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Although, in recent years, significant developments have been made in road safety, traffic statistics indicate that we still need significant improvements in the field. Since traffic accidents usually reflect human factors, in this paper, we focus on clarifying the understanding of driver behaviors under hazardous scenarios. Brake pedal signals or driver speech, or both, are utilized to detect incidents from a real-world driving database of 373 drivers. Results are then analyzed to address the individuality in driver behaviors, the multimodality of driver reactions, and the detection of potentially dangerous locations. All of the existing 25 potentially hazardous scenes in the database are hand labeled and categorized. Based on the joint histograms of behavioral signals and their time derivatives, a detection feature is proposed and satisfactorily applied to the indication of anomalies in driving behavior. Seventeen scenes, where a reaction utilizing the brake pedal was observed, are detected with a true positive (TP) rate of 100% and a false positive (FP) rate of 4.1%. We demonstrate the relevance of considering behavior individuality. During 11 scenes, the drivers verbally reacted. Scenes that included high-energy words are adequately detected by the speech-based method, which achieved a TP rate of 54% for an FP rate of 6.4%. The integration of different behavior modalities satisfactorily boosts the detection of the most subjectively hazardous situations, which suggests the importance of considering multimodal reactions. Finally, a strong relationship is presented between locations where potentially hazardous situations occurred and areas of frequent strong braking.
Intelligent Transportation Systems, IEEE Transactions on (Volume:10 , Issue: 2 )
Date of Publication: June 2009