The primary mission of the Bridge Resource Program (BRP) is to provide ongoing engineering evaluation and research support to the New Jersey Department of Transportation’s (NJDOT) Division of Bridge Engineering and Infrastructure Management. Major Goals of BRP is to (1) Preserve the state’s Bridge and Structural Assets, (2) Optimize the overall condition of the state’s assets within available funding limits and (3) Assist in developing the policy and standard based on new technologies to ensure structures safety and preserve NJDOT’s structures.
This project aims to improve the efficiency of mobility-on-demand services with the help of machine learning. The goal is to create an algorithm that public paratransit services, private rideshare companies, and future autonomous vehicle fleets could use to improve operations and lower costs.
Led by NYU Rudin Center Assistant Director Sarah Kaufman, the Emerging Leaders in Transportation program develops early-career transportation professionals to develop and promote innovations within their organizations. The three-day program includes professional development with executive leaders, communication work through networking activities, and site visits to major transportation management locations.
The main deliverable for this project was a smartphone navigation app that addresses the specific mobility needs and priorities of seniors, improving their ability to travel around their cities. After the prototype was developed, the researchers recruited seniors to test the app for a few weeks, and then gathered their feedback.
This project will investigate technologies to screen overweight trucks including a high-speed weigh-in-motion (HS-WIM) system integrated with a license plate reader and/or security camera, and to evaluate the feasibility of such technologies compared to current screening practices at weighing stations.=.
Researchers at NYU are working with NYCDOT and other partners on this portion of the NYC CV Pilot, as well as on safety performance evaluation of the CV technology deployment.
This research project aimed to develop a data-driven approach for modeling cities, with a focus on pedestrian dynamics, which play a fundamental role in urban planning. It focused on detecting and counting objects such as pedestrians, cars, and bicycles in visual data sources that can provide insight into how people move around a city. The research team used an image database made up of tens of millions of images produced by Brooklyn-based start-up Carmera as its main data source.
This project developed real-time distributed network control techniques capable of utilizing various types of real-time traffic data, from both fixed and mobile sources. The work is divided into two major parts: traffic state estimation when data is limited and adaptive control.
This work will be conducted with the research group 6-t: Bureau de Recherche, based in Paris. The project aims to better understand and compare the consumption practices and mobility behaviors of the residents living in two of the major cities in the world (Paris and NYC). The work will be conducted through a simultaneous survey in both cities, analysis, stakeholder meeting and narrative.
This research aims to explore the basic research on developing signal control and coordination methods under the CV environment, develop a framework for urban traffic signal optimization with CVs, and test the developed methods both in traffic simulation and using real-world CV data.