Interaction between pedestrians and Wizard of Oz automated vehicles. Master thesis Delft University of Technology.

Author(s)
Rodríguez Palmeiro, A.
Year
Abstract

Automated Vehicles (AV) will be introduced on public roads in the near future. This would result in automated vehicles sharing the urban space with other road users including drivers of traditional vehicles and vulnerable road users. Pedestrians might be unable to distinguish the vehicle type (traditional or automated) they are interacting with and crossing situations might become confusing, possibly leading to dangerous encounters between pedestrians and vehicles. There is currently little knowledge about the interactions between pedestrians and AVs from the point of view of the pedestrian in a real life environment. The aim of this master thesis is to determine whether pedestrians’ crossing intentions differ when interacting with automated vehicles compared to when interacting with traditional vehicles. An experiment was developed on a closed road where participants encountered a Wizard of Oz automated vehicle and a traditional vehicle in a within-subject design. In the Wizard of Oz set-up, a fake ‘driver’ sat on the driver seat while the vehicle was driven by the passenger with a joystick. Different scenarios were studied regarding vehicle appearance (‘driver’ reading a newspaper, roof signs, hood/side signs) and approach direction (left vs. right). Results showed that the majority of participants reported that the vehicle was (sometimes) driven autonomously, which indicates that the Wizard of Oz was credible. Moreover, most of the participants perceived the differences in vehicle appearance and reported to be influenced by these features. Despite of this, measurements of critical gaps and self-reported level of stress showed no significant differences between the different conditions of vehicle appearance. (Author/publisher)

Publication

Library number
20180462 ST [electronic version only]
Source

Delft, Delft University of Technology, Faculty of Civil Engineering - Transport & Planning, 2017, XIII + 109 p. + app., ref.

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