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Evaluation of Traffic Assignment Models through Simulation

Author

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  • Marta Rojo

    (Department of Civil Engineering, University of Burgos, 09001 Burgos, Spain)

Abstract

Assignment methodologies attempt to determine the traffic flow over each network arc based on its characteristics and the total flow over the entire area. There are several methodologies—some fast and others that are more complex and require more time to complete the calculation. In this study, we evaluated different assignment methodologies using a computer simulation and tested the results in a specific case study. The results showed that the “all-or-nothing” methods and the incremental assignment methods generally yield results with an unacceptable level of error unless the traffic is divided into four or more equal parts. The method of successive averages (MSA) was valid starting from a relatively low number of iterations, while the user equilibrium methodologies (approximated using the Frank and Wolfe algorithm) were valid starting from an even lower number of iterations. These results may be useful to researchers in the field of computer simulation and planners who apply these methodologies in similar cases.

Suggested Citation

  • Marta Rojo, 2020. "Evaluation of Traffic Assignment Models through Simulation," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5536-:d:382190
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    References listed on IDEAS

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    1. Xinhua Mao & Jianwei Wang & Changwei Yuan & Wei Yu & Jiahua Gan, 2018. "A Dynamic Traffic Assignment Model for the Sustainability of Pavement Performance," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    2. Ennio Cascetta, 2009. "Transportation Systems Analysis," Springer Optimization and Its Applications, Springer, number 978-0-387-75857-2, July.
    3. Pel, Adam J. & Chaniotakis, Emmanouil, 2017. "Stochastic user equilibrium traffic assignment with equilibrated parking search routes," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 123-139.
    4. S. F. A. Batista & Ludovic Leclercq, 2019. "Regional Dynamic Traffic Assignment Framework for Macroscopic Fundamental Diagram Multi-regions Models," Transportation Science, INFORMS, vol. 53(6), pages 1563-1590, November.
    5. Morten Eltved & Otto Anker Nielsen & Thomas Kjær Rasmussen, 2019. "An assignment model for public transport networks with both schedule- and frequency-based services," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 769-793, December.
    6. Long, Jiancheng & Szeto, W.Y. & Du, Jie & Wong, R.C.P., 2017. "A dynamic taxi traffic assignment model: A two-level continuum transportation system approach," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 222-254.
    7. Guangming Xu & Shuo Zhao & Feng Shi & Feilian Zhang, 2017. "Cell transmission model of dynamic assignment for urban rail transit networks," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-31, November.
    8. Iris, Çağatay & Christensen, Jonas & Pacino, Dario & Ropke, Stefan, 2018. "Flexible ship loading problem with transfer vehicle assignment and scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 113-134.
    9. Kucharski, Rafał & Gentile, Guido, 2019. "Simulation of rerouting phenomena in Dynamic Traffic Assignment with the Information Comply Model," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 414-441.
    10. Heqing Tan & Muqing Du & Xiaowei Jiang & Zhaoming Chu, 2019. "The Combined Distribution and Assignment Model: A New Solution Algorithm and Its Applications in Travel Demand Forecasting for Modern Urban Transportation," Sustainability, MDPI, vol. 11(7), pages 1-18, April.
    11. Stavri Dimitrov & Avishai (Avi) Ceder & Subeh Chowdhury & Mikaël Monot, 2017. "Modeling the interaction between buses, passengers and cars on a bus route using a multi-agent system," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(5), pages 592-610, July.
    12. Wang, Yi & Szeto, W.Y. & Han, Ke & Friesz, Terry L., 2018. "Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 370-394.
    13. Iris, Çağatay & Pacino, Dario & Ropke, Stefan & Larsen, Allan, 2015. "Integrated Berth Allocation and Quay Crane Assignment Problem: Set partitioning models and computational results," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 75-97.
    14. Y. Arezki & D. Van Vliet, 1990. "A Full Analytical Implementation of the PARTAN/Frank–Wolfe Algorithm for Equilibrium Assignment," Transportation Science, INFORMS, vol. 24(1), pages 58-62, February.
    15. Cantarella, Giulio Erberto & Cartenì, Armando & de Luca, Stefano, 2015. "Stochastic equilibrium assignment with variable demand: Theoretical and implementation issues," European Journal of Operational Research, Elsevier, vol. 241(2), pages 330-347.
    16. Bagdasar, Ovidiu & Berry, Stuart & O’Neill, Sam & Popovici, Nicolae & Raja, Ramachandran, 2019. "Traffic assignment: Methods and simulations for an alternative formulation of the fixed demand problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 360-373.
    17. Qun Chen & Shuangli Pan, 2017. "Direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(7), pages 757-770, October.
    18. Giulio Erberto Cantarella, 1997. "A General Fixed-Point Approach to Multimode Multi-User Equilibrium Assignment with Elastic Demand," Transportation Science, INFORMS, vol. 31(2), pages 107-128, May.
    19. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
    20. Stefano Starita & Arne K. Strauss & Xin Fei & Radosav Jovanović & Nikola Ivanov & Goran Pavlović & Frank Fichert, 2020. "Air Traffic Control Capacity Planning Under Demand and Capacity Provision Uncertainty," Transportation Science, INFORMS, vol. 54(4), pages 882-896, July.
    21. Hassan M. Al-Ahmadi & Arshad Jamal & Imran Reza & Khaled J. Assi & Syed Anees Ahmed, 2019. "Using Microscopic Simulation-Based Analysis to Model Driving Behavior: A Case Study of Khobar-Dammam in Saudi Arabia," Sustainability, MDPI, vol. 11(11), pages 1-18, May.
    22. Li, Shuqin & Jia, Shuai, 2019. "The seaport traffic scheduling problem: Formulations and a column-row generation algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 158-184.
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    1. Zhanzhong Wang & Ruijuan Chu & Minghang Zhang & Xiaochao Wang & Siliang Luan, 2020. "An Improved Hybrid Highway Traffic Flow Prediction Model Based on Machine Learning," Sustainability, MDPI, vol. 12(20), pages 1-22, October.
    2. Federico Cavallaro & Francesco Bruzzone & Silvio Nocera, 2023. "Effects of high-speed rail on regional accessibility," Transportation, Springer, vol. 50(5), pages 1685-1721, October.

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