PyANGKernel.GKExperiment¶

class GKExperiment¶

Dynamic experiment that can be either a Micro, a Meso or a Hybrid experiment.

Details

This object holds all needed parameters to run a Dynamic simulation.

A dynamic experiment can be defined either as a SRC (stochastic route choice) or a DUE (dynamic user-equilibrium). If it is defined as a SRC then it has a collection of replications ( GKReplication ) an one or more averages ( GKExperimentResult ). If it is defined as a DUE then it has a collection of experiment results ( GKExperimentResult ). In both cases this experiment belongs to a single scenario ( GKScenario ).

Synopsis¶

Methods¶

def __init__()
def addReplication()
def addRouteChoiceODParameter()
def addSimulationArea()
def appliedMFC()
def appliedTWOPAS()
def blockedODPairsMatrix()
def clearArrivalsType()
def clearMaxPathAlternativesPerVehicle()
def clearRouteChoiceODParameters()
def clearSimulationAreas()
def clearVariableReactionTimes()
def disablePathCalculation()
def getActivateExternalBehaviouralModel()
def getApplyTwoDimensionalModel()
def getApplyTwoLanesCarFollowingModel()
def getApplyTwoWayOvertakingModel()
def getArrivalType()
def getArrivalsType()
def getAttractivenessWeight()
def getBinomialModelProbability()
def getCLogitBetaFactor()
def getCLogitGammaFactor()
def getCarFollowingConsiderMinHeadway()
def getDelayOfAllowedSimultaneousOvertaking()
def getDelayThreshold()
def getEnRouteForODRoutesPercentage()
def getEnRouteForPathAssignmentResultsPercentage()
def getEnRouteForRouteChoicePathsPercentage()
def getEnRoutePathUpdate()
def getEnRoutePathUpdateVirtualQueue()
def getEngineMode()
def getFirstAndLastSegmentTravelTimeType()
def getGlobalFare()
def getHybridMicroFlags()
def getHybridMicroObjects()
def getInitialStateType()
def getIntervalDuration()
def getLinkCostsReplication()
def getLogitModelScaleFactor()
def getLookAheadDistanceVariability()
def getMacroMesoUnitsConversionFactor()
def getMaxPathAlternativesPerVehicle()
def getMaximumDistance()
def getMaximumRank()
def getMaximumRoutes()
def getMaximumSpeedDifference()
def getMaximumSpeedDifferenceOnRamp()
def getMaximumSpeedDifferenceThreshold()
def getMesoReactionTimeAtTrafficLight()
def getMinimumSpeedDifferenceThreshold()
def getNameAutomatically()
def getNbMicroSimThreads()
def getNbReplications()
def getNbResults()
def getNbThreadsSim()
def getNumberOfAllowedSimultaneousOvertaking()
def getNumberOfIntervals()
def getNumberOfVehicles()
def getODRoutesPercentage()
def getPathAssignmentResultsPercentage()
def getPathCalculationAlgorithm()
def getPathCostsType()
def getPrimaryReplication()
def getProportionalModelAlphaFactor()
def getQueueEntrySpeed()
def getQueueExitSpeed()
def getRCUserDefinedFunction()
def getReactionTime()
def getReactionTimeAtStop()
def getReactionTimeAtTrafficLight()
def getReactionTimeType()
def getReenteringSegmentTravelTimeType()
def getReplications()
def getRouteChoiceODParameters()
def getSensitivityFactorForReducedGap()
def getSimulationAreas()
def getSimulationStep()
def getSimulatorEngine()
def getSpeedAcceptanceForOvertaking()
def getSpeedDifferenceThresholdForOvertakingSpeedAcceptance()
def getStoppingCriteria()
def getTrafficSnapshot()
def getTransferPenaltyFunction()
def getTravelTimeFunctionComponent()
def getTravelTimeThreshold()
def getTwoLanesSpeedDifferenceType()
