{"title":"A Method for Designing and Analyzing Automotive Software Architecture: A Case Study for an Autonomous Electric Vehicle","authors":"Junghwan Lee, Longda Wang","doi":"10.1109/ICCEAI52939.2021.00004","DOIUrl":null,"url":null,"abstract":"Software complexity is increased in automotive systems because many software functions are required for autonomous driving, electrified vehicles, and connected cars. In addition, autonomous driving requires centralized software that generally decreases evolvability with many connections. Thus, the automotive industry adopted the microservice architecture within the service-oriented architecture (SOA), which was already being used in distributed computing environments in the information and communication technology (ICT) industry. However, the software characteristics of an automotive system are different from those of an ICT system. Automotive software generally fulfills safety and real-time requirements that are not required in ICT software. Another challenge is integrating electric control units (ECUs) because software platforms supporting SOA require relatively high computational power and network bandwidth, which increases ECU cost. Thus, the deployment of software functions must be considered before integrating ECUs to find an optimal design solution for evolvability, dependability, real-time performance, cost, etc. However, many OEMs integrate ECUs based on deploying vehicular features without software architecture. It causes optimality problems during integrating ECUs. We propose component-based sensor-process-actuator architectural style for high-level architecture to handle quality attributes. Software architecture for an autonomous electrified vehicle will be presented with the proposed architectural style. The architecture is used to deploy software components and integrated ECUs with empirical quantitative analysis. Four design patterns for dependability with the architectural style will also be introduced.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEAI52939.2021.00004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Software complexity is increased in automotive systems because many software functions are required for autonomous driving, electrified vehicles, and connected cars. In addition, autonomous driving requires centralized software that generally decreases evolvability with many connections. Thus, the automotive industry adopted the microservice architecture within the service-oriented architecture (SOA), which was already being used in distributed computing environments in the information and communication technology (ICT) industry. However, the software characteristics of an automotive system are different from those of an ICT system. Automotive software generally fulfills safety and real-time requirements that are not required in ICT software. Another challenge is integrating electric control units (ECUs) because software platforms supporting SOA require relatively high computational power and network bandwidth, which increases ECU cost. Thus, the deployment of software functions must be considered before integrating ECUs to find an optimal design solution for evolvability, dependability, real-time performance, cost, etc. However, many OEMs integrate ECUs based on deploying vehicular features without software architecture. It causes optimality problems during integrating ECUs. We propose component-based sensor-process-actuator architectural style for high-level architecture to handle quality attributes. Software architecture for an autonomous electrified vehicle will be presented with the proposed architectural style. The architecture is used to deploy software components and integrated ECUs with empirical quantitative analysis. Four design patterns for dependability with the architectural style will also be introduced.