From gridlock to green lights: ΢ÃÜȦ student researcher uses AI to smooth traffic
“Growing up in Dhaka, Bangladesh, I’ve been stuck in traffic a gazillion times,� says Azizul Hakim ’26. “So when the chance to spend my summer improving traffic lights came up, I jumped at it without second thoughts.�
Azizul is a computer science major at ΢ÃÜȦ and a computer engineering student through the College’s 2-1-1-1 engineering program with Dartmouth College.
As part of ΢ÃÜȦ's Summer Faculty Student Research Program, he worked with Assistant
Professor of Computer Science Wenlu Du to . His simulations showed that AI-powered signals can significantly outperform traditional
systems — offering a glimpse into a future where commutes are shorter and streets
flow more smoothly, both in the U.S. and back home.
A traffic simulation that Azizul used as part of his research.
Q: Can you give a quick summary of your research project?
We applied state-of-the-art deep reinforcement learning algorithms — PPO, DQN, and
QL — to optimize traffic signal timing at North Broadway in Saratoga Springs. Using
a traffic simulator, we generated realistic traffic demand and trained agents to control
signal phases. Our results showed that these reinforcement learned-based controllers
outperformed the current fixed-time traffic light settings, reducing delays and improving
flow.
Q: How does this project tie into your major or future goals?
As a computer science major, there are multiple career paths open to us after graduation. Machine learning is one of them. People often think of ChatGPT when they hear “machine learning� these days, but machine learning research has been going on for years and has many other real-world applications. This project gave me a strong introduction to machine learning techniques and workflows — skills that will be valuable whether I pursue a role in industry or continue to graduate study.
Q: What drew you to this research opportunity?
I grew up in Dhaka, Bangladesh, where severe congestion is often managed manually by traffic officers rather than by traffic signals. I was motivated to learn how intelligent traffic systems work here, with the hope of applying similar solutions back home someday.
Q: What’s your working relationship been like with your faculty mentor?
Professor Du was very involved and supportive — more of a mentor than a distant supervisor. She encouraged us to choose our own research questions and guided us throughout the process. Outside of work, she made meetings enjoyable; we often played Nintendo Switch or VR games and shared snacks.
Q: What’s one really cool thing you’ve learned or are still figuring out?
I’m fascinated by how neural networks and reinforcement learning algorithms can quickly learn efficient strategies for complex, real-world problems. The blend of theoretical design and practical performance in AI is especially impressive.
Q: What role does creativity or innovation play in your work?
Creativity was essential to building a realistic, safe simulation. I had to design signal-phase controls that were effective but not erratic, and ensure the system behaved reliably under varied traffic conditions. Balancing realism, safety, and performance required innovative thinking.
Q: How has this experience shaped your thinking about post-grad plans?
Before this project, I was set on going straight into industry. After this positive
research experience, I’m now open to graduate school if I find a compelling project
in a similar area.
Q: What’s unique about doing this kind of project at ΢ÃÜȦ?
Machine learning is rapidly growing, and ΢ÃÜȦ now has faculty expertise in the area. That makes it an excellent place for computer science students to take machine learning courses and participate in hands-on research opportunities that have real-world impact.
Q: What else are you involved in at ΢ÃÜȦ outside of this project?
I will serve as co-president for both ΢ÃÜȦ Codes, a computer science-oriented club, and the Muslim Students Association this fall. I’m involved with Hayat, a club celebrating South Asian cultures, and the International Student Union. I will also be a peer mentor for a first-year Scribner Seminar taught by Associate Professor of Computer Science Aarathi Prasad.