Link Restriction: Methods of Testing and Avoiding Braess Paradox in Networks Considering Traffic Demands
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 2
Abstract
Braess paradox is a well-known paradox in transportation researches. In urban cities, there are many different kinds of complex road networks. Unavoidably, some of them fall into the Braess paradox and it is hardly realized. In this paper, two proposed approaches are applied to find and avoid the Braess paradox in urban road networks. With the first approach, the links that cause the Braess paradox in the urban road networks with the current origination-destination (OD) matrix can be tested. The other approach is to calculate the range of the OD flows that makes these links fall into the Braess paradox. Unlike other approaches proposed in literature, this proposed approach can figure out the range of traffic demands in the networks with multiple OD pairs. Moreover, by applying these two approaches, the authors design a traffic management called link restriction which can easily figure out which link should be closed down temporarily and when to resume operation to reduce the total travel times of networks with flexible managements.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research is supported by the National Natural Science Foundation of China (Nos. 51178110, 51378119, and 51608115); the Fundamental Research Funds for the Central Universities and the Research Innovation Program for College Graduates of Jiangsu Province (No. KYLX16_0275) and the Natural Science Foundation of Jiangsu Province (No. BK20150613). Comments provided by anonymous referees are much appreciated.
References
Akamatsu, T., and Heydecker, B. (2003). “Detecting dynamic traffic assignment capacity paradoxes in saturated networks.” Transp. Sci., 37(2), 123–138.
Askoura, Y., Lebacque, J. P., and Haj-Salem, H. (2011). “Optimal sub-networks in traffic assignment problem and the Braess paradox.” Comput. Indus. Eng., 61(2), 382–390.
Beckmann, M., McGuire, C., and Winsten, C. (1956). Studies in the economics of transportation, Yale University Press, New Haven, CT.
Braess, D. (1968). “Über ein Paradoxon aus der Verkehrsplanung.” Math. Methods Oper. Res., 12(1), 258–268.
Braess, D., Nagurney, A., and Wakolbinger, T. (2005). “On a paradox of traffic planning.” Transp. Sci., 39(4), 446–450.
Bullock, D. M., Day, C. M., and Brennan, T. M., Jr. (2011). “Architecture for active management of geographically distributed signal systems.” Inst. Transp. Eng. J., 81(5), 20.
Calvert, B., and Keady, G. (1993). “Braess’s paradox and power-law nonlinearities in networks.” J. Aust. Math. Soc. Ser. B., 35(1), 1–22.
Dafermos, S., and Nagurney, A. (1984). “On some traffic equilibrium theory paradoxes.” Transp. Res. Part B, 18(2), 101–110.
Gkritza, K., and Karlaftis, M. G. (2013a). “Intelligent transportation systems applications for the environment and energy conservation (part 1).” J. Intell. Transp. Syst., 17(1), 1–2.
Gkritza, K., and Karlaftis, M. G. (2013b). “Intelligent transportation systems applications for the environment and energy conservation (part 2).” J. Intell. Transp. Syst., 17(3), 177–178.
Gkritza, K., and Labi, S. (2008). “Estimating cost discrepancies in highway contracts: Multistep econometric approach.” J. Constr. Eng. Manage., 953–962.
Hallefjord, A., Jornsten, K., and Storoy, S. (1994). “Traffic equilibrium paradoxes when travel demand is elastic.” Asia-Pacific J. Oper. Res., 11(1), 41–50.
Hendrickson, C. (2011). “Sustainable energy challenges for civil engineering management.” J. Manage. Eng., 2–4.
Hendrickson, C., Cicas, G., and Matthews, H. (2006). “Transportation sector and supply chain performance and sustainability.” Transp. Res. Rec., 1983, 151–157.
Inoie, A., Kameda, H., and Touati, C. (2006). “A paradox in optimal flow control of M/M/n queues.” Comput Oper. Res., 33(2), 356–368.
Jiang, Y., and Szeto, W. Y. (2016). “Reliability-based stochastic transit assignment: Formulations and capacity paradox.” Transp. Res. Part B, 93, 181–206.
Leblanc, L. J. (1975). “An algorithm for the discrete network design problem.” Transp. Sci., 9(3), 183–199.
Li, D., Miwa, T., and Morikawa, T. (2013). “Dynamic route choice behavior analysis considering en route learning and choices.” Transp. Res. Rec., 2383, 1–9.
Li, R., and Guo, M. (2016). “Effects of odd-even traffic restriction on travel speed and traffic volume: Evidence from Beijing Olympic Games.” J. Traffic Transp. Eng., 3(1), 71–81.
Liu, Y., Hong, Z., and Liu, Y. (2016). “Do driving restriction policies effectively motivate commuters to use public transportation?” Energy Policy, 90, 253–261.
Long, J., Gao, Z., Zhang, H., and Szeto, W. Y. (2010). “A turning restriction design problem in urban road networks.” Eur. J. Oper. Res., 206(3), 569–578.
