First really working version for ad-hoc

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/data/JamInformationContainer.java

+/*
+ * Copyright (c) 2005-2010 KOM – Multimedia Communications Lab
+ *
+ * This file is part of Simonstrator.KOM.
+ * 
+ * Simonstrator.KOM is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * any later version.
+ * 
+ * PeerfactSim.KOM is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ * 
+ * You should have received a copy of the GNU General Public License
+ * along with PeerfactSim.KOM.  If not, see <http://www.gnu.org/licenses/>.
+ *
+ */
+
+
+package de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data;
+
+/**
+ * @author Tobias Meuser (tobias.meuser@kom.tu-darmstadt.de)
+ * @version 1.0 at 24.04.2018
+ *
+ */
+public class JamInformationContainer {
+    public static long EVENT_DURATION = 0;
+}

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/data/ProbabilityDistribution.java

+/*
+ * Copyright (c) 2005-2010 KOM – Multimedia Communications Lab
+ *
+ * This file is part of Simonstrator.KOM.
+ * 
+ * Simonstrator.KOM is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * any later version.
+ * 
+ * PeerfactSim.KOM is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ * 
+ * You should have received a copy of the GNU General Public License
+ * along with PeerfactSim.KOM.  If not, see <http://www.gnu.org/licenses/>.
+ *
+ */
+
+
+package de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data;
+
+/**
+ * @author Tobias Meuser (tobias.meuser@kom.tu-darmstadt.de)
+ * @version 1.0 at 23.04.2018
+ *
+ */
+public enum ProbabilityDistribution {
+	SIMPLE, GAUSSIAN
+}

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/data/RoadProperty.java

@@ -32,4 +32,6 @@ public interface RoadProperty extends LocationBasedEnvironmentProperty {
 	RoadNetworkEdge getEdge();
 
 	EnvironmentProperty getDefaultProperty();
+
+	long getDetectionDate();
 }

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/data/VectoralJamProperty.java

@@ -22,7 +22,10 @@
 package de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data;
 
 import java.util.Arrays;
+import java.util.HashMap;
+import java.util.Map;
 
+import de.tudarmstadt.maki.simonstrator.api.Time;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.vector.TemporalDependencyMatrix;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.location.Location;
 import de.tudarmstadt.maki.simonstrator.api.component.vehicular.roadnetwork.RoadNetworkEdge;
@@ -34,16 +37,67 @@ import de.tudarmstadt.maki.simonstrator.api.component.vehicular.roadnetwork.Road
  */
 public class VectoralJamProperty extends NumericVectoralProperty {
 	public static final double SCALING = 6;
-	private static final int DIMENSIONS = 15;
+	private static final int DIMENSIONS = 10;
 
-	private static final double TEMPORAL_CHANGE = 0.05;
+	private static Map<Double, Double> _requiredStandardDeviation = new HashMap<>();
+	private static TemporalDependencyMatrix _temporalDependencyMatrix;
 
 	public VectoralJamProperty(Location pLocation, RoadNetworkEdge pEdge) {
 		super(pLocation, pEdge, DIMENSIONS);
 	}
 