def getUserDefinedCostWeight()
def getVariableReactionTimesMeso()
def getVariableReactionTimesMicro()
def getWarmupDemand()
def getWarmupTime()
def getWarmupTimeWithScenario()
def initialSPTrees()
def intervalsRC()
def isCustomModel()
def isMacro()
def isMeso()
def isMicro()
def isPolicyActive()
def maxAssignmentResultsPaths()
def maxODRoutesPaths()
def relativeGapMatrix()
def removeReplication()
def removeSimulationArea()
def setActivateExternalBehaviouralModel()
def setAppliedMFC()
def setAppliedTWOPAS()
def setApplyTwoDimensionalModel()
def setApplyTwoLanesCarFollowingModel()
def setApplyTwoWayOvertakingModel()
def setArrivalType()
def setAttractivenessWeight()
def setBinomialModelProbability()
def setBlockedODPairsMatrix()
def setCLogitBetaFactor()
def setCLogitGammaFactor()
def setCarFollowingConsiderMinHeadway()
def setCustomModel()
def setDelayOfAllowedSimultaneousOvertaking()
def setDelayThreshold()
def setDisablePathCalculation()
def setEnRouteForODRoutesPercentage()
def setEnRouteForPathAssignmentResultsPercentage()
def setEnRouteForRouteChoicePathsPercentage()
def setEnRoutePathUpdate()
def setEnRoutePathUpdateVirtualQueue()
def setEngineMode()
def setFirstAndLastSegmentTravelTimeType()
def setGlobalFare()
def setHybridMicroFlags()
def setInitialSPTrees()
def setInitialStateType()
def setIntervalDuration()
def setIntervalsRC()
def setLinkCostsReplication()
def setLogitModelScaleFactor()
def setLookAheadDistanceVariability()
def setMacroMesoUnitsConversionFactor()
def setMaxAssignmentResultsPaths()
def setMaxODRoutesPaths()
def setMaxPathAlternativesPerVehicle()
def setMaximumDistance()
def setMaximumRank()
def setMaximumRoutes()
def setMaximumSpeedDifference()
def setMaximumSpeedDifferenceOnRamp()
def setMaximumSpeedDifferenceThreshold()
def setMesoReactionTimeAtTrafficLight()
def setMinimumSpeedDifferenceThreshold()
def setNbMicroSimThreads()
def setNbThreadsSim()
def setNumberOfAllowedSimultaneousOvertaking()
def setNumberOfIntervals()
def setNumberOfVehicles()
def setODRoutesPercentage()
def setPathAssignmentResultsPercentage()
def setPathCalculationAlgorithm()
def setPathCostsType()
def setProportionalModelAlphaFactor()
def setQueueEntrySpeed()
def setQueueExitSpeed()
def setRCUserDefinedFunction()
def setReactionTime()
def setReactionTimeAtStop()
def setReactionTimeAtTrafficLight()
def setReactionTimeType()
def setReenteringSegmentTravelTimeType()
def setRelativeGapMatrix()
def setRouteChoiceODParameters()
def setSensitivityFactorForReducedGap()
def setSimulationStep()
def setSimulatorEngine()
def setSpeedAcceptanceForOvertaking()
def setSpeedDifferenceThresholdForOvertakingSpeedAcceptance()
def setStoppingCriteria()
def setTrafficSnapshot()
def setTransferPenaltyFunction()
def setTravelTimeFunctionComponent()
def setTravelTimeThreshold()
def setTwoLanesSpeedDifferenceType()
def setUseDynamicPTAssignment()
def setUseFlatFare()
def setUseProfiledRC()
def setUseTravelTimeFromPathAssignmentPlanInHybridMacroMeso()
def setUserDefinedCostWeight()
def setVariableReactionTimesMeso()
def setVariableReactionTimesMicro()
def setWarmupDemand()
def setWarmupTime()
def useDynamicPTAssignment()
def useFlatFare()
def useProfiledRC()
def useTravelTimeFromPathAssignmentPlanInHybridMacroMeso()
def usesMaxPathAlternativesPerVehicle()
def usesSimulationArea()

