Controlling steering and judging heading: retinal flow, visual direction, and extraretinal information

Optic flow density modulates corner-cutting in a virtual steering task for younger and older adults

There is a critical need to understand how aging visual systems contribute to age-related increases in vehicle accidents. We investigated the potential contribution of age-related detriments in steering based on optic flow, a source of information known to play a role in navigation control. Seventeen younger adults (mean age: 21.1 years) and thirteen older adults (mean age: 57.3 years) performed a virtual reality steering task. The virtual environment depicted movement at 19 m/s along a winding road. Participants were tasked with maintaining a central lane position while experiencing eight repetitions of each combination of optic flow density (low, medium, high), turn radius (35, 55, 75 m), and turn direction (left, right), presented in random order. All participants cut corners, but did so less on turns with rotational flow from distant landmarks and without proximal optic flow. We found no evidence of an interaction between age and optic flow density, although older adults cut corners more on all turns. An exploratory gaze analysis revealed no age-related differences in gaze behavior. The lack of age-related differences in steering or gaze behavior as a function of optic flow implies that processing of naturalistic optic flow stimuli when steering may be preserved with age.

Atypical Time to Contact Estimation in Young Adults with Autism Spectrum Disorder

Individuals with Autism Spectrum Disorder (ASD) present atypical sensory processing in the perception of moving stimuli and biological motion. The present study aims to explore the performance of young adults with ASD in a time to contact (TTC) estimation task involving social and non-social stimuli. TTC estimation involves extrapolating the trajectory of a moving target concealed by an occluder, based on the visible portion of its path, to predict the target's arrival time at a specific position. Sixteen participants with a diagnosis of level-1 ASD (M = 19.2 years, SE = 0.54 years; 3 F, 13 M) and sixteen participants with TD (M = 22.3 years, SE = 0.44 years; 3 F, 13 M) took part in the study and underwent a TTC estimation task. The task presented two object types (a car and a point-light walker), different object speeds, occluder lengths, motion directions and motion congruency. For the car object, a larger overestimation of TTC emerged for ASDs than for TDs, whereas no difference between ASDs and TDs emerged for the point-light walker. ASDs exhibited a larger TTC overestimation for the car object than for the point-light walker, whereas no difference between object types emerged for TDs. Our results indicated an atypical TTC estimation process in young adults with ASD. Given its importance in daily life, future studies should further explore this skill. Significant effects that emerged from the analysis are discussed.

Processing of complex traffic scenes for effective steering and collision avoidance: a perspective, from research into human control, on the challenges for sensor-based autonomous vehicles on urban roads

An overview is provided of behavioral research into human steering and collision avoidance including the processing of optic flow, optical looming and the role of the human mobile gaze system. A consideration is then made of the issues that may occur for autonomous vehicles (AV) when they move from grid-type road networks into complex inner-city streets and interact with human drivers, pedestrians and cyclists. Comparisons between human processing and AV processing of these interactions are made. This raises issues as to whether AV control systems need to mimic human visual processing more closely and highlights the need for AV systems to develop a "theory of road users" that allows attribution of intent to other drivers, cyclists or pedestrians. Guidelines for the development of a "theory of road users" for AVs are suggested.

Gravity and Known Size Calibrate Visual Information to Time Parabolic Trajectories

Catching a ball in a parabolic flight is a complex task in which the time and area of interception are strongly coupled, making interception possible for a short period. Although this makes the estimation of time-to-contact (TTC) from visual information in parabolic trajectories very useful, previous attempts to explain our precision in interceptive tasks circumvent the need to estimate TTC to guide our action. Obtaining TTC from optical variables alone in parabolic trajectories would imply very complex transformations from 2D retinal images to a 3D layout. We propose based on previous work and show by using simulations that exploiting prior distributions of gravity and known physical size makes these transformations much simpler, enabling predictive capacities from minimal early visual information. Optical information is inherently ambiguous, and therefore, it is necessary to explain how these prior distributions generate predictions. Here is where the role of prior information comes into play: it could help to interpret and calibrate visual information to yield meaningful predictions of the remaining TTC. The objective of this work is: (1) to describe the primary sources of information available to the observer in parabolic trajectories; (2) unveil how prior information can be used to disambiguate the sources of visual information within a Bayesian encoding-decoding framework; (3) show that such predictions might be robust against complex dynamic environments; and (4) indicate future lines of research to scrutinize the role of prior knowledge calibrating visual information and prediction for action control.

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.

