Risky Driver Recognition Based on Vehicle Speed Time Series

Risky driving is a major cause of traffic accidents. In this paper, we propose a new method that recognizes risky driving behaviors purely based on vehicle speed time series. This method first retrieves the important distribution pattern of the sampled positive speed-change (value and duration) tuples for individual drivers within different speed ranges. Then, it identifies the risky drivers based on different patterns of drivers. Tests show the effectiveness of the proposed method. Since speed measurement is available on most of the newly build vehicles, this method can be easily implemented and used. The conclusion is useful to many traffic applications, e.g., driver training and insurance pricing.