摘要
The emergence of software-defined vehicles(SDVs),combined with autonomous driving technologies,has en-abled a new era of vehicle computing(VC),where vehicles serve as a mobile computing platform.However,the interdisci-plinary complexities of automotive systems and diverse technological requirements make developing applications for au-tonomous vehicles challenging.To simplify the development of applications running on SDVs,we propose a comprehen-sive suite of vehicle programming interfaces(VPIs).In this study,we rigorously explore the nuanced requirements for ap-plication development within the realm of VC,centering our analysis on the architectural intricacies of the Open Vehicu-lar Data Analytics Platform(OpenVDAP).We then detail our creation of a comprehensive suite of standardized VPIs,spanning five critical categories:Hardware,Data,Computation,Service,and Management,to address these evolving pro-gramming requirements.To validate the design of VPIs,we conduct experiments using the indoor autonomous vehicle,Ze-bra,and develop the OpenVDAP prototype system.By comparing it with the industry-influential AUTOSAR interface,our VPIs demonstrate significant enhancements in programming efficiency,marking an important advancement in the field of SDV application development.We also show a case study and evaluate its performance.Our work highlights that VPIs significantly enhance the efficiency of developing applications on VC.They meet both current and future technologi-cal demands and propel the software-defined automotive industry toward a more interconnected and intelligent future.
作者
吴宝福
仲任
王昱心
万健
张纪林
施巍松
Bao-Fu Wu;Ren Zhong;Yuxin Wang;Jian Wan;Ji-Lin Zhang;Weisong Shi(School of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou 310018,China;Department of Computer Science,Wayne State University,Detroit,MI 48202,U.S.A;Department of Computer and Information Sciences,University of Delaware,Newark,DE 19716,U.S.A)
基金
Bao-Fu Wu,Jian Wan,and Ji-Lin Zhang were supported by the National Natural Science Foundation of China under Grant No.62072146
the Key Research and Development Program of Zhejiang Province of China under Grant Nos.2023C03194,2021C03187,and 2023C01044
the National Natural Science Foundation of China(Youth Fund)under Grant No.62302133.