From the early stages of autonomous vehicle's development, traffic light detection/perception
system have been an important area of research for making collision safe self-driving …

Automated Driving Systems (ADS) have made great achievements in recent years thanks to
the efforts from both academia and industry. A typical ADS is composed of multiple modules …

Reliable traffic light detection and classification is crucial for automated driving in urban
environments. Currently, there are no systems that can reliably perceive traffic lights in real …

This paper presents the challenges that researchers must overcome in traffic light
recognition (TLR) research and provides an overview of ongoing work. The aim is to …

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

The recent explosion of large volume of standard dataset of annotated images has offered
promising opportunities for deep learning techniques in effective and efficient object …

For facing of the problems caused by the YOLOv4 algorithm's insensitivity to small objects
and low detection precision in traffic light detection and recognition, the Improved YOLOv4 …

Autonomous terrestrial vehicles must be capable of perceiving traffic lights and recognizing
their current states to share the streets with human drivers. Most of the time, human drivers …

Traffic light detection (TLD) is a vital part of both intelligent vehicles and driving assistance
systems (DAS). hard to determine the exact performance of a given method. In this paper we …

Deep neural networks (DNNs) have achieved outstanding results in domains such as image
processing, computer vision, natural language processing and bioinformatics. In recent …