Contingency planning over probabilistic hybrid obstacle predictions for autonomous road vehicles

This paper presents a novel optimization based path planner that can simultaneously plan multiple contingency paths to account for the uncertain actions of dynamic obstacles. This planner addresses the particular problem of collision avoidance for autonomous road vehicles which are required to safely interact with other vehicles with unknown intentions. The presented path planner utilizes an efficient spline based trajectory representation and fast but accurate collision probability approximations to enable the simultaneous optimization of multiple contingency paths.