Can gaze control steering?

When steering a trajectory, we direct our gaze to locations (1-3 s ahead) that we want to steer through. How and why are these active gaze patterns conducive to successful steering? While various sources of visual information have been identified that could support steering control, the role of stereotypical gaze patterns during steering remains unclear. Here, experimental and computational approaches are combined to investigate a possible direct connection between gaze and steering: Is there enough information in gaze direction that it could be used in isolation to steer through a series of waypoints? For this, we test steering models using waypoints supplied from human gaze data, as well as waypoints specified by optical features of the environment. Steering-by-gaze was modeled using a "pure-pursuit" controller (computing a circular trajectory toward a steering point), or a simple "proportional" controller (yaw-rate set proportional to the visual angle of the steering point). Both controllers produced successful steering when using human gaze data as the input. The models generalized using the same parameters across two scenarios: (a) steering through a slalom of three visible waypoints located within lane boundaries and (b) steering a series of connected S bends comprising visible waypoints without a visible road. While the trajectories on average broadly matched those generated by humans, the differences in individual trajectories were not captured by the models. We suggest that "looking where we are going" provides useful information and that this can often be adequate to guide steering. Capturing variation in human steering responses, however, likely requires more sophisticated models or additional sensory information.

Psychometric analysis of the flow short scale translated to Finnish.

Flow is a well-known construct describing the experience of deep absorption in a task, typically demanding but intrinsically motivating, and conducted with high skill. Flow is operationalized by self-report, and various instruments have been developed for this, but none have been made available in the Finnish language in thoroughly validated form. We present a psychometric scale-validation study for the Finnish translation of the Flow Short Scale (FSS). We collected data from 201 Finnish speaking participants using the Prolific Academic platform. We assessed the scale's factorial structure using Mokken scale analysis, Parallel Analysis, Very Simple Structures analysis and a standard Confirmatory Factor Analysis. We then evaluated how correlated was the FSS with the Flow State Scale and Flow Core Scale. Finally, we evaluated how well the FSS distinguished Flow-inducing experiences from boring (non-Flow-inducing) experiences. Taken together, our results show that an 8-item, two-factor version of the scale was a justified instrument with good psychometric properties.

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

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.

Gaze Strategies in Driving-An Ecological Approach.

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.

Tracking an occluded visual target with sequences of saccades.

Gaze behavior during visual tracking consists of a combination of pursuit and saccadic movements. When the tracked object is intermittently occluded, the role of smooth pursuit is reduced, with a corresponding increase in the role of saccades. However, studies of visual tracking during occlusion have focused only on the first few saccades, usually with occlusion periods of less than 1 second in duration. We investigated tracking on a circular trajectory with random occlusions and found that an occluded object can be tracked reliably for up to several seconds with mainly anticipatory saccades and very little smooth pursuit. Furthermore, we investigated the accumulation of uncertainty in prediction and found that prediction errors seem to accumulate faster when an absolute reference frame is not available during tracking. We suggest that the observed saccadic tracking reflects the use of a time-based internal estimate of object position that is anchored to the environment via fixations.

Visual anticipation of the future path: Predictive gaze and steering.

Skillful behavior requires the anticipation of future action requirements. This is particularly true during high-speed locomotor steering where solely detecting and correcting current error is insufficient to produce smooth and accurate trajectories. Anticipating future steering requirements could be supported using "model-free" prospective signals from the scene ahead or might rely instead on model-based predictive control solutions. The present study generated conditions whereby the future steering trajectory was specified using a breadcrumb trail of waypoints, placed at regular intervals on the ground to create a predictable course (a repeated series of identical "S-bends"). The steering trajectories and gaze behavior relative to each waypoint were recorded for each participant (N = 16). To investigate the extent to which drivers predicted the location of future waypoints, "gaps" were included (20% of waypoints) whereby the next waypoint in the sequence did not appear. Gap location was varied relative to the S-bend inflection point to manipulate the chances that the next waypoint indicated a change in direction of the bend. Gaze patterns did indeed change according to gap location, suggesting that participants were sensitive to the underlying structure of the course and were predicting the future waypoint locations. The results demonstrate that gaze and steering both rely upon anticipation of the future path consistent with some form of internal model.

Dynamic scan paths investigations under manual and highly automated driving.

Active visual scanning of the scene is a key task-element in all forms of human locomotion. In the field of driving, steering (lateral control) and speed adjustments (longitudinal control) models are largely based on drivers' visual inputs. Despite knowledge gained on gaze behaviour behind the wheel, our understanding of the sequential aspects of the gaze strategies that actively sample that input remains restricted. Here, we apply scan path analysis to investigate sequences of visual scanning in manual and highly automated simulated driving. Five stereotypical visual sequences were identified under manual driving: forward polling (i.e. far road explorations), guidance, backwards polling (i.e. near road explorations), scenery and speed monitoring scan paths. Previously undocumented backwards polling scan paths were the most frequent. Under highly automated driving backwards polling scan paths relative frequency decreased, guidance scan paths relative frequency increased, and automation supervision specific scan paths appeared. The results shed new light on the gaze patterns engaged while driving. Methodological and empirical questions for future studies are discussed.

