org.opentrafficsim.draw.egtf.Egtf

Direct Known Subclasses:: TypedEgtf

public class Egtf extends Object

Extended Generalized Treiber-Helbing Filter (van Lint and Hoogendoorn, 2009). This is an extension of the Adaptive Smoothing Method (Treiber and Helbing, 2002). A fast filter for equidistant grids (Schreiter et al., 2010) is available. This fast implementation also supports multiple data sources.

To allow flexible usage the EGTF works with DataSource, DataStream and Quantity.

A DataSource, such as "loop detectors", "floating-car data" or "camera" is mostly an identifier, but can be requested to provide several data streams.

A DataStream is one DataSource supplying one Quantity. For instance "loop detectors" supplying "flow". In a DataStream, supplied by the DataSource, standard deviation of measurements in congestion and free flow are defined. These determine the reliability of the Quantity data from the given DataSource, and thus ultimately the weight of the data in the estimation of the quantity.

A Quantity, such as "flow" or "density" defines what is measured and what is requested as output. The output can be in typed format using a Converter. Default quantities are available under SPEED_SI, FLOW_SI and DENSITY_SI, all under Quantity.

Data can be added using several methods for point data, vector data (multiple independent location-time combinations) and grid data (data in a grid pattern). Data is added for a particular DataStream.

For simple use-cases where a single data source is used, data can be added directly with a Quantity, in which case a default DataSource, and default DataStream for each Quantity is internally used. All data should either be added using Quantity's, or it should all be added using DataSource's. Otherwise relative data reliability is undefined.

Output can be requested from the EGTF using a Kernel, a spatiotemporal pattern determining measurement weights. The Kernel defines an optional maximum spatial and temporal range for measurements to consider, and uses a Shape to determine the weight for a given distance and time from the estimated point. By default this is an exponential function. A Gaussian kernel is also available, while any other shape could be also be implemented.

Parameters from the EGTF are found in the following places:

EGTF: cCong, cFree, deltaV and vc, defining the overall traffic flow properties.
Kernel: tMax and xMax, defining the maximum range to consider.
KernelShape: sigma and tau, determining the decay of weights for further measurements in space and time. (Specifically GaussKernelShape)
DataStream: thetaCong and thetaFree, defining the reliability by the standard deviation of measured data in free flow and congestion from a particular data stream.

References:

van Lint, J. W. C. and Hoogendoorn, S. P. (2009). A robust and efficient method for fusing heterogeneous data from traffic sensors on freeways. Computer Aided Civil and Infrastructure Engineering, accepted for publication.
Schreiter, T., van Lint, J. W. C., Treiber, M. and Hoogendoorn, S. P. (2010). Two fast implementations of the Adaptive Smoothing Method used in highway traffic state estimation. 13th International IEEE Conference on Intelligent Transportation Systems, 19-22 Sept. 2010, Funchal, Portugal.
Treiber, M. and Helbing, D. (2002). Reconstructing the spatio-temporal traffic dynamics from stationary detector data. Cooper@tive Tr@nsport@tion Dyn@mics, 1:3.1–3.24.

Author:: Wouter Schakel

Constructor Summary

Constructors

Constructor

Description

Egtf()

Constructor using cCong = -18km/h, cFree = 80km/h, deltaV = 10km/h and vc = 80km/h.

Egtf(double cCong, double cFree, double deltaV, double vc)

Constructor defining global settings.

Egtf(double cCong, double cFree, double deltaV, double vc, double sigma, double tau, double xMax, double tMax)

Convenience constructor that also sets a specified kernel.
Method Summary

Modifier and Type

Method

Description

void

addGridDataSI(DataStream<?> dataStream, double[] location, double[] time, double[][] values)

Adds grid data.

void

addGridDataSI(Quantity<?,?> quantity, double[] location, double[] time, double[][] values)

Adds grid data.

final void

addListener(EgtfListener listener)

Add listener.

void

addPointDataSI(DataStream<?> dataStream, double location, double time, double value)

Adds point data.

void

addPointDataSI(Quantity<?,?> quantity, double location, double time, double value)

Adds point data.

void

addVectorDataSI(DataStream<?> dataStream, double[] location, double[] time, double[] values)

Adds vector data.

void

addVectorDataSI(Quantity<?,?> quantity, double[] location, double[] time, double[] values)

Adds vector data.

void

clearDataBefore(double time)

Removes all data from before the given time.