Note

This documentation may contain snippets that were automatically translated from C++ to Python. We always welcome contributions to the snippet translation. If you see an issue with the translation, you can also let us know by creating a ticket on https:/bugreports.qt.io/projects/PYSIDE

class GKInitialStateType¶: The initial state generated either by a wram-up or a save traffic state ( GKDynamicTrafficSnapshot ).

class GKArrivalType¶: Types of arrivals. Refer to the Aimsun Next Micro manual section for more information on the different types. The eNone special value is returned by getArrivalType when the origin object (centroid or section) has no value.

class GKReactionTimeType¶: Type of reaction time. - eAsSimStep: reaction time is the same for all the vehicle types. It is equal to the simulation step for micro experiments. - eVariableVehType: reaction time is set for each vehicle type and according to some percentages.

class SimulatorEngine¶: Network loading type: - eMacroAssignment: BaseForest use only. Last generation information - eMicro: using the microscopic simulator. - eMeso: using the mesoscopic simulator. - eSimplifiedMeso: using the simplified mesoscopic simulator. - eHybrid: using the meso-micro hybrid simulator. - eDynamicMacro: using the macroscopic simulator. No pure MACRO (static). - eMacroMesoHybrid: using the macro-meso hybrid

class EngineMode¶: Type of the dynamic traffic assignment: - eIterative: dynamic traffic assignment based on user equilibrium (DUE). - eOneShot: dynamic traffic assignment based on stochastic route choice (SRC).

class PathCalculationAlgorithm¶: Choose Path Calculation Algorithm:

class DisablePathCalculation¶: Disable Path Calculation type: - eNo: Don’t disable the path calculation. - eForAllODPairs: Disable the path calculation for all ODPairs. - eForTheBlockedODPairsInMatrix: Disable the path calculation for all ODPairs that are blocked in the selected matrix (mBlockedODPairsMatrix).

class HybridMicroFlags¶: Flag values describing the additional objects (other than those obtained from simulation areas) to be micro-simulated in a hybrid experiment

class TravelTime¶

class DUEPathCost¶: DUE: use instantaneous, experienced or time-dependent costs

__init__()¶

addReplication(replication)¶

Parameters:: replication – GKReplication

Adds a new replication to this experiment.

addRouteChoiceODParameter(params)¶

Parameters:: params – GKExperimentODParameters

Adds an OD route choice parameter.

addSimulationArea(area)¶

Parameters:: area – GKSimulationArea

Adds a simulation area to this experiment.

appliedMFC()¶

Return type:: bool

Returns true if the MFC acceleration model is activated

See also

setAppliedMFC()

appliedTWOPAS()¶

Return type:: bool

Returns true if the TWOPAS acceleration model is activated

See also

setAppliedTWOPAS()

blockedODPairsMatrix()¶

Return type:: GKODMatrix

Returns the blocked ODPairs matrix

See also

setBlockedODPairsMatrix()

clearArrivalsType()¶

Removes all the arrivals for the origin objects (section or centroid).

clearMaxPathAlternativesPerVehicle()¶

Removes all the max path alternatives per vehicle.

clearRouteChoiceODParameters()¶

Removes all OD route choice parameters.

clearSimulationAreas()¶

Removes all simulation areas from this experiment.

clearVariableReactionTimes()¶

Discards the variable reaction times data.

disablePathCalculation()¶

Return type:: DisablePathCalculation

Returns which ODPairs won’t be considered during the path calculation

See also

setDisablePathCalculation()

getActivateExternalBehaviouralModel()¶

Return type:: bool

getApplyTwoDimensionalModel()¶

Return type:: bool

getApplyTwoLanesCarFollowingModel()¶

Return type:: bool

getApplyTwoWayOvertakingModel()¶

Return type:: bool

getArrivalType()¶

Return type:: GKArrivalType

Gets the arrival type.

getArrivalType(entry)

Parameters:: entry – GKObject
Return type:: GKArrivalType

Returns the arrival type for an origin object (section or centroid). If no arrival has been set then the eNone arrival type will be returned.

getArrivalsType()¶

Return type:: Dictionary with keys of type .GKObject and values of type GKExperiment.GKArrivalType.

