Urban autonomous driving systems face significant safety challenges in non-line-of-sight (NLOS) situations, particularly when pedestrians suddenly emerge from behind occlusions. Cooperative perception, enabled by ETSI-standard Cooperative Perception Messages (CPMs), addresses this limitation by extending situational awareness beyond onboard sensors. This paper presents a virtual testing study of an autonomous driving system (ADS) equipped with CPM-based cooperative perception for a darting-out pedestrian scenario. A simulation environment integrating OMNeT++, Veins, and SUMO is developed, featuring a camera-based perception model with occlusion handling and an ADS control module that fuses CPM data for speed adaptation and emergency braking. This virtual-first approach enables rapid scenario exploration and scalable evaluation of ADS and V2X performance. Key Performance Indicators (KPIs) assess perception coverage, CPM delivery ratio, communication latency, mobility adaptation, and safety outcomes. Results show that CPM-augmented perception identifies the pedestrian up to two seconds earlier than onboard sensing alone. Connectivity evaluation indicates high CPM delivery ratios with low latency in ideal conditions, supporting reliable cooperative perception. Time-to-Collision and braking profiles confirm smooth and safe ADS responses, while edge cases highlight operational limits where collisions remain unavoidable, providing valuable scenarios for subsequent high-fidelity testing. Overall, the study demonstrates that virtual-first testing is an effective and scalable method for developing and validating CPM-based cooperative perception in urban autonomous driving.
Ali et al. (Thu,) studied this question.
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