Cross-Area Travel Time Uncertainty Estimation From Trajectory Data: A Federated Learning Approach

Along with urbanization and the deployment of GPS sensors in vehicles and mobile phones, massive amounts of trajectory data have been generated for city areas. The analysis of these data has substantially contributed to research and advancements of travel time estimation. However, existing work focu...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2022-12, Vol.23 (12), p.24966-24978
Hauptverfasser:	Zhu, Yuanshao, Ye, Yongchao, Liu, Yi, Yu, James J. Q.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian deep learning Collaborative work Data exchange Data models Deep learning Estimation Federated learning Global Positioning System Machine learning Neural networks Privacy privacy-preserving Trajectory Trajectory analysis trajectory analytics Travel time Travel time estimation Uncertainty Urbanization User requirements
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