How we avoid collisions with stationary and moving objects.

Abstract

When moving through cluttered environments we use different forms of the same source of information to avoid stationary and moving objects. A stationary obstacle can be avoided by looking at it, registering the differential parallactic displacements on the retina around it during pursuit fixation, and then acting on that information. Such information also specifies one's general heading. A moving obstacle can be avoided by looking at it, registering the displacements reflecting constancy or change in one's gaze-movement angle, and then acting on that information. Such information, however, does not generally specify one's heading. Passing in front of a moving object entails retrograde motion of objects in the deep background; collisions entail the lamellar pattern of optical flow; and passing behind entails more nearly uniform flow against one's direction of motion. Accuracy in the laboratory compares favorably with that of real-world necessities.We and other animals move through cluttered environments many times each day, often at considerable speed. Most objects in these environments are stationary and need to be avoided if we are to get safely from one place to another. Some objects also move, and these too often must be avoided. 1 Such acts of avoidance are of obvious and considerable importance; to fail to execute them with reasonable accuracy is to risk our daily well-being as well as that of others. What visual information subserves these acts, particularly for mobile-eyed creatures like ourselves?Psychological research on collisions and how to avoid them began with Gibson and Crooks (1938; see also Gibson, 1961). This research then progressed in several directions. One line has focused on driver behavior and automobile safety (e.g., Caird &

Spatial Thinking by Young Children: Neurologic Evidence for Early Development and “Educability”

“…In effect, our visual systems and brains subconsciously build a kind of imaginary shell or buffer zone around our bodies and all nearby people and objects. An alarm of some kind goes off in our heads when our subconscious "traffic monitor" notices a possible future intersection of auras (Cutting et al 1995;Hubbard and Ruppel 2000). This particular kind of eye-brain activity sets us free to ignore other people (and even vehicles on a highway) unless their aura seems likely to intersect ours.…”

A neural model of visually guided steering, obstacle avoidance, and route selection.

“…For low simulated rotational velocity (< 1 deg/sec), heading judgments are still relatively accurate (Warren & Hannon, 1988), but at higher velocities heading judgments are systematically biased in the direction of the simulated eye rotation (Royden et al 1992(Royden et al , 1994). Even at low rotational velocities, heading perception can be inaccurate if the simulated rotation is designed to mimic tracking of an independently moving object, rather than a fixed point in the environment (Cutting, Vishton, & Braren, 1995).…”

Computational Streetscapes

“…Certainly, some interactions that pedestrians engage in are physical, but most are not. For example, physics approaches to treating streetscape dynamics may invoke considerations of distance and personal space in collision, which are relevant in examining Newtonian-type forces between pedestrians [88,91], whether through tangible collisions, or as human-perceived repulsion and attraction effects [73,[92][93][94][95][96]. However, decades of socio-behavioral science provide alternative cognitive and social explanations for much of the dynamics presented in physics-based models [45].…”

“…Interestingly, psychologists often make use of virtual reality environments and game engines as proxy settings for their experiments, although these are generally limited to avatar representation of interacting participants for task-performance, rather than representation of the behaviors for characters within those environments [207][208][209]. Much of the perception (awareness) and cognition (understanding) that takes place in streetscapes is well-explored in the psychology of spatial behavior and movement [93,210], and recently this work has extended to cognitive neuroscience [211]. At least anecdotally, aspects of both observational [9] and clinical [5,27] studies seem to have some synergy with computational methods used in streetscape modeling (see Torrens [65] for a discussion).…”

“…In particular, work on visual aspects of streetscape behavior is finding considerable interest in biology (and computational biology), where it has proven useful in relating gaze and the acquisition of environmental information to ideas about how humans and animals use visual flow to process environmental stimuli [68,69]. Thanks in large part to the development of motion capture technology alongside eye-tracking systems, new work is also being performed in the intellectual space between vision and locomotion that connects action and response to issues of neurological pathways [92,93,210,238], timing, and ordering in cognition [239][240][241], to motor impairment as a function of memory loss [242], and other related issues.…”