Reproducibility of Driving Profiles - Application of the Wizard of Oz Method for Vehicle Pedestrian Interaction

T. Fuest, L. Michalowski, E. Schmidt, K. Bengler

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Wizard of Oz (WoZ) studies are a method used to examine pedestrians' understanding of the different driving behaviors of automated vehicles (AV). In this WoZ study, a human driver, hidden behind a seat cover, repeatedly followed predefined trajectories. First, we asked the participants to rate different AV driving behaviors from a pedestrian's perspective. Then we examined the performance of the human driver in following the trajectories. The results showed that 98 % of pedestrians understood the intentions of an AV by judging the driving behavior, if the trajectory met certain criteria. Ambiguous driving profiles decreased the recognition rate to 26 %. Furthermore, the driver followed diverse trajectories of differing qualities. The results also demonstrated that more complex trajectories were harder to follow. Reducing speed until reaching the exact point of a complete standstill appeared to be problematic. In conclusion, the findings suggest that WoZ studies are a useful way to evaluate large differences in trajectories, but are not suited to evaluating slight speed or acceleration differences.

Original languageEnglish
Title of host publication2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3954-3959
Number of pages6
ISBN (Electronic)9781538670248
DOIs
StatePublished - Oct 2019
Event2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand
Duration: 27 Oct 201930 Oct 2019

Publication series

Name2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Country/TerritoryNew Zealand
CityAuckland
Period27/10/1930/10/19

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