{"title":"一种智能驾驶仿真平台:架构、实现与应用","authors":"Yongling Sun, Xiaosong Yang, Hai Xiao, H. Feng","doi":"10.1109/MetroCAD48866.2020.00019","DOIUrl":null,"url":null,"abstract":"with the fast-growing advancements in highly automated driving technologies, cost-effective evaluation and validation of functional modules and full-stack driving system have become great challenges for automakers prior to the release of new intelligent vehicle models. Simulation based on high-fidelity rendering and physics engine has been widely used as a powerful tool to develop self-driving systems. From an OEM perspective, a flexible, extensible, and scalable virtual platform is proposed to integrate individual functional modules, support typical scenario libraries, and evaluate single functional algorithm or an entire domain controller system for rapid algorithm iterations and high-efficiency system testing. The platform demonstrates that a stand-alone machine can support up to 32-channel simulations in parallel depending on system resources, a semi-automatic method is introduced to generate a couple of scenarios based on map data and standard road network format, and typical perception algorithms are visualized and evaluated. In addition, such evaluation system can be deployed to the cloud to support large-scale simulations and testing automation.","PeriodicalId":117440,"journal":{"name":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An intelligent driving simulation platform: architecture, implementation and application\",\"authors\":\"Yongling Sun, Xiaosong Yang, Hai Xiao, H. Feng\",\"doi\":\"10.1109/MetroCAD48866.2020.00019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"with the fast-growing advancements in highly automated driving technologies, cost-effective evaluation and validation of functional modules and full-stack driving system have become great challenges for automakers prior to the release of new intelligent vehicle models. Simulation based on high-fidelity rendering and physics engine has been widely used as a powerful tool to develop self-driving systems. From an OEM perspective, a flexible, extensible, and scalable virtual platform is proposed to integrate individual functional modules, support typical scenario libraries, and evaluate single functional algorithm or an entire domain controller system for rapid algorithm iterations and high-efficiency system testing. The platform demonstrates that a stand-alone machine can support up to 32-channel simulations in parallel depending on system resources, a semi-automatic method is introduced to generate a couple of scenarios based on map data and standard road network format, and typical perception algorithms are visualized and evaluated. In addition, such evaluation system can be deployed to the cloud to support large-scale simulations and testing automation.\",\"PeriodicalId\":117440,\"journal\":{\"name\":\"2020 International Conference on Connected and Autonomous Driving (MetroCAD)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Connected and Autonomous Driving (MetroCAD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MetroCAD48866.2020.00019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MetroCAD48866.2020.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An intelligent driving simulation platform: architecture, implementation and application
with the fast-growing advancements in highly automated driving technologies, cost-effective evaluation and validation of functional modules and full-stack driving system have become great challenges for automakers prior to the release of new intelligent vehicle models. Simulation based on high-fidelity rendering and physics engine has been widely used as a powerful tool to develop self-driving systems. From an OEM perspective, a flexible, extensible, and scalable virtual platform is proposed to integrate individual functional modules, support typical scenario libraries, and evaluate single functional algorithm or an entire domain controller system for rapid algorithm iterations and high-efficiency system testing. The platform demonstrates that a stand-alone machine can support up to 32-channel simulations in parallel depending on system resources, a semi-automatic method is introduced to generate a couple of scenarios based on map data and standard road network format, and typical perception algorithms are visualized and evaluated. In addition, such evaluation system can be deployed to the cloud to support large-scale simulations and testing automation.