Tunable and Stable Real-Time Trajectory Planning for Urban Autonomous Driving

This paper investigates real-time on-road motion planning algorithms for autonomous passenger vehicles (APV) in urban environments, and propose a computationally efficient planning formulation. Two key properties, tunability and stability, are emphasized when designing the proposed planner. The main contributions of this paper are: · A computationally efficient decoupled space-time trajectory planning structure. · The formulation of optimization-free elastic-band-based path planning and speed-constraint-based temporal planning routines with pre-determined runtime. · Identification of continuity problems with previous cost-based planners that cause tunability and stability issues.