Safety Assurance System Utilizing Visual Attention for Advanced Driver-Assistance Systems

The research team will apply their results from neuroscience and safe control to improve driver-assistance technology as follows. First, the team will study the use of visual attention information to detect risks early, before the failure to detect risk-critical obstacles can be identified from the drivers' control action and vehicle states. Second, the team will find safer control actions even when conventional methods, which are unnecessarily conservative, become infeasible in finding safe intervention strategies.

• Record URL:
  https://ppms.cit.cmu.edu/projects/detail/405

Language

• English

Project

• Status: Completed
• Funding: $200000
• Contract Numbers:

  69A3551747111

• Sponsor Organizations:

  Carnegie Mellon University

  Mobility21 National USDOT UTC for Mobility of Goods and People
  Pittsburgh, PA  United States  15213

  Office of the Assistant Secretary for Research and Technology

  University Transportation Center Program
  ,    
• Managing Organizations:

  Carnegie Mellon University

  Mobility21 National USDOT UTC for Mobility of Goods and People
  Pittsburgh, PA  United States  15213
• Project Managers:

  Kline, Robin

• Performing Organizations:

  Carnegie Mellon University

  ,    
• Principal Investigators:

  Nakahira, Yorie

• Start Date: 20220701
• Expected Completion Date: 20230630
• Actual Completion Date: 20230807
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Attention; Driver support systems; Risk assessment
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01848335
• Record Type: Research project
• Source Agency: National University Transportation Center for Improving Mobility (Mobility21)
• Contract Numbers: 69A3551747111
• Files: UTC, RIP
• Created Date: Jun 10 2022 2:40PM