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Human Factors Engineering

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KRC has performed Human Factors studies for customers to develop the relationship of human subjective interpretations of vehicle handling in snow to objective vehicle handling performance data from a proving ground’s road surface. In this study KRC collected subjective data from the general public after driving vehicles with various types of drive and stability control systems on packed snow surfaces. KRC had also instrumented the vehicles to collect vehicle lateral and longitudinal acceleration, yaw, speed, brake useage and steering wheel angle and recorded this data for each individual performing a subjective evaluation.

Snow Cornering

Working with MTU’s Mechanical Engineering department faculty and graduate students, the team used statistical analysis to analyze and correlate the subjective and objective data. MTU faculty and graduate students then developed neural net models that were able to predict human subjective evaluations of vehicle handling performance on snow for various drive or control systems based on data taken at a proving ground. This study also involved the development of specific vehicle metrics for rating the general public's interpretations and also putting the objective data into a form that could be related to the subjective interpretations.



In the end, the customer had a working non-linear model that could relate how well people would like a certain type of vehicle for driving on snow based on test data collected at their proving ground.

Input Output Chart

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