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http://dx.doi.org/10.12815/kits.2021.20.2.43

Estimation of Traffic Safety Improvement Effect of Forward Collision Warning (FCW)  

Kim, Hyung-kyu (Dept. of Future Tech. and Convergence Research, Korea Institute of Civil Eng, and Buiding Tech.)
Lee, Soo-beom (Dept. of Transportation Eng., Univ. of Seoul)
Lee, Hye-rin (Dept. of Transportation Eng., Univ. of Seoul)
Hong, Su-jeong (Dept. of Transportation Eng., Univ. of Seoul)
Min, hye-Ryung (Dept. of Transportation Eng., Univ. of Seoul)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.20, no.2, 2021 , pp. 43-57 More about this Journal
Abstract
The Forward Collision Warning, a representative technology of the Advanced Driver Assistance Systems, was selected as the target technology. The cognitive response time, deceleration, and impact were selected as the measures of effectiveness. And the amount of change with and without the Forward Collision Warning was measured. The experimental scenarios included a sudden stop event (1) of the vehicle in front of the driver and an event (2) in which the vehicle intervened in the next lane. All experiments were divided into day and night. As a result of the analysis, response time and the deceleration rate decreased when the forward collision warning system was installed. It was analyzed that the driver's risk situation could be detected quickly and the number of front-end collisions could be reduced as a result. Reflecting the driver's operating habits and diversifying the experimental scenarios will increase the installation effectiveness of ADAS and be used to estimate the effectiveness of other technologies.
Keywords
ADAS; FCW; Driving Simulation; Reaction Time; Estimation of Effect;
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  • Reference
1 AAAFoundation for Traffic Safety(2018), Vehicle Owner's Experiences with and Reactions to Advanced Driver Assistance Systems, pp.53-71.
2 Adell E. et al.(2011), "The effects of a driver assistance system for safe speed and safe distance-A real-life field study," Transp. Res. Part C Emerg. Technol., vol. 19, pp.145-155.   DOI
3 Adrian I. D. et al.(2018), "Effects of smartphone based advanced driver assistance system on distracted driving behavior: A simulator study," Computers in Human Behavior, vol. 83, pp.1-7.   DOI
4 Eleonora P. et al.(2018), "Analysis of driver behaviour through smartphone data: The case of mobile phone use while driving," Safety Science, vol. 119, pp.91-97.   DOI
5 Francesco B. and Roberta R.(2011), "A Collision Warning System for rear-end collision: A driving simulator study," Proc. Social Behav. Sci., vol. 20, pp.676-686.   DOI
6 Insurance Institute for Highway Safety(2016a), Crash test report-FCW, pp.72-79.
7 Insurance Institute for Highway Safety(2016b), Effectiveness of Forward Collision Warning Systems with and without Autonomous Emergency Braking in Reducing Police-Reported Crash Rates, pp.131-133.
8 James M. F. et al.(2019), "Adaptive driver modelling in ADAS to improve user acceptance: A study using naturalistic data," Safety Science, Vol. 119, pp.76-83.   DOI
9 Nengchao L. et al.(2019), "A field operational test in China: Exploring the effect of an advanced driver assistance system on driving performance and braking behavior," Transportation Research Part F: Traffic Psychology and Behaviour, vol. 65, pp.730-747.   DOI
10 Traffic Accident Analysis System, http://taas.koroad.or.kr/, 2021.03.23.
11 Yesim U. et al.(2019), "Traffic climate and driver behaviors: Explicit and implicit measures," Transportation Research Part F: Traffic Psychology and Behaviour, vol. 62, pp.805-818.   DOI