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Comparison of the Minisim and Stisim Driving Simulators for the Detection of Impairment: An Alcohol Validation Study
Author(s) -
Gary G. Kay,
Omar Ahmad,
Timothy L. Brown,
Andrew Veit
Publication year - 2013
Language(s) - English
Resource type - Conference proceedings
DOI - 10.17077/drivingassessment.1487
Subject(s) - driving simulator , sensitivity (control systems) , simulation , alcohol , standard deviation , blood alcohol , computer science , statistics , poison control , medicine , mathematics , injury prevention , engineering , medical emergency , chemistry , biochemistry , electronic engineering
Detection of alcohol impairment is often used to evaluate the sensitivity of a protocol to detect the effects of other types of impairment. This study was designed to compare the sensitivity of two simulator platforms with different underlying architectures using equivalent driving scenarios. The driving scenario consisted of a twenty minute drive on a relatively straight rural roadway with a divided attention task presented infrequently during the drive. A total of 18 subjects completed drives on both simulators at two levels of t blood alcohol concentration (BAC). It was hypothesized that both simulator platforms would be sensitive to the effects of alcohol. On driving variables and on divided attention variables the MiniSim simulator showed greater sensitivity to the impairing effects of alcohol (at doses below 0.10% BAC) than was found with the STI simulator. The Standard Deviation of Lane Position (SDLP) variable (lane position deviation) was sensitive to alcohol effects with both simulators. However, there was clearly greater sensitivity seen with the MiniSim simulator. For a number of driving and divided attention variables significant results were obtained with the MiniSim, whereas results for the STISIM failed to show a significant alcohol effect. The greater sensitivity of the MiniSim compared to the STISIM is potentially due to a number of differences between the two simulators, though the difference in the vehicle dynamics model would be expected to be the largest determining factor.

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