idealGroundTruthSensor

Generate ground truth measurements as sensor detections or track reports from driving scenario or RoadRunner Scenario

Since R2025a

Description

The idealGroundTruthSensor System object™ generates detections or track reports for ground-truth measurements of all the targets in the field-of-view of the sensor. The sensor also generates ground-truth measurements for lane boundaries in the scenario. You can mount the idealGroundTruthSensor on a vehicle and use it in a scenario containing other actors and trajectories created using a drivingScenario object.

You can also use the idealGroundTruthSensor object with vehicle actors in RoadRunner Scenario simulation. First you must create a SensorSimulation object to interface sensors with RoadRunner Scenario, and then register the sensor model using the addSensors object function before simulation.

To generate ideal ground-truth detections:

1. Create the idealGroundTruthSensor object and set its properties.

2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?

Creation

Syntax

idealGTSensor = idealGroundTruthSensor

idealGTSensor = idealGroundTruthSensor(Name=Value)

Description

idealGTSensor = idealGroundTruthSensor creates an ideal ground truth sensor object with default property values.

idealGTSensor = idealGroundTruthSensor(Name=Value) sets properties using one or more name-value pairs. For example, idealGroundTruthSensor(DetectionCoordinates="Host Coordinates",MaxRange=200) creates an ideal ground truth sensor that reports detections in the host vehicle coordinate system and has a maximum detection range of 200 meters.

Properties

Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

SensorIndex — Unique sensor identifier

positive integer

Unique sensor identifier, specified as a positive integer. This property distinguishes detections that come from different sensors in a multi-sensor system.

Example: 5

Data Types: double

DetectorOutput — Types of detections generated by sensor

'Objects Only' (default) | 'Objects and Lanes'

Types of detections generated by the sensor, specified as 'Objects' or 'Objects and Lanes'.

• When set to 'Objects Only', only actors are detected.

• When set to 'Objects and Lanes', the sensor generates both object detections and unoccluded lane detections.

Example: 'Objects and Lanes'

Data Types: char | string

UpdateInterval — Required time interval between sensor updates

0.1 | positive real scalar

Required time interval between sensor updates, specified as a positive real scalar. The drivingScenario object calls the ideal ground truth sensor at regular time intervals. The vision detector generates new detections at intervals defined by the UpdateInterval property. The value of the UpdateInterval property must be an integer multiple of the simulation time interval. Updates requested from the sensor between update intervals contain no detections. Units are in seconds.

Example: 5

Data Types: double

SensorLocation — Sensor mounting location on ego vehicle

[3.4 0 0.2] (default) | 1-by-3 real-valued vector of form [x y z]

Sensor mounting location on the ego vehicle, specified as a 1-by-3 real-valued vector of the form [x y z]. This property defines the coordinates of the sensor in meters, along the x-, y-, and z-axes relative to the ego vehicle origin, where:

• The x-axis points forward from the vehicle.

• The y-axis points to the left of the vehicle.

• The z-axis points up from the ground.

The default value defines a sensor that is mounted at the center of the front grill of a sedan.

For more details on the ego vehicle coordinate system, see Coordinate Systems in Automated Driving Toolbox.

Data Types: double

Yaw — Yaw angle of sensor

0 (default) | real scalar

Yaw angle of the sensor, specified as a real scalar. The yaw angle is the angle between the center line of the ego vehicle and the down-range axis of the vision sensor. A positive yaw angle corresponds to a clockwise rotation when looking in the positive direction of the z-axis of the ego vehicle coordinate system. Units are in degrees.

Example: -4

Data Types: double

Pitch — Pitch angle of sensor

0 (default) | real scalar

Pitch angle of the sensor, specified as a real scalar. The pitch angle is the angle between the down-range axis of the vision sensor and the x-y plane of the ego vehicle coordinate system. A positive pitch angle corresponds to a clockwise rotation when looking in the positive direction of the y-axis of the ego vehicle coordinate system. Units are in degrees.

Example: 3

Data Types: double

Roll — Roll angle of sensor

0 (default) | real scalar

Roll angle of the sensor, specified as a real scalar. The roll angle is the angle of rotation of the down-range axis of the vision sensor around the x-axis of the ego vehicle coordinate system. A positive roll angle corresponds to a clockwise rotation when looking in the positive direction of the x-axis of the coordinate system. Units are in degrees.

Example: -4

Data Types: double

FieldOfView — Angular field of view of vision sensor

[120 30] (default) | real-valued 1-by-2 vector of positive values

Angular field of view of the sensor, specified as a real-valued 1-by-2 vector of positive values, [azfov,elfov]. The field of view defines the azimuth and elevation extents of the sensor data. Each component must lie in the interval from 0 degrees to 180 degrees. Targets outside of the angular field of view of the sensor are not detected. Units are in degrees.

Data Types: double

MaxRange — Maximum detection range

50 (default) | positive real scalar

Maximum detection range, specified as a positive real scalar. The sensor cannot detect a target beyond this range. Units are in meters.

Example: 200

Data Types: double

DetectionCoordinates — Coordinate system of reported detections

'Host Coordinates' (default) | 'Sensor Coordinates'

Coordinate system of reported detections, specified as one of these values:

• 'Host Coordinates' — Detections are reported in the ego vehicle Cartesian coordinate system.

