IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v299y2022i1p195-207.html
   My bibliography  Save this article

Improving the performance of a traffic system by fair rerouting of travelers

Author

Listed:
  • Eikenbroek, Oskar A.L.
  • Still, Georg J.
  • van Berkum, Eric C.

Abstract

Some traffic management measures route drivers towards socially-desired paths in order to achieve the system optimum: the traffic state with minimum total travel time. In previous attempts, the behavioral response to route advice is often not accounted for since some drivers are advised to take significantly longer paths for the system’s benefit. Hence, these drivers may not comply with such advice and the optimal state will not be achieved. In this paper, we propose a social routing strategy to approach the optimal state while accounting for fairness in the resulting state. This routing strategy asks travelers to take a limited detour in order to improve efficiency. We show that the best possible paths (in terms of efficiency) to be proposed by a service adopting this strategy can be found by solving a bilevel optimization problem with a non-unique lower-level solution. We use techniques from parametric analysis to show that the directional derivative of the lower-level link flows however exists. This derivative is the optimal solution of a quadratic optimization problem with a suitable route flow solution as parameter. We use the derivative in a descent algorithm to solve the bilevel problem. Numerical experiments in a realistic environment show that the routing strategy only asks a small fraction of the drivers to take a limited detour and thereby substantially improves the performance of the traffic system.

