National Academies Press: OpenBook

Activity-Based Travel Demand Models: A Primer (2014)

Chapter: REFERENCES FOR PART 1

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Suggested Citation:"REFERENCES FOR PART 1." National Academies of Sciences, Engineering, and Medicine. 2014. Activity-Based Travel Demand Models: A Primer. Washington, DC: The National Academies Press. doi: 10.17226/22357.
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Suggested Citation:"REFERENCES FOR PART 1." National Academies of Sciences, Engineering, and Medicine. 2014. Activity-Based Travel Demand Models: A Primer. Washington, DC: The National Academies Press. doi: 10.17226/22357.
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Page 124
Page 125
Suggested Citation:"REFERENCES FOR PART 1." National Academies of Sciences, Engineering, and Medicine. 2014. Activity-Based Travel Demand Models: A Primer. Washington, DC: The National Academies Press. doi: 10.17226/22357.
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Page 125
Page 126
Suggested Citation:"REFERENCES FOR PART 1." National Academies of Sciences, Engineering, and Medicine. 2014. Activity-Based Travel Demand Models: A Primer. Washington, DC: The National Academies Press. doi: 10.17226/22357.
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Page 126

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121 REFERENCES FOR PART 1 Atlanta Regional Commission. 2010. ARC Activity-Based Model Visualization System. Atlanta Regional Commission, Ga. Ben-Akiva, M., and S. Lerman. 1985. Discrete Choice Analysis: Theory and Application to Travel Demand. The MIT Press, Cambridge, Mass. Bowman, J. L. 1995. Activity-Based Travel Demand Model System with Daily Activity Schedules. MS thesis. Massachusetts Institute of Technology, Cambridge, Mass. Bowman, J. L. 1998. The Day Activity Schedule Approach to Travel Demand Analysis. PhD dissertation. Massachusetts Institute of Technology, Cambridge, Mass. Bowman, J. L., M. Bradley, and J. Castiglione. 2013. Making Advanced Travel Forecasting Models Affordable Through Model Transferability. Presented at 93rd Annual Meeting of the Transportation Research Board, Washington, D.C. Cambridge Systematics. 2010. Travel Model Validation and Reasonableness Checking Manual, Second Ed. Travel Model Improvement Program, FHWA, U.S. Department of Transportation, Washington, D.C. Castiglione, J., J. Freedman, and M. Bradley. 2003. Systematic Investigation of Variability Due to Random Simulation Error in an Activity-Based Microsimulation Forecasting Model. In Transportation Research Record: Journal of the Transportation Research Board, No. 1831, Transportation Research Board of the National Academies, Washington, D.C., pp. 76–88. Castiglione, J., R. Hiatt, T. Chang, and B. Charlton. 2006. Application of Travel Demand Microsimulation Model and Equity Analysis. In Transportation Research Record: Journal of the Transportation Research Board, No. 1977, Transportation Research Board of the National Academies, Washington, D.C., pp. 35–42. Chiu, Y.-C., J. Bottom, M. Mahut, A. Paz, R. Balakrishna, T. Waller, and J. Hicks. 2011. Transportation Research Circular E-C153: Dynamic Traffi c Assignment: A Primer. Transportation Research Board of the National Academies, Washington, D.C. http:// onlinepubs.trb.org/onlinepubs/circulars/ec153.pdf.

