Evaluating the Intensity of Green Warning Light for Snowplow Trucks Using CIELAB Color Space

Snowplow Trucks (SPTs) work under extremely challenging conditions, typically traveling at lower speeds compared with other vehicles. Because of reduced speeds and poor visibility, a major safety concern during snow plowing and deicing is the risk of rear-end crashes involving vehicles and SPTs. Crashes involving SPTs may lead to significant property damage, expenses for vehicle repairs, and medical costs. Furthermore, these crashes have the potential to temporarily render the SPTs inoperable, leading to higher operating costs and decreased mobility and safety on the affected road networks. Even with the advancement and accessibility of different kinds of warning light technologies, a significant portion of collisions are still ascribed to the insufficient visibility of SPTs or winter maintenance trucks. This study examines the effectiveness of warning lights of different colors by taking into account the various times of day and weather conditions during winter maintenance activities, including clear, overcast, rain, and snow. Using CIELAB (International Commission on Illumination La*b*) and HSV color space, a prototype system measures green and blue light intensity at varying snow levels and distances. Weighted image entropy is calculated using varying snow intensity and distance. Finally, with the help of Image grayscale histogram and computer vision techniques, the intensity of green and blue lights is calculated. Except for the heavy snow conditions, the green light-emitting diode (LED) light exhibits a higher intensity, ranging from 28% to 134%, than the blue LED light. The results show that the green LED provides increased perceptual lightness than the blue LED in varying reduced visibility.