Novel RSS based UGV tracking scheme using coverage area distribution

Accurate tracking of unmanned ground vehicles (UGVs) is essential for intelligent transportation systems (ITSs), enabling reliable traffic monitoring, navigation, and collision avoidance. Conventional received signal strength (RSS)-based methods, such as trilateration and fingerprinting, require three or more base stations (BSs), which increase infrastructure cost and computational complexity while suffering from localization ambiguity in road junctions. This paper presents a novel lightweight RSS-based UGV tracking framework that divides each BS coverage region into virtual concentric ring intervals to distinguish intersecting and non-intersecting zones. Only a single BS is required for straight-road tracking and two BSs for junctions, achieving efficient handover with minimal infrastructure. A probabilistic RSS aggregation and averaging model is incorporated to mitigate noise, multipath fading, and shadowing effects. The framework is validated through comprehensive MATLAB simulations and real-world experiments using ESP32 IoT modules operating at 2.4 GHz. Experimental results demonstrate that the proposed method achieves an average tracking error reduction of 29.50% (with average relative tracking accuracy 85.10%) and a handover delay reduction of 42.93% compared with state-of-the-art RSS-based schemes, while maintaining energy-efficient operation (average power consumption 0.25 W). These outcomes confirm that the proposed design offers a scalable, low-cost, and robust solution for next-generation ITS and cooperative UGV tracking applications.