基于无人驾驶车辆的不同车道模式交通流优化  

Traffic flow optimization of different lane modes based on autonomous vehicles

作　　者：周昭明 黄中祥[3] 袁剑波[3] 李盼[2] ZHOU Zhao-ming;HUANG Zhong-xiang;YUAN jian-bo;LI pan(Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road&Traffic Safety of Ministry of Education,Changsha University of Science&Technology,Changsha 410114,Hunan,China;School of Civil Engineering,Hunan City University,Yiyang 413000,Hunan,China;School of Traffic and Transportation Engineering,Changsha University of Science Technology,Changsha 410004,Hunan,China)

机构地区：[1]长沙理工大学道路灾变防治及交通安全教育部工程研究中心,湖南长沙410114 [2]湖南城市学院土木工程学院,湖南益阳413000 [3]长沙理工大学交通运输工程学院,湖南长沙410004

出　　处：《长安大学学报（自然科学版）》2021年第1期103-115,共13页Journal of Chang’an University(Natural Science Edition)

基　　金：国家自然科学基金项目(E080703);湖南省大学生创新创业训练计划项目(S202011527008);长沙理工大学道路灾变防治及交通安全教育部工程研究中心开放基金项目(kfj190406);湖南省教育厅科学研究项目(20C0375,20A093)。

摘　　要：为研究不同类型车辆组成的混合交通流的运行模式,假定无人驾驶车辆、先进出行者出行系统(advanced traveler information systems,ATIS)装置车辆和普通驾驶车辆分别遵从系统最优模式、用户均衡模式、随机用户均衡模式选择路径,分别建立普通车道、专用车道模式下的交通分配模型,给出求解模型的连续平均算法(method of successive averages,MSA)。通过算例确定路段通行能力,分析信息质量水平、出行需求量、市场渗透率对出行时间的影响,在确定模型各项参数取值的基础上,根据专用车道设置情况对混合均衡流状态进行研究,验证模型算法的可行性和收敛性。研究结果表明:通行能力随着行驶速度的增加先提高后下降,选择合适的行驶速度将提高路段通行能力,且无人驾驶专用道的通行能力明显高于普通车道;适当提高信息质量水平,可降低路径选择的随机性,有效减少平均出行时间;随着出行需求量的增加,平均出行时间逐渐提高,其中系统最优模式(无人驾驶专用道)的平均出行时间最小;根据市场渗透率的变化情况选择合适的车道配置模式,既能提高道路资源的使用效率,又能减少出行者的出行成本;不同车道配置模式下的混合交通流均随着迭代次数的增加逐渐达到稳定状态;当无人驾驶车辆的市场渗透率较高时,设置无人驾驶专用道将缩短行驶时间,提高运行效率。In order to research the operation mode of mixed traffic flow composed of different types of vehicles, it was assumed that autonomous vehicles, advanced traveler information systems(ATIS) device vehicles and ordinary driving vehicles respectively follow the system optimum mode, user equilibrium mode and stochastic user equilibrium mode to select the path. The traffic assignment models of ordinary lane and special lane were established respectively, and method of successive averages(MSA) algorithm was cooperated with the model. The calculation of road capacity, the influence of information quality level, travel demand and market penetration on travel time was analyzed through an example. On the basis of determining the parameters of the model, the mixed equilibrium flow state was researched according to the setting of the special lane, and the feasibility and convergence of the model algorithm were verified. The results show that with the increase of driving speed, the traffic capacity first increases and then decreases, choosing an appropriate driving speed will improve the road capacity, and the capacity of the autonomous lane will be significantly higher than that of the ordinary lane. Properly improving the level of information quality can reduce the randomness of route selection and effectively reduce the average travel time. With the increase of travel demand, the average travel time gradually increases, among which the average travel time of the system optimal mode(autonomous lane) is the smallest. According to the change of market penetration rate, choosing the appropriate lane configuration mode can not only improve the use efficiency of road resources, but also reduce the travel cost of travelers. The mixed traffic flow under different lane configuration modes gradually reaches a stable state with the increase of iteration times. When the market penetration rate of autonomous vehicles is high, the setting of autonomous driving lanes will shorten the driving time and improve the operating efficiency. 9 ta

关 键 词：交通工程 混合交通流优化 连续平均法 无人驾驶车辆 市场渗透率 专用车道 

分 类 号：U491.1[交通运输工程—交通运输规划与管理]