Theoretical interpretation of drivers' gaze strategy influenced by optical flow

Driver analysis, particularly revealing where drivers gaze, is a key factor in understanding drivers’ perception. Several studies have examined drivers’ gaze behavior and the two main hypotheses that have been developed are Tangent Point (TP) and Future Path Point (FP). TP is a point on the inner side of the lane, where the driver’s gaze direction becomes tangential with the lane edge. FP is an arbitrary single point on the ideal future path for an individual driver on the road. The location of this single point is dependent on the individual driver. While these gaze points have been verified and discussed by various psychological experiments, it is unclear why drivers gaze at these points. Therefore, in this study, we used optical flow theory to understand drivers’ gaze strategy. Optical flow theory is a method to quantify the extent to which drivers can perceive the future path of the vehicle. The results of numerical simulations demonstrated that optical flow theory can potentially estimate drivers’ gaze behavior. We also conducted an experiment in which the observed driver gaze behavior was compared to calculated gaze strategy based on optical flow theory. The experimental results demonstrate that drivers’ gaze can be estimated with an accuracy of 70.8% and 65.1% on circular and straight paths, respectively. Thus, these results suggest that optical flow theory can be a determining factor in drivers’ gaze strategy.

Heading perception depends on time-varying evolution of optic flow

There is considerable support for the hypothesis that perception of heading in the presence of rotation is mediated by instantaneous optic flow. This hypothesis, however, has never been tested. We introduce a method, termed "nonvarying phase motion," for generating a stimulus that conveys a single instantaneous optic flow field, even though the stimulus is presented for an extended period of time. In this experiment, observers viewed stimulus videos and performed a forced-choice heading discrimination task. For nonvarying phase motion, observers made large errors in heading judgments. This suggests that instantaneous optic flow is insufficient for heading perception in the presence of rotation. These errors were mostly eliminated when the velocity of phase motion was varied over time to convey the evolving sequence of optic flow fields corresponding to a particular heading. This demonstrates that heading perception in the presence of rotation relies on the time-varying evolution of optic flow. We hypothesize that the visual system accurately computes heading, despite rotation, based on optic acceleration, the temporal derivative of optic flow.

Driver's Preview Modeling Based on Visual Characteristics through Actual Vehicle Tests

This paper proposes a method for obtaining driver's fixation points and establishing a preview model based on actual vehicle tests. Firstly, eight drivers were recruited to carry out the actual vehicle test on the actual straight and curved roads. The curvature radii of test curved roads were selected to be 200, 800, and 1500 m. Subjects were required to drive at a speed of 50, 70 and 90 km/h, respectively. During the driving process, eye movement data of drivers were collected using a head-mounted eye tracker, and road front scene images and vehicle statuses were collected simultaneously. An image-world coordinate mapping model of the visual information of drivers was constructed by performing an image distortion correction and matching the images from the driving recorder. Then, fixation point data for drivers were accordingly obtained using the Identification-Deviation Threshold (I-DT) algorithm. In addition, the Jarque-Bera test was used to verify the normal distribution characteristics of these data and to fit the distribution parameters of the normal function. Furthermore, the preview points were extracted accordingly and projected into the world coordinate. At last, the preview data obtained under these conditions are fit to build general preview time probability density maps for different driving speeds and road curvatures. This study extracts the preview characteristics of drivers through actual vehicle tests, which provides a visual behavior reference for the humanized vehicle control of an intelligent vehicle.

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.

Ecological mechanisms in cognitive science

In 2010, Bechtel and Abrahamsen defined and described what it means to be a dynamic causal mechanistic explanatory model. They discussed the development of a mechanistic explanation of circadian rhythms as an exemplar of the process and challenged cognitive science to follow this example. This article takes on that challenge. A mechanistic model is one that accurately represents the real parts and operations of the mechanism being studied. These real components must be identified by an empirical programme that decomposes the system at the correct scale and localises the components in space and time. Psychological behaviour emerges from the nature of our real-time interaction with our environments—here we show that the correct scale to guide decomposition is picked out by the ecological perceptual information that enables that interaction. As proof of concept, we show that a simple model of coordinated rhythmic movement, grounded in information, is a genuine dynamical mechanistic explanation of many key coordination phenomena.

Steering bends and changing lanes: The impact of optic flow and road edges on two point steering control

Successful driving involves steering corrections that respond to immediate positional errors while also anticipating upcoming changes to the road layout ahead. In popular steering models these tasks are often treated as separate functions using two points: the near region for correcting current errors, and the far region for anticipating future steering requirements. Whereas two-point control models can capture many aspects of driver behavior, the nature of perceptual inputs to these two "points" remains unclear. Inspired by experiments that solely focused on road-edge information (Land & Horwood, 1995), two-point models have tended to ignore the role of optic flow during steering control. There is recent evidence demonstrating that optic flow should be considered within two-point control steering models (Mole, Kountouriotis, Billington, & Wilkie, 2016). To examine the impact of optic flow and road edges on two-point steering control we used a driving simulator to selectively and systematically manipulate these components. We removed flow and/or road-edge information from near or far regions of the scene, and examined how behaviors changed when steering along roads where the utility of far-road information varied. While steering behaviors were strongly influenced by the road-edges, there were also clear contributions of optic flow to steering responses. The patterns of steering were not consistent with optic flow simply feeding into two-point control; rather, the global optic flow field appeared to support effective steering responses across the time-course of each trajectory.

