ADAS functional groupings and Driver Mental Models
Reference number | |
Coordinator | RISE Research Institutes of Sweden AB |
Funding from Vinnova | SEK 499 840 |
Project duration | November 2021 - September 2022 |
Status | Completed |
Venture | Electronics, software and communication - FFI |
Call | Electronics, software and communication - FFI - June 2021 |
End-of-project report | 2021-02514sv.pdf(pdf, 2004 kB) (In Swedish) |
Important results from the project
Groupings of ADAS based on drivers´ driving situations, needs and preferences can facilitate drivers to create mental models that support their understanding of ADAS In cases where the driver´s mental model(s) of ADAS do not match how ADAS is designed and/or presented to the driver, it can lead to risks about what drivers think ADAS can do and what ADAS can actually do Initial information of ADAS can affect drivers´ mental models. It is therefore important to provide information that supports drivers´ development of mental models.
Expected long term effects
The grouping concepts that were evaluated and developed in the preliminary study need to be supplemented with views, needs and eligibility requirements from end users. This can be done through, for example, workshops together with truck drivers, and with so-called "Card sorting" methodology that is used to make visible users´ mental models of how systems are connected. Grouping concepts of ADAS that are based on truck drivers´ mental models and their needs, experiences, preferences can contribute to the development of safer ADAS and more efficient use of these.
Approach and implementation
Three strategies for grouping ADAS have been evaluated based on research/ the literature on ADAS and mental models. The first strategy dealt with the packaging of ADAS from a sales perspective and which is mainly used as a "tool" by dealers of the vehicles. The second strategy is based on how the ADAS functions work in relation to the direction of the vehicle, i.e. longitudinal and lateral movements. The third strategy is based on grouping ADAS according to their functions and their degrees of intervention in different situations.