K.B., Scott, D., Spinney, J.E.L., Kanaroglou, P., and Paez, A. (2005). “Travel Behavior Within Canada's Older Population: A Cohort Analysis,” Journal of Transport Geography, 13(4), 340–351.

  16. Polk, M. (2003). “Are Women Potentially More Accommodating than Men to a Sustainable Transportation System in Sweden?” Transportation Research Part D: Transport and Environment, 8(2), 75–95.

  17. Polk, M. (2004). “The Influence of Gender on Daily Car Use and on Willingness to Reduce Car Use in Sweden,” Journal of Transport Geography, 12(3), 185–195.

  18. Moriarty, P. and Honnery, D. (2005). “Determinants of Urban Travel in Australia,” Proceedings of the 28th Australasian Transport Research Forum (ATRF). Sydney, Australia.

  19. Best, H. and Lanzendorf, M. (2005). “Division of Labour and Gender Differences in Metropolitan Car Use: An Empirical Study in Cologne, Germany,” Journal of Transport Geography, 13(2), 109–121.

  20. Ryley, T. (2005). “Use of Non-Motorised Modes and Life Stage in Edinburgh,” Journal of Transport Geography, 14(5), 367–375.

  21. Dieleman, F.M., Dijst, M., and Burghouwt, G. (2002). “Urban Form and Travel Behaviour: Micro-level Household Attributes and Residential Context,” Urban Studies, 39(3), 507–527.

  22. Giuliano, G. (2003). “Travel, Location and Race/Ethnicity,” Transportation Research Part A: Policy and Practice, 37(4), 351–372.

  23. Giuliano, G. and Narayan, D. (2003). “Another Look at Travel Patterns and Urban Form: The U.S. and Great Britain,” Urban Studies, 11(40), 2295–2312.

  24. Giuliano, G. and Dargay, J. (2006). “Car Ownership, Travel and Land Use: A Comparison of the U.S. and Great Britain,” Transportation Research Part A: Policy and Practice, 40(2), 106–124.

  25. Bomberg, M. and Kockelman, K. (2011). “Traveler Response to the 2005 Gas Price Spike,” in B. Mendex and J. Pena (eds.), Household Energy: Economics, Consumption and Efficiency, NOVA Science Publishers, Inc, Hauppauge, NY.

  26. Boarnet, M. and Crane, R. (2001). “The Influence of Land Use on Travel Behavior: Specification and Estimation Strategies,” Transportation Research Part A: Policy and Practice, 35(9), 823–845.

  27. TCRP. (2004). Traveler Response to Transportation System Changes, Chapter 13: Parking Pricing and Fees, Transit Cooperative Research Program. Obtained from: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c13.pdf.

  28. TCRP. (2003). Traveler Response to Transportation System Changes, Chapter 18: Parking Management and Supply. Obtained from: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c18.pdf.

  29. Schlich, R. and Axhausen, K.W. (2003). “Habitual Travel Behaviour: Evidence from a Six-Week Travel Diary,” Transportation, 30(1), 13–36.

  30. Cherchi, E. and Manca, F. (2011). “Accounting for Inertia in Modal Choices: Some New Evidence Using a RP/SP Dataset,” Transportation, 38(4), 679–695.

  31. Chorus, C.G., Molin, E.J.E., Van Wee, B., Arentze, T.A., and Timmermans, H.J.P. (2006). “Responses to Transit Information Among Car-Drivers: Regret-Based Models and Simulations,” Transportation Planning and Technology, 29(4), 249–271.

  32. Srinivasan, K.K. and Mahmassani, H.S. (2000). “Modeling Inertia and Compliance Mechanisms in Route Choice Behavior Under Real-Time Information,” Transportation Research Record 1725, 45–53, Transportation Research Board, Washington, DC.

  33. Jan, O., Horowitz, A.J., and Peng, Z.R. (2000). “Using Global Positioning System Data to Understand Variations in Path Choice,” Transportation Research Record 1725, 37–44, Transportation Research Board, Washington, DC.

  34. Antonisse, R.W., Daly, A.J., and Ben-Akiva, M. (1989). “Highway Assignment Method Based on Behavioral Models of Car Drivers’ Route Choice,” Transportation Research Record 1220, 1–11, Transportation Research Board, Washington, DC.

  35. Abdel-Aty, M.A., Jovanis, P.P., and Kitamura, R. (1996). “The Impact of Advanced Transit Information on Commuters’ Mode Changing,” Journal of Intelligent Transportation Systems, 3(2), 129–146.

  36. Mahmassani, H.S. and Stephan, D.G. (1988). “Experimental Investigation of Route and Departure Time Choice Dynamics of Urban Commuters,” Transportation Research Record 1203, 69–84, Transportation Research Board, Washington, DC.

  37. Polydoropoulou, A., Ben-Akiva, M., and Kaysi, I. (1994). “Influence of Traffic Information on Drivers’ Route Choice Behavior,” Transportation Research Record 1453, 56–65, Transportation Research Board, Washington, DC.

