{"title":"Cooperative bus eco-approaching and lane-changing strategy in mixed connected and automated traffic environment","authors":"Yun Yuan, Yizhe Yuan, Bangjun Yuan, Xin Li","doi":"10.1016/j.trc.2024.104907","DOIUrl":null,"url":null,"abstract":"<div><div>In mixed traffic environments, existing bus eco-approaching and lane-changing methods fail to adequately consider the uncontrollability of human-driven vehicles and their interactions with surrounding vehicles during lane changes, often leading to increased fuel consumption and emissions. To address this issue, this paper proposes a two-stage cooperative bus motion control model during lane-changing and approaching stops: the first stage finds the optimal positions and timings for bus lane changes in a mixed traffic environment; the second stage constructs a Model Predictive Control (MPC)-based cooperative lane change controller, which couples the lateral and longitudinal movements of buses. Using Lyapunov stability theory, the stability of this controller is demonstrated. A solution algorithm that integrates the Pontryagin Minimum Principle (PMP) and the Broyden–Fletcher–Goldfarb–Shanno Sequential Quadratic Programming (BFGS-SQP) method is proposed. The proposed model is tested on real-world cases with the Simulation of Urban Mobility (SUMO). The results show that, compared to traditional strategies, the cooperative strategy improves lane-changing efficiency by 14.95 %, reduces fuel consumption by 17.24 %, and increases traffic stability by 25.21 %. Under high-traffic conditions, the proposed strategy can significantly reduce lane-changing time by 25.18 %. The higher coefficient values in the objective function drive buses to adopt more proactive actions to quickly complete the space creation process. The results in a whole bus line show the proposed method increases the lane-changing success rate by 25.42 % and reduces the waiting time by 37.35 %.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":7.6000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X24004285","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In mixed traffic environments, existing bus eco-approaching and lane-changing methods fail to adequately consider the uncontrollability of human-driven vehicles and their interactions with surrounding vehicles during lane changes, often leading to increased fuel consumption and emissions. To address this issue, this paper proposes a two-stage cooperative bus motion control model during lane-changing and approaching stops: the first stage finds the optimal positions and timings for bus lane changes in a mixed traffic environment; the second stage constructs a Model Predictive Control (MPC)-based cooperative lane change controller, which couples the lateral and longitudinal movements of buses. Using Lyapunov stability theory, the stability of this controller is demonstrated. A solution algorithm that integrates the Pontryagin Minimum Principle (PMP) and the Broyden–Fletcher–Goldfarb–Shanno Sequential Quadratic Programming (BFGS-SQP) method is proposed. The proposed model is tested on real-world cases with the Simulation of Urban Mobility (SUMO). The results show that, compared to traditional strategies, the cooperative strategy improves lane-changing efficiency by 14.95 %, reduces fuel consumption by 17.24 %, and increases traffic stability by 25.21 %. Under high-traffic conditions, the proposed strategy can significantly reduce lane-changing time by 25.18 %. The higher coefficient values in the objective function drive buses to adopt more proactive actions to quickly complete the space creation process. The results in a whole bus line show the proposed method increases the lane-changing success rate by 25.42 % and reduces the waiting time by 37.35 %.
期刊介绍:
Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.