Follow the leader: visual control of speed in pedestrian following

Human Crowds as Social Networks: Collective Dynamics of Consensus and Polarization

A ubiquitous type of collective behavior and decision-making is the coordinated motion of bird flocks, fish schools, and human crowds. Collective decisions to move in the same direction, turn right or left, or split into subgroups arise in a self-organized fashion from local interactions between individuals without central plans or designated leaders. Strikingly similar phenomena of consensus (collective motion), clustering (subgroup formation), and bipolarization (splitting into extreme groups) are also observed in opinion formation. As we developed models of crowd dynamics and analyzed crowd networks, we found ourselves going down the same path as models of opinion dynamics in social networks. In this article, we draw out the parallels between human crowds and social networks. We show that models of crowd dynamics and opinion dynamics have a similar mathematical form and generate analogous phenomena in multiagent simulations. We suggest that they can be unified by a common collective dynamics, which may be extended to other psychological collectives. Models of collective dynamics thus offer a means to account for collective behavior and collective decisions without appealing to a priori mental structures.

Age-Related Changes in the Utilization of Visual Information for Collision Prediction: A Study Using an Affordance-Based Model

The ability to predict collisions with moving objects deteriorates with aging. We followed the affordance-based model to identify optical variables that older adults had difficulty using for collision prediction. We reproduced a modified version of the interception task used in Steinmetz (Steinmetz, Layton, Powell, & Fajen, 2020, "Affordance-based versus current - future accounts of choosing whether to pursue or abandon the chase of a moving target," Journal of Vision, 20(3), 8) in a virtual reality (VR) environment and newly introduced perturbation for each of three optical variables (vertical and horizontal expansions of a moving object and the bearing angle produced between participants and a moving object). We expected that perturbation would negatively affect the performance only for those who rely on the optical variable to perform the interception task effectively. We tested 18 older and 15 younger adults and showed that older participants were not negatively affected by the perturbation for the vertical and horizontal expansion of a moving object, while they showed decreased performance when the perturbation was introduced with a bearing angle. These findings suggest that predicting collisions with moving objects deteriorates with aging because the perception of object expansion is impaired with aging.

Relative rate of expansion controls speed in one-dimensional pedestrian following

Patterns of crowd behavior are believed to result from local interactions between pedestrians. Many studies have investigated the local rules of interaction, such as steering, avoiding, and alignment, but how pedestrians control their walking speed when following another remains unsettled. Most pedestrian models assume the physical speed and distance of others as input. The present study compares such "omniscient" models with "visual" models based on optical variables. We experimentally tested eight speed control models from the pedestrian- and car-following literature. Walking participants were asked to follow a leader (a moving pole) in a virtual environment, while the leader's speed was perturbed during the trial. In Experiment 1, the leader's initial distance was varied. Each model was fit to the data and compared. The results showed that visual models based on optical expansion (\(\dot{\theta }\)) had the smallest root mean square error in speed across conditions, whereas other models exhibited increased error at longer distances. In Experiment 2, the leader's size (pole diameter) was varied. A model based on the relative rate of expansion (\(\dot{\theta }/\theta \)) performed better than the expansion rate model (\(\dot{\theta }\)), because it is less sensitive to leader size. Together, the results imply that pedestrians directly control their walking speed in one-dimensional following using relative rate of expansion, rather than the distal speed and distance of the leader.

The visual coupling between neighbours explains local interactions underlying human 'flocking'

Patterns of collective motion in bird flocks, fish schools and human crowds are believed to emerge from local interactions between individuals. Most 'flocking' models attribute these local interactions to hypothetical rules or metaphorical forces and assume an omniscient third-person view of the positions and velocities of all individuals in space. We develop a visual model of collective motion in human crowds based on the visual coupling that governs pedestrian interactions from a first-person embedded viewpoint. Specifically, humans control their walking speed and direction by cancelling the average angular velocity and optical expansion/contraction of their neighbours, weighted by visibility (1 - occlusion). We test the model by simulating data from experiments with virtual crowds and real human 'swarms'. The visual model outperforms our previous omniscient model and explains basic properties of interaction: 'repulsion' forces reduce to cancelling optical expansion, 'attraction' forces to cancelling optical contraction and 'alignment' to cancelling the combination of expansion/contraction and angular velocity. Moreover, the neighbourhood of interaction follows from Euclid's Law of perspective and the geometry of occlusion. We conclude that the local interactions underlying human flocking are a natural consequence of the laws of optics. Similar perceptual principles may apply to collective motion in other species.

