Tracking congestion throughout the network road is a critical component of Intelligent
transportation network management systems. Understanding how the traffic flows and short …

The artificial neural network (ANN) is one advance approach to freeway travel time
prediction. Various studies using different inputs have come to no consensus on the effects …

Increasing mobility and congestion results in an increase in travel time variability and in a
decrease in reliability. Reliability becomes an important performance measure for …

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over
the world, particularly in the Western United States. Communities in wildland–urban …

This paper investigates the performance of a flow model in providing efficient travel-time
estimation for varying flow patterns of freeway traffic by adopting a two-phase fundamental …

Loop detectors distributed on freeways are very vulnerable and could be damaged or
malfunctioned due to improper sealing, pavement deterioration. This may lead to poor travel …

Travel time and its reliability are intuitive system performance measures for freeway traffic
operations. This paper proposes a method to estimate travel times based on data collected …

In this study, a new vehicle classification algorithm was developed with inductive loop
signature technology. There were two steps to the proposed algorithm. The first step was to …

The present study summarises the travel time reconstruction performance of a network flow
model by explicitly analysing the adopted fundamental diagram relation under congested …

A simple method for vehicle re-identification to generate vehicle passage times with loop
data is developed. The method departs from other existing methods for vehicle passage time …