The future of Connected and Automated Driving (CAD) depends on resilient, ubiquitous connectivity, and Low-Earth-Orbit (LEO) satellite links are a key ingredient to achieve it. We introduce an analytical model specifically designed to predict Line-of-Sight (LoS) visibility for LEO satellite constellations from a vehicle’s perspective. Moving beyond slow, data-heavy 3D simulations, our model uses street orientation and building heights to calculate exactly how many satellites a vehicle can ”see” in average, given a certain onstellation. The model was validated against realistic simulation results using the OMNeT++/Veins simulator. It achieves sub-1% error rates, providing a powerful, lightweight engine for optimizing V2X reliability and coverage planning in urban environments.

From the Sky to the Canyons: Estimating the Visibility of LEO Satellites in Urban Environments

Leonardo Maccari
2026

Abstract

The future of Connected and Automated Driving (CAD) depends on resilient, ubiquitous connectivity, and Low-Earth-Orbit (LEO) satellite links are a key ingredient to achieve it. We introduce an analytical model specifically designed to predict Line-of-Sight (LoS) visibility for LEO satellite constellations from a vehicle’s perspective. Moving beyond slow, data-heavy 3D simulations, our model uses street orientation and building heights to calculate exactly how many satellites a vehicle can ”see” in average, given a certain onstellation. The model was validated against realistic simulation results using the OMNeT++/Veins simulator. It achieves sub-1% error rates, providing a powerful, lightweight engine for optimizing V2X reliability and coverage planning in urban environments.
2026
Proceedings of IEEE Vehicular Networking Conference
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5117167
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