Amr Shafik

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Teaching Assistant

Virginia Tech

United States

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About

Amr Shafik is a Teaching Assistant at Virginia Tech, USA. His research focuses on deep learning applications in traffic signal management, including the prediction of signal timing and vehicle trajectories. Recent publications include studies on real-time traffic density estimation and optimization strategies for vehicular movements at actuated traffic signals, particularly in urban environments.

Recent Grants

Grant: Close

Last Mile Leadership Scholarship

Open Date: 2024-08-01

Close Date: 2025-03-01

Articles (5)

Year:

2025

Year:

2025

Year:

2024

Year:

2023

Year:

2022

Collaborators (1)

Hesham Rakha

Samuel Reynolds Pritchard Professor of Engineering

Virginia Tech

UNITED STATES

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Amr Shafik

Research Interests

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About

Recent Grants

Articles (5)

Deep Learning Ensemble Approach for Predicting Expected and Confidence Levels of Signal Phase and Timing Information at Actuated Traffic Signals

Real-Time Turning Movement, Queue Length, and Traffic Density Estimation and Prediction Using Vehicle Trajectory and Stationary Sensor Data

Integrated Back of Queue Estimation and Vehicle Trajectory Optimization Considering Uncertainty in Traffic Signal Timings

Optimization of Vehicle Trajectories Considering Uncertainty in Actuated Traffic Signal Timings

Development of Online Vissim Traffic Microscopic Calibration Framework Using Artificial Intelligence for Cairo CBD Area

Collaborators (1)

Hesham Rakha

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