Vehicle route reconstruction from GPS data: a map-matching algorithm harnessing open source software

The availability of large sensor-generated transportation datasets has increased rapidly in many parts of the world, but it has not yet been fully leveraged by transportation modellers in the USA, Australia and elsewhere. Further, the low quantity and quality of data available for freight transportation planning model development requires modellers to extract as much information as possible from every dataset. While GPS data from vehicles has the potential to provide a wealth of data for route choice behaviours, cross-validation of traditional vehicle classification counts, and vehicle movement animations, these areas have yet to be fully explored. In the case of freight modelling, the absence of sufficient data to support modelling makes it even more pressing to extract all possible information from datasets for freight-carrying vehicles. This means moving beyond the use of truck GPS data for simple travel time and speed measurements but rather developing methods to extract highly detailed truck activity data depicting route selection, trip chaining, and stop clusters, for instance. Before these detailed analyses for passenger or freight GPS data are possible, it is necessary to first reconstruct the vehicle routes based on their GPS data. This paper presents an algorithm for route reconstruction leveraging solely open source software. The paper also presents a successful application of the algorithm developed to the case of bus GPS data for a European city, as currently no truck GPS data is freely available for research purposes. The steps necessary for applying this algorithm to proprietary vehicle GPS data are also presented. The final result of this research is the source code developed for vehicle GPS map matching, available on an online repository.

• Record URL:
  http://arrbknowledge.com
• Authors:
  • Camargo, P V
  • Hernandez, S V
• Conference:
  • ARRB Conference, 27th, 2016, Melbourne, Victoria, Australia
• Publication Date: 2016-11

Language

• English

Media Info

• Pagination: 7p
• Monograph Title: Linking people, places and opportunities: 27th ARRB Conference, 16-18 November 2016, Melbourne, Victoria

Subject/Index Terms

• TRT Terms: Computer programs; Data collection; Freight transportation; Geographic information systems; Highway traffic control; Mathematical models; Route choice; Route guidance; Sensors; Software
• ATRI Terms: Computer program; Data collection; Freight transport; Geographic information system (GIS); Modelling; Route choice; Sensor; Traffic management
• ITRD Terms: 1112: Freight transport; 8605: Geographical information system; 8735: Intelligent transport system
• Subject Areas: Freight Transportation; Operations and Traffic Management; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01622957
• Record Type: Publication
• Source Agency: ARRB
• Files: ITRD, ATRI
• Created Date: Jan 24 2017 12:03PM