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arXiv · 1705.03955

VehSense: Slippery Road Detection Using Smartphones

Yunfei Hou·Abhishek Gupta·Tong Guan·Shaohan Hu·Lu Su·Chunming Qiao
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Abstract

This paper investigates a new application of vehicular sensing: detecting and reporting the slippery road conditions. We describe a system and associated algorithm to monitor vehicle skidding events using smartphones and OBD-II (On board Diagnostics) adaptors. This system, which we call the VehSense, gathers data from smartphone inertial sensors and vehicle wheel speed sensors, and processes the data to monitor slippery road conditions in real-time. Specifically, two speed readings are collected: 1) ground speed, which is estimated by vehicle acceleration and rotation, and 2) wheel speed, which is retrieved from the OBD-II interface. The mismatch between these two speeds is used to infer a skidding event. Without tapping into vehicle manufactures' proprietary data (e.g., antilock braking system), VehSense is compatible with most of the passenger vehicles, and thus can be easily deployed. We evaluate our system on snow-covered roads at Buffalo, and show that it can detect vehicle skidding effectively.

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Yunfei Hou, Abhishek Gupta, Tong Guan, Shaohan Hu, Lu Su, Chunming Qiao. 2017-05-10. VehSense: Slippery Road Detection Using Smartphones. https://arxiv.org/abs/1705.03955

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