Predicting the effects of in-car interface use on driver performance: an integrated model approach

While researchers have made great strides in evaluating and comparing user interfaces using computational models and frameworks, their work has focused almost exclusively on interfaces that serve as the only or primary task for the user. This paper presents an approach of evaluating and comparing interfaces that users interact with as secondary tasks while executing a more critical primary task. The approach centers on the integration of two computational behavioral models, one for the primary task and another for the secondary task. The resulting integrated model can then execute both tasks together and generate a priori predictions about the effects of one task on the other. The paper focuses in particular on the domain of driving and the comparison of four dialing interfaces for in-car cellular phones. Using the ACT-R cognitive architecture (Anderson & Lebiere, 1998) as a computational framework, behavioral models for each possible dialing interface were integrated with an existing model of driver behavior (Salvucci, Boer & Liu, in press). The integrated model predicted that two different manual-dialing interfaces would have significant effects on driver steering performance while two different voice-dialing interfaces would have no significant effect on performance. An empirical study conducted with human drivers in a driving simulator showed that while model and human performance differed with respect to overall magnitudes, the model correctly predicted the overall pattern of effects for human drivers. These results suggest that the integration of computational behavioral models provides a useful, practical method for predicting the effects of secondary-task interface use on primary-task performance.