{"title":"Eco-Cooperative Driving at Back-to-Back Signalized Intersections for Battery-Electric Vehicles During Both Red and Green Phases of the Traffic Light","authors":"Ali Parsi, Ebrahim Farjah, Teymoor Ghanbari","doi":"10.1155/atr/5983597","DOIUrl":null,"url":null,"abstract":"<p>Battery electric vehicles (BEVs) are known as a sustainable solution for decarbonizing the transportation system and attaining the objectives of Paris Agreement. The main challenge issues for the widespread adoption of BEVs are battery capacity and driving range limitations. Signalized intersections are one of the places where a considerable amount of the total trip energy is consumed due to their stop-and-go nature. One efficient solution to deal with range limitations in BEVs is eco-driving. In this study, an eco-cooperative driving strategy was developed for BEVs at back-to-back signalized intersections in free-flow traffic. The optimal trip time and acceleration and deceleration levels are calculated to enable the vehicle to pass through signalized intersections without stopping. The proposed eco-cooperative driving optimizes a cost function that considers both energy consumption and travel time. The optimization problem was solved using an approach based on the particle swarm optimization technique. The results show that the proposed eco-cooperative driving strategy could save energy consumption and trip time up to 26.61% and 44.29%, respectively.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5983597","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advanced Transportation","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/atr/5983597","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
Battery electric vehicles (BEVs) are known as a sustainable solution for decarbonizing the transportation system and attaining the objectives of Paris Agreement. The main challenge issues for the widespread adoption of BEVs are battery capacity and driving range limitations. Signalized intersections are one of the places where a considerable amount of the total trip energy is consumed due to their stop-and-go nature. One efficient solution to deal with range limitations in BEVs is eco-driving. In this study, an eco-cooperative driving strategy was developed for BEVs at back-to-back signalized intersections in free-flow traffic. The optimal trip time and acceleration and deceleration levels are calculated to enable the vehicle to pass through signalized intersections without stopping. The proposed eco-cooperative driving optimizes a cost function that considers both energy consumption and travel time. The optimization problem was solved using an approach based on the particle swarm optimization technique. The results show that the proposed eco-cooperative driving strategy could save energy consumption and trip time up to 26.61% and 44.29%, respectively.
期刊介绍:
The Journal of Advanced Transportation (JAT) is a fully peer reviewed international journal in transportation research areas related to public transit, road traffic, transport networks and air transport.
It publishes theoretical and innovative papers on analysis, design, operations, optimization and planning of multi-modal transport networks, transit & traffic systems, transport technology and traffic safety. Urban rail and bus systems, Pedestrian studies, traffic flow theory and control, Intelligent Transport Systems (ITS) and automated and/or connected vehicles are some topics of interest.
Highway engineering, railway engineering and logistics do not fall within the aims and scope of JAT.