Term 232

Traffic Flow Optimization Using Deep Reinforcement Learning Enabled Traffic Lights Network

Project Type: Self-Initiated

Project Description

Urban traffic congestion increases delays, fuel use, and emissions due to outdated traffic management systems that cannot adapt to real-time conditions. This inefficiency underscores the urgent need for an intelligent traffic light system that dynamically optimizes flow and reduces congestion.


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Project Team

Abdulhadi Ibrahim Zubailah
Abdulhadi Ibrahim Zubailah
Computer Science
Tariq Mousa Madkhali
Tariq Mousa Madkhali
Computer Science
Abdulrahman Waseem Hajjar
Abdulrahman Waseem Hajjar
Electrical Engineering
Mohammed Abdulsalam Almutlaq
Mohammed Abdulsalam Almutlaq
Modelling & Simulation
Abdulmohsen Abdulaziz Aleisa
Abdulmohsen Abdulaziz Aleisa
Industrial & Systems Engg.
Abdulrahman Saad Alajlan
Abdulrahman Saad Alajlan
Industrial & Systems Engg.

Team Coach

DR. Yasser Almoghathawi
DR. Yasser Almoghathawi
Assistant Professor

Industrial & Sys. Engineering Dept.

Interdisciplinary Research Center for Smart Mobility and Logistics