Artificial neural network (ANN) techniques are applied to build a travel time estimation
model. The model exhibits a functional relation between real-time traffic data as the input …

Short-term travel-time prediction is very important to the real-time traveler information and
route guidance system. Various methodologies have been developed for dynamic travel …

This paper introduces a novel approach to the online short-term prediction of point-to-point
freeway travel time, combining statistical forecasting techniques with traffic simulation. At …

One of the major requirements of advanced traveler information systems (ATISs) is a
mechanism to estimate link travel times. This article examines the use of an artificial neural …

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 …

A travel time prediction algorithm scalable to large freeway networks with many nodes with
arbitrary travel routes is proposed. Instead of constructing separate predictors for individual …

Prediction of short-term future traffic condition on real-time basis is important as it can allow
travelers to avoid traffic congestion and react to the traffic incidents immediately after they …

Providing reliable travel time prediction is very much needed for commuters for their
upcoming trips to reduce travel time and relieve traffic congestion. This article proposes an …

Travel time prediction has been an interesting research area for decades during which
various prediction models have been developed. This paper discusses the results and …

With the advent of advanced traveler information systems, the prediction of short-term link
and corridor travel times has become increasingly important. The standard method for …