Speeding through the pandemic: Perceptual and psychological factors associated with speeding during the COVID-19 stay-at-home period

During the COVID-19 stay-at-home period there were observed increases in both the percentage of cars engaged in extreme speeding, and the percentage of cars traveling below the speed limit. These changes have been attributed to unusually low traffic volume during the stay-at-home period. We develop a novel theoretical account, based on existing empirical research, of perceptual and psychological processes that may account for changes in speeding behavior under low traffic volume conditions. These include impaired ability to accurately perceive and control speed due to change in visual information, decreased salience of certain norms about socially appropriate speeds, lower perceived risk of speeding, and increased boredom leading to risk-taking behaviors. Further, we consider that individual attitude functions may account for the observed split in speeding behavior.

Spontaneous Interpersonal Synchronization of Gait: A Systematic Review

Objective

To systematically review the existing evidence of spontaneous synchronization in human gait.

Data Sources

EBSCO, PubMed, Google Scholar, and PsycINFO were searched from inception to July 2020 using all possible combinations of (1) “spontaneous interpersonal synchronization” or “spontaneous interpersonal coordination” or “unintentional interpersonal synchronization” or “unintentional interpersonal coordination” and (2) “human movement” or “movement” or “walking” or “ambulation” or “gait.”

Study Selection

Studies had to focus on spontaneous synchronization in human gait, be published in a peer-reviewed journal, present original data (no review articles were included), and be written in English. The search yielded 137 results, and the inclusion criteria were met by 16 studies.

Data Extraction

Participant demographics, study purpose, setup, procedure, biomechanical measurement, coordination analytical technique, and findings were extracted. Our synthesis focused on the context in which this phenomenon has been studied, the role of sensory information in the emergence of spontaneous interpersonal synchronization in human gait, and the metrics used to quantify this behavior.

Data Synthesis

The included 16 articles ranged from 2007-2019 and used healthy, primarily young subjects to investigate the role of spontaneous interpersonal synchronization on gait behavior, with the majority using a side-by-side walking/running paradigm. All articles reported data supporting spontaneous interpersonal synchronization, with the strength of the synchronization depending on the sensory information available to the participants.

Conclusions

Walking alongside an intact locomotor system may provide an effective and biologically variable attractor signal for rehabilitation of gait behavior. Future research should focus on the utility of spontaneous interpersonal synchronization in clinical populations as a noninvasive method to enhance gait rehabilitation.

The Untapped Potential of Virtual Reality in Rehabilitation of Balance and Gait in Neurological Disorders

Dynamic systems theory transformed our understanding of motor control by recognizing the continual interaction between the organism and the environment. Movement could no longer be visualized simply as a response to a pattern of stimuli or as a demonstration of prior intent; movement is context dependent and is continuously reshaped by the ongoing dynamics of the world around us. Virtual reality is one methodological variable that allows us to control and manipulate that environmental context. A large body of literature exists to support the impact of visual flow, visual conditions, and visual perception on the planning and execution of movement. In rehabilitative practice, however, this technology has been employed mostly as a tool for motivation and enjoyment of physical exercise. The opportunity to modulate motor behavior through the parameters of the virtual world is often ignored in practice. In this article we present the results of experiments from our laboratories and from others demonstrating that presenting particular characteristics of the virtual world through different sensory modalities will modify balance and locomotor behavior. We will discuss how movement in the virtual world opens a window into the motor planning processes and informs us about the relative weighting of visual and somatosensory signals. Finally, we discuss how these findings should influence future treatment design.

The effects of human following behaviours on decision making during aperture crossing scenarios

BACKGROUND

Everyday locomotion often requires that we navigate crowded and cluttered environments. Individuals navigating through nonconfined space will require a deviation from the straight path in order to avoid apertures smaller than 1.4 times their shoulder width. When in a crowd, humans will follow the behaviours of those directly in front of them, making changes to their walking speed and direction heading based on the changes made by the people they are following.

