Driving Behavioral Learning Leveraging Sensing Information from Innovation Hub

The primary goal of this proposal is to develop machine-learning algorithms for driving behavior mining, using real-time vehicle, pedestrian, and infrastructure data. The proposed algorithms will improve our understanding of how people drive on both highways and urban roads, which will help monitor and maintain roadside infrastructure and support the transportation systems to accommodate not only the existing human-driven vehicle but also the upcoming connected and automated mobility systems. The intended outcome of the project is an algorithm suite to learn human behavior patterns from LiDAR and camera datasets. To facilitate its adoption by public agencies, the software will be open-sourced with friendly interface design. The proposed smart mobility testbed concept could be deployed at local intersections and arterial corridors in the City of New Brunswick, NJ and utilized by the Robert Wood Johnson hospital’s patient shuttle services and parking services.

Language

  • English

Project

  • Status: Active
  • Funding: $140157
  • Contract Numbers:

    69A3551847102

    CAIT-UTC-REG46

  • 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:

    Middlesex County Transportation

    75 Bayard Street
    New Brunswick, NJ  United States  08901

    Center for Advanced Infrastructure and Transportation

    Rutgers University
    100 Brett Road
    Piscataway, NJ  United States  08854-8058
  • Project Managers:

    Caviness, Solomon

    Szary, Patrick

  • Performing Organizations:

    Columbia University

    610 SW Mudd
    500W 120th Street
    New York, New York  United States  10027

    Center for Advanced Infrastructure and Transportation

    Rutgers University
    100 Brett Road
    Piscataway, NJ  United States  08854-8058
  • Principal Investigators:

    Di, Xuan

    Jin, Peter

  • Start Date: 20210101
  • Expected Completion Date: 20211231
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01771378
  • Record Type: Research project
  • Source Agency: Center for Advanced Infrastructure and Transportation
  • Contract Numbers: 69A3551847102, CAIT-UTC-REG46
  • Files: UTC, RIP
  • Created Date: May 6 2021 11:28AM