Returns all the arrivals for the origin objects (section or centroid).

getAttractivenessWeight()¶

Return type:: float

getBinomialModelProbability()¶

Return type:: float

getCLogitBetaFactor()¶

Return type:: float

getCLogitGammaFactor()¶

Return type:: float

getCarFollowingConsiderMinHeadway()¶

Return type:: bool

getDelayOfAllowedSimultaneousOvertaking()¶

Return type:: float

getDelayThreshold()¶

Return type:: float

getEnRouteForODRoutesPercentage(vehicle)¶

Parameters:: vehicle – GKMobileAgent
Return type:: float

Gets the number of vehicles that are following an OD-Route and can change its paths during the simulation. This percentage is taken into account only when the experiment is “Dynamic”.

getEnRouteForPathAssignmentResultsPercentage(vehicle)¶

Parameters:: vehicle – GKMobileAgent
Return type:: float

Gets the number of vehicles that are following a path from the Path Assignment results and can change its paths during the simulation. This percentage is taken into account only when the experiment is “Dynamic”.

getEnRouteForRouteChoicePathsPercentage(vehicle)¶

Parameters:: vehicle – GKMobileAgent
Return type:: float

Gets the number of vehicles that are following route choice paths (paths calculated using the Route Choice model) and can change its paths during the simulation. This percentage is taken into account only when the experiment is “Dynamic”.

getEnRoutePathUpdate()¶

Return type:: bool

getEnRoutePathUpdateVirtualQueue()¶

Return type:: bool

getEngineMode()¶

Return type:: EngineMode

Gets the dynamic traffic assignment’s type.

getFirstAndLastSegmentTravelTimeType()¶

Return type:: TravelTime

getGlobalFare()¶

Return type:: float

getHybridMicroFlags()¶

Return type:: int

Sets the flags value describing the additional objects to be micro-simulated in a hybrid experiment.

getHybridMicroObjects()¶

Return type:: .QSetGKGeoObject

Returns the set of objects to be micro-simulated in a hybrid experiment, according to the simulation area and flags configured into the experiment.

getInitialStateType()¶

Return type:: GKInitialStateType

The initial state generated either by a wram-up or a save traffic state ( GKDynamicTrafficSnapshot ).

getIntervalDuration()¶

Return type:: int

getLinkCostsReplication()¶

Return type:: GKReplication

getLogitModelScaleFactor()¶

Return type:: float

getLookAheadDistanceVariability()¶

Return type:: int

For hybrid micro-meso experiments gets the look-ahead distance variability

getMacroMesoUnitsConversionFactor()¶

Return type:: float

getMaxPathAlternativesPerVehicle(vehicle)¶

Parameters:: vehicle – GKMobileAgent
Return type:: int

Gets the maximum number of path alternatives the route choice will calculate for the specified vehicle. If no data has been set for the vehicle, it returns GKExperiment::getMaxPathAlternativesPerVehicle

getMaximumDistance()¶

Return type:: float

getMaximumRank()¶

Return type:: int

getMaximumRoutes()¶

Return type:: int

getMaximumSpeedDifference()¶

Return type:: float

getMaximumSpeedDifferenceOnRamp()¶

Return type:: float

getMaximumSpeedDifferenceThreshold()¶

Return type:: float

getMesoReactionTimeAtTrafficLight()¶

Return type:: float

getMinimumSpeedDifferenceThreshold()¶

Return type:: float

getNameAutomatically()¶

Return type:: str

Generates the name of this object automatically based on its simulator engine and engine mode.

