Class WienerProcess

All Implemented Interfaces:
Serializable

public class WienerProcess
extends DistNormal
A numerical update scheme that represents a Wiener process if dt << tau. A Wiener process is a process that results in random values that follow a Normal distribution with parameters mu and sigma. However, there is a time progression with correlation tau, such that the process has a tendency to stay close to the previous value. The correlation time tau is a measure for this tendency. Given sufficient time (and dt << tau) the overall probability remains equal to the Normal distribution.

The Wiener process is typically used for measurement or perception errors in cases where the error of two consecutive time steps is unlikely to deviate much.

Treiber, M., A. Kesting, D. Helbing (2006) "Delays, Inaccuracies and Anticipation in Microscopic Traffic Models", Physica A – Statistical Mechanics and its Applications, Vol. 360, Issue 1, pp. 71-88.

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BSD-style license. See OpenTrafficSim License.

Version:
$Revision$, $LastChangedDate$, by $Author$, initial version 18 okt. 2018
Author:
Alexander Verbraeck, Peter Knoppers, Wouter Schakel
See Also:
Serialized Form
  • Constructor Details

    • WienerProcess

      public WienerProcess​(StreamInterface stream, double mu, double sigma, Duration tau, OTSSimulatorInterface simulator)
      Parameters:
      stream - StreamInterface; random number stream
      mu - double; mean
      sigma - double; standard deviation
      tau - Duration; correlation time
      simulator - OTSSimulatorInterface; simulator
  • Method Details