Abstract
Advanced traveler information systems (ATIS) can not only improve drivers’ accessibility to the more accurate route travel time information, but also can improve drivers’ adaptability to the stochastic network capacity degradations. In this paper, a mixed stochastic user equilibrium model was proposed to describe the interactive route choice behaviors between ATIS equipped and unequipped drivers on a degradable transport network. In the proposed model, the information accessibility of equipped drivers was reflected by lower degree of uncertainty in their stochastic equilibrium flow distributions, and their behavioral adaptability was captured by multiple equilibrium behaviors over the stochastic network state set. The mixed equilibrium model was formulated as a fixed point problem defined in the mixed route flows, and its solution was achieved by executing an iterative algorithm. Numerical experiments were provided to verify the properties of the mixed network equilibrium model and the efficiency of the iterative algorithm.
摘要
先进的出行者信息系统(简写ATIS)不仅能帮助出行者获取更准确的交通时间信息,还能提 高出行者在面对路网通行能力下降等随机事件时的应急和实时调整能力。本文提出了一类新的混合随 机用户均衡模型,用以描述在通行能力随机退化的路网中,装备ATIS 和未装备ATIS 两类出行者各自 的路径选择行为和由此形成的路网交通流均衡状态。在提出的模型中,ATIS 向出行者提供交通信息 的优势体现在路网流量均衡分布状态的随机性更低,而ATIS 对出行者适应路网能力随机退化的强化 优势,则通过路网流量的多均衡态加以体现。论文将该混合随机用户均衡模型表示成一个关于混合路 径流量的不动点问题,并设计了一类迭代求解算法。通过数值算例,论文分析了模型的相关数学特性, 并验证了迭代算法的求解效率。
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References
WATLING D, van VUREN T. The modeling of dynamic route guidance systems [J]. Transportation Research Part C-Emerging Technologies, 1993, 1(2): 159–182. DOI: 10.1016/0968-090X(93)90012-5.
WATLING D. Urban traffic network models and dynamic driver information system [J]. Transport Reviews, 1994, 14(3): 219–246. DOI: 10.1080/01441649408716881.
EMMERINK R H, AXHAUSEN K W, NIJKAMP P, RIETVELD P. Effects of information in road transport networks with recurrent congestion [J]. Transportation, 1995, 22(1): 21–53. DOI: 10.1007/BF01151617.
EMMERINK R H, AXHAUSEN K W, NIJKAMP P, RIETVELD P. The potential of information provision in a simulated road transport network with non-recurrent congestion [J]. Transportation Research Part C-Emerging Technologies, 1995, 3(5): 293–309. DOI: 10.1016/0968-090X(95)00012-8.
AL-DEEK H M, KHATTAK A J, THANANJEYAN P. A combined traveler behavior and system performance model with advanced travel information systems [J]. Transportation Research Part A-Policy and Practice, 1998, 32(7): 479–493. DOI: 10.1016/S0965-8564(98)00010-X.
CHORUS C G, MOLIN E J, VAN WEE B. Use and effects of advanced traveler information services (ATIS): A review of the literature [J]. Transport Reviews, 2006, 26(2): 127–149. DOI: 10.1080/01441640500333677.
ZHANG Rong, VERHOEF E T. A monopolistic market for advanced traveler information systems and road use efficiency [J]. Transportation Research Part A-Policy and Practice, 2006, 40(5): 424–443. DOI: 10.1016/j.tra.2005.08. 010.
FERNANDEZ E J, de CEA J, VALVERDE G G. Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion [J]. Transportation Research Part A-Policy and Practice, 2009, 43(5): 481–499. DOI: 10.1016/j.tra.2008.12.001.
YAO Xue-heng, ZHAN F B, LU Yong-mei, YANG Min-hua. Effects of real-time traffic information systems on traffic performance under different network structures [J]. Journal of Central South University, 2012, 19(2): 586–592. DOI: 10.1007/s11771-012-1043-0.
HAGHANI M, SHAHHOSEINI Z, SARVI M. Quantifying benefits of traveler information systems to performance of transport networks prior to implementation: A double-class structured-parameter stochastic trip assignment approach [J]. Transportation Letters: The International Journal of Transportation Research, 2016, 8(1): 1–12. DOI: 10.1179/1942787515Y.0000000013.
KHATTAK A, POLYDOROPOULOU A, BEN-AKIVA M. Modeling revealed and stated pretrip travel response to advanced traveler information systems [J]. Transportation Research Record: Journal of the Transportation Research Board, 1996, 1537: 46–54. DOI: 10.3141/1537-07.
MAHMASSANI H S, LIU Y H. Dynamics of commuting decision behavior under advanced traveler information systems [J]. Transportation Research Part C-Emerging Technologies, 1999, 7(2,3): 91–107. DOI: 10.1016/S0968-090X(99)00014-5.
ABDEL-ATY M, ABDALLA M F. Modeling drivers’ diversion from normal routes under ATIS using generalized estimating equations and binomial probit link function [J]. Transportation, 2004, 31(3): 327–348. DOI: 10.1023/B:PORT.0000025396.32909.dc.
