Abstract
Vehicles with SAE Level 2 automated features are already in active use on the road, and vehicles with Level 3 or 4 will be with us soon. Although the vehicles provide support for longitudinal and lateral control, partially automated driving experience is sometimes more demanding than manual driving. However, the effects of automated driving on workload in naturalistic conditions have not been extensively investigated, as most studies have been undertaken in driving simulators. This study aims to extend the current understanding about workload in partially automated driving on public roads. Drivers' perceived workload was assessed after conducting manual and automated driving activities using a small sample (N = 8). They performed driving tasks in three contemporary vehicles with SAE Level 2 features, in highway and urban environments. The comparative findings revealed that drivers' perceived workload was higher in partially automated driving than manual driving. Furthermore, perceived workload was higher in urban environments than highway environments and in less experienced drivers than more experienced drivers. Although the findings may need to be interpreted with caution due to the small sample size, they provide a future research agenda that can be built upon.
Original language | English |
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Pages (from-to) | 40-54 |
Number of pages | 15 |
Journal | Human Factors and Ergonomics In Manufacturing |
Volume | 33 |
Issue number | 1 |
Early online date | 22 Aug 2022 |
DOIs | |
Publication status | Published - Jan 2023 |
Bibliographical note
Funding Information:This study was supported by Jaguar Land Rover and the UK-EPSRC grant EP/N011899/1 as part of the jointly funded Towards Autonomy: Smart and Connected Control (TASCC) Programme.
Funding Information:
This study was supported by Jaguar Land Rover and the UK‐EPSRC grant EP/N011899/1 as part of the jointly funded Towards Autonomy: Smart and Connected Control (TASCC) Programme.
Publisher Copyright:
© 2022 Wiley Periodicals LLC.
Keywords
- driver interaction
- environment complexity
- on-road
- partial driving automation
- perceived workload