考虑CAV自主停车行为的混合交通均衡配流模型  

Mixed traffic equilibrium assignment model considering automated parking behaviors of CAV

作　　者：韩飞[1] 王子捷 王建[2] 孙超 Han Fei;Wang Zijie;Wang Jian;Sun Chao(College of Transport Engineering,Chang an University,Xi'an 710064,China;School of Transportation,Southeast University,Nanjing 211189,China;School of Automotive and Traffic Engineering,Jiangsu University,Zhenjiang 212016,China)

机构地区：[1]长安大学运输工程学院,西安710064 [2]东南大学交通学院,南京211189 [3]江苏大学汽车与交通工程学院,镇江212016

出　　处：《东南大学学报（自然科学版）》2024年第1期208-213,共6页Journal of Southeast University：Natural Science Edition

基　　金：国家重点研发计划资助项目(2021YFB1600100);陕西省自然科学基金资助项目(2020JQ-370)。

摘　　要：为了评估网联自动驾驶汽车(CAV)的自主停车行为对交通系统效率的影响,建立了CAV通勤流、人工驾驶汽车(HDV)通勤流、CAV自主停车流3类交通流混行下的交通均衡配流模型.通过引入CAV停车需求内生变量,考虑CAV对路段通行能力的提升效应,从而定量描述CAV停车需求分布以及3类交通流在路段上混行的拥挤效应.分别采用用户均衡、随机用户均衡原则描述CAV、HDV出行者的路径选择行为,采用Logit离散选择模型描述自主停车CAV的停车场选择行为,由此建立多用户混合交通均衡条件以及等价的变分不等式(VI)模型.由于模型中CAV自主停车需求为未知的内生变量,提出一种改进的相继加权平均法求解该模型.最后,通过算例验证了混合交通均衡配流模型及求解算法的有效性.In order to evaluate the impacts of automated parking behaviors of connected and autonomous vehicle(CAV)on the traffic system efficiency,a traffic equilibrium assignment model is established in the context of the mixed traffic flows consisting of the commuter flows of CAV and human-driven vehicle(HDV)and automated parking flows of CAV.By introducing the endogenous variables of CAV parking demands and considering the improvement effect of CAV on road capacity,the demand distribution of CAV parking flows and the congestion effects of three types of mixed traffic flows on a road section are described quantitatively.The user equilibrium(UE)and stochastic user equilibrium(SUE)principles are adopted to describe the route choice behaviors of CAV and HDV travelers,respectively.Meanwhile,the Logit-based discrete choice model is adopted to describe the parking facility choice behaviors of the parking CAV.Based on them,the multi-class mixed traffic equilibrium conditions and the equivalent variational inequality(VI)model are established.Since the CAV parking demands are unknown endogenous variables in the model,the modified method of successive weighted averaging(MSWA)is developed to solve the model.Finally,numerical examples are provided to validate the effectiveness of the mixed traffic equilibrium assignment model and its solution algorithm.

关 键 词：智能交通 交通分配 自主停车行为 网联自动驾驶汽车 混合交通流 

分 类 号：U491[交通运输工程—交通运输规划与管理]