“To ensure safety of CCAM, it is essential that vehicles are not only safe during the (first) type approval, but also during their complete lifetime in a fast-changing road transport system. Changes can result from the evolution of the CCAM system itself, for example, as a result of increasing connectivity using V2X communication, the use of AI-based systems, and (OTA: over-the-air) software updates. The traffic system, in which CCAM systems are being deployed, is changing at a rapid pace as well, with an increased market share of vehicles with higher levels of automation, new (personal) mobility devices and autonomous mobility robots (e.g., for package delivery).
-Develop validation methodology for scenario-based safety assurance of AI-based CCAM functions
-Develop validation procedures for CCAM systems that rely on V2X for safety-critical functions i.e., the inclusion of the connectivity context
-Develop an approach for a continuous safety validation methodology, to monitor the safety state of deployed CCAM systems in operation (real traffic) during its service life, following type approval
-Develop tools that ensure the relevant degree of detail and the appropriate representation of other road users’ behaviour in virtual scenario-based testing
-Develop a safety assurance methodology that incorporates the assessment of Human Machine Interaction concepts for higher levels of automation ensuring safe communication between driver and vehicle and between vehicle and other road users, making Human Machine Interaction inclusive
-Safe scaling up of the deployment of CCAM systems for all levels of automation, including systems that for part of the driving phases rely on human-machine interaction
-Assurance of vehicle safety despite system changes, e.g., due to software updates and data exchanges between vehicles and the infrastructure
-Facilitating the introduction of fast developing technological innovations in the CCAM system’s functionality, such as AI.”
