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The rise of cooperative vehicles presents new solutions for tackling traffic challenges, particularly in route optimization for travellers. This paper introduces two innovative modules: Secure Hybrid Authentication and Fusion Algorithm (SHAFA), which form a secure, localized route recommendation system. This work utilizes traffic data—such as vehicle speed and density—gathered from a centralized hub to inform real-time routing through Fusion Algorithm (FA). By combining genetic and heuristic methods, FA evaluates factors to deliver optimal routes to cooperative vehicles. Secure communication is ensured through the SHA framework, maintaining privacy and data integrity. Simulation results demonstrate that SHAFA consistently identifies better routes than the traditional greedy algorithms, highlighting its potential to enhance traffic flow and improve user experience.

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A Novel Framework for Route Recommendation in Cooperative Vehicle Systems: The SHAFA Model

  • 会议论文

  • 发表日期：

    2026年

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  • Manipriya Sankaranarayanan,
  • C. Mala

摘要

The rise of cooperative vehicles presents new solutions for tackling traffic challenges, particularly in route optimization for travellers. This paper introduces two innovative modules: Secure Hybrid Authentication and Fusion Algorithm (SHAFA), which form a secure, localized route recommendation system. This work utilizes traffic data—such as vehicle speed and density—gathered from a centralized hub to inform real-time routing through Fusion Algorithm (FA). By combining genetic and heuristic methods, FA evaluates factors to deliver optimal routes to cooperative vehicles. Secure communication is ensured through the SHA framework, maintaining privacy and data integrity. Simulation results demonstrate that SHAFA consistently identifies better routes than the traditional greedy algorithms, highlighting its potential to enhance traffic flow and improve user experience.