When flow is not enough: evidence from a lane changing task

Humans are able to estimate their heading on the basis of optic flow information and it has been argued that we use flow in this way to guide navigation. Consistent with this idea, several studies have reported good navigation performance in flow fields. However, one criticism of these studies is that they have generally focused on the task of walking or steering towards a target, offering an additional, salient directional cue. Hence, it remains a matter of debate as to whether humans are truly able to control steering in the presence of optic flow alone. In this study, we report a set of maneuvers carried out in flow fields in the absence of a physical target. To do this, we studied the everyday task of lane changing, a commonplace multiphase steering maneuver which can be conceptualized without the need for a target. What is more (and here is the crucial quirk), previous literature has found that in the absence of visual feedback, drivers show a systematic, asymmetric steering response, resulting in a systematic final heading error. If optic flow is sufficient for controlling navigation through our environment, we would expect this asymmetry to disappear whenever optic flow is provided. However, our results show that this asymmetry persisted, even in the presence of a flow field, implying that drivers are unable to use flow to guide normal steering responses in this task.

The influence of visual flow and perceptual load on locomotion speed

Visual flow is used to perceive and regulate movement speed during locomotion. We assessed the extent to which variation in flow from the ground plane, arising from static visual textures, influences locomotion speed under conditions of concurrent perceptual load. In two experiments, participants walked over a 12-m projected walkway that consisted of stripes that were oriented orthogonal to the walking direction. In the critical conditions, the frequency of the stripes increased or decreased. We observed small, but consistent effects on walking speed, so that participants were walking slower when the frequency increased compared to when the frequency decreased. This basic effect suggests that participants interpreted the change in visual flow in these conditions as at least partly due to a change in their own movement speed, and counteracted such a change by speeding up or slowing down. Critically, these effects were magnified under conditions of low perceptual load and a locus of attention near the ground plane. Our findings suggest that the contribution of vision in the control of ongoing locomotion is relatively fluid and dependent on ongoing perceptual (and perhaps more generally cognitive) task demands.

A Two-Point Visual Control Model of Steering

When steering down a winding road, drivers have been shown to use both near and far regions of the road for guidance during steering. We propose a model of steering that explicitly embodies this idea, using both a ‘near point’ to maintain a central lane position and a ‘far point’ to account for the upcoming roadway. Unlike control models that integrate near and far information to compute curvature or more complex features, our model relies solely on one perceptually plausible feature of the near and far points, namely the visual direction to each point. The resulting parsimonious model can be run in simulation within a realistic highway environment to facilitate direct comparison between model and human behavior. Using such simulations, we demonstrate that the proposed two-point model is able to account for four interesting aspects of steering behavior: curve negotiation with occluded visual regions, corrective steering after a lateral drift, lane changing, and individual differences.

Children's Brain Responses to Optic Flow Vary by Pattern Type and Motion Speed

Structured patterns of global visual motion called optic flow provide crucial information about an observer's speed and direction of self-motion and about the geometry of the environment. Brain and behavioral responses to optic flow undergo considerable postnatal maturation, but relatively little brain imaging evidence describes the time course of development in motion processing systems in early to middle childhood, a time when psychophysical data suggest that there are changes in sensitivity. To fill this gap, electroencephalographic (EEG) responses were recorded in 4- to 8-year-old children who viewed three time-varying optic flow patterns (translation, rotation, and radial expansion/contraction) at three different speeds (2, 4, and 8 deg/s). Modulations of global motion coherence evoked coherent EEG responses at the first harmonic that differed by flow pattern and responses at the third harmonic and dot update rate that varied by speed. Pattern-related responses clustered over right lateral channels while speed-related responses clustered over midline channels. Both children and adults show widespread responses to modulations of motion coherence at the second harmonic that are not selective for pattern or speed. The results suggest that the developing brain segregates the processing of optic flow pattern from speed and that an adult-like pattern of neural responses to optic flow has begun to emerge by early to middle childhood.

The need for speed: global optic flow speed influences steering

How do animals follow demarcated paths? Different species are sensitive to optic flow and one control solution is to maintain the balance of flow symmetry across visual fields; however, it is unclear whether animals are sensitive to changes in asymmetries when steering along curved paths. Flow asymmetries can alter the global properties of flow (i.e. flow speed) which may also influence steering control. We tested humans steering curved paths in a virtual environment. The scene was manipulated so that the ground plane to either side of the demarcated path produced larger or smaller asymmetries in optic flow. Independent of asymmetries and the locomotor speed, the scene properties were altered to produce either faster or slower globally averaged flow speeds. Results showed that rather than being influenced by changes in flow asymmetry, steering responded to global flow speed. We conclude that the human brain performs global averaging of flow speed from across the scene and uses this signal as an input for steering control. This finding is surprising since the demarcated path provided sufficient information to steer, whereas global flow speed (by itself) did not. To explain these findings, existing models of steering must be modified to include a new perceptual variable: namely global optic flow speed.

