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03/20/2023
Deep trip generation with graph neural networks for bike sharing system expansion
Bike sharing is emerging globally as an active, convenient, and sustaina...
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12/31/2022
Adapting Node-Place Model to Predict and Monitor COVID-19 Footprints and Transmission Risks
The node-place model has been widely used to classify and evaluate trans...
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11/16/2022
Cross-Mode Knowledge Adaptation for Bike Sharing Demand Prediction using Domain-Adversarial Graph Neural Networks
For bike sharing systems, demand prediction is crucial to ensure the tim...
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10/14/2022
HGARN: Hierarchical Graph Attention Recurrent Network for Human Mobility Prediction
Human mobility prediction is a fundamental task essential for various ap...
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06/18/2022
Deep Inverse Reinforcement Learning for Route Choice Modeling
Route choice modeling, i.e., the process of estimating the likely path t...
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03/18/2022
Bike Sharing Demand Prediction based on Knowledge Sharing across Modes: A Graph-based Deep Learning Approach
Bike sharing is an increasingly popular part of urban transportation sys...
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12/15/2021
Joint Demand Prediction for Multimodal Systems: A Multi-task Multi-relational Spatiotemporal Graph Neural Network Approach
Dynamic demand prediction is crucial for the efficient operation and man...
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09/17/2021
Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic Data Imputation with Complex Missing Patterns
Missing data is an inevitable and ubiquitous problem for traffic data co...
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06/24/2021
Identifying Hidden Visits from Sparse Call Detail Record Data
Despite a large body of literature on trip inference using call detail r...
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06/21/2021
Vehicle Trajectory Prediction in City-scale Road Networks using a Direction-based Sequence-to-Sequence Model with Spatiotemporal Attention Mechanisms
Trajectory prediction of vehicles at the city scale is of great importan...
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01/11/2021