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An Adaptive Traffic-Flow Management System with a Cooperative Transitional Maneuver for Vehicular Platoons.

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Autonomous vehicles (AVs) in platoons improve traffic flow and reduce accidents. This study proposes an adaptive approach using cooperative adaptive cruise control (CACC) for safer, efficient platooning.

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Area of Science:

  • Traffic management and autonomous systems
  • Road safety and vehicle dynamics
  • Intelligent transportation systems

Background:

  • Increasing vehicle numbers cause congestion and accidents.
  • Vehicle platooning offers solutions for traffic flow and safety.
  • Cooperative Adaptive Cruise Control (CACC) is key for connected, automated vehicles.

Purpose of the Study:

  • To propose an adaptive traffic flow and collision avoidance approach for vehicular platoons.
  • To enhance congestion mitigation and reduce accidents using CACC-based platooning.
  • To address platoon creation, evolution, and maneuverability in uncertain traffic.

Main Methods:

  • Developing an adaptive approach for vehicular platoons based on CACC.
  • Implementing platoon creation and evolution strategies.
  • Simulating merge and join maneuvers for steady platoon movement.

Main Results:

  • Significant improvement in traffic flow and congestion mitigation.
  • Reduction in travel time through efficient platooning.
  • Successful avoidance of collisions in various scenarios.

Conclusions:

  • The proposed CACC-based approach effectively manages traffic flow and enhances safety in platoons.
  • Platooning with CACC is a viable solution for mitigating congestion and preventing accidents.
  • Adaptive strategies are crucial for stable platoon operations during dynamic maneuvers.