  38. Khattak, A.J., Schofer, J.L., and Wang, M.H. (1995). “A Simple Time Sequential Procedure for Predicting Freeway Incident Duration,” Journal of Intelligent Transportation Systems, 2(2), 113–138.

  39. Srinivasan, K.K. and Mahmassani, H.S. (2002). Dynamic Decision and Adjustment Processes in Commuter Behavior Under Real-Time Information, Report No. SWUTC/02/167204-1, Southwest University Regional Center, University of Texas, Austin, TX.

  40. Mahmassani, H.S. and Herman, R. (1990). “Interactive Experiments for the Study of Trip Maker Behaviour Dynamics in Congested Commuting Systems,” Developments in Dynamic and Activity-Based Approaches to Travel Analysis, 272–298, Gower, Aldershot, England.

  41. Mahmassani, H.S. (1997). “Dynamics of Commuter Behaviour: Recent Research and Continuing Challenges,” Understanding Travel Behaviour in an Era of Change, 279–313.

  42. Avineri, E. and Prashkey, J.N. (2005). “Sensitivity to Travel Time Variability: Travelers’ Learning Perspective,” Transportation Research Part C, 13, 157–183.

  43. Avineri, E. and Prashker, J.N. (2006). “The Impact of Travel Time Information on Travelers’ Learning Under Uncertainty,” Transportation, 33, 393–408.

  44. Kraan, M., Mahmassani, H., and Huynh, N. (2000). “Traveler Responses to Advanced Traveler Information Systems for Shopping Trips: Interactive Survey Approach,” Transportation Research Record 1725, (1), 116–123, Transportation Research Board, Washington, DC.

  45. Hensher, D.A. and King, J. (2001). “Parking Demand and Responsiveness to Supply, Pricing and Location in the Sydney Central Business District,” Transportation Research Part A: Policy and Practice, 35(3), 177–196.

  46. Handy, S., Weston, L., and Mokhtarian, P.L. (2005). “Driving by Choice or Necessity?” Transportation Research Part A: Policy and Practice Positive Utility of Travel, 39(2–3), 183–203.

  47. Puget Sound Regional Council. (2008). Travel Choices Study: Summary Report, Seattle, WA. Obtained from: http://www.psrc.org/projects/trafficchoices/summaryreport.pdf.

  48. Gupta, S. and Kockelman, K. (2006). “Road Pricing Simulations: Traffic, Land Use, and Welfare Impacts for Austin, Texas,” Transportation Planning & Technology, 29(1), 1–23.

  49. Gulipalli, S. and Kockelman, K. (2008). “Credit-Based Congestion Pricing: A Dallas-Fort Worth Application,” Transport Policy,” 15(1), 23–32.

  50. Saleh, W. and Farrell, S. (2005). “Implications of Congestion Charging for Departure Time Choice: Work and Non-Work Schedule Flexibility,” Transportation Research Part A, 39, 773–791.

  51. TCRP. (2006). Traveler Response to Transportation System Changes, Chapter 2: HOV Facilities. Obtained from: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c2.pdf. Site last accessed December 1, 2011.

  52. Cervero, R. and Kockelman, K. (1998). “Travel Demand and the 3Ds: Density, Diversity, and Design,” Transportation Research Part D, 2(3), 199–219.

  53. Soltani, A. and Primerano, F. (2005). “The Effects of Community Design,” Proceedings of the 28th Australasian Transport Research Forum (ATRF), Sydney, Australia.

  54. Naess, P. (2003). “Urban Structures and Travel Behaviour—Experiences from Empirical Research in Norway and Denmark,” European Journal of Transport and Infrastructure Research, 3(2), 155–178.

  55. Naess, P. and Jensen, O. (2004). “Urban Structure Matters, Even in a Small Town,” Journal of Environmental Planning and Management, 47(1), 35–57.

  56. Cervero, R. (2002). “Built Environments and Mode Choice: Toward a Normative Framework,” Transportation Research Part D: Transport and Environment, 7(4), 265–284.

  57. Gärling, T. and Axhausen, K.W. (2003). “Introduction: Habitual Travel Choice,” Transportation, 30(1), 1–11.

  58. Mahmassani, H.S. and Chang, G.L. (1986). “Experiments with Departure Time Choice Dynamics of Urban Commuters,” Transportation Research Part B: Methodological, 4(20), 297–320.

  59. Bayarma, A., Kitamura, R., and Susilo, Y.O. (2007). “Recurrence of Daily Travel Patterns: Stochastic Process Approach to Multiday Travel Behavior,” Transportation Research Record 2021, 55–63, Transportation Research Board, Washington, DC.

  60. Charles River Associates. (1978). On the Development of a Theory of Traveler Attitude-Behavior Interrelationships, Vol III: Executive Summary: Overview of Methods, Results, and Conclusions, U.S. Department of Transportation, Washington, DC.

  61. Bamberg, S. (2000). “The Promotion of New Behavior by Forming an Implementation Intention: Results of a Field Experiment in the Domain of Travel Mode Choice,” Journal of Applied Social Psychology, 30(9), 1903–1922.

