Determinants of take-over time from automated driving: A meta-analysis of 129 studies

An important question in automated driving research is how quickly drivers take over control of the vehicle in response to a critical event or a take-over request. Although a large number of studies have been performed, results vary strongly. In this study, we investigated mean take-over times from 129 studies with SAE level 2 automation or higher. We used three complementary approaches: (1) a within-study analysis, in which differences in mean take-over time were assessed for pairs of experimental conditions, (2) a between-study analysis, in which correlations between experimental conditions and mean take-over times were assessed, and (3) a linear mixed-effects model combining between-study and within-study effects. The three methods showed that a shorter mean take-over time is associated with a higher urgency of the situation, not using a handheld device, not performing a visual non-driving task, having experienced another take-over scenario before in the experiment, and receiving an auditory or vibrotactile take-over request as compared to a visual-only or no take-over request. A consistent effect of age was not observed. We also found the mean and standard deviation of the take-over time were highly correlated, indicating that the mean is predictive of variability. Our findings point to directions for new research, in particular concerning the distinction between drivers’ ability and motivation to take over, and the roles of urgency and prior experience. © 2019 Elsevier Ltd

[1]  Philipp Wintersberger,et al.  Let Me Finish before I Take Over: Towards Attention Aware Device Integration in Highly Automated Vehicles , 2018, AutomotiveUI.

[2]  Jing Feng,et al.  Age differences in the takeover of vehicle control and engagement in non-driving-related activities in simulated driving with conditional automation. , 2017, Accident; analysis and prevention.

[3]  Heikki Summala,et al.  Brake reaction times and driver behavior analysis , 2000 .

[4]  Paul Green,et al.  The Conclusion of a Driving Study About Warnings Depends upon How Response Time is Defined , 2017 .

[5]  Graham. Parkhurst,et al.  Manual Takeover and Handover of a Simulated Fully Autonomous Vehicle Within Urban and Extra-Urban Settings , 2017 .

[6]  Douglas G Bonett,et al.  Meta-analytic interval estimation for bivariate correlations. , 2008, Psychological methods.

[7]  L. Cronbach.  Beyond the Two Disciplines of Scientific Psychology. , 1975 .

[8]  Frederik Diederichs,et al.  Take-Over Requests for Automated Driving , 2015 .

[9]  Andrew L. Kun,et al.  Switching Back to Manual Driving: How Does it Compare to Simply Driving Away After Parking? , 2016, AutomotiveUI.

[10]  Neville A Stanton,et al.  Back to the future: Brake reaction times for manual and automated vehicles , 2007, Ergonomics.

[11]  Göran Falkman,et al.  Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving , 2013, AutomotiveUI.

[12]  L. Hedges,et al.  Fixed- and random-effects models in meta-analysis. , 1998 .

[13]  Klaus Bengler,et al.  How the Duration of Automated Driving Influences Take-Over Performance and Gaze Behavior , 2017 .

[14]  Klaus Bengler,et al.  Vibrotactile Displays: A Survey With a View on Highly Automated Driving , 2016, IEEE Transactions on Intelligent Transportation Systems.

[15]  William Payre,et al.  Impact of training and in-vehicle task performance on manual control recovery in an automated car , 2017 .

[16]  Bo Zhang,et al.  The Effect of See-Through Truck on Driver Monitoring Patterns and Responses to Critical Events in Truck Platooning , 2017 .

[17]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement , 2009, BMJ : British Medical Journal.

[18]  T. Salthouse.  When does age-related cognitive decline begin? , 2009, Neurobiology of Aging.

[19]  Marieke Hendrikje Martens,et al.  Driver headway choice: A comparison between driving simulator and real-road driving , 2014 .

[20]  Kelly Funkhouser,et al.  Putting the Brakes on Autonomous Vehicle Control , 2016 .

[21]  William Payre,et al.  Fully Automated Driving , 2016, Hum. Factors.

[22]  Natasha Merat,et al.  Engaging with Highly Automated Driving: To be or Not to be in the Loop? , 2017 .

[23]  Riender Happee,et al.  Modeling take-over performance in level 3 conditionally automated vehicles. , 2017, Accident; analysis and prevention.

[24]  Claes Wohlin,et al.  Systematic literature studies: Database searches vs. backward snowballing , 2012, Proceedings of the 2012 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement.

[25]  A. Hamish Jamson,et al.  Driving Simulators as Research Tools in Traffic Psychology , 2011 .

[26]  Riender Happee,et al.  Human factors of transitions in automated driving: A general framework and literature survey , 2016 .

[27]  K. Bengler,et al.  Literaturanalyse und Methodenauswahl zur Gestaltung von Systemen zum hochautomatisierten Fahren , 2015 .

[28]  Mark S. Young,et al.  Journey's End: Will Vehicle Automation Make Skilled Drivers Redundant? , 2000 .

[29]  Neville A. Stanton,et al.  Take-Over Time in Highly Automated Vehicles , 2018, Driver Reactions to Automated Vehicles.

[30]  Jonathan J Deeks,et al.  The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. , 2005, Journal of clinical epidemiology.

[31]  Klaus Bengler,et al.  Take-over again: Investigating multimodal and directional TORs to get the driver back into the loop. , 2017, Applied ergonomics.

[32]  Andrew Patterson,et al.  The Evolution of Embedded Architectures for the Next Generation of Vehicles , 2017, ATZelektronik worldwide.

[33]  Wendy Ju,et al.  Distraction Becomes Engagement in Automated Driving , 2015 .

[34]  Philipp Wintersberger,et al.  Workaholistic: on balancing typing- and handover-performance in automated driving , 2018, MobileHCI.

[35]  G. Box.  Science and Statistics , 1976 .

[36]  Toshio Ito,et al.  Time Required for Take-over from Automated to Manual Driving , 2016 .

[37]  Tobias Vogelpohl,et al.  Asleep at the automated wheel-Sleepiness and fatigue during highly automated driving. , 2019, Accident; analysis and prevention.

[38]  Neville A. Stanton,et al.  Rolling Out the Red (and Green) Carpet: Supporting Driver Decision Making in Automation-to-Manual Transitions , 2019, IEEE Transactions on Human-Machine Systems.

[39]  Louis Tijerina,et al.  The Effects of a Scheduled Driver Engagement Strategy in Automated Driving , 2015 .

[40]  Young Woo Kim,et al.  The effects of takeover request modalities on highly automated car control transitions. , 2019, Accident; analysis and prevention.

[41]  Changxu Wu,et al.  The Effects of Lead Time of Take-Over Request and Nondriving Tasks on Taking-Over Control of Automated Vehicles , 2018, IEEE Transactions on Human-Machine Systems.

[42]  Changxu Wu,et al.  The Effects of Vibration Patterns of Take-Over Request and Non-Driving Tasks on Taking-Over Control of Automated Vehicles , 2018, Int. J. Hum. Comput. Interact..

[43]  Klaus Bengler,et al.  The Influence of Non-driving Related Tasks on Driver Availability in the Context of Conditionally Automated Driving , 2018, Advances in Intelligent Systems and Computing.

[44]  Frederik Naujoks,et al.  Testing Scenarios for Human Factors Research in Level 3 Automated Vehicles , 2017 .

[45]  Christopher D. Wickens,et al.  In-Vehicle Glance Duration , 2007 .

[46]  Klaus Bengler,et al.  How Traffic Situations and Non-Driving Related Tasks Affect the Take-Over Quality in Highly Automated Driving , 2014 .

[47]  D. Shinar,et al.  Effects of uncertainty, transmission type, driver age and gender on brake reaction and movement time. , 2002, Journal of safety research.

[48]  Tal Oron-Gilad,et al.  The Effects of Continuous Driving-Related Feedback on Drivers’ Response to Automation Failures , 2017 .

[49]  Kathrin Zeeb,et al.  Why is steering not the same as braking? The impact of non-driving related tasks on lateral and longitudinal driver interventions during conditionally automated driving , 2017 .

[50]  Omer Tsimhoni,et al.  Using a Vibrotactile Seat for Facilitating the Handover of Control during Automated Driving , 2017, Int. J. Mob. Hum. Comput. Interact..

[51]  Kathrin Zeeb,et al.  What determines the take-over time? An integrated model approach of driver take-over after automated driving. , 2015, Accident; analysis and prevention.

[52]  Omer Tsimhoni,et al.  Haptic seat for automated driving: preparing the driver to take control effectively , 2015, AutomotiveUI.

[53]  Bo Zhang,et al.  Beyond mere take-over requests: The effects of monitoring requests on driver attention, take-over performance, and acceptance , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[54]  Marieke Hendrikje Martens,et al.  Transitions to manual control from highly automated driving in non-critical truck platooning scenarios , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[55]  Xin Zhang,et al.  Effect of Warning Levels on Drivers’ Decision-Making with the Self-driving Vehicle System , 2017 .

[56]  Mike Thelwall,et al.  Google Scholar, Web of Science, and Scopus: a systematic comparison of citations in 252 subject categories , 2018, J. Informetrics.

[57]  Neville A. Stanton,et al.  The effects of driving with different levels of unreliable automation on self-reported workload and secondary task performance , 2016 .

[58]  Klaus Bengler,et al.  How Automation Level and System Reliability Influence Driver Performance in a Cut-In Situation , 2017 .

[59]  Klaus Bengler,et al.  Does Shifting Between Conditionally and Partially Automated Driving Lead to a Loss of Mode Awareness , 2017 .

[60]  Alexandra Neukum,et al.  A Review of Non-driving-related Tasks Used in Studies on Automated Driving , 2017 .

[61]  Michael Weber,et al.  Autonomous Driving: Investigating the Feasibility of Bimodal Take-Over Requests , 2017, Int. J. Mob. Hum. Comput. Interact..

[62]  P. Fitts.  The information capacity of the human motor system in controlling the amplitude of movement. , 1954, Journal of experimental psychology.

[63]  Wolfgang Rosenstiel,et al.  Ready for Take-Over? A New Driver Assistance System for an Automated Classification of Driver Take-Over Readiness , 2017, IEEE Intelligent Transportation Systems Magazine.

[64]  Lutz Lorenz,et al.  Designing take over scenarios for automated driving , 2014 .

[65]  Nadja Schömig,et al.  Effects of Non-Driving Related Task Modalities on Takeover Performance in Highly Automated Driving , 2018, Hum. Factors.

[66]  Kathrin Zeeb,et al.  Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving. , 2016, Accident; analysis and prevention.

[67]  Yong Gu Ji,et al.  How we can measure the non-driving-task engagement in automated driving: Comparing flow experience and workload. , 2018, Applied ergonomics.

[68]  Susanne Boll,et al.  From reading to driving: priming mobile users for take-over situations in highly automated driving , 2018, MobileHCI.

[69]  Philip L. Roth,et al.  The Usefulness of Unit Weights in Creating Composite Scores , 2007 .

[70]  Philipp Wintersberger,et al.  Steer-By-WiFi: Lateral Vehicle Control for Take-Overs with Nomadic Devices , 2018, AutomotiveUI.

[71]  Ina Othersen,et al.  Methoden und Wechselwirkung Kognitive Übernahmefähigkeit nach einer pilotierten Fahrt , 2017 .

[72]  Susanne Boll,et al.  Assisting Drivers with Ambient Take-Over Requests in Highly Automated Driving , 2016, AutomotiveUI.

[73]  Louis Tijerina,et al.  Driver brake vs. steer response to sudden forward collision scenario in manual and automated driving modes , 2017 .

[74]  Frederik Naujoks,et al.  From partial and high automation to manual driving: Relationship between non-driving related tasks, drowsiness and take-over performance. , 2018, Accident; analysis and prevention.

[75]  Geert Molenberghs,et al.  Discussion of Likelihood Inference for Models with Unobservables: Another View , 2009 .

[76]  Klaus Bengler,et al.  How does relaxing posture influence take-over performance in an automated vehicle? , 2018, Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

[77]  Tobias Vogelpohl,et al.  Transitioning to manual driving requires additional time after automation deactivation , 2018 .

[78]  Michael Weber,et al.  From Car-Driver-Handovers to Cooperative Interfaces: Visions for Driver–Vehicle Interaction in Automated Driving , 2017 .

[79]  Tatyana Shamliyan,et al.  Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program. , 2011, Journal of clinical epidemiology.

[80]  Marc Green,et al.  "How Long Does It Take to Stop?" Methodological Analysis of Driver Perception-Brake Times , 2000 .

[81]  Moritz Körber,et al.  Introduction matters: Manipulating trust in automation and reliance in automated driving. , 2018, Applied ergonomics.

[82]  Phil Blythe,et al.  Investigation of older driver's takeover performance in highly automated vehicles in adverse weather conditions , 2018, IET Intelligent Transport Systems.

[83]  Klaus Bengler,et al.  The influence of age on the take-over of vehicle control in highly automated driving , 2016 .

[84]  Frank E. Pollick,et al.  Language-based multimodal displays for the handover of control in autonomous cars , 2015, AutomotiveUI.

[85]  Klaus Bengler,et al.  Taking Over Control From Highly Automated Vehicles in Complex Traffic Situations , 2016, Hum. Factors.

[86]  Alexis Paljic,et al.  Get ready for automated driving using Virtual Reality. , 2018, Accident; analysis and prevention.

[87]  M. Borenstein,et al.  Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments , 2006 .

[88]  Mascha C. van der Voort,et al.  Supporting the Changing Driver’s Task: Exploration of Interface Designs for Supervision and Intervention in Automated Driving , 2016 .

[89]  Josef F. Krems,et al.  Prior Familiarization With Takeover Requests Affects Drivers’ Takeover Performance and Automation Trust , 2017, Hum. Factors.

[90]  Neville A. Stanton,et al.  Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence , 2014 .

[91]  Joost C. F. de Winter,et al.  The expansion of Google Scholar versus Web of Science: a longitudinal study , 2013, Scientometrics.

[92]  Jürgen Schmidt,et al.  The Influence of Prolonged Conditionally Automated Driving on the Take-Over Ability of the Driver , 2017 .

[93]  C. Begg,et al.  Operating characteristics of a rank correlation test for publication bias. , 1994, Biometrics.

[94]  A. Zuur,et al.  Mixed Effects Models and Extensions in Ecology with R , 2009 .

[95]  R. Hogarth,et al.  Unit weighting schemes for decision making , 1975 .

[96]  Alexandra Neukum,et al.  Effect of different alcohol levels on take-over performance in conditionally automated driving. , 2018, Accident; analysis and prevention.

[97]  J. Theeuwes,et al.  Driving Simulator Validity: Some Considerations , 1996 .

[98]  Heinrich H. Bülthoff,et al.  Feel the Movement: Real Motion Influences Responses to Take-over Requests in Highly Automated Vehicles , 2018, CHI.

[99]  Willem Vlakveld,et al.  Situation awareness increases when drivers have more time to take over the wheel in a Level 3 automated car: A simulator study , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.

[100]  H. G. Osburn,et al.  A note on the sampling variance of the mean uncorrected correlation in meta-analysis and validity generalization. , 1992 .

[101]  Klaus Bengler,et al.  Utilization of Drivetime – Performing Non-Driving Related Tasks While Driving Highly Automated , 2015 .

[102]  Nadja Schömig,et al.  Secondary task engagement and disengagement in the context of highly automated driving , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.

[103]  Klaus Bengler,et al.  “Take over!” How long does it take to get the driver back into the loop? , 2013 .

[104]  F Dan Richard,et al.  Meta-analysis of raw mean differences. , 2003, Psychological methods.

[105]  J C F de Winter,et al.  Comparing spatially static and dynamic vibrotactile take-over requests in the driver seat. , 2017, Accident; analysis and prevention.

[106]  Philippe Fuchs,et al.  An Immersive Virtual Reality System for Semi-autonomous Driving Simulation: A Comparison between Realistic and 6-DoF Controller-based Interaction , 2017, ICCAE '17.

[107]  Frank E. Pollick,et al.  Using Multimodal Displays to Signify Critical Handovers of Control to Distracted Autonomous Car Drivers , 2017, Int. J. Mob. Hum. Comput. Interact..

[108]  Klaus Bengler,et al.  It's Out of Our Hands Now! Effects of Non-Driving Related Tasks During Highly Automated Driving on Drivers' Fatigue , 2017 .

[109]  Lee Skrypchuk,et al.  An Evaluation of Inclusive Dialogue-Based Interfaces for the Takeover of Control in Autonomous Cars , 2018, IUI.

[110]  Ji Hyun Yang,et al.  Takeover Requests in Simulated Partially Autonomous Vehicles Considering Human Factors , 2017, IEEE Transactions on Human-Machine Systems.