PEETA S, YU J W. A hybrid model for driver route choice incorporating en-route attributes and real-time information effects [J]. Networks and Spatial Economics, 2005, 5(1): 21–40. DOI: 10.1007/s11067-005-6660-9.
TSIRIMPA A, POLYDOROPOULOU A, ANTONIOU C. Development of a mixed multi-nomial logit model to capture the impact of information systems on travelers’ switching behavior [J]. Journal of Intelligent Transportation System, 2007, 11(2): 79–89. DOI: 10.1080/15472450701293882.
GAO S, HUANG H J. Real-time traveler information for optimal adaptive routing in stochastic time-dependent networks [J]. Transportation Research Part C-Emerging Technologies, 2012, 21(1): 196–213. DOI: 10.1016/j.trc. 2011.09.007.
LOU X M, CHENG L, CHU Z M. Modeling travelers’ en-route path switching in a day-to-day dynamical system [J]. Transportmetrica B: Transport Dynamics, 2017, 5(1): 15–37. DOI:10.1080/21680566.2016.1147001.
YANG H. Multiple equilibrium behaviors and advanced traveler information systems with endogenous market penetration [J]. Transportation Research Part B-Methodological, 1998, 32(3): 205–218. DOI: 10.1016/S0191-2615(97)00025-8.
YANG H, MENG Q. Modeling user adoption of advanced traveler information systems: Dynamic evolution and stationary equilibrium [J]. Transportation Research Part A-Policy and Practice, 2001, 35(10): 895–912. DOI: 10.1016/S0965-8564(00)00030-6.
YANG H, ZHANG X. Modeling competitive transit and road traffic information services with heterogeneous endogenous demand [J]. Transportation Research Record: Journal of the Transportation Research Board, 2002, 1783: 7–18. DOI: 10.3141/1783-02.
LO H K, SZETO W Y. A methodology for sustainable traveler information services [J]. Transportation Research Part B-Methodological, 2002, 36(2): 113–130. DOI: 10.1016/S0191-2615(00)00040-0.
YIN Y, YANG H. Simultaneous determination of the equilibrium market penetration and compliance rate of advanced traveler information systems [J]. Transportation Research Part A-Policy and Practice, 2003, 37(2): 165–181. DOI: 10.1016/S0965-8564(02)00011-3.
YANG H, HUANG H J. Modeling user adoption of advanced traveler information systems: A control theoretic approach for optimal endogenous growth [J]. Transportation Research Part C-Emerging Technologies, 2004, 12(3): 193–207. DOI: 10.1016/j.trc.2004.07.004.
HUANG H J, LI Z C. A multiclass, multicriteria logit-based traffic equilibrium assignment model under ATIS [J]. European Journal of Operational Research, 2007, 176(3): 1464–1477. DOI: 10.1016/j.ejor.2005.09.035.
LO H K, TUNG Y K. Network with degradable links: Capacity analysis and design [J]. Transportation Research Part B-Methodological, 2003, 37(4): 345–363. DOI: 10.1016/S0191-2615(02)00017-6.
LO H K, LUO X W, SIU B W Y. Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion [J]. Transportation Research Part B-Methodological, 2006, 40(9): 792–806. DOI: 10.1016/j.trb.2005.10.003.
SIU B W Y, LO H K. Doubly uncertain transportation network: Degradable capacity and stochastic demand [J]. European Journal of Operational Research, 2008, 191(1): 166–181. DOI: 10.1016/j.ejor.2007.08.026.
FRIESZ T L, BERNSTEIN D, MEHTA N J, TOBIN R L, GANJALIZADEH S. Day-to-day dynamic network disequilibria and idealized traveler information systems [J]. Operations Research, 1994, 42(6): 1120–1136. DOI: 10.1287/opre.42.6.1120.
HUANG H J, LIU T L, YANG H. Modeling the evolutions of day-to-day route choice and year-to-year ATIS adoption with stochastic user equilibrium [J]. Journal of Advanced Transportation, 2008, 42(2): 111–127. DOI: 10.1002/atr. 5670420202.
CANTARELLA G E. Day-to-day dynamic models for intelligent transportation systems design and appraisal [J]. Transportation Research Part C-Emerging Technologies, 2013, 29: 117–130. DOI: 10.1016/j.trc.2012.03.005.
BIFULCO G N, CANTARELLA G E, SIMONELLI F, VELONA P. Advanced traveler information systems under recurrent traffic conditions: Network equilibrium and stability [J]. Transportation Research Part B-Methodological, 2016, 92: 73–87. DOI: 10.1016/j.trb.2015.12.008.
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Foundation item: Projects(51378119, 51578150) supported by the National Natural Science Foundation of China
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Cheng, L., Lou, Xm., Zhou, J. et al. A mixed stochastic user equilibrium model considering influence of advanced traveller information systems in degradable transport network. J. Cent. South Univ. 25, 1182–1194 (2018). https://doi.org/10.1007/s11771-018-3817-5
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DOI: https://doi.org/10.1007/s11771-018-3817-5
Key words
- mixed stochastic user equilibrium model
- degradable transport network
- advanced traveler information systems (ATIS)
- drivers’ behavioral adaptability
- multiple equilibrium behaviors
- fixed point problem