{"title":"Traffic operation for longer battery life of connected automated vehicles in signal-free networks","authors":"Fushata A. Mohammed, Mahyar Amirgholy","doi":"10.1080/21680566.2023.2223769","DOIUrl":null,"url":null,"abstract":"Coordinating the movement of Connected Automated Vehicles (CAVs) can significantly improve traffic operations at signal-free intersections. However, we show there is a tradeoff between the operational capacity and the battery loss of CAVs at intersections. This research aims to enhance the battery life of CAVs with the minimum impact on operational capacity. To this end, we develop a stochastic model for the battery-capacity loss of CAV platoons at signal-free intersections. We account for the stochasticity in traffic operations at intersections by considering a probability distribution for the operational error in synchronizing the arrival and departure of consecutive platoons in crossing directions. We then balance the tradeoff between the battery-capacity loss rate and intersection capacity by optimizing the platoon size, traffic speed, and marginal gap length at a macroscopic scale. The numerical results of the research show that adjusting the macro-level control variables can improve CAVs' battery life by 27.6% at the cost of a 3.5% reduction from the maximum capacity.","PeriodicalId":48872,"journal":{"name":"Transportmetrica B-Transport Dynamics","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportmetrica B-Transport Dynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/21680566.2023.2223769","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 1
Abstract
Coordinating the movement of Connected Automated Vehicles (CAVs) can significantly improve traffic operations at signal-free intersections. However, we show there is a tradeoff between the operational capacity and the battery loss of CAVs at intersections. This research aims to enhance the battery life of CAVs with the minimum impact on operational capacity. To this end, we develop a stochastic model for the battery-capacity loss of CAV platoons at signal-free intersections. We account for the stochasticity in traffic operations at intersections by considering a probability distribution for the operational error in synchronizing the arrival and departure of consecutive platoons in crossing directions. We then balance the tradeoff between the battery-capacity loss rate and intersection capacity by optimizing the platoon size, traffic speed, and marginal gap length at a macroscopic scale. The numerical results of the research show that adjusting the macro-level control variables can improve CAVs' battery life by 27.6% at the cost of a 3.5% reduction from the maximum capacity.
期刊介绍:
Transportmetrica B is an international journal that aims to bring together contributions of advanced research in understanding and practical experience in handling the dynamic aspects of transport systems and behavior, and hence the sub-title is set as “Transport Dynamics”.
Transport dynamics can be considered from various scales and scopes ranging from dynamics in traffic flow, travel behavior (e.g. learning process), logistics, transport policy, to traffic control. Thus, the journal welcomes research papers that address transport dynamics from a broad perspective, ranging from theoretical studies to empirical analysis of transport systems or behavior based on actual data.
The scope of Transportmetrica B includes, but is not limited to, the following: dynamic traffic assignment, dynamic transit assignment, dynamic activity-based modeling, applications of system dynamics in transport planning, logistics planning and optimization, traffic flow analysis, dynamic programming in transport modeling and optimization, traffic control, land-use and transport dynamics, day-to-day learning process (model and behavioral studies), time-series analysis of transport data and demand, traffic emission modeling, time-dependent transport policy analysis, transportation network reliability and vulnerability, simulation of traffic system and travel behavior, longitudinal analysis of traveler behavior, etc.