Leading to distraction: Driver distraction, lead car, and road environment

Driver distraction is strongly associated with crashes and near-misses, and despite the attention this topic has received in recent years, the effect of different types of distracting task on driving performance remains unclear. In the case of non-visual distractions, such as talking on the phone or other engaging verbal tasks that do not require a visual input, a common finding is reduced lateral variability in steering and gaze patterns where participants concentrate their gaze towards the centre of the road and their steering control is less variable. In the experiments presented here, we examined whether this finding is more pronounced in the presence of a lead car (which may provide a focus point for gaze) and whether the behaviour of the lead car has any influence on the driver's steering control. In addition, both visual and non-visual distraction tasks were used, and their effect on different road environments (straight and curved roadways) was assessed. Visual distraction was found to increase variability in both gaze patterns and steering control, non-visual distraction reduced gaze and steering variability in conditions without a lead car; in the conditions where a lead car was present there was no significant difference from baseline. The lateral behaviour of the lead car did not have an effect on steering performance, a finding which indicates that a lead car may not necessarily be used as an information point. Finally, the effects of driver distraction were different for straight and curved roadways, indicating a stronger influence of the road environment in steering than previously thought.

Fixation Biases towards the Index Finger in Almost-Natural Grasping

We use visual information to guide our grasping movements. When grasping an object with a precision grip, the two digits need to reach two different positions more or less simultaneously, but the eyes can only be directed to one position at a time. Several studies that have examined eye movements in grasping have found that people tend to direct their gaze near where their index finger will contact the object. Here we aimed at better understanding why people do so by asking participants to lift an object off a horizontal surface. They were to grasp the object with a precision grip while movements of their hand, eye and head were recorded. We confirmed that people tend to look closer to positions that a digit needs to reach more accurately. Moreover, we show that where they look as they reach for the object depends on where they were looking before, presumably because they try to minimize the time during which the eyes are moving so fast that no new visual information is acquired. Most importantly, we confirmed that people have a bias to direct gaze towards the index finger’s contact point rather than towards that of the thumb. In our study, this cannot be explained by the index finger contacting the object before the thumb. Instead, it appears to be because the index finger moves to a position that is hidden behind the object that is grasped, probably making this the place at which one is most likely to encounter unexpected problems that would benefit from visual guidance. However, this cannot explain the bias that was found in previous studies, where neither contact point was hidden, so it cannot be the only explanation for the bias.

The temporal dynamics of heading perception in the presence of moving objects

Many forms of locomotion rely on the ability to accurately perceive one's direction of locomotion (i.e., heading) based on optic flow. Although accurate in rigid environments, heading judgments may be biased when independently moving objects are present. The aim of this study was to systematically investigate the conditions in which moving objects influence heading perception, with a focus on the temporal dynamics and the mechanisms underlying this bias. Subjects viewed stimuli simulating linear self-motion in the presence of a moving object and judged their direction of heading. Experiments 1 and 2 revealed that heading perception is biased when the object crosses or almost crosses the observer's future path toward the end of the trial, but not when the object crosses earlier in the trial. Nonetheless, heading perception is not based entirely on the instantaneous optic flow toward the end of the trial. This was demonstrated in Experiment 3 by varying the portion of the earlier part of the trial leading up to the last frame that was presented to subjects. When the stimulus duration was long enough to include the part of the trial before the moving object crossed the observer's path, heading judgments were less biased. The findings suggest that heading perception is affected by the temporal evolution of optic flow. The time course of dorsal medial superior temporal area (MSTd) neuron responses may play a crucial role in perceiving heading in the presence of moving objects, a property not captured by many existing models.

Development of Automatic Steering System by Modeling Human Behavior Based on Optical Flow

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/03.jpg"" width=""300"" /> Manipulated optical flow field</div> Recently, various driving support systems have been developed to improve safety. However, because drivers occasionally feel that something is wrong, systems need to be designed based on information that drivers perceive. Therefore, we focused on optical flow, which is one of the visual information used by humans to improve driving feel. Humans are said to perceive the direction of self-motion from optical flow and also utilize it during driving. Applying the optical flow model to automatic steering systems, a human-oriented system might be able to be developed. In this paper, we derive the focus of expansion (FOE) in the frame of a camera that is the direction of self-motion in optical flow and propose a nonlinear control method based on the FOE. The effectiveness of the proposed method was verified through a vehicle simulation, and the results showed that the proposed method simulates human behavior. Based on these results, this approach may serve as a foundation of human-oriented system designs. </span>

On-line and model-based approaches to the visual control of action

Two general approaches to the visual control of action have emerged in last few decades, known as the on-line and model-based approaches. The key difference between them is whether action is controlled by current visual information or on the basis of an internal world model. In this paper, we evaluate three hypotheses: strong on-line control, strong model-based control, and a hybrid solution that combines on-line control with weak off-line strategies. We review experimental research on the control of locomotion and manual actions, which indicates that (a) an internal world model is neither sufficient nor necessary to control action at normal levels of performance; (b) current visual information is necessary and sufficient to control action at normal levels; and (c) under certain conditions (e.g. occlusion) action is controlled by less accurate, simple strategies such as heuristics, visual-motor mappings, or spatial memory. We conclude that the strong model-based hypothesis is not sustainable. Action is normally controlled on-line when current information is available, consistent with the strong on-line control hypothesis. In exceptional circumstances, action is controlled by weak, context-specific, off-line strategies. This hybrid solution is comprehensive, parsimonious, and able to account for a variety of tasks under a range of visual conditions.