getNbMicroSimThreads()¶

Return type:: int

Gets the number of threads used to simulate this Micro replication. Requires an Aimsun Next Advanced License.

getNbReplications()¶

Return type:: int

Returns the number of replications on this experiment.

getNbResults()¶

Return type:: int

Returns the number of results on this experiment.

getNbThreadsSim()¶

Return type:: int

This function is Obsolete, please use: uint getNbMicroSimThreads() .

getNumberOfAllowedSimultaneousOvertaking()¶

Return type:: int

getNumberOfIntervals()¶

Return type:: int

getNumberOfVehicles()¶

Return type:: int

getODRoutesPercentage(vehicle)¶

Parameters:: vehicle – GKMobileAgent
Return type:: float

Gets the OD-Routes’s percentage. This is the percentage that will be used to assign paths to vehicle vehicle.

getPathAssignmentResultsPercentage(vehicle)¶

Parameters:: vehicle – GKMobileAgent
Return type:: float

Gets the path assignment result’s percentage. This is the percentage that will be used to assign paths to vehicle vehicle.

getPathCalculationAlgorithm()¶

Return type:: PathCalculationAlgorithm

Gets the assigned Path Calculation Algorithm.

getPathCostsType()¶

Return type:: DUEPathCost

Gets the type of cost for the paths of the DUE: to use instantaneous, experienced or time-dependent costs

getPrimaryReplication()¶

Return type:: GKReplication

Returns the primary replication of this experiment. Is the one that will be simulated when executing the experiment. The primary replication is the one with the lower id.

getProportionalModelAlphaFactor()¶

Return type:: float

getQueueEntrySpeed()¶

Return type:: float

getQueueExitSpeed()¶

Return type:: float

getRCUserDefinedFunction()¶

Return type:: GKFunctionCost

getReactionTime()¶

Return type:: float

getReactionTimeAtStop()¶

Return type:: float

getReactionTimeAtTrafficLight()¶

Return type:: float

getReactionTimeType()¶

Return type:: GKReactionTimeType

getReenteringSegmentTravelTimeType()¶

Return type:: TravelTime

getReplications()¶

Return type:: GKFolder

Returns all the replications of this experiment.

getRouteChoiceODParameters()¶

Return type:: .list of GKExperimentODParameters

Returns the route choice parameters for an Origin and Destination.

getSensitivityFactorForReducedGap()¶

Return type:: float

getSimulationAreas()¶

Return type:: .list of GKSimulationArea

Returns the simulation areas in this experiment.

getSimulationStep()¶

Return type:: float

getSimulatorEngine()¶

Return type:: SimulatorEngine

Gets the type of network loading or simulator engine.

getSpeedAcceptanceForOvertaking()¶

Return type:: float

getSpeedDifferenceThresholdForOvertakingSpeedAcceptance()¶

Return type:: float

getStoppingCriteria()¶

Return type:: GKExperimentStoppingCriteria

getTrafficSnapshot()¶

Return type:: GKDynamicTrafficSnapshot

A traffic snapshot to use as the initial point of a simulation.

getTransferPenaltyFunction()¶

Return type:: GKFunctionCost

getTravelTimeFunctionComponent()¶

Return type:: GKFunctionComponent

getTravelTimeThreshold()¶

Return type:: float

getTwoLanesSpeedDifferenceType()¶

Return type:: int

getUserDefinedCostWeight()¶

Return type:: float

getVariableReactionTimesMeso()¶

Return type:: .QMapconst GKVehicle,list of GKVehicleReactionTimes

Gets all the variable reaction times for the meso model.

getVariableReactionTimesMicro()¶

Return type:: .QMapconst GKVehicle,list of GKVehicleReactionTimes

Gets all the variable reaction times for the micro model.

