Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness
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 Roa...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11023842/ |
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| author | Alexis Yanez Felipe Salas Cesar A. Azurdia-Meza Jorge Ignacio Sandoval Sandra Cespedes |
| author_facet | Alexis Yanez Felipe Salas Cesar A. Azurdia-Meza Jorge Ignacio Sandoval Sandra Cespedes |
| author_sort | Alexis Yanez |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-3efd2b879d9b48eb986e116a6019eb58 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-3efd2b879d9b48eb986e116a6019eb582025-08-20T03:44:54ZengIEEEIEEE Access2169-35362025-01-0113991709918210.1109/ACCESS.2025.357672611023842Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users AwarenessAlexis Yanez0https://orcid.org/0000-0001-6987-8856Felipe Salas1https://orcid.org/0000-0001-6769-9555Cesar A. Azurdia-Meza2https://orcid.org/0000-0003-3461-4484Jorge Ignacio Sandoval3https://orcid.org/0000-0003-0179-4474Sandra Cespedes4https://orcid.org/0000-0003-1686-2644Department of Computer Science and Software Engineering, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC, CanadaBain and Company, Inc., Boston, MA, USADepartment of Electrical Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago, ChileDepartment of Electrical Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago, ChileDepartment of Computer Science and Software Engineering, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC, CanadaThe 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.https://ieeexplore.ieee.org/document/11023842/Autonomous resource allocationcellular vehicle-to-everything (C-V2X)new radio (NR)semi-persistent scheduling (SPS)vulnerable road user (VRU) |
| spellingShingle | Alexis Yanez Felipe Salas Cesar A. Azurdia-Meza Jorge Ignacio Sandoval Sandra Cespedes Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness IEEE Access Autonomous resource allocation cellular vehicle-to-everything (C-V2X) new radio (NR) semi-persistent scheduling (SPS) vulnerable road user (VRU) |
| title | Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness |
| title_full | Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness |
| title_fullStr | Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness |
| title_full_unstemmed | Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness |
| title_short | Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness |
| title_sort | enhancing urban road safety a 5g nr model for vulnerable road users awareness |
| topic | Autonomous resource allocation cellular vehicle-to-everything (C-V2X) new radio (NR) semi-persistent scheduling (SPS) vulnerable road user (VRU) |
| url | https://ieeexplore.ieee.org/document/11023842/ |
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