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基于空间比和感知密度的混合自行车交通流模型
引用本文:李黎山,李冰,成卫.基于空间比和感知密度的混合自行车交通流模型[J].交通运输系统工程与信息,2019,19(1):104-110.
作者姓名:李黎山  李冰  成卫
作者单位:昆明理工大学 a. 基建处;b. 交通工程学院,昆明 650093
基金项目:国家自然科学基金/National Natural Science Foundation of China(61364019).
摘    要:针对混合自行车流的异质特性,从空间比和感知密度概念出发,分别对3种混合自行车流状态的密度及流量进行计算,并根据元胞传输模型得出混合自行车流交通波计算公式. 采用昆明市6种不同自行车道宽度的实际调查数据,以停车波和启动波作为验证参数,并与单一车流交通波(LWR)模型计算结果进行对比.结果表明,不同自行车道宽度下本文模型计算精度均高于单一车流交通波(LWR)模型;从MAPE可以看出,本文模型的停车波、启动波计算精度较单一车流交通波(LWR)模型分别提高9.25%、13.64%,表明本文模型能较好地描述混合自行车流运行特征,为进一步揭示混合自行车流交通机理提供新思路.

关 键 词:交通工程  混合自行车交通流  空间比  感知密度  交通波  元胞传输模型  
收稿时间:2018-09-30

Mixed Bicycle Traffic Flow Model Based on Space Split and Perceived Density
LI Li-shan,LI Bing,CHENG Wei.Mixed Bicycle Traffic Flow Model Based on Space Split and Perceived Density[J].Transportation Systems Engineering and Information,2019,19(1):104-110.
Authors:LI Li-shan  LI Bing  CHENG Wei
Institution:a. Infrastructure Construction Department; b. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650093, China
Abstract:Aiming at the heterogeneity of mixed bicycle flow, the density and flow of three mixed bicycle flow states were calculated from the concepts of space split and perceived density, and the traffic wave formula of mixed bicycle flow was derived from the cell transmission model (CTM). In this paper, the actual survey data of six different bicycle lanes width in Kunming are used, the stopping wave is taken as the contrast parameters, and the calculated results are compared with the single class LWR model. The results show that the calculation accuracy of the proposed model is higher than that of the single class LWR model under different bicycle lane widths, as can be seen from MAPE, the calculation accuracy of stopping wave and starting wave of the proposed model is 9.25% and 13.64% higher than that of the single class LWR model, respectively, which indicates that the proposed model can describe the running characteristics of the mixed bicycle flow well. It provides a new way to reveal the traffic mechanism of mixed bicycle flow.
Keywords:traffic engineering  mixed bicycle traffic flow  space split  perceived density  shockwave  cell transmission model  
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