A three-stage framework pre-trains multi-agent RL agents on real safety-critical data, refines them via online learning in CARLA, and generates the VPSCI dataset of over 198,000 realistic vehicle-pedestrian interaction episodes.
In: Proceedings of the 2017 Fifteenth IAPR International Conference on machine vision applications (MVA), pp
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Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions
A three-stage framework pre-trains multi-agent RL agents on real safety-critical data, refines them via online learning in CARLA, and generates the VPSCI dataset of over 198,000 realistic vehicle-pedestrian interaction episodes.