Development of hazard prediction test and interventions for two-wheeled electric vehicle riders in China.

Traffic Inj Prev

Joint International Research Laboratory on Traffic Psychology & Behaviours, Fuzhou University, Fujian, China.

Published: October 2024

AI Article Synopsis

  • The study aimed to create a hazard prediction test for two-wheeled electric vehicle (TWEV) riders and evaluated two interventions to improve their hazard perception skills.
  • In Study 1, a video test was developed to categorize riders into high and low hazard prediction groups and validated using ROC curves.
  • Study 2 found that both the self-commentary and the "what happens next" (WHN) interventions significantly improved riders' hazard prediction abilities, with WHN proving more effective, and these improvements persisted even after a week.

Article Abstract

Objective: This paper aimed to develop a hazard prediction test and enhance two-wheeled electric vehicle (TWEV) riders' hazard perception and prediction capabilities interventions by executing two distinct studies. Study 1 aimed to develop and validate a hazard prediction test. Study 2 evaluated the efficacy of two interventions, self-commentary and what happens next (WHN), integrating expert commentary.

Method: For Study 1, a video-based hazard prediction test was developed through video recording and clipping, with participants categorized into high and low prediction ability groups for experimentation. Data analysis employed the receiver operating characteristic (ROC) curve. Study 2 categorized participants into four groups: self-commentary with licenses (SCL), self-commentary without licenses (SCNL), WHN with licenses (WHNL), and WHN without licenses (WHNNL), for conducting a one-week intervention experiment. Data collected from participants' pre-intervention, post-intervention, and aftereffect tests were subjected to repeated measures analysis of variance (ANOVA).

Results: Analysis of the ROC curve indicated the test can distinguish the riders with different hazard prediction levels. ANOVA results demonstrated that the measurement time had a significant positive effect on scores ( < 0.001). Both interventions significantly improved hazard prediction ability ( < 0.05), and the effect persisted one week after administration. The effect of the WHN intervention was significantly greater than the self-commentary method across all time points.

Conclusion: The hazard prediction test developed in this study could assess riders' hazard prediction ability, with the identified interventions demonstrating effectiveness in enhancing this ability. These findings suggested potential application in future qualification tests for TWEV riders, contributing to enhanced traffic safety awareness among TWEV riders in China, thus advancing overall traffic safety.

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Source
http://dx.doi.org/10.1080/15389588.2024.2410417DOI Listing

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