Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …

Real-time traffic state (eg, speed) prediction is an essential component for traffic control and
management in an urban road network. How to build an effective large-scale traffic state …

Planning effective routes and monitoring vehicle traffic are essential for creating sustainable
smart cities. Accurate speed prediction is a key component of these efforts, as it aids in …

Short-term traffic prediction is of great importance to the management of traffic congestion, a
pervasive and difficult-to-solve problem in many metropolises all over the world. However …

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 …

This study proposes a framework to classify traffic flow states. The framework is capable of
processing massive, high-density, and noise-contaminated data sets generated from …

Travel time estimation is one of the core tasks for the development of intelligent
transportation systems. Most previous works model the road segments or intersections …

Queue length is an important parameter to evaluate the congestion level of urban
intersections. Abundant methods based on different data sources, such as loop detector …

In practice, most of the intelligent transportation systems provide average travel times of all
vehicles on selected paths in real time on a regular basis. However, path travel times of …

This paper presents a framework for signalized road network predictive optimization using
real-time routing information from connected vehicles (CVs). An important feature of the real …