Ezequiel Castellano, A. Cetinkaya, Cédric Ho Thanh, Stefan Klikovits, Xiaoyi Zhang, Paolo Arcaini
{"title":"Frenetic at the SBST 2021 Tool Competition","authors":"Ezequiel Castellano, A. Cetinkaya, Cédric Ho Thanh, Stefan Klikovits, Xiaoyi Zhang, Paolo Arcaini","doi":"10.1109/SBST52555.2021.00016","DOIUrl":null,"url":null,"abstract":"Frenetic is a genetic approach that leverages a curvature-based road representation. Given an autonomous driving agent, the goal of Frenetic is to generate roads where the agent fails to stay within its lane. In other words, Frenetic tries to minimize the “out of bound distance”, which is the distance between the car and either edge of the lane if the car is within the lane, and proceeds to negative values once the car drives off. This work resembles classic aspects of genetic algorithms such as mutations and crossover, but introduces some nuances aiming at improving diversity of the generated roads.","PeriodicalId":199085,"journal":{"name":"2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing (SBST)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing (SBST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBST52555.2021.00016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
Frenetic is a genetic approach that leverages a curvature-based road representation. Given an autonomous driving agent, the goal of Frenetic is to generate roads where the agent fails to stay within its lane. In other words, Frenetic tries to minimize the “out of bound distance”, which is the distance between the car and either edge of the lane if the car is within the lane, and proceeds to negative values once the car drives off. This work resembles classic aspects of genetic algorithms such as mutations and crossover, but introduces some nuances aiming at improving diversity of the generated roads.