Class WienerProcess
java.lang.Object
nl.tudelft.simulation.jstats.distributions.Dist
nl.tudelft.simulation.jstats.distributions.DistContinuous
nl.tudelft.simulation.jstats.distributions.DistNormal
org.opentrafficsim.road.gtu.lane.perception.categories.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) 2013-2020 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
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Field Summary
Fields inherited from class nl.tudelft.simulation.jstats.distributions.DistNormal
CUMULATIVE_NORMAL_PROBABILITIES, haveNextNextGaussian, mu, sigma -
Constructor Summary
Constructors Constructor Description WienerProcess(StreamInterface stream, double mu, double sigma, Duration tau, OTSSimulatorInterface simulator) -
Method Summary
Modifier and Type Method Description doubledraw()Methods inherited from class nl.tudelft.simulation.jstats.distributions.DistNormal
getCumulativeProbability, getInverseCumulativeProbability, getMu, getSigma, nextGaussian, probDensity, toString
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Constructor Details
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WienerProcess
public WienerProcess(StreamInterface stream, double mu, double sigma, Duration tau, OTSSimulatorInterface simulator)- Parameters:
stream- StreamInterface; random number streammu- double; meansigma- double; standard deviationtau- Duration; correlation timesimulator- OTSSimulatorInterface; simulator
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Method Details
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draw
public double draw()- Overrides:
drawin classDistNormal
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