743 citations · 762 across the 8 of their papers we have counts for
8 papers
TorchDCM: A Unified PyTorch-Native Package for Discrete Choice Modeling
Baichuan Mo, Zhengzhong Ricky You, Xiqun Michael Chen +1
Estimating large and simulation-intensive discrete choice models (DCMs) requires repeated evaluation of utilities, probabilities, derivatives, and simulated likelihoods over many o…
Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing
Wang Chen, Jintao Ke, Xiqun Chen
Despite the promising benefits that ride-sharing offers, there has been a lack of research on the benefits of high-capacity ride-sharing services. Prior research has also overlooke…
Modeling Ride-Sourcing Matching and Pickup Processes based on Additive Gaussian Process Models
Zheng Zhu, Meng Xu, Yining Di +2
Matching and pickup processes are core features of ride-sourcing services. Previous studies have adopted abundant analytical models to depict the two processes and obtain operation…
Spatial-Temporal Inference of Urban Traffic Emissions Based on Taxi Trajectories and Multi-Source Urban Data
Jielun Liu, Ke Han, Xiqun +2
Vehicle trajectory data collected via GPS-enabled devices have played increasingly important roles in estimating network-wide traffic, given their broad spatial-temporal coverage a…
PCA-Based Missing Information Imputation for Real-Time Crash Likelihood Prediction Under Imbalanced Data
Jintao Ke, Shuaichao Zhang, Hai Yang +1
The real-time crash likelihood prediction has been an important research topic. Various classifiers, such as support vector machine (SVM) and tree-based boosting algorithms, have b…
Short-Term Forecasting of Passenger Demand under On-Demand Ride Services: A Spatio-Temporal Deep Learning Approach
Jintao Ke, Hongyu Zheng, Hai Yang +2
Short-term passenger demand forecasting is of great importance to the on-demand ride service platform, which can incentivize vacant cars moving from over-supply regions to over-dem…