Inattention and Uncertainty in the Predictive Brain.

Negative effects of inattention on task performance can be seen in many contexts of society and human behavior, such as traffic, work, and sports. In traffic, inattention is one of the most frequently cited causal factors in accidents. In order to identify inattention and mitigate its negative effects, there is a need for quantifying attentional demands of dynamic tasks, with a credible basis in cognitive modeling and neuroscience. Recent developments in cognitive science have led to theories of cognition suggesting that brains are an advanced prediction engine. The function of this prediction engine is to support perception and action by continuously matching incoming sensory input with top-down predictions of the input, generated by hierarchical models of the statistical regularities and causal relationships in the world. Based on the capacity of this predictive processing framework to explain various mental phenomena and neural data, we suggest it also provides a plausible theoretical and neural basis for modeling attentional demand and attentional capacity "in the wild" in terms of uncertainty and prediction error. We outline a predictive processing approach to the study of attentional demand and inattention in driving, based on neurologically-inspired theories of uncertainty processing and experimental research combining brain imaging, visual occlusion and computational modeling. A proper understanding of uncertainty processing would enable comparison of driver's uncertainty to a normative level of appropriate uncertainty, and thereby improve definition and detection of inattentive driving. This is the necessary first step toward applications such as attention monitoring systems for conventional and semi-automated driving.

Humans use Optokinetic Eye Movements to Track Waypoints for Steering.

It is well-established how visual stimuli and self-motion in laboratory conditions reliably elicit retinal-image-stabilizing compensatory eye movements (CEM). Their organization and roles in natural-task gaze strategies is much less understood: are CEM applied in active sampling of visual information in human locomotion in the wild? If so, how? And what are the implications for guidance? Here, we directly compare gaze behavior in the real world (driving a car) and a fixed base simulation steering task. A strong and quantifiable correspondence between self-rotation and CEM counter-rotation is found across a range of speeds. This gaze behavior is "optokinetic", i.e. optic flow is a sufficient stimulus to spontaneously elicit it in naïve subjects and vestibular stimulation or stereopsis are not critical. Theoretically, the observed nystagmus behavior is consistent with tracking waypoints on the future path, and predicted by waypoint models of locomotor control - but inconsistent with travel point models, such as the popular tangent point model.

Effect of Meditative Movement on Affect and Flow in Qigong Practitioners.

Qigong is a Meditative Movement exercise that consists of mindful movements, regulation of breathing and attentional control. In this study we investigated whether Qigong practice might be associated with the affect and flow of its practitioners during the exercise. Although practitioners of Meditative Movement anecdotally describe flow-like experiences and strong effects on affect there are only a few empirical studies that focus on acute effects of Qigong practice on affect, and to our knowledge none on flow. Understanding these phenomena could shed new light on the interrelationship between body movement and the embodied mind. Self-reported affect and flow of qigong practitioners (N = 19) was probed in four qigong sessions, 1 week apart, each lasting about an hour. We used the PANAS (Positive And Negative Affect Schedule) to measure self-reported affect pre- and post-session. Additionally, open-ended questions were used to further inquire the specific quality of the post-session affect. Flow was measured using the Flow Short Scale, twice during each Qigong session and once after it. Our results confirm previous studies that Qigong practice shifts affect toward positive valence. Content analysis of the open-ended questions further revealed that the resulting experience can be described as restful, relaxed, happy, balanced, and clear. Although the lack of a control group/condition preclude drawing firm causal conclusions, our results indicate that Qigong practice produced flow already 20 min into the session, and that flow state intensified at 40 and 60 min. Future directions for studying affect and flow in meditative exercise are discussed.

Looking at the Road When Driving Around Bends: Influence of Vehicle Automation and Speed.

When negotiating bends car drivers perform gaze polling: their gaze shifts between guiding fixations (GFs; gaze directed 1-2 s ahead) and look-ahead fixations (LAFs; longer time headway). How might this behavior change in autonomous vehicles where the need for constant active visual guidance is removed? In this driving simulator study, we analyzed this gaze behavior both when the driver was in charge of steering or when steering was delegated to automation, separately for bend approach (straight line) and the entry of the bend (turn), and at various speeds. The analysis of gaze distributions relative to bend sections and driving conditions indicate that visual anticipation (through LAFs) is most prominent before entering the bend. Passive driving increased the proportion of LAFs with a concomitant decrease of GFs, and increased the gaze polling frequency. Gaze polling frequency also increased at higher speeds, in particular during the bend approach when steering was not performed. LAFs encompassed a wide range of eccentricities. To account for this heterogeneity two sub-categories serving distinct information requirements are proposed: mid-eccentricity LAFs could be more useful for anticipatory planning of steering actions, and far-eccentricity LAFs for monitoring potential hazards. The results support the idea that gaze and steering coordination may be strongly impacted in autonomous vehicles.

