基于路网抗毁可靠度的交通突发事件态势分析

交通运输系统工程与信息 ›› 2013, Vol. 13 ›› Issue (5): 79-85.

基于路网抗毁可靠度的交通突发事件态势分析

赵新勇^1,2，安实^*1，丛浩哲²

1. 哈尔滨工业大学交通科学与工程学院，哈尔滨 150001；2. 公安部道路交通安全研究中心，北京，100062

收稿日期:2013-03-12 修回日期:2013-05-15 出版日期:2013-10-25 发布日期:2013-11-08
作者简介:赵新勇（1968- ），男，江苏南通人，研究员.

Traffic Incident Situation Evaluation Based on Road Network Reliability of Invulnerability

ZHAO Xin-yong^1,2, AN Shi¹, CONG Hao-zhe²

1. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;2.Road Traffic Safety Research Center of the Ministry of Public Security, Beijing 100062, China

Received:2013-03-12 Revised:2013-05-15 Online:2013-10-25 Published:2013-11-08

摘要/Abstract

摘要：

非常态交通管理需要测算路网应对交通突发事件的能力，从而理解和判断事件态势的严重程度.引入路网抗毁可靠度的概念及方法，借助交通突发事件态势感知路网拓扑结构，建立基于路网抗毁可靠度的高速公路网络交通突发事件态势理解模型，并建立相应指标体系，最后对区域高速公路网子系统及整体网络的抗毁可靠度进行实例分析.路网抗毁可靠度与事发地点、网络结构及交通需求的空间分布密切相关，该模型能够从局部和整体双重角度评价路网的抗毁性能，可以满足交通管理部门对交通突发事件状态及趋势的判断需求.

关键词: 智能交通, 网络可靠性, 路网抗毁可靠度, 交通突发事件, 态势理解

Abstract:

To comprehend and evaluate the severity of traffic incident situations, an unconventional traffic management strategy should measure and calculate the severity of incident situations. This paper presents a freeway network traffic incident situation evaluation model by introducing the invulnerability concept in the complex network theory and perceiving the topological structure of a road network with the help of traffic incident situations. A case analysis was conducted for the invulnerability of a regional freeway network subsystem and the overall network. The model provides a solution for incident situation comprehension from the road network structure point of view. 

Key words: intelligent transportation, road network reliability, road network invulnerability, traffic incident situation, situation evaluation

中图分类号:

U491

赵新勇，安实，丛浩哲. 基于路网抗毁可靠度的交通突发事件态势分析[J]. 交通运输系统工程与信息, 2013, 13(5): 79-85.

ZHAO Xin-yong, AN Shi, CONG Hao-zhe. Traffic Incident Situation Evaluation Based on Road Network Reliability of Invulnerability[J]. Journal of Transportation Systems Engineering and Information Technology, 2013, 13(5): 79-85.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/abstract/abstract18649.shtml

http://www.tseit.org.cn/CN/Y2013/V13/I5/79

参考文献

[1]Asakura Y, Kashiwadani M. Road network reliability caused by daily fluctuation of traffic flow[C]//Proceedings of the 19th PTRC Summer Annual Meeting. Brighton, 1991. 

[2] Michael G H, Bell Iida Y. Transportation network analysis [M]. Hoboken: John Wiley & Sons, 1997.

[3] Asakura Y.Reliability measures of an origin and destination pair in a deteriorated road network with variable flows [C]//Proceeding of the 4th Meeting of the EURO Working Group in Transportation. Brighton, 1996.

[4]Anthony Chen, Hai Yang, Hong K Lo, et al. Capacity reliability of a road network: An assessment methodology and numerical results [J]. Transportation Research Part B, 2002, 36(3): 225-252.

[5]Anthony Chen, Hai Yang, Hong K Lo, et al. A capacity related reliability for transportation networks [J]. Journal of Advanced Transportation, 1999, 33(2): 183-200.

[6]Hong K Lo, YeouKoung Tung. Network with degradable links: Capacity analysis and design [J]. Transportation Research Part B, 2003, 37(4): 345-363.

