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

Jisun Kim; Kirsten Revell; Pat Langdon; Mike Bradley; Ioannis Politis; Simon Thompson; Lee Skrypchuk; Jim O-Donoghue; Joy Richardson; Jed Clark; Aaron Roberts; Alex Mouzakitis; Neville A. Stanton

doi:10.1007/978-3-030-39512-4_4

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

Jisun Kim^*, Kirsten Revell, Pat Langdon, Mike Bradley, Ioannis Politis, Simon Thompson, Lee Skrypchuk, Jim O-Donoghue, Joy Richardson, Jed Clark, Aaron Roberts, Alex Mouzakitis, Neville A. Stanton

^*Corresponding author for this work

Research output: Chapter in Book/Published conference output › Conference publication

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.

Original language	English
Title of host publication	Intelligent Human Systems Integration 2020
Subtitle of host publication	Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020) Integrating People and Intelligent Systems
Editors	Tareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar
Pages	20-26
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-030-39512-4_4
Publication status	E-pub ahead of print - 22 Jan 2020
Event	3rd International Conference on Intelligent Human Systems Integration, IHSI 2020 - Modena, Italy Duration: 19 Feb 2020 → 21 Feb 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1131 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	3rd International Conference on Intelligent Human Systems Integration, IHSI 2020
Country/Territory	Italy
City	Modena
Period	19/02/20 → 21/02/20

Bibliographical note

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.

Keywords

Acceptance
Autonomous vehicles
Human factors
Human-machine interaction
Usability
Workload

Access to Document

10.1007/978-3-030-39512-4_4

Cite this

Kim, J., Revell, K., Langdon, P., Bradley, M., Politis, I., Thompson, S., Skrypchuk, L., O-Donoghue, J., Richardson, J., Clark, J., Roberts, A., Mouzakitis, A., & Stanton, N. A. (2020). Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings. In T. Ahram, W. Karwowski, A. Vergnano, F. Leali, & R. Taiar (Eds.), Intelligent Human Systems Integration 2020 : Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020) Integrating People and Intelligent Systems (pp. 20-26). (Advances in Intelligent Systems and Computing; Vol. 1131 AISC). Advance online publication. https://doi.org/10.1007/978-3-030-39512-4_4

Kim, Jisun ; Revell, Kirsten ; Langdon, Pat et al. / Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings. Intelligent Human Systems Integration 2020 : Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020) Integrating People and Intelligent Systems. editor / Tareq Ahram ; Waldemar Karwowski ; Alberto Vergnano ; Francesco Leali ; Redha Taiar. 2020. pp. 20-26 (Advances in Intelligent Systems and Computing).

@inproceedings{05c9612e4ea0412a9d7d3e2dd3975d56,

title = "Drivers{\textquoteright} interaction with, and perception toward semi-autonomous vehicles in naturalistic settings",

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{\textquoteright} intervention in certain conditions, effective collaboration between the driver and vehicle seems essential for driving safety. Having a clear understanding about drivers{\textquoteright} interactions with the current technologies is key to enhance them. Additionally, comprehending drivers{\textquoteright} 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{\textquoteright} 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.",

keywords = "Acceptance, Autonomous vehicles, Human factors, Human-machine interaction, Usability, Workload",

author = "Jisun Kim and Kirsten Revell and Pat Langdon and Mike Bradley and Ioannis Politis and Simon Thompson and Lee Skrypchuk and Jim O-Donoghue and Joy Richardson and Jed Clark and Aaron Roberts and Alex Mouzakitis and Stanton, {Neville A.}",

note = "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: {\textcopyright} Springer Nature Switzerland AG 2020.; 3rd International Conference on Intelligent Human Systems Integration, IHSI 2020 ; Conference date: 19-02-2020 Through 21-02-2020",

year = "2020",

month = jan,

day = "22",

doi = "10.1007/978-3-030-39512-4_4",

language = "English",

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Kim, J, Revell, K, Langdon, P, Bradley, M, Politis, I, Thompson, S, Skrypchuk, L, O-Donoghue, J, Richardson, J, Clark, J, Roberts, A, Mouzakitis, A & Stanton, NA 2020, Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings. in T Ahram, W Karwowski, A Vergnano, F Leali & R Taiar (eds), Intelligent Human Systems Integration 2020 : Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020) Integrating People and Intelligent Systems. Advances in Intelligent Systems and Computing, vol. 1131 AISC, pp. 20-26, 3rd International Conference on Intelligent Human Systems Integration, IHSI 2020, Modena, Italy, 19/02/20. https://doi.org/10.1007/978-3-030-39512-4_4

Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings. / Kim, Jisun; Revell, Kirsten; Langdon, Pat et al.
Intelligent Human Systems Integration 2020 : Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020) Integrating People and Intelligent Systems. ed. / Tareq Ahram; Waldemar Karwowski; Alberto Vergnano; Francesco Leali; Redha Taiar. 2020. p. 20-26 (Advances in Intelligent Systems and Computing; Vol. 1131 AISC).

Research output: Chapter in Book/Published conference output › Conference publication

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T1 - Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings

AU - Kim, Jisun

AU - Revell, Kirsten

AU - Langdon, Pat

AU - Bradley, Mike

AU - Politis, Ioannis

AU - Thompson, Simon

AU - Skrypchuk, Lee

AU - O-Donoghue, Jim

AU - Richardson, Joy

AU - Clark, Jed

AU - Roberts, Aaron

AU - Mouzakitis, Alex

AU - Stanton, Neville A.

N1 - 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.

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N2 - 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.

AB - 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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KW - Human factors

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KW - Usability

KW - Workload

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Kim J, Revell K, Langdon P, Bradley M, Politis I, Thompson S et al. Drivers’ interaction with, and perception toward semi-autonomous vehicles in naturalistic settings. In Ahram T, Karwowski W, Vergnano A, Leali F, Taiar R, editors, Intelligent Human Systems Integration 2020 : Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020) Integrating People and Intelligent Systems. 2020. p. 20-26. (Advances in Intelligent Systems and Computing). Epub 2020 Jan 22. doi: 10.1007/978-3-030-39512-4_4

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this