RESEARCH QUESTION

The current study aimed to discover whether the decisions made by young adults regarding the passability of an aperture would be influenced by the presence of a leader completing the same nonconfined aperture crossing task.

METHODS

Participants (N = 24) walked in a virtual reality environment along a 6.5 m pathway towards a goal while avoiding two virtual poles which created an aperture (0.8-1.8 times the participants' shoulder widths). For some trials, a sex-matched avatar (shoulder width of 0.8, 1.0, or 1.2 times the participants' shoulder widths) completed the aperture crossing task, using its own body-scaled information, ahead of the participant.

RESULTS

Participants walked through apertures smaller than 1.4 times their shoulder width (i.e. critical point) regardless of avatars' independent behaviours. Participants began to deviate 3.69 m from the aperture on all trials that required a deviation and approached their goal at a slower speed when the avatar was present.

SIGNIFICANCE

This study demonstrates that during a nonconfined aperture crossing task, individuals are not influenced by human following behaviours and will continue to make decisions based on their own body-scaled information.

Influence of path curvature on collision avoidance behaviour between two walkers

Navigating crowded community spaces requires interactions with pedestrians that follow rectilinear and curvilinear trajectories. In the case of rectilinear trajectories, it has been shown that the perceived action opportunities of the walkers might be afforded based on a future distance of closest approach. However, little is known about collision avoidance behaviours when avoiding walkers that follow curvilinear trajectories. Twenty-two participants were immersed in a virtual environment and avoided a virtual human (VH) that followed either a rectilinear path or a curvilinear path with a 5 m or 10 m radius curve at various distances of closest approach. Compared to a rectilinear path (control condition), the curvilinear path with a 5 m radius yielded more collisions when the VH approached from behind the participant and more inversions when the VH approached from in-front. During each trial, the evolution of the future distance of closest approach showed similarities between rectilinear paths and curvilinear paths with a 10 m radius curve. Overall, with few collisions and few inversions of crossing order, we can conclude that participants were capable of predicting future distance of closest approach of virtual walkers that followed curvilinear trajectories. The task was solved with similar avoidance adaptations to those observed for rectilinear interactions. These findings should inform future endeavors to further understand collision avoidance strategies and the role of-for example-non-constant velocities.

Nonverbal leadership emergence in walking groups

The mechanisms underlying the emergence of leadership in multi-agent systems are under investigation in many areas of research where group coordination is involved. Nonverbal leadership has been mostly investigated in the case of animal groups, and only a few works address the problem in human ensembles, e.g. pedestrian walking, group dance. In this paper we study the emergence of leadership in the specific scenario of a small walking group. Our aim is to propose a rigorous mathematical methodology capable of unveiling the mechanisms of leadership emergence in a human group when leader or follower roles are not designated a priori. Two groups of participants were asked to walk together and turn or change speed at self-selected times. Data were analysed using time-dependent cross correlation to infer leader-follower interactions between each pair of group members. The results indicate that leadership emergence is due both to contextual factors, such as an individual’s position in the group, and to personal factors, such as an individual’s characteristic locomotor behaviour. Our approach can easily be extended to larger groups and other scenarios such as team sports and emergency evacuations.

Initial impact of COVID-19’s stay-at-home order on motor vehicle traffic and crash patterns in Connecticut: an interrupted time series analysis

Introduction

Understanding how the COVID-19 pandemic has impacted our health and safety is imperative. This study sought to examine the impact of COVID-19’s stay-at-home order on daily vehicle miles travelled (VMT) and MVCs in Connecticut.

Methods

Using an interrupted time series design, we analysed daily VMT and MVCs stratified by crash severity and number of vehicles involved from 1 January to 30 April 2017, 2018, 2019 and 2020. MVC data were collected from the Connecticut Crash Data Repository; daily VMT estimates were obtained from StreetLight Insight’s database. We used segmented Poisson regression models, controlling for daily temperature and daily precipitation.

Results

The mean daily VMT significantly decreased 43% in the post stay-at-home period in 2020. While the mean daily counts of crashes decreased in 2020 after the stay-at-home order was enacted, several types of crash rates increased after accounting for the VMT reductions. Single vehicle crash rates significantly increased 2.29 times, and specifically single vehicle fatal crash rates significantly increased 4.10 times when comparing the pre-stay-at-home and post-stay-at-home periods.

