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网联交通环境下自适应交通事件的信号控制方法

蒋贤才 吴战领 伞景奇

华南理工大学学报(自然科学版)2025,Vol.53Issue(12):46-60,15.
华南理工大学学报(自然科学版)2025,Vol.53Issue(12):46-60,15.DOI:10.12141/j.issn.1000-565X.240533

网联交通环境下自适应交通事件的信号控制方法

Signal Control Method of Adaptive Traffic Events in Connected Traffic Environment

蒋贤才 1吴战领 1伞景奇1

作者信息

  • 1. 东北林业大学 土木与交通学院,黑龙江 哈尔滨 150040
  • 折叠

摘要

Abstract

The existing signal control methods for traffic incidents often fail to account for the impact of traffic flow redistribution caused by current intersection control scheme adjustments on adjacent intersections.This oversight essentially shifts traffic problems to adjacent intersections rather than resolving congestion effectively.In view of this,this study proposes an adaptive traffic incident signal control method(SCM-ATE)by leveraging the testability of networked traffic,the controllability of connected autonomous vehicles(CAVs),and the inducibility of connected human-driven vehicles.The SCM-ATE method uses the shortest path algorithm to plan the diversion path of ob-structed traffic flow based on the determination of lanes and traffic flow caused by events,as well as the sufficient traffic capacity of adjacent intersections.The optimization objective is to minimize the average delay of vehicles at all intersections on the diversion path.A dynamic programming approach is then applied to jointly optimize signal timings and trajectories of connected vehicles along the designated route,thereby mitigating the adverse effects of incidents.The simulation results show that under low,medium,and high traffic loads,compared with traditional sig-nal control methods,the SCM-ATE method reduces the average delay of vehicles by 12.56%,20.34%,and 5.29%,respectively.Compared with the single-layer method using single intersection traffic signals and collaborative ve-hicle trajectory joint optimization(JOTS-CVT),the average delay of vehicles is reduced by 13.27%,10.40%,and 1.25%,respectively.These outcomes confirm the effectiveness of SCM-ATE in enhancing traffic efficiency.Fur-ther research shows that the intersection traffic load and the penetration rate of networked autonomous vehicle have a significant impact on the optimization effect of SCM-ATE and the SCM-ATE method is more suitable for traffic scenarios where the penetration rate of networked autonomous vehicle is≥0.3 and the lane flow rate ratio at the in-tersection is≤0.7.

关键词

网联交通/交通分流/信号控制方法/自适应交通事件/车均延误

Key words

connected traffic/traffic diversion/signal control method/adaptive traffic events/average delay of ve-hicles

分类

交通工程

引用本文复制引用

蒋贤才,吴战领,伞景奇..网联交通环境下自适应交通事件的信号控制方法[J].华南理工大学学报(自然科学版),2025,53(12):46-60,15.

基金项目

黑龙江省自然科学基金项目(PL2024E012)Supported by the Natural Science Foundation of Heilongjiang Province(PL2024E012) (PL2024E012)

华南理工大学学报(自然科学版)

OA北大核心

1000-565X

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