Mental States & Machine: Enhancing Driver Engagement in Automated Vehicles for Safer Transitions

Automated vehicles still need human drivers to take over when the system reaches limitations. This proposed research aims to conduct three phases of studies to understand the impact of various mental states on takeover performance, develop machine learning models for predicting these interactions, and design an advanced Human-Machine Interface (HMI) tool. Together, these phases seek to enhance traffic operations, bolster infrastructure resilience, and fortify transportation cybersecurity, ensuring a safer and more efficient future for automated driving.

Language

• English

Project

• Status: Active
• Funding: $150000
• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Howard University

  2400 6th Street, NW
  Washington, DC  United States  20059
• Performing Organizations:

  San Jose State University

  1 Washington Sq
  San Jose, California  United States  95192
• Principal Investigators:

  Huang, Gaojian

  Etu, Egbe-Etu

• Start Date: 20231123
• Expected Completion Date: 20241031
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Autonomous vehicle handover; Drivers; Human machine systems; Machine learning; Mental condition
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01931420
• Record Type: Research project
• Source Agency: Research and Education in Promoting Safety (REPS) University Transportation Center
• Files: UTC, RIP
• Created Date: Sep 19 2024 2:32PM