Towards the detection of potentially hazardous situations in vehicle traffic using driver speech and brake pedal operation

Abstract

A method for automatic detection of potentially dangerous situations in motor vehicle traffic is introduced. Unlike precedent works, which typically relied on camera arrays or road‐traffic monitoring sensors to detect collision incidents, the proposed approach specifically incorporates changes in a drivers’ behavior, detected through driver speech and brake pedal operation. Experiments were performed using a large real‐world multimedia driving database of 493 drivers, obtained from the Centre for Integrated Acoustic Information Research (CIAIR, Nagoya University). The drivers, who interacted verbally with a human operator, uttered expletive words to express negative feelings in 11 of the 25 situations that we selected as potentially hazardous. In 17 of them, sudden and intense compression of the brake pedal was observed. The proposed lexicographical speech‐feature‐based method also detected 33 false alarms to detect 80% of these 11 scenes. As for the other 17 scenes, our method based on two‐dimensional histograms of brake pressure and its dynamics achieved an 80% detection rate for 473 false alarms. Analyses of data recorded while drivers interacted with a machine and a Wizard of Oz system as well as a rank of the most commonly uttered words in dangerous situations are also presented.