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Article

A Reliability-Based Network Equilibrium Model with Electric Vehicles and Gasoline Vehicles
Qiang Tu, Manman Li, Yongjun Wu
Keywords:transportation engineering, reliability-based network equilibrium, electric vehicle, driving range, recharge requirement

Abstract

With the popularity of electric vehicles, they have become an indispensable part of traffic flow on the road network. This paper presents a reliability-based network equilibrium model to realise the traffic flow pattern prediction on the road network with electric vehicles and gasoline vehicles, which incorporates travel time reliability, electric vehicles’ driving range and recharge requirement. The mathematical expression of reliable path travel time is derived, and the reliability-based network equilibrium model is formulated as a variational inequality problem. Then a multi-criterion labelling algorithm is proposed to solve the reliable shortest path problem, and a column-generation-based method of the successive average algorithm is proposed to solve the reliability-based network equilibrium model. The applicability and efficiency of the proposed model and algorithm are verified on the Nguyen-Dupuis network and the real road network of Sioux Falls City. The proposed model and algorithm can be extended to other road networks and help traffic managers analyse traffic conditions and make sustainable traffic policies.

References

[1] Kumar RR, Alok K. Adoption of electric vehicle: A literature review and prospects for sustainability. Journal of Cleaner Production. 2020;253:119911. DOI: 10.1016/j.jclepro.2019.119911.
[2] IEA. Global EV Outlook 2022. https://www.iea.org/reports/global-ev-outlook-2022. html.
[3] CleanTechnica. 31 Countries, States, And Cities Have Gas/Diesel Car Bans In Place. https://cleantechnica.com/2021/01/02/31-countries-states-and-cities-have-ice-bans-in-place/.
[4] Hu Y, et al. The Chinese plug-in electric vehicles industry in post-COVID-19 era towards 2035: Where is the path to revival? Journal of Cleaner Production. 2022;361:132291. DOI: 10.1016/j.jclepro.2022.132291.
[5] Li M, et al. Network traffic flow evolution with battery electric vehicles and conventional gasoline vehicles. Journal of Southeast University (English Edition). 2019;35(2):213-219. DOI: 10.3969/j.issn.1003-7985.2019.02.011.
[6] Tu Q, et al. Stochastic transportation network considering ATIS with the information of environmental cost. Sustainability. 2018;10(11):3861. DOI: 10.3390/su10113861.
[7] Tu Q, et al. Traffic paradox under different equilibrium conditions considering elastic demand. Promet – Traffic&Transportation. 2019;31(1):1-9. DOI: 10.7307/PTT.V31I1.2795.
[8] Sheffi Y. Urban transportation networks.Englewood Cliffs, NJ: Prentice-Hall. 1985.
[9] Zhu S, Levinson D. Do people use the shortest path? An empirical test of Wardrop’s first principle. PloS one. 2015;10(8):e0134322. DOI: 10.1371/journal.pone.0134322.
[10] Maher M. Algorithms for logit-based stochastic user equilibrium assignment. Transportation Research Part B: Methodological. 1998;32(8):539-549. DOI: 10.1016/S0191-2615(98)00015-0.
[11] Prashker JN, Bekhor S. Route choice models used in the stochastic user equilibrium problem: A review. Transport reviews. 2004;24(4):437-463. DOI: 10.1080/0144164042000181707.
[12] Huang HJ, Lam WHK. Modeling and solving the dynamic user equilibrium route and departure time choice problem in network with queues. Transportation Research Part B: Methodological. 2002;36(3):253-273. DOI: 10.1016/S0191-2615(00)00049-7.
[13] Shao H, et al. A reliability-based stochastic traffic assignment model for network with multiple user classes under uncertainty in demand. Networks and Spatial Economics. 2006;6:173-204. DOI: 10.1007/s11067-006-9279-6.
[14] Wang L, et al. A reliability-based traffic equilibrium model with boundedly rational travelers considering acceptable arrival thresholds. Sustainability. 2023;15(8):6988. DOI: 10.3390/su15086988.
[15] Yan D, Guo J. A Multiclass cumulative prospect theory-based stochastic user equilibrium model with path constraints in degradable transport networks. Promet – Traffic&Transportation. 2021;33(5):775-787. DOI: 10.7307/PTT.V33I5.3586.
[16] Dafermos S. The general multimodal network equilibrium problem with elastic demand. Networks. 1982;12(1):57-72. DOI: 10.1002/net.3230120105.
[17] Ge Y, MacKenzie D. Charging behavior modeling of battery electric vehicle drivers on long-distance trips. Transportation Research Part D: Transport and Environment. 2022;113:103490. DOI: 10.1016/j.trd.2022.103490.
[18] Mansfield C, et al. An efficient detour computation scheme for electric vehicles to support smart cities’ electrification. Electronics. 2022;11(5):803. DOI: 10.3390/electronics11050803.
[19] Ma J, et al. Stochastic electric vehicle network considering environmental costs. Sustainability. 2018;10(8):2888. DOI: 10.3390/su10082888.
[20] Ma J, Wang H, Tang T. Stochastic electric vehicle network with elastic demand and environmental costs. Journal of Advanced Transportation. 2020;2020:1-11. DOI: 10.1155/2020/4169826.
[21] Ahn K, et al. Multi-objective eco-routing model development and evaluation for battery electric vehicles. Transportation Research Record. 2021;2675(12):867-879. DOI: 10.1177/03611981211031529.
