Luodai Yang, Qian Jia, Ruijun Wang, Jie Cao, Weisong Shi
{"title":"HydraView: A Synchronized 360◦-View of Multiple Sensors for Autonomous Vehicles","authors":"Luodai Yang, Qian Jia, Ruijun Wang, Jie Cao, Weisong Shi","doi":"10.1109/MetroCAD48866.2020.00017","DOIUrl":null,"url":null,"abstract":"Today’s autonomous vehicles will deploy multiple sensors to achieve safe and reliable navigation and precise perception of the environment. Although multiple sensors can be advantageous in terms of providing a robust and complete description of the surrounding area, the synchronization of multi-sensors in real-time processing is extremely important. When data is synchronized, primary functional systems such as localization, perception, planning, and control, will all benefit. In this paper, we proposed a synchronized data illustration and collection method to assist the data processing applications for autonomous driving. Our proposed solution among different sensors can be directly deployed on autonomous vehicles for data integration and environment analysis to support the driving model construction. The experimental results validate that our proposed method can present a 360◦ synchronized view while providing the capability of real-time scanning with up to 80% reduced latency.","PeriodicalId":117440,"journal":{"name":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MetroCAD48866.2020.00017","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
Today’s autonomous vehicles will deploy multiple sensors to achieve safe and reliable navigation and precise perception of the environment. Although multiple sensors can be advantageous in terms of providing a robust and complete description of the surrounding area, the synchronization of multi-sensors in real-time processing is extremely important. When data is synchronized, primary functional systems such as localization, perception, planning, and control, will all benefit. In this paper, we proposed a synchronized data illustration and collection method to assist the data processing applications for autonomous driving. Our proposed solution among different sensors can be directly deployed on autonomous vehicles for data integration and environment analysis to support the driving model construction. The experimental results validate that our proposed method can present a 360◦ synchronized view while providing the capability of real-time scanning with up to 80% reduced latency.