Flow Experiences During Visuomotor Skill Acquisition Reflect Deviation From a Power-Law Learning Curve, but Not Overall Level of Skill.

Flow is a state of "optimal experience" that arises when skill and task demands match. Flow has been well studied in psychology using a range of self-report and experimental methods; with most research typically focusing on how Flow is elicited by a particular task. Here, we focus on how the experience of Flow changes during task skill development. We present a longitudinal experimental study of learning, wherein participants (N = 9) play a novel steering-game task designed to elicit Flow by matching skill and demand, and providing clear goals and feedback. Experimental design involves extensive in-depth measurement of behavior, physiology, and Flow self-reports over 2 weeks of 40 game trials in eight sessions. Here we report behavioral results, which are both strikingly similar and strong within each participant. We find that the game induces a near-constant state of elevated Flow. We further find that the variation in Flow across all trials is less affected by overall performance improvement than by deviation of performance from the expected value predicted by a power law model of learning.

Humans Use Predictive Gaze Strategies to Target Waypoints for Steering.

A major unresolved question in understanding visually guided locomotion in humans is whether actions are driven solely by the immediately available optical information (model-free online control mechanisms), or whether internal models have a role in anticipating the future path. We designed two experiments to investigate this issue, measuring spontaneous gaze behaviour while steering, and predictive gaze behaviour when future path information was withheld. In Experiment 1 participants (N = 15) steered along a winding path with rich optic flow: gaze patterns were consistent with tracking waypoints on the future path 1-3 s ahead. In Experiment 2, participants (N = 12) followed a path presented only in the form of visual waypoints located on an otherwise featureless ground plane. New waypoints appeared periodically every 0.75 s and predictably 2 s ahead, except in 25% of the cases the waypoint at the expected location was not displayed. In these cases, there were always other visible waypoints for the participant to fixate, yet participants continued to make saccades to the empty, but predictable, waypoint locations (in line with internal models of the future path guiding gaze fixations). This would not be expected based upon existing model-free online steering control models, and strongly points to a need for models of steering control to include mechanisms for predictive gaze control that support anticipatory path following behaviours.

Getting Back Into the Loop: The Perceptual-Motor Determinants of Successful Transitions out of Automated Driving.

OBJECTIVE: To present a structured, narrative review highlighting research into human perceptual-motor coordination that can be applied to automated vehicle (AV)-human transitions. BACKGROUND: Manual control of vehicles is made possible by the coordination of perceptual-motor behaviors (gaze and steering actions), where active feedback loops enable drivers to respond rapidly to ever-changing environments. AVs will change the nature of driving to periods of monitoring followed by the human driver taking over manual control. The impact of this change is currently poorly understood. METHOD: We outline an explanatory framework for understanding control transitions based on models of human steering control. This framework can be summarized as a perceptual-motor loop that requires (a) calibration and (b) gaze and steering coordination. A review of the current experimental literature on transitions is presented in the light of this framework. RESULTS: The success of transitions are often measured using reaction times, however, the perceptual-motor mechanisms underpinning steering quality remain relatively unexplored. CONCLUSION: Modeling the coordination of gaze and steering and the calibration of perceptual-motor control will be crucial to ensure safe and successful transitions out of automated driving. APPLICATION: This conclusion poses a challenge for future research on AV-human transitions. Future studies need to provide an understanding of human behavior that will be sufficient to capture the essential characteristics of drivers reengaging control of their vehicle. The proposed framework can provide a guide for investigating specific components of human control of steering and potential routes to improving manual control recovery.

Effects of an Active Visuomotor Steering Task on Covert Attention.

In complex dynamic tasks such as driving it is essential to be aware of potentially important targets in peripheral vision. While eye tracking methods in various driving tasks have provided much information about drivers' gaze strategies, these methods only inform about overt attention and provide limited grounds to assess hypotheses concerning covert attention. We adapted the Posner cue paradigm to a dynamic steering task in a driving simulator. The participants were instructed to report the presence of peripheral targets while their gaze was fixed to the road. We aimed to see whether and how the active steering task and complex visual stimulus might affect directing covert attention to the visual periphery. In a control condition, the detection task was performed without a visual scene and active steering. Detection performance in bends was better in the control task compared to corresponding performance in the steering task, indicating that active steering and the complex visual scene affected the ability to distribute covert attention. Lower targets were discriminated slower than targets at the level of the fixation circle in both conditions. We did not observe higher discriminability for on-road targets. The results may be accounted for by either bottom-up optic flow biasing of attention, or top-down saccade planning.

