Through wearable sensors and realistic representations of work zones in virtual reality, we plan to collect worker behavioral and physiological (heart rate) responses to warnings issued under various realistic scenarios and various warning mechanisms.
This project aims to develop a comprehensive holistic model of urban transportation demand given multiple available modes, including for-hire vehicles and their shared options. The model will enable assessment of the impact of shared mobility on urban transportation mode choice, which can be further translated into economic, social, and environmental impacts.
This research will focus on false data injection attacks, in which a malicious agent aims to affect the behavior of vehicles in the network by injecting false information about, for example, the traffic condition in the area or the availability of charging stations.
This project has many parts, and the NYU team is currently working with Rutgers on the RE-CAST 2D subproject. This subproject aims to test the bend strength of reinforced concrete that is repaired and strengthened using the four techniques: External Prestressing, Fiber-Reinforced Ferrocement Composite, Fiber-Reinforced Self Consolidating Concrete, and Fiber-Reinforced.
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.
These new sensors are focused on obtaining data about the bicyclist’s behavior, which will complement the current data and contribute to new findings. An iOS platform is also being developed to track the devices and visualize real-time data collected with them. More units are expected to be implemented into the device in the near future for crowdsourcing.
C2SMART researchers are working under the direction of NYCT staff in administering surveys/conducting interviews and collecting data from users of the proposed features/installations. As the data analysis partner, C2SMART is collecting and analyzing the collected data to develop analytics to assist NYCT in evaluating the performance of each of the features being tested as part of the Accessible Station Pilot.
In this study, the team investigated the effect of overweight trucks on the pavement and bridge damage from a national perspective to develop the most efficient enforcement approach to minimize infrastructure damage. The enforcement approach will include the continuation of the development of the A-WIM system and expanding its deployment.
This research aims to develop modeling and analysis methods to capture the key behaviors and intersections of the major players when integrating ridesourcing with transit.
The knowledge base from this data can be used to support design of portfolios of service options for a city. Given all the myriad of different options and existing public data, can we design a framework that can identify operating strategies that dominate in one or more sustainability criteria and quantify their performances within a portfolio of projects for city agencies to evaluate?