Advanced Driver Distraction Detection System

According to the National Center for Statistics and Analysis about 50% of car crashes are due to driver distraction. Monitoring a driver's activities form the basis of a security system that can potentially reduce the number of accidents by detecting anomalous situations. Because distraction while driving is a leading safety issue, the aim of this proposal is to develop an improved driver monitoring system. To achieve this goal, the project proposes to build a system that concurrently monitors the driver's focus of attention on the road and performs early detection of some of the driver's activities. The project's advanced driver detection system (ADDDS) will have one camera facing the driver and another capturing the driver's field of view. The proposed system is therefore capable of monitoring both the driver's status and the environment surrounding the car. There are two main modules of ADDDS: (1) Detecting where the driver is looking in the road, and (2) detecting the driver's behavior. To detect where the driver is looking, the project will propose a method for mapping from the driver's gaze to the exterior view that is based on a 3D reconstruction of the interior and exterior of the car. ADDDS avoids the necessity for re-calibration in a controlled environment cause by changes in the driving position, which is the main drawback of other approaches. To detect the driver's behavior, the project will propose a novel temporal classifier for detecting a driver's activities such as talking, texting on the phone, operating the radio, eating, or talking to the passengers. Both systems are combined to create a unique framework that takes advantage of a complete reconstruction of the driver/car environment to reliably estimate driver distraction.

  • Supplemental Notes:
    • Contract to a Performing Organization has not yet been awarded.


  • English


  • Status: Active
  • Funding: $85,000
  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Project Managers:

    Ehrlichman, Courtney

  • Performing Organizations:

    Carnegie Mellon University

    Pittsburgh, PA  United States 
  • Principal Investigators:

    De la Torre, Fernando

  • Start Date: 20160101
  • Expected Completion Date: 20170101
  • Actual Completion Date: 0
  • Source Data: Technologies for Safe and Efficient Transportation University Transportation Center

Subject/Index Terms

Filing Info

  • Accession Number: 01586685
  • Record Type: Research project
  • Source Agency: Technologies for Safe and Efficient Transportation University Transportation Center
  • Files: UTC, RiP
  • Created Date: Jan 8 2016 3:07PM