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G. Navratil, I. Giannopoulos, G. Kotzbek:
"Classification of Urban and Rural Routes based on Motorcycle Riding Behaviour";
Talk: 22nd AGILE Conference on Geographic Information Science, Limassol; 2019-06-17 - 2019-06-20; in: "Geospatial Technologies for Local and Regional Development", P. Kyriakidis et al. (ed.); Springer, (2019), ISBN: 978-3-030-14744-0; 95 - 108.

A basic problem in navigation is the selection of a suitable route. This requires a determination of costs or suitability. There are approaches for many standard situations, e.g., the shortest route for pedestrians, the fastest route for cars, a physically possible and legal route for trucks, or the safest route for bicycle riders. However, not much research has been done yet for motorcycle riders. Published approaches rely on interpretation of geometry, interviews, or user feedback. None of these approaches is precise and scalable. Since modern motorcycles have an increasing number of internal sensors (e.g., lean angle sensors for curve ABS), they could provide the data required for a classification of route segments. The combination with a navigational device allows to georeferenced the data and thus attach riding characteristics to a specific road segment. This work sketches the classification concept and presents data from a real-driving experiment using an external IMU.

A basic problem in navigation is the selection of a suitable route. This requires a determination of costs or suitability. There are approaches for many standard situations, e.g., the shortest route for pedestrians, the fastest route for cars, a physically possible and legal route for trucks, or the safest route for bicycle riders. However, not much research has been done yet for motorcycle riders. Published approaches rely on interpretation of geometry, interviews, or user feedback. None of these approaches is precise and scalable. Since modern motorcycles have an increasing number of internal sensors (e.g., lean angle sensors for curve ABS), they could provide the data required for a classification of route segments. The combination with a navigational device allows to georeferenced the data and thus attach riding characteristics to a specific road segment. This work sketches the classification concept and presents data from a real-driving experiment using an external IMU.

Routing, Inertial Measurement Unit, Motorcycle, Classification, Navigation