Discussion

Despite a decrease in the number of MVCs and VMT, the crash rate of single vehicles increased post stay-at-home order enactment in Connecticut after accounting for reductions in VMT.

Evaluating Human Movement Coordination During Immersive Walking in a Virtual Crowd

This paper describes our investigation on how participants coordinate movement behavior in relation to a virtual crowd that surrounds them while immersed in a virtual environment. The participants were immersed in a virtual metropolitan city and were instructed to cross the road and reach the opposite sidewalk. The participants performed the task ten times. The virtual crowd that surrounded them was scripted to move in the same direction. During the experiment, several measurements were obtained to evaluate human movement coordination. Moreover, the time and direction in which the participants started moving toward the opposite sidewalk were also captured. These data were later used to initialize the parameters of simulated characters that were scripted to become part of the virtual crowd. Measurements were extracted from the simulated characters and used as a baseline to evaluate the movement coordination of the participants. By analyzing the data, significant differences between the movement behaviors of the participants and the simulated characters were found. However, simple linear regression analyses indicated that the movement behavior of participants was moderately associated with the simulated characters' movements when performing a locomotive task within a virtual crowd population. This study can be considered as a baseline for further research that evaluates the movement coordination of participants during human-virtual-crowd interactions using measurements obtained by the simulated characters.

Decoding collective communications using information theory tools

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

Timing and correction of stepping movements with a virtual reality avatar

Research into the ability to coordinate one's movements with external cues has focussed on the use of simple rhythmic, auditory and visual stimuli, or interpersonal coordination with another person. Coordinating movements with a virtual avatar has not been explored, in the context of responses to temporal cues. To determine whether cueing of movements using a virtual avatar is effective, people's ability to accurately coordinate with the stimuli needs to be investigated. Here we focus on temporal cues, as we know from timing studies that visual cues can be difficult to follow in the timing context. Real stepping movements were mapped onto an avatar using motion capture data. Healthy participants were then motion captured whilst stepping in time with the avatar's movements, as viewed through a virtual reality headset. The timing of one of the avatar step cycles was accelerated or decelerated by 15% to create a temporal perturbation, for which participants would need to correct to, in order to remain in time. Step onset times of participants relative to the corresponding step-onsets of the avatar were used to measure the timing errors (asynchronies) between them. Participants completed either a visual-only condition, or auditory-visual with footstep sounds included, at two stepping tempo conditions (Fast: 400ms interval, Slow: 800ms interval). Participants' asynchronies exhibited slow drift in the Visual-Only condition, but became stable in the Auditory-Visual condition. Moreover, we observed a clear corrective response to the phase perturbation in both the fast and slow tempo auditory-visual conditions. We conclude that an avatar's movements can be used to influence a person's own motion, but should include relevant auditory cues congruent with the movement to ensure a suitable level of entrainment is achieved. This approach has applications in physiotherapy, where virtual avatars present an opportunity to provide the guidance to assist patients in adhering to prescribed exercises.

Walking with avatars: Gait-related visual information for following a virtual leader

Dynamic situations, such as interactive sports or walking on a busy street, impose high demands on a person's ability to interact with (others in) its environment (i.e., 'interact-ability'). The current study examined how distance regulation, a fundamental component of these interactions, is mediated by different sources of visual information. Participants were presented with a back and forwards moving virtual leader, which they had to follow by walking back and forwards themselves. We presented the leader in several appearances that differed in the presence of segmental (i.e., relative movements of body segments), cadence-related (i.e., sway and bounce), and global (i.e., optical expansion-compression) information. Results indicated that removing segmental motion information from the virtual leader significantly deteriorated both temporal synchronization and spatial accuracy of the follower to the leader, especially when the movement path of the leader was less regular/predictable. However, no difference was found between cadence-related and global motion information appearances. We argue that regulating distance with others effectively requires a versatile attunement to segmental and global motion information depending on the specific task demands. The results further support the notion that detection of especially segmental information allows for more timely 'anticipatory' tuning to another person's locomotor movements and intentions.

