@article{oai:nagoya.repo.nii.ac.jp:00007876,
 author = {Malta, Lucas and Miyajima, Chiyomi and Takeda, Kazuya},
 journal = {IEEE Intelligent Vehicles Symposium},
 month = {},
 note = {This study focused on the analysis of drivers' reactions under hazardous scenarios in vehicle traffic. Driving behavior signals were utilized to detect a chain of changes in driver status and to retrieve incidents from a large real-world driving database obtained from the Center for Integrated Acoustic Information Research (CIAIR). All the existing 25 potentially hazardous scenes in the database were hand-labeled and categorized. A new feature, based on joint-histograms of these behavioral signals and their dynamics was proposed and utilized to indicate anomalies in driving behavior. Brake pedal force-based method attained a true positive (TP) rate of 100 ％　for a false positive (FP) rate of 4.5 ％, concerning the detection of 17 scenes where drivers slammed on the brakes. Results stressed the relevance of individuality in drivers' reactions for this retrieval. In 11 of the 25 hand-labeled scenes, drivers reacted verbally. Scenes where high-energy words were present were adequately retrieved by the speech-based detection, which achieved a TP rate of 54 ％ (6 scenes), for a FP rate of 6.4 ％. In addition, the proposed integration method, which combined brake force and speech signals, was satisfactory in boosting the detection of the most subjectively dangerous situations.},
 pages = {1144--1149},
 title = {Analysis of Drivers' Responses under Hazardous Situations in Vehicle Traffic},
 year = {2007}
}