Influence of optic flow on the control of heading and target egocentric direction during steering toward a goal

Although previous studies have shown that people use both optic flow and target egocentric direction to walk or steer toward a goal, it remains in question how enriching the optic flow field affects the control of heading specified by optic flow and the control of target egocentric direction during goal-oriented locomotion. In the current study, we used a control-theoretic approach to separate the control response specific to these two cues in the visual control of steering toward a goal. The results showed that the addition of optic flow information (such as foreground motion and global flow) in the display improved the overall control precision, the amplitude, and the response delay of the control of heading. The amplitude and the response delay of the control of target egocentric direction were, however, not affected. The improvement in the control of heading with enriched optic flow displays was mirrored by an increase in the accuracy of heading perception. The findings provide direct support for the claim that people use the heading specified by optic flow as well as target egocentric direction to walk or steer toward a goal and suggest that the visual system does not internally weigh these two cues for goal-oriented locomotion control.

Displaying optic flow to simulate locomotion: Comparing heading and steering

Optic flow can be used by humans to determine their direction of heading as well as controlling steering. Dot-flow displays have been widely used to investigate these abilities but it is unclear whether photorealistic textures would provide better information for controlling high-speed steering. Here, we examine the accuracy of heading judgements from dot-flow displays of different densities and luminance and then compare to a scene containing a textured ground. We then examine steering behaviour using these same displays to determine whether accurate heading conditions necessarily equate to successful steering. Our findings suggest that the bright dense dot-flow displays led to equivalent performance as the ground texture when judging heading, and this was also true when steering. The intermediate dot-flow conditions (with fewer and faded dots) revealed that some conditions that led to accurate heading judgements were insufficient for accurate steering. It seems, therefore, that heading perception should not be considered synonymous with successful steering control, and displays that support one ability will not necessarily support the other.

Path curvature discrimination: dependence on gaze direction and optical flow speed

Many experimental approaches to the control of steering rely on the tangent point (TP) as major source of information. The TP is a good candidate to control self-motion. It corresponds to a singular and salient point in the subject's visual field, and its location depends on the road geometry, the direction of self-motion relative to the road and the position of the driver on the road. However, the particular status of the TP in the optical flow, as a local minimum of flow speed, has often been left aside. We therefore assume that the TP is actually an optimal location in the dynamic optical array to perceive a change in the trajectory curvature. In this study, we evaluated the ability of human observers to detect variations in their path curvature from optical flow patterns, as a function of their gaze direction in a virtual environment. We simulated curvilinear self-motion parallel to a ground plane. Using random-dot optic flow stimuli of brief duration and a two-alternative forced-choice adaptive procedure, we determined path curvature discrimination thresholds, as a function of gaze direction. The discrimination thresholds are minimal for a gaze directed toward a local minimum of optical flow speed. A model based on Weber fraction of the foveal velocities () correctly predicts the relationship between experimental thresholds and local flow velocities. This model was also tested for an optical flow computation integrating larger circular areas in central vision. Averaging the flow over five degrees leads to an even better fit of the model to experimental thresholds. We also found that the minimal optical flow speed direction corresponds to a maximal sensitivity of the visual system, as predicted by our model. The spontaneous gazing strategies observed during driving might thus correspond to an optimal selection of relevant information in the optical flow field.

Motion perception: behavior and neural substrate

Visual motion perception is vital for survival. Single-unit recordings in primate primary visual cortex (V1) have revealed the existence of specialized motion sensing neurons; perceptual effects such as the motion after-effect demonstrate their importance for motion perception. Human psychophysical data on motion detection can be explained by a computational model of cortical motion sensors. Both psychophysical and physiological data reveal at least two classes of motion sensor capable of sensing motion in luminance-defined and texture-defined patterns, respectively. Psychophysical experiments also reveal that motion can be seen independently of motion sensor output, based on attentive tracking of visual features. Sensor outputs are inherently ambiguous, due to the problem of univariance in neural responses. In order to compute stimulus direction and speed, the visual system must compare the responses of many different sensors sensitive to different directions and speeds. Physiological data show that this computation occurs in the visual middle temporal (MT) area. Recent psychophysical studies indicate that information about spatial form may also play a role in motion computations. Adaptation studies show that the human visual system is selectively sensitive to large-scale optic flow patterns, and physiological studies indicate that cells in the middle superior temporal (MST) area derive this sensitivity from the combined responses of many MT cells. Extraretinal signals used to control eye movements are an important source of signals to cancel out the retinal motion responses generated by eye movements, though visual information also plays a role. A number of issues remain to be resolved at all levels of the motion-processing hierarchy. WIREs Cogni Sci 2011 2 305-314 DOI: 10.1002/wcs.110 For further resources related to this article, please visit the WIREs website Additional Supporting Information may be found in http://www.lifesci.sussex.ac.uk/home/George_Mather/Motion/index.html.

