Detection of steering events using hidden Markov models with multivariate observations
Artikel i vetenskaplig tidskrift, 2016

In this article we propose a method to identify steering events, such as curves and manoeuvres for vehicles. We use a hidden Markov model with multidimensional observations, to estimate the number of events. Three signals, lateral acceleration, steering angle speed and vehicle speed, are used as observations. We demonstrate that hidden Markov models with a combination of continuous and discrete distributions for observations can be used to detect steering events. Further, the expected number of events is estimated using the transition matrix of hidden states. The results from both measured and simulated data show that the method works well and accurately estimates the number of steering events.

steering events

Discrete distribution


Laplace distribution

hidden Markov models

EM algorithm


Roza Maghsood

Chalmers, Matematiska vetenskaper, Matematisk statistik

P. Johannesson

SP Sveriges Tekniska Forskningsinstitut AB

Jonas Wallin

Lunds universitet

International Journal of Vehicle Systems Modelling and Testing

1745-6436 (ISSN) 1745-6444 (eISSN)

Vol. 11 4 313-329



Sannolikhetsteori och statistik




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