Abstract Intelligent Transportation Systems (ITS) help improve the ever‐increasing vehicular
flow and traffic efficiency in urban traffic to reduce the number of accidents. The generation …

This research explores the increasing applications of deep learning in traffic management
systems, with a focus on traffic prediction, object detection and recognition, autonomous …

As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

Abstract In recent years, Intelligent Transportation Systems (ITS) have seen efficient and
faster development by implementing deep learning techniques in problem domains which …

Abstract Machine learning (ML) plays the core function to intellectualize the transportation
systems. Recent years have witnessed the advent and prevalence of deep learning which …

Already known as densely populated areas with land use including housing, transportation,
sanitation, utilities and communication, nowadays, cities tend to grow even bigger. Genuine …

With the emerging concepts of smart cities and intelligent transportation systems, accurate
traffic sensing and prediction have become critically important to support urban …

Intelligent transportation systems (ITSs) will be a major component of tomorrow's smart
cities. However, realizing the true potential of ITSs requires ultralow latency and reliable …

This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

Recent years have seen a significant amount of transportation data collected from multiple
sources including road sensors, probe, GPS, CCTV and incident reports. Similar to many …