Journal of Intelligent and Connected Vehicles (Sep 2021)

Evaluation of fog warning system on driving under heavy fog condition based on driving simulator

  • Xiaohua Zhao,
  • Xuewei Li,
  • Yufei Chen,
  • Haijian Li,
  • Yang Ding

DOI
https://doi.org/10.1108/JICV-11-2020-0012
Journal volume & issue
Vol. 4, no. 2
pp. 41 – 51

Abstract

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Purpose – Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance. Design/methodology/approach – First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered. Findings – The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly. Originality/value – This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

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