The proposed actions are expected to address all of the following aspects:

• Developing a validation methodology for scenario-based safety assurance of AI-based CCAM functions. Trustworthiness of the AI-algorithms depends on how well the system responds to scenarios in its Operational
• Design Domain (ODD) – specificity and how it responds in case it ends-up outside its ODD – robustness. Consequently, methods need to be developed on the use of scenarios to describe the ODD of AI-based systems.
• Connectivity. Developing validation procedures for CCAM systems that rely on V2X for safety-critical functions i.e., the inclusion of the connectivity context. Ensuring aspects of reliability, trustworthiness and cyber-security with respect to V2X is essential. The approach to V2X connectivity is technology neutral.
• Continuous Safety Assurance approach. Developing 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. Performance metrics for the reliability of the monitored data, including cyber-security aspects, and indicators for the safety state should be proposed. Also needed is the development of requirements for the monitoring system for use in future standardisation, regarding the exchange of data and safety performance indicators with service organisations and authorities.
• Validating the virtual approach. Developing tools that ensure the relevant degree of detail and the appropriate representation of other road users’ behaviour (incl. Vulnerable Road Users such as pedestrians and/or bicyclists) in virtual scenario-based testing. This includes methods to deal with perception, localisation, and world modelling errors in the validation procedures.
• Human Machine Interaction. Developing a safety assurance methodology that incorporates the assessment of Human Machine Interaction (both driver-vehicle and vehicle-road user) concepts for higher levels of automation (conformity checks as well as test set-ups with suitable metrics) ensuring safe communication between driver and vehicle and between vehicle and other road users, making Human Machine Interaction inclusive (i.e. in terms of age, mental and physical ability, cultural aspects, etc.).

Upcoming CCAM projects, in particular in the area of large-scale demonstrations, validation, digital infrastructure and key enabling technologies should be taken into account to ensure compatibility.

Links should be established with the Mobility Data Space initiatives from Digital Europe, federated data infrastructure projects (Gaia-X, International Data Spaces, Big Data Value – BDV).

International cooperation is encouraged, in particular with Japan and the United States but also with other relevant strategic partners in third countries.

This topic implements the co-programmed European Partnership on ‘Connected, Cooperative and Automated Mobility’ (CCAM). As such, projects resulting from this topic will be expected to report on results to the European Partnership ‘Connected, Cooperative and Automated Mobility’ (CCAM) in support of the monitoring of its KPIs.