Human stopping strategies in multiple-target search

All visual search tasks must stop at some point. A reasonable decision for stopping times during search tasks is critical to search task performance. This paper presented an economic model for determining an optimal stopping time. The optimal stopping time model of a one-target search was extended to that of a multiple-target search. Additionally, three optimal stopping time usage strategies: a self-stopping strategy, an externally forced stopping strategy and a hybrid-stopping strategy, were compared under several task conditions. The self-stopping strategy resulted in a better performance than either of the other two under most task conditions. The higher the degree of time pressure, and the more ambiguous the pre-information on the number of targets in a search field, the lower the relative effectiveness of the self-stopping strategy. However, even under the worst task conditions (i.e. high time pressure condition), the performance of the self-stopping strategy was not lower than the other stopping strategies. Such effectiveness of the self-stopping strategy might be caused by the human observers' ability to use an extended set of decision cues to heighten awareness of the situation.