Gaze doesn't always lead steering.

In car driving, gaze typically leads the steering when negotiating curves. The aim of the current study was to investigate whether drivers also use this gaze-leads-steering strategy when time-sharing between driving and a visual secondary task. Fourteen participants drove an instrumented car along a motorway while performing a secondary task: looking at a specified visual target as long and as much as they felt it was safe to do so. They made six trips, and in each trip the target was at a different location relative to the road ahead. They were free to glance back at the road at any time. Gaze behaviour was measured with an eye tracker, and steering corrections were recorded from the vehicle's CAN bus. Both in-car 'Fixation' targets and outside 'Pursuit' targets were used. Drivers often used a gaze-leads-steering strategy, glancing at the road ahead 200-600 ms before executing steering corrections. However, when the targets were less eccentric (requiring a smaller change in glance direction relative to the road ahead), the reverse strategy, in which glances to the road ahead followed steering corrections with 0-400 ms latency, was clearly present. The observed use of strategies can be interpreted in terms of predictive processing: The gaze-leads-steering strategy is driven by the need to update the visual information and is therefore modulated by the quality/quantity of peripheral information. Implications for steering models are discussed.

The Racer's Mind-How Core Perceptual-Cognitive Expertise Is Reflected in Deliberate Practice Procedures in Professional Motorsport.

The exceptional performance of elite practitioners in domains like sports or chess is not a reflection of just exceptional general cognitive ability or innate sensorimotor superiority. Decades of research on expert performance has consistently shown that experts in all fields go to extraordinary lengths to acquire their perceptual-cognitive and motor abilities. Deliberate Practice (DP) refers to special (sub)tasks that are designed to give immediate and accurate feedback and performed repetitively with the explicit goal of improving performance. DP is generally agreed to be one of the key ingredients in acquisition of expertise (not necessarily the only one). Analyzing in detail the specific aspects of performance targeted by DP procedures may shed light on the underlying cognitive processes that support expert performance. Document analysis of professional coaching literature is one knowledge elicitation method that can be used in the early phases of inquiry to glean domain information about the skills experts in a field are required to develop. In this study this approach is applied to the domain of motor racing - specifically the perceptual-cognitive expertise enabling high-speed curve negotiation. A systematic review procedure is used to establish a corpus of texts covering the entire 60 years of professional motorsport textbooks. Descriptions of specific training procedures (that can be unambiguously interpreted as DP procedures) are extracted, and then analyzed within the hierarchical task analysis framework driver modeling. Hypotheses about the underlying cognitive processes are developed on the basis of this material. In the traditional psychological literature, steering and longitudinal control are typically considered "simple" reactive tracking tasks (model-free feedback control). The present findings suggest that-as in other forms expertise-expert level driving skill is in fact dependent on vast body of knowledge, and driven by top-down information. The knowledge elicitation in this study represents a first step toward a deeper psychological understanding of the complex cognitive underpinnings of expert performance in this domain.

Visuomotor control, eye movements, and steering: A unified approach for incorporating feedback, feedforward, and internal models.

The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engineering, which share an underlying architecture but have historically developed in very separate ways. The authors then show how these traditions can be naturally (re)integrated with each other and with contemporary neuroscience, to better understand the skill and gaze strategies involved. They then propose a conceptual model that (a) gives a unified account to the coordination of gaze and steering control, (b) incorporates higher-level path planning, and (c) draws on the literature on paired forward and inverse models in predictive control. Although each of these (a-c) has been considered before (also in the context of driving), integrating them into a single framework and the authors' multiple waypoint identification hypothesis within that framework are novel. The proposed hypothesis is relevant to all forms of visually guided locomotion. (PsycINFO Database Record

A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task.

We present a computational model of intermittent visual sampling and locomotor control in a simple yet representative task of a car driver following another vehicle. The model has a number of features that take it beyond the current state of the art in modelling natural tasks, and driving in particular. First, unlike most control theoretical models in vision science and engineering-where control is directly based on observable (optical) variables-actions are based on a temporally enduring internal representation. Second, unlike the more sophisticated engineering driver models based on internal representations, our model explicitly aims to be psychologically plausible, in particular in modelling perceptual processes and their limitations. Third, unlike most psychological models, it is implemented as an actual simulation model capable of full task performance (visual sampling and longitudinal control). The model is developed and validated using a dataset from a simplified car-following experiment (N = 40, in both three-dimensional virtual reality and a real instrumented vehicle). The results replicate our previously reported connection between time headway and visual attention. The model reproduces this connection and predicts that it emerges from control of action uncertainty. Implications for traffic psychological models and future developments for psychologically plausible yet computationally rigorous models of full natural task performance are discussed.