  62. Schönfelder, S. and Axhausen, K.W. (2003). “Activity Spaces: Measures of Social Exclusion?” Transport Policy, 10(4), 273–286.

  63. Ortuzar, J. de D. and Willumsen, L.G. (2001). Modelling Transport, Wiley, Chichester, United Kingdom.

  64. Simon, H. (1959). “A Behavioral Model of Rational Choice,” Quarterly Journal of Economics, 69, 99–118.

  65. Mahmassani, H.S. and Chang, G.L. (1987). “On Boundedly Rational User Equilibrium in Transportation Systems,” Transportation Science, 21(2), 89–99.

  66. Sheehan, R. (2010). The Future of Transportation: Smart Cars/Smart Roads, Presentation at the 2010 APWA Annual Congress and Exposition, Boston, MA.

  67. Ewing, R. and Cervero, R. (2010). “Travel and the Built Environment: A Meta-Analysis,” Journal of the American Planning Association, 76(3), 265–294.

  68. Zhang, M. (2004). “The Role of Land Use in Travel Mode Choice: Evidence from Boston and Hong Kong,” Journal of the American Planning Association, 70(3), 344–360.

  69. Litman, T.A. (2005). Land Use Impacts on Transport: How Land Use Factors Affect Travel Behavior, Victoria Transport Institute, Victoria, Canada. Obtained from: http://www.vtpi.org/landtravel.pdf. Site last accessed March 5, 2014.

  70. Levinson, D. (2012) Directions for Research in Transport and Land Use. Obtained from: http://blog.lib.umn.edu/levin031/transportationist/2012/04/directions-for-research-in-tra.html. Site last accessed March 5, 2014.

  71. Boarnet, M.G. (2011). “A Broader Context for Land Use and Travel Behavior, and a Research Agenda,” Journal of the American Planning Association, 77(3), 197–213.

  72. Cervero, R. (1994). “Transit-Based Housing in California: Evidence on Ridership Impacts,” Transport Policy, 1(3), 174–183.

  73. Salon, D. (2006). Cars and the City: An Investigation of Transportation and Residential Location Choices in New York City, Ph.D. dissertation, Department of Agricultural and Resource Economics, University of California, Davis, Davis, CA.

  74. Bhat, C.R. and Guo, J.Y. (2007). “A Comprehensive Analysis of Built Environment Characteristics on Household Residential Choice and Auto Ownership Levels,” Transportation Research Part B, 41(5), 506–526.

  75. Brownstone, D. and Golob, T. (2009). “The Impact of Residential Density on Vehicle Usage and Energy Consumption,” Journal of Urban Economics, 65(1), 91–98.

  76. Levine, J. (2006). Zoned Out: Regulation, Markets, and Choices in Transportation and Metropolitan Land Use, RFF Press, Washington, DC.

  77. Kozuki, A.T.C.Y. and Mahmassani, H.S. (2009). Information Acquisition and Social Interaction Mechanisms in Opinion Formation and Market Adoption of Transportation Services, Presented at the 88th Annual Meeting of the Transportation Research Board, Washington, DC.

  78. Abt SRBI. (2009). Rider/Non-Rider Behavior and Attitudes Survey, Final Draft Report, Chicago, IL.

  79. Loukaitou-Sideris, A., Ligget, R., and Hiseki, H. (2002). The Geography of Transit Crime: Documetation and Evaluation of Crime Incidence on and Around the Green Line Stations in Los Angeles, Working Paper, University of California Transportation Center, Berkeley, CA.

  80. Ingalls, G.L., Hartgen, D.T., and Owners, T.W. (1994). “Public Fear of Crime and its Role in Bus Transit Use,” Transportation Research Record 1433, Transportation Research Board, Washington, DC.

  81. Needle, J.A. and Cobb, R.M. (1997). “Improving Transit Security,” Transportation Research Board TCRP Synthesis 21, Transportation Research Board, Washington, DC.

  82. Painter, K. (1996). “The Influence of Street Lighting Improvements on Crime, Fear and Pedestrian Street Use, After Dark,” Landscape and Urban Planning, 35(2–3), 193–201.

  83. (2012). Crime Prevention through Environmental Design. Obtained from: http://www.cpted.net/. Site last accessed March 5, 2014.

  84. Loukaitou-Sideris, A. (1999). “Hot Spots of Bus Stop Crime: The Importance of Environmental Attributes,” Journal of the American Planning Association, 65(4), 395–411.

  85. Ferrell, C.E., Mathur, S., and Mendoza, E. (2008). “Neighborhood Crime and Non-Auto Mode Choice,” Mineta Transportation Institute Report, 7(2), 1–119.

  86. Ferrell, C.E., Mathur, S., Meek, J., and Piven, M. (2012). “Neighborhood Crime and Travel Behavior: An Investigation of the Influence of Neighborhood Crime Rates on Mode Choice—Phase 2,” Mineta Transportation Institute Report, 11(4), 1–114.

