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 …

Intelligent Transportation System (ITS) is vital in improving traffic congestion, reducing traffic
accidents, optimizing urban planning, etc. However, due to the complexity of the traffic …

Accurate travel-time prediction of public transport is essential for reliable journey planning in
urban transportation systems. However, existing studies on bus travel-/arrival-time prediction …

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 number of short-term travel time prediction approaches have been developed in the past
decade. However, few studies take into account spatial and temporal travel time information …

This study presents a feature selection method that uses genetic algorithms to create two
artificial neural network‐based models that provide a sequential forecast of accident …

(56) References Cited 7.433, 696 B2 10/2008 Dietrich et al. 7.463, 890 B2 12/2008 Herz et
al. US PATENT DOCUMENTS 7,512.462 B2 3/2009 Nichols et al. 7,565,157 B1 7/2009 …

While vehicular congestion is very often defined in terms of aggregate parameters, such as
traffic volume and lane occupancies, based on recent findings, the interpretation that …

Travel time serves as a fundamental measurement for transportation systems and becomes
increasingly important to both drivers and traffic operators. Existing speed interpolation …

Prediction of travel time has major concern in the research domain of Intelligent
Transportation Systems (ITS). Clustering strategy can be used as a powerful tool of …