Using Virtual Environments to Assess Time-to-Contact Judgments from Pedestrian Viewpoints

Abstract

This thesis explores the use of desktop and immersive virtual environments to study judgments that pedestrians make when deciding to cross a street. In particular, the ability of people to discriminate and estimate time-to-contact (TTC) for approaching vehicles under a variety of conditions is examined. Four experiments observing time-to-contact judgments under various conditions were conducted. These conditions are the effect of type of vehicle, viewpoint, presentation mode, and TTC reference value on TTC judgments. No significant effect of type of vehicle or of viewpoint is found, extending prior work to cover all views typically encountered by pedestrians. Discrimination of short reference values for TTC judgments is consistent with the literature, but performance degrades significantly for long reference values. We find no significant difference between judgments made in a desktop environment versus a head-mounted display, indicating that tracking the approaching vehicle with one's head does not aid discrimination. In general, people appear to use strategies similar to those that pedestrians use to make real-world, street-crossing decisions.