{"title":"Centralization potential of automotive E/E architectures","authors":"Lucas Mauser, Stefan Wagner","doi":"arxiv-2409.10690","DOIUrl":null,"url":null,"abstract":"Current automotive E/E architectures are subject to significant\ntransformations: Computing-power-intensive advanced driver-assistance systems,\nbandwidth-hungry infotainment systems, the connection of the vehicle with the\ninternet and the consequential need for cyber-security drives the\ncentralization of E/E architectures. A centralized architecture is often seen\nas a key enabler to master those challenges. Available research focuses mostly\non the different types of E/E architectures and contrasts their advantages and\ndisadvantages. There is a research gap on guidelines for system designers and\nfunction developers to analyze the potential of their systems for\ncentralization. The present paper aims to quantify centralization potential\nreviewing relevant literature and conducting qualitative interviews with\nindustry practitioners. In literature, we identified seven key automotive\nsystem properties reaching limitations in current automotive architectures:\nbusload, functional safety, computing power, feature dependencies, development\nand maintenance costs, error rate, modularity and flexibility. These properties\nserve as quantitative evaluation criteria to estimate whether centralization\nwould enhance overall system performance. In the interviews, we have validated\ncentralization and its fundament - the conceptual systems engineering - as\ncapabilities to mitigate these limitations. By focusing on practical insights\nand lessons learned, this research provides system designers with actionable\nguidance to optimize their systems, addressing the outlined challenges while\navoiding monolithic architecture. This paper bridges the gap between\ntheoretical research and practical application, offering valuable takeaways for\npractitioners.","PeriodicalId":501278,"journal":{"name":"arXiv - CS - Software Engineering","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10690","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Current automotive E/E architectures are subject to significant
transformations: Computing-power-intensive advanced driver-assistance systems,
bandwidth-hungry infotainment systems, the connection of the vehicle with the
internet and the consequential need for cyber-security drives the
centralization of E/E architectures. A centralized architecture is often seen
as a key enabler to master those challenges. Available research focuses mostly
on the different types of E/E architectures and contrasts their advantages and
disadvantages. There is a research gap on guidelines for system designers and
function developers to analyze the potential of their systems for
centralization. The present paper aims to quantify centralization potential
reviewing relevant literature and conducting qualitative interviews with
industry practitioners. In literature, we identified seven key automotive
system properties reaching limitations in current automotive architectures:
busload, functional safety, computing power, feature dependencies, development
and maintenance costs, error rate, modularity and flexibility. These properties
serve as quantitative evaluation criteria to estimate whether centralization
would enhance overall system performance. In the interviews, we have validated
centralization and its fundament - the conceptual systems engineering - as
capabilities to mitigate these limitations. By focusing on practical insights
and lessons learned, this research provides system designers with actionable
guidance to optimize their systems, addressing the outlined challenges while
avoiding monolithic architecture. This paper bridges the gap between
theoretical research and practical application, offering valuable takeaways for
practitioners.