{"title":"Eco-friendly platooning operation algorithm of the electric vehicles","authors":"Joonwon Jang , Sung Il Kwag , Young Dae Ko","doi":"10.1080/15472450.2023.2209911","DOIUrl":null,"url":null,"abstract":"<div><div>Platooning is one of the promising technologies that maximizes the power efficiency of electric vehicles by decreasing the distances between the vehicles. Along with the development of autonomous driving technology, platooning is expected to be commercialized. Recent studies on the operation of platooning focused on power-efficient maintenance of platooning. However, power-efficient operation strategy is also needed for practical applications. Therefore, this study deals with platooning operations that can maximize the power efficiency of electric vehicles in various operational situations. In order to derive the operation method, a mathematical model structured with an objective function that minimizes power consumption is developed. To derive the solution of the mathematical model, a hybrid genetic algorithm is applied. The numerical experiments on four different operational situations are performed to verify the validity of the model and the solution procedure. The four situations consider overall situation that can happen during the platooning stage. The stages are formation, disassembly, join and breakaway of vehicles of platoon. Those four situations are decided upon since they can represent the general situation that can happen during platooning. As a result, the power-efficient driving patterns of electric vehicles are identified. After the development of electric and systematic technology, operational technology for platooning will collaborate for the further improvement. Therefore, throughout consideration of the formation of platooning, technology will expand the sustainability of technological development.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 6","pages":"Pages 775-792"},"PeriodicalIF":2.8000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Transportation Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1547245023000804","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Platooning is one of the promising technologies that maximizes the power efficiency of electric vehicles by decreasing the distances between the vehicles. Along with the development of autonomous driving technology, platooning is expected to be commercialized. Recent studies on the operation of platooning focused on power-efficient maintenance of platooning. However, power-efficient operation strategy is also needed for practical applications. Therefore, this study deals with platooning operations that can maximize the power efficiency of electric vehicles in various operational situations. In order to derive the operation method, a mathematical model structured with an objective function that minimizes power consumption is developed. To derive the solution of the mathematical model, a hybrid genetic algorithm is applied. The numerical experiments on four different operational situations are performed to verify the validity of the model and the solution procedure. The four situations consider overall situation that can happen during the platooning stage. The stages are formation, disassembly, join and breakaway of vehicles of platoon. Those four situations are decided upon since they can represent the general situation that can happen during platooning. As a result, the power-efficient driving patterns of electric vehicles are identified. After the development of electric and systematic technology, operational technology for platooning will collaborate for the further improvement. Therefore, throughout consideration of the formation of platooning, technology will expand the sustainability of technological development.
期刊介绍:
The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new.
The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption.
The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.