{"title":"CRAG - 用于 ADS 测试的基于组合测试的道路几何生成器","authors":"Paolo Arcaini , Ahmet Cetinkaya","doi":"10.1016/j.scico.2024.103171","DOIUrl":null,"url":null,"abstract":"<div><p>Simulation-based testing of autonomous driving systems (ADS) consists in finding scenarios in which the ADS misbehaves, e.g., it leads the car to drive off the road. The road geometry is an important feature of the scenario, as it has a direct impact on the ADS, e.g., its ability to keep the car inside the driving lane. In this paper, we present <span>CRAG</span>, a road generator for ADS testing. <span>CRAG</span> uses combinatorial testing to explore high level road configurations, and search for finding concrete road geometries in these configurations. <span>CRAG</span> has been designed in a way that it can be easily extended in terms of generator of combinatorial test suites, search algorithms, and test goals.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"238 ","pages":"Article 103171"},"PeriodicalIF":1.5000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CRAG – a combinatorial testing-based generator of road geometries for ADS testing\",\"authors\":\"Paolo Arcaini , Ahmet Cetinkaya\",\"doi\":\"10.1016/j.scico.2024.103171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Simulation-based testing of autonomous driving systems (ADS) consists in finding scenarios in which the ADS misbehaves, e.g., it leads the car to drive off the road. The road geometry is an important feature of the scenario, as it has a direct impact on the ADS, e.g., its ability to keep the car inside the driving lane. In this paper, we present <span>CRAG</span>, a road generator for ADS testing. <span>CRAG</span> uses combinatorial testing to explore high level road configurations, and search for finding concrete road geometries in these configurations. <span>CRAG</span> has been designed in a way that it can be easily extended in terms of generator of combinatorial test suites, search algorithms, and test goals.</p></div>\",\"PeriodicalId\":49561,\"journal\":{\"name\":\"Science of Computer Programming\",\"volume\":\"238 \",\"pages\":\"Article 103171\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of Computer Programming\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167642324000947\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Computer Programming","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167642324000947","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
CRAG – a combinatorial testing-based generator of road geometries for ADS testing
Simulation-based testing of autonomous driving systems (ADS) consists in finding scenarios in which the ADS misbehaves, e.g., it leads the car to drive off the road. The road geometry is an important feature of the scenario, as it has a direct impact on the ADS, e.g., its ability to keep the car inside the driving lane. In this paper, we present CRAG, a road generator for ADS testing. CRAG uses combinatorial testing to explore high level road configurations, and search for finding concrete road geometries in these configurations. CRAG has been designed in a way that it can be easily extended in terms of generator of combinatorial test suites, search algorithms, and test goals.
期刊介绍：
Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design.
The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice.
The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including
• Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software;
• Design, implementation and evaluation of programming languages;
• Programming environments, development tools, visualisation and animation;
• Management of the development process;
• Human factors in software, software for social interaction, software for social computing;
• Cyber physical systems, and software for the interaction between the physical and the machine;
• Software aspects of infrastructure services, system administration, and network management.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
