周囲車両の予測不能性は運転行動に影響を与えるか
Does Unpredictability Influence Driving Behavior?
高速道路での車線変更を対象に、周囲車両の予測不能性を特徴量として組み込んだ逆強化学習で報酬関数を学習し、人間の運転データへの適合度が向上することを示した。
著者: Sepehr Samavi, Florian Shkurti, Angela P. Schoellig
分類: cs.RO
原文アブストラクト
In this paper we investigate the effect of the unpredictability of surrounding cars on an ego-car performing a driving maneuver. We use Maximum Entropy Inverse Reinforcement Learning to model reward functions for an ego-car conducting a lane change in a highway setting. We define a new feature based on the unpredictability of surrounding cars and use it in the reward function. We learn two reward functions from human data: a baseline and one that incorporates our defined unpredictability feature, then compare their performance with a quantitative and qualitative evaluation. Our evaluation demonstrates that incorporating the unpredictability feature leads to a better fit of human-generated test data. These results encourage further investigation of the effect of unpredictability on driving behavior.
