Abstract
People seem to hold the human driver to be primarily responsible when their partially automated vehicle crashes, yet is this reasonable? While the driver is often required to immediately take over from the automation when it fails, placing such high expectations on the driver to remain vigilant in partially automated driving is unreasonable. Drivers show difficulties in taking over control when needed immediately, potentially resulting in dangerous situations. From a normative perspective, it would be reasonable to consider the impact of automation on the driver’s ability to take over control when attributing responsibility for a crash. We, therefore, analyzed whether the public indeed considers driver ability when attributing responsibility to the driver, the vehicle, and its manufacturer. Participants blamed the driver primarily, even though they recognized the driver’s decreased ability to avoid the crash. These results portend undesirable situations in which users of partially driving automation are the ones held responsible, which may be unreasonable due to the detrimental impact of driving automation on human drivers. Lastly, the outcome signals that public awareness of such human-factors issues with automated driving should be improved.
| Original language | English |
|---|---|
| Article number | 16193 |
| Number of pages | 11 |
| Journal | Scientific Reports |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Dec 2022 |
Bibliographical note
Funding Information:This project was funded by AiTech, the initiative for meaningful human control over artificial intelligence, at Delft University of Technology. This research was partially supported by TAILOR, a project funded by EU Horizon 2020 research and innovation programme under GA No 952215. This work was partially supported by the European Commission funded project “Humane AI: Toward AI Systems That Augment and Empower Humans by Understanding Us, our Society and the World Around Us” (grant # 820437) and by the National Science Foundation (NWO) Hybrid Intelligence project under Grant No. (1136993). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The support is gratefully acknowledged.
Publisher Copyright:
© 2022, The Author(s).