Filter

filterFastSI(double xMin, double xStep, double xMax, double tMin, double tStep, double tMax, Quantity<?,?>... quantities)

Returns filtered data that is processed using fast fourier transformation.

EgtfParallelListener

filterParallelFastSI(double xMin, double xStep, double xMax, double tMin, double tStep, double tMax, Quantity<?,?>... quantities)

Executes fast filtering in parallel.

EgtfParallelListener

filterParallelSI(double[] location, double[] time, Quantity<?,?>... quantities)

Executes filtering in parallel.

Filter

filterSI(double[] location, double[] time, Quantity<?,?>... quantities)

Returns filtered data.

DataSource

getDataSource(String name)

Return a data source, which is created if necessary.

(package private) final double

getWaveSpeedCongestion()

Returns the wave speed in congestion.

(package private) final double

getWaveSpeedFreeFlow()

Returns the wave speed in free flow.

final void

interrupt()

Interrupt the calculation.

final void

removeListener(EgtfListener listener)

Remove listener.

void

setGaussKernelSI(double sigma, double tau)

Sets a Gaussian kernel with infinite range.

void

setGaussKernelSI(double sigma, double tau, double xMax, double tMax)

Sets a Gaussian kernel with limited range.

void

setKernel()

Sets a default exponential kernel with infinite range, sigma = 300m, and tau = 30s.

void

setKernelSI(double sigma, double tau)

Sets an exponential kernel with infinite range.

void

setKernelSI(double sigma, double tau, double xMax, double tMax)

Sets an exponential kernel with limited range.

void

setKernelSI(double xMax, double tMax, KernelShape shape)

Sets a kernel with limited range and provided shape.

String

toString()

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Details
- Egtf
  
  public Egtf()
  
  Constructor using cCong = -18km/h, cFree = 80km/h, deltaV = 10km/h and vc = 80km/h. A default kernel is set.
- Egtf
  
  public Egtf(double cCong, double cFree, double deltaV, double vc)
  
  Constructor defining global settings. A default kernel is set.
  
  Parameters:
  
  cCong - double; shock wave speed in congestion [km/h]
  
  cFree - double; shock wave speed in free flow [km/h]
  
  deltaV - double; speed range between congestion and free flow [km/h]
  
  vc - double; flip-over speed below which we have congestion [km/h]
- Egtf
  
  public Egtf(double cCong, double cFree, double deltaV, double vc, double sigma, double tau, double xMax, double tMax)
  
  Convenience constructor that also sets a specified kernel.
  
  Parameters:
  
  cCong - double; shock wave speed in congestion [km/h]
  
  cFree - double; shock wave speed in free flow [km/h]
  
  deltaV - double; speed range between congestion and free flow [km/h]
  
  vc - double; flip-over speed below which we have congestion [km/h]
  
  sigma - double; spatial kernel size in [m]
  
  tau - double; temporal kernel size in [s]
  
  xMax - double; maximum spatial range in [m]
  
  tMax - double; maximum temporal range in [s]
Method Details
- getDataSource
  
  public DataSource getDataSource(String name)
  
  Return a data source, which is created if necessary.
  
  Parameters:
  
  name - String; unique name for the data source
  
  Returns:
  
  DataSource; data source
  
  Throws:
  
  IllegalStateException - when data has been added without a data source
- clearDataBefore
  
  public void clearDataBefore(double time)
  
  Removes all data from before the given time. This is useful in live usages of this class, where older data is no longer required.
  
  Parameters:
  
  time - double; time before which all data can be removed
- addPointDataSI
  
  public void addPointDataSI(Quantity<?,?> quantity, double location, double time, double value)
  
  Adds point data.
  
  Parameters:
  
  quantity - Quantity<?, ?>; quantity of the data
  
  location - double; location in [m]
  
  time - double; time in [s]
  
  value - double; data value
  
  Throws:
  
  IllegalStateException - if data was added with a data stream previously
- addPointDataSI
  
  public void addPointDataSI(DataStream<?> dataStream, double location, double time, double value)
  
  Adds point data.
  
