The consequences of a road crash for vulnerable road users (VRUs), especially children, are more severe compared to car drivers; in addition, child mortality rates are predominantly attributed to road crashes. With the recent advancements in technology, virtual reality (VR) has emerged as a valuable tool for researching crash-related phenomena. This study's primary objective is to validate the use of a VR headset as a tool for investigating pedestrian behavior. We conducted tests on 122 middle school children, subjecting them to 15 scenarios involving road-crossing and strolling tasks. Kinematic data, specifically speed, was collected and statistically analyzed, comparing it to existing literature. The results obtained align with prior naturalistic studies, affirming the device's suitability for studying pedestrian behavior. Notably, no abnormal behaviors were observed during strolls. Furthermore, the riskiest behaviors, characterized by higher speeds, were predominantly associated with non-signalized crossings. These findings, in addition to validating the scenarios and tools used in this study, highlight the importance of designing intersections that minimize crash risks and educating children about road safety and crossing-related dangers.

Validation of an urban environment for pedestrian behavior analysis in full immersive virtual reality

Baldassa A.
;
Orsini F.;De Cet G.;Tagliabue M.;Rossi R.;Gastaldi M.
2024

Abstract

The consequences of a road crash for vulnerable road users (VRUs), especially children, are more severe compared to car drivers; in addition, child mortality rates are predominantly attributed to road crashes. With the recent advancements in technology, virtual reality (VR) has emerged as a valuable tool for researching crash-related phenomena. This study's primary objective is to validate the use of a VR headset as a tool for investigating pedestrian behavior. We conducted tests on 122 middle school children, subjecting them to 15 scenarios involving road-crossing and strolling tasks. Kinematic data, specifically speed, was collected and statistically analyzed, comparing it to existing literature. The results obtained align with prior naturalistic studies, affirming the device's suitability for studying pedestrian behavior. Notably, no abnormal behaviors were observed during strolls. Furthermore, the riskiest behaviors, characterized by higher speeds, were predominantly associated with non-signalized crossings. These findings, in addition to validating the scenarios and tools used in this study, highlight the importance of designing intersections that minimize crash risks and educating children about road safety and crossing-related dangers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3510948
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