Low-cost realtime horizontal curve detection using inertial sensors of a smartphone

Fatal accidents occur frequently on low-volume rural roads, and the accident rates are up to 4 times higher at curves. It is thus of paramount importance to perform road inventory of rural roads to develop safety plans. However, most states in U.S. face a challenge to maintain a database for low-volume rural roads due to limited funds for road inventory. In this paper, we propose to significantly reduce the cost for road inventory specifically focusing on horizontal curve detection by developing a mobile road inventory system based on off-the-shelf smartphones. The proposed system is capable of accurately detecting various kinds of horizontal curves by synthesizing heterogeneous smartphone sensor data to generate curve models by exploiting a machine learning technique. We implemented the system on iOS-based smartphones and tested with more than 400-miles of field data. We demonstrate that the proposed system achieves a median of 93.8% curve identification accuracy with a median of 5% false positive rates