Local interactions underlying collective motion in human crowds

It is commonly believed that global patterns of motion in flocks, schools and crowds emerge from local interactions between individuals, through a process of self-organization. The key to explaining such collective behaviour thus lies in deciphering these local interactions. We take an experiment-driven approach to modelling collective motion in human crowds. Previously, we observed that a pedestrian aligns their velocity vector (speed and heading direction) with that of a neighbour. Here we investigate the neighbourhood of interaction in a crowd: which neighbours influence a pedestrian's behaviour, how this depends on neighbour position, and how the influences of multiple neighbours are combined. In three experiments, a participant walked in a virtual crowd whose speed and heading were manipulated. We find that neighbour influence is linearly combined and decreases with distance, but not with lateral position (eccentricity). We model the neighbourhood as (i) a circularly symmetric region with (ii) a weighted average of neighbours, (iii) a uni-directional influence, and (iv) weights that decay exponentially to zero by 5 m. The model reproduces the experimental data and predicts individual trajectories in observational data on a human 'swarm'. The results yield the first bottom-up model of collective crowd motion.

Collision Avoidance With Multiple Walkers: Sequential or Simultaneous Interactions?

Collision avoidance between multiple walkers, such as pedestrians in a crowd, is based on a reciprocal coupling between the walkers with a continuous loop between perception and action. Such interpersonal coordination has previously been studied in the case of dyadic locomotor interactions. However, when walking through a crowd of people, collision avoidance is not restricted to dyadic interactions. We examined how dyadic avoidance (1 vs. 1) compared to triadic avoidance (1 vs. 2). Additionally, we examined how the dynamics of a passable gap between two walkers affected locomotor interactions. To this end, we manipulated the starting formation of two walkers that formed a potentially pass-able gap for the other walker. We analyzed the interactions in terms of the evolution over time of the Minimal Predicted Distance and the Dynamics of the Gap, which both provide information about what action is afforded (i.e., passing in front/behind and the pass-ability of the gap). Results showed that some triadic interactions invited for sequential interactions, resulting in avoidance strategies comparable with dyadic interactions. However, some formations resulted in simultaneous interactions where the dynamics of the pass-ability of the gap revealed that the coordination strategy emerged over time through the bi-directional interactions between all walkers. Future work should address which circumstances invite for simultaneous and which for sequential interactions between multiple walkers. This study contributed toward understanding how collision is avoided between multiple walkers at the level of the local interactions.

Guided by gaze: Prioritization strategy when navigating through a virtual crowd can be assessed through gaze activity

Modelling crowd behavior is essential for the management of mass events and pedestrian traffic. Current microscopic approaches consider the individual's behavior to predict the effect of individual actions in local interactions on the collective scale of the crowd motion. Recent developments in the use of virtual reality as an experimental tool have offered an opportunity to extend the understanding of these interactions in controlled and repeatable settings. Nevertheless, based on kinematics alone, it remains difficult to tease out how these interactions unfold. Therefore, we tested the hypothesis that gaze activity provides additional information about pedestrian interactions. Using an eye tracker, we recorded the participant's gaze behavior whilst navigating through a virtual crowd. Results revealed that gaze was consistently attracted to virtual walkers with the smallest values of distance at closest approach (DCA) and time to closest approach (TtCA), indicating a higher risk of collision. Moreover, virtual walkers gazed upon before an avoidance maneuver was initiated had a high risk of collision and were typically avoided in the subsequent avoidance maneuver. We argue that humans navigate through crowds by selecting only few interactions and that gaze reveals how a walker prioritizes these interactions. Moreover, we pose that combining kinematic and gaze data provides new opportunities for studying how interactions are selected by pedestrians walking through crowded dynamic environments.

Collective Motion in Human Crowds

The balletic motion of bird flocks, fish schools, and human crowds is believed to emerge from local interactions between individuals, in a process of self-organization. The key to explaining such collective behavior thus lies in understanding these local interactions. After decades of theoretical modeling, experiments using virtual crowds and analysis of real crowd data are enabling us to decipher the 'rules' governing these interactions. Based on such results, we build a dynamical model of how a pedestrian aligns their motion with that of a neighbor, and how these binary interactions are combined within a neighborhood in a crowd. Computer simulations of the model generate coherent motion at the global level and reproduce individual trajectories at the local level. This approach yields the first experiment-driven, bottom-up model of collective motion, providing a basis for understanding more complex patterns of crowd behavior in both everyday and emergency situations.

