{"title":"Cluster-based route planning for electric vehicles travel time optimization","authors":"Alberto Ponso , Angelo Bonfitto","doi":"10.1080/15568318.2025.2474029","DOIUrl":null,"url":null,"abstract":"<div><div>Private mobility electrification is slowed down by technical limitations, such as the low autonomy of electric vehicles (EVs) compared to internal combustion engine vehicles (ICEVs). As a consequence, accurate planning of the route is needed before a travel with an EV begins. Routing algorithms are of crucial importance to identify the route which allows to minimize total travel time, reducing the drawbacks of battery’s limited energy density. The complexity of the problem and the size of road networks considered for this task imply computational times which are not in line with users’ needs. The method proposed in this article employs clustering and pruning techniques to speed up planning by downsizing the network analyzed during route planning. By reducing the computational cost, it is possible to apply Dijkstra algorithm, which provides an exact minimization of total travel time.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 3","pages":"Pages 277-296"},"PeriodicalIF":3.1000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Sustainable Transportation","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1556831825000103","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Private mobility electrification is slowed down by technical limitations, such as the low autonomy of electric vehicles (EVs) compared to internal combustion engine vehicles (ICEVs). As a consequence, accurate planning of the route is needed before a travel with an EV begins. Routing algorithms are of crucial importance to identify the route which allows to minimize total travel time, reducing the drawbacks of battery’s limited energy density. The complexity of the problem and the size of road networks considered for this task imply computational times which are not in line with users’ needs. The method proposed in this article employs clustering and pruning techniques to speed up planning by downsizing the network analyzed during route planning. By reducing the computational cost, it is possible to apply Dijkstra algorithm, which provides an exact minimization of total travel time.
期刊介绍:
The International Journal of Sustainable Transportation provides a discussion forum for the exchange of new and innovative ideas on sustainable transportation research in the context of environmental, economical, social, and engineering aspects, as well as current and future interactions of transportation systems and other urban subsystems. The scope includes the examination of overall sustainability of any transportation system, including its infrastructure, vehicle, operation, and maintenance; the integration of social science disciplines, engineering, and information technology with transportation; the understanding of the comparative aspects of different transportation systems from a global perspective; qualitative and quantitative transportation studies; and case studies, surveys, and expository papers in an international or local context. Equal emphasis is placed on the problems of sustainable transportation that are associated with passenger and freight transportation modes in both industrialized and non-industrialized areas. All submitted manuscripts are subject to initial evaluation by the Editors and, if found suitable for further consideration, to peer review by independent, anonymous expert reviewers. All peer review is single-blind. Submissions are made online via ScholarOne Manuscripts.