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Map-matching på iPhone mot ett digitaliseratgångvägnät i stadsmiljö
KTH, School of Computer Science and Communication (CSC).
2013 (Swedish)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Map-matching on a digitized pedestrianroad-network of an urban environment using aniPhone (English)
Abstract [sv]

I rapporten utreds villkoren för personlig navigering på en aktuell mobilplattform (iPhone 4). I kapital 3 redogörs för geometriska, topologiska och probabilistiska metoder för map-matching. I kapital 4 diskuteras kvalitetsmått för map-matchingalgoritmer. Implementerade algoritmer beskrivs ingående i kapitel 6 och en kombinerad GPS/DR-metod presenteras. Att positionera en gående person i ett digitalt gångvägnät i stadsmiljö givet enbart en smarttelefon med icke-differentierad GPS och ett antal lågkostnads MEMS- sensorer är väsentligt svårare än att positionera en bil som kör på en väg. En algoritm såsom den som presenteras i rapporten kan ofta avgöra vilken gata användaren befinner sig på, däremot är det i praktiken svårt att bedöma vilken sida av vägen användaren befinner sig på. Bristen i positioneringsprecision är i huvudsak GPSbunden, exempelvis är precisionen på GPS-mottagaren generellt sett för låg för att kunna avgöra användarens startposition inom 10 sekunder.

Abstract [en]

This report investigates conditions for personal navigation on a contemporary mobile platform (iPhone 4). Chapter 3 describes geometrical, topological and probabilistic methods for map-matching. In Chapter 4, quality metrics used for evaluating map-matching lgorithms are discussed. Implemented algorithms are thoroughly described in Chapter 6 and a combined GPS/DR method is presented. Determining the position of a pedestrian in a digital road network of an urban environment using only a smartphone with a non-differentiated GPS and a number of low-cost MEMS sensors is considerably more difficult than determining the position of a car driving down a road. An algorithm such as the one presented in this report can often determine which street the user is on. However, determining which sidewalk a user is on proves very difficult. Lack of positioning precision is mainly GPS-bound. For instance, precision is too low to determine the users starting position within 10 seconds.

Place, publisher, year, edition, pages
2013.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-142373OAI: oai:DiVA.org:kth-142373DiVA: diva2:700008
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2014-03-12 Created: 2014-03-03 Last updated: 2014-03-12Bibliographically approved

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