Optimization of colored pavement considering driving behavior and psychological characteristics under dynamic low-visibility conditions related to fog—a driving simulator study

Abstract

Objective

Colored pavement is commonly used to reduce the road traffic risk and promote road traffic safety, but its performance in foggy environments has not been fully assessed. The goal of this research is to explore the effectiveness and optimization of colored pavement in a dynamic low-visibility environment.

Methods

A driving simulation experiment is conducted. Three road risk sections in which collisions are common, including a long straight section, a sharp bend section, and a long downslope section, are considered, and three forms of colored pavement are used in five different visibility environments. The effectiveness of the colored pavement is explored by collecting and analyzing driving behavior and physiological characteristic data for 30 drivers in the established driving environment, and information is obtained through a subjective colored evaluation questionnaire. Eight evaluation indexes are selected from the perspectives of driving behavior and physiological characteristics, and the gray premium evaluation method is applied to evaluate the effectiveness of different forms of colored pavement considering the influence of visibility. Finally, the optimal colored pavement under various visibility and road alignment conditions is proposed.

Results

The results show that reasonably selecting colored pavement can effectively improve drivers’ behaviors and physiological characteristics under foggy conditions. For different road alignments and visibility conditions, different forms of colored pavement should be used to ensure road traffic safety.

Conclusions

The findings provide a theoretical reference for the optimization of colored pavement in foggy conditions.

Keywords:

• Traffic safety
• colored pavement
• driving behavior
• physiological characteristic

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data supporting this study’s findings are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the Introduction of Talents and Doctoral Initiation Fund for Universities [Grant no. 2022QDZ25], the National Natural Science Foundation of China [Grant Nos. 51878236 and 71971073], the Open Fund for the Key Traffic Safety Laboratory of the Ministry of Public Security [Grant no. 2021ZDSYSKFKT01], and the Natural Science Research Project of the University in Anhui Province, China [Grant no. KJ2021A0019].