  Parameters:
  
  dataStream - DataStream<?>; data stream of the data
  
  location - double; location in [m]
  
  time - double; time in [s]
  
  value - double; data value
  
  Throws:
  
  IllegalStateException - if data was added with a quantity previously
- addVectorDataSI
  
  public void addVectorDataSI(Quantity<?,?> quantity, double[] location, double[] time, double[] values)
  
  Adds vector data.
  
  Parameters:
  
  quantity - Quantity<?, ?>; quantity of the data
  
  location - double[]; locations in [m]
  
  time - double[]; times in [s]
  
  values - double[]; data values in SI unit
  
  Throws:
  
  IllegalStateException - if data was added with a data stream previously
- addVectorDataSI
  
  public void addVectorDataSI(DataStream<?> dataStream, double[] location, double[] time, double[] values)
  
  Adds vector data.
  
  Parameters:
  
  dataStream - DataStream<?>; data stream of the data
  
  location - double[]; locations in [m]
  
  time - double[]; times in [s]
  
  values - double[]; data values in SI unit
  
  Throws:
  
  IllegalStateException - if data was added with a quantity previously
- addGridDataSI
  
  public void addGridDataSI(Quantity<?,?> quantity, double[] location, double[] time, double[][] values)
  
  Adds grid data.
  
  Parameters:
  
  quantity - Quantity<?, ?>; quantity of the data
  
  location - double[]; locations in [m]
  
  time - double[]; times in [s]
  
  values - double[][]; data values in SI unit
  
  Throws:
  
  IllegalStateException - if data was added with a data stream previously
- addGridDataSI
  
  public void addGridDataSI(DataStream<?> dataStream, double[] location, double[] time, double[][] values)
  
  Adds grid data.
  
  Parameters:
  
  dataStream - DataStream<?>; data stream of the data
  
  location - double[]; locations in [m]
  
  time - double[]; times in [s]
  
  values - double[][]; data values in SI unit
  
  Throws:
  
  IllegalStateException - if data was added with a quantity previously
- setKernel
  
  public void setKernel()
  
  Sets a default exponential kernel with infinite range, sigma = 300m, and tau = 30s.
- setKernelSI
  
  public void setKernelSI(double sigma, double tau)
  
  Sets an exponential kernel with infinite range.
  
  Parameters:
  
  sigma - double; spatial kernel size
  
  tau - double; temporal kernel size
- setKernelSI
  
  public void setKernelSI(double sigma, double tau, double xMax, double tMax)
  
  Sets an exponential kernel with limited range.
  
  Parameters:
  
  sigma - double; spatial kernel size in [m]
  
  tau - double; temporal kernel size in [s]
  
  xMax - double; maximum spatial range in [m]
  
  tMax - double; maximum temporal range in [s]
- setGaussKernelSI
  
  public void setGaussKernelSI(double sigma, double tau)
  
  Sets a Gaussian kernel with infinite range.
  
  Parameters:
  
  sigma - double; spatial kernel size
  
  tau - double; temporal kernel size
- setGaussKernelSI
  
  public void setGaussKernelSI(double sigma, double tau, double xMax, double tMax)
  
  Sets a Gaussian kernel with limited range.
  
  Parameters:
  
  sigma - double; spatial kernel size in [m]
  
  tau - double; temporal kernel size in [s]
  
  xMax - double; maximum spatial range in [m]
  
  tMax - double; maximum temporal range in [s]
- setKernelSI
  
  public void setKernelSI(double xMax, double tMax, KernelShape shape)
  
  Sets a kernel with limited range and provided shape. The shape allows using non-exponential kernels.
  
  Parameters:
  
  xMax - double; maximum spatial range
  
  tMax - double; maximum temporal range
  
  shape - KernelShape; shape of the kernel
- getWaveSpeedCongestion
  
  final double getWaveSpeedCongestion()
  
  Returns the wave speed in congestion.
  
