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arxiv: 2605.00556 · v1 · submitted 2026-05-01 · 💻 cs.HC · cs.AI· cs.CY· cs.RO

Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving

Ashwin George , Lucas Elbert Suryana , Lorenzo Flipse , Bart van Arem , David A. Abbink , Simeon Craig Calvert , Luciano Cavalcante Siebert , Arkady Zgonnikov This is my paper

Pith reviewed 2026-05-09 18:49 UTC · model grok-4.3

classification 💻 cs.HC cs.AIcs.CYcs.RO
keywords meaningful human controlpartially automated drivingsteering torque conflictsreaction timesdriver perceptionhaptic shared controlsimulator studyhuman factors
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0 comments X

The pith

Steering torque conflicts decrease when drivers feel the automation understands their intent in partial driving.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tests whether behavioural measures and perception scores can evaluate meaningful human control in partially automated driving. In a simulator with silent failures, twenty-four drivers interacted under haptic shared control and traded control modes while researchers recorded steering torques, reaction times, and post-trial survey responses. Confirmatory results showed a significant negative correlation between perceived automation understanding and steering conflicts, while exploratory results showed a positive correlation between reaction times and perceived sufficient control. Qualitative comments linked intention mismatches and input resistance to lower perceived control. These links matter because drivers remain responsible yet risk disengaging without a felt sense of control.

Core claim

The confirmatory analysis showed a significant negative correlation between the perception of the automated vehicle understanding the driver and conflict in steering torques. An exploratory analysis also revealed a positive correlation between reaction times and the perception of sufficient control. Qualitative feedback revealed that mismatches in intentions, lack of safety, and resistance to driver inputs reduce perceived meaningful human control, while subtle haptic guidance aligned with driver intent improves it.

What carries the argument

The tested correlations between telemetry-derived behavioural metrics (steering torque conflicts and reaction times) and subjective perception scores of automation understanding and sufficient control, drawn from hypothesised properties of meaningful human control systems.

If this is right

  • Minimising steering conflicts through better intent alignment will raise drivers' perception that the automation understands them.
  • Allowing drivers time to react may increase their sense of having sufficient control.
  • Subtle haptic guidance aligned with driver intent will support higher perceived meaningful human control.
  • Transparent communication of automation intent and context-sensitive authority allocation will reduce intention mismatches and strengthen overall control.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • These metrics could support real-time vehicle systems that adapt automation behaviour to maintain driver engagement.
  • The approach of linking objective behaviour to subjective perception could apply to human oversight in other automated domains such as aviation.
  • On-road studies would test whether the simulator correlations hold under actual traffic and failure conditions.

Load-bearing premise

The selected behavioural metrics and perception scores accurately reflect the abstract construct of meaningful human control, and simulator results with silent failures apply to real driving.

What would settle it

A replication study that finds no negative correlation between perceived automation understanding and steering torque conflicts would undermine the proposed evaluation method.

read the original abstract

Partial driving automation creates a tension: drivers remain legally responsible for vehicle behaviour, yet their active control is significantly reduced. This reduction undermines the engagement and sense of agency needed to intervene safely. Meaningful human control (MHC) has been proposed as a normative framework to address this tension. However, empirical methods for evaluating whether existing systems actually provide MHC remain underdeveloped. In this study, we investigated the extent to which drivers experience MHC when interacting with partially automated driving systems. Twenty-four drivers completed a simulator study involving silent automation failures under two modes - haptic shared control (HSC) and traded control (TC). We derived behavioural metrics from telemetry data, subjective perception scores from post-trial surveys and used them to test hypothesised relations between them derived from the properties of systems under MHC. The confirmatory analysis showed a significant negative correlation between the perception of the automated vehicle (AV) understanding the driver and conflict in steering torques. An exploratory analysis also revealed a surprising positive correlation between reaction times and the perception of sufficient control. Qualitative feedback from open-ended post-experiment questionnaires revealed that mismatches in intentions between the driver and automation, lack of safety, and resistance to driver inputs contribute to the reduction of perceived MHC, while subtle haptic guidance aligned with driver intent had a positive effect. These findings suggest that future designs should prioritise effortless driver interventions, transparent communication of automation intent, and context-sensitive authority allocation to strengthen meaningful human control in partially automated driving.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript reports on a simulator-based study with 24 participants examining meaningful human control (MHC) in partially automated driving. Drivers experienced silent automation failures in haptic shared control (HSC) and traded control (TC) modes. Behavioral metrics derived from telemetry data (steering torque conflicts, reaction times) were correlated with subjective perception scores from post-trial surveys. The study found a significant negative correlation between perceived AV understanding of the driver and steering torque conflicts (confirmatory), a positive correlation between reaction times and perceived sufficient control (exploratory), and qualitative themes from questionnaires on intention mismatches, safety, and haptic guidance.

