Studying the Response of Drivers against Different Collision Warning Systems: A Review

Autor: Muzammel, M, Yusoff, M. Zuki, Malik , Aamir Saeed, Mohamad Saad , Mohamad Naufal, Meriaudeau , Fabrice
Přispěvatelé: université de Bourgogne, LE2I, Nagahara, H., Umeda, K., Yamashita, A., Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre for Intelligent Signal and Imaging Research (Universiti Teknologi Petronas) ( CISIR ), Ministry of Education Malaysia under Higher Institution Centre of Excellence (HICoE) Scheme, Centre for Graduate Studies (CGS), Universiti Teknologi PETRONAS, Malaysia, Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR), Universiti Teknologi PETRONAS (UTP)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: THIRTEENTH INTERNATIONAL CONFERENCE ON QUALITY CONTROL BY ARTIFICIAL VISION 2017
13th International Conference on Quality Control by Artificial Vision
Nagahara, H.; Umeda, K.; Yamashita, A. 13th International Conference on Quality Control by Artificial Vision, May 2017, Tokyo, Japan. SPIE-INT SOC OPTICAL ENGINEERING, 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA, THIRTEENTH INTERNATIONAL CONFERENCE ON QUALITY CONTROL BY ARTIFICIAL VISION 2017 10338 pp.UNSP 1033816 2017, Proceedings of SPIE 〈https://translate.google.fr/translate?hl=fr&sl=en&u=http://www.tc-iaip.org/QCAV2017/AboutQCAV2017.html&prev=search〉
13th International Conference on Quality Control by Artificial Vision, May 2017, Tokyo, Japan. pp.UNSP 1033816
Popis: International audience; The number of vehicle accidents is rapidly increasing and causing significant economic losses in many countries. According to the World Health Organization, road accidents will become the fifth major cause of death by the year 2030. To minimize these accidents different types of collision warning systems have been proposed for motor vehicle drivers. These systems can early detect and warn the drivers about the potential danger, up to a certain accuracy. Many researchers study the effectiveness of these systems by using different methods, including Electroencephalography (EEG). From the literature review, it has been observed that, these systems increase the drivers' response and can help to minimize the accidents that may occur due to drivers unconsciousness. For these collision warning systems, tactile early warnings are found more effective as compared to the auditory and visual early warnings. This review also highlights the areas, where further research can be performed to fully analyze the collision warning system. For example, some contradictions are found among researchers, about these systems' performance for drivers within different age groups. Similarly, most of the EEG studies focus on the front collision warning systems and only give beep sound to alert the drivers. Therefore, EEG study can be performed for the rear end collision warning systems, against proper auditory warning messages which indicate the types of hazards. This EEG study will help to design more friendly collision warning system and may save many lives.
Databáze: OpenAIRE
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