Movement Pattern Recognition Assisted Map Matching for Pedestrian/Wheelchair Navigation
- 15 June 2012
- journal article
- Published by Cambridge University Press (CUP) in Journal of Navigation
- Vol. 65 (4), 617-633
- https://doi.org/10.1017/s0373463312000252
Abstract
Today's mobile technology features several sensors that when integrated can provide ubiquitous navigation assistance to pedestrians including wheelchair users. Common sensors found in most smartphones are Global Positioning System (GPS), accelerometer, and compass. In this paper, a user's movement pattern recognition algorithm to improve map matching efficiency and accuracy in pedestrian/wheelchair navigation systems/services is discussed. The algorithm integrates GPS positions, orientation data from compass, and movement states recognized from accelerometer data in a client/server architecture. The algorithm is tested in an Android mobile phone, and the results show that the proposed map matching algorithm is efficient and provides good accuracy. © 2012 The Royal Institute of NavigationKeywords
This publication has 11 references indexed in Scilit:
- Universal Navigation on SmartphonesPublished by Springer Nature ,2011
- A Hidden Markov Model-Based Map-Matching Algorithm for Wheelchair NavigationJournal of Navigation, 2009
- A Chain‐Code‐Based Map Matching Algorithm for Wheelchair NavigationTransactions in GIS, 2009
- Accuracy and time to first fix using consumer-grade GPS receiversPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- Current map-matching algorithms for transport applications: State-of-the art and future research directionsTransportation Research Part C: Emerging Technologies, 2007
- A Methodology for Predicting Performances of Map-Matching AlgorithmsLecture Notes in Computer Science, 2006
- Classification of basic daily movements using a triaxial accelerometerMedical & Biological Engineering & Computing, 2004
- A Map Matching Method for GPS Based Real-Time Vehicle LocationJournal of Navigation, 2004
- A general map matching algorithm for transport telematics applicationsGPS Solutions, 2003
- Detection of posture and motion by accelerometry: a validation study in ambulatory monitoringComputers in Human Behavior, 1999