JUCS - Journal of Universal Computer Science 30(5): 617-644, doi: 10.3897/jucs.108550
Assessing the driving behaviour of motorcyclists to improve road safety
Ayoub Charef‡, Zahi Jarir‡, Mohamed Quafafou§‡ Cadi Ayyad University, Marrakech, Morocco§ University of Aix-Marseille, Marseille, France
Corresponding author: Ayoub Charef ( ayoub.charef@ced.uca.ma ) © Ayoub Charef, Zahi Jarir, Mohamed Quafafou. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. Citation:
Charef A, Jarir Z, Quafafou M (2024) Assessing the driving behaviour of motorcyclists to improve road safety. JUCS - Journal of Universal Computer Science 30(5): 617-644. https://doi.org/10.3897/jucs.108550 |  |
Abstract
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.
Keywords
Road safety, Traffic violations, Motorcycles, Object detection, License plate recognition