{"title":"Research on Traffic Characteristics of Signal Intersections with Mixed Traffic Flow","authors":"X. Cui, Xiansheng Li, Xue-lian Zheng, X. Zhang, Lan Zhao, Jing-hai Zhang","doi":"10.1109/ICITE50838.2020.9231426","DOIUrl":null,"url":null,"abstract":"With the development of intelligent transportation system, the vehicle on the road by a single human gradually evolved into a vehicle flow with automatic driving vehicle and the acceleration automatic vehicle traffic, the mixed with different types of vehicle are bound to impact on traffic characteristics of vehicles, traffic characteristic of intersection is the intersection design and optimization of the premise and foundation. Therefore, this paper uses SUMO to simulate MV, AV and CAV mixed in pairs at different proportions to study the common characteristics of mixed vehicles at urban intersections. Firstly, different following models are defined for different vehicles to describe their different following behavior. Then, by setting the mixing rate of mixed vehicles to gradually increase, the traffic data of mixed vehicles at intersections under different proportions was obtained through simulation. Finally, through data analysis and calculation, the six indicators and the spatial and temporal trajectory map that can represent the traffic characteristics of mixed vehicles at intersections are obtained. From the analysis and comparison of the changing trend of the six indicators with the change of vehicle proportion and the spatial and temporal trajectory map, the optimal proportion of mixed vehicles with traffic capacity can be obtained. The research results can provide theoretical support for intelligent intersection design and optimization.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITE50838.2020.9231426","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the development of intelligent transportation system, the vehicle on the road by a single human gradually evolved into a vehicle flow with automatic driving vehicle and the acceleration automatic vehicle traffic, the mixed with different types of vehicle are bound to impact on traffic characteristics of vehicles, traffic characteristic of intersection is the intersection design and optimization of the premise and foundation. Therefore, this paper uses SUMO to simulate MV, AV and CAV mixed in pairs at different proportions to study the common characteristics of mixed vehicles at urban intersections. Firstly, different following models are defined for different vehicles to describe their different following behavior. Then, by setting the mixing rate of mixed vehicles to gradually increase, the traffic data of mixed vehicles at intersections under different proportions was obtained through simulation. Finally, through data analysis and calculation, the six indicators and the spatial and temporal trajectory map that can represent the traffic characteristics of mixed vehicles at intersections are obtained. From the analysis and comparison of the changing trend of the six indicators with the change of vehicle proportion and the spatial and temporal trajectory map, the optimal proportion of mixed vehicles with traffic capacity can be obtained. The research results can provide theoretical support for intelligent intersection design and optimization.