Connected Cities for Smart Mobility toward Accessible and Resilient Transportation
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.
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.
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.
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 will increase the safety profile and ease-of-use of the VISION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation) platform toward ‘connected’ dynamic navigation in complex urban environments, providing a new level of security to the end user and permitting one to break down significant barriers to employment and social interaction.
The primary objective of this research project is to define quantifiable metrics that make it possible to adequately represent accessibility of EV charging infrastructure and to internalize these metrics in decision-support procedures and tools that are used by utilities and authorities to determine electricity rates (tariffs) and additional incentives to promote investments in EV charging infrastructure.