[7]Cho D J, Morlork E K, Chen Z L. Efficient algorithms for measuring the reliability of transportation network system capacity [D]. Philadelphia: University of Pennsylvania, 2002.

[8]Michael G, H Bell. A game theory approach to measuring the performance reliability of transport networks [J]. Transportation Research Part B, 2000, 34(6): 533-545.

[9]Du Z P, Nicholson A. Degradable transportation systems: Sensitivity and reliability analysis [J]. Transportation Research Part B, 1997, 31(3): 225-237.

[10]Berdica K. An introduction to road vulnerability: What has been done is done and should be done [J]. Transport Policy, 2002, 9(2): 117-127.

[11]Tarlor M A P. Dense network traffic models, travel time reliability and traffic management: General introduction [J]. Journal of Advanced Transportation, 1992, 33(2): 218-233.

[1]	郭烈, 胥林立, 秦增科, 王旭. 自动驾驶接管影响因素分析与研究进展[J]. 交通运输系统工程与信息, 2022, 22(2): 72-90.
[2]	徐猛, 刘涛, 钟绍鹏, 姜宇. 城市智慧公交研究综述与展望[J]. 交通运输系统工程与信息, 2022, 22(2): 91-108.
[3]	程君, 张立炎, 陈启宏. 一种基于地图辅助的自动驾驶视-惯融合定位方法[J]. 交通运输系统工程与信息, 2022, 22(2): 117-126.
[4]	王国栋, 刘立, 孟宇, 马智萍, 郑淏清, 顾青, 白国星. 一体式车辆避撞轨迹规划与跟踪控制[J]. 交通运输系统工程与信息, 2022, 22(2): 127-136.
[5]	马东方, 陈曦, 吴晓东, 金盛. 基于强化学习的干线信号混合协同优化方法[J]. 交通运输系统工程与信息, 2022, 22(2): 145-153.
[6]	许波桅, 王玲玲, 李军军. 自动化码头多级作业超网络延误传导特性研究[J]. 交通运输系统工程与信息, 2022, 22(2): 280-289.
[7]	田会娟, 刘嘉伟, 翟佳豪, 邓琳琳. 基于多入侵线的视频车速检测方法[J]. 交通运输系统工程与信息, 2022, 22(1): 49-56.
[8]	贾彦峰, 曲大义, 赵梓旭, 王韬, 宋慧. 基于安全势场的网联自主车辆跟驰行为决策及模型[J]. 交通运输系统工程与信息, 2022, 22(1): 85-97.
[9]	刘文, 汪文博. 基于秩最小化矩阵去噪的船舶轨迹重构方法[J]. 交通运输系统工程与信息, 2022, 22(1): 106-114.
[10]	赵建东, 陈溱, 焦彦利, 张凯丽, 韩明敏. 重点营运车辆的异常驾驶行为识别研究[J]. 交通运输系统工程与信息, 2022, 22(1): 282-291.
[11]	徐东伟, 彭航, 商学天, 魏臣臣, 杨艳芳. 基于图自编码-生成对抗网络的路网数据修复[J]. 交通运输系统工程与信息, 2021, 21(6): 33-41.
[12]	游峰, 梁健中, 曹水金, 肖智豪, 吴镇江, 王海玮. 面向多目标跟踪的密集行人群轨迹提取和运动语义感知[J]. 交通运输系统工程与信息, 2021, 21(6): 42-54.
[13]	王福建, 俞佳浩, 赵锦焕, 梅振宇. 基于站点实时关联度的短时公交客流预测方法[J]. 交通运输系统工程与信息, 2021, 21(6): 131-144.
[14]	张毅, 姚丹亚, 李力, 裴华鑫, 晏松, 葛经纬. 智能车路协同系统关键技术与应用[J]. 交通运输系统工程与信息, 2021, 21(5): 40-51.
[15]	龙建成, 郭嘉琪. 动态交通分配问题研究回顾与展望[J]. 交通运输系统工程与信息, 2021, 21(5): 125-138.