{"title":"Edge-Assisted Collaborative Perception in Autonomous Driving: A Reflection on Communication Design","authors":"Ruozhou Yu, Dejun Yang, Hao Zhang","doi":"10.1145/3453142.3491413","DOIUrl":null,"url":null,"abstract":"Collaborative perception enables autonomous driving vehicles to share sensing or perception data via broadcast-based vehicle-to-everything (V2X) communication technologies such as Cellular-V2X (C-V2X), hoping to enable accurate perception in face of inaccurate perception results by each individual vehicle. Nevertheless, the V2X communication channel remains a significant bottleneck to the performance and usefulness of collaborative perception due to limited bandwidth and ad hoc communication scheduling. In this paper, we explore challenges and design choices for V2X-based collaborative perception, and propose an architecture that lever-ages the power of edge computing such as road-side units for central communication scheduling. Using NS-3 simulations, we show the performance gap between distributed and centralized C-V2X scheduling in terms of achievable throughput and communication efficiency, and explore scenarios where edge assistance is beneficial or even necessary for collaborative perception.","PeriodicalId":6779,"journal":{"name":"2021 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"2 1","pages":"371-375"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACM Symposium on Edge Computing (SEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3453142.3491413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Collaborative perception enables autonomous driving vehicles to share sensing or perception data via broadcast-based vehicle-to-everything (V2X) communication technologies such as Cellular-V2X (C-V2X), hoping to enable accurate perception in face of inaccurate perception results by each individual vehicle. Nevertheless, the V2X communication channel remains a significant bottleneck to the performance and usefulness of collaborative perception due to limited bandwidth and ad hoc communication scheduling. In this paper, we explore challenges and design choices for V2X-based collaborative perception, and propose an architecture that lever-ages the power of edge computing such as road-side units for central communication scheduling. Using NS-3 simulations, we show the performance gap between distributed and centralized C-V2X scheduling in terms of achievable throughput and communication efficiency, and explore scenarios where edge assistance is beneficial or even necessary for collaborative perception.