A Tier 1 University Transportation Center taking on today’s mobility challenges

2021 C2SMART Student of the Year – Apply Now!

Apply Now for the 2021 Outstanding Student of the Year Award! Each year, the C2SMART Center acknowledges one student from any of its member institutions as a Student of the Year as chosen by the Center’s executive leadership committee. The chosen student will be acknowledged and awarded: Cash prize of $1,000 and a certificate from…

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FloodSense Project Helps Target Flood Response

Remnants of Hurricanes Ida and Henri caused torrential rain and flash flooding across New York City this summer, highlighting the city’s urgent need for more resilient infrastructure. Between the two storms, Manhattan weathered the greatest influx of rainfall since 1943, registering 1.94 inches per hour with Henri, and a record-shattering 3.15 inches per hour during…

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C2SMART USDOT Tier 1 Designation Extended Through 2023

C2SMART Center has been awarded an additional year of funding worth $1.4 million by the US Department of Transportation (USDOT), extending C2SMART’s Tier 1 University Transportation Center (UTC) designation to September 2023. With this additional year of funding and designation, C2SMART aims to continue and expand its slate of funded research projects in transportation in smart cities, big data analytics, infrastructure…

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CycleBack NYC

CycleBack NYC: Scaling Employer-Based Bike Access Cycling as a commuter option is growing rapidly, and New York City seeks to build on this momentum by introducing a new affordable way for New Yorkers to obtain bicycles. Employer bicycle leasing in Europe has allowed employees to obtain a new bicycle as a fringe benefit and repay…

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Our Research

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Climate change exacerbates the frequency and impacts of hazardous events, such as hurricanes, flooding, and wildfires. During emergencies that require preemptive evacuation, drivers using alternative fuel vehicles can be vulnerable under conventional evacuation routes that do not provide access to refueling and charging stations on their way to safety. In this talk, I will discuss a novel evacuation routing problem considering multiple fuel vehicle types. An evacuation tree problem with hop constraints that capture each vehicle fuel type & refueling/charging needs as they are routed to safety is introduced. Large-scale network numerical experiments in South Florida are conducted and planning insights are presented. Even though refueling and charging infrastructure is deployed to meet habitual travel demand, in the second part of my talk I will focus on the extension of the alt-fuel evacuation problem to decide the location of emergency refueling and/or charging infrastructure on the transportation network. Presented by UIUC's Prof. Ria Kontou
Alternative Fuel Vehicle Evacuation and Refueling Infrastructure Location Planning
YouTube Video UC-JzRVBnWGJ3_Jv5iYmpo6A_VvVoey_Exto
While an omnipresent element in almost all sci-fi content, robots remain hard to find in our daily lives. What's the last time you have seen a functioning robot doing useful work in our society? However, despite the limited public exposure, robotic technologies are undergoing rapid improvement in their own corner. Today our presenter will speak about some of the latest advancements made in academia, and how we are just starting to see robots maturing into useful products. He will also discuss some of the biggest hurdles going forward and conclude with a case study on Amazon Robotics' rocky adoption of robotics technologies. Presented by NYU's Irving Fang as part of the Student Learning Hub
SLH: Where Are All the Robots, and Why Aren’t There More of Them?
YouTube Video UC-JzRVBnWGJ3_Jv5iYmpo6A_67KPl8UVeFs
Drones are becoming an invaluable tool for urban data collection, offering a wide range of applications from traffic monitoring to environmental analysis. This course introduces participants to the full scope of using drones for traffic data collection, starting with the necessary FAA licensing and airspace regulations, followed by practical guidance on drone operation and control. We’ll explore the different sensors and gimbals that can be equipped on drones, such as cameras, thermal imaging, and LiDAR, and their respective applications in collecting urban data. This session provides a comprehensive understanding of how drones can be utilized for diverse data-driven urban analyses. Presented by NYU's Tu Lan and Vivaldi Rinaldi as part of the Student Learning Hub
SLH Comprehensive Urban Data Collection Using Drones: From Licensing to Advanced Sensor Applications
YouTube Video UC-JzRVBnWGJ3_Jv5iYmpo6A_pqIkLLNuGU8
Rapidly developing mobile and sensor networks are accumulating massive volumes of human mobility data in cities. Predictive modeling on these data is a fundamental problem in building decision support systems for various urban and transportation applications. In the real world, such spatio-temporal data show multifold heterogeneity over space and non-stationarity over time, which makes the prediction task especially challenging. My research focuses on developing adaptive AI algorithms (e.g., meta learning) to enhance the robustness of mobility prediction models. Making robust predictions across space and time lays a foundation for not only next generation mobility services, but also emergency response to adverse events, including traffic accidents, pandemic lockdown, and natural disasters. Presented by Zhaonan Wang, Asst. Prof., NYU Shanghai
Spatio-temporal Adaptive AI for Urban Mobility Modeling
YouTube Video UC-JzRVBnWGJ3_Jv5iYmpo6A_iJohkUoBfzg
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