Exploring Cost-effective Computer Vision Solutions for Smart Transportation Systems

The project is focused on developing a deep learning based data acquisition and analytics tool using vision - based sensors (i.e., cameras) to understand cities with machine eyes . The team will assess the maturity of various smart city applications using computer vision and object detection (e.g., pedestrian detection, work zone identification , curb lane usage, connected and automated vehicles [CAVs] ) as well as the needs of the local agencies. The goal is to demonstrate the c ost - effectiveness of the computer vision technology to generate new stream of mobility data and provide support for planning and operational strategies , utilizing both existing transportation infrastructure and emerging probe and CAVs . More specifically, t his project aims to establish an inventory of available traffic camera systems in the U.S. and deploy two computer vision smart city applications based on stakeholder feedback that are customized for New York City (NYC) . The team will also establish a formalized pipeline for running the computer vision algorithm enhanced for NYC conditions and prototype the applications for real - world implementation.

• Record URL:
  https://c2smart.engineering.nyu.edu/exploring-cost-effective-computer-vision-solutions-for-smart-transportation-systems/

Language

• English

Project

• Status: Completed
• Funding: $48614
• Contract Numbers:

  69A3551747124

• Sponsor Organizations:

  New York University Tandon School of Engineering

  6 Metrotech Center
  Brooklyn, NY  United States  11201

  Office of the Assistant Secretary for Research and Technology

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

  New York University Tandon School of Engineering

  6 Metrotech Center
  Brooklyn, NY  United States  11201
• Performing Organizations:

  Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)

  New York University
  Tandon School of Engineering
  Brooklyn, NY  United States 
• Principal Investigators:

  Gao, Jingqin

• Start Date: 20220301
• Expected Completion Date: 20230228
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Cameras; Computer vision; Connected vehicles; Cost effectiveness; Data collection; Infrastructure; Intelligent transportation systems; Pedestrian detectors; Probe vehicles; Sensors; Traffic surveillance
• Geographic Terms: New York (New York)
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01845601
• Record Type: Research project
• Source Agency: Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
• Contract Numbers: 69A3551747124
• Files: UTC, RIP
• Created Date: May 18 2022 1:26PM