Publications

@inproceedings{ma_metaverses_2024,

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

author = {H. Ma and X. Yao and X. Wang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214916181&doi=10.1109%2fDTPI61353.2024.10778876&partnerID=40&md5=94a6bf4b06a2a45f7c483936beee840f},

doi = {10.1109/DTPI61353.2024.10778876},

isbn = {979-835034925-2 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Proc. - IEEE Int. Conf. Digit. Twins Parallel Intell., DTPI},

pages = {598–603},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

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. © 2024 IEEE.},

keywords = {Advanced traffic management systems, Data fusion, generative artificial intelligence, Highway administration, Information Management, Intelligent transportation systems, Interactive Intelligent Transportation System, Metaverses, Mixed Traffic, Parallel Traffic System, Social Diversity and Uncertainty, Traffic control, Traffic Metaverse, Traffic systems, Uncertainty, Virtual addresses, Virtual environments},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{liang_construction_2024,

title = {Construction of Emergency Rescue Virtual Exercise Platform Based on AIGC Perspective},

author = {J. Liang and X. Li},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206094403&doi=10.1145%2f3686424.3686477&partnerID=40&md5=e32351dc68be5d0fa0d771656b02256f},

doi = {10.1145/3686424.3686477},

isbn = {979-840071036-0 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {ACM Int. Conf. Proc. Ser.},

pages = {312–316},

publisher = {Association for Computing Machinery},

abstract = {In order to address the suddenness of emergency events and the phenomenon that the rescue process contains too many behavioural uncertainties, an emergency rescue virtual exercise platform framework has been designed from the perspective of generative artificial intelligence (AIGC). This framework analyses human behaviour during the simulated emergency rescue process and collects relevant data. The module function is determined by the parallel emergency management method. The system comprises three data processing modules: the behavioural input module, the emergency event feedback module, and the data classification and processing module. The logic of AI data processing is employed to establish a data cycle evolution system, which assists rescue personnel in enhancing their professional abilities, increasing the success rate of rescue operations, and optimising the role of AI technology and computer simulation methodology in the design of the practice. © 2024 Copyright held by the owner/author(s).},

keywords = {Artificial intelligence, Behavioral theory, Data handling, Data Processing, Emergency events, Emergency management, Emergency rescue, Emergency Response, Human behaviors, Processing modules, Rescue process, Risk management, Uncertainty, Virtual environments, Virtual exercise, Virtual Exercises, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}