Young drivers are overrepresented in motor-vehicle crashes compared to experienced drivers. Research shows that young drivers are generally clueless, not careless, failing to anticipate and mitigate latent hazards. There are several error-feedback training interventions that emphasize the teaching of latent hazard anticipation skills (e.g., risk awareness and perception training, RAPT) and a few that emphasize both the teaching of hazard anticipation and hazard mitigation skills (e.g., the driver simulation ACCEL). In the current study, a virtual reality, headset-based latent hazard anticipation and mitigation training program (V-RAPT) was developed on a head-mounted display (Oculus Rift). The headset provides the participant with a 100-degree wide field of view of six high-risk driving scenarios, the view changing appropriately as the participant rotates his or her head. Thirty-six young drivers were exposed to one of three training programs—V-RAPT, RAPT, and a placebo—and then evaluated on a driving simulator. Eye movement and vehicle data were collected throughout the simulator evaluation. The drives included the six scenarios used in training and four other scenarios dissimilar to the ones used in training, but previously validated as measures of hazard anticipation. The drivers trained on V-RAPT were found to anticipate a significantly greater proportion (86.25%) of latent hazards than the RAPT (62.36%) and placebo (30.97%) trained drivers. The V-RAPT trained drivers were also found to be better at mitigating potential threats. The virtual reality, headset-based training program holds out the promise of improving drivers’ ability to anticipate and mitigate latent threats and thereby reduce crashes.


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    Title :

    Virtual Reality Headset Training: Can It Be Used to Improve Young Drivers’ Latent Hazard Anticipation and Mitigation Skills


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2018-05-05




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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