Four-step modeling of transportation demand for cities with a population of 100,000 to 300,000

Document Type : Original Article

Authors

1 Assistant Professor, School of Rail Engineering, Iran University of Science and Technology, Tehran, Iran.

2 Ph.D., Grad., Department of Civil Engineering, University of Technology, Tehran, Iran.

Abstract

Urban transportation planning is a process that leads to decisions about transportation plans and policies. The purpose of this process is to provide the information needed to decide when, where, and how to improve the transportation system. Requiring this information and making sure it works is followed by a rational and systematic planning process. For this purpose, in this study, we first introduce different methods of transportation management and important policies in the field of urban transportation planning. Subsequently, it has attempted to implement mathematical and statistical models used in the four-steps of trip production and attraction, trip distribution, mode choice, and traffic assignment by developing a four-step transportation demand modeling computer program. C ++ has been used to build this program. The program written in this study will enable transport policymakers to analyze and evaluate the positive and negative consequences of their plans to improve transportation conditions prior to project implementation and the high costs involved.

Keywords

Main Subjects

References

- http://iscanews.ir/news/829191.
- https://www.amar.org.ir.
-Larsen, O. I., & Østmoe, K., (2001), “The experience of urban toll cordons in Norway: lessons for the future”, Journal of Transport Economics and Policy (JTEP), 35(3),
pp.457-471.
- Panis, L. I., Beckx, C., & Wets, G., (2009-2), “Modelling Gender Specific Exposure to Air Pollution”, Epidemiology, 20(6), S19.
- Safirova, E., Gillingham, K., Harrington, W., & Nelson, P., (2003), “Are hot lanes a hot deal? the potential consequences of converting hov to hot lanes in northern virginia”, RFF Issue Brief, 03-03.
- Sosslau, A. B., Hassam, A. B., Carter, M. M., & Wickstrom, G. V., (1978), “Quick Response Urban Travel Estimation Techniques and Transferable Parameters”, User Guide, NCHRP Report 187, Transportation Research Board, Washington, DC.
- T. A. I. Council, (2018), “T1 Travel Demand Modelling”.
- Vander Laan, Z., & Sadabadi, K. F., (2017), “Operational performance of a congested corridor with lanes dedicated to autonomous vehicle traffic”, International Journal of Transportation Science and Technology, 6(1), pp.42-52.
- Wikipedia, “https://en.wikipedia.org/wiki.
- Zhu, F., & Ukkusuri, S. V., (2015), “A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment”, Transportation Research Part C: Emerging Technologies, 55, pp.363-378.
-Beckx, C., Panis, L. I., Uljee, I., Arentze, T., Janssens, D., & Wets, G., (2009-3), “Disaggregation of nation-wide dynamic population exposure estimates in The Netherlands: Applications of activity-based transport models”, Atmospheric Environment, 43(34), pp.5454-5462.
-­Beckx, C., Panis, L. I., Van De Vel, K., Arentze, T., Lefebvre, W., Janssens, D., & Wets, G., (2009-1), “The contribution of activity-based transport models to air quality modelling: a validation of the ALBATROSS–AURORA model chain”, Science of the Total Environment, 407(12), pp.3814-3822.
-Beckx, C., Panis, L. I., Vankerkom, J., Janssens, D., Wets, G., & Arentze, T.,
(2009-2), “An integrated activity-based modelling framework to assess vehicle emissions: approach and application”, Environment and Planning B: Planning and Design, 36(6), pp.1086-1102.
-­Biezus, L., & Rocha, A. J. O., (2000), “Does Congestion Management Improve Public Transit? In Urban Public Transportation Systems”, Proceedings of the First International ConferenceAmerican Society of Civil Engineers”, Committee on Public Transport, Urban Transportation Division.
-­Broaddus, A., Litman, T. and Menon, G., (2009), “Transportation demand management: Training document. Eschborn, Germany: Federal Ministry for Economic Cooperation and Development”.
-Choobchian, P., Mohammadi, A., Vali Nejad, M., Zou, B., Shin, J., & Sriraj, P. S. (2023), “A Data-Driven Approach to Evaluate Walkability Using Actual Commute Walk Trips” Transportation Research Board, No. TRBAM-23-04742.
