J. Villagrá, Antonio Artuñedo, Vinicius Trentin, Jorge Godoy
{"title":"Interaction-aware risk assessment: focus on the lateral intention","authors":"J. Villagrá, Antonio Artuñedo, Vinicius Trentin, Jorge Godoy","doi":"10.1109/CAVS51000.2020.9334597","DOIUrl":null,"url":null,"abstract":"To make the massive deployment of automated vehicles possible in complex urban environments, it is essential to provide them with the ability of making safe and useful decisions. To that end, it is necessary to improve their capability to infer the intentions of the surrounding vehicles and their associated collision risk for the ego-vehicle in complex driving scenes. This work shows the implementation and validation in simulation of a probabilistic approach to estimate the risk of driving under uncertain conditions, combining (i) intention estimations and (ii) the expected behaviour of vehicles according to the topology and the subsequent traffic rules of the considered driving scenario. Promising results in terms of success rate and prediction horizon have been obtained testing the proposed approach in driving situations where lateral intention estimation is relevant, namely in multi-lane roundabouts and highways.","PeriodicalId":409507,"journal":{"name":"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAVS51000.2020.9334597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
To make the massive deployment of automated vehicles possible in complex urban environments, it is essential to provide them with the ability of making safe and useful decisions. To that end, it is necessary to improve their capability to infer the intentions of the surrounding vehicles and their associated collision risk for the ego-vehicle in complex driving scenes. This work shows the implementation and validation in simulation of a probabilistic approach to estimate the risk of driving under uncertain conditions, combining (i) intention estimations and (ii) the expected behaviour of vehicles according to the topology and the subsequent traffic rules of the considered driving scenario. Promising results in terms of success rate and prediction horizon have been obtained testing the proposed approach in driving situations where lateral intention estimation is relevant, namely in multi-lane roundabouts and highways.