111 citations · 469 across the 13 of their papers we have counts for
5 papers · 1 filter
Joint Demand Prediction for Multimodal Systems: A Multi-task Multi-relational Spatiotemporal Graph Neural Network Approach
Yuebing Liang, Guan Huang, Zhan Zhao
Dynamic demand prediction is crucial for the efficient operation and management of urban transportation systems. Extensive research has been conducted on single-mode demand predict…
Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic Data Imputation with Complex Missing Patterns
Yuebing Liang, Zhan Zhao, Lijun Sun
Missing data is an inevitable and ubiquitous problem for traffic data collection in intelligent transportation systems. Despite extensive research regarding traffic data imputation…
Identifying Hidden Visits from Sparse Call Detail Record Data
Zhan Zhao, Haris N. Koutsopoulos, Jinhua Zhao
Despite a large body of literature on trip inference using call detail record (CDR) data, a fundamental understanding of their limitations is lacking. In particular, because of the…
NetTraj: A Network-based Vehicle Trajectory Prediction Model with Directional Representation and Spatiotemporal Attention Mechanisms
Yuebing Liang, Zhan Zhao
Trajectory prediction of vehicles in city-scale road networks is of great importance to various location-based applications such as vehicle navigation, traffic management, and loca…
Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
Baichuan Mo, Zhan Zhao, Haris N. Koutsopoulos +1
Individual mobility is driven by demand for activities with diverse spatiotemporal patterns, but existing methods for mobility prediction often overlook the underlying activity pat…