Studying the response of drivers against different collision warning systems: A review

Muzammel, M. and Yusoff, M.Z. and Malik, A.S. and Saad, M.N.M. and Meriaudeau, F. (2017) Studying the response of drivers against different collision warning systems: A review. In: UNSPECIFIED.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

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.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 2; Conference of 13th International Conference on Quality Control by Artificial Vision, QCAV 2017 ; Conference Date: 14 May 2017 Through 16 May 2017; Conference Code:127966
Uncontrolled Keywords: Accidents; Electroencephalography; Electrophysiology; Highway accidents; Highway planning; Losses; Quality control; Response time (computer systems); Vehicles; Vision, Auditory warning; Collision warning system; Economic loss; Literature reviews; Number of vehicles; Rear-end collision warnings; Vehicle accidents; World Health Organization, Alarm systems
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:21
Last Modified: 09 Nov 2023 16:21
URI: https://khub.utp.edu.my/scholars/id/eprint/9275

Actions (login required)

View Item
View Item