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arXiv · 2301.05293

HTTE: A Hybrid Technique For Travel Time Estimation In Sparse Data Environments

Nikolaos Zygouras·Nikolaos Panagiotou·Yang Li·Dimitrios Gunopulos·Leonidas Guibas
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Abstract

Travel time estimation is a critical task, useful to many urban applications at the individual citizen and the stakeholder level. This paper presents a novel hybrid algorithm for travel time estimation that leverages historical and sparse real-time trajectory data. Given a path and a departure time we estimate the travel time taking into account the historical information, the real-time trajectory data and the correlations among different road segments. We detect similar road segments using historical trajectories, and use a latent representation to model the similarities. Our experimental evaluation demonstrates the effectiveness of our approach.

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Nikolaos Zygouras, Nikolaos Panagiotou, Yang Li, Dimitrios Gunopulos, Leonidas Guibas. 2023-01-12. HTTE: A Hybrid Technique For Travel Time Estimation In Sparse Data Environments. https://doi.org/10.1145/3347146.3359096

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