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In recent years, Unmanned Aerial Vehicles (UAVs) have emerged as effective tools for traffic monitoring and control by offering high-resolution, aerial observations of vehicular movement. Although UAV simulation is well established, tools to capture microscopic traffic measurements from UAV-based observations remain limited. This paper introduces SUAVPy, an open-source SUMO plugin that integrates UAV-based sensing into microscopic traffic simulations in Python. SUAVPy captures detailed vehicle observations by dynamically employing multiple UAVs to observe traffic measurements based on their position and field-of-view. Performance evaluations on a mid-sized network demonstrate that SUAVPy maintains simulation performance comparable to standard post-processing methods, confirming its suitability for large-scale traffic monitoring research.

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Title: SUMO-UAV-Py: A SUMO Plugin For UAV-Based Road Traffic Sensing

Presenter: Charalambos Tsioutis

Authors: Charalambos Tsioutis, Christos Makridis and Stelios Timotheou