Deep neural networks come as an effective solution to many problems associated with
autonomous driving. By providing real image samples with traffic context to the network, the …

Traffic lights perception problem is one of the key challenges for autonomous vehicle
controllers in urban areas. While a number of approaches for traffic light detection have …

Traffic light detection has great significant for unmanned vehicle and driver assistance
system. Meanwhile many detection algorithms have been proposed in recent years …

Traffic light detection is crucial for environment perception and decision-making in
autonomous driving. State-of-the-art detectors are built upon deep Convolutional Neural …

Recent work done on traffic sign and traffic light detection focus on improving detection
accuracy in complex scenarios, yet many fail to deliver real-time performance, specifically …

Traffic light detection technology can assist drivers in making decisions and has potential
applications in autonomous driving to reduce loss of life and property. However, the …

Real-time traffic light recognition is essential for autonomous driving. Yet, a cohesive
overview of the underlying model architectures for this task is currently missing. In this work …

This paper is to recognize the current traffic light phase to reliably detect the status of the
traffic light. eg; Red, Green and, Off-status and to focus cases where cameras have …

Due to the unavailability of Vehicle-to-Infrastructure (V2I) communication in current
transportation systems, Traffic Light Detection (TLD) is still considered an important module …

Traffic light and sign detectors on autonomous cars are integral for road scene perception.
The literature is abundant with deep learning networks that detect either lights or signs, not …