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Article

INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications

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Center for Sustainable Mobility, Virginia Tech Transportation Institute, Virginia Tech, Blacksburg, VA 24061, USA
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College of Computing and Information Technology, Arab Academy for Science, Technology, and Maritime Transport, Alexandria 21500, Egypt
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The Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061, USA
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The Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA 24061, USA
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Electrical Engineering, Sohag University, New Sohag, Sohag 82511, Egypt
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Ford Motor Company, Dearborn, MI 48126, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Michail Makridis
Sensors 2021, 21(6), 2127; https://doi.org/10.3390/s21062127
Received: 22 February 2021 / Revised: 15 March 2021 / Accepted: 16 March 2021 / Published: 18 March 2021
(This article belongs to the Special Issue Sensing the Future of Intelligent Transportation Systems)
The transportation system has evolved into a complex cyber-physical system with the introduction of wireless communication and the emergence of connected travelers and connected automated vehicles. Such applications create an urgent need to develop high-fidelity transportation modeling tools that capture the mutual interaction of the communication and transportation systems. This paper addresses this need by developing a high-fidelity, large-scale dynamic and integrated traffic and direct cellullar vehicle-to-vehicle and vehicle-to-infrastructure (collectively known as V2X) modeling tool. The unique contributions of this work are (1) we developed a scalable implementation of the analytical communication model that captures packet movement at the millisecond level; (2) we coupled the communication and traffic simulation models in real-time to develop a fully integrated dynamic connected vehicle modeling tool; and (3) we developed scalable approaches that adjust the frequency of model coupling depending on the number of concurrent vehicles in the network. The proposed scalable modeling framework is demonstrated by running on the Los Angeles downtown network considering the morning peak hour traffic demand (145,000 vehicles), running faster than real-time on a regular personal computer (1.5 h to run 1.86 h of simulation time). Spatiotemporal estimates of packet delivery ratios for downtown Los Angeles are presented. This novel modeling framework provides a breakthrough in the development of urgently needed tools for large-scale testing of direct (C-V2X) enabled applications. View Full-Text
Keywords: connected vehicles; C-V2X; V2V; INTEGRATION software; traffic simulation; communication modeling connected vehicles; C-V2X; V2V; INTEGRATION software; traffic simulation; communication modeling
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MDPI and ACS Style

Farag, M.M.G.; Rakha, H.A.; Mazied, E.A.; Rao, J. INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications. Sensors 2021, 21, 2127. https://doi.org/10.3390/s21062127

AMA Style

Farag MMG, Rakha HA, Mazied EA, Rao J. INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications. Sensors. 2021; 21(6):2127. https://doi.org/10.3390/s21062127

Chicago/Turabian Style

Farag, Mohamed M.G., Hesham A. Rakha, Emadeldin A. Mazied, and Jayanthi Rao. 2021. "INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications" Sensors 21, no. 6: 2127. https://doi.org/10.3390/s21062127

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