122 Part 1: ACTIVITY-BASED TRAVEL DEMAND MODELS: A PRIMER Fehr & Peers. 2007. An Assessment of Integrated Land Use/Transportation Models. Southern California Association of Governments. Hensher, D. A., J. M. Rose, and W. H. Greene. 2005. Applied Choice Analysis: A Primer. Cambridge University Press, Cambridge, UK. Johnston, R. A., and M. C. McCoy. 2006. Assessment of Integrated Transportation/ Land Use Models. Information Center for the Environment, Department of Environmental Science and Policy, University of California, Davis. Koppelman, F. S., and C. Bhat. 2006. A Self-Instructing Course in Mode Choice Modeling: Multinomial and Nested Logit Models. U.S. Department of Transportation, Washington, D.C. Lin, D.-Y., N. Eluru, T. Waller, and C. Bhat. 2006. Integration of Activity-Based Modeling and Dynamic Traffic Assignment. In Transportation Research Record: Journal of the Transportation Research Board, No. 2076, Transportation Research Board of the National Academies, Washington, D.C., pp. 52–61. Mueller, K., and K. Axhausen. 2011. Population Synthesis for Microsimulation: State of the Art. Presented at 90th Annual Meeting of the Transportation Research Board, Washington, D.C. North Central Texas Council of Governments. 2013. NCTCOG Path Towards Advanced Analytic Tools. Travel Model Improvement Program, FHWA, U.S. Department of Transportation, Washington, D.C. http://tmiponline.org/Clearinghouse/Items/20130425_-_ NCTCOG_Path_Towards_Advanced_Analytical_Tools.aspx. Accessed Nov. 18, 2013. Parsons Brinckerhoff, Northwestern University, Mark Bradley Research and Consulting, University of California at Irvine, Resource Systems Group, University of Texas at Austin, F. Koppelman, and Geostats. 2013. SHRP2_S2-C04-RW-1: Improving our Understanding of How Highway Congestion and Price Affect Travel Demand. Transportation Research Board of the National Academies, Washington, D.C. Picado, R. 2013. A Test of Transferability: The SE Florida Activity-Based Travel Demand Model. Presented at 14th Transportation Research Board Planning Applications Confer- ence, Columbus, Ohio. Rasouli, S., T. Arentze, and H. Timmermans. 2012. Analysis of Uncertainty in Performance Indicators of a Complex Activity-Based Model: The Case of the Albatross Model System. Presented at 4th Conference on Innovations in Travel Modeling, Tampa, Fla. Resource Systems Group. 2012a. Activity-Based Modeling Forecasting and Application Session 2. Travel Model Improvement Program, FHWA, U.S. Department of Transportation, Washington, D.C. http://tmiponline.org/Clearinghouse/Items/20120223_-_ Activity-Based_Modeling_Management_-_Institutional_Session_2.aspx. Accessed Nov. 18, 2013. Resource Systems Group. 2012b. Activity-Based Modeling Forecasting and Application Session 12. Travel Model Improvement Program, FHWA, U.S. Department of Transportation, Washington, D.C. http://tmiponline.org/Clearinghouse/Items/20120930_ Activity-Based_Modeling_Forecasting_and_Application_Session_12.aspx. Accessed Nov. 18, 2013. Resource Systems Group. 2012c. The ARC and SACOG Experience with Activity- Based Models: Synthesis and Lessons Learned. Association of Metropolitan Planning Organizations, Washington, D.C.

123 REFERENCES FOR PART 1 Resource Systems Group. 2012d. Activity-Based Modeling Population Synthesis and Household Evolution Session 5. Travel Model Improvement Program, FHWA, U.S. Depart- ment of Transportation, Washington, D.C. http://tmiponline.org/activity-based-modeling- population-synthesis-and-household-evolution-session-5/. Accessed January 23, 2014. Resource Systems Group, AECOM, Mark Bradley Research and Consulting, John Bowman Research and Consulting, M. Hadi, R. Pendyala, C. Bhat, T. Waller, and North Florida Transportation Planning Organization. 2014. SHRP 2 Report S2-C10A-RW-1: Dynamic, Integrated Model System—Jacksonville-Area Application. Transportation Research Board of the National Academies, Washington, D.C. Train, K. E. 2009. Discrete Choice Methods with Simulation, Second Ed. Cambridge University Press, Cambridge, UK. Vovsha, P., M. A. Bradley, and J. L. Bowman. 2004. Activity-Based Travel Forecasting Models in the United States: Progress Since 1995 and Prospects for the Future. Presented at EIRASS Conference on Progress in Activity-Based Analysis, Vaeshartelt Castle, Maastricht, Netherlands.

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TRB’s second Strategic Highway Research Program (SHRP 2) Report S2-C46-RR-1: Activity-Based Travel Demand Models: A Primer explores ways to inform policymakers’ decisions about developing and using activity-based travel demand models to better understand how people plan and schedule their daily travel.

The document is composed of two parts. The first part provides an overview of activity-based model development and application. The second part discusses issues in linking activity-based models to dynamic network assignment models.

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