摘要
为研究车联网环境下异质交通流的演变规律,基于改进的NaSch模型,针对智能网联化程度的前期、中期和后期分别进行仿真实验,得到交通流基本图,并分析通行能力与网联车渗透率的内在联系;其次,通过马尔可夫链证明了网联车形成的有序排列能提高道路通行能力,随机仿真实验验证了理论推导的正确性;最后,引入考虑车辆排列方式的相对熵,从而定量描述异质车流的有序性,阐明了智能网联车辆(connected and autonomous vehicle,CAV)改善交通状况的本质原因.研究结果表明:随着智能网联车渗透率的增加,通行能力增加,在智能网联化前期,渗透率的增加对通行能力提升较小,最高仅提升23.5%,中、后期通行能力最高能提升125.0%;在一定交通密度下,CAV渗透率与流量呈现正相关,相对熵与流量呈现负相关;智能网联车处于分离态时相对熵较小,分离态对随机混合的通行能力的提升随着CAV渗透率的增加而降低.
To understand the evolutionary law of heterogeneous traffic flows in intelligent network,based on the improved NaSch model,the simulation experiments are conducted respectively for the early,middle and late stages of intelligent network connectivity,and the basic diagram of traffic flow is obtained via numerical simulation to analyze the intrinsic connection between the capacity and the penetration rate of connected vehicles.Through Markov chain,the orderly arrangement of connected vehicles is proved to improve the road capacity,and random simulation experiments verify the theoretical derivation.The relative entropy in terms of vehicle arrangement is introduced to quantify the order of heterogeneous traffic flow,and clarify the essence of the connected and autonomous vehicle(CAV)improving traffic conditions.The results show that:the capacity increases with the penetration of CAV;in the early stage,the increase of penetration has a little effect on the capacity improvement with the maximum of 23.5%,while in the middle and late stages,it improves the capacity by 125.0%;under certain traffic density,CAV penetration positively correlates with traffic,and the relative entropy negatively correlates with traffic;when CAVs are in a separated state,the relative entropy is low and the improvement in the randomly mixed capacity reduces with increasing CAV penetration.
作者
吴德华
彭锐
林熙玲
WU Dehua;PENG Rui;LIN Xiling(College of Civil Engineering,Fuzhou University,Fuzhou 350108,China)
出处
《西南交通大学学报》
EI
CSCD
北大核心
2022年第4期761-768,共8页
Journal of Southwest Jiaotong University
基金
福建省自然科学基金(2016J01230)。
关键词
智能交通
异质交通流
元胞自动机
智能网联车
马尔可夫链
相对熵
intelligent transportation
heterogeneous traffic flow
cellular automaton
connected and autonomous vehicle
Markov chain
relative entropy
