Collision Avoidance With Multiple Walkers: Sequential or Simultaneous Interactions?

Trend change analysis in the assessment of body balance during posture adjustment in reaction to anterior-posterior ground perturbation

Postural adjustments (PA) occur to counteract predictable perturbations and can be impaired as a result of musculoskeletal and neurological dysfunctions. The most common way to detect PA is through electromyography measurements or center of pressure (COP) position measurements, where analysis in time domain and frequency domain are the most common. Aim of the research was to determine whether a new method of analyzing stabilographic measurements-the COP trend change analysis (TCI) of temporary posture corrections- can expand understanding of changes in balance strategy connected with PA. The study group involved 38 individuals (27women, 11men) aged 23±2.6 years. Measurements were performed using a stabilographic platform placed on a perturbation platform. The tests involved three measurements with forward and backward momentary movements of the platform. Participants were tested in three conditions-knowing the nature, time and direction of perturbation (Tr3), knowing only the nature of perturbation (Tr2) and without any information about the perturbation (Tr1). Statistically significant differences were revealed in the last second of Tr3 for the mean velocity of COP (p<0.05) and for two TCI parameters-TCI_dV (p<0.05) and TCI_dS (p<0.01). The increase in TCI_dV was related to the increase in the mean distance between trend changes (TCI_dS) and constant value of the mean time between trend changes (TCI_dT). The increase of the mean value of TCI_dS was the result of smaller number of posture corrections with the distance 0-2 mm and lager number with the distance 4-6 mm. Obtained results proved that the TCI analysis is a method enabling an extended analysis of PA, indicating the nature of changes occurring in posture corrections-longer momentary jumps of COP-related to a change in the strategy of maintaining balance before a known disorder, which has not been analyzed in this type of research so far.

Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of ‘stripe’ formation in human data

When two streams of pedestrians cross at an angle, striped patterns spontaneously emerge as a result of local pedestrian interactions. This clear case of self-organized pattern formation remains to be elucidated. In counterflows, with a crossing angle of 180°, alternating lanes of traffic are commonly observed moving in opposite directions, whereas in crossing flows at an angle of 90°, diagonal stripes have been reported. Naka (1977) hypothesized that stripe orientation is perpendicular to the bisector of the crossing angle. However, studies of crossing flows at acute and obtuse angles remain underdeveloped. We tested the bisector hypothesis in experiments on small groups (18-19 participants each) crossing at seven angles (30° intervals), and analyzed the geometric properties of stripes. We present two novel computational methods for analyzing striped patterns in pedestrian data: (i) an edge-cutting algorithm, which detects the dynamic formation of stripes and allows us to measure local properties of individual stripes; and (ii) a pattern-matching technique, based on the Gabor function, which allows us to estimate global properties (orientation and wavelength) of the striped pattern at a time T. We find an invariant property: stripes in the two groups are parallel and perpendicular to the bisector at all crossing angles. In contrast, other properties depend on the crossing angle: stripe spacing (wavelength), stripe size (number of pedestrians per stripe), and crossing time all decrease as the crossing angle increases from 30° to 180°, whereas the number of stripes increases with crossing angle. We also observe that the width of individual stripes is dynamically squeezed as the two groups cross each other. The findings thus support the bisector hypothesis at a wide range of crossing angles, although the theoretical reasons for this invariant remain unclear. The present results provide empirical constraints on theoretical studies and computational models of crossing flows.

You may have noticed that pedestrians in a crosswalk often form multiple lanes of traffic, moving in opposite directions (180°). Such spontaneous pattern formation is an example of self-organized collective behavior, a topic of intense interdisciplinary interest. When two groups of pedestrians cross at an intersection (90°), similar diagonal stripes appear. Naka (1977) conjectured that the stripes are perpendicular to the mean walking direction of the two groups. This facilitates the forward motion of each group and reduces collisions. We present the first empirical test of the hypothesis by studying two groups of participants crossing at seven different angles (30° intervals). To analyze the striped patterns, we introduce two computational methods, a local Edge-cutting algorithm and a global Pattern-matching technique. We find that stripes are indeed perpendicular to the mean walking direction at all crossing angles, consistent with the hypothesis. But other properties depend on the crossing angle: the number of stripes increases with crossing angle, whereas the spacing of stripes, the number of pedestrians per stripe, and the crossing time all decrease. Moreover, the width of individual stripes is “squeezed” in the middle of the crossing. Future models of crowd dynamics will need to capture these properties.

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.

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.