Emergency-braking Distance Prediction using Deep Learning

Ruisi Zhang; Ashkan Pourkand

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arXiv · 2112.01708

Emergency-braking Distance Prediction using Deep Learning

Ruisi Zhang·Ashkan Pourkand

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Abstract

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.

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BibTeX RIS

Ruisi Zhang, Ashkan Pourkand. 2021-12-03. Emergency-braking Distance Prediction using Deep Learning. https://arxiv.org/abs/2112.01708

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