  87. Humpel, N., Owen, N., and Leslie, E. (2002). “Environmental Factors Associated with Adults’ Participation in Physical Activity: A Review,” American Journal of Preventive Medicine, 22(3), 188–199.

  88. Kim, S., Ulfarsson, G.F., and Hennessy, J.T. (2007). “Analysis of Light Rail Rider Travel Behavior: Impacts of Individual, Built Environment, and Crime Characteristics on Transit Access,” Transportation Research Part A, 41(6), 511–522.

  89. Smith, R., Reed, S., and Baker, S. (2010). “Street Design: Part 1—Complete Streets,” Public Roads, 74(1).

  90. Bento, A.M., Cropper, M.L., Mobarak, A.M., and Vinha, K. (2003). “The Impact of Urban Spatial Structure on Travel Demand in the United States,” Working Paper 3007, The World Bank, Washington, DC.

  91. Ewing, R., Greenwald, M.J., Zhang, M., Walters, J., Feldman, M., Cervero, R., and Thomas, J. (2009). Measuring the Impact of Urban Form and Transit Access on Mixed Use Site Trip Generation Rates—Portland Pilot Study, U.S. Environmental Protection Agency, Washington, DC.

  92. Frank, L.D., Kavage, S., Greenwald, M., Chapman, J., and Bradley, M. (2009). I-PLACE3S Health & Climate Enhancements and Their Application in King County, King County HealthScape, Seattle, WA.

  93. Kitamura, R., Mokhtarian, P.L., and Laidet, L. (1997). “A Micro-Analysis of Land Use and Travel in Five Neighborhoods in San Francisco Bay Area,” Transportation, 24(2), 125–158.

  94. Rajamani, J., Bhat, C., Handy, S., Knaap, G., and Song, Y. (2003). “Assessing Impact of Urban Form Measures on Nonwork Trip Mode Choice After Controlling for Demographic and Level-of-Service Effects,” Transportation Research Record 1831, 158–165, Transportation Research Board, Washington, DC.

  95. Frank, L.D. and Engelke, P. (2005). “Multiple Impacts of the Built Environment on Public Health: Walkable Places and the Exposure to Air Pollution,” International Regional Science Review, 28(2), 193–216.

  96. Hedel, R. and Vance, C. (2007). Impact of Urban Form on Automobile Travel: Disentangling Causation from Correlation, Presented at the 86th Annual Meeting of the Transportation Research Board, Washington, DC.

  97. Naess, P. (2005). “Residential Location Affects Travel Behavior—But How and Why? The Case of Copenhagen Metropolitan Area,” Progress in Planning, 63(1), 167–257.

  98. Pushkar, A.O., Hollingworth, B.J., and Miller, E.J. (2000). A Multivariate Regression Model for Estimating Greenhouse Gas Emissions from Alternative Neighborhood Designs, Presented at the 79th Annual Meeting of the Transportation Research Board, Washington, DC.

  99. Cervero, R. and Murakami, J. (2010). “Effects of Built Environments on Vehicle Miles Traveled: Evidence from 370 US Urbanized Areas,” Environment and Planning A, 42(2), 400–418.

  100. Chatman, D.G. (2009). “Residential Self-Selection, the Built-Environment, and Nonwork Travel: Evidence Using New Data and Methods,” Environment and Planning A, 41(5), 1072–1089.

  101. Ben-Akiva, M., Walker, J., Bernardino, A.T., Gopinath, D.A., Morikawa, T., and Polydoropoulou, A. (2002). “Integration of Choice and Latent Variable Models,” In Perpetual Motion: Travel Behavior Opportunities and Application Challenges, 431470, International Association for Travel Behavior Research, Washington, DC.

  102. Walk Score. (2012). Walk Score APIs Overview. Obtained from: http://www.WalkScore.com/professional/walk-score-apis.php. Site last accessed May 12, 2012.

  103. Mahmassani, H.S., Hu, T., Peeta, S., and Ziliaskopoulos, A. (1994). Development and Testing of Dynamic Traffic Assignment and Simulation Procedures for ATIS/ATMS Applications, Technical Report No. DTFH61-90-R-00074-FG, Center for Transportation Research, University of Texas at Austin, Austin, TX.

  104. CMAP. (2008). Traveler Tracker Survey, Chicago, IL. Obtained from: http://www.cmap.illinois.gov/travel-tracker-survey. Site last accessed April 1, 2013.

  105. METRA. (2007). 2007 Metra Program and Budget. Obtained from: http://metrarail.com/ metra/en/home/about_metra/planning_records_reports/finance_budget.html. Site last accessed April 29, 2014.

  106. Bhat, C.R. and Gossen, R. (2002). A Mixed Multinomial Logit Model Analysis of Weekend Recreational Episode Type Choice, Technical Report, Department of Civil Engineering, University of Texas at Austin, Austin, TX.

  107. Handy, S.L., Boarnet, M.G., Ewing, R., and Killingsworth, R.E. (2002). “How the Built Environment Affects Physical Activity: Views from Urban Planning,” American Journal of Preventive Medicine, 23(2S), 64–73.

