{"title":"Spatiotemporal-rights-based coordinate control of isolated intersections under i-VICS","authors":"Song Yan, Yi Zhang, Jun-li Wang, X. Pei","doi":"10.1109/CVCI51460.2020.9338560","DOIUrl":null,"url":null,"abstract":"Most of the existing researches only consider vehicles and signals as control objects, and there are also problems of loss of space and time resources caused by unreasonable distribution of spatiotemporal-right. In this paper, an overall collaborative control model for intersections considering the distribution of spatiotemporal right, vehicle trajectory and signal timing was established. A solution algorithm for the assignment of spatiotemporal-rights based on decision tree C4.5 is proposed. A high-dimensional solution based on genetic algorithm and an enumerated low-dimensional solution for signal timing and vehicle trajectory optimization are proposed respectively. Finally, an overall control model including the phase and lane, signal timing and vehicle trajectory was established. The simulation program was developed with python3.7, and the effectiveness of algorithm proposed in this paper was verified by experiments. When flow intensity is 0.23, the algorithm has the best improvement effect, the high-dimensional and low-dimensional algorithms can reduce the delay by 57.6% and 44.8% respectively. It also verified that the algorithm has better adaptability to the change of traffic demand than the algorithm that only considers the vehicle trajectory or signal timing.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI51460.2020.9338560","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
Most of the existing researches only consider vehicles and signals as control objects, and there are also problems of loss of space and time resources caused by unreasonable distribution of spatiotemporal-right. In this paper, an overall collaborative control model for intersections considering the distribution of spatiotemporal right, vehicle trajectory and signal timing was established. A solution algorithm for the assignment of spatiotemporal-rights based on decision tree C4.5 is proposed. A high-dimensional solution based on genetic algorithm and an enumerated low-dimensional solution for signal timing and vehicle trajectory optimization are proposed respectively. Finally, an overall control model including the phase and lane, signal timing and vehicle trajectory was established. The simulation program was developed with python3.7, and the effectiveness of algorithm proposed in this paper was verified by experiments. When flow intensity is 0.23, the algorithm has the best improvement effect, the high-dimensional and low-dimensional algorithms can reduce the delay by 57.6% and 44.8% respectively. It also verified that the algorithm has better adaptability to the change of traffic demand than the algorithm that only considers the vehicle trajectory or signal timing.