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Building Personalized Transportation Model for Online Taxi-Hailing Demand Prediction | IEEE Journals & Magazine | IEEE Xplore

Building Personalized Transportation Model for Online Taxi-Hailing Demand Prediction


Abstract:

The accurate prediction of online taxi-hailing demand is challenging but of significant value in the development of the intelligent transportation system. This article fo...Show More

Abstract:

The accurate prediction of online taxi-hailing demand is challenging but of significant value in the development of the intelligent transportation system. This article focuses on large-scale online taxi-hailing demand prediction and proposes a personalized demand prediction model. A model with two attention blocks is proposed to capture both spatial and temporal perspectives. We also explored the impact of network architecture on taxi-hailing demand prediction accuracy. The proposed method is universal in the sense that it is applicable to problems associated with large-scale spatiotemporal prediction. The experimental results on city-wide online taxi-hailing demand dataset demonstrate that the proposed personalized demand prediction model achieves superior prediction accuracy.
Published in: IEEE Transactions on Cybernetics ( Volume: 51, Issue: 9, September 2021)
Page(s): 4602 - 4610
Date of Publication: 06 July 2020

ISSN Information:

PubMed ID: 32628608

Funding Agency:


References

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