Significance. If the reported correlations are robust and the metrics appropriately capture MHC constructs, this work provides valuable empirical evidence linking behavioral telemetry to perceptual aspects of control in automated driving. It offers concrete design recommendations for improving MHC through better intention alignment and transparent automation behavior, advancing the application of the MHC framework beyond normative theory to practical evaluation methods in human-computer interaction for vehicles.

major comments (2)
  1. [Methods and Results] The central claim that the chosen behavioural metrics (steering torque conflicts and reaction times) and subjective scores validly capture MHC properties rests on hypothesized relations without detailed prior validation or explicit mapping to specific MHC normative properties. This weakens the interpretation of the confirmatory negative correlation as direct evidence for MHC evaluation methods.
  2. [Results] The exploratory positive correlation between reaction times and perceived sufficient control is presented as surprising; the manuscript should provide a more detailed discussion of possible mechanisms or confounds (e.g., individual differences in trust or attention) and ensure it is not over-weighted relative to the pre-specified confirmatory analysis.
minor comments (2)
  1. [Abstract] The abstract states 'significant negative correlation' but omits the actual correlation coefficient, p-value, and sample details; adding these would make the key finding more precise and verifiable.
  2. [Discussion] The simulator setup with silent failures is appropriately scoped as a controlled probe, but the discussion of limitations could more explicitly address potential differences in driver behavior compared to real-world noisy environments or non-silent failures.

Simulated Author's Rebuttal

2 responses · 0 unresolved

Thank you for the constructive feedback on our manuscript. We appreciate the referee's recognition of the study's potential to link behavioral metrics with perceptual aspects of meaningful human control (MHC) in partial automation. We have addressed both major comments below with targeted revisions that clarify our approach without overclaiming the results. These changes will strengthen the paper's methodological transparency and interpretive balance.

read point-by-point responses

  1. Referee: [Methods and Results] The central claim that the chosen behavioural metrics (steering torque conflicts and reaction times) and subjective scores validly capture MHC properties rests on hypothesized relations without detailed prior validation or explicit mapping to specific MHC normative properties. This weakens the interpretation of the confirmatory negative correlation as direct evidence for MHC evaluation methods.

    Authors: We acknowledge that while the hypotheses were derived from MHC normative properties (as outlined in the Introduction and Methods, drawing on established MHC literature regarding intention alignment, authority, and transparency), an explicit mapping was not presented in tabular or subsection form. In the revised manuscript, we will add a new subsection (likely in Methods) that explicitly maps each metric and subjective score to specific MHC properties, with citations to the normative framework. This will make the theoretical grounding more visible and support a stronger interpretation of the confirmatory correlation. We note that the study is exploratory in nature regarding MHC evaluation methods and does not claim prior empirical validation of the metrics; the revisions will clarify this scope without altering the core findings. revision: yes

  2. Referee: [Results] The exploratory positive correlation between reaction times and perceived sufficient control is presented as surprising; the manuscript should provide a more detailed discussion of possible mechanisms or confounds (e.g., individual differences in trust or attention) and ensure it is not over-weighted relative to the pre-specified confirmatory analysis.