getWarmupDemand()¶

Return type:: GKTrafficDemand

Get traffic demand used during the warm-up simulation.

getWarmupTime()¶

Return type:: GKTimeDuration

Gets the simulation warm-up period.

getWarmupTimeWithScenario()¶

Return type:: GKTimeDuration

Gets the simulation warm-up period considering scenario information too.

initialSPTrees()¶

Return type:: int

intervalsRC()¶

Return type:: .list of int

isCustomModel()¶

Return type:: bool

Returns true if the experiment uses customized values for the core model.

isMacro()¶

Return type:: bool

isMeso()¶

Return type:: bool

isMicro()¶

Return type:: bool

isPolicyActive(policy)¶

Parameters:: policy – GKPolicy
Return type:: bool

Returns true if the given policy is active in this experiment or is active in the scenario of this experiment (as traffic condition).

maxAssignmentResultsPaths()¶

Return type:: int

maxODRoutesPaths()¶

Return type:: int

relativeGapMatrix()¶

Return type:: GKODMatrix

removeReplication(replication)¶

Parameters:: replication – GKReplication

Removes a replication from this experiment. The replication is not deleted.

removeSimulationArea(area)¶

Parameters:: area – GKSimulationArea

Removes a simulation area from this experiment.

setActivateExternalBehaviouralModel(activate)¶

Parameters:: activate – bool

setAppliedMFC(aAppliedMFC)¶

Parameters:: aAppliedMFC – bool

Sets if the MFC acceleration model is activated

See also

appliedMFC()

setAppliedTWOPAS(aAppliedTWOPAS)¶

Parameters:: aAppliedTWOPAS – bool

Sets if the TWOPAS acceleration model is activated

See also

appliedTWOPAS()

setApplyTwoDimensionalModel(apply)¶

Parameters:: apply – bool

setApplyTwoLanesCarFollowingModel(apply)¶

Parameters:: apply – bool

setApplyTwoWayOvertakingModel(apply)¶

Parameters:: apply – bool

setArrivalType(atype)¶

Parameters:: atype – GKArrivalType

Sets the arrival type.

setArrivalType(entry, atype)

Parameters:

entry – GKObject
atype – GKArrivalType

Sets the arrival type for an origin centroid.

setAttractivenessWeight(value)¶

Parameters:: value – float

setBinomialModelProbability(value)¶

Parameters:: value – float

setBlockedODPairsMatrix(matrix)¶

Parameters:: matrix – GKODMatrix

Sets the blocked ODPairs matrix that will be used if “ eForTheBlockedODPairsInMatrix “ is selected

See also

blockedODPairsMatrix()

setCLogitBetaFactor(value)¶

Parameters:: value – float

setCLogitGammaFactor(value)¶

Parameters:: value – float

setCarFollowingConsiderMinHeadway(value)¶

Parameters:: value – bool

setCustomModel([set=true])¶

Parameters:: set – bool

Set it to true if the experiment will use customized values for the core model.

See also

isCustomModel()

setDelayOfAllowedSimultaneousOvertaking(value)¶

Parameters:: value – float

setDelayThreshold(value)¶

Parameters:: value – float

setDisablePathCalculation(value)¶

Parameters:: value – DisablePathCalculation

Set which ODPairs won’t be considered during the path calculation

See also

disablePathCalculation()

setEnRouteForODRoutesPercentage(vehicle, percentage)¶

Parameters:

vehicle – GKMobileAgent
percentage – float

Sets the number of vehicles that are following an OD-Route and can change its paths during the simulation. This percentage is taken into account only when the experiment is “Dynamic”.

setEnRouteForPathAssignmentResultsPercentage(vehicle, percentage)¶

Parameters:

vehicle – GKMobileAgent
percentage – float

Sets the number of vehicles that are following a path from the Path Assignment results and can change its paths during the simulation. This percentage is taken into account only when the experiment is “Dynamic”.

