How Will Autonomous Vehicles Decide in Case of an Accident? An Interval Type-2 Fuzzy Best–Worst Method for Weighting the Criteria from Moral Values Point of View

ALTAY B. C., BOZTAŞ A. E., OKUMUŞ A., GÜL M., ÇELİK E.

Sustainability (Switzerland), cilt.15, sa.11, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 11
  • Basım Tarihi: 2023
  • Doi Numarası: 10.3390/su15118916
  • Dergi Adı: Sustainability (Switzerland)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Aerospace Database, CAB Abstracts, Communication Abstracts, Food Science & Technology Abstracts, Geobase, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: artificial intelligence, autonomous vehicles, ethics, the best–worst method, transportation, trolley dilemma
  • İstanbul Üniversitesi Adresli: Evet

Özet

The number of studies on Autonomous Vehicle (AV) ethics discussing decision-making algorithms has increased rapidly, especially since 2017. Many of these studies handle AV ethics through the eye of the trolley problem regarding various moral values, regulations, and matters of law. However, the literature of this field lacks an approach to weighting and prioritizing necessary parameters that need to be considered while making a moral decision to provide insights about AVs’ decision-making algorithms and related legislations as far as we know. This paper bridges the gap in the literature and prioritizes some main criteria indicated by the literature by employing the best–worst method in interval type-2 fuzzy sets based on the evaluations of five experts from different disciplines of philosophy, philosophy of law, and transportation. The criteria included in the weighting were selected according to expert opinions and to the qualitative analysis carried out by coding past studies. The weighing process includes a comparison of four different approaches to the best–worst method. The paper’s findings reveal that social status is the most important criterion, while gender is the least important one. This paper is expected to provide valuable practical insights for Autonomous Vehicle (AV) software developers in addition to its theoretical contribution.