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Map Matching to road segments using Hidden Markov Model with GNSS, Odometer and Gyroscope
Linköpings universitet, Institutionen för datavetenskap, Programvara och system.
2019 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

In this thesis the Hidden Markov Model (HMM) is used in the process of map matching to investigate the accuracy for road segment map matching. A few HMM algorithms using a Global Navigation Satellite System (GNSS) receiver, odometer and gyroscope sensors are presented. The HMM algorithms are evaluated on four accuracy metrics. Two of these metrics have been seen in previous literature and captures road map match accuracy. The other have not been seen before and captures road segment accuracy. In the evaluation process a dataset is created by simulation to achieve positional ground truth for each sensor measurement. The accuracy distribution for different parts of the map matched trajectory is also evaluated. The result shows that HMM algorithms presented in previous literature, falls short to capture the accuracy for road segment map matching. The results further shows that by using less noisy sensors, as odometer and gyroscope, the accuracy for road segment map matching can be increased.

sted, utgiver, år, opplag, sider
2019. , s. 69
Emneord [en]
map matching, hmm, hidden markov model, gnss
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-162706ISRN: LIU-IDA/LITH-EX-A--2019/024--SEOAI: oai:DiVA.org:liu-162706DiVA, id: diva2:1379326
Fag / kurs
Computer Engineering
Veileder
Examiner
Tilgjengelig fra: 2020-01-08 Laget: 2019-12-16 Sist oppdatert: 2020-01-08bibliografisk kontrollert

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