What determines the take-over time? An integrated model approach of driver take-over after automated driving

Zeeb, Kathrin; Buchner, Axel; Schrauf, Michael

doi:10.1016/j.aap.2015.02.023

Cited by 387 publications

(248 citation statements)

References 27 publications

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“…Current methods for estimating the safety benefits of such systems assume BRT-type driver responses to the warning (Van Auken et al, 2011;Kusano and Gabler, 2012;Erbsmehl and Schebdat, 2015;van Noort et al, 2015), whereas, as mentioned above, evidence from simulator studies (Lee et al, 2002;Ljung Aust et al, 2013) suggest that driver responses remain kinematics-dependent also in the presence of warnings 5 . The results presented here also seem relevant to current research on self-driving vehicles, where much effort is being spent on understanding the driver's response process when suddenly brought back into the control loop, for example because of a collision risk (Gold et al, 2013;Louw et al, 2015;Zeeb et al, 2015). What has been presented here points to a possible deeper understanding of how drivers make use of their perceptual input in critical situations, in terms of various perceptual mechanisms acting on visual looming information.…”

Section: Discussionmentioning

confidence: 94%

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies

Markkula

Engström

Lodin

et al. 2016

Accident Analysis & Prevention

129

106

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ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request.Note: This is a freely distributable postprint, which does not reflect final copyediting and typesetting of the published article, to be cited as: Markkula, G., Engström, J., Lodin, J., Bärgman, J., Victor, T., 2016. A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies. Accident Analysis & Prevention, xx(x), xxxx-xxxx. Abstract: Driver braking behavior was analyzed using time-series recordings from naturalistic rear-end conflicts (116 crashes and 241 near-crashes), including events with and without visual distraction among drivers of cars, heavy trucks, and buses. A simple piecewise linear model could be successfully fitted, per event, to the observed driver decelerations, allowing a detailed elucidation of when drivers initiated braking and how they controlled it. Most notably, it was found that, across vehicle types, driver braking behavior was strongly dependent on the urgency of the given rear-end scenario's kinematics, quantified in terms of visual looming of the lead vehicle on the driver's retina. In contrast with previous suggestions of brake reaction times (BRTs) of 1.5 s or more after onset of an unexpected hazard (e.g., brake light onset), it was found here that braking could be described as typically starting less than a second after the kinematic urgency reached certain threshold levels, with even faster reactions at higher urgencies. The rate at which drivers then increased their deceleration (towards a maximum) was also highly dependent on urgency. Probability distributions are provided that quantitatively capture these various patterns of kinematics-dependent behavioral response. Possible underlying mechanisms are suggested, including looming response thresholds and neural evidence accumulation. These accounts argue that a naturalistic braking response should not be thought of as a slow reaction to some single, researcher-defined "hazard onset", but instead as a relatively fast response to the visual looming cues that build up later on in the evolving traffic scenario.

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Section: Discussionmentioning

confidence: 94%

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies

Markkula

Engström

Lodin

et al. 2016

Accident Analysis & Prevention

129

106

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“…A recent study on partially automated driving argued that intermediate levels of automation in which the human driver is expected to monitor the automated driving system, may be hazardous because humans are not good at tasks that require vigilance for prolonged periods of time [14]. Empirical studies also confirmed the out-of-loop problem in driving automation by showing that accidents are likely to occur in situations where drivers suddenly have to resume manual control from an automated driving system [15][16][17].…”

Section: Introductionmentioning

confidence: 61%

“…It may cause serious accidents if the driver is not able to manage the situation due to loss of situation awareness or temporal inability to drive. Thus, the time to resume manual control after automated driving has attracted growing attention in recent years [17]. The temporal sequence of a take-over process after highly automated driving is illustrated in Figure 1.…”

Section: Transitions In Automated Drivingmentioning

confidence: 99%

“…The temporal sequence of a take-over process after highly automated driving is illustrated in Figure 1. The take-over time is specific for a particular set of situation variables such as traffic complexity, Human-Machine Interface (HMI) concept, and level of driver distraction, and driver variables, including age and driving skill [17].…”

Section: Transitions In Automated Drivingmentioning

confidence: 99%

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Situation Awareness and Transitions in Highly Automated Driving: A Framework and Mini Review

Son¹,

Park²

2017

J Ergonomics

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The human factors of transition in highly automated driving is becoming crucial, because transitions between the driver and the automation will remain a key element of automated driving until fully automated driving replace manual operation. This paper aims to suggest the framework to investigate human factors in transition of highly automated driving. The framework classifies transitions according to the transition initiator, control after transition, and situation awareness. Based on the framework, we retrieved previous studies and categorized their experimental designs. The inclusion criteria for the review were transitions which involved SAE level 3 automated driving and the research topics on driver behavior and/or performance during a transition. Finally, we interpreted the empirical studies on transitions using the proposed framework, and suggested areas for future research.

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“…However, previous works [4] have shown the difficulties encountered by the driver to quickly assess the situation and to make a proper decision; these difficulties are reminiscent of the "out of the loop syndrome", well known in the aviation domain. Beyond these general findings, various studies [5] [6] [7] indicate that drivers' take-over actions may be of a different type and quality depending upon contextual variables (e.g., traffic density, action possibilities, HMI) as well as personal factors (type of secondary tasks, drivers' distraction, drivers' gaze behaviour during automated driving). In line with these works, the present article presents an exploratory study aimed at characterizing drivers' take-over behaviours on the basis of two types of data: quantitative ones (vehicle data) and qualitative ones (user experience expressed by the drivers).…”

Section: Introductionmentioning

confidence: 99%

Automated vehicles: Multivariate analysis of drivers' take-over behaviour

Saïd

Chauvin

2017

2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

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Abstract-This paper presents a study carried out within the context of Level 3 automated driving. It aims to characterize drivers take-over behaviour by exploring quantitative data related to the driver's performance (vehicle data) and qualitative data (user experience expressed in post-activity interviews). For this purpose, several techniques of multivariate analysis were used such as clustering of variables and units. This study illustrates that user experience is associated with the magnitude of actions related to lateral and longitudinal control; positive experience being associated with smoother actions, whereas negative feelings were associated with rougher ones. Furthermore, two main driver's profiles emerged; they are described by two latent variables, one of which is quality of the actions. Future research will investigate the determinants of these profiles.

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What determines the take-over time? An integrated model approach of driver take-over after automated driving

Cited by 387 publications

References 27 publications

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies

Situation Awareness and Transitions in Highly Automated Driving: A Framework and Mini Review

Automated vehicles: Multivariate analysis of drivers' take-over behaviour

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