Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings
Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings
Partially automated vehicles are in actual use, and vehicles with higher levels of automation are under development. Given that highly automated vehicles (AVs) still require drivers’ intervention in certain conditions, effective collaboration between the driver and vehicle seems essential for driving safety. Having a clear understanding about drivers’ interactions with the current technologies is key to enhance them. Additionally, comprehending drivers’ perceptions toward AVs investigated in naturalistic settings seems important. This study particularly focuses on usability, workload, and acceptance of AVs as they are key indicators of drivers’ perceptions. Eight drivers conducted manual and automated driving in urban and highway environments. Their interactions and verbal descriptions were recorded, and perceptions were measured after each drive. Instances that may have negatively affected the perceptions were identified. The results showed that workload was higher, usability and acceptance were lower in automated driving in general. Findings show what should be considered to improve driver-autonomous vehicle interaction, in turn to help reduce workload, enhance usability, and acceptance.
Acceptance, Autonomous vehicles, Human factors, Human-machine interaction, Usability, Workload
20-26
Kim, Jisun
95e8d9df-8383-4fb5-9806-5b5d064cda37
Revell, Kirsten
e80fedfc-3022-45b5-bcea-5a19d5d28ea0
Langdon, Pat
dbcea6d6-9d1b-4840-b745-2daaaf7598c5
Bradley, Mike
13c46902-142e-4334-9ca8-22538ad3a5f1
Politis, Ioannis
3e066508-0573-4b9e-bfdb-3f30ca795c49
Thompson, Simon
251a3271-54c3-4bfd-af10-9c25aa8f026a
Skrypchuk, Lee
c50ee672-ee07-44bc-83f6-3cbb4ef55d98
O-Donoghue, Jim
d21d470b-15ab-4dec-89c5-6b787789bb95
Richardson, Joy
e2587944-ff00-4a72-bed0-9547b62f95aa
Clark, Jed
5d82ac6c-58be-4366-9b11-5e3179d85b33
Roberts, Aaron
a2fb35d9-a42f-4a07-848d-01cecae9d893
Mouzakitis, Alex
6b9a6eb0-e893-4028-aec6-0e61c4e900ff
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
2020
Kim, Jisun
95e8d9df-8383-4fb5-9806-5b5d064cda37
Revell, Kirsten
e80fedfc-3022-45b5-bcea-5a19d5d28ea0
Langdon, Pat
dbcea6d6-9d1b-4840-b745-2daaaf7598c5
Bradley, Mike
13c46902-142e-4334-9ca8-22538ad3a5f1
Politis, Ioannis
3e066508-0573-4b9e-bfdb-3f30ca795c49
Thompson, Simon
251a3271-54c3-4bfd-af10-9c25aa8f026a
Skrypchuk, Lee
c50ee672-ee07-44bc-83f6-3cbb4ef55d98
O-Donoghue, Jim
d21d470b-15ab-4dec-89c5-6b787789bb95
Richardson, Joy
e2587944-ff00-4a72-bed0-9547b62f95aa
Clark, Jed
5d82ac6c-58be-4366-9b11-5e3179d85b33
Roberts, Aaron
a2fb35d9-a42f-4a07-848d-01cecae9d893
Mouzakitis, Alex
6b9a6eb0-e893-4028-aec6-0e61c4e900ff
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Kim, Jisun, Revell, Kirsten, Langdon, Pat, Bradley, Mike, Politis, Ioannis, Thompson, Simon, Skrypchuk, Lee, O-Donoghue, Jim, Richardson, Joy, Clark, Jed, Roberts, Aaron, Mouzakitis, Alex and Stanton, Neville A.
(2020)
Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings.
Ahram, Tareq, Karwowski, Waldemar, Vergnano, Alberto, Leali, Francesco and Taiar, Redha
(eds.)
In Intelligent Human Systems Integration - Proceedings of the 3rd International Conference on Intelligent Human Systems Integration IHSI 2020: Integrating People and Intelligent Systems.
vol. 1131 AISC,
Springer.
.
(doi:10.1007/978-3-030-39512-4_4).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Partially automated vehicles are in actual use, and vehicles with higher levels of automation are under development. Given that highly automated vehicles (AVs) still require drivers’ intervention in certain conditions, effective collaboration between the driver and vehicle seems essential for driving safety. Having a clear understanding about drivers’ interactions with the current technologies is key to enhance them. Additionally, comprehending drivers’ perceptions toward AVs investigated in naturalistic settings seems important. This study particularly focuses on usability, workload, and acceptance of AVs as they are key indicators of drivers’ perceptions. Eight drivers conducted manual and automated driving in urban and highway environments. Their interactions and verbal descriptions were recorded, and perceptions were measured after each drive. Instances that may have negatively affected the perceptions were identified. The results showed that workload was higher, usability and acceptance were lower in automated driving in general. Findings show what should be considered to improve driver-autonomous vehicle interaction, in turn to help reduce workload, enhance usability, and acceptance.
This record has no associated files available for download.
More information
Published date: 2020
Additional Information:
Funding Information:
Acknowledgments. This work 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. The authors thank the funders for their support.
Publisher Copyright:
© Springer Nature Switzerland AG 2020.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
Venue - Dates:
3rd International Conference on Intelligent Human Systems Integration, IHSI 2020, , Modena, Italy, 2020-02-19 - 2020-02-21
Keywords:
Acceptance, Autonomous vehicles, Human factors, Human-machine interaction, Usability, Workload
Identifiers
Local EPrints ID: 453349
URI: http://eprints.soton.ac.uk/id/eprint/453349
ISSN: 2194-5357
PURE UUID: 1e26b12c-716a-468b-95ad-df7b7626731f
Catalogue record
Date deposited: 13 Jan 2022 17:53
Last modified: 18 Mar 2024 03:47
Export record
Altmetrics
Contributors
Author:
Jisun Kim
Author:
Pat Langdon
Author:
Mike Bradley
Author:
Ioannis Politis
Author:
Simon Thompson
Author:
Lee Skrypchuk
Author:
Jim O-Donoghue
Author:
Joy Richardson
Author:
Jed Clark
Author:
Alex Mouzakitis
Editor:
Tareq Ahram
Editor:
Waldemar Karwowski
Editor:
Alberto Vergnano
Editor:
Francesco Leali
Editor:
Redha Taiar
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics