Cross-Assist: Road Assistance Application for Visually Impaired People

According to WHO (World Health Organization) 2.2 billion people in the world have visual impairment. About 40 million of them experience complete vision loss. This number is substantial for the world population. Lack of visual function is one factor that makes it difficult for the individual to participate in social life. Because a barrier-free life is aimed, studies have emerged due to the difficulties encountered. One of these difficulties is that they need help seeing pedestrian lights and roads to cross the street. In this study, a mobile application is designed to address this issue. The application provides visually impaired individuals with voice alerts about the status of crosswalks and traffic lights. This mobile application was developed using Flutter. The convolutional neural network model and YOLO (You Only Look Once) v2Tiny algorithm were used for real-time object recognition from the images taken from the mobile phone camera. Mobile application successfully recognizes red light, green light, and crosswalk with 89.52%, 89.1%, and 88.57% accuracies, respectively. The novelty of this study lies in incorporating both pedestrian traffic light detection and crosswalk identification within a mobile application.