Sensors Know When to, What to, and How to Interact With Human in Vehicles

From laptops to smartphones, ubiquitous computing devices equipped with sensors generate information about our daily routines on the go. This information enables computers to estimate our in-situ states and proactively provide information services to users. Consequently, users can interact with cyber information anywhere, at anytime, including in vehicles while driving. However, arbitrary or inopportune prompts to interact with cyber information interfere with safe vehicle operation. As humans attention is finite, the ubiquity of HCI opportunities comes at a cost, more significantly during driving. To address this problem, this project explores the issues of when to intervene (i.e., optimal timing), how to intervene (i.e., presentation methods), and what to intervene (i.e., types of HCI demands or information). The research team aims to enable sensor-equipped computers to handle these issues and design human-centered intelligent interventions. This project extends the team's prior UTC work to create enabling technologies that support seamless interaction between human and ubiquitous computing spaces. In this project, the team will collect big sensor data streams from a least intrusive set of wearable or internet-of-things sensors, worn by vehicle users and/or embedded in vehicles, including daily smart devices. During a set of human-subject experiments in naturalistic field driving situations, the team will investigate how drivers interact with proactive adjustments of information initiated by system intelligence rather than user demand. The team also considers presentation methods and types of interaction schemes across human visual, auditory, and haptic sensory channels. The near goal is to create a smarter, contextually intelligent cyber-physical system that supports intelligibility of system behavior. These experiments will provide a set of sensor-based real-time models of drivers cognitive load, user interruptibility, and user experience of proactive information services. Ultimately, these technologies will help drivers safely interact with proactive cyber-information interventions.


  • English


  • Status: Active
  • Funding: $127500
  • Contract Numbers:


  • Sponsor Organizations:

    Carnegie Mellon University

    Mobility 21 National UTDOT for Mobility of Goods and People

    Office of the Assistant Secretary for Research and Technology

    University Transportation Program
  • Managing Organizations:

    Carnegie Mellon Univeristy

    Mobility 21 National UTDOT for Mobility of Goods and People
  • Project Managers:

    Schweyer, Lisa Kay

  • Performing Organizations:

    Carnegie Mellon University

  • Principal Investigators:

    Dey, Anind

  • Start Date: 20170101
  • Expected Completion Date: 20180831
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01677492
  • Record Type: Research project
  • Source Agency: Technologies for Safe and Efficient Transportation University Transportation Center
  • Contract Numbers: DTRT-13-GUTC-26
  • Files: UTC, RiP
  • Created Date: Aug 7 2018 12:04PM