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.
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
on snow based on test data collected at their proving ground.