9 citations · 36 across the 22 of their papers we have counts for
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Non-Stationary Time Series Model for Station Based Subway Ridership During Covid-19 Pandemic (Case Study: New York City)
Bahman Moghimi, Camille Kamga, Abolfazl Safikhani +2
The COVID-19 pandemic in 2020 has caused sudden shocks in transportation systems, specifically the subway ridership patterns in New York City. Understanding the temporal pattern of…
Hybrid Modeling of Regional COVID-19 Transmission Dynamics in the U.S
Yue Bai, Abolfazl Safikhani, George Michailidis
The fast transmission rate of COVID-19 worldwide has made this virus the most important challenge of year 2020. Many mitigation policies have been imposed by the governments at dif…
Predicting Short-Term Uber Demand Using Spatio-Temporal Modeling: A New York City Case Study
Sabiheh Sadat Faghih, Abolfazl Safikhani, Bahman Moghimi +1
The demand for e-hailing services is growing rapidly, especially in large cities. Uber is the first and popular e-hailing company in the United Stated and New York City. A comparis…
Short-Term Prediction of Signal Cycle in Actuated-Controlled Corridor Using Sparse Time Series Models
Bahman Moghimi, Abolfazl Safikhani, Camille Kamga +2
Traffic signals as part of intelligent transportation systems can play a significant role toward making cities smart. Conventionally, most traffic lights are designed with fixed-ti…
Spatio-temporal Modeling of Yellow Taxi Demands in New York City Using Generalized STAR Models
Abolfazl Safikhani, Camille Kamga, Sandeep Mudigonda +2
A highly dynamic urban space in a metropolis such as New York City, the spatio-temporal variation in demand for transportation, particularly taxis, is impacted by various factors s…