Drivers’ Evaluation of Different Automated Driving Styles: Is It Both Comfortable and Natural?
Peng, Chen and Merat, Natasha and Romano, Richard and Hajiseyedjavadi, Foroogh and Paschalidis, Evangelos and Wei, Chongfeng and Radhakrishnan, Vishnu and Solernou, Albert and Forster, Deborah and Boer, Erwin (2022) Drivers’ Evaluation of Different Automated Driving Styles: Is It Both Comfortable and Natural? Human Factors: The Journal of the Human Factors and Ergonomics Society, 66 (3). ISSN 0018-7208
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Abstract
Objective
This study investigated users’ subjective evaluation of three highly automated driving styles, in terms of comfort and naturalness, when negotiating a UK road in a high-fidelity, motion-based, driving simulator.
Background
Comfort and naturalness play an important role in contributing to users’ acceptance and trust of automated vehicles (AVs), although not much is understood about the types of driving style which are considered comfortable or natural.
Method
A driving simulator study, simulating roads with different road geometries and speed limits, was conducted. Twenty-four participants experienced three highly automated driving styles, two of which were recordings from human drivers, and the other was based on a machine learning (ML) algorithm, termed Defensive, Aggressive, and Turner, respectively. Participants evaluated comfort or naturalness of each driving style, for each road segment, and completed a Sensation Seeking questionnaire, which assessed their risk-taking propensity.
Results
Participants regarded both human-like driving styles as more comfortable and natural, compared with the less human-like, ML-based, driving controller. Particularly, between the two human-like controllers, the Defensive style was considered more comfortable, especially for the more challenging road environments. Differences in preference for controller by driver trait were also observed, with the Aggressive driving style evaluated as more natural by the high sensation seekers.
Conclusion
Participants were able to distinguish between human- and machine-like AV controllers. A range of psychological concepts must be considered for the subjective evaluation of controllers.
Application
Insights into how different driver groups evaluate automated vehicle controllers are important in designing more acceptable systems.
| Item Type: | Article | ||||||
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| Identification Number: | https://doi.org/10.1177/00187208221113448 | ||||||
| Dates: |
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| Subjects: | CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-02 - building | ||||||
| Divisions: | Faculty of Computing, Engineering and the Built Environment > College of Built Environment | ||||||
| Depositing User: | Gemma Tonks | ||||||
| Date Deposited: | 06 Jun 2024 13:15 | ||||||
| Last Modified: | 20 Jun 2024 11:45 | ||||||
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/15551 |
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