Planning Long Dynamically-Feasible Maneuvers For Autonomous Vehicles
Maxim Likhachev* and Dave Ferguson**
Abstract
In this paper, we present an algorithm for generating complex
dynamically-feasible maneuvers for autonomous vehicles traveling at
high speeds over large distances. Our approach is based on
performing anytime incremental search on a multi-resolution,
dynamically-feasible lattice state space. The resulting planner
provides real-time performance and guarantees on and control of the
suboptimality of its solution. We provide theoretical properties
and experimental results from an implementation on an autonomous
passenger vehicle that competed and won the first place in the
Urban Challenge competition.