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<p>Intelligent Transportation Systems (ITS) and Vehicle Ad Hoc Networks (VANETs) are expected to significantly improve urban mobility and public safety by enabling efficient communication, real-time data exchange, and coordinated traffic management. However, challenges such as unreliable infrastructure, communication disruptions between vehicles, and limited data throughput impede Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. Unmanned Aerial Vehicles (UAVs) can help address these issues by acting as dynamic communication relays in areas that lack adequate infrastructure. Investigating UAV mobility patterns within VANETs is essential to ensure optimal utilization and cost efficiency. This paper introduces a novel State-Based UAV Mobility (SBUM) model to manage UAV movements for communication coverage in VANETs. The primary objective of the proposed approach is improving vehicular connectivity while minimizing the required UAVs, and reducing deployment costs. Traditional methods often rely on the fixed or random positioning of UAVs, leading to inefficient coverage and high costs. In contrast, the SBUM model dynamically adjusts UAV positioning based on the status of neighboring UAVs, achieving high performance with fewer UAVs and reduced costs. The results show substantial improvements in Packet Delivery Ratio (PDR) and throughput, along with reductions in Uncovered Vehicle Duration (UVD) and Maximum Vehicle Disconnection Time (MVDT) compared to fixed and random UAV positioning approaches. Achieving results comparable to the SBUM model would require doubling the number of UAVs deployed in both stationary and random deployment strategies.</p>

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A state machine-based mobility model for UAVs supporting VANETs

  • 期刊论文

  • 发表日期：

    2025年7月7日

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  • Leila Bouchrit,
  • Sajeh Zairi,
  • Ikbal C. Msadaa,
  • Amine Dhraief

摘要

Intelligent Transportation Systems (ITS) and Vehicle Ad Hoc Networks (VANETs) are expected to significantly improve urban mobility and public safety by enabling efficient communication, real-time data exchange, and coordinated traffic management. However, challenges such as unreliable infrastructure, communication disruptions between vehicles, and limited data throughput impede Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. Unmanned Aerial Vehicles (UAVs) can help address these issues by acting as dynamic communication relays in areas that lack adequate infrastructure. Investigating UAV mobility patterns within VANETs is essential to ensure optimal utilization and cost efficiency. This paper introduces a novel State-Based UAV Mobility (SBUM) model to manage UAV movements for communication coverage in VANETs. The primary objective of the proposed approach is improving vehicular connectivity while minimizing the required UAVs, and reducing deployment costs. Traditional methods often rely on the fixed or random positioning of UAVs, leading to inefficient coverage and high costs. In contrast, the SBUM model dynamically adjusts UAV positioning based on the status of neighboring UAVs, achieving high performance with fewer UAVs and reduced costs. The results show substantial improvements in Packet Delivery Ratio (PDR) and throughput, along with reductions in Uncovered Vehicle Duration (UVD) and Maximum Vehicle Disconnection Time (MVDT) compared to fixed and random UAV positioning approaches. Achieving results comparable to the SBUM model would require doubling the number of UAVs deployed in both stationary and random deployment strategies.