Assessing the driving behaviour of motorcyclists to improve road safety - Ayoub Charef; Zahi Jarir; Mohamed Quafafou (Journal of Universal Computer Science, 2024)
Traffic violations by motorcycle riders pose a significant risk to urban road safety. In this paper, we present a novel approach that utilizes computer vision algorithms to detect and quantify traffic violations committed by motorcycle riders. These violations include non-compliance with helmet regulations, illegal lane changing, wrong way driving, weaving between vehicles, and running red lights. To enhance the awareness of motorcycle riders regarding the infractions they commit and the potential hazards these pose to road safety, we have developed a mobile application. This application not only provides riders with valuable feedback but also encourages them to be more conscientious and responsible for their actions. A series of experiments was conducted in the city of Marrakech, Morocco, demonstrating the system's effectiveness in positively influencing the behavior of motorcyclists on urban roads.