Red Light Camera Expansion in New York City: Spillover Effect, Behavioral Insights and Strategic Allocation

Red Light Cameras (RLCs) are being deployed across various cities in the U.S. as tools to combat red-light running behavior at intersections on arterial roads which can lead to severe crashes and fatalities. Launched in 1994, New York City (NYC)'s Red Light Camera Program has played a vital role in enhancing traffic safety over the past three decades. The current deployment consists of 150 locations (1% of city intersections), each issuing a $50 fine for red light violations. According to the NYC Department of Transportation (NYC DOT), red light running has been reduced by 73% at locations with cameras, T-bone collisions have dropped by 65%, and rear-end collisions have fallen by 49%. In June 2024, New York State passed a renewal and expansion of the Red Light Camera Program to cover 5% of intersections (~600 locations). This provides an opportunity to evaluate the expansion’s impact and determine if it could further improve traffic safety and compliance, potentially leading to other benefits such as reduced congestion due to fewer incidents from red light running. This research project, in partnership with NYC DOT, aims to provide timely analytical support for the expansion of NYC's Red Light Camera Program. Through spatiotemporal analysis of historical RLC data combined with transportation and demographic data, the project will provide insights on the longitudinal effectiveness of the current program. Moreover, predictive analysis based on machine learning and spatial models will be developed to estimate the RLC network spillover effect and recommend strategic allocation of cameras to achieve the desired impact. This will help NYC DOT make data-driven decisions to maximize the program's benefits throughout the expansion. The expanded RLC network is expected to reduce intersection incidents, improve traffic flow, and decrease congestion, contributing to overall mobility and safety. The findings will also provide valuable insights for other states and communities with red light safety camera programs.

• Record URL:
  https://c2smarter.engineering.nyu.edu/red-light-camera-expansion-in-new-york-city-spillover-effect-behavioral-insights-and-strategic-allocation/

Language

• English

Project

• Status: Active
• Funding: $75000
• 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:

  Gao, Jingqin

  Zuo, Fan

  Bian, Zilin

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

Subject/Index Terms

• TRT Terms: Cameras; Machine learning; Red light running; Traffic safety
• Geographic Terms: New York City
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01937749
• 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 4:54PM