UAV Surveillance Augmentation for Real-Time Road Condition Analysis and Autonomous Control under Restricted Communication

Abstract

The integration of Unmanned Aerial Vehicles (UAVs) into traffic monitoring systems has the potential to revolutionize real-time road condition analysis and autonomous vehicular control, particularly in areas where traditional communication networks are unreliable. This paper explores a novel framework for augmenting UAV-based surveillance to support enhanced data acquisition and processing under restricted communication environments. Key contributions include a multi-modal sensor suite for UAVs, an edge-computing pipeline for processing real-time road conditions, and an adaptive communication protocol for intermittent data transfer to ground stations and vehicles. The proposed system is designed to address challenges in latency, bandwidth constraints, and energy efficiency. Simulated and real-world experiments demonstrate that the UAV system can achieve low-latency analysis while maintaining accurate road condition monitoring in various scenarios, including adverse weather and dynamic traffic. Results show significant improvements in autonomous vehicle control decisions, even with limited connectivity. This paper highlights the implications of UAV-supported traffic systems on safety, efficiency, and sustainability in smart cities.