Mehmet Onur Aybek, Rodolfo Jordão, John Lundbäck, Kurt-Lennart Lundbäck, Matthias Becker
{"title":"从计算的同步数据流模型到汽车部件模型","authors":"Mehmet Onur Aybek, Rodolfo Jordão, John Lundbäck, Kurt-Lennart Lundbäck, Matthias Becker","doi":"10.1109/ETFA45728.2021.9613621","DOIUrl":null,"url":null,"abstract":"The size and complexity of automotive software systems are steadily increasing. Software functions are subject to different requirements and belong to different functional domains of the car. Meanwhile, streaming applications have become increasingly relevant in emerging application areas such as Advanced Driving Assistance Systems. Among models for streaming applications, the Synchronous Data Flow model is well-known for its analysable properties. This work presents transformation rules that allow transforming applications described by the Synchronous Data Flow model to an automotive component model. The proposed transformation rules are implemented in form of a software plugin for an automotive tool suite that allows for timing analysis, code synthesis and deployment to a Real-Time Operating System. To demonstrate the applicability of the proposed approach, a case study of a Kalman filter that is part of a simplified cruise control application is presented. An abstract Synchronous Data Flow model of the filter is transformed into a component that is deployed on an Electronic Control Unit with hard timing guarantees.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"From the Synchronous Data Flow Model of Computation to an Automotive Component Model\",\"authors\":\"Mehmet Onur Aybek, Rodolfo Jordão, John Lundbäck, Kurt-Lennart Lundbäck, Matthias Becker\",\"doi\":\"10.1109/ETFA45728.2021.9613621\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The size and complexity of automotive software systems are steadily increasing. Software functions are subject to different requirements and belong to different functional domains of the car. Meanwhile, streaming applications have become increasingly relevant in emerging application areas such as Advanced Driving Assistance Systems. Among models for streaming applications, the Synchronous Data Flow model is well-known for its analysable properties. This work presents transformation rules that allow transforming applications described by the Synchronous Data Flow model to an automotive component model. The proposed transformation rules are implemented in form of a software plugin for an automotive tool suite that allows for timing analysis, code synthesis and deployment to a Real-Time Operating System. To demonstrate the applicability of the proposed approach, a case study of a Kalman filter that is part of a simplified cruise control application is presented. An abstract Synchronous Data Flow model of the filter is transformed into a component that is deployed on an Electronic Control Unit with hard timing guarantees.\",\"PeriodicalId\":312498,\"journal\":{\"name\":\"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETFA45728.2021.9613621\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA45728.2021.9613621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
From the Synchronous Data Flow Model of Computation to an Automotive Component Model
The size and complexity of automotive software systems are steadily increasing. Software functions are subject to different requirements and belong to different functional domains of the car. Meanwhile, streaming applications have become increasingly relevant in emerging application areas such as Advanced Driving Assistance Systems. Among models for streaming applications, the Synchronous Data Flow model is well-known for its analysable properties. This work presents transformation rules that allow transforming applications described by the Synchronous Data Flow model to an automotive component model. The proposed transformation rules are implemented in form of a software plugin for an automotive tool suite that allows for timing analysis, code synthesis and deployment to a Real-Time Operating System. To demonstrate the applicability of the proposed approach, a case study of a Kalman filter that is part of a simplified cruise control application is presented. An abstract Synchronous Data Flow model of the filter is transformed into a component that is deployed on an Electronic Control Unit with hard timing guarantees.