    Authors: We agree that the exploratory nature of this correlation requires more careful handling. In the revised Results and Discussion sections, we will expand the analysis of potential mechanisms and confounds, including how higher perceived control might lead drivers to adopt a more cautious verification strategy before intervening (increasing reaction times), as well as individual differences in trust, attention allocation, and risk perception. We will also add explicit language underscoring that this is exploratory, not pre-specified, and should not be weighted equally with the confirmatory analysis. These additions will prevent over-interpretation while providing readers with a balanced view of the finding. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper reports results from a new simulator experiment with 24 participants, deriving behavioral metrics (steering torque conflict, reaction times) from telemetry data and subjective perception scores from post-trial surveys, then testing hypothesized correlations against properties of meaningful human control drawn from the normative framework. The confirmatory negative correlation and exploratory positive correlation are presented as statistical findings from fresh data, accompanied by qualitative themes, with no equations, self-definitional constructs, fitted parameters renamed as predictions, or load-bearing self-citations that reduce any central claim to its own inputs by construction. The analysis chain is self-contained empirical hypothesis testing.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The paper relies on standard statistical methods and domain assumptions about simulation validity rather than introducing new free parameters or entities.

axioms (2)
  • standard math Statistical assumptions for correlation analysis (e.g., normality, independence of observations)
    Used in confirmatory and exploratory analyses of correlations.
  • domain assumption The simulator environment accurately models real partial automation interactions
    Central to generalizing findings to actual driving.

pith-pipeline@v0.9.0 · 5599 in / 1345 out tokens · 55545 ms · 2026-05-09T18:49:28.739141+00:00 · methodology

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Reference graph

Works this paper leans on

68 extracted references · 68 canonical work pages

  1. [1]

    Towards a dynamic balance between humans and automation: Authority, ability, responsibility and control in shared and cooperative control situations,

    F. Flemisch, M. Heesen, T. Hesse, J. Kelsch, A. Schieben, and J. Beller, “Towards a dynamic balance between humans and automation: Authority, ability, responsibility and control in shared and cooperative control situations,”Cognition, Technology & Work, vol. 14, pp. 3–18, Mar. 2012

    work page 2012

  2. [2]

    Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid,

    N. Beckers, L. C. Siebert, M. Bruijnes, C. Jonker, and D. Abbink, “Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid,”Scientific Reports, vol. 12, p. 16193, Sept. 2022

    work page 2022

  3. [3]

    Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations,

    D. J. Fagnant and K. Kockelman, “Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations,”Transportation Research Part A: Policy and Practice, vol. 77, pp. 167–181, 2015

    work page 2015

  4. [4]

    Comparison of waymo rider-only crash rates by crash type to human benchmarks at 56.7 million miles,

    K. D. Kusano, J. M. Scanlon, Y. H. Chen, T. L. McMurry, T. Gode, and T. Victor, “Comparison of waymo rider-only crash rates by crash type to human benchmarks at 56.7 million miles,”Traffic Injury Prevention, pp. 1–13, 2025

    work page 2025

  5. [5]

    Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems,

    SAE International, “Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems,” Standard J3016_202104, 2021

    work page 2021

  6. [6]

    Autonomous driving systems: A preliminary naturalistic study of the tesla model s,

    M. R. Endsley, “Autonomous driving systems: A preliminary naturalistic study of the tesla model s,”Journal of Cognitive Engineering and Decision Making, vol. 11, no. 3, pp. 225–238, 2017

    work page 2017

  7. [7]

    Automation complacency on the road,

    Y. Chu and P. Liu, “Automation complacency on the road,”Ergonomics, vol. 66, no. 11, pp. 1730–1749, 2023

    work page 2023

  8. [8]

    Human factors of highly automated driving: results from the easy and citymobil projects,

    N. Merat, H. A. Jamson, F. Lai, and O. Carsten, “Human factors of highly automated driving: results from the easy and citymobil projects,” inRoad vehicle automation, pp. 113–125, Springer, 2014

    work page 2014

  9. [9]

