Travel-Mode Classification for Optimizing Vehicular Travel Route Planning

  • Lijuan ZhangEmail author
  • Sagi Dalyot
  • Monika Sester
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Navigating and travelling between destinations with the help of Geographic Information Systems route planning is a very common task carried out by millions of commuters daily. The route is mostly based on geocoding of the addresses given by the traveller based on static road network into digital-map positions, and thus the creation of path and directions needed to be taken. Today’s navigation data sets rarely contain information about parking lots, related to building entrances, and walking paths. This is especially relevant for large building complexes (hospitals, industrial buildings, city halls, universities). A fine-tuned route tailored for the driver requirement, e.g., park the car close-by to destination, is required in such cases to save time and frustration. The idea of this chapter is to extract this information from the navigational behaviour of users, which is accessible via an analysis of GPS traces; analysis of car commuters in relation to their point of departure and destination by analysing the walking path they took from—and to—their parked car in relation to a specific address. A classification scheme of GPS-traces is suggested, which enables to classify robustly different travel modes that compose a single GPS trace. By ascribing the classified vehicular car trace, which is accompanied by a walking path to/from the car, to a specific address, it is made feasible to extract the required ascribed data: parking places corresponding to that address. This additional data can later be added to the road network navigation maps used by the route planning scheme to enable the construction of a more fine-tuned optimal and reliable route that will prevent subsequent detours.


Data mining Classification GPS Route planner Optimization 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institut für Kartographie und Geoinformatik (IKG)Leibniz Universität HannoverHannoverGermany

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