Metaverses for Parallel Transportation: From General 3D Traffic Environment Construction to Virtual-Real I<sup>2</sup>TS Management and Control

Metaverse technologies have enabled the creation of highly realistic artificial traffic system via real-time multi-source data fusion, while generative artificial intelligence (GAI) has facilitated the construction of large-scale traffic scenarios and the evaluation of strategies. This integration allows for the modeling of traffic environments that blend virtual and real-world interactions, providing digital proving grounds for the management and control (M&C) of intelligent transportation systems (ITS). This paper comprehensively reviews the evolution of traffic modeling tools, from traditional 2D and 3D traffic simulations to the construction of generative 3D traffic environments based on digital twin (DT) technologies and the metaverse. Furthermore, to address the challenges posed by social diversity and uncertainty in mixed traffic, as well as the limitations of traditional methods, we propose a virtual-real interaction M&C strategy based on GAI. This strategy integrates the metaverse into parallel traffic systems (PTS), enabling bidirectional interaction and collaboration between virtual and physical environments. Through specific case studies, this research demonstrates the potential of combining the metaverse with PTS to enhance the efficiency of mixed traffic systems.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/dtpi61353.2024.10778876
Primary Topic
Simulation and Modeling Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Metaverses for Parallel Transportation: From General 3D Traffic Environment Construction to Virtual-Real I2TS Management and Control

Xiao Wang, Hao Ma, Xiaoyue Yao
Simulation and Modeling Applications
article

Metaverses for Parallel Transportation: From General 3D Traffic Environment Construction to Virtual-Real I2TS Management and Control

Xiao Wang, Hao Ma, Xiaoyue Yao
article en

Abstract

Metaverse technologies have enabled the creation of highly realistic artificial traffic system via real-time multi-source data fusion, while generative artificial intelligence (GAI) has facilitated the construction of large-scale traffic scenarios and the evaluation of strategies. This integration allows for the modeling of traffic environments that blend virtual and real-world interactions, providing digital proving grounds for the management and control (M&C) of intelligent transportation systems (ITS). This paper comprehensively reviews the evolution of traffic modeling tools, from traditional 2D and 3D traffic simulations to the construction of generative 3D traffic environments based on digital twin (DT) technologies and the metaverse. Furthermore, to address the challenges posed by social diversity and uncertainty in mixed traffic, as well as the limitations of traditional methods, we propose a virtual-real interaction M&C strategy based on GAI. This strategy integrates the metaverse into parallel traffic systems (PTS), enabling bidirectional interaction and collaboration between virtual and physical environments. Through specific case studies, this research demonstrates the potential of combining the metaverse with PTS to enhance the efficiency of mixed traffic systems.

Anhui University (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 73%
Simulation and Modeling Applications
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