Evaluating methods to measure time-to-contact

Abstract

Many every-day activities necessitate an estimate of the time remaining until an object will hit us: the time-to-contact (TTC). Observers' skill in estimating TTC has been studied by considering the use and combination of key visual signals (e.g. looming and disparity). However, establishing observers' proficiency in estimating TTC can be complicated, as the variable of interest (time) is typically highly correlated with other signals (e.g. target velocity or displacement). As a result, observers' responses may be based on correlates of TTC rather than on TTC itself. Here we evaluate two widely-used TTC tasks: one absolute task in which observers pressed a button to indicate the estimated TTC, and a relative task in which TTC was judged relative to a reference. We test how a wide range of experimental variables that co-vary with TTC contribute to observers' judgments. We systematically vary the correlation between TTC and its covariates and test how psychophysical judgments are affected. We show that for both absolute and relative estimation tasks, observers' responses are best explained on the basis that they judge TTC rather than one (or more) of its covariates. Our results suggest that relative tasks are preferable when assessing TTC, and we suggest a number of analyses methods to ensure that participants' judgements correspond to the variable under investigation.

Impending Collision Judgment from an Egocentric Perspective in Real and Virtual Environments: A Review

“…TTC and TTA can be determined from three-dimensional low-order information, or deduced solely from two-dimensional optical variables, such as looming. The low-order information method builds on the ratio of the oncoming object’s distance to the approaching velocity and is computed as follows: The looming method , on the other hand, consists of Lee’s (1976) concept using the variable τ, also noted as tau , relying on the visually perceived angular size of the approaching object, for example, vehicle height, that is taken in proportion to the instantaneous rate of its size expansion—perceived while approaching—and is computed as follows: While numerous studies have shown that human participants are capable of estimating low-order parameters, such as distance and velocity, humans will mainly rely on the perceived change of optic array to judge an approaching object (Lugtigheid & Welchman, 2011; McLeod & Ross, 1983; Yan, Lorv, Li, & Sun, 2011). Interestingly, this contrasts machine systems such as autonomous vehicles which usually deduce temporal distances based on three-dimensional, sensor-tracked parameters such as described in the low-order information method .…”

The common rate control account of prediction motion

“…1c). This has a slightly different history and is more often called 'time-to-contact estimation', or 'arrival-time estimation' (Hecht & Savelsburgh, 2004;Lee, 1976;Lugtigheid & Welchman, 2011;Schiff & Detwiler, 1979).…”

Temporal Audiovisual Motion Prediction in 2D- vs. 3D-Environments

“…Even in humans this ability still governs behaviour in everyday traffic and sport, e.g., when driving a car, crossing a road or catching a ball. Previous studies on motion prediction predominantly focused on different tasks (e.g., time-to-arrival, Schiff and Oldak, 1990 ; same-different-discrimination, Kawachi and Gyoba, 2006 ; predicted motion, Prime and Harris, 2010 ) and the visual modality (e.g., DeLucia, 2004 ; Lugtigheid and Welchman, 2011 ; Landwehr et al, 2013 ).…”