    What is the sense of agency and why does it matter?,

    J. W. Moore, “What is the sense of agency and why does it matter?,”Frontiers in psychology, vol. 7, p. 1272, 2016

    work page 2016

  10. [10]

    The sense of agency in emerging technologies for human–computer integration: A review,

    P. Cornelio, P. Haggard, K. Hornbaek, O. Georgiou, J. Bergström, S. Subramanian, and M. Obrist, “The sense of agency in emerging technologies for human–computer integration: A review,”Frontiers in Neuroscience, vol. 16, p. 949138, 2022

    work page 2022

  11. [11]

    Automation technology and sense of control: a window on human agency,

    B. Berberian, J.-C. Sarrazin, P. Le Blaye, and P. Haggard, “Automation technology and sense of control: a window on human agency,”PloS one, vol. 7, no. 3, p. e34075, 2012

    work page 2012

  12. [12]

    Experience of agency and sense of responsibility,

    G. Moretto, E. Walsh, and P. Haggard, “Experience of agency and sense of responsibility,”Consciousness and cognition, vol. 20, no. 4, pp. 1847–1854, 2011

    work page 2011

  13. [13]

    The responsibility gap: Ascribing responsibility for the actions of learning automata,

    A. Matthias, “The responsibility gap: Ascribing responsibility for the actions of learning automata,”Ethics and information technology, vol. 6, pp. 175–183, 2004

    work page 2004

  14. [14]

    Four responsibility gaps with artificial intelligence: Why they matter and how to address them,

    F. Santoni de Sio and G. Mecacci, “Four responsibility gaps with artificial intelligence: Why they matter and how to address them,”Philosophy & Technology, vol. 34, no. 4, pp. 1057–1084, 2021. 22 Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving

    work page 2021

  15. [15]

    Gaps in the control of automated vehicles on roads,

    S. C. Calvert, B. van Arem, D. D. Heikoop, M. Hagenzieker, G. Mecacci, and F. S. de Sio, “Gaps in the control of automated vehicles on roads,”IEEE intelligent transportation systems magazine, vol. 13, no. 4, pp. 146–153, 2020

    work page 2020

  16. [16]

    Meaningful human control over autonomous systems: A philosophical account,

    F. Santoni de Sio and J. Van den Hoven, “Meaningful human control over autonomous systems: A philosophical account,”Frontiers in Robotics and AI, vol. 5, p. 15, 2018

    work page 2018

  17. [17]

    Meaningful human control: Actionable properties for AI system development,

    L. Cavalcante Siebert, M. L. Lupetti, E. Aizenberg, N. Beckers, A. Zgonnikov, H. Veluwenkamp, D. Abbink, E. Giaccardi, G.-J. Houben, C. M. Jonker, J. van den Hoven, D. Forster, and R. L. Lagendijk, “Meaningful human control: Actionable properties for AI system development,”AI and Ethics, May 2022

    work page 2022

  18. [18]

    Principles and framework for the operationalisation of meaningful human control over autonomous systems,

    S. C. Calvert, “Principles and framework for the operationalisation of meaningful human control over autonomous systems,”Science and Engineering Ethics, vol. 31, no. 5, p. 27, 2025

    work page 2025

  19. [19]

    Meaningful human control as reason-responsiveness: the case of dual-mode vehicles,

    G. Mecacci and F. Santoni de Sio, “Meaningful human control as reason-responsiveness: the case of dual-mode vehicles,”Ethics and Information Technology, vol. 22, no. 2, pp. 103–115, 2020

    work page 2020

  20. [20]

    Meaningful human control of partially automateddrivingsystems: Insightsfrominterviewswithteslausers,

    L. E. Suryana, S. Nordhoff, S. Calvert, A. Zgonnikov, and B. van Arem, “Meaningful human control of partially automateddrivingsystems: Insightsfrominterviewswithteslausers,”TransportationResearchPartF:TrafficPsychology and Behaviour, vol. 113, pp. 213–236, 2025

    work page 2025

  21. [21]

    A lack of meaningful human control for automated vehicles: Pressing issues for deployment and regulation,

