Traffic congestion has become a major challenge in recent years in many countries of the
world. One way to alleviate congestion is to manage the traffic efficiently by applying …

Data fusion is one of the recent approaches in traffic analysis for the accurate estimation and
prediction of traffic parameters. In this approach, the parameters are estimated using the …

Traffic congestion occurs when traffic demand is greater than the available network capacity.
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …

Big data have been used widely in many areas, including the transportation industry. Using
various data sources, traffic states can be well estimated and further predicted to improve the …

The knowledge of road traffic parameters is of crucial importance to ensure state-of-the-art
traffic services either in public or private transport. In our days, a plethora of road traffic data …

Recently, development in intelligent transportation systems (ITS) requires the input of
various kinds of data in real-time and from multiple sources, which imposes additional …

Traffic state prediction is a key problem with considerable implications in modern traffic
management. Traffic flow theory has provided significant resources, including models based …

With the rapid development of urbanization and modernization, it is increasingly crucial to
sense network-wide traffic. Network-wide traffic volume information is of great benefit for …

Estimation of densities on freeways and arterials is critical to traffic control and management.
Most previous work, however, focused on freeway density estimation based merely on …

Increased amount of vehicular traffic on roads is a significant issue. High amount of
vehicular traffic creates traffic congestion, unwanted delays, pollution, money loss, health …