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Page 64
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2017. Developing a Method Selection Tool for Travel Forecasting. Washington, DC: The National Academies Press. doi: 10.17226/24931.
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Page 64
Page 65
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2017. Developing a Method Selection Tool for Travel Forecasting. Washington, DC: The National Academies Press. doi: 10.17226/24931.
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Page 65
Page 66
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2017. Developing a Method Selection Tool for Travel Forecasting. Washington, DC: The National Academies Press. doi: 10.17226/24931.
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Page 66
Page 67
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2017. Developing a Method Selection Tool for Travel Forecasting. Washington, DC: The National Academies Press. doi: 10.17226/24931.
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Page 67

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Final Report Project No. 08-94 64 REFERENCES California Department of Transportation. Evaluation of Traffic Simulation Model Use in the Development of Corridor System Management Plans (CSMPs). Office of System Management Planning, Sacramento, CA, 2012. http://www.caltrans.ca.gov/hq/tpp//corridor- mobility/documents/library/CSMP_Simulation_Draft_Report_2012-10-04.pdf. Accessed Feb. 1, 2017. Cambridge Systematics, Inc. Accounting for Commercial Vehicles in Urban Transportation Models, prepared for Federal Highway Administration, March 2004. Cambridge Systematics, Inc. and GeoStats, LLP. NCFRP Report 8: Freight-Demand Modeling to Support Public-Sector Decision Making. TRB, National Academy of Sciences, Washington, DC, 2010. Cervenka, K. Large-Scale Traffic Microsimulation from an MPO Perspective. Presented at 6th TRB Conference on the Application of Transportation Planning Methods, Dearborn, MI, 1997. http://ntl.bts.gov/lib/7000/7400/7484/789782.pdf. Accessed Feb. 1, 2017. Coffel, K., Parks, J, Semler, C., Sampson, D., Kachadoorian, C., Levinson, H. S. and J. L. Schofer. TCRP Report 153: Guidelines for Providing Access to Public Transportation Stations. TRB, National Research Council, Washington, DC, 2012. http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_153.pdf. Accessed Feb. 1, 2017. Donnelly, R., Erhardt, G. D., Moeckel, R. and W. A. Davidson. NCHRP Synthesis of Highway Practice 406: Advanced Practices in Travel Forecasting. TRB, National Research Council, Washington, DC, 2010. http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_syn_406.pdf. Accessed Feb. 1, 2017. Dowling, R. Skabardonis, A. and V. Alexiadis. Traffic Analysis Toolbox Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software. Pub. No. FHWA-HRT-04-040. FHWA, US Department of Transportation, 2004. http://ops.fhwa.dot.gov/trafficanalysistools/tat_vol3/vol3_guidelines.pdf. Accessed Feb. 1, 2017. Ferdous, F., Bhat, C., Vana, L., Schmitt, D., Bowman, J., Bradley, M. and R. Pendyala. Comparison of Four-Step Versus Tour-Based Models in Predicting Travel Behavior Before and After Transportation System Changes—Results Interpretation and Recommendations. Report No. FHWA/OH-2011/4. FHWA, US Department of Transportation, 2011. http://www.ce.utexas.edu/prof/bhat/REPORTS/ODOTFinalReport_18Feb2011.pdf. Accessed Feb. 1, 2017. FHWA, US Department of Transportation. The Effective Integration of Analysis, Modeling and Simulation. Pub. No. FHWA-HRT-13-036. Research, Development, and Technology Turner- Fairbank Highway Research Center, 2013. http://www.fhwa.dot.gov/publications/research/operations/13036/13036.pdf. Accessed Feb. 1, 2017.

Final Report Project No. 08-94 65 Florida Department of Transportation. Moving Ahead for Progress in the 21st Century (MAP- 21) 2014 Performance Report. A report to the Florida Congressional Delegation. March 2014. http://www.dot.state.fl.us/planning/performance/MAP-21/MAP-21PerformanceReport.pdf. Accessed Feb. 1, 2017. FTA, US Department of Transportation. STOPS – FTA’s Simplified Trips-on-Project Software. https://www.transit.dot.gov/funding/grant-programs/capital-investments/stops-%E2%80%93- fta%E2%80%99s-simplified-trips-project-software. Accessed Feb. 1, 2017. FTA, US Department of Transportation. Travel Forecasting for New Starts. https://www.transit.dot.gov/funding/grant-programs/capital-investments/travel-forecasts. Accessed Feb 2, 2017. Gannett Fleming, Inc. and AECOM USA, Inc. The Florida Guidebook for Model Application in FTA New Starts and Small Starts. Florida Department of Transportation, 2010. http://www.dot.state.fl.us/transit/Pages/ModelNewStarts2010.pdf. Accessed Feb. 1, 2017. Horowitz, A. NCHRP Synthesis of Highway Practice 358: Statewide Travel Forecasting Models. TRB, National Research Council, Washington, DC, 2006. http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_syn_358.pdf. Accessed Feb. 1, 2017. Johnston, R.A. The Urban Transportation Planning Process. In The Geography of Urban Transportation, 3rd ed. (S. Hanson and G. Giuliano, eds.), The Guilford Press, New York, NY, 2004, pp. 115–140. Khan, O. Modelling Passenger Mode Choice Behaviour Using Computer Aided Stated Preference Data. PhD dissertation. School of Urban Development, Queensland University of Technology, 2004. http://eprints.qut.edu.au/4924/1/4924_1.pdf. Accessed Feb. 1, 2017. Lemp, J. D., McWethy, L. B., and K. M. Kockelman. From Aggregate Methods to Microsimulation: Assessing the Benefits of Microscopic Activity-Based Models of Travel Demand. In Transportation Research Record: Journal of the Transportation Research Board, No. 1994, TRB, National Research Council, Washington, DC, 2007, pp. 80–88. McNally, M. G. The Four Step Model. In Handbook of Transport Modeling, 2nd ed. (D. A. Hensher and K. J. Button, eds.), Pergamon, Irvine, CA, 2000, pp. 35–52. Mishra, S., Wang, Y., Zhu, X., Moeckel, R. and S. Mahapatra. Comparison Between Gravity and Destination Choice Models for Trip Distribution in Maryland. In 92nd Annual TRB Conference Proceedings, TRB, National Research Council, Washington, DC, 2013. NCHRP Report 187: Quick-Response Urban Travel Estimation Techniques and Transferable Parameters. TRB, National Research Council, Washington, DC, 1978. NCHRP Report 365: Travel Estimation Techniques for Urban Planning. TRB, National Research Council, Washington, DC, 1998. http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_365.pdf. Accessed Feb. 1, 2017.