-	public void setSpeed(double pSpeed, double pDeviation) {
-		setProbabilities(pSpeed / SCALING, pDeviation / SCALING);
+	/**
+	 * 
+	 */
+	public VectoralJamProperty() {
+		this(null, null);
+	}
+
+	public void setSpeed(double pSpeed) {
+		double[] valueProbabilities = getValueProbabilities();
+		Arrays.fill(valueProbabilities, 0);
+		valueProbabilities[(int) (pSpeed / SCALING)] = 1;
+	}
+
+	public void setSpeed(double pSpeed, double pAccuracy, ProbabilityDistribution pDist) {
+		switch (pDist) {
+		case SIMPLE:
+			setSimpleSpeed(pSpeed, pAccuracy);
+			break;
+		case GAUSSIAN:
+			setGaussianSpeedWithAccuracy(pSpeed, pAccuracy);
+			break;
+		default:
+			throw new AssertionError("Unknown ProbablilityDistribution " + pDist);
+		}
+	}
+
+	private void setSimpleSpeed(double pSpeed, double pAccuracy) {
+		double[] valueProbabilities = getValueProbabilities();
+		Arrays.fill(valueProbabilities, 0);
+		int index = (int) (pSpeed / SCALING);
+		valueProbabilities[index] += pAccuracy;
+
+		if (index + 1 < valueProbabilities.length) {
+			valueProbabilities[index + 1] += (1 - pAccuracy) / 2.0;
+		} else {
+			valueProbabilities[index - 1] += (1 - pAccuracy) / 2.0;
+		}
+
+		if (index - 1 >= 1) {
+			valueProbabilities[index - 1] += (1 - pAccuracy) / 2.0;
+		} else {
+			valueProbabilities[index + 1] += (1 - pAccuracy) / 2.0;
+		}
+	}
+
+	public void setGaussianSpeedWithAccuracy(double pSpeed, double pAccuracy) {
+		double deviation = determineCorrectDeviation(pSpeed, pAccuracy);
+		setGaussianProbabilities(pSpeed / SCALING, deviation / SCALING);
+	}
+
+	public void setGaussianSpeed(double pSpeed, double pDeviation) {
+		setGaussianProbabilities(pSpeed / SCALING, pDeviation / SCALING);
 	}
 
 	@Override
@@ -54,6 +108,11 @@ public class VectoralJamProperty extends NumericVectoralProperty {
 		return vectoralJamProperty;
 	}
 
+	@Override
+	public VectoralJamProperty age(long pAge) {
+		return (VectoralJamProperty) super.age(pAge);
+	}
+
 	@Override
 	public EnvironmentProperty getDefaultProperty() {
 		return new VectoralJamProperty(getLocation(), getEdge());
@@ -66,16 +125,28 @@ public class VectoralJamProperty extends NumericVectoralProperty {
 
 	@Override
 	public TemporalDependencyMatrix getDependencyMatrix() {
-		TemporalDependencyMatrix temporalDependencyMatrix = new TemporalDependencyMatrix(DIMENSIONS);
-		for (int x = 0; x < DIMENSIONS; x++) {
-			double[] probabilities = new double[DIMENSIONS];
-			probabilities[Math.max(0, x - 1)] += TEMPORAL_CHANGE;
-			probabilities[Math.min(DIMENSIONS - 1, x + 1)] += TEMPORAL_CHANGE;
-			probabilities[x] += (1 - 2 * TEMPORAL_CHANGE);
-
-			temporalDependencyMatrix.setTransitionProbability(x, probabilities);
+		if (_temporalDependencyMatrix == null) {
+			TemporalDependencyMatrix temporalDependencyMatrix = new TemporalDependencyMatrix(DIMENSIONS);
+			double TEMPORAL_CHANGE = 1 / ((double) JamInformationContainer.EVENT_DURATION / Time.SECOND) / 2.0;
+			for (int x = 0; x < DIMENSIONS; x++) {
+				double[] probabilities = new double[DIMENSIONS];
+				if (x > 1) {
+					probabilities[x - 1] += TEMPORAL_CHANGE;
+				} else {
+					probabilities[x + 1] += TEMPORAL_CHANGE;
+				}
+				if (x < DIMENSIONS - 1) {
+					probabilities[x + 1] += TEMPORAL_CHANGE;
+				} else {
+					probabilities[x - 1] += TEMPORAL_CHANGE;
+				}
+				probabilities[x] += (1 - 2 * TEMPORAL_CHANGE);
+
+				temporalDependencyMatrix.setTransitionProbability(x, probabilities);
+			}
+			_temporalDependencyMatrix = temporalDependencyMatrix;
 		}
-		return temporalDependencyMatrix;
+		return _temporalDependencyMatrix;
 	}
 
