34 citations · 53 across the 14 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CY2021★ 3 cited
Real-Time Forecasting of Dockless Scooter-Sharing Demand: A Spatio-Temporal Multi-Graph Transformer Approach
Yiming Xu, Xilei Zhao, Xiaojian Zhang +1
Accurately forecasting the real-time travel demand for dockless scooter-sharing is crucial for the planning and operations of transportation systems. Deep learning models provide r…
cs.LG2021★ 1 cited
A Clustering-aided Ensemble Method for Predicting Ridesourcing Demand in Chicago
Xiaojian Zhang, Xilei Zhao
Accurately forecasting ridesourcing demand is important for effective transportation planning and policy-making. With the rise of Artificial Intelligence (AI), researchers have sta…
cs.CY2021★ 3 cited
Do e-scooters fill mobility gaps and promote equity before and during COVID-19? A spatiotemporal analysis using open big data
Xiang Yan, Wencui Yang, Xiaojian Zhang +3
The growing popularity of e-scooters and their rapid expansion across urban streets has attracted widespread attention. A major policy question is whether e-scooters substitute exi…