  Returns:
  
  double; wave speed in congestion
- getWaveSpeedFreeFlow
  
  final double getWaveSpeedFreeFlow()
  
  Returns the wave speed in free flow.
  
  Returns:
  
  double; wave speed in free flow
- filterParallelSI
  
  public EgtfParallelListener filterParallelSI(double[] location, double[] time, Quantity<?,?>... quantities)
  
  Executes filtering in parallel. The returned listener can be used to report progress and wait until the filtering is done. Finally, the filtering results can then be obtained from the listener.
  
  Parameters:
  
  location - double[]; location of output grid in [m]
  
  time - double[]; time of output grid in [s]
  
  quantities - Quantity<?, ?>...; quantities to calculate filtered data of
  
  Returns:
  
  EgtfParallelListener; listener to notify keep track of the progress
- filterParallelFastSI
  
  public EgtfParallelListener filterParallelFastSI(double xMin, double xStep, double xMax, double tMin, double tStep, double tMax, Quantity<?,?>... quantities)
  
  Executes fast filtering in parallel. The returned listener can be used to report progress and wait until the filtering is done. Finally, the filtering results can then be obtained from the listener.
  
  Parameters:
  
  xMin - double; minimum location value of output grid [m]
  
  xStep - double; location step of output grid [m]
  
  xMax - double; maximum location value of output grid [m]
  
  tMin - double; minimum time value of output grid [s]
  
  tStep - double; time step of output grid [s]
  
  tMax - double; maximum time value of output grid [s]
  
  quantities - Quantity<?, ?>...; quantities to calculate filtered data of
  
  Returns:
  
  EgtfParallelListener; listener to notify keep track of the progress
- filterSI
  
  public Filter filterSI(double[] location, double[] time, Quantity<?,?>... quantities)
  
  Returns filtered data. This is the standard EGTF implementation.
  
  Parameters:
  
  location - double[]; location of output grid in [m]
  
  time - double[]; time of output grid in [s]
  
  quantities - Quantity<?, ?>...; quantities to calculate filtered data of
  
  Returns:
  
  Filter; filtered data, null when interrupted
- filterFastSI
  
  public Filter filterFastSI(double xMin, double xStep, double xMax, double tMin, double tStep, double tMax, Quantity<?,?>... quantities)
  
  Returns filtered data that is processed using fast fourier transformation. This is much faster than the standard filter, at the cost that all input data is discretized to the output grid. The gain in computation speed is however such that finer output grids can be used to alleviate this. For discretization the output grid needs to be equidistant. It is recommended to set a Kernel with maximum bounds before using this method.
  More than being a fast implementation of the Adaptive Smoothing Method, this implementation includes all data source like the Extended Generalized Treiber-Helbing Filter.
  
  Parameters:
  
  xMin - double; minimum location value of output grid [m]
  
  xStep - double; location step of output grid [m]
  
  xMax - double; maximum location value of output grid [m]
  
  tMin - double; minimum time value of output grid [s]
  
  tStep - double; time step of output grid [s]
  
  tMax - double; maximum time value of output grid [s]
  
  quantities - Quantity<?, ?>...; quantities to calculate filtered data of
  
  Returns:
  
  Filter; filtered data, null when interrupted
- interrupt
  
  public final void interrupt()
  
  Interrupt the calculation.
- addListener
  
  public final void addListener(EgtfListener listener)
  
  Add listener.
  
  Parameters:
  
  listener - EgtfListener; listener
- removeListener
  
  public final void removeListener(EgtfListener listener)
  
  Remove listener.
  
  Parameters:
  
  listener - EgtfListener; listener
- toString
  
  public String toString()
  
  Overrides:
  
  toString in class Object

Class Egtf

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Details

Egtf

Egtf

Egtf

Method Details

getDataSource

clearDataBefore

addPointDataSI

addPointDataSI

addVectorDataSI

addVectorDataSI

addGridDataSI

addGridDataSI

setKernel

setKernelSI

setKernelSI

setGaussKernelSI

setGaussKernelSI

setKernelSI

getWaveSpeedCongestion

getWaveSpeedFreeFlow

filterParallelSI

filterParallelFastSI

filterSI

filterFastSI

interrupt

addListener

removeListener

toString