Collision Avoidance Behavior between Walkers: Global and Local Motion Cues

Daily activities require agents to interact with each other, such as during collision avoidance. The nature of visual information that is used for a collision free interaction requires further understanding. We aim to manipulate the nature of visual information in two forms, global and local information appearances. Sixteen healthy participants navigated towards a target in an immersive computer-assisted virtual environment (CAVE) using a joystick. A moving passive obstacle crossed the participant's trajectory perpendicularly at various pre-defined risks of collision distances. The obstacle was presented with one of five virtual appearances, associated to global motion cues (i.e., a cylinder or a sphere), or local motion cues (i.e., only the legs or the trunk). A full body virtual walker, showing both local and global motion cues, used as a reference condition. The final crossing distance was affected by the global motion appearances, however, appearance had no qualitative effect on motion adaptations. These findings contribute towards further understanding what information people use when interacting with others.

How Interpersonal Coordination Affects Individual Behavior (and Vice Versa): Experimental analysis and adaptive HKB model of social memory

How one behaves after interacting with a friend may not be the same as before the interaction. The present study investigated which spontaneous coordination patterns formed between two persons and whether a remnant of the interaction remained ("social memory"). Pairs of people sat face-to-face and continuously flexed index fingers while vision between partners was manipulated to allow or prevent information exchange. Trials consisted of three successive twenty-second intervals: without vision, with vision, and again without vision. Steady, transient, or absent phase coupling was observed during vision. In support of social memory, participants tended to remain near each other's movement frequency after the interaction ended. Furthermore, the greater the stability of interpersonal coordination, the more similar partners' post-interactional frequencies became. Proposing that social memory resulted from prior frequency adaptation, a model based on Haken-Kelso-Bunz oscillators reproduced the experimental findings, even for patterns observed on individual trials. Parametric manipulations revealed multiple routes to social memory through the interplay of adaptation and other model parameters. The experimental results, model, and interpretation motivate potential future research and therapeutic applications.

How cognitive heuristics can explain social interactions in spatial movement

The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour.

Intercepting a moving target: On-line or model-based control?

When walking to intercept a moving target, people take an interception path that appears to anticipate the target's trajectory. According to the constant bearing strategy, the observer holds the bearing direction of the target constant based on current visual information, consistent with on-line control. Alternatively, the interception path might be based on an internal model of the target's motion, known as model-based control. To investigate these two accounts, participants walked to intercept a moving target in a virtual environment. We degraded the target's visibility by blurring the target to varying degrees in the midst of a trial, in order to influence its perceived speed and position. Reduced levels of visibility progressively impaired interception accuracy and precision; total occlusion impaired performance most and yielded nonadaptive heading adjustments. Thus, performance strongly depended on current visual information and deteriorated qualitatively when it was withdrawn. The results imply that locomotor interception is normally guided by current information rather than an internal model of target motion, consistent with on-line control.

Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match

The combination of sports sciences theorization and social networks analysis (SNA) has offered useful new insights for addressing team behavior. However, SNA typically represents the dynamics of team behavior during a match in dyadic interactions and in a single cumulative snapshot. This study aims to overcome these limitations by using hypernetworks to describe illustrative cases of team behavior dynamics at various other levels of analyses. Hypernetworks simultaneously access cooperative and competitive interactions between teammates and opponents across space and time during a match. Moreover, hypernetworks are not limited to dyadic relations, which are typically represented by edges in other types of networks. In a hypernetwork, n-ary relations (with n > 2) and their properties are represented with hyperedges connecting more than two players simultaneously (the so-called simplex-plural, simplices). Simplices can capture the interactions of sets of players that may include an arbitrary number of teammates and opponents. In this qualitative study, we first used the mathematical formalisms of hypernetworks to represent a multilevel team behavior dynamics, including micro (interactions between players), meso (dynamics of a given critical event, e.g., an attack interaction), and macro (interactions between sets of players) levels. Second, we investigated different features that could potentially explain the occurrence of critical events, such as, aggregation or disaggregation of simplices relative to goal proximity. Finally, we applied hypernetworks analysis to soccer games from the English premier league (season 2010-2011) by using two-dimensional player displacement coordinates obtained with a multiple-camera match analysis system provided by STATS (formerly Prozone). Our results show that (i) at micro level the most frequently occurring simplices configuration is 1vs.1 (one attacker vs. one defender); (ii) at meso level, the dynamics of simplices transformations near the goal depends on significant changes in the players' speed and direction; (iii) at macro level, simplices are connected to one another, forming "simplices of simplices" including the goalkeeper and the goal. These results validate qualitatively that hypernetworks and related compound variables can capture and be used in the analysis of the cooperative and competitive interactions between players and sets of players in soccer matches.

