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| DOI | 10.1109/ACCESS.2025.3576726 | ||
| Año | 2025 | ||
| Tipo |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
The widespread adoption of cellular networks has played an important role in the integration of road safety applications, capitalizing on the ubiquitous use of this technology by road users and its extensive market penetration. This paper introduces an analytical model to evaluate the Vulnerable Road User (VRU) Awareness Probability (VAP)—the likelihood that vehicles can detect VRUs via 5G New Radio (NR) cellular vehicle-to-everything (C-V2X) communication at urban intersections. The model assumes full VRU connectivity to the 5G network and simulates 5G NR operating in communication mode 2, incorporating realistic urban mobility patterns (via SUMO traces) and signal propagation effects, including building-induced obstructions. Results demonstrate high model accuracy, with Root Mean Square Error (RMSE) values of 0.0265 in partially obstructed and 0.0309 in highly obstructed scenarios, using the non-obstructed case as a baseline. This model provides a robust framework for assessing the impact of C-V2X-based safety applications on VRU protection across varying traffic densities, network conditions, and deployment architectures.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Yanez, Alexis | Hombre |
Concordia University - Canadá
Universidad de Chile - Chile |
| 2 | Salas, Felipe | - | |
| 3 | Azurdia-Meza, Cesar A. | - |
Universidad de Chile - Chile
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| 4 | Ignacio Sandoval, Jorge | - |
Universidad de Chile - Chile
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| 5 | CESPEDES-UMANA, SANDRA LORENA | Mujer |
Concordia University - Canadá
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| Fuente |
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| Comisión Nacional de Investigación Científica y Tecnológica |
| Natural Sciences and Engineering Research Council of Canada |
| Agencia Nacional de Investigación y Desarrollo |
| Agradecimiento |
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| This work was supported in part by CONICYT Chile under grant CONICYT-PFCHA/Doctorado Nacional/2020-21201428, in part by ANID under Grant Basal Project AFB240002, and in part by Natural Sciences and Engineering Research Council of Canada (NSERC), Discover Grant RGPIN-2024-05730. |