Toward Mitigating Phantom Jam Using Vehicle-to-Vehicle Communication

Traffic jams often occur without any obvious reasons such as traffic accidents, roadwork, or closed lanes. Under moderate to high traffic density, minor perturbations to traffic flow (e.g., a strong braking motion) are easily amplified into a wave of stop-and-go traffic. This is known as a phantom jam. In this paper, the authors aim to mitigate phantom jams leveraging the three-phase traffic theory and vehicle-to-vehicle (V2V) communication. More specifically, an efficient phantom jam control protocol is proposed in which a fuzzy inference system is integrated with a V2V-based phantom jam detection algorithm to effectively capture the dynamics of traffic jams. Per-lane speed difference under traffic congestion is taken into account in the protocol design, so that a phantom jam is controlled separately for each lane, improving the performance of the proposed protocol. The authors implemented the protocol in the Jist/SWAN traffic simulator. Simulations with artificially generated traffic data and real-world traffic data collected from vehicle loop detectors on Interstate 880, California, USA, demonstrate that the authors' approach has by up to 9% and 4.9% smaller average travel times (at penetration rates of 10%) compared with a state-of-the-art approach, respectively.

Language

  • English

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Filing Info

  • Accession Number: 01637106
  • Record Type: Publication
  • Files: TLIB, TRIS
  • Created Date: May 4 2017 2:42PM