The aim of this research was to analyze if current generation PC-driven virtual reality simulations can be used to accurately mimic and therefore, observe behavior at a crosswalk. Toward that goal, the following research tasks were carried out: a) Designing a 3D virtual crosswalk and recruiting volunteers to wear the HTC Vive headset and to walk across the street, b) Setting up cameras near the midblock crosswalk on University Drive at California Polytechnic State University, San Luis Obispo to observe pedestrians, and c) Comparing pedestrian behavior data from both the virtual and real midblock crosswalk. The comparison was based on the following criteria: a) Pedestrian walking speed, b) Observation patterns prior to crossing the road, characterized by glancing left and right to detect cars, and c) Pedestrians’ decisions as to where to cross, defined by if they chose to walk directly on or outside of the midblock crosswalk. Walking speed and the number of pedestrians who looked left and right before crossing were significantly different in both the virtual and real environments. On the other hand, the proportion of people who chose to walk on the crosswalk was similar in both environments. This result indicates that there is a future potential in using virtual reality to analyze pedestrian behavior at roundabouts. Although this study showed that PC-driven virtual reality is not effective in replicating pedestrian walking speeds or pedestrian observation patterns at a midblock crosswalk, researchers may expect PC-driven virtual reality to have greater applications within the transportation discipline once the technology improves over the years. Potential improvements in technology that would help include being wireless, allowing users to walk in a non-confining space, and making the equipment more affordable, allowing the technology to become more mainstream.
Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-3031 |
Date | 01 June 2017 |
Creators | Mai, Kristina Lynn |
Publisher | DigitalCommons@CalPoly |
Source Sets | California Polytechnic State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Master's Theses |
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