Add a new estimator approach

contribs/drt/src/main/java/org/matsim/contrib/drt/estimator/impl/EuclideanDistanceBasedDrtEstimator.java

@@ -0,0 +1,78 @@
+package org.matsim.contrib.drt.estimator.impl;
+
+import org.matsim.api.core.v01.Coord;
+import org.matsim.api.core.v01.network.Network;
+import org.matsim.contrib.drt.estimator.DrtEstimator;
+import org.matsim.contrib.drt.routing.DrtRoute;
+import org.matsim.core.utils.geometry.CoordUtils;
+import org.matsim.core.utils.misc.OptionalTime;
+
+import java.util.Random;
+
+public class EuclideanDistanceBasedDrtEstimator implements DrtEstimator {
+	private final Network network;
+	/**
+	 * For travel distance related scoring (e.g., marginal utility distance), we need estimated network distance:
+	 * Estimated network distance = Euclidean distance * network distance factor
+	 */
+	private final double networkDistanceFactor;
+	/**
+	 * Slope of the linear regression
+	 */
+	private final double slope;
+	/**
+	 * Intercept of the linear regression
+	 */
+	private final double intercept;
+
+	private final double estimatedMeanWaitTime;
+
+	private final double waitTimeStd;
+
+	private final double mu;
+	private final double sigma;
+	private final Random random = new Random(1234);
+
+	/**
+	 * We use log normal distribution to estimate the ride duration of each individual trip. The distribution
+	 * is based on the linear regression.
+	 * @params networkDistanceFactor: Estimated network distance = Euclidean distance * network distance factor
+	 * @params slope: slope for the linear regression
+	 * @params intercept: intercept for linear regression
+	 * @params mu: mu for log normal distribution
+	 * @params sigma: sigma for log normal distribution.
+	 */
+	public EuclideanDistanceBasedDrtEstimator(Network network, double networkDistanceFactor, double slope,
+											  double intercept, double estimatedMeanWaitTime, double waitTimeStd,
+											  double mu, double sigma) {
+		this.network = network;
+		this.networkDistanceFactor = networkDistanceFactor;
+		this.slope = slope;
+		this.intercept = intercept;
+		this.estimatedMeanWaitTime = estimatedMeanWaitTime;
+		this.waitTimeStd = waitTimeStd;
+		this.mu = mu;
+		this.sigma = sigma;
+	}
+
+	@Override
+	public Estimate estimate(DrtRoute route, OptionalTime departureTime) {
+		Coord fromCoord = network.getLinks().get(route.getStartLinkId()).getToNode().getCoord();
+		Coord toCoord = network.getLinks().get(route.getEndLinkId()).getToNode().getCoord();
+		double euclideanDistance = CoordUtils.calcEuclideanDistance(fromCoord, toCoord);
+		double typicalRideDuration = euclideanDistance * slope + intercept;
+		double typicalRideDistance = networkDistanceFactor * euclideanDistance;
+		double randomFactor = nextLogNormal(mu, sigma);
+		double waitTime = Math.max(estimatedMeanWaitTime * (1 + random.nextGaussian() * waitTimeStd), 0);
+
+		return new Estimate(typicalRideDistance * randomFactor, typicalRideDuration * randomFactor,
+			waitTime, 0);
+	}
+
+	public double nextLogNormal(double mu, double sigma) {
+		if (sigma == 0)
+			return Math.exp(mu);
+
+		return Math.exp(sigma * random.nextGaussian() + mu);
+	}
+}

contribs/drt/src/test/java/org/matsim/contrib/drt/teleportation/DrtTeleportationWithModeChoiceTest.java

@@ -4,8 +4,10 @@
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.extension.RegisterExtension;
 import org.matsim.api.core.v01.TransportMode;
+import org.matsim.api.core.v01.network.Network;
 import org.matsim.contrib.drt.estimator.DrtEstimator;
 import org.matsim.contrib.drt.estimator.impl.DetourBasedDrtEstimator;
+import org.matsim.contrib.drt.estimator.impl.EuclideanDistanceBasedDrtEstimator;
 import org.matsim.contrib.drt.run.DrtConfigGroup;
 import org.matsim.contrib.drt.run.DrtControlerCreator;
 import org.matsim.contrib.drt.run.MultiModeDrtConfigGroup;
@@ -37,7 +39,7 @@ void testModeChoice() {
 		config.network().setInputFile("network.xml");
 		config.plans().setInputFile("plans_only_drt_4.0.xml.gz");
 		config.controller().setOutputDirectory(utils.getOutputDirectory());
-		config.controller().setLastIteration(100);
+		config.controller().setLastIteration(3);
 
 		config.replanning().setFractionOfIterationsToDisableInnovation(0.8);
 		config.replanning().setMaxAgentPlanMemorySize(3);
@@ -58,7 +60,7 @@ void testModeChoice() {
 		bikeModeParams.setMarginalUtilityOfTraveling(-6.);
 		config.scoring().addModeParams(bikeModeParams);
 		// Update change mode
-		config.changeMode().setModes( new String[] { TransportMode.drt, TransportMode.bike });
+		config.changeMode().setModes(new String[]{TransportMode.drt, TransportMode.bike});
 
 		// Setting DRT config group
 		DrtConfigGroup drtConfigGroup = DrtConfigGroup.getSingleModeDrtConfig(config);
@@ -70,8 +72,11 @@ void testModeChoice() {
 		controler.addOverridingModule(new AbstractDvrpModeModule(drtConfigGroup.mode) {
 			@Override
 			public void install() {
-				bindModal(DrtEstimator.class).toInstance(DetourBasedDrtEstimator.normalDistributed(1.2, 32,
-						0.3, 300, 0.4));
+//				bindModal(DrtEstimator.class).toInstance(DetourBasedDrtEstimator.normalDistributed(1.2, 32,
+//						0.3, 300, 0.4));
+				bindModal(DrtEstimator.class).toProvider(modalProvider(getter -> new
+					EuclideanDistanceBasedDrtEstimator(getter.getModal(Network.class), 2.0, 0.1577493,
+					103.0972273, 120, 0.3, -0.1, 0.28)));
 			}
 		});