    S. C. Calvert and A. Zgonnikov, “A lack of meaningful human control for automated vehicles: Pressing issues for deployment and regulation,”Frontiers in Future Transportation, vol. 6, p. 1534157, 2025

    work page 2025

  22. [22]

    Meaningful human control and variable autonomy in human-robot teams for firefighting,

    R. S. Verhagen, M. A. Neerincx, and M. L. Tielman, “Meaningful human control and variable autonomy in human-robot teams for firefighting,”Frontiers in Robotics and AI, vol. 11, p. 1323980, 2024

    work page 2024

  23. [23]

    A topology of shared control systems—finding common ground in diversity,

    D. A. Abbink, T. Carlson, M. Mulder, J. C. De Winter, F. Aminravan, T. L. Gibo, and E. R. Boer, “A topology of shared control systems—finding common ground in diversity,”IEEE Transactions on Human-Machine Systems, vol. 48, no. 5, pp. 509–525, 2018

    work page 2018

  24. [24]

    The effect of a haptic guidance steering system on fatigue-related driver behavior,

    Z. Wang, R. Zheng, T. Kaizuka, K. Shimono, and K. Nakano, “The effect of a haptic guidance steering system on fatigue-related driver behavior,”IEEE Transactions on Human-Machine Systems, vol. 47, no. 5, pp. 741–748, 2017

    work page 2017

  25. [25]

    Shared control driver assistance system based on driving intention and situation assessment,

    M. Li, H. Cao, X. Song, Y. Huang, J. Wang, and Z. Huang, “Shared control driver assistance system based on driving intention and situation assessment,”IEEE Transactions on Industrial Informatics, vol. 14, no. 11, pp. 4982–4994, 2018

    work page 2018

  26. [26]

    Shared control versus traded control in driving: a debate around automation pitfalls,

    J. C. de Winter, S. M. Petermeijer, and D. A. Abbink, “Shared control versus traded control in driving: a debate around automation pitfalls,”Ergonomics, vol. 66, no. 10, pp. 1494–1520, 2023

    work page 2023

  27. [27]

    Joan: A framework for human-automated vehicle interaction experiments in a virtual reality driving simulator,

    N. Beckers, O. Siebinga, J. Giltay, and A. van der Kraan, “Joan: A framework for human-automated vehicle interaction experiments in a virtual reality driving simulator,”Journal of Open Source Software, vol. 8, no. 82, p. 4250, 2023

    work page 2023

  28. [28]

    Carla: An open urban driving simulator,

    A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun, “Carla: An open urban driving simulator,” inConference on robot learning, pp. 1–16, PMLR, 2017

    work page 2017

  29. [29]

    Four design choices for haptic shared control,

    M. R. van Paassen, R. P. Boink, D. A. Abbink, M. Mulder, and M. Mulder, “Four design choices for haptic shared control,” inAdvances in Aviation Psychology, Volume 2, pp. 237–254, Routledge, 2017

    work page 2017

  30. [30]

    A meaningful human control perspective on user perception of partially automated driving systems: a case study of tesla users,

    L. E. Suryana, S. Nordhoff, S. C. Calvert, A. Zgonnikov, and B. Van Arem, “A meaningful human control perspective on user perception of partially automated driving systems: a case study of tesla users,” in2024 IEEE intelligent vehicles symposium (IV), pp. 409–416, IEEE, 2024

    work page 2024

  31. [31]

    Understanding and reducing conflicts between driver and haptic shared control,

    R. Boink, M. M. Van Paassen, M. Mulder, and D. A. Abbink, “Understanding and reducing conflicts between driver and haptic shared control,” in2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1510–1515, IEEE, 2014

    work page 2014

  32. [32]

    A predictive control framework for torque-based steering assistance to improve safety in highway driving,

    Z. Ercan, A. Carvalho, H. E. Tseng, M. Gökaşan, and F. Borrelli, “A predictive control framework for torque-based steering assistance to improve safety in highway driving,”Vehicle system dynamics, vol. 56, no. 5, pp. 810–831, 2018

    work page 2018

  33. [33]

