Journal cover Journal topic
Proceedings of the ICA
Journal topic
Volume 2
Proc. Int. Cartogr. Assoc., 2, 34, 2019
https://doi.org/10.5194/ica-proc-2-34-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Proc. Int. Cartogr. Assoc., 2, 34, 2019
https://doi.org/10.5194/ica-proc-2-34-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Jul 2019

10 Jul 2019

A framework for automatically visualizing and recommending efficient routes

Stefan Fuest and Monika Sester Stefan Fuest and Monika Sester
  • Institute of Cartography and Geoinformatics, Leibniz University Hannover, Germany

Keywords: route visualization, cartographic generalization, route choice behavior, cognitive map, traffic management

Abstract. Due to an increasing traffic density in urban environments, the traffic management as well as the society needs to face various problems including congestion, air pollution or a higher probability of accidents. Therefore, it is getting more important to make road users aware of efficient route alternatives to obtain a better distribution of the traffic flow. Since the time for making route decisions is usually limited, the visualization of the information, which should be conveyed, needs to be prepared in a very clear and easily understandable format. In this approach, we propose a framework for automatically visualizing route efficiency based on various environmentally relevant scenarios. Our methods used to create the map visualizations are based on human perception of space, in order to communicate routes and traffic-related situations more intuitively. That is, humans are assumed to mentally abstract the geographic space using various types of distortions rather than perceiving the environment in its actual shape. Based on these concepts, we argue that a perception-based representation of the route, as well as the visual communication of temporary disturbances may not only simplify the navigation process, but also supports an awareness for the current traffic dynamics, which thus may influence route choice behavior towards a more altruistic behavior. In this paper, we further present two algorithmic approaches for automatically abstracting the geometry of a route in more detail, using cartographic generalization techniques - to present the road network in a way, how it might be perceived based on a certain traffic situation.

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