Traffic state estimation (TSE) refers to the process of the inference of traffic state variables
(ie, flow, density, speed and other equivalent variables) on road segments using partially …

Due to the increase in vehicle transit and congestion in road networks, providing information
about the state of the traffic to commuters has become a critical issue for Advanced Traveller …

Traffic state estimation is a crucial elemental function in Intelligent Transportation Systems
(ITS). However, the collected traffic state data are often incomplete in the real world. In this …

Recently connected vehicle (CV) technology has received significant attention thanks to
active pilot deployments supported by the US Department of Transportation (USDOT). At …

The operation of traffic signals is currently limited by the data available from traditional point
sensors. Point detectors can provide only limited vehicle information at a fixed location. The …

We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …

Previous studies have presented convincing arguments that a frequent pattern mining
algorithm should not mine all frequent patterns but only the closed ones because the latter …

This paper presents two algorithms to estimate traffic state in urban street networks with a
mixed traffic stream of connected and unconnected vehicles and incorporates them in a real …

This paper presents a Bayesian inference-based dynamic linear model (DLM) to predict
online short-term travel time on a freeway stretch. The proposed method considers the …

Traditional technologies, such as inductive loop detectors, do not usually produce
measurements of the quality required by real-time applications. Therefore, one wonders …