setEnRouteForRouteChoicePathsPercentage(vehicle, percentage)¶

Parameters:

vehicle – GKMobileAgent
percentage – float

Sets the number of vehicles that are following route choice paths (paths calculated using the Route Choice model) and can change its paths during the simulation. This percentage is taken into account only when the experiment is “Dynamic”.

setEnRoutePathUpdate(value)¶

Parameters:: value – bool

setEnRoutePathUpdateVirtualQueue(value)¶

Parameters:: value – bool

setEngineMode(em)¶

Parameters:: em – EngineMode

Sets the dynamic traffic assignment’s type.

setFirstAndLastSegmentTravelTimeType(type)¶

Parameters:: type – TravelTime

setGlobalFare(value)¶

Parameters:: value – float

setHybridMicroFlags(microFlags)¶

Parameters:: microFlags – int

Returns the flags value describing the additional objects to be micro-simulated in a hybrid experiment.

setInitialSPTrees(value)¶

Parameters:: value – int

setInitialStateType(atype)¶

Parameters:: atype – GKInitialStateType

The initial state generated either by a wram-up or a save traffic state ( GKDynamicTrafficSnapshot ).

setIntervalDuration(value)¶

Parameters:: value – int

setIntervalsRC(intervals)¶

Parameters:: intervals – .list of int

setLinkCostsReplication(replication)¶

Parameters:: replication – GKReplication

setLogitModelScaleFactor(value)¶

Parameters:: value – float

setLookAheadDistanceVariability(value)¶

Parameters:: value – int

For hybrid micro-meso experiments sets the look-ahead distance variability

setMacroMesoUnitsConversionFactor(factor)¶

Parameters:: factor – float

setMaxAssignmentResultsPaths(value)¶

Parameters:: value – int

setMaxODRoutesPaths(value)¶

Parameters:: value – int

setMaxPathAlternativesPerVehicle(vehicle, maxPathAlternatives)¶

Parameters:

vehicle – GKMobileAgent
maxPathAlternatives – int

Sets the maximum number of path alternatives the route choice will calculate for the specified vehicle.

setMaximumDistance(distance)¶

Parameters:: distance – float

setMaximumRank(value)¶

Parameters:: value – int

setMaximumRoutes(value)¶

Parameters:: value – int

setMaximumSpeedDifference(value)¶

Parameters:: value – float

setMaximumSpeedDifferenceOnRamp(value)¶

Parameters:: value – float

setMaximumSpeedDifferenceThreshold(value)¶

Parameters:: value – float

setMesoReactionTimeAtTrafficLight(value)¶

Parameters:: value – float

setMinimumSpeedDifferenceThreshold(value)¶

Parameters:: value – float

setNbMicroSimThreads(aThreads)¶

Parameters:: aThreads – int

Sets the number of threads used to simulate this Micro replication. Requires an Aimsun Next Advanced License.

setNbThreadsSim(aths)¶

Parameters:: aths – int

This function is Obsolete, please use: void setNbMicroSimThreads ( uint aThreads ).

setNumberOfAllowedSimultaneousOvertaking(value)¶

Parameters:: value – int

setNumberOfIntervals(value)¶

Parameters:: value – int

setNumberOfVehicles(num)¶

Parameters:: num – int

setODRoutesPercentage(vehicle, percentage)¶

Parameters:

vehicle – GKMobileAgent
percentage – float

Sets the OD-Routes’s percentage. This is the percentage that will be used to assign paths to vehicle vehicle.

setPathAssignmentResultsPercentage(vehicle, percentage)¶

Parameters:

vehicle – GKMobileAgent
percentage – float

Sets the path assignment result’s percentage. This is the percentage that will be used to assign paths to vehicle vehicle.

setPathCalculationAlgorithm(pca)¶

Parameters:: pca – PathCalculationAlgorithm

Sets the assigned Path Calculation Algorithm.

