Detection of the Curves based on Lateral Acceleration using Hidden Markov Models
Paper in proceeding, 2013
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.
1977
curve detection
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL
Engineering
MPSTER AP
1973
P1
Hidden Markov models (HMMs)
V39
Mechanical
event classification
RNEY GD
V61
Markov chain
ALGORITHM
RECOGNITION
PROCEEDINGS OF THE IEEE
P268
lateral acceleration
Author
Roza Maghsood
University of Gothenburg
Chalmers, Mathematical Sciences, Mathematical Statistics
Pär Johannesson
Chalmers, Mathematical Sciences, Mathematical Statistics
University of Gothenburg
Procedia Engineering
18777058 (ISSN)
Vol. 66 425-434Subject Categories (SSIF 2011)
Mathematics
DOI
10.1016/j.proeng.2013.12.096