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SWSCAV: Real-time traffic management using connected autonomous vehicles.

Ilgin Gokasar1, Alperen Timurogullari1, Muhammet Deveci2

  • 1Department of Civil Engineering, Bogazici University, 34342 Bebek, Istanbul, Turkey.

ISA Transactions
|July 6, 2022
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Summary

A new traffic management system using connected autonomous vehicles (CAVs) slows incoming traffic to prevent congestion. This shockwave warning system for CAVs (SWSCAV) effectively reduces traffic density, even at low CAV penetration rates.

Keywords:
Connected autonomous vehiclesLCSShockwave speedTraffic managementVSL

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Area of Science:

  • Intelligent Transportation Systems (ITS)
  • Traffic Engineering
  • Autonomous Vehicle Technology

Background:

  • Traffic congestion remains a significant challenge, impacting efficiency and safety.
  • Connected autonomous vehicles (CAVs) offer new possibilities for active traffic management.
  • Existing systems like Lane Control Signals (LCS) and Variable Speed Limits (VSL) have limitations.

Purpose of the Study:

  • To propose and evaluate a novel CAV-based traffic management strategy called Shockwave Warning System for CAVs (SWSCAV).
  • To compare the performance of SWSCAV against traditional traffic management systems (LCS and VSL).
  • To assess the effectiveness of SWSCAV under various traffic conditions and CAV market penetration rates.

Main Methods:

  • Developed the SWSCAV algorithm where CAVs detect and match the speed of detected shockwaves.
  • Simulated traffic flow on a three-lane highway using the Simulation of Urban Mobility (SUMO) environment.
  • Evaluated 4800 scenarios varying CAV market penetration, control distances, incident lane, and duration.

Main Results:

  • SWSCAV reduced traffic density exceeding 38 veh/km/lane by 12.68% and 28 veh/km/lane by 8.15% near incident sites.
  • The proposed method demonstrated a twofold greater reduction in traffic density compared to LCS, even at low CAV penetration.
  • SWSCAV effectively mitigated queue extension by proactively slowing down approaching traffic.

Conclusions:

  • SWSCAV is a promising, effective traffic management strategy leveraging CAV capabilities.
  • The system significantly reduces traffic density and improves flow stability around incidents.
  • SWSCAV offers superior performance over existing methods, particularly in scenarios with limited CAV adoption.