Suggested Citation

  • Eikenbroek, Oskar A.L. & Still, Georg J. & van Berkum, Eric C., 2022. "Improving the performance of a traffic system by fair rerouting of travelers," European Journal of Operational Research, Elsevier, vol. 299(1), pages 195-207.
  • Handle: RePEc:eee:ejores:v:299:y:2022:i:1:p:195-207
    DOI: 10.1016/j.ejor.2021.06.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722172100552X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.06.036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Angelelli, E. & Morandi, V. & Savelsbergh, M. & Speranza, M.G., 2021. "System optimal routing of traffic flows with user constraints using linear programming," European Journal of Operational Research, Elsevier, vol. 293(3), pages 863-879.
    2. Shu Lu, 2008. "Sensitivity of Static Traffic User Equilibria with Perturbations in Arc Cost Function and Travel Demand," Transportation Science, INFORMS, vol. 42(1), pages 105-123, February.
    3. Mariska van Essen & Tom Thomas & Eric van Berkum & Caspar Chorus, 2020. "Travelers’ compliance with social routing advice: evidence from SP and RP experiments," Transportation, Springer, vol. 47(3), pages 1047-1070, June.
    4. Grazia Speranza, M., 2018. "Trends in transportation and logistics," European Journal of Operational Research, Elsevier, vol. 264(3), pages 830-836.
    5. Stephen M. Robinson, 2006. "Strong Regularity and the Sensitivity Analysis of Traffic Equilibria: A Comment," Transportation Science, INFORMS, vol. 40(4), pages 540-542, November.
    6. Jong-Shi Pang & Daniel Ralph, 1996. "Piecewise Smoothness, Local Invertibility, and Parametric Analysis of Normal Maps," Mathematics of Operations Research, INFORMS, vol. 21(2), pages 401-426, May.
    7. Sang Nguyen & Clermont Dupuis, 1984. "An Efficient Method for Computing Traffic Equilibria in Networks with Asymmetric Transportation Costs," Transportation Science, INFORMS, vol. 18(2), pages 185-202, May.
    8. Yang, Hai & Zhang, Xiaoning & Meng, Qiang, 2007. "Stackelberg games and multiple equilibrium behaviors on networks," Transportation Research Part B: Methodological, Elsevier, vol. 41(8), pages 841-861, October.
    9. Byung Chung & Hsun-Jung Cho & Terry Friesz & Henh Huang & Tao Yao, 2014. "Sensitivity Analysis of User Equilibrium Flows Revisited," Networks and Spatial Economics, Springer, vol. 14(2), pages 183-207, June.
    10. Yuping Qiu & Thomas L. Magnanti, 1989. "Sensitivity Analysis for Variational Inequalities Defined on Polyhedral Sets," Mathematics of Operations Research, INFORMS, vol. 14(3), pages 410-432, August.
    11. Michael Patriksson & R. Tyrrell Rockafellar, 2003. "Sensitivity Analysis of Aggregated Variational Inequality Problems, with Application to Traffic Equilibria," Transportation Science, INFORMS, vol. 37(1), pages 56-68, February.
    12. Eikenbroek, Oskar A.L. & Still, Georg J. & van Berkum, Eric C. & Kern, Walter, 2018. "The Boundedly Rational User Equilibrium: A parametric analysis with application to the Network Design Problem," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 1-17.
    13. Lu, Shu & (Marco) Nie, Yu, 2010. "Stability of user-equilibrium route flow solutions for the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 609-617, May.
    14. Olaf Jahn & Rolf H. Möhring & Andreas S. Schulz & Nicolás E. Stier-Moses, 2005. "System-Optimal Routing of Traffic Flows with User Constraints in Networks with Congestion," Operations Research, INFORMS, vol. 53(4), pages 600-616, August.
    15. Angelelli, E. & Arsik, I. & Morandi, V. & Savelsbergh, M. & Speranza, M.G., 2016. "Proactive route guidance to avoid congestion," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 1-21.
    16. Josefsson, Magnus & Patriksson, Michael, 2007. "Sensitivity analysis of separable traffic equilibrium equilibria with application to bilevel optimization in network design," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 4-31, January.
    17. Michael Patriksson & R. Tyrrell Rockafellar, 2002. "A Mathematical Model and Descent Algorithm for Bilevel Traffic Management," Transportation Science, INFORMS, vol. 36(3), pages 271-291, August.
    18. Roger L. Tobin & Terry L. Friesz, 1988. "Sensitivity Analysis for Equilibrium Network Flow," Transportation Science, INFORMS, vol. 22(4), pages 242-250, November.
    19. Lou, Yingyan & Yin, Yafeng & Lawphongpanich, Siriphong, 2010. "Robust congestion pricing under boundedly rational user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 15-28, January.
    20. Ohazulike, Anthony E. & Still, Georg & Kern, Walter & van Berkum, Eric C., 2013. "An origin–destination based road pricing model for static and multi-period traffic assignment problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 58(C), pages 1-27.
    21. S. Dempe & A. Zemkoho, 2012. "Bilevel road pricing: theoretical analysis and optimality conditions," Annals of Operations Research, Springer, vol. 196(1), pages 223-240, July.
    22. Di, Xuan & Liu, Henry X. & Pang, Jong-Shi & Ban, Xuegang (Jeff), 2013. "Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 300-313.
    23. Li, Ruijie & Liu, Xiaobo & Nie, Yu (Marco), 2018. "Managing partially automated network traffic flow: Efficiency vs. stability," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 300-324.
    24. Yin, Yafeng & Madanat, Samer M. & Lu, Xiao-Yun, 2009. "Robust improvement schemes for road networks under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 198(2), pages 470-479, October.
    25. Michael Patriksson, 2004. "Sensitivity Analysis of Traffic Equilibria," Transportation Science, INFORMS, vol. 38(3), pages 258-281, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Du, Muqing & Chen, Anthony, 2022. "Sensitivity analysis for transit equilibrium assignment and applications to uncertainty analysis," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 175-202.
    2. Byung Chung & Hsun-Jung Cho & Terry Friesz & Henh Huang & Tao Yao, 2014. "Sensitivity Analysis of User Equilibrium Flows Revisited," Networks and Spatial Economics, Springer, vol. 14(2), pages 183-207, June.
    3. Jafari, Ehsan & Boyles, Stephen D., 2016. "Improved bush-based methods for network contraction," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 298-313.
    4. Shu Lu, 2008. "Sensitivity of Static Traffic User Equilibria with Perturbations in Arc Cost Function and Travel Demand," Transportation Science, INFORMS, vol. 42(1), pages 105-123, February.
    5. Wang, Jian & He, Xiaozheng & Peeta, Srinivas, 2016. "Sensitivity analysis based approximation models for day-to-day link flow evolution process," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 35-53.
    6. Connors, Richard D. & Sumalee, Agachai & Watling, David P., 2007. "Sensitivity analysis of the variable demand probit stochastic user equilibrium with multiple user-classes," Transportation Research Part B: Methodological, Elsevier, vol. 41(6), pages 593-615, July.
    7. S. Dempe & A. Zemkoho, 2012. "Bilevel road pricing: theoretical analysis and optimality conditions," Annals of Operations Research, Springer, vol. 196(1), pages 223-240, July.
    8. Bar-Gera, Hillel & Hellman, Fredrik & Patriksson, Michael, 2013. "Computational precision of traffic equilibria sensitivities in automatic network design and road pricing," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 485-500.
    9. Chiou, Suh-Wen, 2015. "A cutting plane projection method for bi-level area traffic control optimization with uncertain travel demand," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 390-403.
    10. Josefsson, Magnus & Patriksson, Michael, 2007. "Sensitivity analysis of separable traffic equilibrium equilibria with application to bilevel optimization in network design," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 4-31, January.
    11. Lederman, Roger & Wynter, Laura, 2011. "Real-time traffic estimation using data expansion," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1062-1079, August.
    12. Patriksson, Michael, 2008. "On the applicability and solution of bilevel optimization models in transportation science: A study on the existence, stability and computation of optimal solutions to stochastic mathematical programs," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 843-860, December.
    13. Michael Patriksson, 2004. "Sensitivity Analysis of Traffic Equilibria," Transportation Science, INFORMS, vol. 38(3), pages 258-281, August.
    14. Clark, Stephen D. & Watling, David P., 2006. "Applications of sensitivity analysis for probit stochastic network equilibrium," European Journal of Operational Research, Elsevier, vol. 175(2), pages 894-911, December.
    15. Eikenbroek, Oskar A.L. & Still, Georg J. & van Berkum, Eric C. & Kern, Walter, 2018. "The Boundedly Rational User Equilibrium: A parametric analysis with application to the Network Design Problem," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 1-17.
    16. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    17. Michael Patriksson & R. Tyrrell Rockafellar, 2003. "Sensitivity Analysis of Aggregated Variational Inequality Problems, with Application to Traffic Equilibria," Transportation Science, INFORMS, vol. 37(1), pages 56-68, February.
    18. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    19. Xia Yang & Xuegang Jeff Ban & Rui Ma, 2017. "Mixed Equilibria with Common Constraints on Transportation Networks," Networks and Spatial Economics, Springer, vol. 17(2), pages 547-579, June.
    20. Jafari, Ehsan & Pandey, Venktesh & Boyles, Stephen D., 2017. "A decomposition approach to the static traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 270-296.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:299:y:2022:i:1:p:195-207. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.