Automatic information processing (AVIP) in traffic refers to a driver state, in which expectations have replaced a large part of the active information intake exerted by a highly attentive driver. Instead of actively scanning the visual environment, the driver only passively monitors the outside world, requiring little attention. This state has drawbacks in the sense that it is only adequate if the drivers¦ expectations are correct. In case something happens that does not correspond to the expectations, the driver could either miss crucial information or there may be a delay in response time due to the process of re-allocating attention resources. This report gives an overview of theoretical approaches that are valuable for the explanation of this phenomenon, discussing automatic performance, expectation approaches, signal detection theory, visual search approaches and vigilance research. Various methods for measuring attention, expectations or visual information processing are discussed, all with their advantages and their limitations. The advantage of combining these measures is that they can complement one another. Physiological measures, space capacity measures, eye movement measures, verbal reports and the recording of driving behaviour are discussed. Although a lot of research touches the subject, many interesting research questions remain unanswered, leaving open a large area for research. The report ends with a description of experiments that may fill in gaps in knowledge, focusing on the effect of expectations or automaticity on visual information processing in driving. (Author/publisher)
Abstract