Real-time road traffic prediction with spatio-temporal correlations

Real-time road traffic prediction is a fundamental capability needed to make use of advanced, smart transportation technologies. Both from the point of view of network operators as well as from the point of view of travelers wishing real-time route guidance, accurate short-term traffic prediction is a necessary first step. While techniques for short-term traffic prediction have existed for some time, emerging smart transportation technologies require the traffic prediction capability to be both fast and scalable to full urban networks. We present a method that has proven to be able to meet this challenge. The method presented provides predictions of speed and volume over 5-min intervals for up to 1 h in advance.

Research highlights
► New approach for short-term road traffic prediction.
► Effective on urban road networks, both expressway and arterial roads.
► Scalable from medium-sized to large urban or inter-urban networks.
► Highly accurate up to one hour in advance.