1 citations · 1 across the 2 of their papers we have counts for
5 papers
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…
Simultaneous Optimization of Signal Timing and Capacity Improvement in Urban Transportation Networks Using Simulated Annealing
Bahman Moghimi, Navid Kalantari, Camille Kamga +1
Capacity expansions as well as its reduction have been widely anticipated as important countermeasures for traffic congestion. Although capacity expansion had been traditionally we…
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…