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Validation of driver support system based on real-world bicycle and motor vehicle flows.
- Source :
-
Accident; analysis and prevention [Accid Anal Prev] 2021 Jun; Vol. 156, pp. 106131. Date of Electronic Publication: 2021 Apr 16. - Publication Year :
- 2021
-
Abstract
- The incidence of traffic accidents in Japan has been decreasing annually. Nineteen percent of all accidents involve bicycles, with 51 % of these accidents being at road crossing intersections. Therefore, to reduce the number of accidents, this study analyses driving and cycling characteristics and proposes suitable collisions prevention methods. First, the study measured traffic environment variables using video cameras at a target non-signalized intersection and analyzed the speed and time to intersection of bicycles and motor vehicles. Thus, 47 dangerous situations were observed via the video analysis, and most of these situations occurred when the vehicle's time to intersection ranged from 0.50 to 0.75 s and the bicycle's speed ranged from 2.0-3.0 m/s. Second, using the results of video camera analysis as experimental parameters (e.g., the speed and timing of the presence of the bicycle), this study conducted an experiment with a driving simulator to investigate the effect of warning drivers about the risk of collision. A driver support system was then utilized to provide acoustic and optical warnings to drivers. The experiments revealed that the motor vehicle time to the anticipated collision point (V-TTC) increased with the use of a driver support system. Significant differences between experiments with and without driver support systems were observed when the calculated time between the bicycle and the motor vehicle was 0.25 and 0.50 s. Therefore, when the calculated time was 0.25 and 0.50 s, a driver support system, indicating the presence of a bicycle, was effective in preventing an intersection collision.<br /> (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1879-2057
- Volume :
- 156
- Database :
- MEDLINE
- Journal :
- Accident; analysis and prevention
- Publication Type :
- Academic Journal
- Accession number :
- 33873133
- Full Text :
- https://doi.org/10.1016/j.aap.2021.106131