Chemical Engineering Transactions (Jun 2017)

Assessing Perceptions and Alerts of Tractor Instability

  • N. Ochoa Lleras,
  • S. Brennan,
  • D. Murphy,
  • J. Klena,
  • P. Garvey,
  • H.J. Sommer III

DOI
https://doi.org/10.3303/CET1758002
Journal volume & issue
Vol. 58

Abstract

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This paper presents ongoing results from a Tractor Driving Simulator study at Penn State University studying how tractor overturn events can be prevented. The simulator is used to expose subjects, in a controlled environment, to situations that would be unsafe to test in the field. Two sets of experiments are examined here. The first experiment consisted of a tilt perception study whose goal was to quantify the ability of subjects to remember and reproduce certain poses with pitch and roll angles. Nineteen subjects were individually exposed to a tilt angle; then, they used a controller to drive the simulator until they perceived they have reached the exposure angle; the process was repeated with 28 different poses representing combinations of pitch and roll of the tractor cabin. Overall, subjects reproduced angles with a smaller amplitude than they were exposed to, indicating that they were overestimating their tilt angles while actively controlling the cabin angle. Roll angles presented an overestimation of 8%, while pitch was accurately reproduced. There was no statistically significant difference between experienced tractor operators and non-experienced subjects, nor any significant influence of pitch angle on roll perception, or vice versa. The second experiment compared visual, haptic, and acoustic interfaces to alert a subject that they were driving at a hazardous roll angle. A screen with a bubble display—indicating the pitch and roll angles of the cabin—was enhanced with auditory (buzzers) and haptic (vibration on the steering wheel) alerts. When the simulator cab tilts over a pre-defined safety threshold, an alert was given to the operator along one or more alerting systems. The experiment collected the reaction times of the subjects to each type of alert interface to determine which one was the most effective at capturing the driver’s attention.