Much of the current activity in the area of intelligent vehicle-highway systems (IVHSs)
focuses on one simple objective: to collect more data. Clearly, improvements in sensor …

Accurate short-term traffic flow forecasting has become a crucial step in the overall goal of
better road network management. Previous research [H. Kirby, M. Dougherty, S. Watson …

This paper presents a new short-term traffic flow prediction system based on an advanced
Time Delay Neural Network (TDNN) model, the structure of which is synthesized using a …

Proper prediction of traffic flow parameters is an essential component of any proactive traffic
control system and one of the pillars of advanced management of dynamic traffic networks …

Traffic flow on freeways is a complex process that often is described by a set of highly
nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However …

This paper presents a recursive traffic flow prediction algorithm using artificial neural
networks. The system prediction model is specified based on the understanding of how …

An approach to freeway travel time prediction based on recurrent neural networks is
presented. Travel time prediction requires a modeling approach that is capable of dealing …

Short term forecasts of traffic flow at a site may need to be based on inputs from several
other sites and times. Neural networks can be readily used for this purpose, because they …

Forecasting traffic volume is an important task in controlling urban highways, guiding drivers'
routes, and providing real-time transportation information. Previous research on traffic …

Short-term traffic flow prediction has long been regarded as a critical concern for intelligent
transportation systems. On the basis of many existing prediction models, each having good …