Improving driving behavior by allowing drivers to browse their own recorded driving data

In this paper, we present our on-going efforts to develop a self-diagnosis system to improve safe-driving behavior by allowing drivers to review a record of their own driving activity. By employing stochastic driver-behavior modeling, the proposed system is able to detect various types of potentially hazardous situations, which conventional event data recorders are not able to capture, or which drivers themselves are not aware of such latent risky situations. Utilizing these automatically detected hazardous situations, our web-based system offers a user-friendly interface for drivers to navigate and review each hazardous situation in detail (e.g., driving scenes are displayed with corresponding driving signals). Furthermore, the system provides feedback on each risky driving behavior and suggests how the users can appropriately respond to such situations in a safe manner. The proposed system establishes a cooperative relationship between the driver, the vehicle, and the driving environment in order to develop the next-generation of safety systems and pave the way for an alternative form of driver education that could further reduce the number of fatal accidents. The system´s potential benefits are demonstrated through experimental evaluation, showing that safe-driving behavior improved significantly after using the proposed system.