This paper systematically reviews studies that forecast short-term traffic conditions using
spatial dependence between links. We extract and synthesise 130 research papers …

In the last two decades, the growing need for short‐term prediction of traffic parameters
embedded in a real‐time intelligent transportation systems environment has led to the …

Delft University of Technology oad traffic is the visible result of the complex interplay
between traffic demand (the amount and mix of vehicles arriving at a particular place and …

Short-term forecasting of traffic parameters such as flow and occupancy is an essential
element of modern Intelligent Transportation Systems research and practice. Although many …

Accuracy and robustness with respect to missing or corrupt input data are two key
characteristics for any travel time prediction model that is to be applied in a real-time …

Traffic state prediction is a key component in intelligent transport systems (ITS) and has
attracted much attention over the last few decades. Advances in computational power and …

Accurate short-term prediction of traffic conditions on freeways and major arterials has
recently become increasingly important because of its vital role in the basic traffic …

The forecasting of short-term traffic flow is one of the key issues in the field of dynamic traffic
control and management. Because of the uncertainty and nonlinearity, short-term traffic flow …

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 forecasting of high-speed rail (HSR) passenger flow provides daily ridership
estimates that account for day-to-day demand variations in the near future (eg, next week …