Managed Automated Driving (MAD): Real-World Demonstration of Infrastructure Controlled Vehicle Automation

Kurzfassung

Recent advances in Connected and Automated Vehicle (CAV) technology have intensified interest in Cooperative Intelligent Transport Systems (C-ITS), in particular, the cooperation between CAVs and smart road infrastructure as a means to manage the complexity of urban traffic. However, most prior work has either been limited to low cooperation levels, e.g., simple status sharing, or has only been tested in simulation. In this paper, we present real-world test results of Managed Automated Driving (MAD). MAD integrates collective perception from infrastructure- and vehicle-mounted sensors with infrastructure-based multi-vehicle trajectory planning to support and/or control automated vehicles in mixed traffic. To the best of our knowledge, this is the first real-world realization of closed-loop infrastructure-based trajectory prescription on public urban roads. Our experiments indicate that, despite perception noise, heterogeneous human-driven traffic, and non-negligible variability in network performance, infrastructure-based prescriptive planning maintains comfortable motion profiles while meeting real-time execution bounds. The results demonstrate the feasibility of infrastructure-supported automated driving on public roads and provide an architectural blueprint for robust C-ITS deployments in complex urban environments.