Literature DB >> 33981134

Examination of Realism in a High-fidelity Tractor Driving Simulator.

Kayla Faust1, Carri Casteel1, Daniel V McGehee1,2, Corinne Peek-Asa1, Diane S Rohlman1, Marizen Ramirez1,3.   

Abstract

Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S., including the agricultural industry, which suffers thou- sands of crashes involving farm equipment each year. Simulated driving studies offer a safe and cost-effective way to conduct driving research that would not be feasible in the real world. A tractor driving miniSim was developed and then evaluated for realism at the University of Iowa among 99 Midwestern farm equipment operators. It is important for driving simulators to have a high degree of realism for their results to be applicable to non-simulated driving operations. High-fidelity driving simulators facilitate extrapolations made by driving research but should be re-tested for realism when changes are made to the design of the simulator. The simulator used in this study emulated a tractor cab with realistic controls, three high-resolution screens, and high-fidelity sound. After completing a 10-minute drive, farm equipment operators completed a survey and scored four specific domains assessing specific characteristics (i.e., appearance, user interface, control, and sound) of the tractor simulator's realism using a seven-point Likert scale (from 0 = not at all realistic to 6 = completely realistic). An overall realism score and domain scores were calculated. Farm equipment operators were also asked to provide recommendations for improving the tractor miniSim. Overall, farm equipment operators rated the simulator's realism favorably (i.e., >3 on a scale from 0 to 6) for all individual items and domains. The appearance domain received the highest average realism score (mean = 4.58, SD = 1.03), and the sound domain received the lowest average realism score (mean = 3.86, SD = 1.57). We found no significant differences in realism scores across farm equipment operator characteristics. The most frequently suggested improvements were to tighten the steering wheel (27%), make the front tires visible (19%), and that no improvements were needed to improve the simulator realism (18%). This study demonstrates that the new trac- tor miniSim is a viable approach to studying farm equipment operations and events that can lead to tractor-related crashes. Future studies should incorporate the suggested improvements and seek to validate the simulator as a research and outreach instrument.

Entities:  

Keywords:  Driving simulator; Farm equipment operators; Realism; Tractors

Mesh:

Year:  2020        PMID: 33981134      PMCID: PMC8112449          DOI: 10.13031/jash.14043

Source DB:  PubMed          Journal:  J Agric Saf Health        ISSN: 1074-7583


  10 in total

1.  Prevalence of ROPS-equipped tractors in U.S. aquaculture.

Authors:  M L Myers; S C Westneat; J R Myers; H P Cole
Journal:  J Agric Saf Health       Date:  2009-04

2.  Cost-effectiveness of a ROPS social marketing campaign.

Authors:  J A Sorensen; P Jenkins; B Bayes; S Clark; J J May
Journal:  J Agric Saf Health       Date:  2010-01

3.  Perceptions of tilt angles of an agricultural tractor.

Authors:  Serap Görücü; Eugenio Cavallo; Dennis Murphy
Journal:  J Agromedicine       Date:  2014       Impact factor: 1.675

4.  Prevalence of alcohol impairment and odds of a driver injury or fatality in on-road farm equipment crashes.

Authors:  Karisa K Harland; Ronald Bedford; Hongqian Wu; Marizen Ramirez
Journal:  Traffic Inj Prev       Date:  2018-03-01       Impact factor: 1.491

5.  Prevalence of hearing loss in older adults in Beaver Dam, Wisconsin. The Epidemiology of Hearing Loss Study.

Authors:  K J Cruickshanks; T L Wiley; T S Tweed; B E Klein; R Klein; J A Mares-Perlman; D M Nondahl
Journal:  Am J Epidemiol       Date:  1998-11-01       Impact factor: 4.897

6.  Characteristics of Farm Equipment-Related Crashes Associated With Injury in Children and Adolescents on Farm Equipment.

Authors:  Maisha Toussaint; Kayla Faust; Corinne Peek-Asa; Marizen Ramirez
Journal:  J Rural Health       Date:  2015-12-03       Impact factor: 4.333

7.  Characteristics of crashes with farm equipment that increase potential for injury.

Authors:  Corinne Peek-Asa; Nancy L Sprince; Paul S Whitten; Scott R Falb; Murray D Madsen; Craig Zwerling
Journal:  J Rural Health       Date:  2007       Impact factor: 4.333

8.  Six-item screener to identify cognitive impairment among potential subjects for clinical research.

Authors:  Christopher M Callahan; Frederick W Unverzagt; Siu L Hui; Anthony J Perkins; Hugh C Hendrie
Journal:  Med Care       Date:  2002-09       Impact factor: 2.983

9.  Public health application of predictive modeling: an example from farm vehicle crashes.

Authors:  Shabbar I Ranapurwala; Joseph E Cavanaugh; Tracy Young; Hongqian Wu; Corinne Peek-Asa; Marizen R Ramirez
Journal:  Inj Epidemiol       Date:  2019-06-17

10.  The effects of roadway characteristics on farm equipment crashes: a geographic information systems approach.

Authors:  Mitchell Greenan; Maisha Toussaint; Corinne Peek-Asa; Diane Rohlman; Marizen R Ramirez
Journal:  Inj Epidemiol       Date:  2016-12-20
  10 in total

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