Comprehending and effectively using automated driving functions in heavy truck operations

Important results from the project

The project focused on investigating how AI-based voice agents, in combination with 6G, can support learning about vehicle automation. The project´s goal was met by developing prototypes for different levels of voice interaction that were then evaluated in a study with truck drivers. The results showed that adaptive two-way dialogue has particular potential to improve both user experience and learning support in heavy vehicles. The work has been published as a thesis at Linköping University.

Expected long term effects

The project shows how 6G and new interaction technologies can enable new decision support and learning support. In the long term, the project contributes to the development of solutions that make it easier and safer for users to learn to use vehicle functions, perform tasks and interact with technical systems. We expect this to lead to increased safety, more efficient skill development and lower thresholds for adopting new technology, both in the automotive field and in other applications.

Approach and implementation

The project was carried out as a master´s degree project at RISE and Linköping University. The project was implemented according to plan. The work included a needs analysis, development of prototypes for different types of voice interaction and a user test with truck drivers in simulated driving situations. RISE and Scania provided input and feedback on prototypes and evaluation methods. Data was collected and analyzed to draw conclusions and create design recommendations.