TY - GEN
T1 - Modeling route complexity ratings
AU - Schwartz-Chassidim, H.
AU - Meyer, J.
AU - Parmet, Y.
N1 - Publisher Copyright:
Copyright 2014 Human Factors and Ergonomics Society.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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 (R2 = 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.
AB - 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 (R2 = 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.
KW - Digital road map
KW - Model development
KW - Pereived complexity
KW - Route
KW - Scale
UR - https://www.scopus.com/pages/publications/84957656545
U2 - 10.1177/1541931214581354
DO - 10.1177/1541931214581354
M3 - Conference contribution
AN - SCOPUS:84957656545
T3 - Proceedings of the Human Factors and Ergonomics Society
SP - 1696
EP - 1700
BT - 2014 International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014
PB - Human Factors an Ergonomics Society Inc.
T2 - 58th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014
Y2 - 27 October 2014 through 31 October 2014
ER -