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New challenges and complexities are continuously increasing in advanced driver assistance systems (ADAS) development (e.g. active safety, driver assistant and autonomous vehicle systems). Therefore, the health management of ADAS’ components needs special improvements. Since software contribution in ADAS’ development is increasing significantly, remote diagnosis and maintenance for ADAS become more important. Furthermore, it is highly recommended to predict the remaining useful life (RUL) for the prognosis of ADAS’ safety critical components; e.g. (Ultrasonic, Cameras, Radar, LIDAR). This paper presents a remote diagnosis, maintenance and prognosis (RDMP) framework for ADAS, which can be used during development phase and mainly after production. An overview of RDMP framework’s elements is explained to demonstrate how/when this framework is connected to database servers and remote analysis servers.

The evaluation of Advanced Driver Assistance Systems (ADAS including driver assistance and active safety) has increasing interest from authorities, industry and academia. AsPeCSS active safety project concludes that good results in a laboratory test for active safety system design does not necessarily equate to an effective system in real traffic conditions. Moreover, many ADAS assessment projects and standards require physical testing on test tracks (dummy vehicles, pedestrian mannequins…), which are expensive and limit testing capabilities. This research presents a conceptual framework for on-board evaluation (OBE) of ADAS, which can be used as a cost effective evaluation in real-life traffic conditions. OBE shall monitor, record, analyze and report both internal behavior and external environment (external objects list and video stream) of ADAS under evaluation (ADASUE).