[22] Ma J, et al. Analysis of urban electric vehicle adoption based on operating costs in urban transportation network. Systems. 2023;11(3):149. DOI: 10.3390/systems11030149.
[23] Jiang N, Xie C, Waller ST. Path-constrained traffic assignment: model and algorithm. Transportation Research Record. 2012;2283(1):25-33. DOI: 10.3141/2283-03.
[24] Jiang N, Xie C. Computing and analyzing mixed equilibrium network flows with gasoline and electric vehicles. Computer‐Aided Civil and Infrastructure Engineering. 2014;29(8):626-641. DOI: 10.1111/mice.12082.
[25] Jing W, et al. Stochastic traffic assignment of mixed electric vehicle and gasoline vehicle flow with path distance constraints. Transportation Research Procedia. 2017;21:65-78. DOI: 10.1016/j.trpro.2017.03.078.
[26] Jing W, et al. Location design of electric vehicle charging facilities: A path-distance constrained stochastic user equilibrium approach. Journal of Advanced Transportation. 2017. DOI: 10.1155/2017/4252946.
[27] Xie C, Jiang N. Relay requirement and traffic assignment of electric vehicles. Computer-Aided Civil and Infrastructure Engineering. 2016;31(8):580-598. DOI: 10.1111/mice.12193.
[28] He F, Yin Y, Lawphongpanich S. Network equilibrium models with battery electric vehicles. Transportation Research Part B: Methodological. 2014;67:306-319. DOI: 10.1016/j.trb.2014.05.010.
[29] Xu M, Meng Q, Liu K. Network user equilibrium problems for the mixed battery electric vehicles and gasoline vehicles subject to battery swapping stations and road grade constraints. Transportation Research Part B: Methodological. 2017;99:138-166. DOI: 10.1016/j.trb.2017.01.009.
[30] Zhang X, et al. Range-constrained traffic assignment with multi-modal recharge for electric vehicles. Networks and Spatial Economics. 2019;19(2):633-668. DOI: 10.1007/s11067-019-09454-9.
[31] Asakura Y, Kashiwadani M. Road network reliability caused by daily fluctuation of traffic flow. 19th PTRC Summer Annual Meeting, 1991, University of Sussex, United Kingdom. 1991.
[32] Gu Y, et al. Performance of transportation network under perturbations: Reliability, vulnerability, and resilience. Transportation Research Part E: Logistics and Transportation Review. 2020;133:101809. DOI: 10.1016/j.tre.2019.11.003.
[33] Sun C, Cheng L, Ma J. Travel time reliability with boundedly rational travelers. Transportmetrica A: Transport Science. 2017;14(3):210-229. DOI: 10.1080/23249935.2017.1368733.
[34] Senna LADS. The influence of travel time variability on the value of time. Transportation. 1994;21:203-228. DOI: 10.1007/bf01098793.
[35] Tu Q, et al. The constrained reliable shortest path problem for electric vehicles in the urban transportation network. Journal of Cleaner Production. 2020;261:121130. DOI: 10.1016/j.jclepro.2020.121130.
[36] Ruß M, Gust G, Neumann D. The constrained reliable shortest path problem in stochastic time-dependent networks. Operations Research. 2021;69(3):709-726. DOI: 10.1287/opre.2020.2089.
[37] Shen L, et al. An energy-efficient reliable path finding algorithm for stochastic road networks with electric vehicles. Transportation Research Part C: Emerging Technologies. 2019;102:450-473. DOI: 10.1016/j.trc.2019.03.020.
[38] Shen L, et al. A reliability-based stochastic traffic assignment model for signalized traffic network with consideration of link travel time correlations. Sustainability. 2022;14(21):14520. DOI: 10.3390/su142114520.
[39] Chen A, Zhou Z. The α-reliable mean-excess traffic equilibrium model with stochastic travel times. Transportation Research Part B: Methodological. 2010;44(4):493-513. DOI: 10.1016/j.trb.2009.11.003.
[40] Sun C, et al. Day-to-day traffic user equilibrium model considering influence of intelligent highways and advanced traveler information systems. Journal of Central South University. 2022;29(4):1376-1388. DOI: 10.1007/s11771-022-4974-0.
[41] Tao Y, et al. Review of optimized layout of electric vehicle charging infrastructures. Journal of Central South University. 2021;28(10):3268-3278. DOI: 10.1007/s11771-021-4842-3.
[42] Zhan W, et al. A review of siting, sizing, optimal scheduling, and cost-benefit analysis for battery swapping stations. Energy. 2022;124723. DOI: 10.1016/j.energy.2022.124723.
[43] Ma J, et al. Link restriction: Methods of testing and avoiding braess paradox in networks considering traffic demands. Journal of Transportation Engineering, Part A: Systems. 2018;144(2):04017076. DOI: 10.1061/jtepbs.0000111.
[44] Zhang TY, et al. Deploying public charging stations for battery electric vehicles on the expressway network based on dynamic charging demand. IEEE Transactions on Transportation Electrification. 2022;8(2):2531-2548. DOI: 10.1109/tte.2022.3141208.
[45] Wang D, et al. A generalized mean-variance metric of route choice model under travel time uncertainty. Transportmetrica A: Transport Science. 2022;18(2):299-323. DOI: 10.1080/23249935.2020.1773573.
[46] Nguyen S, Dupuis C. An efficient method for computing traffic equilibria in networks with asymmetric transportation costs. Transportation Science. 1984;18(2):185-202. DOI: 10.1287/trsc.18.2.185.
[47] Stabler B. Transportation networks for research. 2020. https://github.com/bstabler/TransportationNetworks.
Published
01.03.2024
Copyright (c) 2023 Qiang Tu, Manman Li, Yongjun Wu

Published by
University of Zagreb, Faculty of Transport and Traffic Sciences
Online ISSN
1848-4069
Print ISSN
0353-5320
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