Naturalistic Experiment for Surface Transportation: A Study of Snowplow Lighting under Winter Conditions.

Autor: Wong, Andy H., Sharma, Davesh, Kilani, Omar, Momeni Rad, Faeze, Wong, Stephen D., Kwon, Tae J., El-Basyouny, Karim
Zdroj: Journal of Transportation Engineering. Part A. Systems; Feb2025, Vol. 151 Issue 2, p1-12, 12p
Abstrakt: Inclement winter weather poses a safety risk to all road users, primarily due to roads covered with snow or ice and substantially reduced visibility. The winter road maintenance vehicles used are often larger and slower moving than the surrounding traffic and often become a hazard themselves. To enhance visibility and safety, agencies equip their fleets with lighting to make them more visible to the surrounding motorists. In Alberta, Canada, the use of amber-only lights is currently permitted for maintenance vehicles. To evaluate whether the addition of light colors could measurably improve road safety for snowplow trucks and motorists, we conducted a human reaction field study (n=384 trials) and a general public survey (n=454 participants), testing several combinations of light colors. The field experiment revealed that amber-only lights resulted in slower reaction times, whereas amber-blue and amber-white performed better. Survey results demonstrated a preference for amber-white lighting, which was deemed the most effective setup. The survey also indicated that lighting perception varies across age, gender, and specific types of driver's license among demographics. Although this research identifies optimal lighting configurations and underscores targeted policy-making and operational strategies, its direct impact on road safety remains to be determined. It is possible that shorter perception/reaction times given the lighting changes could reduce the number of collisions. Incorporating these results into existing practices could potentially enhance road safety standards, making winter roads safer across jurisdictions in North America. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index