GreenEye: Development of Real-Time Traffic Signal Recognition System for Visual Impairments
Recognizing a traffic signal, determining if the signal is green or red, and figuring out the time left to cross the crosswalk are significant challenges to visually impaired people. Previous research has focused on recognizing only two traffic signals, green and red lights, using machine learning techniques. The proposed method developed a GreenEye system that recognizes the traffic signals' color and tells the time left for pedestrians to cross the crosswalk in real-time. GreenEye's first training showed the highest precision of 74.6%; four classes reported 40% or lower recognition precision in this training session. The data imbalance caused low precision; thus, extra labeling and database formation were performed to stabilize the number of images between different classes. After the stabilization, all 14 classes showed excelling precision rate of 99.5%.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras
This paper introduces SynTraC, the first public image-based traffic signal control dataset, aimed at bridging the gap between simulated environments and real-world traffic management challenges. Unlike traditional datase…
ManagementTraffic Signal ControlGreenEyes: An Air Quality Evaluating Model based on WaveNet
Accompanying rapid industrialization, humans are suffering from serious air pollution problems. The demand for air quality prediction is becoming more and more important to the government's policy-making and people's dai…
Intelligent City Traffic Management and Public Transportation System
Intelligent Transportation System in case of cities is controlling traffic congestion and regulating the traffic flow. This paper presents three modules that will help in managing city traffic issues and ultimately gives…
ManagementCoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement Learning
The target of reducing travel time only is insufficient to support the development of future smart transportation systems. To align with the United Nations Sustainable Development Goals (UN-SDG), a further reduction of f…
Autonomous VehiclesDeep Reinforcement LearningA Survey on Traffic Signal Control Methods
Traffic signal control is an important and challenging real-world problem, which aims to minimize the travel time of vehicles by coordinating their movements at the road intersections. Current traffic signal control syst…
reinforcement-learningReinforcement LearningReinforcement Learning (RL)Survey+1