Truls Nyberg, José Manuel Gaspar Sánchez, Christian Pek, Jana Tumova, Martin Törngren
{"title":"Evaluating Sequential Reasoning about Hidden Objects in Traffic","authors":"Truls Nyberg, José Manuel Gaspar Sánchez, Christian Pek, Jana Tumova, Martin Törngren","doi":"10.1109/iccps54341.2022.00044","DOIUrl":null,"url":null,"abstract":"Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccps54341.2022.00044","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
Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving.