Journal of Intelligent and Connected Vehicles 2018, 1(3): 99-106 https://doi.org/10.1108/JICV-08-2018-0006

Research paper |

Open Access | Issue | Published: 13 November 2018

Influence of automated driving on driver’s own localization: a driving simulator study

Show Author's Information Hide Author's Information Ryuichi Umeno^¹(

), Makoto Itoh^¹, Satoshi Kitazaki^²

University of Tsukuba, Ibaraki, Japan

National Institute of Advanced Industrial Science and Technology, Tsukuba Center, Tsukuba Central, Ibaraki, Japan

Keywords:

Autonomous driving, Human–machine interfaces, Automated vehicles, Driver behaviors and assistance, Advanced driver assistant systems, Request to intervene

Cite this article:

Umeno R, Itoh M, Kitazaki S. Influence of automated driving on driver’s own localization: a driving simulator study. Journal of Intelligent and Connected Vehicles, 2018, 1(3): 99-106. https://doi.org/10.1108/JICV-08-2018-0006

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Abstract

Purpose

Level 3 automated driving, which has been defined by the Society of Automotive Engineers, may cause driver drowsiness or lack of situation awareness, which can make it difficult for the driver to recognize where he/she is. Therefore, the purpose of this study was to conduct an experimental study with a driving simulator to investigate whether automated driving affects the driver’s own localization compared to manual driving.

Design/methodology/approach

Seventeen drivers were divided into the automated operation group and manual operation group. Drivers in each group were instructed to travel along the expressway and proceed to the specified destinations. The automated operation group was forced to select a course after receiving a Request to Intervene (RtI) from an automated driving system.

Findings

A driver who used the automated operation system tended to not take over the driving operation correctly when a lane change is immediately required after the RtI.

Originality/value

This is a fundamental research that examined how the automated driving operation affects the driver's own localization. The experimental results suggest that it is not enough to simply issue an RtI, and it is necessary to tell the driver what kind of circumstances he/she is in and what they should do next through the HMI. This conclusion can be taken into consideration for engineers who design automatic driving vehicles.

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About this article

Influence of automated driving on driver’s own localization: a driving simulator study

Show Author's information Hide Author's Information Ryuichi Umeno^¹(

), Makoto Itoh^¹, Satoshi Kitazaki^²

University of Tsukuba, Ibaraki, Japan

National Institute of Advanced Industrial Science and Technology, Tsukuba Center, Tsukuba Central, Ibaraki, Japan

Abstract

Purpose

Design/methodology/approach

Findings

A driver who used the automated operation system tended to not take over the driving operation correctly when a lane change is immediately required after the RtI.

Originality/value

Keywords: Autonomous driving, Human–machine interfaces, Automated vehicles, Driver behaviors and assistance, Advanced driver assistant systems, Request to intervene

References(23)

Abbink, D.A., Mulder, M. and Boer, E.R. (2012), “Haptic shared control: smoothly shifting control authority?”, Cognition, Technology & Work, Vol. 14 No. 1, pp. 19-28, available at: https://doi.org/10.1007/s10111-011-0192-5

DOI Google Scholar

Brookhuis, K.A., de Waard, D.D. and Janssen, W.H. (2001), “Behavioural impacts of advanced driver assistance systems – an overview”, European Journal of Transport and Infrastructure Research, pp. 245-253.

Google Scholar

De Winter, J.C.F., Happee, R., Martens, M.H. and Stanton, N.A. (2014), “Effects of adaptive cruise control and highly automated driving on workload and situation awareness: a review of the empirical evidence”, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 27, pp. 196-217, available at: https://doi.org/10.1016/j.trf.2014.06.016

DOI Google Scholar

Endsley, M.R. and Kiris, E.O. (1995), “The out-of-the-loop performance problem and level of control in automation”, Human Factors: The Journal of the Human Factors and Ergonomics Society, Vol. 37 No. 2, pp. 381-394, available at: https://doi.org/10.1518/001872095779064555

DOI Google Scholar

Fagnant, D.J. and Kockelman, K. (2015), “Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations”, Transportation Research Part A, Vol. 77, pp. 167-181, available at: https://doi.org/10.1016/j.tra.2015.04.003

DOI Google Scholar

Freund, B., Colgrove, L.A., Burke, B.L. and McLeod, R. (2005), “Self-rated driving performance among elderly drivers referred for driving evaluation”, Accident Analysis & Prevention, Vol. 37 No. 4, pp. 613-618, available at: https://doi.org/10.1016/j.aap.2005.03.002

DOI Google Scholar

Fricke, N., Griesche, A., Schieben, A., Hasse, T. and Baumann, M. (2015), “Driver behavior following an automatic steering intervention”, Accident Analysis and Prevention, Vol. 83, pp. 190-196, available at: https://doi.org/10.1016/j.aap.2015.07.018

DOI Google Scholar

Gold, C., Dambock, D., Lorenz, L. and Bengler, K. (2013), “‘take over!’– how long does it take to get the driver back into the loop?”, in Proceedings of the Human Factors and Ergonomics Society, 57th annual meeting, 2013, pp. 1938-1942, available at: https://doi.org/10.1177/1541931213571433

Jamson, A.H., Merat, N., Carsten, O.M.J. and Lai, F.C.H. (2013), “Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions”, Transportation Research Part C: Emerging Technologies, Vol. 30, pp. 116-125, available at: https://doi.org/10.1016/j.trc.2013.02.008

DOI Google Scholar

Körber, M., Gold, C., Lechner, D. and Bengler, K. (2016), “The influence of age on the take-over of vehicle control in highly automated driving”, Transportation Research Part F, Vol. 39, pp. 19-32, available at: https://doi.org/10.1016/j.trf.2016.03.002

DOI Google Scholar

Larsson, P., Johansson, E., Söderman, M. and Thompson, D. (2015), “Interaction design for communicating system state and capabilities during automated highway driving”, Procedia Manufacturing, Vol. 3, pp. 2784-2791, available at: https://doi.org/10.1016/j.promfg.2015.07.735

DOI Google Scholar

Louw, T., Markkula, G., Boer, E., Madigan, R. and Carsten, O. (2017), “Coming back into the loop: drivers’ perceptual-motor performance in critical events after automated driving”, Accident Analysis and Prevention, Vol. 108, pp. 9-18, available at: https://doi.org/10.1016/j.aap.2017.08.011

DOI Google Scholar

Merat, N. and Jamson, A.H. (2009), “How do drivers behave in a highly automated car”, Proceedings of the Fifth International Driving Symposium on Human factors in Driving Assessment, Training and Vehicle Design, pp. 514-521, available at: https://doi.org/10.17077/drivingassessment.1365

DOI Google Scholar

Merat, N., Jamson, A.H., Lai, F.C.H., Daly, M. and Carsten, O.M.J. (2014), “Transition to manual: driver behavior when resuming control from a highly automated vehicle”, Transportation Research Part F: Traffic Psychology and Behavior, Vol. 26, pp. 1-9, available at: https://doi.org/10.1016/j.trf.2014.09.005

DOI Google Scholar

Naujoks, F., Mai, C. and Alexandra, N. (2014), “The effect of urgency of take-over requests during highly automated driving under distraction conditions”, Conference: 5th International Conference on Applied Human Factors and Ergonomics.

Naujoks, F., Purucker, C. and Neukum, A. (2016), “Secondary task engagement and vehicle automation – comparing the effects of different automation levels in an on-road experiment”, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 38, pp. 67-82, available at: https://doi.org/10.1016/j.trf.2016.01.011

DOI Google Scholar

New Energy and Industrial Technology Development Organization of Japan (2018), “FY2017 report strategic innovation promotion program (SIP) automated driving systems/large-scale field operational test/HMI” (in Japanese), available at: http://www.sip-adus.go.jp/file/121_s.pdf

Petermeijer, S.M., De Winter, J.C.F. and Bengler, K.J. (2016), “Vibrotactile displays: a survey with a view on highly automated driving”, IEEE Transactions on Intelligent Transportation Systems, Vol. 17 No. 4, pp. 897-907, available at: https://doi.org/10.1109/TITS.2015.2494873

DOI Google Scholar

Petermeijer, S., Bazilinskyy, P., Bengler, K. and De Winter, J.C.F. (2017), “Take-over again: investigating multimodal and directional TORs to get the driver back into the loop”, Applied Ergonomics, Vol. 62, pp. 204-215, available at: https://doi.org/10.1016/j.apergo.2017.02.023

DOI Google Scholar

SAE international (2016), “Taxonomy and definitions for terms related to driving automated systems for on-road motor vehicles”, J3016-201609.

Stanton, N.A. and Young, M.S. (2005), “Driver behaviour with adaptive cruise control”, Ergonomics, Vol. 48 No. 10, pp. 1294-1313, available at: https://doi.org/10.1080/00140130500252990

DOI Google Scholar

Tombaugh, T.N. (2004), “Trail making test a and B: normative data stratified by age and education”, Archives of Clinical Neuropsychology: The Official Journal of the National Academy of Neuropsychologists, Vol. 19 No. 2, pp. 203-214, available at: https://doi.org/10.1016/S0887-6177(03)00039-8

DOI Google Scholar

Zeeb, K., Buchner, A. and Schrauf, M. (2016), “Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving”, Accident Analysis & Prevention, Vol. 92, pp. 230-239, available at: https://doi.org/10.1016/j.aap.2016.04.002

DOI Google Scholar

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Publication history

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Publication history

Received: 13 August 2018

Revised: 14 October 2018

Accepted: 22 October 2018

Published: 13 November 2018

Issue date: February 2019

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Acknowledgements

This work was supported by Council for Science, Technology and Innovation (CSTI), Crossministerial Strategic Innovation Promotion Program (SIP), entitled "Human Factors and HMI Research for Automated Driving".

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