A Cloud-Based Solutions to Commercial Driver Hazard Perception Training and Screening
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2017/08/21
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Series: Grant Final Reports
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Description:Motor vehicle crashes are the leading cause of work-related fatalities in the U.S. and costs employers $60 billion annually. However, few studies have assessed the hazard detection (HD) challenges of experienced, skilled drivers. This paper presents the pilot study results of a HD training program, the Commercial Driver Assessment & Training System (CDATS), developed for commercial motor vehicle (CMV) drivers. The training involved simulation-based videos that highlight potential vehicle, pedestrian, and visually hidden hazards during unprotected intersection maneuvers: left-turn, right-turn, and straight-thru. Low-fidelity, driving simulations were designed to reinforce video lessons and increase the expectation and detection of potential hazards. A CDATS prototype was evaluated using a driving simulator HD task presented to a sample of 16 short-haul, single-unit truck, CMV drivers before and after random assignment to CDATS training or a control group. Results provided two key findings. First, experienced, CMV drivers can also exhibit poor HD skills-particularly for visually hidden and visible pedestrian hazards-and may benefit from HD training. Second, the CDATS program showed potential to improve HD skills for CMV drivers during unprotected intersection maneuvers. Post-training results suggested overall HD improvement in the CDATS training group with no change in the control group. Results of this project highlight the traffic safety needs of CMV drivers and informs the development of future CMV driver safety and training interventions. [Description provided by NIOSH]
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Pages in Document:1-25
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NIOSHTIC Number:nn:20052939
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Citation:Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, R43-OH-011160, 2017 Aug; :1-25
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Contact Point Address:Theodore J. Rosenthal, Systems Technology, Inc. (STI), 13766 Hawthorne Blvd., Hawthorne, CA 90250
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Email:trosenthal@systemstech.com
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Federal Fiscal Year:2017
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Performing Organization:Systems Technology, Inc., Hawthorne, California
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Peer Reviewed:False
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Start Date:20160901
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Source Full Name:National Institute for Occupational Safety and Health
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End Date:20170531
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Main Document Checksum:urn:sha-512:01a69a2d8021d883b648809f91a595cc7a959a57ecd36b7c659237574e9fd319bc5ce4f52cf769e8ecbefc8c03e77983e1845d42927873f9f0fced0f708fd0e5
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