Abstract:

Service-Oriented Architecture （SOA） stands as the core design concept for software-defined intelligent vehicles. This paper presents an analysis and synthesis of the software and hardware layers of SOA in intelligent vehicles， along with a categorization of key environmental factors influencing SOA scheduling. Building upon this analysis， this paper proposes an extended-domain SOA architecture tailored for vehicles， establishes a model for SOA service layers and service response parameters， and devise a service scheduling mechanism for this architecture. The service scheduling mechanism centers around the concept of service confidence， and takes into account multiple factors such as service capability， estimated runtime， resource consumption， and performance stability of sub-services， to make optimal sub-service selections under the current environmental constraints. Simulation tests are performed using a simplified double-layer SOA model in scenarios including highways， congested roadways， and low-light tunnels. Results indicate that compared to scenarios without service scheduling， the proposed SOA architecture with the scheduling mechanism significantly reduces computing load and energy consumption by approximately 36% and decreases the predicted service time by around 30%， all while maintaining comparable service capacity.

Key words: SOA, intelligent vehicles, service scheduling, service confidence, quality of service