Improvements of Warning Signs for Black Ice Based on Driving Simulator Experiments

Int J Environ Res Public Health. 2022 Jun 20;19(12):7549. doi: 10.3390/ijerph19127549.

Abstract

Black ice is one of the main causes of traffic accidents in winter, and warning signs for black ice are generally ineffective because of the lack of credible information. To overcome this limitation, new warning signs for black ice were developed using materials that change color in response to different temperatures. The performance and effects of the new signs were investigated by conducting driver behavior analysis. To this end, driving simulator experiments were conducted with 37 participants for two different rural highway sections, i.e., a curve and a tangent. The analysis results of the driving behavior and visual behavior experiments showed that the conventional signs had insufficient performance in terms of inducing changes in driving behavior for safety. Meanwhile, the new signs actuated by weather conditions offered a statistically significant performance improvement. Typically, driver showed two times higher speed deceleration when they fixed eyes on the new weather-actuated warning sign (12.80 km/h) compared to the conventional old warning sign (6.84 km/h) in the curve segment. Accordingly, this study concluded that the new weather-actuated warning signs for black ice are more effective than the conventional ones for accident reduction during winters.

Keywords: driving behavior; eye tracker; hazard perception; road signs visibility; speeding; static warning sign; visual behavior.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic* / prevention & control
  • Automobile Driving*
  • Computer Simulation
  • Humans
  • Ice*
  • Safety
  • Weather

Substances

  • Ice

Grants and funding

The authors would like to express their gratitude for the financial support received from the Korea Agency for Infrastructure Technology Advancement, project “Development of road traffic safety improvement technology considering characteristics of external stimuli and traffic vehicles, grant number KAIA22POQW-B152745-04”.