    Analysis of human-machine cooperation when driving with different degrees of haptic shared control,

    F. Mars, M. Deroo, and J.-M. Hoc, “Analysis of human-machine cooperation when driving with different degrees of haptic shared control,”IEEE transactions on haptics, vol. 7, no. 3, pp. 324–333, 2014

    work page 2014

  34. [34]

    A steering wheel reversal rate metric for assessing effects of visual and cognitive secondary task load,

    G. Markkula and J. Engström, “A steering wheel reversal rate metric for assessing effects of visual and cognitive secondary task load,” inProceedings of the 13th ITS World Congress, Leeds, 2006

    work page 2006

  35. [35]

    A fast calculation of two-dimensional Time-to-Collision,

    Y. Jiao, “A fast calculation of two-dimensional Time-to-Collision,” Mar. 2023

    work page 2023

  36. [36]

    A coefficient of agreement for nominal scales,

    J. Cohen, “A coefficient of agreement for nominal scales,”Educational and psychological measurement, vol. 20, no. 1, pp. 37–46, 1960

    work page 1960

  37. [37]

    Computing inter-rater reliability and its variance in the presence of high agreement,

    K. L. Gwet, “Computing inter-rater reliability and its variance in the presence of high agreement,”British Journal of Mathematical and Statistical Psychology, vol. 61, no. 1, pp. 29–48, 2008

    work page 2008

  38. [38]

    Using thematic analysis in psychology,

    V. Braun and V. Clarke, “Using thematic analysis in psychology,”Qualitative research in psychology, vol. 3, no. 2, pp. 77–101, 2006. 23 Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving

    work page 2006

  39. [39]

    Consensual qualitative research: An update,

    C. E. Hill, B. J. Thompson, and E. N. Williams, “Consensual qualitative research: An update,”Journal of Counseling Psychology, vol. 52, no. 2, pp. 196–205, 2005

    work page 2005

  40. [40]

    Coding in-depth semistructured interviews: Problems of unitization and intercoder reliability and agreement,

    J. L. Campbell, C. Quincy, J. Osserman, and O. K. Pedersen, “Coding in-depth semistructured interviews: Problems of unitization and intercoder reliability and agreement,”Sociological methods & research, vol. 42, no. 3, pp. 294–320, 2013

    work page 2013

  41. [41]

    High agreement but low kappa: I. the problems of two paradoxes,

    A. R. Feinstein and D. V. Cicchetti, “High agreement but low kappa: I. the problems of two paradoxes,”Journal of clinical epidemiology, vol. 43, no. 6, pp. 543–549, 1990

    work page 1990

  42. [42]

    Fully automated driving: Impact of trust and practice on manual control recovery,

    W. Payre, J. Cestac, and P. Delhomme, “Fully automated driving: Impact of trust and practice on manual control recovery,”Human factors, vol. 58, no. 2, pp. 229–241, 2016

    work page 2016

  43. [43]

    Autonomous vehicles: disengagements, accidents and reaction times,

    V. V. Dixit, S. Chand, and D. J. Nair, “Autonomous vehicles: disengagements, accidents and reaction times,”PLoS one, vol. 11, no. 12, p. e0168054, 2016

    work page 2016

  44. [44]

    The sense of agency in perception, behaviour and human–machine interactions,

    W. Wen and H. Imamizu, “The sense of agency in perception, behaviour and human–machine interactions,”Nature Reviews Psychology, vol. 1, pp. 211–222, Feb. 2022

    work page 2022

  45. [45]

    Automation Technology and Sense of Control: A Window on Human Agency,

    B. Berberian, J.-C. Sarrazin, P. Le Blaye, and P. Haggard, “Automation Technology and Sense of Control: A Window on Human Agency,”PLoS ONE, vol. 7, p. e34075, Mar. 2012

    work page 2012

  46. [46]

    Attenuation of Self-Generated Tactile Sensations Is Predictive, not Postdictive,

    P. M. Bays, J. R. Flanagan, and D. M. Wolpert, “Attenuation of Self-Generated Tactile Sensations Is Predictive, not Postdictive,”PLoS Biology, vol. 4, p. e28, Jan. 2006

    work page 2006

  47. [47]

