NYU Tandon School of Engineering’s C2SMARTER transportation center collaborates with the New York City Fire Department (FDNY) to implement AI technology.
The goal is to reduce emergency vehicle response times in the city’s congested streets and advance urban emergency services.
The collaboration aims to create a digital twin that mimics neighborhood traffic flow. This virtual model allows for analyzing emergency response delays and testing effective solutions.
The organizations say the digital twin overcomes the constraints of conventional approaches in evaluating emergency response times. It bypasses costly infrastructure changes, fleet upgrades and alternate routing, saving expenses and disruptions to traffic.
Joseph Chow, an institute associate professor in the Department of Civil & Urban Engineering and associate director of C2SMARTER, notes that communities like Harlem have been underserved in the past.
“They can see significant benefits from faster emergency vehicle responses,” adds Chow.
“The project with FDNY is a prime example of C2SMARTER’s commitment to using New York City as a living laboratory to create engineering solutions that improve urban mobility and make life better for all New Yorkers.”
This approach leverages the MATSim-NYC traffic software Chow, created in 2020. This project integrates real-time data obtained from Harlem’s network of traffic cameras and sensors and FDNY vehicle dispatch data. By incorporating artificial intelligence, it also simulates realistic driver reactions to the wail of sirens.
The technology aims to reduce response times, currently 7 minutes and 26 seconds, to improve patient survivability and recovery rates. The digital twin project started in October 2023 and is expected to conclude by September 2024.
According to Rebecca Mason, the assistant commissioner of management analysis and planning at FDNY, improved patient outcomes are linked to shorter response times.
“It’s critical we understand what impedes the fastest possible response and that we develop strategies to deal with those roadblocks,” Mason adds.
The C2SMARTER team aims to make the traffic simulation and AI tools available as open-source software. Additionally, they will publish playbooks outlining optimal emergency vehicle strategies, enabling other agencies to implement the strategies.
“If successful, this Digital Twin will be the first of its kind in the US, advancing the adoption of cutting-edge technologies for emergency response,” adds Jingqin (Jannie) Gao, the assistant director of research at C2SMARTER.
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AI technology | digital twin | US Department of Transportation
