Visualisation of uncertainty in probabilistic traffic models for policy and operations |
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Authors: | S C Calvert J Rypkema B Holleman D Azulay A de Jong |
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Institution: | 1.TNO,Netherlands Organisation for Applied Scientific Research, Research Group Smart Mobility,Delft,The Netherlands;2.Department of Transport & Planning,Delft University of Technology,Delft,The Netherlands;3.TNO,Research Group Human Behaviour and Organisational Innovations,Soesterberg,The Netherlands;4.TNO,Research Group Perceptual and Cognitive Systems,Soesterberg,The Netherlands;5.TNO,Research Group Business Information Systems,Groningen,The Netherlands |
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Abstract: | This study investigates different methods to visualise uncertainty in static representations of probabilistic traffic models predictions on road-networks. Although various graphical cues may be used to represent uncertainty it is not a priori clear which of them are most suited for this purpose, since their legibility, intelligibility and the degree to which they interfere with other graphical elements in a representation differ widely. Several graphical uncertainty representations were therefore developed and analysed in expert sessions. A selection of the initial set of uncertainty visualisations was further evaluated in a cognitive alternative task-switching experiment. The results show that graphical representations are able to convey uncertainty information relatively accurately, while some uncertainty visualisations outperform others. It depends on the model and scenario which representation is most suited for a given application. This paper presents an overview of possible graphic uncertainty representations and the considerations involved when applying them to uncertainty in traffic model visualisations. |
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