都市交差点を自律走行するための信念状態プランニング
Belief State Planning for Autonomously Navigating Urban Intersections
信号のない都市交差点の走行をPOMDPとして定式化し、モンテカルロサンプリングで計画する手法を提案。シミュレーションで安全性と効率の指標において閾値ベースのヒューリスティックを上回ることを示した。
著者: Maxime Bouton, Akansel Cosgun, Mykel J. Kochenderfer
分類: cs.RO
原文アブストラクト
Urban intersections represent a complex environment for autonomous vehicles with many sources of uncertainty. The vehicle must plan in a stochastic environment with potentially rapid changes in driver behavior. Providing an efficient strategy to navigate through urban intersections is a difficult task. This paper frames the problem of navigating unsignalized intersections as a partially observable Markov decision process (POMDP) and solves it using a Monte Carlo sampling method. Empirical results in simulation show that the resulting policy outperforms a threshold-based heuristic strategy on several relevant metrics that measure both safety and efficiency.
