Toward Data-Centric Software Architecture for Automotive Systems - Embedded Data Stream Processing Approach

In the automotive field, intelligent control systems and information services using vehicle data are rapidly expanding. However, there is no software architecture to efficiently handle sensor data in vehicles and their surroundings. In order to address these problems and develop automotive software with higher productivity and trustworthiness, we have researched and developed data-centric software architecture for a data-stream management system for an automotive embedded system (eDSMS) and a stream local dynamic map (LDM) using eDSMS. An LDM is a collection of data that is intended to be used in cooperative intelligent transportation systems. In this paper, we present features of eDSMS and LDM using eDSMS, and demonstrate collision warning application software with eDSMS and a driver assistance system with a stream-based LDM.