This paper demonstrates the capabilities of wavelet transform (WT) for analyzing importantfeatures related to bottleneck activations and traffic oscillations in congested traffic in asystematic and reproducible manner. In particular, the analysis of loop detector data from afreeway shows that the use of wavelet-based energy can effectively identify the location of anactive bottleneck, the arrival time of the resulting queue at each upstream sensor location, andthe start and end of a transition during the onset of a queue. Vehicle trajectories were alsoanalyzed using WT and our analysis shows the wavelet-based energies of individual vehicles caneffectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lanechanging). The spatiotemporal propagations of oscillations identified by tracing wavelet-basedenergy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration andintensity.
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