DRIVING EVENT CLASSIFICATION USING MULTIPLE SENSORS

摘要

The present invention suggests an interface to visualize driving information by classifying driving events using a three-axis acceleration sensor and a camera inside a black box and by fusing the same with GPS information. In order to classify driving events, a multi-dimensional feature vector is formed by using three-axis acceleration information and image stabilization. The driving events are classified into driving straight, turning left, turning right, stopping, and a speed bump through a Bayesian classifier, and a lane change event that cannot be measured by a GPS is assumed. A visualization map about the entire driving information is generated by fusing the classified driving events and the GPS information acquired from the black box together, and through the visualization map, a user-friendly driving information visualization interface can be provided.