 	public double getProbabilityForValue(Object pValue) {
@@ -123,4 +194,38 @@ public class VectoralJamProperty extends NumericVectoralProperty {
 		}
 		return super.equals(pObj);
 	}
+
+	public double determineCorrectDeviation(double speed, double pAccuracy) {
+		if (!_requiredStandardDeviation.containsKey(speed)) {
+			if (pAccuracy < 1) {
+				VectoralJamProperty vectoralJamProperty = new VectoralJamProperty(null, null);
+
+				double deviation = 10;
+
+				boolean reduceChange = false;
+				double currentChange = deviation / 2;
+
+				do {
+					vectoralJamProperty.setGaussianSpeed(speed, deviation);
+					if (vectoralJamProperty.getProbabilityForValue(speed) > pAccuracy) {
+						deviation += currentChange;
+					} else {
+						deviation -= currentChange;
+						reduceChange = true;
+					}
+
+					if (reduceChange) {
+						currentChange /= 2.0;
+					}
+				} while (Math.round(vectoralJamProperty.getProbabilityForValue(speed) * 10000) != Math
+						.round(pAccuracy * 10000));
+
+				_requiredStandardDeviation.put(speed, deviation);
+			} else {
+				_requiredStandardDeviation.put(speed, 0d);
+			}
+		}
+
+		return _requiredStandardDeviation.get(speed);
+	}
 }
\ No newline at end of file

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/data/VectoralProperty.java

@@ -59,7 +59,7 @@ public abstract class VectoralProperty implements RoadProperty, Cloneable {
 		_valueProbabilities = pValueProbabilities;
 	}
 
-	protected void setProbabilities(double pMean, double pDeviation) {
+	protected void setGaussianProbabilities(double pMean, double pDeviation) {
 		if (pDeviation > 0) {
 			double sum = 0;
 			for (int i = 0; i < _valueProbabilities.length; i++) {
@@ -112,7 +112,7 @@ public abstract class VectoralProperty implements RoadProperty, Cloneable {
 
 	public abstract Object getValueAtIndex(int pIndex);
 
-	public Object getMostProbableValue() {
+	public int getMostProbableIndex() {
 		double max = -1;
 		int index = 0;
 
@@ -124,7 +124,11 @@ public abstract class VectoralProperty implements RoadProperty, Cloneable {
 			}
 		}
 
-		return getValueAtIndex(index);
+		return index;
+	}
+
+	public Object getMostProbableValue() {
+		return getValueAtIndex(getMostProbableIndex());
 	}
 
 	public abstract TemporalDependencyMatrix getDependencyMatrix();
@@ -170,6 +174,10 @@ public abstract class VectoralProperty implements RoadProperty, Cloneable {
 		return result;
 	}
 
+	public double getProbabilityForIndex(int pIndex) {
+		return getValueProbabilities()[pIndex];
+	}
+
 	public abstract double getProbabilityForValue(Object pValue);
 
 	public VectoralProperty combine(VectoralProperty pVectoralProperty) {

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/data/vector/TemporalDependencyMatrix.java

@@ -22,6 +22,8 @@
 package de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.vector;
 
 import java.util.Arrays;
+import java.util.HashMap;
+import java.util.Map;
 
 /**
  * @author Tobias Meuser (tobias.meuser@kom.tu-darmstadt.de)
@@ -32,6 +34,8 @@ public class TemporalDependencyMatrix implements Cloneable {
 	// Value x | y --> Transition probability from state x to state y
 	private double[][] _dependencies;
 
+	private Map<Long, TemporalDependencyMatrix> _agedMatrices = new HashMap<>();
+
 	public TemporalDependencyMatrix(int dimension) {
 		_dependencies = new double[dimension][dimension];
 	}
@@ -51,23 +55,31 @@ public class TemporalDependencyMatrix implements Cloneable {
 	}
 
 	public TemporalDependencyMatrix age(long pAge) {
-		double[][] current = cloneArray(_dependencies);
-
-		for (long t = 0; t < pAge; t++) {
-			double[][] next = createEmptyArray(current);
-
+		if (!_agedMatrices.containsKey(pAge)) {
+			double[][] current = new double[_dependencies.length][];
+			
 			for (int i = 0; i < current.length; i++) {
-				for (int j = 0; j < current[i].length; j++) {
-					for (int k = 0; k < current[i].length; k++) {
-						next[i][j] += current[i][k] * _dependencies[k][j];
+				current[i] = new double[_dependencies[i].length];
+				current[i][i] = 1;
+			}
+			
+			for (long t = 0; t < pAge; t++) {
+				double[][] next = createEmptyArray(current);
+				
+				for (int i = 0; i < current.length; i++) {
+					for (int j = 0; j < current[i].length; j++) {
+						for (int k = 0; k < current[i].length; k++) {
+							next[i][j] += current[i][k] * _dependencies[k][j];
+						}
 					}
 				}
+				
+				current = next;
 			}
-
-			current = next;
+			
+			_agedMatrices.put(pAge, new TemporalDependencyMatrix(current));
 		}
-
-		return new TemporalDependencyMatrix(current);
+		return _agedMatrices.get(pAge);
 	}
 
