Digital Signal Processing Reference
In-Depth Information
5.2
Linear Prediction Model for Driver Behavior
With a goal of extracting individuality from these three measurements
and the physical realities of moving vehicles a method based on Linear
Prediction (LPC) Theory is proposed. LPC is now a ubiquitous method not
only for speech but also other signal processing realms including image
processing, geophysics and earthquake
studies due to is effectiveness,
tractability and computational ease.
At a given discrete time
t,
let us assume that the relation between the
acceleration signal
and the acceleration pedal pressure
and the brake
pedal pressure
is given by:
where is an uncorrelated random variable with zero mean and
variance In linear prediction (LPC) theory, the present acceleration value
is estimated in terms of its previous values, the associated excitation signals,
and the parameter set
where the first group of parameter set forms the weights for the acceleration
history, the second and third sets and are the coefficients for the
pressure sensor history for the accelerator and the break pedal, respectively.
As expected, would be the excitation at the time instant
t.
We have thus
reformulated the vehicle acceleration behavior as an extended multi-sensory
linear prediction problem.
In our case, the optimum parameter set is found by the usual
minimization of the total prediction error
E
:
