Deriving Incline for Street Networks from Voluntarily Collected GPS Traces
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Methods of Geoinformation Science Institute of Geodesy and Geoinformation Science Faculty VI Planning Building Environment MASTER’S THESIS Deriving incline for street networks from voluntarily collected GPS traces Submitted by: Steffen John Matriculation number: 343372 Email: [email protected] Supervisors: Prof. Dr.-Ing. Marc-O. Löwner (TU Berlin) Dr.-Ing. Stefan Hahmann (Universität Heidelberg) Submission date: 24.07.2015 in cooperation with: GIScience Group Institute of Geography Faculty of Chemistry and Earth Sciences Declaration of Authorship I, Steffen John, declare that this thesis titled, 'Deriving incline for street networks from voluntarily collected GPS traces’ and the work presented in it are my own. I confirm that: This work was done wholly or mainly while in candidature for a research degree at this Uni- versity. Where any part of this thesis has previously been submitted for a degree or any other qualifi- cation at this University or any other institution, this has been clearly stated. Where I have consulted the published work of others, this is always clearly attributed. Where I have quoted from the work of others, the source is always given. With the exception of such quotations, this thesis is entirely my own work. I have acknowledged all main sources of help. Where the thesis is based on work done by myself jointly with others, I have made clear exact- ly what was done by others and what I have contributed myself. Signed: Date: ii Abstract The knowledge of incline is useful for many use-cases in navigation for electricity-powered vehicles, cyclists or mobility-restricted people (e.g. wheelchair users). Digital elevation models (DEMs) such as from laser scanning obtained DEMs or SRTM are either too expensive, not globally available or not accurate enough. Therefore, voluntarily collected GPS traces collect by users of the OpenStreetMap project have been used to derive the incline of a street network. Due to a high relative accuracy of the GPS traces, the incline was computed in a, for many use-cases, reasonable accuracy. The comparison with the SRTM DEM has shown that the inclines calculated with GPS perform slightly better with a standard deviation of σGPS = 1.6 % (σSRTM = 3.1 %), considering street with at least 5 GPS traces. Contrary to SRTM with a full coverage, the incline could only be derived for 18 % of the street network (> 5 traces). Kurzfassung (Abstract in German Language) Steigungsinformationen haben einen Mehrwert für viele Routing Anwendungen, zum Beispiel für das Routing von elektronisch betriebenen Fahrzeugen, Radfahrenden oder Menschen mit Mobilitätsein- schränkungen (z.B. Rollstuhlfahrende). Digitale Geländemodelle (DGM), wie durch Laserscanning erstellte DGMs oder SRTM-1 DGM, sind entweder zu teuer, nicht flächendeckend vorhanden oder unzureichend in der Auflösung und der Genauigkeit. Daher sollen nutzergenerierte GPS Trajektorien genutzt werden um die Steigung von Straßen zu berechnen. Aufgrund der festgestellten hohen relativen Genauigkeit der Trajektorien war es möglich die Steigung in einer für viele Anwendungen ausreichenden Genauigkeit zu berechnen. Der Vergleich mit dem SRTM DGM hat ergeben, dass die Steigungen aus GPS Daten mit einer Standardabweichung von σGPS = 1,6 % besser sind (σSRTM = 3,1 %). Für die Ermittlung der Standardabweichung wurden ausschließlich Straßen mit mindestens 5 GPS Trajektorien verwendet. Im Gegensatz zu SRTM konnten die Steigungen nicht für alle, sondern nur für 18 % der Straßen bestimmt werden (mit mehr als 5 Trajektorien). iii Table of Content 1 Introduction ................................................................................................... 1 1.1 Motivation .............................................................................................................................. 1 1.2 Objectives .............................................................................................................................. 3 1.3 Outline ................................................................................................................................... 4 2 Background .................................................................................................... 5 2.1 Global Navigation Satellite Systems ..................................................................................... 5 2.1.1 GPS Setup and Determination of Location ................................................................ 5 2.1.2 Error Sources .............................................................................................................. 7 2.1.3 GLONASS, Galileo and Beidou ................................................................................. 9 2.2 Volunteered Geographic Information .................................................................................. 10 2.2.1 Terminology and Nature of VGI .............................................................................. 10 2.2.2 Classification and Examples ..................................................................................... 12 2.3 OpenStreetMap .................................................................................................................... 13 2.3.1 Introduction to Project .............................................................................................. 13 2.3.2 Data Model ............................................................................................................... 15 2.3.3 Incline Information in OpenStreetMap ..................................................................... 16 2.4 Data Mining ......................................................................................................................... 17 3 Related Work ............................................................................................... 19 3.1 3D Routing ........................................................................................................................... 19 3.1.1 Wheelchair routing ................................................................................................... 19 3.1.2 Energy-efficient routing ........................................................................................... 20 3.2 Extraction of Street Attributes from user-generated Movement Trajectories ...................... 21 3.3 Derivation of 3D information, using high-accurate GPS measurements ............................. 22 3.4 Map Matching ...................................................................................................................... 23 3.4.1 Categorization of Map Matching Algorithms ........................................................... 24 3.4.2 Functionality of Selected Algorithms ....................................................................... 24 3.5 Smoothing of Time Series Measurements ........................................................................... 26 4 Methodology ................................................................................................ 28 4.1 Definition of Pilot Region .................................................................................................... 28 4.2 Tools .................................................................................................................................... 29 4.3 Data ...................................................................................................................................... 29 4.3.1 Crowdsourced GPS traces ........................................................................................ 29 4.3.1.1 Platforms and Devices ................................................................................ 30 4.3.1.2 The GPX Format ........................................................................................ 31 iv 4.3.1.3 OpenStreetMap GPS traces ........................................................................ 32 4.3.1.4 Typical Errors ............................................................................................. 34 4.3.2 Street Network .......................................................................................................... 35 4.3.3 Land Use Information ............................................................................................... 36 4.3.4 Digital Elevation Models .......................................................................................... 37 4.4 Workflow and Implementation ............................................................................................ 39 4.4.1 Data Import ............................................................................................................... 40 4.4.1.1 GPS traces .................................................................................................. 40 4.4.1.2 OSM Street Network and Land Use Information ....................................... 43 4.4.2 Preprocessing ............................................................................................................ 43 4.4.2.1 GPS data ..................................................................................................... 43 4.4.2.2 Street Network ........................................................................................... 46 4.4.3 Map Matching........................................................................................................... 47 4.4.4 Calculation of Incline ............................................................................................... 52 4.5 Validation