Student’s research seeks to educate consumers on driver assistance technologies

New vehicle technologies, such as Lane Keeping Assist and Adaptive Cruise Control, can assist drivers with steering, speed maintenance, and other operational tasks. However, what is the best way to educate consumers on how to use them safely?

Graduate student Alexandria Noble is investigating this question as part of her research on driver behavior and training. She believes that consumers need to be aware of how and when to use driver assistance technologies — in essence, to understand what these systems can and cannot do currently.

“When a user’s expectations are not in alignment with the systems’ capabilities, we have the potential for misuse or disuse of these systems,” Noble explained. “Improved training can help consumers better manage their expectations of what driving automation systems are available today and better prepare them for new systems available in the future.”

Recently, Noble received the prestigious Alphonse Chapanis Student Paper Award for her research during the Human Factors and Ergonomics Society (HFES) International Annual Meeting. Noble is pursuing a Ph.D. in industrial and systems engineering and is a graduate student researcher at the Virginia Tech Transportation Institute (VTTI).

“I am incredibly honored to receive the Chapanis Best Student Paper Award. I feel very privileged to have had an opportunity to work with some of the very best transportation safety researchers in the world, both at Virginia Tech and Texas A&M Transportation Institute,” said Noble.

Her award-winning study focused on knowledge, behaviors, and perceived familiarity with automated vehicle technology. Forty volunteers were randomly assigned to one of two training groups to learn how to use the Traffic Aware Cruise Control and Autosteer features of a 2016 Tesla Model S. The control group read a section of the operator’s manual. The experimental group, on the other hand, completed an interactive multimedia module via the display monitors inside the vehicle.

Following the training sessions, both groups completed the post-training questionnaire and drove on the Virginia Smart Roads, a closed test track. Perhaps surprisingly, according to the study findings, the type of training received had little bearing on the participants’ overall knowledge scores. There were also no significant differences in driver behaviors or attitudes between the two groups. After the drive, many participants reported being more familiar with vehicle automation. However, their general knowledge of the vehicle systems remained the same.

These findings could indicate that a brief tutorial might not be enough to alter potential misconceptions about the technology’s abilities and limitations, according to Noble. Instead, a long-term training distributed over time may be more effective.

Noble is continuing this research for her dissertation. She hopes her work will help identify areas in which drivers might especially need targeted training.

“The goal of my dissertation is to make suggestions about the future of driver training for automated systems based on observation of driver behavior with the systems in the real world. I believe this work is going to be a good first step in redefining the driver training models to meet the needs of driver education in the future,” said Noble.

The Alphonse Chapanis Student Paper Award is presented to a student for outstanding human factors research presented during the HFES Annual Meeting.

The project was funded by the Safety through Disruption (Safe-D) National UTC, a grant from the U.S. Department of Transportation’s University Transportation Centers Program (Federal Grant Number: 69A3551747115).

Related links

·        Driver Training for Automated Vehicle Technology – Knowledge, Behaviors, and Perceived Familiarity

·        Safe-D: Driver Training for Automated Vehicle Technology

·        Safety through Disruption University Transportation Center