Long, J., Szeto, W. Y., and Huang, H. J. (2014). “A bi-objective turning restriction design problem in urban road networks.” Eur. J. Oper. Res., 237(2), 426–439.
MATLAB [Computer software]. MathWorks, Natick, MA.
Nagurney, A. (2000). “Congested urban transportation networks and emission paradoxes.” Transp. Res. Part D, 5(2), 145–151.
Nikolova, N. D., Armenski, I. S., Tenekedjieva, L. T. K., and Toneva-Zheynova, D. S. (2012). “Multi-dimensional Nash arbitration in the Braess paradox.” IFAC Proc. Vol., 45(24), 132–137.
Pas, E. I., and Principio, S. L. (1997). “Braess’ paradox: Some new insights.” Transp. Res. Part B, 31(3), 265–276.
Rapoport, A., Kugler, T., Dugar, S., and Gisches, E. J. (2009). “Choice of routes in congested traffic networks: Experimental tests of the Braess paradox.” Games Econ. Behav., 65(2), 538–571.
Roughgarden, T. (2006). “On the severity of Braess’s paradox: Designing networks for selfish users is hard.” J. Comput. Syst. Sci. Int., 72(5), 922–953.
Sheffi, Y., and Daganzo, C. F. (1978). “Another ‘paradox’ of traffic flow.” Transp. Res., 12(1), 43–46.
Steinberg, R., and Zangwill, W. I. (1983). “The prevalence of Braess’ paradox.” Transp. Sci., 17(3), 301–318.
Tiratanapakhom, T., Kim, H., Nam, D., and Lim, Y. (2016). “Braess’ paradox in the uncertain demand and congestion assumed stochastic transportation network design problem.” KSCE J. Civ. Eng., 20(7), 2928–2937.
Wang, D. Z., Liu, H., and Szeto, W. Y. (2015). “A novel discrete network design problem formulation and its global optimization solution algorithm.” Transp. Res. Part E, 79, 213–230.
Wang, D. Z., Liu, H., Szeto, W. Y., and Chow, A. H. (2016a). “Identification of critical combination of vulnerable links in transportation networks—A global optimisation approach.” Transportmetrica A, 12(4), 346–365.
Wang, S., Meng, Q., and Yang, H. (2013). “Global optimization methods for the discrete network design problem.” Transp. Res. Part B, 50, 42–60.
Wang, W. W., Wang, D. Z., Sun, H., Feng, Z., and Wu, J. (2016b). “Braess paradox of traffic networks with mixed equilibrium behaviors.” Transp. Res. Part E, 93, 95–114.
Wang, W. W., Wang, D. Z., Zhang, F., Sun, H., Zhang, W., and Wu, J. (2017). “Overcoming the Downs-Thomson paradox by transit subsidy policies.” Transp. Res. Part A: Policy Pract., 95, 126–147.
Wardrop, J. G. (1952). “Some theoretical aspects of road traffic research.” Proc. Inst. Civ. Eng., 1(3), 325–362.
Willemse, E. J., and Joubert, J. W. (2016). “Constructive heuristics for the mixed capacity arc routing problem under time restrictions with intermediate facilities.” Comput. Oper. Res., 68, 30–62.
Xu, X. Y., Liu, J., Li, H. Y., and Hu, J. Q. (2014). “Analysis of subway station capacity with the use of queueing theory.” Transp. Res. Part C, 38, 28–43.
Xu, X. Y., Liu, J., Li, H. Y., and Jiang, M. (2016). “Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study.” Transp. Res. Part E, 87, 130–148.
Yan, X., Li, X., Liu, Y., and Zhao, J. (2014). “Effects of foggy conditions on drivers’ speed control behaviors at different risk levels.” Saf. Sci., 68, 275–287.
Yan, X., Wang, J., and Wu, J. (2016). “Effect of in-vehicle audio warning system on driver’s speed control performance in transition zones from rural areas to urban areas.” Int. J. Environ. Res. Public Health, 13(7), 634.
Yang, H., and Bell, M. G. (1998). “A capacity paradox in network design and how to avoid it.” Transp. Res. Part A: Policy Pract., 32(7), 539–545.
Yao, J., and Chen, A. (2014). “An analysis of logit and weibit route choices in stochastic assignment paradox.” Transp. Res. Part B, 69, 31–49.
Zhang, F., Lindsey, R., and Yang, H. (2016). “The Downs–Thomson paradox with imperfect mode substitutes and alternative transit administration regimes.” Transp. Res. Part B, 86, 104–127.
Zhao, C., Fu, B., and Wang, T. (2014). “Braess paradox and robustness of traffic networks under stochastic user equilibrium.” Transp. Res. Part E, 61, 135–141.
Zhou, X., Yang, Z., Zhang, W., Tian, X., and Bing, Q. (2016). “Urban link travel time estimation based on low frequency probe vehicle data.” Discrete Dyn. Nat. Soc., 7348705.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 2 • February 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Oct 26, 2016
Accepted: Aug 1, 2017
Published online: Nov 30, 2017
Published in print: Feb 1, 2018
Discussion open until: Apr 30, 2018
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.