Open Access

ARTICLE

3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Dun Cao¹, Jia Ru¹, Jian Qin¹, Amr Tolba², Jin Wang¹, Min Zhu^3,*

1 College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410114, China
2 Department of Computer Science, Community College, King Saud University, Riyadh, 11437, Saudi Arabia
3 College of Information Science and Technology, Zhejiang Shuren University, Hangzhou, 310015, China

* Corresponding Author: Min Zhu. Email:

(This article belongs to the Special Issue: Computer Modelling for Safer Built Environment and Smart Cities)

Computer Modeling in Engineering & Sciences 2024, 138(2), 1365-1384. https://doi.org/10.32604/cmes.2023.030260

Received 28 March 2023; Accepted 18 August 2023; Issue published 17 November 2023

Abstract

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles, people, transportation infrastructure, and networks, thereby realizing a more intelligent and efficient transportation system. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topological structure of IoV to have the high space and time complexity. Network modeling and structure recognition for 3D roads can benefit the description of topological changes for IoV. This paper proposes a 3D general road model based on discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles are analyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed and acceleration are studied. Finally, a general 3D road network model based on road section features is established. This paper also presents intersection and road section recognition methods based on the structural features of the 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted to create the simulation scenario, and the simulation results validate the general 3D road network model and the recognition method. Therefore, this work makes contributions to the field of intelligent transportation by providing a comprehensive approach to modeling the 3D road network and its topological changes in achieving efficient traffic flow and improved road safety.

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Keywords

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