Expert Drivers’ Prospective Thinking-Aloud to Enhance Automated Driving Technologies : Investigating Uncertainty and Anticipation in Traffic
Grahn, H., Kujala, T., Silvennoinen, J., Leppänen, A., & Saariluoma, P. (2020). Expert Drivers’ Prospective Thinking-Aloud to Enhance Automated Driving Technologies : Investigating Uncertainty and Anticipation in Traffic. Accident Analysis and Prevention, 146, Article 105717. https://doi.org/10.1016/j.aap.2020.105717
Julkaistu sarjassa
Accident Analysis and PreventionPäivämäärä
2020Tekijänoikeudet
© 2020 Elsevier Ltd.
Current automated driving technology cannot cope in numerous conditions that are basic daily driving situations for human drivers. Previous studies show that profound understanding of human drivers’ capability to interpret and anticipate traffic situations is required in order to provide similar capacities for automated driving technologies. There is currently not enough a priori understanding of these anticipatory capacities for safe driving applicable to any given driving situation. To enable the development of safer, more economical, and more comfortable automated driving experience, expert drivers’ anticipations and related uncertainties were studied on public roads. First, driving instructors’ expertise in anticipating traffic situations was validated with a hazard prediction test. Then, selected driving instructors drove in real traffic while thinking aloud anticipations of unfolding events. The results indicate sources of uncertainty and related adaptive and social behaviors in specific traffic situations and environments. In addition, the applicability of these anticipatory capabilities to current automated driving technology is discussed. The presented method and results can be utilized to enhance automated driving technologies by indicating their potential limitations and may enable improved situation awareness for automated vehicles. Furthermore, the produced data can be utilized for recognizing such upcoming situations, in which the human should take over the vehicle, to enable timely take-over requests.
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Julkaisija
Elsevier BVISSN Hae Julkaisufoorumista
0001-4575Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/41776282
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Suomen AkatemiaRahoitusohjelmat(t)
Strategisen tutkimuksen ohjelmat STN, SALisätietoja rahoituksesta
The research was partly funded by the project Ethical AI for the Governance of the Society (ETAIROS), funded by Academy of Finland.Lisenssi
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