Class WienerProcess
- java.lang.Object
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- nl.tudelft.simulation.jstats.distributions.Dist
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- nl.tudelft.simulation.jstats.distributions.DistContinuous
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- nl.tudelft.simulation.jstats.distributions.DistNormal
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- org.opentrafficsim.road.gtu.lane.perception.categories.WienerProcess
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- All Implemented Interfaces:
Serializable
public class WienerProcess extends DistNormal
A numerical update scheme that represents a Wiener process ifdt << 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 correlationtau
, such that the process has a tendency to stay close to the previous value. The correlation timetau
is a measure for this tendency. Given sufficient time (anddt << 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
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Field Summary
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Fields inherited from class nl.tudelft.simulation.jstats.distributions.DistNormal
haveNextNextGaussian, mu, sigma
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Constructor Summary
Constructors Constructor Description WienerProcess(StreamInterface stream, double mu, double sigma, Duration tau, OTSSimulatorInterface simulator)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
draw()
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Methods inherited from class nl.tudelft.simulation.jstats.distributions.DistNormal
getCumulativeProbability, getInverseCumulativeProbability, getMu, getProbabilityDensity, getSigma, nextGaussian, setStream, toString
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Constructor Detail
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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 Detail
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draw
public double draw()
- Overrides:
draw
in classDistNormal
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