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.

    Copyright (c) 2013-2022 Delft University of Technology, PO Box 5, 2600 AA, Delft, the Netherlands. All rights reserved.
    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 Detail

      • 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 Detail