Quantifying and Modeling Coordination and Coherence in Pedestrian Groups

Coherent collective behavior emerges from local interactions between individuals that generate group dynamics. An outstanding question is how to quantify group coordination of non-rhythmic behavior, in order to understand the nature of these dynamics at both a local and global level. We investigate this problem in the context of a small group of four pedestrians walking to a goal, treating their speed, and heading as behavioral variables. To measure the local coordination between pairs of pedestrians, we employ cross-correlation to estimate coupling strength and cross-recurrence quantification (CRQ) analysis to estimate dynamic stability. When compared to reshuffled virtual control groups, the results indicate lower-dimensional behavior and a stronger, more stable coupling of walking speed in real groups. There were no differences in heading alignment observed between the real and virtual groups, due to the common goal. By modeling the local speed coupling, we can simulate coordination at the dyad and group levels. The findings demonstrate spontaneous coordination in pedestrian groups that gives rise to coherent global behavior. They also offer a methodological approach for investigating group dynamics in more complex settings.

Influence of gait mode and body orientation on following a walking avatar

Regulating distance with a moving object or person is a key component of human movement and of skillful interpersonal coordination. The current set of experiments aimed to assess the role of gait mode and body orientation on distance regulation using a cyclical locomotor tracking task in which participants followed a virtual leader. In the first experiment, participants moved in the backward-forward direction while the body orientation of the virtual leader was manipulated (i.e., facing towards, or away from the follower), hence imposing an incongruence in gait mode between leader and follower. Distance regulation was spatially less accurate when followers walked backwards. Additionally, a clear trade-off was found between spatial leader-follower accuracy and temporal synchrony. Any perceptual effects were overshadowed by the effect of one's gait mode. In the second experiment we examined lateral following. The results suggested that lateral following was also constrained strongly by perceptual information presented by the leader. Together, these findings demonstrated how locomotor tracking depends on gait mode, but also on the body orientation of whoever is being followed.

Effects of visual information on decision making during way-finding in emergency and non-emergency situations

Finding the way out of a building during evacuation is not an easy task. Ideally, instructions provide clear and unambiguous information to occupants about the best means to evacuate. However, many times, building occupants may find the best course of action is not always clear. Conflicting or ambiguous cues can make a process that requires a quick response, slow and possibly more dangerous. Emergency signage may be vague, conflicting with other cues, or easily overlooked. The egress route directed by signage may appear difficult to traverse or dangerous. It is crucial then to best understand how evacuees find, interpret, and act upon visual information provided by emergency signage and egress routes in emergency situations. We tested the way visual information of signage and routes is used when an occupant needs to evacuate a building. In a virtual reality experiment, conflicting visual cues were pitted against each other in order to best understand how participants use visual information.

How visual information influences coordination dynamics when following the leader

Coordinating one's movements with others is an important aspect of human interactions. Regulating the distance to other moving agents is often necessary to achieve specific task goals such as in invasion sports. This study aimed to examine how distance regulation is mediated by different sources of information that are typically available when humans coordinate their actions to others. Participants followed a virtual leader that moved backwards and forwards, and were instructed to maintain the initial distance. In one condition, participants were presented with a life-size fully animated human avatar as the leader, displaying both segmental (limb motion) and global (optical expansion) motion information. In the other condition, participants had to follow an expanding and receding sphere in which segmental motion information was absent. Optical expansion rates revealed that participants regulated distance equally effective in both conditions. Given the phase relation and response times to direction changes however, the timing to the leader appeared to be more accurate in the avatar condition. These results provide support that forward-backward following can indeed be successfully mediated through global information, but that detection of segmental information allows for earlier tuning to another person's movement intentions.