How will SUNY Poly make our roads safer? New lab will use virtual reality, AI in research

Can technological breakthroughs in fields like artificial intelligence and virtual reality be used to help make traveling from place to place easier and safer?  

SUNY Polytechnic Institute in Marcy is on it. It has a new Transportation Research AI (artificial intelligence) Lab, or TRAIL, in Donovan Hall for education and research into how to make transportation better.  

Projects might help to change the timing of traffic lights so that fewer drivers run red lights, find the most dangerous spots for driving so a town can prioritize improvements or improve safety in work zones by studying driver behavior. 

"Our research team is at the forefront of pioneering advancements, utilizing data-driven AI and machine learning solutions to address transportation challenges in four key areas: operation, safety, sustainability, and resiliency," said Abolfazi Karimpour, assistant professor of transportation engineering. "TRAIL focuses on research, education, and workforce development initiatives. Students using TRAIL are supported by these funded projects, gaining hands-on experience in transportation analysis, data analysis, and how to apply this knowledge to benefit the public." 

About the lab

Karimpour founded the lab using a combination of grants from within and outside SUNY Poly. 

More: Another step forward: SUNY Poly hires permanent provost

More: SUNY appoints first SUNY Poly president since Kaloyeros stepped down 7 years ago

The lab will be used for both education — classes, independent study, capstone projects — and research. It's equipped with strong computing systems and transportation software with access to statewide traffic data. Over the summer, emerging technologies for collecting data, such as unmanned aerial vehicles and virtual reality sets will be added.  

Karimpour described some of the projects taking place in the lab:  

• Optimizing the timing of traffic lights in an area and helping traffic to flow more efficiently. 

• Using data-driven studies to time traffic lights to lower the number of vehicles running red lights. 

• Use machine learning modeling to determine the factors that lead people to make public transportation decisions. A machine learning model finds patterns and makes decisions based on a previously unseen data set. (Facial recognition software is based on it.) This application would look at the behavior of people using so-called micromobility, such as electric scooters and bicycles. 

• Developing interactive platforms so departments of transportation can monitor congestion on local roadways.  

• Improving safety in work zones by using virtual reality to understand how drivers behave. 

• Looking for disparities in the location of emerging modes of transportation and their accessibility.  

Michael Carpenter, interim dean of the College of Engineering and associate provost for research at SUNY Poly, commended Karimpour for establishing such a tremendous resource.  

"TRAIL will enhance transportation systems' efficiency, safety, and resilience," he said, "and position SUNY Poly as leaders in the field, driving forward innovative solutions for the future of transportation."  

This article originally appeared on Observer-Dispatch: SUNY Poly opens new Transportation Research AI Lab