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This paper presents a planning system for autonomous driving among manypedestrians. A key ingredient of our approach is PORCA, a pedestrian motionprediction model that accounts for both a pedestrian's global navigationintention and local interactions with the vehicle and other pedestrians.Unfortunately, the autonomous vehicle does not know the pedestrian's intentiona priori and requires a planning algorithm that hedges against the uncertaintyin pedestrian intentions. Our planning system combines a POMDP algorithm withthe pedestrian motion model and runs in near real time. Experiments show thatit enables a robot vehicle to drive safely, efficiently, and smoothly among acrowd with a density of nearly one person per square meter.

PORCA: Modeling and Planning for Autonomous Driving among Many Pedestrians