 	public double[][] cloneArray(double[][] pDependencies) {
@@ -104,4 +116,12 @@ public class TemporalDependencyMatrix implements Cloneable {
 
 		return new TemporalDependencyMatrix(dependencies);
 	}
+
+	/**
+	 * @param pI
+	 * @return
+	 */
+	public double getChangeProbability(int pI) {
+		return 1 - _dependencies[pI][pI];
+	}
 }

src/de/tudarmstadt/maki/simonstrator/api/component/sensor/environment/plugin/VectoralJamEnvironmentSensorPlugin.java

@@ -22,9 +22,7 @@
 package de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.plugin;
 
 import java.util.ArrayList;
-import java.util.HashMap;
 import java.util.List;
-import java.util.Map;
 import java.util.Random;
 
 import de.tudarmstadt.maki.simonstrator.api.Host;
@@ -32,6 +30,7 @@ import de.tudarmstadt.maki.simonstrator.api.Randoms;
 import de.tudarmstadt.maki.simonstrator.api.component.ComponentNotAvailableException;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.EnvironmentProperty;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.JamProperty;
+import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.ProbabilityDistribution;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.RoadProperty;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.VectoralJamProperty;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.location.Location;
@@ -54,13 +53,29 @@ public class VectoralJamEnvironmentSensorPlugin implements EnvironmentSensorPlug
 
 	private double _accuracy;
 
-	private Map<Double, Double> _requiredStandardDeviation = new HashMap<>();
-
 	private static Random _random = Randoms.getRandom(VectoralJamEnvironmentSensorPlugin.class);
 
+	private static Random _accuracyRandom = Randoms.getRandom(VectoralJamEnvironmentSensorPlugin.class + "Accuracy");
+
+	private ProbabilityDistribution _probabilityDistribution = ProbabilityDistribution.SIMPLE;
+
 	@XMLConfigurableConstructor({ "accuracy" })
 	public VectoralJamEnvironmentSensorPlugin(double pAccuracy) {
-		setAccuracy(pAccuracy);
+		double deviation = 0.2 * pAccuracy;
+		if (deviation + pAccuracy > 1) {
+			deviation = 1 - pAccuracy;
+		}
+		if (pAccuracy - deviation < 0.6) {
+			deviation = pAccuracy - 0.6;
+		}
+		double accuracy = pAccuracy + _accuracyRandom.nextGaussian() * deviation;
+		if (accuracy < pAccuracy - deviation) {
+			accuracy = pAccuracy - deviation;
+		}
+		if (accuracy > pAccuracy + deviation) {
+			accuracy = pAccuracy + deviation;
+		}
+		setAccuracy(accuracy);
 	}
 
 	@Override
@@ -95,17 +110,10 @@ public class VectoralJamEnvironmentSensorPlugin implements EnvironmentSensorPlug
 				speed = (int) (edge.getOriginalMaxSpeed() / VectoralJamProperty.SCALING) * VectoralJamProperty.SCALING;
 			}
 
-			if (!_requiredStandardDeviation.containsKey(speed)) {
-				determineCorrectDeviation(speed);
-			}
-
-			double measuredSpeed = measureValue(speed, _requiredStandardDeviation.get(speed));
+			double measuredSpeed = measureValue(speed);
 			VectoralJamProperty vectoralJamProperty = new VectoralJamProperty(location, edge);
 
-			if (!_requiredStandardDeviation.containsKey(measuredSpeed)) {
-				determineCorrectDeviation(measuredSpeed);
-			}
-			vectoralJamProperty.setSpeed(measuredSpeed, _requiredStandardDeviation.get(measuredSpeed));
+			vectoralJamProperty.setSpeed(measuredSpeed, _accuracy, _probabilityDistribution);
 
 			List<EnvironmentProperty> properties = new ArrayList<>();
 			EnvironmentProperty property = vectoralJamProperty;
@@ -116,9 +124,9 @@ public class VectoralJamEnvironmentSensorPlugin implements EnvironmentSensorPlug
 		}
 	}
 