  108. Sallis, J.R., Frank, L.D., Saelens, B.E., and Kraft, M.K. (2004). “Active Transportation and Physical Activity: Opportunities for Collaboration on Transportation and Public Health Research,” Transportation Research Part A, 38(4), 349–268.

  109. Vautin, D. and Walker, J.L. (2011). Transportation Impacts of Information Provision & Data Collection via Smartphones, Presented at the 90th Annual Meeting of the Transportation Research Board, Washington, DC.

  110. Taylor, T.L. (2006). Play Between Worlds: Exploring Online Game Culture, MIT Press, Cambridge, MA.

  111. Mahmassani, H.S., Chen, R.B., Huang, Y., Williams, D., and Contractor, N. (2010). “Time to Play? Activity Engagement in Multiplayer Online Role Playing Games,” Transportation Research Record 2157, 129–137, Transportation Research Board, Washington, DC.

  112. Giuliano, G. (1998). “Information Technology, Work Pattern and Intra-Metropolitan Location: A Case Study,” Urban Studies, 35(7), 1077–1095.

  113. Golob, T.F. and Regan, A.C. (2001). “Impact of Information Technology on Personal Travel and Commercial Vehicle Operations: Research Challenges and Opportunities,” Transportation Research C, 9(2), 87–121.

  114. Mahmassani, H.S., Yen, J-R., Herman, R., and Sullivan, M. (1993). “Employee Attitudes and Stated Preferences Towards Telecommuting: An Exploratory Analysis,” Transportation Research Record 1413, 31–41, Transportation Research Board, Washington, DC.

  115. Mokhtarian, P.L. (2003). “Telecommunications and Travel: the Case for Complementarity,” Journal of Industrial Ecology, 6(2), 43–57.

  116. Mokhtarian, P.L., Collantes, G.O., and Carsten, G. (2004). “Telecommuting, Residential Location, and Commute Distance Traveled: Evidence from State of California Employees,” Environment and Planning A, 36, 1879–1897.

  117. DC Capital Bikeshare. (2013). Obtained from: http://www.capitalbikeshare.com/. Site last accessed April 26, 2013.

  118. Department of Environmental Services. (2012). Arlington Transportation Demand Management Strategic Plan, FY 2013–FY 2040, Arlington, VA.

  119. Co, S. (2011) Regional Bicycle Working Group and Regional Pedestrian Committee, San Francisco, CA. Obtained from: http://apps.mtc.ca.gov/events/agendaView.akt?p=1769. Site last accessed March 5, 2014.

  120. Southern California Association of Governments. (2009). Maximizing Mobility in Los Angeles—First and Last Mile Strategies, Final Report, Los Angeles, CA.

  121. Doyle, G.L., Liban, E.C., Goldsmith, L., Ledbetter, L., Marcelo, M., and Cooper, K.B. (2012). Bicycle-Rail Trip Analysis and Greenhouse Gas Emissions Reduction Focused Study, Presented at the 91st Annual Meeting of the Transportation Research Board, Washington DC.

  122. Metropolitan Washington, Council of Governments. (2010). MWCOG Bikesharing Analysis of the DC Region. Obtained from: http://www.mwcog.org/uploads/committee-documents/bV5YWlxe20100820155649.pdf. Site last accessed March 25, 2013.

  123. Bay Area Rapid Transit. (2012). BART Bicycle Plan: Modeling Access to Transit, Eisen/Letunic in association with Fehr and Peers and Nelson/Nygaard, San Francisco, CA.

  124. Bay Area Rapid Transit. (2012). BART Bicycle Investment Tool, San Francisco, CA. Obtained from: http://bart.gov/guide/bikes/investment.aspx. Site last accessed March 5, 2014.

  125. Flamm, B.J. (2012). “Determinants of Bicycle-on-Bus Boardings: A Case Study of the Greater Cleveland RTA,” Journal of Public Transportation, 16(2).

  126. Koppelman, F.S. and Pas, E.I. (1980). “Travel-Choice Behavior: Models of Perceptions, Feelings, Preference, and Choice,” Transportation Research Record 765, 26–33, Transportation Research Board, Washington, DC.

  127. McFadden, D. (1986). “The Choice Theory Approach to Market Research,” Marketing Science, 5(4), 275–297.

  128. Golob, T. (2003). “Structural Equation Modeling for Travel Behavior Research,” Transportation Research Part B: Methodological, 37(1), 1–25.

  129. Ben-Akiva, M., McFadden, D., Garling, T., Gopinath, D., Walker, J., Bolduc, D., Boersch-Supan, A., Delquie, P., Larichev, O., Morikawa, T., Polydoropoulou, A., and Rao, V. (1999). “Extended Framework for Modeling Choice Behavior,” Marketing Letters, 10(3), 187–203.

