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Read MoreOn Wednesday, November 16, 2022, Town+Gown: NYC held its annual Vision Zero Research on the Road symposium, a public event for city agency staff, academic researchers, and other analysts to share recent findings that relate to road safety. Various topics were covered during the symposium, including the intersection of sustainability and traffic safety, enforcement and education, emerging trends in e-micromobility, speeding, substances and driving, and road design. C2SMART Center Director, Dr. Kaan Ozbay, and Senior Research Associate, Dr. Jingqin Gao, were invited to present C2SMART work at the event.
Town+Gown:NYC's collaborative working on Urban Hazard Mitigation for Infrastructural and Community Resiliency will share updates on the progress on Nov. 3rd, 8:30am-12pm. DYCD, 2 Lafayette, 14th Floor/online.
— NYU CUSP (@NYU_CUSP) November 1, 2022
RVSP at matthewte@ddc.nyc.gov indicating in-person/online attendance. pic.twitter.com/p5dJSn7yCp
Professor Ozbay spoke on Data-driven Determination of the Impact of Truck Traffic on Traffic Safety using Weigh-In-Motion (WIM) Data. He explained the importance of considering truck traffic when estimating crash frequency by severity levels and proposed a framework to model segment-level fatal and injury proportion based on Weigh-in-Motion Data and other traditional data sources. He highlighted that one critical finding is the negative impact of truck traffic, especially truck weight, on traffic safety. Dr. Ozbay also introduced the usage of WIM data and two current research conducted by C2SMART, namely NYC Overweight Truck Impact Study and WIM Selection and Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed. At the end of his presentation, he also emphasized that there is a need for a holistic approach to provide integrated solutions to address truck-related issues, not only truck safety, but also emission & air pollution, mobility & congestion, truck parking, as well as infrastructure resilience.
Dr. Jingqin Gao showcased the recent research on AI-Based Video Analytics for Vehicle and Pedestrian Detection, Tracking, and Speed Estimation Using Traffic Cameras conducted by a team of researchers at C2SMART. She presented the vision-based data acquisition framework using the existing traffic camera system in NYC and introduced what kind of new stream of safety and mobility data can be generated and how we can use them for traffic performance monitoring and evaluation, as well as real-time warning applications.
She also demonstrated various video analytics use cases, including speed estimation, queue detection, curb management, near-miss identification, pedestrian intention estimation, and pedestrian detection with mobility aids to provide insights about how these applications can potentially improve vehicle and vulnerable road user safety.
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