Dr. Abhijit Karimipour, Assistant Professor of Transportation Engineering at SUNY Polytechnic Institute, has developed an innovative framework that can estimate the length and duration of traffic delays caused by congestion and traffic accidents without relying on roadside physical sensors. Dr. Karimipour is the lead author of the new paper published in Case Studies on Transport Policy.

By integrating real-time vehicle speed and location data from extensive crowdsourced sources, the method enables continuous statewide monitoring of collision impacts at a fraction of the cost of traditional methods. In practice, this study provides transportation agencies with a powerful tool to detect and respond to incidents more quickly, better manage traffic congestion, and improve road safety for drivers.

The latest publication was co-authored with Anthony Alteri, a recent graduate of SUNY Polytechnic Institute, Adrian Cottam from the Auburn University Transportation Research Institute, and Ellwood Hanrahan II from the New York State Department of Transportation (NYSDOT).

The project was conducted by the Transportation Artificial Intelligence Research Laboratory (TRAIL) at SUNY Polytechnic Institute, where Dr. Karimipour serves as Director. The project greatly benefited from the collaboration with the New York State Department of Transportation (NYSDOT). The agency provided critical traffic data, participated in brainstorming sessions, and offered key insights that helped shape the research direction and outcomes.