A stochastic sequential model for man-machine tracking systems

A sequential model developed by the authors (1985), which provides probabilistic descriptions of perception and control effects during manual control tracking, is further developed, analyzed, and applied. The sequential model is extended to represent anticipation and delay in tracking. The strategy parameters are shown to have independent effects and to be uniquely defined. The sequential model is shown to provide at least a partial separation of perception and control effects. Evidence of a duality between the perception variables and the control velocity is given. The sequential model parameters are identified in an experimental application and related to the tracking attributes of accuracy, consistency, and degree of anticipation or delay