高速公路突发事件救援车辆诱导

赵朋, 王建伟, 孙茂棚, 周雅欣

中国公路学报 ›› 2018, Vol. 31 ›› Issue (9) : 175-181.

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中国公路学报 ›› 2018, Vol. 31 ›› Issue (9) : 175-181.
交通工程

高速公路突发事件救援车辆诱导

  • 赵朋, 王建伟, 孙茂棚, 周雅欣
作者信息 +

Vehicle Scheduling for Mountainous Expressway Traffic Emergency

  • ZHAO Peng, WANG Jian-wei, SUN Mao-peng, ZHOU Ya-xin
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文章历史 +

摘要

为了提升高速公路突发事件应急救援效率,将交通状况、在途潜在风险等信息纳入高速公路突发事件救援车辆诱导研究中,基于实时和时变路网环境下的交通信息,以车辆出行时间最小,路径可靠性最强为目标,构建基于在途时间和路径可靠性的车辆诱导最优化模型。设计一种实时信息和时变信息结合策略,使模型规划路径随路网交通量变化而相应做出阶段性调整,采用滚动时域策略将该动态决策问题转化为一系列离散时间点的静态决策问题,用于计算应急救援路径时间;在此基础上,考虑到高速公路突发事件发生后路网交通事故率升高,同时容易发生拥堵的状况,进一步将救援规划路径可靠性作为决策目标,即应急救援车辆规划路径在面对道路中断或者严重拥堵时是否拥有更多的调整策略,更新救援路径尽快完成救援任务;为了便于量化计算将上述目标转化为统一的价值成本,共同决定救援车辆的行驶路径。研究结果表明:当行驶路段交叉口间距离较长,中间无其他道路连通,行驶过程中由于突发事件破坏趋势蔓延导致道路中断或拥堵等意外发生时,无法更新调整救援路径,最终导致救援延误;因此,基于救援时间和路径可靠性的车辆诱导最优化模型能够克服以上问题,进一步提高救援效率。

Abstract

In order to improve the efficiency of emergency rescue in expressway emergencies, the traffic conditions, potential risks on the road, and other traffic information were considered in this study of highway emergency rescue vehicle induction. Based on traffic information in a real-time and time-varying road network environment, the goal is to minimize the travel time of vehicles and obtain the strongest path reliability. In this paper, a combined strategy of real-time and time-varying information model is proposed so that the path planning can be adjusted periodically according to changes in road network traffic volume. The dynamic decision-making problem was transformed into a series of static decision-making problems at discrete time points by rolling time-domain strategy, which were then used to calculate the emergency rescue path time. On this basis, the traffic accident rates on a road network were increased, which is likely to cause congestion. This study further considered the reliability of the rescue path planning as the decision target. That is, the emergency rescue vehicle path planning has more adjustment strategies in the face of road interruptions or severe congestion in order to update the rescue path and complete the rescue task as soon as possible. In order to facilitate calculation, the above factors were converted into unified cost values. The research results showed that when the distance between road intersections is relatively large and there are no other road connections in the middle, the road interruptions or congestion caused by the spread of the destruction trend of emergencies in the driving process, the rescue path cannot be updated and adjusted, resulting in rescue delay. Therefore, the vehicle induction optimization model based on rescue time and path reliability can overcome the abovementioned problems and further improve rescue efficiency.

关键词

交通工程 / 车辆诱导 / 改进遗传算法 / 应急救援 / 高速公路突发事件

Key words

traffic engineering / vehicle scheduling / improvement the genetic algorithm / emergency rescue / expressway emergency

引用本文

导出引用
赵朋, 王建伟, 孙茂棚, 周雅欣. 高速公路突发事件救援车辆诱导[J]. 中国公路学报, 2018, 31(9): 175-181
ZHAO Peng, WANG Jian-wei, SUN Mao-peng, ZHOU Ya-xin. Vehicle Scheduling for Mountainous Expressway Traffic Emergency[J]. China Journal of Highway and Transport, 2018, 31(9): 175-181
中图分类号: U491.31   