Final Report Project No. 08-94 66 NCHRP Report 716: Travel Demand Forecasting: Parameters and Techniques. TRB, National Research Council, Washington, DC, 2012. http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_716.pdf. Accessed Feb. 1, 2017. Parsons Brinckerhoff, Inc., University of Texas, Northwestern University, University of California – Irvine, Resource Systems Group, and Mark Bradley Research & Consulting, NCHRP Report 722: Assessing Highway Tolling and Pricing Options and Impacts, TRB, Washington, DC, 2012. Resource Systems Group, Inc. Interim Guidance on the Application of Travel and Land Use Forecasting in NEPA. FHWA, US Department of Transportation, Washington, DC, 2010. http://environment.fhwa.dot.gov/projdev/travel_landUse/travel_landUse_rpt.pdf. Accessed Feb. 1, 2017. Sbayti, H. and D. Roden. Best Practices in the Use of Micro Simulation Models. American Association of State Highway and Transportation Officials, Standing Committee on Planning, March 2010. http://statewideplanning.org/wp-content/uploads/259_NCHRP-08-36-90.pdf. Accessed Feb. 1, 2017. Sloboden, J., Lewis, J., Alexiadis, V., Chiu, Y. and E. Nava. Traffic Analysis Toolbox Volume XIV: Guidebook on the Utilization of Dynamic Traffic Assignment in Modeling. Pub. No. FHWA-HOP-13-015. FHWA, US Department of Transportation, 2012. http://ops.fhwa.dot.gov/publications/fhwahop13015/fhwahop13015.pdf. Accessed Feb. 1, 2017. Special Report 288: Metropolitan Travel Forecasting: Current Practice and Future Direction. TRB, National Research Council, Washington, D.C., 2007. http://onlinepubs.trb.org/onlinepubs/sr/sr288.pdf. Accessed Feb. 1, 2017. Stefan, K.J., J.D.P. McMillan, and J.D. Hunt, Urban Commercial Vehicle Movement Model for Calgary, Alberta, Canada, Transportation Research Record, Journal of the Transportation Research Board, No. 1921, Transportation Research Board of the National Academies, Washington, DC, 2005, pp. 1–10. Transportation Research Circular E-C153: Dynamic Traffic Assignment: A Primer. TRB, National Research Council, Washington, DC, 2011. http://onlinepubs.trb.org/onlinepubs/circulars/ec153.pdf. Accessed Feb. 1, 2017. Vanasse Hangen Brustlin, Resource Systems Group, Inc., Shapiro Transportation Consulting and Urban Analytics. Advanced Travel Modeling Study, Final Report. Association of Metropolitan Planning Organizations, 2011. Virginia Department of Transportation. Implementing Activity-Based Models in Virginia. VTM Research Paper 09-01, 2009. http://www.virginiadot.org/projects/resources/vtm/VTMRP09- 01_Final.pdf. Accessed Feb. 1, 2017. Wang, Q. and J. Holguín-Veras. A Tour-Based Urban Freight Demand Model Using Entropy Maximization. Department of Civil, Structural and Environmental Engineering, University at Buffalo, State University of New York, Buffalo; Department of Civil and Environmental

Final Report Project No. 08-94 67 Engineering, Rensselaer Polytechnic Institute, Troy, 2010. http://onlinepubs.trb.org/onlinepubs/shrp2/C20/015ATour-Based.pdf. Accessed Feb. 1, 2017. Washington State Department of Transportation. The Gray Notebook. WSDOT’s Quarterly Performance Report on Transportation Systems, Programs, and Department Management. Quarter Ending September 30, 2016. Published November 2016. http://wsdot.wa.gov/publications/fulltext/graynotebook/Sep16.pdf. Accessed Feb. 1, 2017. Wies, K., Urban, M., and M. Outwater. Tour-Based & Supply Chain Freight Modeling in Chicago. Presentation for TMIP Webinar, FHWA, US Department of Transportation, Washington, DC, 2013. http://www.fhwa.dot.gov/planning/tmip/publications/annual_reports/2012-2013/page12.cfm. Accessed Feb. 1, 2017.

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TRB's National Cooperative Highway Research Program (NCHRP) Web-Only Document 234: Developing a Method Selection Tool for Travel Forecasting documents research undertaken to provide guidance on travel forecasting methods to agencies with diverse planning needs. This project sought to produce applicable methods by evaluating agencies’ planning programs, desired performance metrics, requirements, and constraints, and this report documents the research and methods behind the final project and software tool.

NCHRP Research Report 852: Method Selection for Travel Forecasting presents guidelines and a tool for travel-forecasting practitioners to assess the suitability and limitations of their travel-forecasting methods and techniques to address specific policy and planning questions.

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