Applied Sciences (Aug 2022)

Coordinated Multi-Platooning Planning for Resolving Sudden Congestion on Multi-Lane Freeways

  • Jia-You Lin,
  • Chia-Che Tsai,
  • Van-Linh Nguyen,
  • Ren-Hung Hwang

DOI
https://doi.org/10.3390/app12178622
Journal volume & issue
Vol. 12, no. 17
p. 8622

Abstract

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Resolving traffic congestion caused by sudden events (e.g., an accident, lane closed due to construction) on the freeway has always been a problem that is challenging to address perfectly. The congestion resolution can take hours if the congestion is severe, and the vehicles must voluntarily line up to exit the congestion spots. Most state-of-the-art traffic scheduling schemes often rely on traffic signal controllers to mitigate traffic congestion in fixed areas (e.g., intersection, blocked areas). Unlike the existing studies, in this work, we introduce a novel decentralized coordinated platooning planning method, namely Coordinated Platooning Planning (CPP), for quickly resolving temporary traffic congestion in any place on multi-lane freeways heuristically. First, based on warning notifications about traffic congestion, we propose a maneuver control protocol that enables the vehicles to negotiate with surrounding vehicles to determine a consensus plan for forming platoons (who is platoon leader, the value of the distance gap, vehicle velocity, platoon size) in sequential areas. After creating the platoons, each platoon leader commands their platoon members through the maneuver protocol to urge the vehicles to move close to or merge into the same lane. Finally, the chains of platooning vehicles can safely exit the congestion using scheduled orders. The simulation results demonstrate that the proposed heuristic approach can reduce up to 22% of the delay for the last few vehicles driving through the congestion area in typical traffic density cases with the best platoon size configuration, which is a significant enhancement compared to the existing schemes.

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