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Detection of the Curves based on Lateral Acceleration using Hidden Markov Models

Roza Maghsood (Institutionen för matematiska vetenskaper, matematisk statistik) ; Pär Johannesson (Institutionen för matematiska vetenskaper, matematisk statistik)
Fatigue Design 2013, International Conference Proceedings (1877-7058). Vol. 66 (2013), p. 425-434.
[Konferensbidrag, refereegranskat]

In vehicle design it is desirable to model the loads by describing the load environment, the customer usage and the vehicle dynamics. In this study a method will be proposed for detection of curves using a lateral acceleration signal. The method is based on hidden Markov models (HMMs) which are probabilistic models that can be used to recognize patterns in time series data. In an HMM, 'hidden' refers to a Markov chain where the states are not observable, however what can be observed is a sequence of data where each observation is a random variable whose distribution depends on the current hidden state. The idea here is to consider the current driving event as the hidden state and the lateral acceleration signal as the observed sequence. Examples of curve detection are presented for both simulated and measured data. The classification results indicate that the method can recognize left and right turns with small misclassification errors.

Nyckelord: Hidden Markov models (HMMs), Markov chain, curve detection, event classification, lateral acceleration, ALGORITHM, RECOGNITION, Engineering, Mechanical, RNEY GD, 1973, PROCEEDINGS OF THE IEEE, V61, P268, MPSTER AP, 1977, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, V39, P1

Denna post skapades 2014-08-01. Senast ändrad 2016-11-07.
CPL Pubid: 200836


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)



Chalmers infrastruktur