{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T16:51:13Z","timestamp":1771519873671,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683164","type":"print"},{"value":"9781643683171","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,14]]},"abstract":"<jats:p>This study describes the MATLAB\/Simulink benchmark of an open-source self-driving system based on Robot Operating System 2 (ROS 2). In recent years, self-driving systems have been the subject of research and development worldwide. Due to the lack of open source models for self-driving systems, model-based development, a common approach to the development of in-vehicle systems, is not yet fully used in the development of self-driving systems. The provided MATLAB\/Simulink benchmarks support the design of ROS 2-based self-driving systems using MATLAB\/Simulink. Improvements to the benchmark\u2019s design issues are discussed. Furthermore, Simulink\u2019s profiling function makes it easier to make redesign decisions. The model can run using only sensor data, and the runtime evaluation revealed that the benchmark models could reduce the runtime, although the number of cores used was different.<\/jats:p>","DOI":"10.3233\/faia220234","type":"book-chapter","created":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T09:07:19Z","timestamp":1663319239000},"source":"Crossref","is-referenced-by-count":3,"title":["Self-Driving Software Benchmark for Model-Based Development"],"prefix":"10.3233","author":[{"given":"Takumi","family":"Onozawa","sequence":"first","affiliation":[{"name":"Graduate School of Science and Engineering, Saitama University"}]},{"given":"Takuya","family":"Azumi","sequence":"additional","affiliation":[{"name":"Graduate School of Science and Engineering, Saitama University"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220234","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T09:07:44Z","timestamp":1663319264000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220234"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,14]]},"ISBN":["9781643683164","9781643683171"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220234","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,14]]}}}