Moving Into the Loop: An Investigation of Drivers' Steering Behavior in Highly Automated Vehicles. (June 2020)
- Record Type:
- Journal Article
- Title:
- Moving Into the Loop: An Investigation of Drivers' Steering Behavior in Highly Automated Vehicles. (June 2020)
- Main Title:
- Moving Into the Loop: An Investigation of Drivers' Steering Behavior in Highly Automated Vehicles
- Authors:
- Alsaid, Areen
Lee, John D.
Price, Morgan - Abstract:
- Objective: This paper investigates driver engagement with vehicle automation and the transition to manual control in the context of a phenomenon that we have termed vicarious steering—drivers steering when the vehicle is under automated control. Background: Automated vehicles introduce many challenges, including disengagement from the driving task and out-of-the-loop performance decrement. We examine drivers' steering behavior when the automation is engaged, and steering input has no effect on the vehicle state. Such vicarious steering is a potential indicator of engagement for evaluating automated vehicles. Method: A total of 32 female and 32 male drivers between 25 and 55 years of age participated in this experiment. A 2 × 2 between-subject design combined control algorithms and instructed responsibility. The control algorithms (lane centering and adaptive) were intended to convey the capability of the automation. The adaptive algorithm drifted across the lane center when latent hazards were present. The instructed levels of responsibility (driver primarily responsible and automation primarily responsible) were intended to replicate the admonitions of owners' manuals. Results: The adaptive algorithm increased vicarious steering ( p < .001), but instructed responsibility did not ( p = .67), and there was no interaction between the algorithm and the responsibility ( p = .75). Vicarious steering was associated with an increase in transitions to manual control and glances toObjective: This paper investigates driver engagement with vehicle automation and the transition to manual control in the context of a phenomenon that we have termed vicarious steering—drivers steering when the vehicle is under automated control. Background: Automated vehicles introduce many challenges, including disengagement from the driving task and out-of-the-loop performance decrement. We examine drivers' steering behavior when the automation is engaged, and steering input has no effect on the vehicle state. Such vicarious steering is a potential indicator of engagement for evaluating automated vehicles. Method: A total of 32 female and 32 male drivers between 25 and 55 years of age participated in this experiment. A 2 × 2 between-subject design combined control algorithms and instructed responsibility. The control algorithms (lane centering and adaptive) were intended to convey the capability of the automation. The adaptive algorithm drifted across the lane center when latent hazards were present. The instructed levels of responsibility (driver primarily responsible and automation primarily responsible) were intended to replicate the admonitions of owners' manuals. Results: The adaptive algorithm increased vicarious steering ( p < .001), but instructed responsibility did not ( p = .67), and there was no interaction between the algorithm and the responsibility ( p = .75). Vicarious steering was associated with an increase in transitions to manual control and glances to the road but was negatively associated with driving performance immediately after the transition to manual control. Conclusion: Vicarious steering is a promising indicator of driver engagement when the vehicle is under automated control and automation algorithms can promote engagement. … (more)
- Is Part Of:
- Human factors. Volume 62:Number 4(2020)
- Journal:
- Human factors
- Issue:
- Volume 62:Number 4(2020)
- Issue Display:
- Volume 62, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 62
- Issue:
- 4
- Issue Sort Value:
- 2020-0062-0004-0000
- Page Start:
- 671
- Page End:
- 683
- Publication Date:
- 2020-06
- Subjects:
- automated vehicles -- steering -- vehicle control algorithms -- trust -- responsibility
Human engineering -- Periodicals
620.82 - Journal URLs:
- http://hfs.sagepub.com/ ↗
http://www.sagepublications.com/ ↗ - DOI:
- 10.1177/0018720819850283 ↗
- Languages:
- English
- ISSNs:
- 0018-7208
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13082.xml