Committee Chair
Sartipi, Mina
Committee Member
Liang, Yu; Sun, Pengyuan
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
In this thesis, we address urban traffic congestion, which imposes substantial economic and environmental costs while traditional infrastructure solutions remain increasingly infeasible due to financial constraints and induced demand. We develop a dynamic Mixed-Integer Linear Programming (MILP) framework for coordinated arterial signal optimization. Our contributions include a unified optimization model that jointly determines cycle length, phase sequencing, green-time allocation, and offset synchronization. We also introduce demand-responsive bounds adapting to real-time traffic conditions and a rolling-horizon execution strategy enabling continuous adaptation. The methodological pipeline integrates three modules: detector-based demand aggregation from VISSIM microsimulation, MILP optimization using Gurobi with operational constraints, and closed-loop signal control through COM interface. We validated the framework on a hypothetical three-intersection corridor and the Martin Luther King Boulevard in Chattanooga, Tennessee, demonstrating measurable improvements in speed, Vehicle Hours Traveled, and vehicle stops. Future work includes scaling to larger networks, incorporating pedestrian phases, and integrating connected vehicle data.
Acknowledgments
I would like to firstly express my heartfelt love, gratitude, and appreciation to my parents, who hold a great place in my heart. I miss them dearly, and their constant support and guidance throughout my life, they are the source of my strength and passion. I am also thankful to sisters and brother for their ongoing support no matter the sacrifice, they played a major part in where I am today. I extend my gratitude to Dr. Mina Sartipi, my supervisor, for the constant support and believing in me, and her continuous guidance that helped me develop both academically and personally. From the very beginning, she has been a constant source of encouragement and inspiration. A mentor I aspire to become like one day. I am also thankful to Dr. Pengyuan Sun for his on going guidance throughout my research and work, and to Dr. Yu Liang, for his valuable comments and continuous assistance, were valuable which made a the path ahead clearer and more simple, as well as to my colleagues in CUIP for their contributions in enhancing my academic experience and path. During these challenging times, my heart is with Sudan, my beloved homeland, as it endures the hardships of war. I pray for peace, for the safe return of its people, and for the day when our land once again knows safety and calm. My thoughts also extend to all people around the world who are suffering from war and displacement. May peace, justice, and dignity prevail everywhere. I owe a great deal of gratitude to my roommate, who have become more than just a friend, but like a brother. I’m also thankful and grateful for the Sudanese community who built a strong homey feeling while also being so far away from. Thanks to my friends also back in Saudi Arabia for their constant support and moments we shared, those are the people that shaped who I am today. I look forward to whats to come, and the future holds.
Degree
M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.
Date
12-2025
Subject
Intelligent transportation systems; Linear programming; Traffic signs and signals--Control systems--Automation
Document Type
Masters theses
DCMI Type
Text
Extent
viii, 48 leaves
Language
English
Rights
http://rightsstatements.org/vocab/InC/1.0/
License
http://creativecommons.org/licenses/by/4.0/
Date Available
1-1-2027
Recommended Citation
Elhag, Firas, "A mixed-integer linear programming (MILP) model for dynamic coordinated signal optimization along a traffic corridor" (2025). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/1041
Department
Dept. of Computer Science and Engineering