Monkey steering responses reveal rapid visual-motor feedback

The neural mechanisms underlying primate locomotion are largely unknown. While behavioral and theoretical work has provided a number of ideas of how navigation is controlled, progress will require direct physiolgical tests of the underlying mechanisms. In turn, this will require development of appropriate animal models. We trained three monkeys to track a moving visual target in a simple virtual environment, using a joystick to control their direction. The monkeys learned to quickly and accurately turn to the target, and their steering behavior was quite stereotyped and reliable. Monkeys typically responded to abrupt steps of target direction with a biphasic steering movement, exhibiting modest but transient overshoot. Response latencies averaged approximately 300 ms, and monkeys were typically back on target after about 1 s. We also exploited the variability of responses about the mean to explore the time-course of correlation between target direction and steering response. This analysis revealed a broad peak of correlation spanning approximately 400 ms in the recent past, during which steering errors provoke a compensatory response. This suggests a continuous, visual-motor loop controls steering behavior, even during the epoch surrounding transient inputs. Many results from the human literature also suggest that steering is controlled by such a closed loop. The similarity of our results to those in humans suggests the monkey is a very good animal model for human visually guided steering.

Using vision to control locomotion: looking where you want to go

Looking at the inside edge of the road when steering a bend seems to be a well-established strategy linked to using a feature called the tangent point. An alternative proposal suggests that the gaze patterns observed when steering result from looking at the points in the world through which one wishes to pass. In this explanation fixation on or near the tangent point results from trying to take a trajectory that cuts the corner. To test these accounts, we recorded gaze and steering when taking different paths along curved roadways. Participants could gauge and maintain their lateral distance, but crucially, gaze was predominantly directed to the region proximal to the desired path rather than toward the tangent point per se. These results show that successful control of high-speed locomotion requires fixations in the direction you want to steer rather than using a single road feature like the tangent point.

Environmental constraints modify the way an interceptive action is controlled

This study concerns the process by which agents select control laws. Participants adjusted their walking speed in a virtual environment in order to intercept approaching targets. Successful interception can be achieved with a constant bearing angle (CBA) strategy that relies on prospective information, or with a modified required velocity (MRV) strategy, which also includes predictive information. We manipulated the curvature of the target paths and the display condition of these paths. The curvature manipulation had large effects on the walking kinematics when the target paths were not displayed (informationally poor display). In contrast, the walking kinematics were less affected by the curvature manipulation when the target paths were displayed (informationally rich display). This indicates that participants used an MRV strategy in the informationally rich display and a CBA strategy in the informationally poor display. Quantitative fits of the respective models confirm this information-driven switch between the use of a strategy that relies on prospective information and a strategy that includes predictive information. We conclude that agents are able of taking advantage of available information by selecting a suitable control law.

Limitations of feedforward control in multiple-phase steering movements

When attempting to perform bi-phasic steering movements (such as a lane change) in the absence of visual and inertial feedback, drivers produce a systematic heading error in the direction of the lane change (Wallis et al., Curr Biol 12(4):295-299, 2002; J Exp Psychol Hum Percept Perform 33(55):1127-1144, 2007). Theories of steering control which employ exclusively open-loop control mechanisms cannot accommodate this finding. In this article we show that a similar steering error occurs with obstacle avoidance, and offer compelling evidence that it stems from a seemingly general failure of human operators to correctly internalise the dynamics of the steering wheel. With respect to lateral position, the steering wheel is an acceleration control device, but we present data indicating that drivers treat it as a rate control device. Previous findings from Wallis et al. can be explained the same way. Since an open-loop control mechanism will never succeed when the dynamics of the controller are internalised improperly, we go on to conclude that regular, appropriately timed sensory feedback-predominantly from vision-is necessary for regulating heading, even during well-practiced, everyday manoeuvres such as lane changing and obstacle avoidance.

Steering behaviour can be modulated by different optic flows during walking

Optic flow is a typical pattern of visual motion that can be used to control locomotion. While the ability to discriminate translational or rotational optic flows have been extensively studied, how these flows control steering during locomotion is not known. The goal of this study was to compare the steering behaviour of subjects subjected to rotational, translational, or combined (rotational added to translational) optic flows with a focus of expansion (FOE) located to the right, left, or straight ahead. Ten healthy young subjects were instructed to walk straight in a virtual room viewed through a helmet mounted display while the location of the FOE was randomly offset. Horizontal trajectory of the body's centre of mass (CoM), as well as rotations of the head, trunk and foot were recorded in coordinates of both the physical and virtual worlds. Results show that subjects experienced a mediolateral shift in CoM opposite to the FOE location, with larger corrections being observed at more eccentric FOE locations. Head and body segment reorientations were only observed for optic flows containing a rotational component. CoM trajectory corrections in the physical world were also of small magnitude, leading to deviation errors in the virtual world. Altogether, these results suggest a profound influence of vision, especially due to the pattern of visual motion, on steering behaviours during locomotion.

