Inaccurate network pavement data can impact pavement management decisions such as roadway repairs and more. CAIT researchers at the Rutgers Asphalt Pavement Lab are working with NJDOT to test new pavement inspection equipment and locations to ensure data is accurate and representative of roads in New Jersey.
This course provides participants with (1) a basic understanding of intersection safety issues, (2) “how to” information for common safety tasks and low cost safety improvements that do not require an engineered design, and (3) background information on safety tasks that do not require an engineer.
Ahead of National Work Zone Awareness Week, Rutgers Center for Advanced Infrastructure and Transportation will host the annual New Jersey Work Zone Safety Conference on Thursday, April 7th, from 8:30 am to 1 pm.
The primary goal of this proposal is to assist NJ TRANSIT’S Bus Service Planning department to create a complete roster of the 500 bus capacity Northern bus garage determining stats such as platform hours and non-revenue mileage totals for potential auditing purposes.
On August 30th, Rutgers CAIT hosted UTC partners from Rowan University to discuss their research Evaluating the Mobility Impacts of American Dream Complex and Developing Innovative Intersection Safety Tools, as part of a presentation during the CAIT Seminar Series.
This proposal will develop machine-learning algorithms using real-time vehicle, pedestrian, and infrastructure data to improve our understanding of how people drive on highways and urban roads. These models will help monitor and support the transportation systems to accommodate both human-driven and automated vehicles.
The primary goal of this project is to define and document JFK Cargo View requirements, evaluating the options and costs to acquire, develop, and manage the system, exploring potential business models to operate and monetize it, and establishing an implementation plan to develop and deploy it.
The goal of this proposal is to develop and assess an innovative real-time proactive safety monitoring system based on the trajectory of road users (e.g., cars, pedestrians, and cyclists) collected by video cameras.