  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.
