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