Detecting the Breakdown of Traffic

Timely traffic prediction is important in advanced traffic management systems. Observing traffic flow, we find repetitive or regular behavior over time. By taking advantage of tools in frequency domain analysis, this paper proposes a new criterion function that can detect the onset of congestion. It is found that the changing rate of the cross-correlation between density dynamics and flow rate identifies traffic moving from free flow phase to the congestion phase. A definition of traffic stability is proposed based on the criterion function. The new method suggests that an unreturnable transition will occur only if the changing rate of the cross-correlation exceeds a threshold. Based on real traffic data, the detection of congestion is conducted in which the new scheme performs well compared to previous studies.