  130. Ben-Akiva, M., McFadden, D., Train, K., Walker, J., Bhat, C., Bierlaire, M., Bolduc, D., Boersch-Supan, A., Brownstone, D., Bunch, D., Daly, A., de Palma, A., Gopinath, D., Karlstrom, A., and Munizaga, M.A. (2002). “Hybrid Choice Models: Progress and Challenges,” Marketing Letters, 13(3), 163–175.

  131. Scheiner, J. and Holz-Rau, C. (2007) “Travel Mode Choice: Affected by Objective or Subjective Determinants?” Transportation, 34, 487–511.

  132. Van Acker, V. and Witlox, F. (2010) “Car Ownership as a Mediating Variable in Car Travel Behaviour Research Using a Structural Equation Modelling Approach to Identify its Dual Relationship,” Journal of Transport Geography, 18(1), 65–74.

  133. Van Acker, V., Mokhtarian, P.L., and Witlox, F. (2011) “Going Soft: On How Subjective Variables Explain Modal Choices for Leisure Travel,” European Journal of Transport and Infrastructure Research, 11, 115–146.

  134. Vredin Johansson, M., Heldt, T., and Johansson, P. (2006). “The Effects of Attitudes and Personality Traits on Mode Choice,” Transportation Research Part A: Policy and Practice, 40(6), 507–525.

  135. Espino, R., Roman, C., and Ortuzar, J. (2006). “Analyzing Demand for Suburban Trips: A Mixed RP/SP Model with Latent Variables and Interaction Effects,” Transportation, 33(3), 241–261.

  136. Abou-Zeid, M., Ben-Akiva, M., Bierlaire, M., Choudhury, C., and Hess, S. (2010). “Attitudes and Value of Time Heterogeneity,” Applied Transport Economics: A Management and Policy Perspective, 523–545.

  137. Rogers, E.M. (2003). Diffusion of Innovations, 5th Ed., Free Press, New York, NY.

  138. Tversky, A. and Kahneman, D. (1974). “Judgment Under Uncertainty: Heuristics and Biases,” Science, 185, 1124–1131.

  139. Ebbinghaus. (1913). Memory: A Contribution to Experimental Psychology, Columbia Univeristy, New York City, NY.

  140. Talebpour, A., Mahmassani, H.S., and Hamdar, S.H. (2013). Speed Harmonization: Effectiveness Evaluation under Congested Conditions, Proceedings of the 92nd Annual Meeting of the Transportation Research Board, Washington, DC.

  141. Wilensky, U. (1999). NetLogo, Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

  142. Federal Highway Administration. (2012). Concept Development and Needs Identification for Intelligent Network Flow Optimization (INFLO)—Concept of Operations Walkthrough Workbook, U.S. Department of Transportation, Washington, DC.

  143. Waller, S.T., Ng, M.W., Ferguson, E., Nezamuddin, N., and Sun, D. (2009). Speed Harmonization and Peak-Period Shoulder Use to Manage Urban Freeway Congestion, Report No. FHWA/TX-10/0-5913-1, Federal Highway Administration, Washington, DC.

  144. Federal Highway Administration. (2012). AERIS Transformative Concepts and Applications Descriptions, U.S. Department of Transportation, Washington, DC.

  145. Chang, G.L, Park, S.Y., and Paracha, J. (2011) “Intelligent Transportation System Field Demonstration: Integration of Variable Speed Limit Control and Travel Time Estimation for a Recurrently Congested Highway,” Transportation Research Record 2243, 55–66, Transportation Research Board, Washington, DC.

  146. Austroads. (2010). Best Practice for Variable Speed Limits: Literature Review, AP-R342/09, Austroads Incorporated, Sydney, Australia.

  147. Fuhs, C. (2010) Synthesis of Active Traffic Management Experiences in Europe and the United States, Report No. FHWA-HOP-10-031, Federal Highway Administration, Washington, DC.

  148. Kwon, E., Brannan, D., Shouman, K., Isackson, C., and Arseneau, B. (2007). Field Evaluation of a Variable Advisory Speed Limit System for Reducing Traffic Conflicts at Work Zones, Presented at the 84th Annual Meeting of the Transportation Research Board, Washington, DC.

  149. Bham, G.H., Long, S., Baik, H., Ryan, T., Gentry, L., Lall, K., Arezoumandi, M., Liu, D., and Schaeffer, B. (2010). Evaluation of Variable Speed Limits on I-270/I-255 in St. Louis, Missouri Department of Transportation, Jefferson City, MO.

  150. The United Kingdom Highway Agency. (2007). M25 Controlled Motorway Summary Report, Department for Transport, London, UK.

  151. Talebpour, A., Mahmassani, H.S., and Kim, J. (2013) Toward Capturing Sources of Travel Time Unreliability in Microscopic Traffic Models: Driver Heterogeneity, Flow Breakdown, and Crash Occurrence, Proceedings of the 92nd Annual Meeting of the Transportation Research Board, Washington, DC.

  152. Hegyi, A., Schutter, B.D., and Hellendoorn, J. (2005). “Optimal Coordination of Variable Speed Limits to Suppress Shock Waves,” IEEE Transactions on Intelligent Transportation Systems, 6(1), 167–174.

