In the area of object detection in road situations, significant advancements have been made
in recent years. Nevertheless, it focuses mostly on vehicles and people as its targets. In …

The increasing number of vehicles, followed by traffic congestion, has posed a great
challenge to the optimal control of traffic for human societies. Therefore, in order to achieve …

The quantity of vehicles on the road is progressively escalating, resulting in heavily
congested roads. This could result in many accidents. Computer vision systems for spotting …

One of the most significant uses of autonomous cars in recent years is the detection of traffic
light signals. Deep learning technology, which has a number of benefits including high …

The number of new vehicles on the road is increasing rapidly, which in turn causes highly
congested roads and serving as a reason to break traffic rules by violating them. This leads …

Traffic jam is a problem that directly affects the quality of life of the population in large cities.
This problem exacerbates at road intersections, where obsolete traffic control systems based …

Autonomous vehicles are one of the increasingly widespread application areas in
automotive technology. These vehicles show significant potential in improving transportation …

One of the most important requirements for the next generation of traffic monitoring systems,
autonomous driving technology and Advanced Driving Assistance Systems (ADAS) is the …

Dynamic traffic management is necessary to reduce congestion levels and the wait time for
vehicles. In this paper, Deep Learning architecture is adopted to implement a dynamic traffic …

Deep Learning based networks especially Convolutional Neural Network (CNN) models are
widely used in vehicle detection, classification and counting system. On the other hand …