{"title":"Unlocking potential capacity benefits of electric vehicles (EVs) with adaptive cruise control (ACC)","authors":"Servet Lapardhaja, Kemal Ulas Yagantekin, Mingyuan Yang, Tasnim Anika Majumder, Xingan (David) Kan, Mohamed Badhrudeen","doi":"10.1080/21680566.2023.2271668","DOIUrl":null,"url":null,"abstract":"Today’s mainstream vehicles are partially automated via Adaptive Cruise Control (ACC) that relies on on-board sensors to automatically adjust speed to maintain a safe following distance. Contrary to expectations for automated vehicles, ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. Fortunately, EV’s unique powertrain characteristics such as instantaneous torque and regenerative braking could allow ACC to adopt shorter headways and accelerate more swiftly to maintain shorter headways during queue discharge, therefore reverse the negative impact on capacity. This has been verified in a series of field experiments, which demonstrate that EVs with ACC could potentially achieve a capacity as high as 2,931 veh/hr/lane in steady-state conditions, and it can be sustained in non-steady-state conditions where speeds fluctuate and queues form.","PeriodicalId":48872,"journal":{"name":"Transportmetrica B-Transport Dynamics","volume":"34 2","pages":"0"},"PeriodicalIF":3.3000,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportmetrica B-Transport Dynamics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/21680566.2023.2271668","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: 0
Abstract
Today’s mainstream vehicles are partially automated via Adaptive Cruise Control (ACC) that relies on on-board sensors to automatically adjust speed to maintain a safe following distance. Contrary to expectations for automated vehicles, ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. Fortunately, EV’s unique powertrain characteristics such as instantaneous torque and regenerative braking could allow ACC to adopt shorter headways and accelerate more swiftly to maintain shorter headways during queue discharge, therefore reverse the negative impact on capacity. This has been verified in a series of field experiments, which demonstrate that EVs with ACC could potentially achieve a capacity as high as 2,931 veh/hr/lane in steady-state conditions, and it can be sustained in non-steady-state conditions where speeds fluctuate and queues form.
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.