基于改进蚁群算法的车辆环保路径规划方法OA
A vehicle environmental-friendly path planning method based on improved ant colony algorithm
为减少城市道路上的汽车尾气排放和燃油消耗,提出一种基于改进蚁群算法的车辆环保行驶路径诱导方法.基于比功率法构建汽车行驶过程尾气排放模型,建立以汽车燃油消耗和尾气排放最小为目标的混合整数规划模型,通过改进蚁群算法对模型进行求解.以中国云南省玉溪市某区域作为研究对象,通过对该区域车载诊断系统数据的实验分析表明,与最短路径相比,本方法所求解路径在总长度增加10.95%的情况下,车辆行驶总排放量减少10.97%,总油耗量减少17.63%.车辆环保路径可在汽车行驶距离小幅增长的情况下,有效降低行驶过程产生的排放和油耗.
To reduce exhaust emissions and fuel consumption from vehicles traveling on urban roads,this paper presents an environmentally friendly vehicle routing guidance method based on an improved ant colony algorithm.Firstly,an exhaust emission model for vehicle travel is constructed using the specific power approach,and a mixed integer programming model is established with the objective of minimizing vehicle fuel consumption and exhaust emissions.Then,the improved ant colony algorithm is used to solve the model.Finally,taking a specific area in Yuxi city of Yunnan province as the research object,experimental analysis of on-board diagnostics(OBD)data in this region demonstrates that compared to the shortest path,the path obtained by this method reduces total vehicle emissions by 10.97%and total fuel consumption by 17.63%,despite an increase in total length by 10.95%.Environmentally friendly vehicle routing can effectively reduce emissions and fuel consumption during travel,even with a slight increase in driving distance.
陈昱光;高加尧;胡山;黄金涛;郭凤香
昆明理工大学交通工程学院,云南 昆明 650500||东南大学交通学院,江苏 南京 211189昆明理工大学交通工程学院,云南 昆明 650500昆明理工大学交通工程学院,云南 昆明 650500昆明理工大学交通工程学院,云南 昆明 650500||东南大学交通学院,江苏 南京 211189昆明理工大学交通工程学院,云南 昆明 650500
交通工程
城市交通管理路径规划节能减排车载诊断系统数据比功率法改进蚁群算法
urban traffic managementroute planningenergy conservation and emission reductionon-board diagnostics(OBD)dataspecific power methodimproved ant colony algorithm
《深圳大学学报（理工版）》 2026 (1)
57-64,8
National Natural Science Foundation of China(52462050)Foundation of Yunnan Innovation Team of Vehicle-Road Cooperation Control and Operation Safety(202505AS350024)Foundation of Yunnan International Joint Laboratory on Intelligent and Connected Transportation(202503AP140016)国家自然科学基金资助项目(52462050)云南省车路协同控制与运行安全创新团队基金资助项目(202505AS350024)云南省智能网联交通国际联合实验室基金资助项目(202503AP140016)
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