Perception of structured optic flow and random visual motion in infants and adults: a high-density EEG study

Electroencephalogram (EEG) was used in 8-month-old infants and adults to study brain electrical activity as a function of perception of structured optic flow and random visual motion. A combination of visual evoked potential (VEP) analyses and analyses of temporal spectral evolution (TSE, time-dependent spectral power) was carried out. Significant differences were found for the N2 component of VEP for optic flow versus random visual motion within and between groups. Both adults and infants showed shorter latencies for structured optic flow than random visual motion, and infants showed longer latencies, particularly for random visual motion, and larger amplitudes than adults. Both groups also showed significant differences in induced activity when TSE of the two motion stimuli (optic flow and random visual motion) was compared with TSE of a static dot pattern. Infants showed an induced decrease in the amplitudes in theta-band frequency, while adults showed an induced increase in beta-band frequency. Differences in induced activity for the two motion stimuli could, however, not be observed. Brain activity related to motion stimuli is different for infants and adults and the differences are observed both in VEPs and in induced activity of the EEG. To investigate how changes in locomotor development are related to accompanying changes in brain activity associated with visual motion perception, more data of infants with different experiences in self-produced locomotion are required.

Behavioral dynamics of intercepting a moving target

From matters of survival like chasing prey, to games like football, the problem of intercepting a target that moves in the horizontal plane is ubiquitous in human and animal locomotion. Recent data show that walking humans turn onto a straight path that leads a moving target by a constant angle, with some transients in the target-heading angle. We test four control strategies against the human data: (1) pursuit, or nulling the target-heading angle beta, (2) computing the required interception angle beta (3) constant target-heading angle, or nulling change in the target-heading angle beta and (4) constant bearing, or nulling change in the bearing direction of the target psi which is equivalent to nulling change in the target-heading angle while factoring out the turning rate (beta - phi) We show that human interception behavior is best accounted for by the constant bearing model, and that it is robust to noise in its input and parameters. The models are also evaluated for their performance with stationary targets, and implications for the informational basis and neural substrate of steering control are considered. The results extend a dynamical systems model of human locomotor behavior from static to changing environments.

Muscular proprioception contributes to the control of interceptive actions

The authors proposed a model of the control of interceptive action over a ground plane (Chardenon, Montagne, Laurent, & Bootsma, 2004). This model is based on the cancellation of the rate of change of the angle between the current position of the target and the direction of displacement (i.e., the bearing angle). While several sources of visual information specify this angle, the contribution of proprioceptive information has not been directly tested. In this study, the authors used a virtual reality setup to study the role of proprioception when intercepting a moving target. In a series of experiments, the authors manipulated proprioceptive information by using the tendon vibration paradigm. The results revealed that proprioception is crucial not only to locate a moving target with respect to the body but also, and more importantly, to produce online displacement velocity changes to intercept a moving target. These findings emphasize the importance of proprioception in the control of interceptive action and illustrate the relevance of our model to account for the regulations produced by the participants.

The dynamics of perception and action

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are treated as a pair of dynamical systems that are coupled mechanically and informationally. Their interactions give rise to the behavioral dynamics, a vector field with attractors that correspond to stable task solutions, repellers that correspond to avoided states, and bifurcations that correspond to behavioral transitions. The framework is used to develop theories of several tasks in which a human agent interacts with the physical environment, including bouncing a ball on a racquet, balancing an object, braking a vehicle, and guiding locomotion. Stable, adaptive behavior emerges from the dynamics of the interaction between a structured environment and an agent with simple control laws, under physical and informational constraints.

Active Steering along Corrugated Surfaces

A study is reported of the effect of dynamic occlusion that arises during locomotion over corrugated surfaces and its facilitating role on the control of locomotion, especially in cluttered environments. Surfaces varied in degree of corrugation and type of texture. Heading accuracy was assessed by having participants perform an active steering task. Results demonstrated the advantage of texture-mapped image surfaces over discrete element surfaces in the corrugated conditions. Observers appear to exploit accretion and deletion of optical texture at the occluding edge to extract and use information about heading direction for the control of movements in cluttered environments.

The role of visual and nonvisual information in the control of locomotion

During locomotion, retinal flow, gaze angle, and vestibular information can contribute to one's perception of self-motion. Their respective roles were investigated during active steering: Retinal flow and gaze angle were biased by altering the visual information during computer-simulated locomotion, and vestibular information was controlled through use of a motorized chair that rotated the participant around his or her vertical axis. Chair rotation was made appropriate for the steering response of the participant or made inappropriate by rotating a proportion of the veridical amount. Large steering errors resulted from selective manipulation of retinal flow and gaze angle, and the pattern of errors provided strong evidence for an additive model of combination. Vestibular information had little or no effect on steering performance, suggesting that vestibular signals are not integrated with visual information for the control of steering at these speeds.

Modeling driver behavior in a cognitive architecture

OBJECTIVE

This paper explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system.

BACKGROUND

Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to simulate driver behavior and explore the parameters and constraints of this behavior.

