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Conditional Information-Bottleneck Graph Clustering for Structured Representation Learning in Dynamic Vehicular ISAC Networks. [PDF]
Entropy (Basel)Wu Y, Zhu H.
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DeepVM: RNN-Based Vehicle Mobility Prediction to Support Intelligent Vehicle Applications
IEEE Transactions on Industrial Informatics, 2020 The recent advances in vehicle industry and vehicle-to-everything communications are creating a huge potential market of intelligent vehicle applications, and exploiting vehicle mobility is of great importance in this field.
Wei Liu, Yozo Shoji
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A Review of Mobility Metrics for Next Generation Vehicle Mobility Models
Journal of Terramechanics, 2020In the United States, the NATO Reference Mobility Model (NRMM) has been used for evaluating military ground vehicle mobility and the Vehicle Cone Index (VCI) has been selected as a mobility metric.
Paramsothy Jayakumar
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A Deep Learning-Based Mobile Crowdsensing Scheme by Predicting Vehicle Mobility
IEEE transactions on intelligent transportation systems (Print), 2021Mobile crowdsensing is an emerging paradigm that selects users to complete sensing tasks. Recently, mobile vehicles are adopted to perform sensing data collection tasks in the urban city due to their ubiquity and mobility.
Xiaoyu Zhu +4 more
semanticscholar +1 more source
Fog Computing Model and Efficient Algorithms for Directional Vehicle Mobility in Vehicular Network
IEEE transactions on intelligent transportation systems (Print), 2021Vehicular fog computing (VFC) has become an appealing paradigm to provide services for vehicles and traffic systems. However, high mobility is one of the great challenges to the communication and computation service qualities in VFC.
Yalan Wu +4 more
semanticscholar +1 more source
Social Relationship Inference Over Private Vehicle Mobility Data
IEEE Transactions on Vehicular Technology, 2021The ubiquity of private vehicles with positioning services leaves a great deal of mobility data in the physical world, which supports abundant mobile applications in the Internet of Vehicles. Despite numerous desirable features that the data provide, the
Jie Li +5 more
semanticscholar +1 more source