Search Results for author:
Found 4 papers, 2 papers with code
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
This paper constructs a large-scale, unified dataset of traffic accident records from official reports of various states in the US, totaling 9 million records, accompanied by road networks and traffic volume reports.
An Integrated Ride-Matching Model for Shared Mobility on Demand Services
We also propose a methodology to solve the integrated shared ride-matching problem by using supply level information based on a grid representation of the city network.
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks
Recently, spatial-temporal deep learning models demonstrate the tremendous potential to enhance prediction accuracy.
Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
Individual mobility is driven by demand for activities with diverse spatiotemporal patterns, but existing methods for mobility prediction often overlook the underlying activity patterns.
