Validating the random search model for a double-target search task

Abstract

A random visual search model was fit to 2980 search times obtained from a double-target search task. The overall adequacy and prediction accuracy of the model for various search time parameters like mean and median search times, and response times for both individual and pooled data show that subjects' search strategy may reasonably be inferred from search time distributions. The results also suggest the general applicability of the random search model for describing the search behaviour of a large number of subjects performing the type of search task used here, and the practical feasibility of its application for determination of stopping policy in optimization of inspection system design. Notwithstanding the general conformity of the data with the model, some extremely long search times were found, and this was accounted for by the characteristics of visual lobes, nonoptimum interfixation distances and inappropriate overlapping of lobes previously reported. An interpretation of temporal changes of subjects' search strategies during target detection was made by considering the cross-over phenomenon exhibited by the two cumulative detection percentage curves.