Behavior and Path Planning Algorithm of Autonomous Vehicle A1 in Structured Environments

This paper presents a path-planning strategy for autonomous vehicles which aims to provide safe and feasible manoeuvres in various driving environments. Our strategy uses a hierarchical architecture which consists of three components: a behaviour planner, a map and path selector and a local-path planner. The behaviour planner performs the rule-based decision process which determines the overall vehicle manoeuvres. The map and path selector preprocesses perception data and chooses a local-path-planning algorithm using the results of the behaviour planner. From this selection, the local-path planner generates a driveable and collision-free path. For reliable path generation under various driving conditions, the proposed local path planner employs two algorithms: a road-model-based path planning algorithm and a graph-structure-based path-planning algorithm. The former is used for structured road driving, such as lane keeping or changing, and the latter is used for unstructured road driving. The proposed hierarchical path-planning algorithm was implemented in the autonomous vehicle called A1, which was applied with an in-vehicle-network-based distributed system architecture. A1 won the 2012 Autonomous Vehicle Competition organized by the Hyundai Motor Group in Korea.This work was supported by an NRF grant funded by the Korea government (MEST) (No. 2011-0017495), IndustrialStrategy Technology Development Program of MKE (No.10039673 and No. 10042633), Energy Resource R&Dprogram (2006ETR11P091C) under the MKE, Science andTechnology through the BK21 Program (201000000000173), and MKE and KIAT through the Workforce Development Program in Strategic Technology