    How voluntary actions modulate time perception,

    D. Wenke and P. Haggard, “How voluntary actions modulate time perception,”Experimental Brain Research, vol. 196, pp. 311–318, July 2009

    work page 2009

  48. [48]

    Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions,

    A. George, L. C. Siebert, D. A. Abbink, and A. Zgonnikov, “Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions,” May 2025

    work page 2025

  49. [49]

    Vision Zero: On a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput,

    S. Shalev-Shwartz, S. Shammah, and A. Shashua, “Vision Zero: On a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput,” Jan. 2019

    work page 2019

  50. [50]

    Learning responsibility allocations for multi-agent interactions: A differen- tiable optimization approach with control barrier functions,

    I. Remy, D. Fridovich-Keil, and K. Leung, “Learning responsibility allocations for multi-agent interactions: A differen- tiable optimization approach with control barrier functions,” Oct. 2024

    work page 2024

  51. [51]

    Conceptualising user comfort in automated driving: Findings from an expert group workshop,

    C. Peng, S. Horn, R. Madigan, C. Marberger, J. D. Lee, J. Krems, M. Beggiato, R. Romano, C. Wei, E. Wooldridge, R. Happee, M. Hagenzieker, and N. Merat, “Conceptualising user comfort in automated driving: Findings from an expert group workshop,”Transportation Research Interdisciplinary Perspectives, vol. 24, p. 101070, Mar. 2024

    work page 2024

  52. [52]

    Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories,

    K. Chen, Z. Li, P. Liu, V. L. Knoop, Y. Han, and Y. Jiao, “Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories,”Accident Analysis & Prevention, vol. 203, p. 107622, Aug. 2024

    work page 2024

  53. [53]

    Towards common ethical and safe ‘behaviour’ standards for automated vehicles,

    E. Papadimitriou, H. Farah, G. van de Kaa, F. Santoni de Sio, M. Hagenzieker, and P. van Gelder, “Towards common ethical and safe ‘behaviour’ standards for automated vehicles,”Accident Analysis & Prevention, vol. 174, p. 106724, Sept. 2022

    work page 2022

  54. [54]

    (mis-) use of standard autopilot and full self-driving (fsd) beta: Results from interviews with users of tesla’s fsd beta,

    S. Nordhoff, J. D. Lee, S. C. Calvert, S. Berge, M. Hagenzieker, and R. Happee, “(mis-) use of standard autopilot and full self-driving (fsd) beta: Results from interviews with users of tesla’s fsd beta,”Frontiers in psychology, vol. 14, p. 1101520, 2023

    work page 2023

  55. [55]

    Understanding trust and acceptance of automated vehicles: An exploratory simulator study of transfer of control between automated and manual driving,

    L. J. Molnar, L. H. Ryan, A. K. Pradhan, D. W. Eby, R. M. S. Louis, and J. S. Zakrajsek, “Understanding trust and acceptance of automated vehicles: An exploratory simulator study of transfer of control between automated and manual driving,”Transportation research part F: traffic psychology and behaviour, vol. 58, pp. 319–328, 2018

    work page 2018

  56. [56]

    Flemisch, D

    F. Flemisch, D. A. Abbink, M. Itoh, M.-P. Pacaux-Lemoine, and G. Weßel, “Joining the blunt and the pointy end of the spear: Towards a common framework of joint action, human–machine cooperation, cooperative guidance and control, shared, traded and supervisory control,”Cognition, Technology & Work, vol. 21, pp. 555–568, Nov. 2019

    work page 2019

  57. [57]

    Haptic shared control: smoothly shifting control authority?,

    D. A. Abbink, M. Mulder, and E. R. Boer, “Haptic shared control: smoothly shifting control authority?,”Cognition, Technology & Work, vol. 14, pp. 19–28, 2012

    work page 2012

  58. [58]