setPathCostsType(type)¶

Parameters:: type – DUEPathCost

Sets the type of cost for the paths of the DUE: to use instantaneous, experienced or time-dependent costs

setProportionalModelAlphaFactor(value)¶

Parameters:: value – float

setQueueEntrySpeed(value)¶

Parameters:: value – float

setQueueExitSpeed(value)¶

Parameters:: value – float

setRCUserDefinedFunction(function)¶

Parameters:: function – GKFunctionCost

setReactionTime(value)¶

Parameters:: value – float

setReactionTimeAtStop(value)¶

Parameters:: value – float

setReactionTimeAtTrafficLight(value)¶

Parameters:: value – float

setReactionTimeType(type)¶

Parameters:: type – GKReactionTimeType

setReenteringSegmentTravelTimeType(type)¶

Parameters:: type – TravelTime

setRelativeGapMatrix(matrix)¶

Parameters:: matrix – GKODMatrix

setRouteChoiceODParameters(params)¶

Parameters:: params – .list of GKExperimentODParameters

Sets the Origin/Destination route choice models.

setSensitivityFactorForReducedGap(value)¶

Parameters:: value – float

setSimulationStep(value)¶

Parameters:: value – float

setSimulatorEngine(se)¶

Parameters:: se – SimulatorEngine

Sets the type of network loading or simulator engine.

setSpeedAcceptanceForOvertaking(value)¶

Parameters:: value – float

setSpeedDifferenceThresholdForOvertakingSpeedAcceptance(value)¶

Parameters:: value – float

setStoppingCriteria(criteria)¶

Parameters:: criteria – GKExperimentStoppingCriteria

setTrafficSnapshot(snap)¶

Parameters:: snap – GKDynamicTrafficSnapshot

A traffic snapshot to use as the initial point of a simulation.

setTransferPenaltyFunction(function)¶

Parameters:: function – GKFunctionCost

setTravelTimeFunctionComponent(component)¶

Parameters:: component – GKFunctionComponent

setTravelTimeThreshold(value)¶

Parameters:: value – float

setTwoLanesSpeedDifferenceType(type)¶

Parameters:: type – int

setUseDynamicPTAssignment(value)¶

Parameters:: value – bool

setUseFlatFare(value)¶

Parameters:: value – bool

setUseProfiledRC(value)¶

Parameters:: value – bool

setUseTravelTimeFromPathAssignmentPlanInHybridMacroMeso(value)¶

Parameters:: value – bool

setUserDefinedCostWeight(value)¶

Parameters:: value – float

setVariableReactionTimesMeso(veh, times)¶

Parameters:

veh – GKVehicle
times – .list of GKVehicleReactionTimes

Sets the variable reaction times by vehicle type for the meso model.

setVariableReactionTimesMicro(veh, times)¶

Parameters:

veh – GKVehicle
times – .list of GKVehicleReactionTimes

Sets the variable reaction times by vehicle type for the micro model.

setWarmupDemand(ademand)¶

Parameters:: ademand – GKTrafficDemand

Set traffic demand used during the warm-up simulation.

setWarmupTime(aTime)¶

Parameters:: aTime – GKTimeDuration

Sets the simulation warm-up period.

useDynamicPTAssignment()¶

Return type:: bool

useFlatFare()¶

Return type:: bool

useProfiledRC()¶

Return type:: bool

useTravelTimeFromPathAssignmentPlanInHybridMacroMeso()¶

Return type:: bool

usesMaxPathAlternativesPerVehicle()¶

Return type:: bool

Returns true if there are max path alternatives by vehicle (if not use GKExperiment::maxRoutesAtt that is what getMaxPathAlternativesPerVehicle uses when asked by an undefined vehicle).

usesSimulationArea(area)¶

Parameters:: area – GKSimulationArea
Return type:: bool

Returns true is the simulation area is used in the experiment.