Low-Distraction Interaction

Developing systems to enable safe and low-distraction Human-Machine-Interaction within the vehicles is an extremely challenging task. Today's information systems in vehicles, which include services for Navigation, Media access and even communications technologies are unsafe because they have no awareness or understanding of the driver, the driving environment, or the broader goals of the interaction. Additionally, current information systems in vehicles are cumbersome to use, significantly increasing the cognitive load of the driver compared to Human-To-Human interaction. In this work the project team explores Human-Centric Design for information-access within vehicles. First the project collect and analyze Human-To-Human interaction in vehicles. analyzing the timing, type and stages of interaction when a human co-pilot provides support and becomes the portal for Navigation, Media-Access and communication with outside parties. The project team then explores and develops the core technologies to support a similar Human-like interaction within the vehicle, using machine learning and sensor networks including camera's, microphones and global positioning systems (GPS) to gain situation knowledge. The situationally aware agent can then interact with the driver in a dynamic and situational manner, reducing cognitive load to a level akin to interacting with another human in the vehicle.

    Language

    • English

    Project

    • Status: Active
    • Funding: $127500
    • 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:

      Shen, John

    • Start Date: 20170101
    • Expected Completion Date: 20170730
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers Program
    • Subprogram: DTRT-13G-UTC-26

    Subject/Index Terms

    Filing Info

    • Accession Number: 01645844
    • Record Type: Research project
    • Source Agency: Technologies for Safe and Efficient Transportation University Transportation Center
    • Files: UTC, RiP
    • Created Date: Sep 6 2017 7:09PM