    A conceptual control system description of cooperative and automated driving in mixed urban traffic with meaningful human control for design and evaluation,

    S. C. Calvert and G. Mecacci, “A conceptual control system description of cooperative and automated driving in mixed urban traffic with meaningful human control for design and evaluation,”IEEE Open Journal of Intelligent Transportation Systems, vol. 1, pp. 147–158, 2020

    work page 2020

  59. [59]

    What Is the Sense of Agency and Why Does it Matter?,

    J. W. Moore, “What Is the Sense of Agency and Why Does it Matter?,”Frontiers in Psychology, vol. 7, Aug. 2016

    work page 2016

  60. [60]

    Investigating the relationship between assisted driver’s SoA and EEG,

    S. Yun, W. Wen, Q. An, S. Hamasaki, H. Yamakawa, Y. Tamura, A. Yamashita, and H. Asama, “Investigating the relationship between assisted driver’s SoA and EEG,” inConverging Clinical and Engineering Research on Neuroreha- bilitation III(L. Masia, S. Micera, M. Akay, and J. L. Pons, eds.), (Cham), pp. 1039–1043, Springer International Publishing, 2019. 24 L...

    work page 2019

  61. [61]

    The sense of agency in emerging technologies for human–computer integration: A review,

    P. Cornelio, P. Haggard, K. Hornbaek, O. Georgiou, J. Bergström, S. Subramanian, and M. Obrist, “The sense of agency in emerging technologies for human–computer integration: A review,”Frontiers in Neuroscience, vol. 16, Sept. 2022

    work page 2022

  62. [62]

    Deceleration Assistance Mitigated the Trade-off Between Sense of Agency and Driving Performance,

    W. Wen, S. Yun, A. Yamashita, B. D. Northcutt, and H. Asama, “Deceleration Assistance Mitigated the Trade-off Between Sense of Agency and Driving Performance,”Frontiers in Psychology, vol. 12, June 2021

    work page 2021

  63. [63]

    Theoretical, Measured, and Subjective Responsibility in Aided Decision Making,

    N. Douer and J. Meyer, “Theoretical, Measured, and Subjective Responsibility in Aided Decision Making,”ACM Transactions on Interactive Intelligent Systems, vol. 11, pp. 1–37, Mar. 2021

    work page 2021

  64. [64]

    Judging One’s Own or Another Person’s Responsibility in Interactions With Automation,

    N. Douer and J. Meyer, “Judging One’s Own or Another Person’s Responsibility in Interactions With Automation,” Human Factors: The Journal of the Human Factors and Ergonomics Society, vol. 64, pp. 359–371, Mar. 2022

    work page 2022

  65. [65]

    Let Me Take Over: Variable Autonomy for Meaningful Human Control,

    L. Methnani, A. Aler Tubella, V. Dignum, and A. Theodorou, “Let Me Take Over: Variable Autonomy for Meaningful Human Control,”Frontiers in Artificial Intelligence, vol. 4, p. 737072, Sept. 2021

    work page 2021

  66. [66]

    Shared control versus traded control in driving: A debate around automation pitfalls,

    J. C. F. De Winter, S. M. Petermeijer, and D. A. Abbink, “Shared control versus traded control in driving: A debate around automation pitfalls,”Ergonomics, vol. 66, pp. 1494–1520, Oct. 2023

    work page 2023

  67. [67]

    Mitigating undesirable emergent behavior arising between driver and semi-automated vehicle,

    T. Melman, N. Beckers, and D. Abbink, “Mitigating undesirable emergent behavior arising between driver and semi-automated vehicle,”arXiv preprint arXiv:2006.16572, 2020

    work page arXiv 2006

  68. [68]

    Designing automated vehicle and traffic systems towards meaningful human control,

    S. C. Calvert, S. O. Johnsen, and A. George, “Designing automated vehicle and traffic systems towards meaningful human control,” inResearch Handbook on Meaningful Human Control of Artificial Intelligence Systems, United Kingdom: Edward Elgar Publishing, 2023 (Accepted). 25

    work page 2023