{"title":"自动驾驶车辆专用车道信号交叉口通行能力模型","authors":"","doi":"10.1080/19427867.2023.2236852","DOIUrl":null,"url":null,"abstract":"<div><p>This paper proposes a capacity model to address the impact of automated dedicated lanes on the capacity of the signalized intersection. Firstly, the car-following modes in the mixed traffic flow are analyzed, and the influence of the setting of the automated dedicated lanes on the average headway is discussed. Secondly, a new capacity model with automated dedicated lanes is derived based on the classic capacity model. Then, a signalized intersection capacity model considering the automated dedicated lanes is further derived based on the saturation flow rate method. Finally, numerical simulation experiments are designed to discuss the key parameters on the traffic capacity of a signalized intersection. The results show that (i) the automated dedicated lanes are conducive to improving the traffic capacity; (ii) when the penetration rate of CAVs is less than 52%, the traffic capacity of the signalized intersection can be increased by nearly 1.25 times with the automated dedicated lanes. These findings can provide theoretical support for designing and optimizing signalized intersections in high levels (i.e. L3-L5) CAVs environments.</p></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 7","pages":"Pages 725-737"},"PeriodicalIF":3.3000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A capacity model of signalized intersection with dedicated lanes for automated vehicles\",\"authors\":\"\",\"doi\":\"10.1080/19427867.2023.2236852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper proposes a capacity model to address the impact of automated dedicated lanes on the capacity of the signalized intersection. Firstly, the car-following modes in the mixed traffic flow are analyzed, and the influence of the setting of the automated dedicated lanes on the average headway is discussed. Secondly, a new capacity model with automated dedicated lanes is derived based on the classic capacity model. Then, a signalized intersection capacity model considering the automated dedicated lanes is further derived based on the saturation flow rate method. Finally, numerical simulation experiments are designed to discuss the key parameters on the traffic capacity of a signalized intersection. The results show that (i) the automated dedicated lanes are conducive to improving the traffic capacity; (ii) when the penetration rate of CAVs is less than 52%, the traffic capacity of the signalized intersection can be increased by nearly 1.25 times with the automated dedicated lanes. These findings can provide theoretical support for designing and optimizing signalized intersections in high levels (i.e. L3-L5) CAVs environments.</p></div>\",\"PeriodicalId\":48974,\"journal\":{\"name\":\"Transportation Letters-The International Journal of Transportation Research\",\"volume\":\"16 7\",\"pages\":\"Pages 725-737\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Letters-The International Journal of Transportation Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/org/science/article/pii/S1942786723001546\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Letters-The International Journal of Transportation Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1942786723001546","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
A capacity model of signalized intersection with dedicated lanes for automated vehicles
This paper proposes a capacity model to address the impact of automated dedicated lanes on the capacity of the signalized intersection. Firstly, the car-following modes in the mixed traffic flow are analyzed, and the influence of the setting of the automated dedicated lanes on the average headway is discussed. Secondly, a new capacity model with automated dedicated lanes is derived based on the classic capacity model. Then, a signalized intersection capacity model considering the automated dedicated lanes is further derived based on the saturation flow rate method. Finally, numerical simulation experiments are designed to discuss the key parameters on the traffic capacity of a signalized intersection. The results show that (i) the automated dedicated lanes are conducive to improving the traffic capacity; (ii) when the penetration rate of CAVs is less than 52%, the traffic capacity of the signalized intersection can be increased by nearly 1.25 times with the automated dedicated lanes. These findings can provide theoretical support for designing and optimizing signalized intersections in high levels (i.e. L3-L5) CAVs environments.
期刊介绍:
Transportation Letters: The International Journal of Transportation Research is a quarterly journal that publishes high-quality peer-reviewed and mini-review papers as well as technical notes and book reviews on the state-of-the-art in transportation research.
The focus of Transportation Letters is on analytical and empirical findings, methodological papers, and theoretical and conceptual insights across all areas of research. Review resource papers that merge descriptions of the state-of-the-art with innovative and new methodological, theoretical, and conceptual insights spanning all areas of transportation research are invited and of particular interest.