Project results are expected to contribute to all of the following outcomes:

• Availability of validated prototypes of next-generation vehicle and infrastructure-based environment perception technologies for robust, reliable and trustworthy CCAM operations to anticipate and avoid foreseeable risks and unexpected safety-critical situations in complex real-world conditions (e.g., at pedestrian crossings, in construction sites, during interactions with emergency vehicles, etc.);
• Understanding the degree (and limits) to which automated CCAM perception systems can anticipate, process, and respond to on-site ‘early-warnings’ (e.g., street design, sounds, smells and other signals from the environment, weather conditions, intentions of pedestrians, cyclists, and other active mobility users, etc.);
• Improvement of the energy-efficiency of the sense-think-act systems of CCAM considering the vehicle, the infrastructure, the cloud at-the-edge, while at the same time increasing the performance to guarantee security and error-free reliability; these developments will contribute to the reduction of the potential climate and environmental footprints of CCAM systems;
• Standardisation and adoption of modular, reusable, and upgradable software and hardware platforms, investigating scalable deployment concepts that lead to cost reduction and improved affordability while adopting a circular, eco-design approach (including efficient materials use, reduced waste, and the repair and reuse of components where feasible).

Scope:

The initial deployment of Level 4 automated vehicle services in urban and other complex settings has encountered significant challenges in environmental perception and decision-making, leading to occasional remote assistance calls, blockages and accidents that have impacted public trust. At the same time, the increasing computing power demand is in conflict with a limited usage of energy and resources to meet sustainability requirements. Thus, emerging large-scale demonstrations of automated vehicles should be accompanied by objective-oriented research aimed at addressing these challenges directly, while targeting improvements in performance, accuracy, reliability, and cyber-security.

To successfully overcome these challenges, proposed actions for this topic are expected to address all of the following aspects:

• Advancements in all steps of the sense-control-act process for both vehicle- and infrastructure-based smart sensor systems and networks, controllers, and actuators to ensure safety and trustworthiness of CCAM, as well as facilitating effective disruption management;
• Utilisation of digital enabling technologies including, for example: AI at-the-edge, machine learning, data spaces with reference scenarios and suitable software architectures^[1];
• Adoption of modular, reusable, and open software platforms supporting the environment perception for CCAM while ensuring transparency of operation, verification, and safety assessment to build trust, with respect to authorities, decision makers and the public via direct performance explainability;
• Energy efficiency, circularity, and eco-design of the environment perception systems by decreasing potential energy and resource consumption in both production and operation as well as facilitating reusability, reparability and upgradability while further enhancing the performance;
• Reduction of potential costs of environment perception systems through scalability, modularity and standardisation, making technologies financially viable for widespread implementation;
• Support remote assistance as a stepping-stone towards higher levels of autonomy and vehicle automation in wider Operational Design Domains (ODD).

Solutions are expected to integrate electronic hardware architectures and software stacks in a co-design approach. Hence, it is strongly encouraged that solutions use, as far as possible, building blocks and tools from projects of the Software-Defined Vehicle of the Future (SDVoF) initiative under the Chips Joint Undertaking, e.g., on the hardware abstraction layer and SDV middleware and API framework. Results from projects funded under HORIZON-CL5-2024-D6-01-04^[2] and complementarities with projects funded under Horizon Europe Cluster 4 “Digital Industry and Space” should also be considered, where appropriate.

As the activities should demonstrate feasibility and their full potential for real-world applications, proposals should foresee exchanges with other relevant EU or national projects for e.g., coordinated validation, transport systems integration and large-scale piloting. Collaboration should also be sought with projects funded under HORIZON-CL5-2024-D6-01-01^[3] and other directly relevant call topics.

In view of the relevance of environment perception and decision-making of automated vehicles for the responsiveness of the innovation to diverse societal interests and concerns, accessibility, inclusiveness as well as regulation, proposals should consider societal, ethical, socio-economical and/ or legal aspects as far as feasible in the requirements of the technical solutions to be developed. This could involve the engagement of institutional users as well as citizen-science approaches, e.g., in collaboration with projects CulturalRoad^[4] and Diversify – CCAM^[5].

To achieve the expected outcomes, international cooperation is highly relevant, considering the lessons learned in this area (for example, from robo-taxi and freight transport trials in the US and China). Activities should foster links between the European ecosystem and relevant stakeholders around the world, in particular with Japan and the United States but also with other relevant strategic partners in third countries, while taking into account the legal, cultural, historical, and social aspects in Europe as well as other specificities of the European road network and cities (including: traffic rules, user behaviour, diverse user groups considering gender, age, disability, socio-economic status, streets morphology, and the structure and condition of roads in rural areas).

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.

Projects resulting from this topic are expected to apply the European Common Evaluation Methodology (EU-CEM) for CCAM^[6].

[1] In line with the European Artificial Intelligence strategy and requirements for trustworthy, explainable, and safe AI.

[2] AI for advanced and collective perception and decision making for CCAM applications

[3] Centralised, reliable, cyber-secure & upgradable in-vehicle electronic control architectures for CCAM connected to the cloud-edge continuum.

[4] Cocreate, Embrace – grant agreement ID: 101147397.

[5] Diversify CCAM by integrating European cultural and regional variations in the design and implementation of citizen-friendly systems to foster mobility equity - grant agreement id: 101147484.

[6] See the evaluation methodology here.