Automated Tactical Maneuver Discovery, Reasoning and Trajectory Planning for Autonomous Driving

Abstract

In a hierarchical motion planning system for urban autonomous driving, it is a common practice to separate tactical reasoning from the lower-level trajectory planning. This separation makes it difficult to achieve robust maneuver-based tactical reasoning, which is intrinsically linked to trajectory planning. We therefore propose a planning method that automatically discovers tactical maneuver patterns, and fuses pattern reasoning and sampling-based trajectory planning. The results demonstrate enhanced planning feasibility, coherency and scalability.