摘要
针对城市路网各类突发事件频繁发生,如何在事件发生之后,找到一条应急车辆行驶的最优路径,对于降低事故的危害程度起着至关重要的作用。文章在综合考虑影响应急救援路径选择多个因素的基础上,从交通状态性和安全性两方面对应急车辆的路径进行了分析,并利用TOPSIS算法构建了应急车辆的多目标最优路径选择模型,最后采用改进的蚁群系统算法对该模型进行求解。相关的案例结果显示,所研究的路径选择模型可以使应急车辆有效避开拥堵路段,在途行程时间减少8.33%。
In view of the frequent occurrence of various emergencies on the urban road network,how to find an optimal route for emergency vehicles to drive after the occurrence of incidents plays a crucial role in reducing the harm degree of accidents.In this study,based on comprehensive consideration of multiple factors that affect the selection of emergency rescue routes,the path of emergency vehicles is analyzed from the aspects of traffic condition and safety,and the TOPSIS algorithm is used to construct the multi-objective optimal path of emergency vehicles.Select the model,and finally use the improved ant colony system algorithm to solve the model.Relevant case results show that the route selection model of this study can make emergency vehicles effectively avoid congested road sections and reduce the travel time on the road by 8.33%.
作者
姚佼
邵楚薇
王品乘
韦钰
YAO Jiao;SHAO Chuwei;WANG Pincheng;WEI Yu(Management School,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《物流科技》
2020年第4期83-87,99,共6页
Logistics Sci-Tech
基金
教育部人文社会科学研究青年基金项目(17YJCZH225)
上海市青年科技英才扬帆计划项目(19YF1435100)。
关键词
应急车辆
路径选择模型
多目标
改进蚁群算法
TOPSIS算法
emergency vehicle
path selection model
multi-objective
improved ant colony algorithm
TOPSIS algorithm
作者简介
姚佼(1982-),男,山西芮城人,上海理工大学管理学院,副教授,工学博士,硕士生导师,研究方向:智能交通控制、交通系统工程;邵楚薇(1996-),女,浙江绍兴人,上海理工大学管理学院硕士研究生,研究方向:智能交通控制。
