Examination of the effectiveness of multiple training methods on supporting drivers’ better understanding towards level 2 automated vehicle systems

Vehicle automation aims to improve driving safety and reduce the workload and stress of a human driver by transferring the driving task from the driver to control devices. As all automated vehicle control systems have limitations, improper expectations and trust can decrease the effectiveness and safety benefits of an automated system. If a driver over-trusts the system, he or she may use the automation when conditions exceed the capacity of the system, compromising safety. Although previous studies suggest that providing accurate knowledge to users may help train them to establish appropriately calibrated trust of automated systems, limited effort has been done to examine how training can improve drivers’ understanding of the systems, and to develop appropriate training programs for this purpose. The main objective of this study is to develop and evaluate the efficacy of different training methods to promote a driver’s safe operation and trust calibration of automated vehicle (AV) systems. Two AV systems were examined in this study: Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA). Both knowledge- and skill-based training strategies were developed to describe the AV system functionalities and limitations associated with the two systems. These strategies were later evaluated to determine their impact on producing an accurate mental models each AV system, and were compared with training based on use of the owners’ manual. It was hypothesized that both knowledge and skill-based training leads to better understanding of system limitations and functionalities, compared to exclusive reliance on the owners’ manual.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ANB30 Standing Committee on Operator Education and Regulation.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Bao, Shan
  • Feng, Fred
  • Pradhan, Anuj
  • Zhang, Yu
  • Jia, Bochen
  • Sullivan, John
• Conference:
  • Transportation Research Board 98th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2019-1-13 to 2019-1-17
• Date: 2019

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 4p

Subject/Index Terms

• TRT Terms: Autonomous intelligent cruise control; Driver education; Highway safety; Intelligent vehicles; Level 2 driving automation; Vehicle safety
• Uncontrolled Terms: Lane keeping assistance
• Subject Areas: Education and Training; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01697699
• Record Type: Publication
• Report/Paper Numbers: 19-01321
• Files: TRIS, TRB, ATRI
• Created Date: Mar 1 2019 3:51PM