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This research paper introduces a cutting-edge fog computing system to enhance autonomous cars and smart transportation networks. Central to our framework are edge twins—distributed digital twins hosted on fog machines. Leveraging car sensor data and real-time images, edge twins update maps with precise vehicle locations. While beneficial for road space distribution, resolving communication lags remains a challenge. Our research integrates a machine learning forecaster to optimize decision-making and an advanced box algorithm for dynamic danger maps. This study advances driverless cars and intelligent transportation, offering practical fog computing solutions for future transportation systems.

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Autonomous Vehicle and Smart Transportation Using Fog Computing

  • 会议论文

  • 发表日期：

    2025年

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  • Harsh,
  • Deepa Gupta,
  • Sonia Saini

摘要

This research paper introduces a cutting-edge fog computing system to enhance autonomous cars and smart transportation networks. Central to our framework are edge twins—distributed digital twins hosted on fog machines. Leveraging car sensor data and real-time images, edge twins update maps with precise vehicle locations. While beneficial for road space distribution, resolving communication lags remains a challenge. Our research integrates a machine learning forecaster to optimize decision-making and an advanced box algorithm for dynamic danger maps. This study advances driverless cars and intelligent transportation, offering practical fog computing solutions for future transportation systems.