华中科技大学学报（自然科学版）2024，Vol.52Issue(1)：118-125,8.DOI:10.13245/j.hust.240608
智能网联环境下CAV混行车流集聚策略及分析
Agglomeration strategy and analysis of CAV mixed traffic flow in intelligent and connected environment
摘要
Abstract
A multi-agent system(MAS)based connected autonomous vehicle(CAV)mixed traffic flow aggregation control model(MTF-ACM)was proposed to address the issue of increased conflicts and reduced efficiency caused by the inability of current intersection control methods to adapt to the mixed traffic of connected manual driving vehicles(CHV)and connected autonomous driving vehicles(CAV).A vehicle-to-vehicle(V2V)based mixed traffic flow aggregation strategy was constructed.To reduce the randomness of mixed traffic flow,a virtual dynamic pre-signal was designed,and the speed of the agglomerated platoon was induced through a spatiotemporal synchronization mechanism.According to the collaborative timing strategy of the main pre-signal,the agglomerated platoon passes through the intersection with the maximum possibility of not stopping.The research results showed that when the market penetration rate(MPR)of CAV is 60％,MTF-ACM achieves the best benefit of capacity,and when the traffic flow is approaching saturation.When the traffic flow approaches saturation,compared to no ACM and CAV-ACM,the average delay time and parking frequency of MTF-ACM decrease by more than 30％and 50％,while fuel consumption and CO2 emissions decrease by 20.59％and 22.21％,respectively.关键词
混行车流集聚控制模型/动态预信号/速度诱导/协同配时/不停车通过交叉口/主干路交叉口Key words
mixed traffic flow agglomeration control model(MTF-ACM)/dynamic pre-signal/speed guidance/cooperative timing/agglomerated platoon passes through the intersection/trunk road intersection分类
交通工程引用本文复制引用
梁军,李燕青,王文飒,于滨..智能网联环境下CAV混行车流集聚策略及分析[J].华中科技大学学报（自然科学版）,2024,52(1):118-125,8.基金项目
国家重点研发计划资助项目(2018YFB1600500) （2018YFB1600500）
江苏省研究生科研创新计划资助项目(KYCX22_3673). （KYCX22_3673）
