A study of the human ability to detect road surface type based on steering wheel vibration feedback

Abstract

A study was performed to investigate the human ability to detect road surface type based on the associated steering wheel vibration feedback. Tangential direction acceleration time histories measured during road testing of a single mid-sized European automobile were used as the basis for the study. Scaled and frequency filtered copies of two base stimuli were presented to test subjects in a laboratory setting during two experiments which each involved 25 participants. Theory of signal detection (TSD) was adopted as the analytical framework and the results were summarised by means of the detectability index d’ and as receiver operating curve (ROC) points. The results of the experiment to investigate the effect of scaling suggested monotonic relationships between stimulus level and detection for both road surfaces. Detection of the tarmac surface improved with reductions in acceleration level while the opposite was true of the cobblestone surface. The ROC points for both surfaces were characterised by gradual increases in detection as a function of acceleration level, obtaining hit rates of nearly 100% at optimum. The results of the experiment to investigate the effect of frequency bandwidth suggested a monotonically increasing relationship between detectability and the bandwi\dth of the vibration stimuli. Detection of both road surfaces improved with increases in bandwidth. Average hit rates exceeded 80% for stimuli covering the frequency range from 0 to 80 Hz. Human detection of road surface type appears to depend on the long term memory model, or cognitive interpretation mechanism, associated with each surface. The complexity of the measured response suggests the need to categorise and classify incoming data before an optimal choice of feedback stimuli can be made in automotive steering systems.