  153. Hegyi, A., Hoogendoorn, S.P., Schreuder, M., Stoelhorst, H., and Viti, F. (2010). SPECIALIST: A Dynamic Speed Limit Control Algorithm Based on Shock Wave Theory, Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems, Madeira Island, Portugal.

  154. Carlson, R.C., Papamichail, I., and Papageorgiou, M. (2011) “Local Feedback-Based Mainstream Traffic Flow Control on Motorways Using Variable Speed Limits,” IEEE Transactions of Intelligent Transportation Systems, 12(4), 1261–1276.

  155. Carlson, R.C., Papamichail, I., and Papageorgiou, M. (2011). Comparison of Local Feedback Controllers for the Mainstream Traffic Flow on Freeways Using Variable Speed Limits, Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems, Washington, DC.

  156. Hegyi, A. and Hoogendoorn, S.P. (2008). Dynamic Speed Limit Control to Resolve Shock Waves on Freeways—Field Test Results of the SPECIALIST Algorithm, Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems, Beijing, China.

  157. Lin, P.W., Kang, K.P., and Chang, G.L. (2004) “Exploring the Effectiveness of Variable Speed Limit Controls on Highway Work-Zone Operations,” Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 8(3), 155–168.

  158. Zheng, Z., Ahn, S., Chen, D., and Laval, J. (2011). “Applications of Wavelettransform for Analysis of Freeway Traffic: Bottlenecks, Transient Traffic, and Traffic Oscillations,” Transportation Research Part B: Methodological, 45(2), 372–384.

  159. Allaby, P., Hellinga, B., and Bullock, M. (2007). “Variable Speed Limits: Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications,” IEEE Transactions on Intelligent Transportation Systems, 8(4), 671–680.

  160. Hamdar, S.H., Treiber, M., Mahmassani, H.S., and Kesting, A. (2008). “Modeling Driver Behavior as Sequential Risk-Taking Task,” Transportation Research Record 2088, 208–217, Transportation Research Board, Washington, DC.

  161. Google Maps. (2012). Geographic characterization of the selected segment in Chicago, IL. Data date: 2012. Data date: 2012. Generated via Google Maps online, obtained from: http://maps.google.com/. Generated January 31, 2012.

  162. Hamdar, S.H. (2009). Modeling Driver Behavior As a Stochastic Hazard-Based Risk Taking Process, PhD Thesis, Northwestern University, Evanston, IL.

  163. Hamdar, S.H. and Mahmassani, H.S. (2009). “Life in the Fast Lane: Duration-Based Investigation of Driver Behavior Differences Across Freeway Lanes,” Transportation Research Record 2124, 89–102, Transportation Research Board, Washington, DC.

  164. Kahneman, D. and Tversky, A. (1979). “Prospect Theory: An Analysis of Decision Under Risk,“ Econometrica, 47(2), 263–291.

  165. Chaudhary, N.A., Zongzhong T., Messer, C.J., and Chu, C. (2004). Ramp Metering Algorithms and Approaches for Texas, Report No. FHWA/TX-05/0-4629-1, Federal Highway Administration, Washington, DC.

  166. Talebpour, A., Mahmassani, H.S., and Hamdar, S.H. (2012). “Safety First: Assessing Congestion Effects on Experienced Driver Risk Using a Microsimulation Approach,” Transportation Research Record 2316, 106–113, Transportation Research Board, Washington, DC.

  167. Kim, J. and Mahmassani, H.S. (2011). “Correlated Parameters in Driving Behavior Models: Car-Following Example and Implications for Traffic Simulation,” Transportation Research Record 2249, 62–77, Transportation Research Board, Washington, DC.

  168. Pisano, P. and Goodwin, L. (2002). Surface Transportation Weather Applications, Presented at the 2002 Institute of Transportation Engineers Annual Meeting, Washington, DC.

  169. Mixon-Hill Inc., et al. (2005). Clarus Weather System Design: Detailed System Requirements Specification. Obtained from: http://www.clarusinitiative.org/documents/Final_Clarus_System_Detailed_Requirements.pdf.

  170. Pisano, P., Alfelor, R.M., Pol, J.S., Goodwin, L.C., and Stern, A.D. (2005). Clarus—The Nationwide Surface Transportation Weather Observing and Forecasting System, Presented at the 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology. Obtained from: http://ams.confex.com/ams/pdfpapers/83961.pdf. Site last accessed March 5, 2014.

  171. Mahmassani, H.S., Dong, J., Kim, J., Chen, R.B., and Park, B. (2009). Incorporating Weather Impacts in Traffic Estimation and Prediction Systems, Report No. FHWA-JPO-09-065, Federal Highway Administration, Washington, DC.

  172. Mahmassani, H.S., Kim, J., Hou, T., Zockaie, A., Saberi, M., Jiang, L., Verbas, Ö., Cheng, S., Chen, Y., and Haas, R. (2012). Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System,Report No. FHWA-JPO-12-055, Federal Highway Administration, Washington, DC.

