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INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications.

Mohamed M G Farag1,2, Hesham A Rakha1,3,4, Emadeldin A Mazied1,5

  • 1Center for Sustainable Mobility, Virginia Tech Transportation Institute, Virginia Tech, Blacksburg, VA 24061, USA.

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This study introduces a high-fidelity, integrated traffic and direct cellular vehicle-to-everything (V2X) modeling tool. The framework enables faster-than-real-time simulation for connected vehicle applications.

Keywords:
C-V2XINTEGRATION softwareV2Vcommunication modelingconnected vehiclestraffic simulation

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Area of Science:

  • Cyber-Physical Systems
  • Transportation Engineering
  • Wireless Communication

Background:

  • Modern transportation systems are complex cyber-physical systems integrating wireless communication.
  • Connected vehicles and travelers necessitate advanced modeling tools to understand system interactions.

Purpose of the Study:

  • To develop a high-fidelity, large-scale, dynamic, and integrated traffic and direct cellular vehicle-to-vehicle and vehicle-to-infrastructure (V2X) modeling tool.
  • To capture the intricate mutual interactions between communication and transportation systems in real-time.

Main Methods:

  • Developed a scalable implementation of an analytical communication model for millisecond-level packet movement.
  • Coupled communication and traffic simulation models in real-time for a dynamic connected vehicle tool.
  • Implemented scalable approaches to adjust model coupling frequency based on concurrent vehicle numbers.

Main Results:

  • Demonstrated a scalable modeling framework on the Los Angeles downtown network during peak hours.
  • Achieved faster-than-real-time simulation performance on a standard personal computer.
  • Provided spatiotemporal estimates of packet delivery ratios for the tested network.

Conclusions:

  • The novel modeling framework offers a breakthrough for large-scale testing of V2X-enabled applications.
  • The integrated tool provides essential capabilities for advancing connected and automated transportation systems.