A microscopic driver attention allocation model

Misallocating attention has been considered the most likely cause of crashes. The acquisition of incomplete or unusable information leads to insufficient comprehension of the current driving environment. Thus, a functional mechanism for attention allocation is a critical issue in crash prevention. Researchers have conducted several field studies to analyze attention allocation from an aggregate perspective. However, in this way, only a few characteristics of attention allocation can be extracted. This study proposes a driver attention allocation model from a microscopic perspective to explore and clarify how drivers allocate attentions. This study treats the continuous process of attention allocation as successive choices of their focal points and derives the probability of choosing specific focal point using a discrete choice model. A set of hypothetical data was generated for numerical analysis to illustrate the appropriateness of the proposed attention allocation model. Although this study only adopts hypothetical data and simple scenarios, the results show that the proposed model can reveal the mechanisms of eyesight shifting for information gathering, and have the potential to be an effective tool for safety evaluation.