Applications of wavelet transform for analysis of freeway traffic: Bottlenecks, transient traffic, and traffic oscillations

This paper demonstrates the capabilities of wavelet transform (WT) for analyzing important features related to bottleneck activations and traffic oscillations in congested traffic in a systematic manner. In particular, the analysis of loop detector data from a freeway shows that the use of wavelet‐based energy can effectively identify the location of an active bottleneck, the arrival time of the resulting queue at each upstream sensor location, and the start and end of a transition during the onset of a queue. Vehicle trajectories were also analyzed using WT and our analysis shows that the wavelet‐based energies of individual vehicles can effectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lane‐changing). The spatiotemporal propagations of oscillations identified by tracing wavelet‐based energy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration and intensity.