{"title":"Plenary Autonomous Intersection Management Protocol for Heterogeneous Connected Vehicles","authors":"Ashkan Gholamhosseinian, J. Seitz","doi":"10.1109/ICUFN57995.2023.10200347","DOIUrl":null,"url":null,"abstract":"This paper proposes a centralized autonomous intersection management scheme for heterogeneous connected vehicles (HCVs). Contributions of this work are as follows. First, we sustainably classify heterogeneous vehicles with their distinctive safety-related characteristics. Second, we conduct a safe and efficient coordination algorithm with respect to some criteria such as vehicle types, road priorities and right of way rules. Third, we consider the impact of different road conditions, vehicle characteristics, load, and braking technology on the system performance. Forth, we demonstrate the efficiency of the system under various traffic densities with symmetric and asymmetric vehicle distribution. Besides, system performance is to be compared with traffic lights (TLs) scenarios in terms of throughput, average travel time (ATT), intersection busy time (IBT), channel busy rate (CBR), and packet loss rate (PLR) in various road conditions.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUFN57995.2023.10200347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a centralized autonomous intersection management scheme for heterogeneous connected vehicles (HCVs). Contributions of this work are as follows. First, we sustainably classify heterogeneous vehicles with their distinctive safety-related characteristics. Second, we conduct a safe and efficient coordination algorithm with respect to some criteria such as vehicle types, road priorities and right of way rules. Third, we consider the impact of different road conditions, vehicle characteristics, load, and braking technology on the system performance. Forth, we demonstrate the efficiency of the system under various traffic densities with symmetric and asymmetric vehicle distribution. Besides, system performance is to be compared with traffic lights (TLs) scenarios in terms of throughput, average travel time (ATT), intersection busy time (IBT), channel busy rate (CBR), and packet loss rate (PLR) in various road conditions.