An Evaluation Study of Network Optimization through Connecting Dead-end-roads
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摘要: 针对断头路的存在会降低道路利用率、加剧交通拥堵等问题, 构建了断头路打通在路网结构以及交通分配层面上的优化评估方法。在路网结构层面, 采用社区探测对路网进行划分, 获取社区作为受断头路影响较大的路段组合; 在交通分配层面, 将断头路打通带来的影响量化为路段平均速率的变化, 构造路网阻抗函数作为约束条件, 在社区内部进行断头路打通前后2次交通分配; 通过连续平均算法建立求解算法, 选取2次用户均衡状态的路段平均速率变化百分比作为评价指数。以北京市朝阳区路网为算例进行分析, 结果表明: ①900 pcu出行需求约束下, 断头路打通的平均指数均值小于0.6%, 表明在低负荷区域打通断头路不能带来明显的优化; ②在剩余3组较大出行需求约束下, 打通跨社区断头路的评价指数均值(3.097%, 1.833%, 2.633%)都大于打通社区内断头路(2.077%, 1.785%, 2.041%), 在市政工程中应该优先考虑打通跨社区路段。Abstract: Dead-end-roads(DERs)are widespread in any city, and their presence can reduce the usage of roads and lead to traffic congestions. However, there are limited quantitative methods to assess the impacts of DERs. A new method is proposed to assess their impacts. At the level of road structure, community detection is used to classify the road network, and analyze the community which greatly affected by responded DERs. At the level of traffic assignment, whether a dead-end-road is opening, two simulations are performed in the community mentioned above. On this basis, the percentage change of the average value in roads' speeds is selected as an evaluation index. Then, this method is varified by a case study of the road network in Chaoyang District, Beijing. The results shows that: ①Under the travel demand of 900 pcu, the mean value of indices is less than 0.6%, indicating that opening DERs in the low-load area cannot bring obvious optimization. ② Under three groups of large travel demand, the mean value of indices of cross-community DERs(3.097%, 1.833%, and 2.633%)are higher than which of intra-community DERs(2.077%, 1.785%, and 2.041%). The opening of cross-community road sections should be given priority in municipal projects.
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表 1 道路通行参数设定
Table 1. Road traffic parameter setting
道路等级 限速(/km/h) 通行能力(/单向pcu) 快速路 80 4 800 主干路 60 2 800 次干路 50 1 690 支路 40 1 640 其他 30 1 550 表 2 评价指数统计表
Table 2. Statistics of evaluation indices
路段类型 评价指数统计 出行需求/pcu 900 1 800 2 700 3 600 跨社区 平均值 -0.445 3.097 1.833 2.633 标准差 3.317 6.037 3.207 7.844 社区内 平均值 0.589 2.077 1.785 2.041 标准差 13.801 11.162 15.230 12.380 -
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