KSU researchers to study traffic congestion, car emissions with AI

KENNESAW, Ga. — Focusing on driverless cars, lower road congestion and smaller environmental impacts, a group of Kennesaw State University researchers will be approaching a new traffic study with the help of artificial intelligence.

According to KSU, Assistant Professor Mahyar Amirgholy, from the Southern Polytechnic College of Engineering and Engineering Technology, is working on a set of research analyses to improve transportation efficiency and sustainability using advanced technology.

To do this, Amirgholy and his team are using what’s called a cooperative control of connected automated vehicles, and advanced machine learning techniques, to analyze and predict traffic and the electric consumption and emissions as the demand for electric vehicle charging grows.

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Amirgholy’s group works out of the Futra Lab and is developing a new control system that will let automated vehicles communicate with each other, and traffic lights, through a cloud computing network.

“By synchronizing their speeds while integrating with human-driven vehicles, CAVs can harmonize mixed traffic flows and align them with green lights,” KSU said. “At the same time, CAV speed and location data is used to optimize traffic light timing for vehicles approaching intersections from conflicting directions.”

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Regarding the research topics on sustainability, KSU said while electric vehicles are often seen as emission-free, higher demand for electricity to charge their batteries puts more pressure on the power grid, which could lead to higher emissions from the power plants that feed it.

“The impact of rising EV energy consumption on power plant emissions largely depends on the energy mix of the grid,” Amirgholy said. “In our recent study, we compared California, Georgia, New York, and Washington. Our findings show that increased EV adoption in states like Georgia, which heavily rely on fossil fuels, will significantly raise emissions from power plants. So, transportation electrification only effectively reduces emissions if the electricity is primarily sourced from renewable energy, as it is in California and Washington, and soon will be in New York.”

To make the research happen, Amirgholy’s team is partnering with Berkeley Lab, with the project funded by the Federal Highway Administration, KSU said. Researchers on the project are working to create an analytical tool called GEMS, or Geospatial Economic Multimodal Systems, to provide support and data for policy analysis and investment decision-making at a national level.

Amirgholy is using the technology to develop an advanced machine-learning model for analyzing urban networks.

“My goal is to use new technologies to develop solutions that improve quality of life for everyone, particularly underserved communities with limited access to the new technologies,” Amirgholy said.

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