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

Författare

Roza Maghsood

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

Pär Johannesson

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Procedia Engineering

18777058 (ISSN)

Vol. 66 425-434

Ämneskategorier

Matematik

DOI

10.1016/j.proeng.2013.12.096