Inclusive and Intelligent Traffic Management System for the Physically Impaired Pedestrians

This study investigates the consideration of physically impaired pedestrians in the existing traffic management system. Although IoT-driven intelligent systems have shown promise in managing traffic flow and incident detection, they overlook the specific needs of physically impaired individuals, leading to longer waiting times and safety. First, an Inclusive and Intelligent Traffic Management System (IITMS) is proposed, designed to support the independent mobility of physically impaired pedestrians by dynamically adjusting traffic signals and incorporating Vehicle to Everything (V2X). The framework integrates CCTV cameras with the YOLOv9 model for detecting individuals with mobility aids including crutches, wheelchairs, and walking frames, at pedestrian crossings. Integrated with V2X for communication amongst vehicles and pedestrians, an action selection strategy algorithm for enhanced optimization of real-time processing by maintaining optimal traffic flow for all users to enhance operational efficiency is then introduced. The simulation results show that integrating IITMS, V2X and an action selection strategy algorithm achieves 94% detection accuracy across various physical impairment categories and enhances operational efficiency compared to non-optimized models.