Traffic Paradox Under Different Equilibrium Conditions Considering Elastic Demand
Traffic paradox is an important phenomenon which needs attention in transportation network design and traffic management. Previous studies on traffic paradox always examined user equilibrium (UE) or stochastic user equilibrium (SUE) conditions with a fixed traffic demand (FD) and set the travel costs of links as constants under the SUE condition. However, traffic demand is elastic, especially when there are new links added to the network that may induce new traffic demand, and the travel costs of links actually depend on the traffic flows on them. This paper comprehensively investigates the traffic paradox under different equilibrium conditions including the user equilibrium and the stochastic user equilibrium with a fixed and elastic traffic demand. Origin-destination (OD) mean unit travel cost (MUTC) has been chosen as the main index to characterize whether the traffic paradox occurs. The impacts of travelers’ perception errors and travel cost sensitivity on the occurrence of the traffic paradox are also analyzed. The conclusions show that the occurrence of the traffic paradox depends on the traffic demand and equilibrium conditions; higher perception errors of travelers may lead to a better network performance, and a higher travel cost sensitivity will create a reversed traffic paradox. Finally, several appropriate traffic management measures are proposed to avoid the traffic paradox and improve the network performance.
 Murchland JD. Braess's paradox of traffic flow. Transportation Research. 1970;4(4): 391-394.
 Steinberg R, Zangwill WI. The prevalence of Braess' paradox. Transportation Science. 1983;17(3): 301-318.
 Dafermos S, Nagurney A. On some traffic equilibrium theory paradoxes. Transportation Research Part B: Methodological. 1984;18(2): 101-110.
 Calvert B, Keady G. Braess's paradox and power-law nonlinearities in networks. The ANZIAM Journal. 1993;35(1): 1-22.
 Hallefjord A, Jornsten K, Storoy S. Traffic equilibrium paradoxes when travel demand is elastic. Asia-Pacific Journal of Operational Research. 1994;11(1): 41-50.
 Ma J, Li D, Cheng L, et al. Link Restriction: Methods of Testing and Avoiding Braess Paradox in Networks Considering Traffic Demands. Journal of Transportation Engineering, Part A: Systems. 2017;144(2): 04017076.
 Pas EI, Principio SL. Braess' paradox: Some new insights. Transportation Research Part B: Methodological. 1997;31(3): 265-276.
 Yang H, Bell MGH. A capacity paradox in network design and how to avoid it. Transportation Research Part A: Policy and Practice. 1998;32(7): 539-545.
 Korilis YA, Lazar AA, Orda A. Avoiding the Braess paradox in non-cooperative networks. Journal of Applied Probability. 1999;36(1): 211-222.
 Sheffy Y. Urban transportation networks: equilibrium analysis with mathematical programming methods. Traffic engineering control. Prentice-Hall; 1985.
 Zhao C, Fu B, Wang T. Braess paradox and robustness of traffic networks under stochastic user equilibrium. Transportation Research Part E: Logistics and Transportation Review. 2014;61: 135-141.
 Arnott R, De Palma A, Lindsey R. Properties of dynamic traffic equilibrium involving bottlenecks, including a paradox and metering. Transportation Science. 1993;27(2): 148-160.
 Nagurney A, Qiang Q. A network efficiency measure for congested networks. EPL (Europhysics Letters). 2007;79(3): 38005.
 Zhao C. Dynamic Traffic Network Model and Time-Dependent Braess’ Paradox. Discrete Dynamics in Nature and Society. 2014;2014: 802129.
 Zhao C, Fu B, Wang T. Braess’ paradox phenomenon of congested traffic networks. Journal of Transportation Systems Engineering and Information Technology. 2012;4: 023.
 Sheffi Y. Urban transportation networks. Englewood Cliffs, NJ: Prentice-Hall; 1985.
 Lo HK, Szeto WY. Modeling advanced traveler information services: static versus dynamic paradigms. Transportation Research Part B: Methodological. 2004;38(6): 495-515.
 Xu X, Chen A, Zhou Z, et al. A multi-class mean-excess traffic equilibrium model with elastic demand. Journal of Advanced Transportation. 2014;48(3): 203-222.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).