Vehicle automation and driving performance

In considering the human contribution to accidents, it seems necessary to make a distinction between errors and violations; two forms of aberration which may have different psychological origins and demand different modes of remediation. The present study investigated whether this distinction was justified for self-reported driver behaviour. Five hundred and twenty drivers completed a driver behaviour questionnaire (DBQ) which asked them to judge the frequency with which they committed various types of errors and violations when driving. Three fairly robust factors were identified: violations, dangerous errors, and relatively harmless lapses, respectively. Violations declined with age, errors did not. Men of all ages reported more violations than women. Women, however, were significantly more prone to harmless lapses (or more honest) than men. These findings were consistent with the view that errors and violations are indeed mediated by different psychological mechanisms. Violations require explanation in terms of social and motivational factors, whereas errors (slips, lapses, and mistakes) may be accounted for by reference to the information-processing characteristics of the individual.

Two experiments are reported which examined operators' trust in and use of the automation in a simulated supervisory process control task. Tests of the integrated model of human trust in machines proposed by Muir (1994) showed that models of interpersonal trust capture some important aspects of the nature and dynamics of human-machine trust. Results showed that operators' subjective ratings of trust in the automation were based mainly upon their perception of its competence. Trust was significantly reduced by any sign of incompetence in the automation, even one which had no effect on overall system performance. Operators' trust changed very little with experience, with a few notable exceptions. Distrust in one function of an automatic component spread to reduce trust in another function of the same component, but did not generalize to another independent automatic component in the same system, or to other systems. There was high positive correlation between operators' trust in and use of the automation; operators used automation they trusted and rejected automation they distrusted, preferring to do the control task manually. There was an inverse relationship between trust and monitoring of the automation. These results suggest that operators' subjective ratings of trust and the properties of the automation which determine their trust, can be used to predict and optimize the dynamic allocation of functions in automated systems.