METHOD

An integrated driver model developed in the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture is described that focuses on the component processes of control, monitoring, and decision making in a multilane highway environment.

RESULTS

This model accounts for the steering profiles, lateral position profiles, and gaze distributions of human drivers during lane keeping, curve negotiation, and lane changing.

CONCLUSION

The model demonstrates how cognitive architectures facilitate understanding of driver behavior in the context of general human abilities and constraints and how the driving domain benefits cognitive architectures by pushing model development toward more complex, realistic tasks.

APPLICATION

The model can also serve as a core computational engine for practical applications that predict and recognize driver behavior and distraction.

Trunk muscle proprioceptive input assists steering of locomotion

During locomotion, human subjects navigate in their environment and choose the direction by means of the internal representation of space that is continuously updated by sensory input. Aim of this study was to assess whether trunk proprioceptive information plays a role in the definition of the reference frame for orientation. Unilateral trunk muscle vibration was applied during locomotion along a straight path in seven subjects. Vibration was administered either from the onset or in the middle of a seven-step task, under eyes-open (EO) or blindfolded condition. The deviation of the walking trajectory was quantified by the distance of the seventh from the first foot print along the medio-lateral axis. Foot angles and stride lengths were computed for all foot-falls. Vibration produced a clear-cut deviation from the straight-ahead direction when delivered in the middle of blindfolded locomotion. With EO the deviation was much smaller. A mild deviation was obtained in blindfolded condition when vibration started at the onset of locomotion. All deviations from the straight-ahead were accompanied by coherent changes in foot orientation on the ground. Trunk proprioception plays a major role in the definition of locomotor trajectory. Trunk input seems to be weighted against vision and whole-body kinematic information.

The Effects of Severe Visual Challenges on Steering Performance in Visually Healthy Young Drivers

PURPOSE

Two experiments explored the extent to which induced blur, reduced luminance, and reduced visual fields affect drivers' steering performance in a driving simulator.

METHODS

In experiment 1, ten young participants (M = 21.2 years) drove at approximately 89 km/h (55 mph) along a curvy roadway while being exposed to blur (0 to + 10 D), luminance (0.003 to 16.7 cd/m), and visual field (1.7 and 150 degrees) manipulations. In experiment 2, a new group of ten young participants (M = 18.5 years) drove while exposed to seven visual field sizes (1.7 to 150 degrees).

RESULTS

Steering was sensitive to a reduced field size but not to the blur and luminance challenges. Acuity, on the other hand, was sensitive to the blur and luminance challenges but not to reduced field size.

DISCUSSION

In healthy young drivers, steering performance is remarkably robust to severe blur and to extremely low luminances. These results support a key element of the selective degradation hypothesis advanced by Leibowitz and colleagues--that steering abilities are preserved at night even when the ability to recognize objects and hazards is not. Additional research should address the other element of this hypothesis--that drivers fail to appreciate the extent to which their visual abilities are degraded at night.

The perceptual support of goal-directed displacement is context-dependent

This study investigates the perceptual-motor organisation underlying the control of goal-directed displacement. We used a virtual reality set-up to study the locomotor interception of a moving ball. Subjects had to intercept moving balls by modifying displacement velocity if necessary, while the ball's place of arrival and the environment were manipulated. The results showed that subjects simultaneously managed multiple sources of information and placed priority on the most salient variables, depending on the task and environmental constraints.

Calibration, Information, and Control Strategies for Braking to Avoid a Collision

This study explored visual control strategies for braking to avoid collision by manipulating information about speed of self-motion. Participants watched computer-generated displays and used a brake to stop at an object in the path of motion. Global optic flow rate and edge rate were manipulated by adjusting eye-height and ground-texture size. Stopping distance, initiation of braking, and the magnitude of brake adjustments were influenced by both optical variables, but global optic flow rate had a stronger effect. A new model is introduced according to which braking is controlled by keeping the perceived ideal deceleration, based in part on global optic flow rate, within a "safe" region between 0 and the maximum deceleration of the brake.

Visual guidance of intercepting a moving target on foot

How do people walk to a moving target, and what visual information do they use to do so? Under a pursuit strategy, one would head toward the target's current position, whereas under an interception strategy, one would lead the target, ideally by maintaining a constant target-heading angle (or constant bearing angle). Either strategy may be guided by the egocentric direction of the target, local optic flow from the target, or global optic flow from the background. In four experiments, participants walked through a virtual environment to reach a target moving at a constant velocity. Regardless of the initial conditions, they walked ahead of the target for most of a trial at a fairly constant speed, consistent with an interception strategy (experiment 1). This behavior can be explained by trying to maintain a constant target-heading angle while trying to walk a straight path, with transient steering dynamics. In contrast to previous results for stationary targets, manipulation of the local optic flow from the target (experiment 2) and the global optic flow of the background (experiments 3 and 4) failed to influence interception behavior. Relative motion between the target and the background did affect the path slightly, presumably owing to its effect on perceived target motion. We conclude that humans use an interception strategy based on the egocentric direction of a moving target.