-	public double measureValue(double pRealSpeed, double pDeviation) {
+	public double measureValue(double pRealSpeed) {
 		VectoralJamProperty vectoralJamProperty = new VectoralJamProperty(null, null);
-		vectoralJamProperty.setSpeed(pRealSpeed, pDeviation);
+		vectoralJamProperty.setSpeed(pRealSpeed, _accuracy, _probabilityDistribution);
 		double nextDouble = _random.nextDouble();
 
 		double currentAggregate = 0;
@@ -133,36 +141,6 @@ public class VectoralJamEnvironmentSensorPlugin implements EnvironmentSensorPlug
 		throw new AssertionError("Unexpected!");
 	}
 
-	public void determineCorrectDeviation(double speed) {
-		if (_accuracy < 1) {
-			VectoralJamProperty vectoralJamProperty = new VectoralJamProperty(null, null);
-
-			double deviation = 10;
-
-			boolean reduceChange = false;
-			double currentChange = deviation / 2;
-
-			do {
-				vectoralJamProperty.setSpeed(speed, deviation);
-				if (vectoralJamProperty.getProbabilityForValue(speed) > _accuracy) {
-					deviation += currentChange;
-				} else {
-					deviation -= currentChange;
-					reduceChange = true;
-				}
-
-				if (reduceChange) {
-					currentChange /= 2.0;
-				}
-			} while (Math.round(vectoralJamProperty.getProbabilityForValue(speed) * 10000) != Math
-					.round(_accuracy * 10000));
-
-			_requiredStandardDeviation.put(speed, deviation);
-		} else {
-			_requiredStandardDeviation.put(speed, 0d);
-		}
-	}
-
 	@Override
 	public VectoralJamEnvironmentSensorPlugin clone() throws CloneNotSupportedException {
 		return new VectoralJamEnvironmentSensorPlugin(_accuracy);

src/de/tudarmstadt/maki/simonstrator/api/component/vehicular/information/RoadInformation.java

@@ -41,4 +41,12 @@ public class RoadInformation extends EnvironmentInformation<RoadProperty>
 		return getValue().getEdge();
 	}
 
+	@Override
+	public <T> T getAttribute(AvailableInformationAttributes pKey) {
+		if (AvailableInformationAttributes.EDGE.equals(pKey)) {
+			return (T) getEdge();
+		}
+		return super.getAttribute(pKey);
+	}
+
 }

src/de/tudarmstadt/maki/simonstrator/api/component/vehicular/roadnetwork/RoadNetworkEdge.java

@@ -26,6 +26,7 @@ import java.util.List;
 
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.JamProperty;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.RoadProperty;
+import de.tudarmstadt.maki.simonstrator.api.component.sensor.environment.data.VectoralJamProperty;
 import de.tudarmstadt.maki.simonstrator.api.component.sensor.location.Location;
 import de.tudarmstadt.maki.simonstrator.api.component.vehicular.api.EdgeController;
 
@@ -80,6 +81,37 @@ public class RoadNetworkEdge {
 		}
 	}
 
+	public double getCurrentSpeedState() {
+		double actualSpeed = -1;
+		JamProperty jamProperty = getJamProperty();
+		if (jamProperty != null) {
+			actualSpeed = jamProperty.getAverageSpeed();
+		} else {
+			actualSpeed = getCorrespondingState(getOriginalMaxSpeed());
+		}
+
+		return actualSpeed;
+	}
+
+	public JamProperty getJamProperty() {
+		List<RoadProperty> activeProperties = getActiveProperties();
+		for (RoadProperty roadProperty : activeProperties) {
+			if (roadProperty instanceof JamProperty) {
+				return (JamProperty) roadProperty;
+			}
+		}
+
+		return null;
+	}
+
+	/**
+	 * @param pExpectation
+	 * @return
+	 */
+	public static double getCorrespondingState(double pExpectation) {
+		return ((int) (pExpectation / VectoralJamProperty.SCALING)) * VectoralJamProperty.SCALING;
+	}
+
 	public void removeRoadProperty(RoadProperty pProperty) {
 		_activeProperties.remove(pProperty);