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Urban traffic congestion increases delays, fuel use, and emissions due to outdated traffic management systems that cannot adapt to real-time conditions.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
Computer Science
Tariq Mousa Madkhali
Computer Science
Abdulrahman Waseem Hajjar
Electrical Engineering
Mohammed Abdulsalam Almutlaq
Modelling & Simulation
Abdulmohsen Abdulaziz Aleisa
Industrial & Systems Engg.
Abdulrahman Saad Alajlan
Industrial & Systems Engg.Team Coach
DR. Yasser Almoghathawi
Assistant ProfessorIndustrial & Sys. Engineering Dept.
Interdisciplinary Research Center for Smart Mobility and Logistics