Upcoming Events

Simulating the Impact of Ridesharing in New York City
Sep 24 @ 2:00 pm – 3:00 pm
Understanding the impact of transportation interventions on urban systems is complex but critical for decision making. The cornerstone for such impact assessments is estimating the mode shift resulting from an intervention. While transportation planning has well-established models for mode-choice assessment, relying on an individual choice simulation could provide a better estimate. In addition, available ground-truth data on real-world transportation choices are often incomplete or inconsistent. Dr. Sobolevsky addresses these challenges by offering an individual mode-choice and mode-shift simulation model, and Bayesian inference framework. It accounts for uncertainties in the data and model estimate and translates them into uncertainties of the resulting mode-shift and their impacts. The framework is evaluated using two case studies: the introduction of ride-sharing for-hire-vehicles in NYC, and the recent introduction of the Manhattan Congestion Surcharge. This webinar also shows how Dr. Sobolevsky’s framework can be used for assessing mode-shift and the resulting economic, social and environmental implications for any future urban transportation solutions and policies being considered by decision-makers or transportation companies.
Stanislav Sobolevsky is an Associate Professor of Practice and Director Of Urban Complexity Lab at the Center for Urban Science and Progress at New York University, and a Research Affiliate at the MIT Senseable City Lab. He holds a Ph.D. (1999) and Doctor of Science habilitation degree (2009) in Mathematics. Dr. Sobolevsky teaches applied aspects of data science, machine learning, and network analysis. Research of his group studies human behavior in the urban context through its digital traces: spatio-temporal big data created by various aspects of human activity, such as social media, cell phone records, vehicle/vessel GPS traces, public service requests, credit card transactions and others.


Pink Tax on Mobility: Workshop
Sep 24 @ 4:00 pm – 5:00 pm

Women are three times as likely to be concerned for their safety, and as a result choose longer, more costly, or less efficient transportation. The physical and psychological impact of gender-based trauma can result in life-long preferences for cars or taxis instead of transit or bikes. And 75% of caregivers are women; escorting children or the elderly reduces travel options and adds costs. As previous C2SMART-funded research led by Sarah Kaufman, has shown, transportation has a “Pink Tax”: women pay more than men to travel.

With support from NYSERDA and Lyft, a series of workshops will bring together diverse leaders from transportation, government, industry, research, investors, and advocates. The purpose of the workshops is to draft an R&D and tech demonstration road map with an emphasis on innovations that can be tested in NYS next year and then scaled. The workshops will also establish a network interested in the broader issue.

Divided into three sessions, the first two sessions will focus fairly narrowly on specific aspects that are more amenable to immediate innovation: Caregiver accessibility (school-related travel, chaperoning those with disabilities, and micro-mobility options) and personal safety (station design, off-peak and essential worker travel, and university access). The third session will be action planning.



Developing C2SMART’s Interactive Data Dashboard: COVID-19 and Transportation
Sep 30 @ 3:00 pm – 4:00 pm
Integrating data sources from multiple agencies and industries, C2SMART researchers have developed a publicly accessible data dashboard that displays in real-time transportation trends such as subway ridership, bus speeds, freight activity, bike usage and, using computer image processing and publicly available NYCDOT traffic cam footage, pedestrian density and social distancing practices. Dr. Jingqin Gao will review the origins of the dashboard, deliver a tutorial, and review the state of New York City transportation in the months after the COVID-19 pandemic.
Jingqin Gao

Jingqin (Jannie) Gao completed her Ph.D. in Transportation Planning and Engineering at NYU Tandon, where she works with C2SMART Director Kaan Ozbay. She studied Science and Technology of Optical Information and received her B.S. from Tongji University in China and her M.S in Transportation Planning and Engineering from New York University. Her research interests lie in offline and real-time simulation modeling, big data and machine learning approach for transportation, and transportation economics. She also worked for the New York City Department of Transportation on modeling and data analysis to support the agency’s internal planning, technical review processes and coordinated with external agencies on regional projects since 2012. Jingqin is the former president of NYU’s joint Institute of Transportation Engineers (ITE) and The Intelligent Transportation Society of America (ITS) Student Chapter during 2018-2019, through which she organized various company visits, tech talks, women in transportation events and the 2019 ITE Northeastern District Traffic Bowl.

Yubin Shen

Yubin Shen is an Assistant Research Engineer at C2SMART Center. He received his M.S. in Computer Science from Stevens Institute of Technology (2015). Previously he worked for MTA New York City Transit. He provides technical support for the center and also cooperates in the research projects at the center. His research interests include database optimization, web data crawling and embedded system.



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