COVID-19 Transportation Data Dashboard and White Papers
The COVID-19 pandemic and ensuing social distancing orders have had dramatic impacts on the use of every mode of transportation. C2SMART researchers have developed an interactive data dashboard that investigates changes in mobility patterns and travel trends as the crisis evolves. Through this dashboard, policymakers and researchers can examine the impact of the outbreak on transportation as it unfolds. This platform will be regularly updated with new data, metrics, and visualization as they become available.
On May 3, C2SMART published the second issue of a white paper on the impact of the pandemic on behavior and travel trends. Leveraging open data from multiple data sources, the white paper updates the data presented in the previous issue of the white paper published on April 3, 2020. It continues to highlight the impacts of COVID-19 on transportation systems in New York City, and adds data from Seattle, WA as well as multiple cities in China to show what potential recovery looks like for transportation systems and mode choice.
Open Source Multi-Agent Virtual Simulation Testbed in NYC
A team of researchers led by Dr. Joseph Chow has developed an open-source multi-agent virtual simulation testbed (MATSim) for NYC. The team has worked to add timely new simulation extensions including the effects of the COVID-19 pandemic, congestion pricing, the BQX streetcar, and more. Visit the project webpage to learn more.
Webinar: MATSim Applications for Congestion Pricing & COVID-19 Pandemic Recovery
Dr. Joseph Chow and Yueshuai Brian He demonstrated how their MATSim model might be used to help policy-makers plan for reopening following COVID-19 and other scenarios. Watch the webinar on the link to the right.
On June 11, C2SMART published the third issue of a white paper on the impact of the pandemic on behavior and travel trends. It highlights the use of C2SMART’s open-source agent-based simulation model to predict the impact of each stage of NY State’s proposed phased reopening strategy on transportation system usage in New York City. It also introduces a new deep learning-based video-processing method to observe social distancing on city streets using traffic monitoring cameras, as well as an algorithm and metrics to quantify the social distancing behavior of pedestrians.
On July 22, C2SMART published the fourth issue of a white paper on the impact of the pandemic on behavior and travel trends. Analyzing new data at the cusp of the final reopening phase of New York City, it provides updates on previous analysis of traffic volumes and speeds, and focuses on MTA bus speeds and ridership, Access-A-Ride ridership, CitiBike patterns and cycling density, and the rise of micro-mobility use through services like Revel, the ever-popular electric moped sharing service.