Yunxia Wu , Le Li , Chenming Jiang , Yangsheng Jiang , Zhihong Yao
{"title":"自动驾驶汽车自驾车行为对混合交通流的影响","authors":"Yunxia Wu , Le Li , Chenming Jiang , Yangsheng Jiang , Zhihong Yao","doi":"10.1016/j.physa.2025.130691","DOIUrl":null,"url":null,"abstract":"<div><div>With the development of automatic control and artificial intelligence technology, autonomous vehicles (AVs) are becoming more and more intelligent. However, this individual intelligence means that the driving behavior of AVs can be more aggressive and selfish. To investigate the impact of the selfish driving behavior of AVs on the characteristics of mixed traffic flow, this paper proposes a cellular automata model that considers the selfish driving behavior of AVs. First, we analyze the vehicle types in the current mixed traffic flow and develop a universal safety distance model. Then, based on this, a cellular automata model is proposed. This model can not only describe the longitudinal car-following and lateral lane-changing behavior of human-driven vehicles and AVs, but also characterize the selfish degree in the driving behavior of AVs. Finally, simulation experiments are designed to analyze the impact of the selfish driving behavior of AVs on the performance indicators of mixed traffic flow. The results show that: (1) The increase in the penetration rate of AVs has a positive effect on the average velocity, traffic stability, and throughput of mixed traffic flow; (2) On the whole, the selfish lane-changing behavior of AVs has a relatively small impact on the average velocity of mixed traffic flow. The impact becomes smaller with the increase in traffic density. (3) In most scenarios, the selfish car-following behavior of AVs has an improving effect on the average velocity and throughput of mixed traffic flow. In summary, the relevant research results can provide theoretical support for the design of micro-behavioral control schemes for AVs.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"672 ","pages":"Article 130691"},"PeriodicalIF":3.1000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of selfish driving behavior of autonomous vehicles on mixed traffic flow\",\"authors\":\"Yunxia Wu , Le Li , Chenming Jiang , Yangsheng Jiang , Zhihong Yao\",\"doi\":\"10.1016/j.physa.2025.130691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With the development of automatic control and artificial intelligence technology, autonomous vehicles (AVs) are becoming more and more intelligent. However, this individual intelligence means that the driving behavior of AVs can be more aggressive and selfish. To investigate the impact of the selfish driving behavior of AVs on the characteristics of mixed traffic flow, this paper proposes a cellular automata model that considers the selfish driving behavior of AVs. First, we analyze the vehicle types in the current mixed traffic flow and develop a universal safety distance model. Then, based on this, a cellular automata model is proposed. This model can not only describe the longitudinal car-following and lateral lane-changing behavior of human-driven vehicles and AVs, but also characterize the selfish degree in the driving behavior of AVs. Finally, simulation experiments are designed to analyze the impact of the selfish driving behavior of AVs on the performance indicators of mixed traffic flow. The results show that: (1) The increase in the penetration rate of AVs has a positive effect on the average velocity, traffic stability, and throughput of mixed traffic flow; (2) On the whole, the selfish lane-changing behavior of AVs has a relatively small impact on the average velocity of mixed traffic flow. The impact becomes smaller with the increase in traffic density. (3) In most scenarios, the selfish car-following behavior of AVs has an improving effect on the average velocity and throughput of mixed traffic flow. In summary, the relevant research results can provide theoretical support for the design of micro-behavioral control schemes for AVs.</div></div>\",\"PeriodicalId\":20152,\"journal\":{\"name\":\"Physica A: Statistical Mechanics and its Applications\",\"volume\":\"672 \",\"pages\":\"Article 130691\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physica A: Statistical Mechanics and its Applications\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378437125003437\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica A: Statistical Mechanics and its Applications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378437125003437","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
The impact of selfish driving behavior of autonomous vehicles on mixed traffic flow
With the development of automatic control and artificial intelligence technology, autonomous vehicles (AVs) are becoming more and more intelligent. However, this individual intelligence means that the driving behavior of AVs can be more aggressive and selfish. To investigate the impact of the selfish driving behavior of AVs on the characteristics of mixed traffic flow, this paper proposes a cellular automata model that considers the selfish driving behavior of AVs. First, we analyze the vehicle types in the current mixed traffic flow and develop a universal safety distance model. Then, based on this, a cellular automata model is proposed. This model can not only describe the longitudinal car-following and lateral lane-changing behavior of human-driven vehicles and AVs, but also characterize the selfish degree in the driving behavior of AVs. Finally, simulation experiments are designed to analyze the impact of the selfish driving behavior of AVs on the performance indicators of mixed traffic flow. The results show that: (1) The increase in the penetration rate of AVs has a positive effect on the average velocity, traffic stability, and throughput of mixed traffic flow; (2) On the whole, the selfish lane-changing behavior of AVs has a relatively small impact on the average velocity of mixed traffic flow. The impact becomes smaller with the increase in traffic density. (3) In most scenarios, the selfish car-following behavior of AVs has an improving effect on the average velocity and throughput of mixed traffic flow. In summary, the relevant research results can provide theoretical support for the design of micro-behavioral control schemes for AVs.
期刊介绍:
Physica A: Statistical Mechanics and its Applications
Recognized by the European Physical Society
Physica A publishes research in the field of statistical mechanics and its applications.
Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents.
Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.