Evidence Accumulation Account of Human Operators' Decisions in Intermittent Control During Inverted Pendulum Balancing

Markkula, Gustav; Zgonnikov, Arkady

doi:10.1109/smc.2018.00130

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…Regarding the candidate frameworks compared in this experiment, a key finding was that initial E influenced steering behaviors. This supports previous research by Markkula & Zgonnikov (2019) who also highlighted the importance of initial error under an Accumulator framework. They investigated whether participants integrated control error during a virtual stick balancing task.…”

Section: Discussionsupporting

confidence: 90%

“…This article details evidence that drivers integrate perceptual information rather than waiting for the perceptual information to surpass a fixed threshold. This provides novel insight into human sensorimotor control and supports previous investigations into a variety of sensorimotor tasks (Markkula, et al, 2018; Markkula & Zgonnikov, 2019; Xue et al, 2018). The findings also allow for improvement in the modeling and replication of sensorimotor action using computational models.…”

Section: Discussionsupporting

confidence: 84%

“…By randomly selecting initial starting errors rather than assuming they were fixed, their model better replicated human sensorimotor action. Markkula and Zgonnikov (2019) did not discuss why accounting for initial error improved the replication of human responses; however, findings from the current study could provide an explanation. If humans integrate perceptual information, then the starting position of the virtual stick in Markkula and Zgonnikov's (2019) task will influence the ensuing integration of error and the consequent initiation of control (just as the starting position of drivers influenced steering responses).…”

Section: Discussioncontrasting

confidence: 61%

“…If humans integrate perceptual information, then the starting position of the virtual stick in Markkula and Zgonnikov's (2019) task will influence the ensuing integration of error and the consequent initiation of control (just as the starting position of drivers influenced steering responses). By randomly selecting initial starting errors, Markkula and Zgonnikov (2019) accounted for random initial errors that would have affected the initiation of responses in human data.…”

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confidence: 99%

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Steering is initiated based on error accumulation.

Goodridge¹,

Mole²,

Billington³

et al. 2022

Journal of Experimental Psychology: Human Perception and Perfor

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Vehicle control by humans is possible because the central nervous system is capable of using visual information to produce complex sensorimotor actions. Drivers must monitor errors and initiate steering corrections of appropriate magnitude and timing to maintain a safe lane position. The perceptual mechanisms determining how a driver processes visual information and initiates steering corrections remain unclear. Previous research suggests two potential alternative mechanisms for responding to errors: (i) perceptual evidence (error) satisficing fixed constant thresholds (Threshold), or (ii) the integration of perceptual evidence over time (Accumulator). To distinguish between these mechanisms an experiment was conducted using a computer-generated steering correction paradigm. Drivers (N=20) steered towards an intermittently appearing 'road-line' that varied in position and orientation with respect to the driver's position and trajectory. One key prediction from a Threshold framework is a fixed absolute error response across conditions regardless of the rate of error development, whereas the Accumulator framework predicts that drivers would respond to larger absolute errors when the error signal develops at a faster rate. Results were consistent with an Accumulator framework, thus we propose that models of steering should integrate perceived control error over time in order to accurately capture human perceptual performance.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 84%

Section: Discussioncontrasting

confidence: 61%

mentioning

confidence: 99%

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Steering is initiated based on error accumulation.

Goodridge¹,

Mole²,

Billington³

et al. 2022

Journal of Experimental Psychology: Human Perception and Perfor

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Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers

2022

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Objective We aim to bridge the gap between naturalistic studies of driver behavior and modern cognitive and neuroscientific accounts of decision making by modeling the cognitive processes underlying left-turn gap acceptance by human drivers. Background Understanding decisions of human drivers is essential for the development of safe and efficient transportation systems. Current models of decision making in drivers provide little insight into the underlying cognitive processes. On the other hand, laboratory studies of abstract, highly controlled tasks point towards noisy evidence accumulation as a key mechanism governing decision making. However, it is unclear whether the cognitive processes implicated in these tasks are as paramount to decisions that are ingrained in more complex behaviors, such as driving. Results The drivers’ probability of accepting the available gap increased with the size of the gap; importantly, response time increased with time gap but not distance gap. The generalized drift-diffusion model explained the observed decision outcomes and response time distributions, as well as substantial individual differences in those. Through cross-validation, we demonstrate that the model not only explains the data, but also generalizes to out-of-sample conditions. Conclusion Our results suggest that dynamic evidence accumulation is an essential mechanism underlying left-turn gap acceptance decisions in human drivers, and exemplify how simple cognitive process models can help to understand human behavior in complex real-world tasks. Application Potential applications of our results include real-time prediction of human behavior by automated vehicles and simulating realistic human-like behaviors in virtual environments for automated vehicles.

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Accumulation of continuously time-varying sensory evidence constrains neural and behavioral responses in human collision threat detection

et al. 2021

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Evidence accumulation models provide a dominant account of human decision-making, and have been particularly successful at explaining behavioral and neural data in laboratory paradigms using abstract, stationary stimuli. It has been proposed, but with limited in-depth investigation so far, that similar decision-making mechanisms are involved in tasks of a more embodied nature, such as movement and locomotion, by directly accumulating externally measurable sensory quantities of which the precise, typically continuously time-varying, magnitudes are important for successful behavior. Here, we leverage collision threat detection as a task which is ecologically relevant in this sense, but which can also be rigorously observed and modelled in a laboratory setting. Conventionally, it is assumed that humans are limited in this task by a perceptual threshold on the optical expansion rate–the visual looming–of the obstacle. Using concurrent recordings of EEG and behavioral responses, we disprove this conventional assumption, and instead provide strong evidence that humans detect collision threats by accumulating the continuously time-varying visual looming signal. Generalizing existing accumulator model assumptions from stationary to time-varying sensory evidence, we show that our model accounts for previously unexplained empirical observations and full distributions of detection response. We replicate a pre-response centroparietal positivity (CPP) in scalp potentials, which has previously been found to correlate with accumulated decision evidence. In contrast with these existing findings, we show that our model is capable of predicting the onset of the CPP signature rather than its buildup, suggesting that neural evidence accumulation is implemented differently, possibly in distinct brain regions, in collision detection compared to previously studied paradigms.

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Evidence Accumulation Account of Human Operators' Decisions in Intermittent Control During Inverted Pendulum Balancing

Cited by 4 publications

References 30 publications

Steering is initiated based on error accumulation.

Steering is initiated based on error accumulation.

Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers

Accumulation of continuously time-varying sensory evidence constrains neural and behavioral responses in human collision threat detection

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