Driver Training for Automated Vehicle Technology – Knowledge, Behaviors, and Perceived Familiarity
| Autor: | Alexandria M. Noble, Sheila G. Klauer, Michael Manser, Zachary R. Doerzaph |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 63:2110-2114 |
| ISSN: | 1071-1813 2169-5067 |
| Popis: | Advanced driver-assistance systems and partial driving automation are becoming increasingly common, yet despite their growing prevalence, drivers seem to know very little about them. Previous studies have found that owners of ADAS equipped vehicles have demonstrated misperceptions or lack of awareness about system limitations, which may impact driver comfort with and reliance on these systems. The purpose of this study was to determine the effectiveness of two training strategies on drivers’ knowledge and perceived familiarity of vehicle automation as well as their environment monitoring behaviors during system use. Forty volunteers participated in a multi-stage research study in which they were exposed to either a conventional training protocol, self-learning through the owner’s manual, or an experimental (multimedia) training protocol, using the in-vehicle display technologies as training tools. Results indicate training strategy elicits limited differences in knowledge and no difference in driver behaviors or attitudes. Behaviors and attitudes were heavily influenced by time and experience with the driving automation system while knowledge of the vehicle systems remained unchanged. |
| Databáze: | OpenAIRE |
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