-Dhondt, S., Beckx, C., Degraeuwe, B., Lefebvre, W., Kochan, B., Bellemans, T., & Putman, K. (2012), “Health impact assessment of air pollution using a dynamic exposure profile: implications for exposure and health impact estimates”, Environmental impact assessment review, 36, pp.42-51.
-­Habibian, M., & Kermanshah, M., (2013), “Coping with congestion: Understanding the role of simultaneous transportation demand management policies on commuters”, Transport Policy, 30, pp.229-237.
-Habibian, M., Dibaj, S., & Rahmati, Y., (2014), “Investigating the Role of Push and Pull TDM Policies on Car Commuters for Short Trips”, In 93rd Transportation Research Board Annual Meeting. Washington DC.
-Habibian, M., Jafari, M. O., & Branch, P., (2013), “Assessing the role of transportation demand management policies on urban air pollution: a case study of Mashad, Iran. Section 3”, Case Studies on Specific Urban Areas: Understanding the Roles of Key Economic, Geographic, and Urban Design Inputs in the Pollution Characterization or Mitigation Scenarios, pp.87-97.
-­Hatzopoulou, M., & Miller, E. J., (2010), “Linking an activity-based travel demand model with traffic emission and dispersion models: Transport’s contribution to air pollution in Toronto”, Transportation Research Part D: Transport and Environment, 15(6), pp.315-325.
-­Hensher, D. A., & Button, K. J., (2000), “Handbook of transport modelling (No. 1)”.
-Litman, T., (2003), “The Online TDM Encyclopedia: mobility management information gateway”, Transport Policy, 10(3), pp.245-249.
-­Mafi, Sh., Mohammadi, A., Kermanshahi, Sh., & Talebian, A., (2023), “Are There Differences between People When it Comes to Adopting Telework from Different Near-Home Shared Offices?”, Transportation Research Board (No. TRBAM-23-03429).
-­Martin, W. A., & McGuckin, N. A., (1998), “Travel estimation techniques for urban planning, Vol. 365, Washington, DC: National Academy Press.
-Menendez, M., & Daganzo, C. F., (2007), “Effects of HOV lanes on freeway bottlenecks”, Transportation Research Part B: Methodological, 41(8), pp.809-822.
-­Mitchell, R. B., & Rapkin, C., (1954), “Urban traffic: A function of land use”, Columbia University Press.
-Mohammadi, A., & Choobchian, P., (2022), “Improving Walkability by Focusing on Residents’ Needs and Neighborhood’s Built Environment”, In Leveraging Sustainable Infrastructure for Resilient Communities,
pp. 70-81.
-­Mohammadi, A., & Kermanshah, M., (2019), “A Comparative Study of Objective and Subjective Variables Between Men and Women on Vehicle Type Choice in a Developing Country”, Transportation Research Board  (No. 19-01088).
-­Panis, L. I., Beckx, C., & Wets, G., (2009-1), “Socio-Economic Class and Exposure to NO2 Air Pollution in the Netherlands”, Epidemiology, 20(6), S19.
-­Pucher, J., Dill, J. and Handy, S., (2010), “Infrastructure, programs, and policies to increase bicycling: an international review”, Preventive medicine, 50, pp.S106-S125.
-­Qian, S., & Yang, S., (2016), “What do autonomous vehicles mean to traffic congestion and crash?”, Network traffic flow modeling and simulation for autonomous vehicles.
-­Shahangian, R., Kermanshah, M., & Mokhtarian, P. L., (2012), “Gender Differences in Response to Policies Targeting Commute to Automobile-Restricted Central Business District”, Stated Preference Study of Mode Choice in Tehran, Iran. Transportation research record, 2320(1), pp.80-89.
-­Shiftan, Y., (2000), “The advantage of activity-based modelling for air-quality purposes: theory vs practice and future needs”, Innovation, The European Journal of Social Science Research, 13(1), pp.95-110.
-­T. A. I. Council, (2018), “T1 Travel Demand Modelling”.
-­Talebpour, A., & Mahmassani, H. S., (2016), “Influence of connected and autonomous vehicles on traffic flow stability and throughput”, Transportation Research Part C: Emerging Technologies, 71, pp.143-163.
Transportation_forecasting” .
-­Weiner, E., (1997), “Urban transportation planning in the United States: an historical overview”, US Department of Transportation.
-­Zhu, F., & Ukkusuri, S. V., (2015), “A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment”, Transportation Research Part C: Emerging Technologies, 55, pp.363-378.
-­Zou, B., Choobchian, P., & Rozenberg, J., (2021), “Cyber resilience of autonomous mobility systems: cyber-attacks and resilience-enhancing strategies”, Journal of transportation security, pp.1-19.
Journal of Transportation Research
Volume 20, Issue 2
April 2023
Pages 175-194

Files

Share

How to cite

Statistics