自動運転のためのルールベース行動プランナ
A Rule-Based Behaviour Planner for Autonomous Driving
専門家の運転判断から学習したルールエンジンを用い、二層構造のルールベース理論で自動運転車の行動計画を実現する手法を提案し、市街地での実車テストで有効性を示した。
著者: Bouchard Frederic, Sedwards Sean, Czarnecki Krzysztof
分類: cs.AI, cs.RO
原文アブストラクト
Autonomous vehicles require highly sophisticated decision-making to determine their motion. This paper describes how such functionality can be achieved with a practical rule engine learned from expert driving decisions. We propose an algorithm to create and maintain a rule-based behaviour planner, using a two-layer rule-based theory. The first layer determines a set of feasible parametrized behaviours, given the perceived state of the environment. From these, a resolution function chooses the most conservative high-level maneuver. The second layer then reconciles the parameters into a single behaviour. To demonstrate the practicality of our approach, we report results of its implementation in a level-3 autonomous vehicle and its field test in an urban environment.