深層学習による緊急制動距離の予測
Emergency-braking Distance Prediction using Deep Learning
制動前0.25秒の3次元加速度データから緊急制動距離を予測する深層学習モデルを提案し、2種類の路面で誤差3フィート以内の精度を達成した。
著者: Ruisi Zhang, Ashkan Pourkand
分類: cs.RO
原文アブストラクト
Predicting emergency-braking distance is important for the collision avoidance related features, which are the most essential and popular safety features for vehicles. In this study, we first gathered a large data set including a three-dimensional acceleration data and the corresponding emergency-braking distance. Using this data set, we propose a deep-learning model to predict emergency-braking distance, which only requires 0.25 seconds three-dimensional vehicle acceleration data before the break as input. We consider two road surfaces, our deep learning approach is robust to both road surfaces and have accuracy within 3 feet.