应急车路径与专用道协同优化的双层规划方法  

Bi-level Programming Method for Coordinated Optimization ofEmergency Vehicle Route and Dedicated Lanes

作　　者：龙科军[1,2] 邹道兴 刘洋 马昌喜[3] 马璐[4] LONG Kejun;ZOU Daoxing;LIU Yang;MA Changxi;MA Lu(Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-infrastructure Systems,Changsha University of Science&Technology,Changsha 410114,China;School of Traffic and Transportation Engineering,Changsha University of Science&Technology,Changsha 410114,China;School of Traffic and Transportation,Lanzhou Jiaotong University,Lanzhou 730070,China;China Merchants Chongqing Communications Technology Research&Design Institute Co Ltd,Chongqing 400067,China)

机构地区：[1]长沙理工大学,智能道路与车路协同湖南省重点实验室,长沙410114 [2]长沙理工大学,交通运输工程学院,长沙410114 [3]兰州交通大学,交通运输学院,兰州730070 [4]招商局重庆交通科研设计院有限公司,重庆400067

出　　处：《交通运输系统工程与信息》2025年第1期202-211,共10页Journal of Transportation Systems Engineering and Information Technology

基　　金：国家自然科学基金(52172313,52062027);新疆维吾尔自治区重点研发计划项目(2023B03004-3)。

摘　　要：已有应急车辆路径规划的研究中,专用车道布设方案通常被视为已知条件,因此,本文提出一种同时优化应急车路径及专用车道的双层规划模型。在规划应急车路径时,将是否设置应急专用车道定义为模型的决策变量,并引入前景理论来衡量设置专用车道对交通流的影响。上层模型目标函数包含应急车行程时间和顺畅通行前景值两部分,其中前景值作为部署应急专用车道的决策依据;下层模型基于Wardrop均衡原理进行交通分配。结合遗传算法和禁忌搜索算法,提出GA-TS(Genetic Algorithm-Tabu Search)算法求解模型。通过在Nguyen-Dupuis仿真网络上进行数值实验,验证了模型和算法的有效性。实验结果表明:与不部署应急专用车道相比,在不增加路径交通饱和度的情况下,本文模型能将应急车辆的行程时间缩短10.69%。敏感性分析结果表明,在不同交通需求下,本文模型均能有效缩短应急车辆行程时间,并且随着交通需求增大,应急车辆行程时间缩短越明显。此外,相比于暴力搜索算法,本文设计的算法在求解模型时的平均耗时降低了87.02%,显著提高了模型的求解效率。Existing research on emergency vehicle route planning typically treating the deployment of dedicated lanes as a predetermined condition.This study proposes a bi-level programming model that concurrently optimizes emergency vehicle route and dedicated lane deployment.In this model,the deployment of dedicated lanes on each road segment is defined as a decision variable in route planning.Prospect theory is introduced to evaluate the impact of these dedicated lanes on traffic saturation.The objective function of the upper-level model comprises two components:emergency vehicle travel time and the prospect value of emergency vehicles travel smoothly,with the latter serving as the decision criterion for dedicated lane deployment.The lower-level model performs traffic assignment based on Wardrop's Equilibrium Principle.An innovative GATS algorithm,combining tabu search and genetic algorithm,is proposed to solve the model.Numerical experiments on the Nguyen-Dupuis simulation network verify the effectiveness of the model and algorithm.Results show that this model reduces emergency vehicle travel time by 10.69%without increasing traffic saturation.Multiple experiments under different traffic demands further confirm that the proposed model can effectively shorten the travel time of emergency vehicles with insignificant impact on traffic saturation,and this reduction becomes more pronounced with increasing traffic demand.Additionally,the GA-TS algorithm improves solving efficiency by reducing the average solution time by 87.02%.

关 键 词：城市交通 应急车辆优先 遗传算法 路径优化 前景理论 

分 类 号：U491[交通运输工程—交通运输规划与管理]