Connected Cities for Smart Mobility toward Accessible and Resilient Transportation
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?
This project aims to develop LOS analysis procedures that estimate or measure the average search time for selected types of parking facilities. Additionally, alternative evaluation methodologies for parking operations based on the IOT will be explored. The new smart cities approach to measure customer service is dubbed PMS to distinguish it from the LOS analysis procedure. Cities are interested in making better use of smart meter usage data.
This project aims to understand the key parameters that play a role in achieving responsive behaviors in workers. Through wearable sensors and representations of traffic loads from real data acquired from hardware in the loop systems and work zones in virtual reality, data on workers’ behavioral and physiological responses to warnings issued under various realistic scenarios and varying warning mechanisms will be studied.
Although lots of research have been conducted on multi-vehicle cooperative perception, few studies have considered combining information from vehicle onboard sensors and roadside sensors. This project argues that it would be highly beneficial to utilize roadside sensors for cooperative driving perception.