Develop In-Vehicle Information Dissemination Mechanisms to Reduce Cognitive Burden in the Information-Rich Driving Environment

In-vehicle information systems (IVIS) are poised to provide drivers with several types of information under the connected and autonomous travel information. Such real-time information can include traffic conditions, weather forecasts, warning/emergency alerts, and infotainment and commercial services. Such an information-rich environment can increase driver cognitive workload in the inherently multitasking driving context, further exacerbated by the multiple sources of information (such as variable message signs, personal devices, global positioning system (GPS), radio, etc.). This can reduce safety and decrease the effectiveness of the disseminated information, especially if the information delivery mechanisms are not well-designed. This study will conduct interactive driving simulator-based experiments to understand the impacts of real-time information characteristics and multiple dissemination sources on driver cognition, and its effects on the driver decision-making process and ability to comprehend information safely. Data will be collected on driver route choice behavior and physiological factors (such as eye movements, brain electrical activity and heart rate) under real-time information provision. These physiological factors will be used to determine cognitive effects (such as cognitive workload, distraction, and level of engagement). The collected data will be used to develop behavior models to investigate the impacts of cognitive effects induced by real-time traffic information, situational factors (such as trip purpose and traffic congestion), real-time travel information characteristics (such as amount, content and source) and individual driver characteristics (such as age, gender and education). These models will be used to design safe and effective information dissemination mechanisms.

• Record URL:
  ccat.umtri.umich.edu

Language

• English

Project

• Status: Completed
• Funding: $119595 (USDOT); 120650 (Chongqing-Cost Share)
• Contract Numbers:

  69A3551747105

• Sponsor Organizations:

  Department of Transportation

  Office of the Secretary
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Connected and Automated Transportation

  University of Michigan, Ann Arbor
  Ann Arbor, MI  United States  48109
• Project Managers:

  Tucker-Thomas, Dawn

• Performing Organizations:

  Purdue University, Lyles School of Civil Engineering

  550 Stadium Mall Drive
  West Lafayette, IN  United States  47907
• Principal Investigators:

  Peeta, Srinivas

• Start Date: 20170815
• Expected Completion Date: 20220930
• Actual Completion Date: 20230302
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Advanced traveler information systems; Behavior; Cognition; Driver information systems; Drivers; Information dissemination; Intelligent vehicles; Mobile communication systems; Multitasking; Physiology; Real time information; Route choice
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01645395
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: Aug 31 2017 2:46PM