Emergency vehicles (EVs) are permitted to travel at high speed to quickly reach the
destination with the aid of audible and visual warning signals, and other road users are …

Emergency vehicle detection plays a critical role in ensuring timely responses and reducing
accidents in modern urban environments. However, traditional methods that rely solely on …

As an effective means of solving collision problems caused by the limited perspective on
board, the cooperative roadside system is gaining popularity. To improve the vehicle …

In intelligent transportation systems, traditional object detection algorithms struggle to
handle complex environments and varying lighting conditions, particularly when detecting …

The use of mobiles phones when driving has been a major factor when it comes to road
traffic i ncidents and the process of capturing such violations can be a laborious task …

Vehicle detection is a fundamental component of intelligent transportation systems.
However, current algorithms often encounter issues such as high computational complexity …

Recent advancements in artificial intelligence (AI) have greatly improved the object
detection capabilities of autonomous vehicles, especially using convolutional neural …

Deep learning-based classification and detection algorithms have emerged as a powerful
tool for vehicle detection in intelligent transportation systems. The limitations of the number …

Under the extreme conditions such as excessive light, insufficient light or high-speed motion,
the detection of vehicles by frame-based cameras still has challenges. Event cameras can …

This study proposes an embedded traffic sign detection system, YOLOV5-MCBS, based on
an enhanced YOLOv5 algorithm. This system aims to mitigate the impact of traditional target …