Dynamic scan paths investigations under manual and highly automated driving

Navarro, Jordan; Lappi, Otto; Hernout, Emma; Gabaude, Catherine; Reynaud, Emanuelle

doi:10.1038/s41598-021-83336-4

Cited by 12 publications

(7 citation statements)

References 72 publications

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“…Guiding fixations are interspersed by occasional gaze polling ( cf . Wilkie et al, 2008 ): forward polling or look-ahead fixations to the road beyond the 1–2 s time headway (TH) far road region ( Lehtonen et al, 2013 , 2014 ; Schnebelen et al, 2019 ) and backwards polling for return fixations to the near road region ( Navarro et al, 2021 ). Guiding fixations and gaze polling characterize the overall pattern of “eyes-on-the-road” fixations.…”

Section: Primary Gaze Strategiesmentioning

confidence: 99%

“…1.3. Saccades are used to scan further (look-ahead fixations, forward polling; Lehtonen et al, 2013Lehtonen et al, , 2014, back to the near road (return fixations, backwards polling; Navarro et al, 2021) as well as at the scenery, mirrors, and instruments. 1.4.…”

Section: Eyes On the Roadmentioning

confidence: 99%

“…5.3. "Just-in-time fixations" (or guiding fixations, GF) are interleaved with look-ahead fixations (LAF) in driving, this happens, for example, in approaching a bend (Lehtonen et al, 2012(Lehtonen et al, , 2013(Lehtonen et al, , 2014Schnebelen et al, 2019;Navarro et al, 2021). 5.4.…”

Section: Eyes On the Roadmentioning

confidence: 99%

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Gaze Strategies in Driving–An Ecological Approach

Lappi

2022

Front. Psychol.

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Human performance in natural environments is deeply impressive, and still much beyond current AI. Experimental techniques, such as eye tracking, may be useful to understand the cognitive basis of this performance, and “the human advantage.” Driving is domain where these techniques may deployed, in tasks ranging from rigorously controlled laboratory settings through high-fidelity simulations to naturalistic experiments in the wild. This research has revealed robust patterns that can be reliably identified and replicated in the field and reproduced in the lab. The purpose of this review is to cover the basics of what is known about these gaze behaviors, and some of their implications for understanding visually guided steering. The phenomena reviewed will be of interest to those working on any domain where visual guidance and control with similar task demands is involved (e.g., many sports). The paper is intended to be accessible to the non-specialist, without oversimplifying the complexity of real-world visual behavior. The literature reviewed will provide an information base useful for researchers working on oculomotor behaviors and physiology in the lab who wish to extend their research into more naturalistic locomotor tasks, or researchers in more applied fields (sports, transportation) who wish to bring aspects of the real-world ecology under experimental scrutiny. Part of a Research Topic on Gaze Strategies in Closed Self-paced tasks, this aspect of the driving task is discussed. It is in particular emphasized why it is important to carefully separate the visual strategies driving (quite closed and self-paced) from visual behaviors relevant to other forms of driver behavior (an open-ended menagerie of behaviors). There is always a balance to strike between ecological complexity and experimental control. One way to reconcile these demands is to look for natural, real-world tasks and behavior that are rich enough to be interesting yet sufficiently constrained and well-understood to be replicated in simulators and the lab. This ecological approach to driving as a model behavior and the way the connection between “lab” and “real world” can be spanned in this research is of interest to anyone keen to develop more ecologically representative designs for studying human gaze behavior.

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Section: Primary Gaze Strategiesmentioning

confidence: 99%

Section: Eyes On the Roadmentioning

confidence: 99%

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Gaze Strategies in Driving–An Ecological Approach

Lappi

2022

Front. Psychol.

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“…(4) Chunking combined with waypoint identification and consideration of different frames of reference (Lappi, 2016 ) into the egocentric chunking hypothesis . (5) Interpretation of this hierarchical task structure/cognitive organization in terms of a neural hierarchy in cognitive neuroscience; wayfinding circuits in the brain involved in landmark-based navigation and representation of large-scale environments (Barry and Burgess, 2014 ; Epstein and Vass, 2014 ; Spiers and Barry, 2015 ; Epstein et al, 2017 ) and driving (Lappi, 2015 ; Navarro et al, 2021 ). (6) Hierarchical predictive processing (predictive brain) in cognitive modeling; the brain as an inference engine for stochastic estimation and control (Friston, 2009 , 2010 ; Friston et al, 2012 ; Clark, 2013 ; on predictive processing in driving, see also Engström et al, 2018 ; Kujala and Lappi, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Egocentric Chunking in the Predictive Brain: A Cognitive Basis of Expert Performance in High-Speed Sports

Lappi

2022

Front. Hum. Neurosci.

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What principles and mechanisms allow humans to encode complex 3D information, and how can it be so fast, so accurately and so flexibly transformed into coordinated action? How do these processes work when developed to the limit of human physiological and cognitive capacity—as they are in high-speed sports, such as alpine skiing or motor racing? High-speed sports present not only physical challenges, but present some of the biggest perceptual-cognitive demands for the brain. The skill of these elite athletes is in many ways an attractive model for studying human performance “in the wild”, and its neurocognitive basis. This article presents a framework theory for how these abilities may be realized in high-speed sports. It draws on a careful analysis of the case of the motorsport athlete, as well as theoretical concepts from: (1) cognitive neuroscience of wayfinding, steering, and driving; (2) cognitive psychology of expertise; (3) cognitive modeling and machine learning; (4) human-in-the loop modellling in vehicle system dynamics and human performance engineering; (5) experimental research (in the laboratory and in the field) on human visual guidance. The distinctive contribution is the way these are integrated, and the concept of chunking is used in a novel way to analyze a high-speed sport. The mechanisms invoked are domain-general, and not specific to motorsport or the use of a particular type of vehicle (or any vehicle for that matter); the egocentric chunking hypothesis should therefore apply to any dynamic task that requires similar core skills. It offers a framework for neuroscientists, psychologists, engineers, and computer scientists working in the field of expert sports performance, and may be useful in translating fundamental research into theory-based insight and recommendations for improving real-world elite performance. Specific experimental predictions and applicability of the hypotheses to other sports are discussed.

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“…It can be expected that a driver's attention distribution depends on whether the driver is driving manually or whether he or she is tasked to supervise an automated driving system. Previous research indicates that drivers of automated vehicles are less likely to glance at the forward roadway than manual drivers, which can be explained by the visual demands associated with manual lane-keeping [18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

What Attracts the Driver’s Eye? Attention as a Function of Task and Events

2022

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This study explores how drivers of an automated vehicle distribute their attention as a function of environmental events and driving task instructions. Twenty participants were asked to monitor pre-recorded videos of a simulated driving trip while their eye movements were recorded using an eye-tracker. The results showed that eye movements are strongly situation-dependent, with areas of interest (windshield, mirrors, and dashboard) attracting attention when events (e.g., passing vehicles) occurred in those areas. Furthermore, the task instructions provided to participants (i.e., speed monitoring or hazard monitoring) affected their attention distribution in an interpretable manner. It is concluded that eye movements while supervising an automated vehicle are strongly ‘top-down’, i.e., based on an expected value. The results are discussed in the context of the development of driver availability monitoring systems.

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Dynamic scan paths investigations under manual and highly automated driving

Cited by 12 publications

References 72 publications

Gaze Strategies in Driving–An Ecological Approach

Gaze Strategies in Driving–An Ecological Approach

Egocentric Chunking in the Predictive Brain: A Cognitive Basis of Expert Performance in High-Speed Sports

What Attracts the Driver’s Eye? Attention as a Function of Task and Events

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