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Articles

A Wizard-of-Oz experimental approach to study the human factors of automated vehicles: Platform and methods evaluation

ORCID Icon, , , ORCID Icon, & ORCID Icon
Pages S140-S144 | Received 06 Mar 2020, Accepted 10 Aug 2020, Published online: 28 Aug 2020
 

Abstract

Objectives

Driving simulation is an important platform for studying vehicle automation. There are different approaches to using this platform – with most using scripting or programmatic tools to simulate vehicle automation. A less frequently used approach, the Wizard-of-Oz method, has potential for increased flexibility and efficiency in designing and conducting experiments. This study designed and evaluated an experimental setup to examine the feasibility of this approach as an alternative for conducting automation studies.

Methods

Twenty-four participants experienced simulated vehicle automation in two platforms, one where the automation was controlled by algorithms, and the other where the automation was simulated by an external operator. Surveys were administered after each drive and the drivers’ takeover performance after the automation disengaged was measured.

Results

Results indicate that while the kinematic parameters of the driving differed significantly for the two platforms, there were no significant differences in the perceptions of participants and in their takeover performance between the two platforms.

Conclusion

These results provide evidence for the use of alternative approaches for the conduct of human factors studies on vehicle automation, potentially lowering barriers to undertaking such experiments while increasing flexibility in designing more complex studies.

Acknowledgments

All authors reviewed the results and approved the final version of the manuscript.

Additional information

Funding

The study was sponsored by research funding from Safety Research Using Simulation (SAFER-SIM) – University Transportation Center (Federal Grant No: 69A3551747131), and with support from the Department of Mechanical and Industrial Engineering at the University of Massachusetts Amherst.

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