Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform

Zheng, Zuduo; Ahn, Soyoung; Chen, Danjue; Laval, Jorge · 2011 · OpenAlex-citations

DOI: 10.1016/j.trb.2011.05.012

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Summary

This study investigates the microscopic mechanisms behind the formation and propagation of freeway traffic oscillations, commonly known as stop-and-go traffic. While previous research often relied on low-resolution loop detector data or limited trajectory samples, this paper addresses the need for a systematic, objective analysis of individual vehicle behaviors. The authors aim to determine whether oscillations are primarily triggered by lane-changing maneuvers (LCMs) or instabilities in car-following (CF) behavior, and to characterize how these disturbances propagate regardless of their origin. To achieve this, the researchers analyzed 53 distinct oscillation cases using high-resolution vehicle trajectory data from the FHWA’s Next Generation Simulation (NGSIM) program. The data were collected at two sites: a straight, level segment of northbound I-80 in Emeryville, California, and an uphill segment of southbound US-101 in Los Angeles, California. The study employed Wavelet Transform (WT) to process the noisy trajectory data, allowing for the precise identification of oscillation origins and the tracing of deceleration and acceleration waves through traffic queues. This method enabled the authors to distinguish between isolated speed changes and propagating disturbances with minimal subjective judgment. The findings reveal that oscillation triggers are site-specific. On the I-80 segment, LCMs were the predominant cause of oscillations, whereas on the US-101 segment, oscillations were primarily triggered by car-following instabilities, likely exacerbated by the uphill grade and roadside maintenance activity. Despite these different origins, the propagation characteristics of the oscillations were statistically similar. All observed cases exhibited an initial "precursor phase" where speed changes were localized and propagation speed was near zero. In 22 of the 53 cases, these oscillations transitioned into a "well-developed phase," propagating upstream at speeds of approximately 8–12 mph. Lane-changing maneuvers were identified as the primary factor driving this transition from precursor to well-developed states in most instances. Additionally, the study found that oscillations have a regressive effect on driver behavior, causing timid drivers to become less timid and aggressive drivers to become less aggressive, a phenomenon accurately modeled by an extended framework of Newell’s car-following theory.

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