A Model and Method for Bottleneck Identification and Capacity Integration Equilibrium Distribution in Trunk Road Networks

Abstract

Abstract: In this paper, the analysis model and method for network capacity equilibrium based on virtual road networks have been proposed. Traffic burdens of the virtual road networks taken as several eigenvectors, a combined model of technology of PA back stepping and a model of traffic equilibrium assignment have been adopted, based on the virtual road networks, to identify the “real bottleneck points (lines or regions)” in the networks and gain a set of capacity equilibrium matching parameters between supply and demand of the networks. Based on this set of matching parameters, systemic deficiencies of the current networks have been diagnosed. A new theory and method for systemic analysis has been proposed to evaluate the level of macro matching between urban trunk networks and traffic demand, develop measures for reducing traffic congestions, synthetically distribute and improve the capacity of the networks under equilibrium.

Key words: integration of road network capacity, traffic congestion, virtual networks, traffic equilibrium, traffic burden

摘要： 本文提出了一套基于虚拟路网的容量均衡分析模型和方法。以虚拟路网（节点及路段）的交通负荷（V/C）为特征变量，采用虚拟路网PA反推技术与交通均衡配流组合模型，辨识路网的真实瓶颈点（段、区域），获得路网供需“均衡容量匹配参数”。以此匹配参数为准则，诊断现有路网的系统性缺陷。为评估城市干道路网与交通需求的宏观匹配水平、制定缓解交通拥堵对策和路网容量一体化均衡配置与改造，提供了新的系统分析理论和方法。

关键词: 路网容量一体化, 交通拥堵, 虚拟路网, 交通均衡, 交通负荷

CLC Number:

U491

Jiao Haixian, Hu Yingpeng, Liu Yizhou, Gong Weiyong. A Model and Method for Bottleneck Identification and Capacity Integration Equilibrium Distribution in Trunk Road Networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2007, 7(5): 63-67 .

焦海贤,胡迎鹏,刘以舟,公维勇. 干道路网瓶颈识别及容量一体化均衡配置模型与方法[J]. 交通运输系统工程与信息, 2007, 7(5): 63-67 .

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URL: http://www.tseit.org.cn/EN/abstract/abstract17579.shtml

http://www.tseit.org.cn/EN/Y2007/V7/I5/63

References

[1] PORTA S, CRUCITTI P and LATORA V. The Network Analysis of Urban Streets: A Dual Approach.arxiv.org preprint condmat/0411241, 2004.
[2] PORTA S, CRUCITTI P and LATORA V. The Network Analysis of Urban Streets: A Primal Approach.arxiv.org preprint physicas/0506009, 2005.
[3] 刘灿齐.现代交通规划学[M].北京：人民交通出版社,2001.
[LIU C Q. Advanced Traffic Planning. Beijing: China Communications Press, 2001.]
[4] 李景，等.由路段交通量推算OD出行量方法研究[J].交通运输工程学报，2001，1(2):78.
[LI J, PENG G X. A Study on Estimating OD Trips from Observed Link Flows. Journal of Traffic and Transportation Engineering, 2001, 1(2):78.]
[5] 陆化普，等.交通规划理论与方法[M].北京：清华大学出版社,1998.
[LU H P. Theory and Methods for Traffic Planning .Beijing: TSINGHUA UNIVERSITY Press, 1998.]
[6] 高自友,任华玲.城市动态交通流分配模型与算法[M].北京：人民交通出版社,2005.
[GAO Z Y, REN H L. Traffic Assignment Problems in Urban Transportation Networks: Models and Methods. Beijing: China Communications Press, 2005.]
[7] 王炜，等.城市交通网络综合平衡交通分配模型研究[J].东南大学学报，2000，30(1):117.
[WANG W, QU D Y, ZHU Z. On the Models of Integrated-Equilibrium Trip Assignment in Urban Traffic Network. Journal of Southeast University, 2000, 30(1):117]
[8] SHEFFI Y. Urban Transportation Network: Equilibrium Analysis with Mathematical Programming Methods [M].New York: Prentice Hall, 1985.
[9] JIAO Hai-xian, GONG Wei-yong, HU Ying-peng. A model for dynamic network traffic flow based on virtual space-time network, The First International Conference of Transportation Engineering (ICTE)，2007.3
[10] 姜桂艳，等.城市快速路交通拥挤识别方法[J].交通运输工程学报，2006，6(3):87.
[JIANG G Y, GANG L H, WAMH J F. Traffic Congestion Identification Method of Urban Expressway. Journal of Traffic and Transportation Engineering, 2006, 6(3):87.]
[11] 黄海军.城市交通网络平衡分析理论与实践[M].北京：人民交通出版社，1994.
[HUANG H J. Urban Transportation Network Equilibrium Analysis: Theory and Practice. Beijing: China Communications Press, 2005.]
[12] 黎茂盛，王炜等.降级路网的认知及交通流平衡分析模型[J].中国公路学报，2006，19(6):87.
[LI M S, WANG W, SHI F. Cognition of Degraded Road Network on Traffic Flow. China Journal of Highway and transport.2006, 19(6):87.]
[13] 焦海贤.随机动态交通分配模型的稳定性分析[J].重庆交通大学学报,2005,24(5):119
[JIAO H X. Stability Analysis for Stochastic Dynamic Traffic Assignment Models. JOURNAL OF CHONGQING JIAOTONG UNIVERSITY, 2005, 24(5):119.]

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