The Center for Advanced Infrastructure and Transportation (CAIT) Regional UTC Consortium led by Rutgers, the State University of New Jersey has awarded a total of $200,000 in grant research funds to three CREATES’ faculty members:
Dr. Mohammad Jalayer
A Real-Time Proactive Intersection Safety Monitoring System Based on Video Data
According to the National Highway Traffic Safety Administration (NHTSA), New Jersey ranked second in the nation with respect to the ratio of pedestrian fatalities to the total number of motor vehicle deaths, necessitating further investigations to mitigate the frequency and severity of crashes involving pedestrians. This project will develop and assess an innovative real-time proactive safety monitoring system using video cameras. The results of this project will provide a great opportunity for transportation agencies to develop appropriate safety solutions to reduce intersection-related crashes and incidents and consequently reduce traffic congestion.
Dr. Adriana Trias Blanco
Bridge Deck Surface Profile Evaluation for Rapid Screening and Deterioration Monitoring
This research project consists on assessing bridge deck condition by evaluating the deck’s profile generated by data gathered via LiDAR. This proposal derives from the promising results found during preliminary work, where the top profile on the bridge decks gathered through LiDAR were compared to Ground Penetrating Radar (GPR) and Electrical Resistivity (ER) data on a search for possible correlations between the deck’s top surface profile and its deterioration pattern. This approach has the potential for implementation as a method for rapid screening of bridge decks.
Dr. Ghulam Rasool
Rotorcraft Landing Sites Identification – Scaling and Generalization of the AI Model
The updated information about the location and type of landing sites is an essential asset for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). We have developed AI-based system that for detecting helipads, heliports, and other lading sites for rotorcrafts from the Google Earth satellite imagery.