参考文献

[1] BEN-TAL A, CHUNG B D, MANDALA S R, et al. Robust Optimization for Emergency Logistics Planning:Risk Mitigation in Humanitarian Relief Supply Chains[J]. Transportation Research Part B, 2011, 45(8):1177-1189.
[2] CHOU T Y, CHUNG L Y, LEE C C. Multiobjective Dynamic Length Genetic Algorithm to Solve the Emergency Logistic Problem[C]//IEEE. International Conference on Advanced Intelligent Mechatronics. New York:IEEE, 2012:1147-1152.
[3] MONTZ T, DIXIT V, WILMOT C, et al. Assessing the Effectiveness of Flexible Response in Evacuations. Natural Hazards Review, 2013, 14(3):200-210.
[4] LI J, OZBAY K, BARTIN B. Effects of Hurricanes Irene and Sandy in New Jersey:Traffic Patterns and Highway Disruptions During Evacuations[J]. Natural Hazards, 2015, 78(3):2081-2107.
[5] WEIGLE M C, OLARIU S. Intelligent Highway Infrastructure for Planned Evacuations[C]//IEEE. Performance, Computing, and Communications Conference, 2007. NewYork:IEEE, 2007:594-599.
[6] CHAI G, HUANG M M, HAN J, et al. Matching Method for Emergency Plans of Highway Traffic Based on Fuzzy Sets and Rough Sets[J]. Journal of Intelligent & Fuzzy Systems, 2015, 29(6):2421-2427.
[7] 王少飞,刘桂强,曾磊,等.长大公路隧道火灾事故专项应急预案编制[J].消防科学与技术,2012(2):197-200. WANG Shao-fei, LIU Gui-qiang, ZENG Lei, et al.Working-out Special Special Emergency Response Plan of Long and Large Road Tunnel Fire Accidents[J]. Fire Science and Technology, 2012(2):197-200.
[8] 顾鸿儒,孙连坤.基于层次颜色Petri网的交通紧急调度算法与建模.计算机工程与应用,2016,52(16):261-270. GU Hong-ru, SUN Lian-kun. Modeling and Algorithm of Emergency Traffic Vehicles Scheduling Based on Hierarchical Colored Petri Net[J]. Computer Engineering & Applications, 2016, 52(16):261-270.
[9] CHAI G, CAO J, HUANG W, et al. Optimized Traffic Emergency Resource Scheduling Using Time Varying Rescue Route Travel Time[J]. Neurocomputing, 2018, 275:1567-1575.
[10] 周永筝,邱恭安,邱永芳.车联网中交通安全消息动态优先调度机制.电讯技术,2017,57(2):132-138. ZHOU Yong-zheng, QIU Gong-an, QIU Yong-fang. Dynamic Priority Scheduling of Traffic Safety Messages in Internet of Vehicles[J]. Telecommunication Engineering, 2017, 57(2):132-138.
[11] 赵韩涛,翟京,毛宏燕,等.城市应急车辆调度模型优化研究[J].交通运输系统工程与信息,2010,10(4):125-130. ZHAO Han-tao, ZHAI Jing, MAO Hong-yan, et al. Optimization of Emergency Vehicle Scheduling Model[J]. Journal of Transportation Systems Engineering & Information Technology, 2010, 10(4):125-130.
[12] 田军,马文正,汪应洛,等.应急物资配送动态调度的粒子群算法[J].系统工程理论与实践,2011,31(5):898-906. TIAN Jun, MA Wen-zheng, WANG Ying-luo, et al. Emergency Supplies Distributing and Vehicle Routes Programming Based on Particle Swarm Optimization[J]. Systems Engineering-Theory & Practice, 2011, 31(5):898-906.
[13] 夏红云,江亿平,赵林度.基于双层规划的应急救援车辆调度模型[J].东南大学学报:自然科学版,2014,44(2):425-429. XIA Hong-yun, JIANG Yi-ping, ZHAO Lin-du. Emergency Rescue Vehicle Scheduling Model Based on Bi-level Programming[J]. Journal of Southeast University:Natural Science Edition, 2014, 44(2):425-429.
[14] 吴腾宇,徐寅峰,温新刚.预知信息和有限运载能力下应急车辆路径选择问题[J].系统工程理论与实践,2015,35(5):1224-1229. WU Teng-yu, XU Yin-feng, WEN Xin-gang, et al. The Emergency Vehicle Routing Problem with Capacity Constraint and Advanced Information[J]. Systems Engineering-Theory & Practice, 2015, 35(5):1224-1229.
[15] 马祖军,胡萍.实时/时变路网环境下城市出救点选择与救援车辆路径的集成动态优化[J].管理工程学报,2014,28(4):165-172. MA Zu-jun,HU Ping. Dynamic Optimization of Combined Emergency Response Facility Selection and Vehicle Routing Problem in Real-time and Time-dependent Road Networks in Urban Environments[J]. Journal of Industrial Engineering and Engineering Management, 2014, 28(4):165-172.
[16] 林杉,许宏科,刘占文,等.公路隧道突发事件CBR-RBR交通控制方法[J].交通运输工程学报,2011,11(4):108-113. LIN Shan, XU Hong-ke, LIU Zhan-wen, et al. Traffic Control Method of Highway Tunnel Emergency Based on CBR and RBR[J]. Journal of Traffic & Transportation Engineering, 2011, 11(4):108-113.
[17] 柴获,何瑞春,马昌喜,等.考虑风险公平的危险品运输车辆调度优化[J].上海交通大学学报,2017,51(7):855-862. CHAI Huo, HE Rui-chun, MA Chang-xi, et al. Optimization for Vehicle Scheduling Problem of Hazardous Materials Transportation Considering Risk Equity[J]. Journal of Shanghai Jiao Tong University, 2017, 51(7):855-862.
[18] BILLAH A H M M, ALAM M S. Seismic Fragility Assessment of Highway Bridges:A State-of-the-art Review[J]. Structure & Infrastructure Engineering, 2015, 11(6):804-832.
[19] SHAHPARVARI S, ABBASI B. Robust Stochastic Vehicle Routing and Scheduling for Bushfire Emergency Evacuation:An Australian Case Study[J]. Transportation Research Part A, 2017, 104:32-49.
[20] MURRAY-TUITE P, WOLSHON B. Evacuation Transportation Modeling:An Overview of Research, Development, and Practice[J]. Transportation Research Part C, 2013, 27(2):25-45.

基金

国家自然科学基金项目(41301130)
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