What is the New Baseline: Helping FDNY understand emergency response needs to tackle traffic and service congestion under a transient population and built environment

Strategic planning for emergency response relies on reliable data on spatial population distributions, built environment inventories, and their cumulative effects on traffic and service congestion. These data support decision-making for assigning and stationing emergency vehicles and prioritizing alternative vehicles in highly congested areas. However, post-COVID data are limited or in flux due to changing work patterns, new traffic policies, and increasing emergency services (EMS) demand. In Year 1, the research team's project with the New York City Fire Department (FDNY) developed an artificial intelligence (AI) model for a New York City (NYC) neighborhood, quantifying the effects of built environment features on emergency response times under congestion. For Year 2, the research team proposes to extend this analysis citywide, employing statistical and machine learning techniques combined with queueing-based optimization methodologies that relate American Community Survey (ACS) population attributes to high-severity calls and built-environment-affected response times, from which treatments for service bottlenecks can be prioritized. This project will also explore innovative EMS interventions, such as alternative vehicles, and provide deployment recommendations that could most benefit response times.

• Record URL:
  https://c2smarter.engineering.nyu.edu/what-is-the-new-baseline-helping-fdny-understand-emergency-response-needs-to-tackle-traffic-and-service-congestion-under-a-transient-population-and-built-environment/

Language

• English

Project

• Status: Active
• Funding: $156,608
• Contract Numbers:

  69A3551747124

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Connected Communities for Smart Mobility Towards Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER)

  New York University
  Brooklyn, New York  United States  11201
• Project Managers:

  Pohl, Lizzie

  Chase, Holly

• Performing Organizations:

  Connected Communities for Smart Mobility Towards Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER)

  New York University
  Brooklyn, New York  United States  11201

  New York University Tandon School of Engineering

  6 Metrotech Center
  Brooklyn, NY  United States  11201
• Principal Investigators:

  Chow, Joseph

  Ozbay, Kaan

  Gao, Jingqin

• Start Date: 20240901
• Expected Completion Date: 20251130
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Emergency response time; Fire departments; Machine learning; Traffic simulation
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Planning and Forecasting; Security and Emergencies;

Filing Info

• Accession Number: 01937750
• Record Type: Research project
• Source Agency: Connected Communities for Smart Mobility Towards Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER)
• Contract Numbers: 69A3551747124
• Files: UTC, RIP
• Created Date: Nov 21 2024 4:59PM