  173. Mahmassani, H.S. (1998). “Dynamic Traffic Simulation and Assignment: Models, Algorithms, and Applications to ATIS/ATMS Evaluation and Operation,” Operations Research and DecisionAid Methodologies in Traffic and Transportation Management, NATO ASI Series, 104–132.

  174. Zhou, X., Qin, X., and Mahmassani, H.S. (2002). “Dynamic Origin-Destination Demand Estimation with Multiday Link Traffic Counts for Planning Applications,” Transportation Research Record 1831, 30–38, Transportation Research Board, Washington, DC.

  175. Dong, J., Mahmassani, H.S., and Lu, C.C. (2006). “How Reliable is this Route?: Predictive Travel Time and Reliability for Anticipatory Traveler Information Systems,” Transportation Research Record 1980, 117–125, Transportation Research Board, Washington, DC.

  176. Luoma, J., Rämä, P., Penttinen, M., and Anttila, V. (2000). “Effects of Variable Message Signs for Slippery Road Conditions on Reported Driver Behaviour,” Transportation Research Part F, 3, 75–84.

  177. Rämä, P. (2001). “Effects of Weather-Controlled Message Signing on Driver Behavior,” PhD Thesis, VTT Publications, 447.

  178. Hogema, J.H. and van der Horst, R. (1997). “Evaluation of A16 Motorway Fog-Signaling System with Respect to Driving Behaviour,” Transportation Research Record 1573, 63–67, Transportation Research Board, Washington, DC.

  179. Cooper, B.R. and Sawyer, H. (1993). Assessment of M25 Automatic Fog-Warning System, Final Report, Report No. TRL-PR-93-16, Transport Research Laboratory, Crowthorne, South Africa.

  180. Gopalakrishna, D., Cluett, C., Kitchener, F., and Balke, K. (2011). Developments in Weather Responsive Traffic Management Strategies, Report No. FHWA-JPO-11-086, Federal Highway Administration, Washington, DC.

  181. Abdel-Aty, M. (2003). “Analysis of Driver Injury Severity Levels at Multiple Locations Using Ordered Probit Models,” Journal of Safety Research34(5), 597–603.

  182. Srinivasan, K.K. and Mahmassani, H.S. (1999). “Role of Congestion and Information in Trip-Makers’ Dynamic Decision Processes: Experimental Investigation,” Transportation Research Record 1676, 44–52, Transportation Research Board, Washington, DC.

  183. Bowman, J.L. and Ben-Akiva, M.E. (2011). “Activity-Based Disaggregate Travel Demand Model System with Activity Schedules,” Transportation Research Part A: Policy and Practice, 35(1), 1–28.

  184. Google Maps. (2012). Chicago, IL, study area and adjacent ASOS stations. Data date: 2012. Generated by: Hani Mahmassani via Google Maps online, obtained from http://maps.google.com/. Generated October 1, 2012.

  185. Google Maps. (2012). Selected detector locations in Chicago, IL. Data date: 2012. Generated by: Hani Mahmassani via Google Maps online, obtained from http://maps.google.com/. Generated October 1, 2012.

  186. Travel Tracker Survey. Chicago Metropolitan Agency for Planning, Chicago, IL. Obtained from: http://www.cmap.illinois.gov/data/transportation/travel-tracker-survey.

  187. National Transit Database. Federal Transit Administration, Charlottesville, VA. Obtained from: http://www.ntdprogram.gov/ntdprogram/.

  188. Domencich, T. and McFadden, D. (1975). Urban Travel Demand: A Behavioral Analysis, North-Holland, Amsterdam.

  189. Ben-Akiva, M. and Lerman, S. (1985). Discrete Choice Analysis, MIT Press, Cambridge, MA.

  190. Noland, R.B. and Small, K.A. (1995). “Travel-Time Uncertainty, Departure Time Choice, and the Cost of Morning Commutes,” Transportation Research Record 1493, 150–158, Transportation Research Board, Washington, DC.

  191. Schrank, D.L., Turner, S.M., and Lomax, T.J. (1993). Estimates of Urban Roadway Congestion—1990, Report No. FHWA/TX-90/1131-5, Texas Transportation Institute, Texas A&M University, College Station, TX.

  192. Knapp, K.K. (2000). Investigation of Volume, Safety, and Vehicle Speeds During Winter Storm Events, 57–64, Ninth AASHTO/TRB Maintenance Management Conference, Juneau, AK.

  193. McBride, J.C., Benlangie, M.C., Kennedy, W.J., McCornkie, F.R., Steward, R.M., Sy, C.C., and Thuet, J.H. (1977). Economic Impacts of Highway Snow and Ice Control, Report No. FHWA-RD-77-95, Federal Highway Administration, Washington, DC.

  194. Hanbali, R.M. (1994). “Economic Impact of Winter Road Maintenance on Road Users,” Transportation Research Record 1442, 151–161, Transportation Research Board, Washington, DC.

 

 

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