Monitoring and Predicting Pedestrian Behavior Using Traffic Cameras

Effective traffic monitoring and control systems must consider all moving objects. While vehicle detection systems have become common, sensor-based solutions capable of detecting and monitoring pedestrian activity have yet to become an integral part of a smart and effective infrastructure capable of protecting these most vulnerable traffic participants. Such systems could alert incoming vehicles about dangerous situations involving pedestrians, or provide adaptive traffic light control systems with information about the motion of people, so that they can operate and make decisions cognizant of all moving objects. In currently ongoing research work the project team is developing a vision-based framework which is capable of detecting, tracking, and predicting the trajectories of people in real time. These abilities constitute the core of a system capable of monitoring any developments concerning pedestrian motion. In this project, the team proposes a natural extension of this work: they focus on the deployment aspects of this framework. The team will address the challenges of bringing a new site into effective action, such as on-site camera calibration and the initial identification of a context to make predictions. The expected outcome is the creation, implementation, and demonstration of a framework which can be deployed in the field, and is capable of providing pedestrian information to systems like SURTRAC—a real time traffic signal control system. The milestones envisioned, to accomplish in one year, are: (1) Definition of methodology for initial station set up for on-site testing; (2) Design and test communications structure; (3) Live testing; and (4) Initial assessment of the impact on systems using pedestrian information. The project team is composed of a Master's student and researchers with many years of experience in computer vision for autonomous systems.     


    • English


    • Status: Active
    • Sponsor Organizations:

      Technologies for Safe and Efficient Transportation University Transportation Center

      Carnegie Mellon University
      Pittsburgh, PA  United States  15213

      Office of the Assistant Secretary for Research and Technology

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

      Carnegie Mellon University

      Pittsburgh, PA  United States 
    • Project Managers:

      Ehrlichman, Courtney

    • Performing Organizations:

      Carnegie Mellon University

      Pittsburgh, PA  United States 
    • Principal Investigators:

      Navarro-Serment, L

    • Start Date: 20170101
    • Expected Completion Date: 20180730
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers Program
    • Subprogram: DTRT-13G-UTC-26

    Subject/Index Terms

    Filing Info

    • Accession Number: 01645854
    • Record Type: Research project
    • Source Agency: Technologies for Safe and Efficient Transportation University Transportation Center
    • Files: UTC, RiP
    • Created Date: Sep 6 2017 7:21PM