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Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings

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
2194-5357
20-26
Springer
Kim, Jisun
95e8d9df-8383-4fb5-9806-5b5d064cda37
Revell, Kirsten
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Langdon, Pat
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Bradley, Mike
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Politis, Ioannis
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Thompson, Simon
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Skrypchuk, Lee
c50ee672-ee07-44bc-83f6-3cbb4ef55d98
O-Donoghue, Jim
d21d470b-15ab-4dec-89c5-6b787789bb95
Richardson, Joy
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Clark, Jed
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Roberts, Aaron
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Mouzakitis, Alex
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Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Ahram, Tareq
Karwowski, Waldemar
Vergnano, Alberto
Leali, Francesco
Taiar, Redha
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
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Roberts, Aaron
a2fb35d9-a42f-4a07-848d-01cecae9d893
Mouzakitis, Alex
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Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Ahram, Tareq
Karwowski, Waldemar
Vergnano, Alberto
Leali, Francesco
Taiar, Redha

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. pp. 20-26 . (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.

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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
ORCID for Jisun Kim: ORCID iD orcid.org/0000-0003-0119-4313
ORCID for Joy Richardson: ORCID iD orcid.org/0000-0001-7716-5370
ORCID for Jed Clark: ORCID iD orcid.org/0000-0002-1356-2462
ORCID for Neville A. Stanton: ORCID iD orcid.org/0000-0002-8562-3279

Catalogue record

Date deposited: 13 Jan 2022 17:53
Last modified: 06 Jun 2024 02:03

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Contributors

Author: Jisun Kim ORCID iD
Author: Kirsten Revell
Author: Pat Langdon
Author: Mike Bradley
Author: Ioannis Politis
Author: Simon Thompson
Author: Lee Skrypchuk
Author: Jim O-Donoghue
Author: Joy Richardson ORCID iD
Author: Jed Clark ORCID iD
Author: Aaron Roberts
Author: Alex Mouzakitis
Editor: Tareq Ahram
Editor: Waldemar Karwowski
Editor: Alberto Vergnano
Editor: Francesco Leali
Editor: Redha Taiar

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