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Research paper | Open Access

Research on the classification for road traffic visibility based on the characteristics of driving behaviour – a driving simulator experiment

Kun Wang1, Weihua Zhang2, Zhongxiang Feng2( ), Cheng Wang1
College of Civil Engineering, Hefei University of Technology, Hefei, China
School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei, China
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Abstract

Purpose

The purpose of this paper is to perform fine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions.

Design/methodology/approach

A driving simulator experiment was conducted to collect data of speed and lane position. ANOVA was used to explore the difference in driving behavior under different visibility conditions.

Findings

The results show that only average speed is significantly different under different visibility conditions. With the visibility reducing, the average vehicle speed decreases. The road visibility conditions in a straight segment can be divided into five levels: less than 20, 20-30, 35-60, 60-140 and more than 140 m. The road visibility conditions in a curve segment can be also divided into four levels: less than 20, 20-30, 35-60 and more than 60 m.

Originality/value

A fine classification of road traffic visibility has been performed, and these classifications help to establish more accurate control measures to ensure road traffic safety under low-visibility conditions.

Keywords

SpeedDriving simulator experimentLane positionLow visibilityTraffic safety

References

【1】
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Journal of Intelligent and Connected Vehicles
Volume 3 Issue 1,
April 2020
Pages 30-36
DOI: 10.1108/JICV-10-2019-0011

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Cite this article:
Wang K, Zhang W, Feng Z, et al. Research on the classification for road traffic visibility based on the characteristics of driving behaviour – a driving simulator experiment. Journal of Intelligent and Connected Vehicles, 2020, 3(1): 30-36. https://doi.org/10.1108/JICV-10-2019-0011

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Received: 22 October 2019
Revised: 23 December 2019
Accepted: 28 January 2020
Published: 11 March 2020
© 2020 Kun Wang, Weihua Zhang, Zhongxiang Feng and Cheng Wang. Published in Journal of Intelligent and Connected Vehicles. Published by Emerald Publishing Limited.

This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode