Development of an Open Source Multi-Agent Virtual Simulation Test Bed for Evaluating Emerging Transportation Technologies and Policies

In previous years, the research team has developed and calibrated a base model implemented in MATSim and SUMO. This virtual testbed simulates an 8-million-person population and includes cars, trains, bus, bikeshare, taxi, and other for-hire vehicles calibrated to the year 2016. The team is building the architecture to host this virtual test bed and developing system design and user guide documentation.

Impact of Ride-Sharing in New York City

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.

Research on Concrete Applications for Sustainable Transportation (RE-CAST)

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.

Development of Mountable Sensors to Improve Bicyclist Safety

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.

Evaluation of New Features at MTA New York City Transit’s Accessible Station Lab

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.

Development of Autonomous Enforcement Approach using Advanced Weigh-In-Motion (A-WIM) System to Minimize Impact of Overweight Trucks on Infrastructure

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.

An Artificial Intelligence Platform for Network-wide Congestion Detection and Prediction Using Multi-source Data

The research team has already established an online transportation platform, named the Digital Roadway Interactive Visualization and Evaluation Network (DRIVE Net). DRIVE NET can be used for sharing, integration, visualization, and analysis of transportation-related data. The proposed research aims to extend the functions of DRIVE Net by developing an AI platform for network-wide congestion detection and prediction using multi-source data.