Abstract
Information is effectively the same as a change in uncertainty, and therefore, they share the same unit system of measurement, such as bit, nat, and qubit. This paper adopts a strict definition of information and implements a method to quantify traveler information provision using an information-based modeling framework developed in earlier research. The framework combines a cognitive grouping model and information update scheme (learning) for calculating in quantified units the amount of information any traveler has about a route, which can be further decomposed to any sub-route during any time period of relevance. Such numerical quantification can be meaningful in evaluating network performance enhancement schemes such as ATIS and in modeling decision making when uncertainty is a significant factor. An application study with traffic network and detector data near downtown Los Angeles is used to demonstrated the use of the method for quantifying information provision from a dynamic message board, as an illustrative case. Further improvement and research directions are identified.