道路交通网络脆弱性动态辨识方法

张勇; 屠宁雯; 陶骏杰

道路交通网络脆弱性动态辨识方法

张勇^1,,
屠宁雯^{1, 2},
陶骏杰¹

1.
苏州大学城市轨道交通学院, 江苏苏州 215006
2.
华中科技大学管理学院, 湖北武汉 430074

基金项目:

国家自然科学基金项目 51108289

江苏省自然科学基金项目 10KJB580003

国家社会科学基金项目 13 & ZD175

详细信息

作者简介:
张勇(1978-), 男, 江苏如东人, 苏州大学副教授, 工学博士, 从事道路交通规划研究

中图分类号: U491.13
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- 被引次数: 0
出版历程
- 收稿日期: 2014-05-10
- 刊出日期: 2014-10-25

Identification method of dynamic road traffic network vulnerability

1.
School of Urban Railway Transportation, Soochow University, Suzhou 215006, Jiangsu, China
2.
School of Management, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China

More Information

Author Bio:
ZHANG Yong(1978-), male, associate professor, PhD, +86-512-67601052, sinkey@126.com

摘要

摘要: 分析了路段和节点的流量传播过程与离散的瞬时动态用户最优路径选择均衡条件, 建立了反应型的动态用户均衡网络交通流模型, 设计了对角化的启发式算法求解模型, 评价了动态化的道路网络脆弱性指数。分析结果表明: 在自由流速度为40km·h^-1、堵塞密度为125veh·km^-1的9节点12路段构成的算例路网中, 在时刻3路段1受损时, 路段3在高峰时的车辆数量从原有的50veh增加到了100veh, 入口流量增加1倍, 路段2的入口流量降为0;在路段3、6、7和10构成的路径上, 路段1受损使得此路径的车辆数将近增加1倍, 车辆数量的增加导致各路段的阻抗增加。提出的方法能刻画车辆绕开受损路段的交通流传播过程, 能有效辨识道路网络在各个路段各个时刻的脆弱性。
- 交通规划 /
- 交通网络 /
- 脆弱性 /
- 灾害 /
- 动态均衡
Abstract: The trfffc flow propagation process of section and node and the discrete instantaneous dynamic equilibrium condition of optimal route choice for user were analyzed, the reactive traffic flow model of dynamic user equilibrium network was established, diagonalizable heuristic algorithm was designed to solve the model, and the dynamic vulnerability index of road network was evaluated.Analysis result shows for an example road network with 12 sections and 9 nodes, free-flow speed is 40 km·h^-1 and jam density is 125 veh·km^-1, when section 1 is broken at time 3, vehicle amount at peak time increases from the original 50 veh to 100 veh at section 3, the inflow of section 3 increases by 1 time, and the inflow of section 2 drops to 0.The damage of section 1 doubles the vehicles on the path consisting of sections 3, 6, 7 and 10, the increase of vehicle amount leads to the increase of impedance on each section.The traffic flow propagation process of vehicle bypassing the broken section can be described, the proposed method is effective to identify the vulnerability of road network for each section at each time.
- traffic planning /
- traffic network /
- vulnerability /
- disaster /
- dynamic equilibrium

HTML全文

图 1 流入与流出车辆数量

Figure 1. Vehicle amounts of inflow and outflow

下载: 全尺寸图片幻灯片

图 2 算法流程

Figure 2. Algorithm flow

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图 3 算例网络

Figure 3. Example network

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图 4 算法的收敛效果

Figure 4. Algorithm convergence effect

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图 5 网络受损前后路段车辆数量

Figure 5. Vehicle amounts before and after network damage

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图 6 网络受损前后路段流入量

Figure 6. Inflows before and after network damage

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图 7 网络受损前后路段3的车辆数量

Figure 7. Vehicle amounts at section 3before and after network damage

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图 8 网络受损前后路段6的车辆数量

Figure 8. Vehicle amounts at section 6before and after network damage

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图 9 网络受损前后路段7的车辆数量

Figure 9. Vehicle amounts at section 7before and after network damage

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图 10 网络受损前后路段10的车辆数量

Figure 10. Vehicle amounts at section 10before and after network damage

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图 11 路网脆弱性指数

Figure 11. Road network vulnerability indexes

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表 1 路段长度与自由流时间

Table 1. Lengths and free-flow times of sections

下载: 导出CSV

表 2 OD需求

Table 2. OD demand

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表 3 阻抗函数系数

Table 3. Impedance function coeffcients

下载: 导出CSV

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