Modeling route complexity ratings Conference Paper uri icon

abstract

  • We develop a predictive model of the perceived complexity of routes in road maps, taking into account the properties of the road, the task and the map display. Sixty subjects ranked the complexity of 120 routes on scales between 0 and 10. Half of them described the route verbally before rating it. Subjects also completed a questionnaire about the influence of different variables on the route complexity. A linear regression model explained much of the dependent variable’s variance (R^2 = 0.63). The number of turns and rotations, the perceived density of the map and route length were significant predictors. Describing the route before rating it may lower its apparent complexity. Subjects’ assessments of the contribution of different variables to perceptions of route complexity differed from the actual contribution of the variables in the models. The model of perceived route complexity can be used to design road maps that minimize the user’s cognitive load.

publication date

  • January 1, 2014