Alireza Soltani, David M. Levinson, Mohsen Ramezani
{"title":"交叉口自动驾驶车辆无通信分布式控制算法","authors":"Alireza Soltani, David M. Levinson, Mohsen Ramezani","doi":"10.1016/j.trc.2025.105309","DOIUrl":null,"url":null,"abstract":"<div><div>This paper introduces a novel approach for managing autonomous vehicles at signal-free intersections through a <em>Communication-free Distributed Control Algorithm</em> (CfDCA). Unlike centralized systems or communication-based decentralized methods, CfDCA relies solely on onboard sensors and in-vehicle decision-making to ensure efficient and collision-free navigation. The algorithm formulates intersection management as a distributed optimization problem with demonstrated safety logics and robustness to measurement errors. The algorithm combines a dynamic resource acquisition graph with a refined priority function and an adaptive tolerance mechanism to ensure efficient performance under varying traffic conditions. A stochastic tie-breaking mechanism is proposed to handle rare cases of identical priorities, while deadlock prevention is guaranteed through strict priority ordering. Simulation experiments demonstrate that CfDCA reduces average delay and queue length and is able to achieve throughput higher than actuated signalized intersections and outperforms a first-come-first-served baseline in delay reduction. Additionally, the algorithm’s distributed design offers scalability and eliminates dependency on communication infrastructure.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"180 ","pages":"Article 105309"},"PeriodicalIF":7.6000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Communication-free Distributed Control Algorithm for autonomous vehicles at intersections\",\"authors\":\"Alireza Soltani, David M. Levinson, Mohsen Ramezani\",\"doi\":\"10.1016/j.trc.2025.105309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper introduces a novel approach for managing autonomous vehicles at signal-free intersections through a <em>Communication-free Distributed Control Algorithm</em> (CfDCA). Unlike centralized systems or communication-based decentralized methods, CfDCA relies solely on onboard sensors and in-vehicle decision-making to ensure efficient and collision-free navigation. The algorithm formulates intersection management as a distributed optimization problem with demonstrated safety logics and robustness to measurement errors. The algorithm combines a dynamic resource acquisition graph with a refined priority function and an adaptive tolerance mechanism to ensure efficient performance under varying traffic conditions. A stochastic tie-breaking mechanism is proposed to handle rare cases of identical priorities, while deadlock prevention is guaranteed through strict priority ordering. Simulation experiments demonstrate that CfDCA reduces average delay and queue length and is able to achieve throughput higher than actuated signalized intersections and outperforms a first-come-first-served baseline in delay reduction. Additionally, the algorithm’s distributed design offers scalability and eliminates dependency on communication infrastructure.</div></div>\",\"PeriodicalId\":54417,\"journal\":{\"name\":\"Transportation Research Part C-Emerging Technologies\",\"volume\":\"180 \",\"pages\":\"Article 105309\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2025-08-28\",\"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/S0968090X25003134\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X25003134","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}
Communication-free Distributed Control Algorithm for autonomous vehicles at intersections
This paper introduces a novel approach for managing autonomous vehicles at signal-free intersections through a Communication-free Distributed Control Algorithm (CfDCA). Unlike centralized systems or communication-based decentralized methods, CfDCA relies solely on onboard sensors and in-vehicle decision-making to ensure efficient and collision-free navigation. The algorithm formulates intersection management as a distributed optimization problem with demonstrated safety logics and robustness to measurement errors. The algorithm combines a dynamic resource acquisition graph with a refined priority function and an adaptive tolerance mechanism to ensure efficient performance under varying traffic conditions. A stochastic tie-breaking mechanism is proposed to handle rare cases of identical priorities, while deadlock prevention is guaranteed through strict priority ordering. Simulation experiments demonstrate that CfDCA reduces average delay and queue length and is able to achieve throughput higher than actuated signalized intersections and outperforms a first-come-first-served baseline in delay reduction. Additionally, the algorithm’s distributed design offers scalability and eliminates dependency on communication infrastructure.
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.