• 'Sensor Coordinates' — Detections are reported in the sensor Cartesian coordinate system.

Data Types: char | string

PointOnTargetReported — Point on the target used to report position

'Origin Point' (default) | 'Closest Point' | 'Rear Center'

Point on target used to report ground truth position, specified as one of these options:

• 'Origin Point' — The sensor reports the origin of the local coordinate frame of the target actor. For driving scenario vehicle actors, the origin is their rear-axle center. For RoadRunner Scenario vehicle actors, the origin is their geometric center.

• 'Closest Point' — The sensor reports the point on the target actor closest to the sensor.

• 'Rear Center' — The sensor reports the rear center of the target actor.

TargetOutputFormat — Format in which sensor reports target actors

'Object detections' (default) | 'Tracks' | 'Target Poses'

Format in which the sensor reports target actors, specified as one of these options:

• 'Object detections' — The sensor generates target reports as an array of objectDetection objects, as described in the dets output argument.

• 'Tracks' — The sensor generates target reports as tracks, which are clustered detections that have been processed by a tracking filter. The sensor returns tracks as an array of objectTrack objects, as described in the tracks output argument.

• 'Target Poses' — The sensor generates target reports as an array of structures as described in the poses output argument. For the target pose structure array definition, see the poses output argument.

MaxNumObjectDetections — Maximum number of reported detections

300 (default) | positive integer

Maximum number of object detections reported by the sensor, specified as a positive integer. The detections closest to the sensor are reported.

Data Types: double

LaneBoundariesReported — Lane boundaries reported by sensor

'Ego Lane' (default) | 'Ego and Adjacent Lanes' | 'All Lanes'

Lane boundaries reported by sensor, specified as one of these options:

• 'Ego Lane' — The sensor returns the boundaries for the lane in which the host vehicle actor is traveling.

• 'Ego and Adjacent Lanes' — The sensor returns the boundaries for the adjacent left and right lanes along with the lane in which host vehicle actor is traveling.

• 'All Lanes' — The sensor returns the boundaries for all lanes on the road.

Dependencies

To enable this property, first set DetectorOutput property to 'Objects and Lanes'.

MaxNumLaneDetections — Maximum number of reported lanes

300 (default) | positive integer

Maximum number of reported lanes, specified as a positive integer.

Dependencies

To enable this property, first set DetectorOutput property to 'Objects and Lanes'.

Data Types: double

Usage

Syntax

[dets,numReports,isValidTime] = idealGTSensor()

[tracks,numReports,isValidTime] = idealGTSensor()

[poses,numReports,isValidTime] = idealGTSensor()

[___,numReports,isValidTime,laneDets,numValidLaneDets,isValidLaneTime] = idealGTSensor()

Description

Generate Detections

This syntax applies when you set the TargetReportFormat property to 'Object Detections' and the DetectorOutput property to 'Objects Only'.

[dets,numReports,isValidTime] = idealGTSensor() returns ground truth object detections dets for actors in field of view, number of valid detections reported, numReports, and a logical value isValidTime indicating whether simTime is a valid time for generating detections. If simTime is an integer multiple of the UpdateInterval property value, then isValidTime is 1 (true).

Generate Tracks

This syntax applies when you set the TargetReportFormat property to 'Tracks and the DetectorOutput property to 'Objects Only'..

[tracks,numReports,isValidTime] = idealGTSensor() returns ground truth object tracks tracks for actors in field of view, number of valid tracks reported, numReports, and a logical value isValidTime indicating whether simTime is a valid time for generating detections. If simTime is an integer multiple of the UpdateInterval property value, then isValidTime is 1 (true).

Generate Target Poses

This syntax applies when you set the TargetReportFormat property to 'Target Poses' and the DetectorOutput property to 'Objects Only'.

[poses,numReports,isValidTime] = idealGTSensor() returns ground truth target poses poses for actors in field of view, number of valid poses reported, numReports, and a logical value isValidTime indicating whether simTime is a valid time for generating detections. If simTime is an integer multiple of the UpdateInterval property value, then isValidTime is 1 (true).

Generate Lane Detections Along with Object Detections, Tracks or Target Poses

This syntax applies when you set the DetectorOutput property to 'Objects and Lanes'.

[___,numReports,isValidTime,laneDets,numValidLaneDets,isValidLaneTime] = idealGTSensor() also returns ground truth lane detections laneDets along with object detections, tracks or target poses using any of the previous syntaxes. This syntax also returns the number of valid lane detections reported, numValidLaneDets, and a flag, isValidLaneTime, indicating whether the required simulation time to generate lane detections has elapsed.

Output Arguments

dets — Generated detections

cell array of objectDetection objects

Generated detections, returned as a cell array of objectDetection objects. Each object contains these properties:

Property	Definition
Time	Measurement time
Measurement	Object measurements
MeasurementNoise	Measurement noise covariance matrix
SensorIndex	Unique ID of the sensor
ObjectClassID	Object classification
MeasurementParameters	Parameters used by initialization functions of nonlinear Kalman tracking filters
ObjectAttributes	Additional information passed to tracker

For rectangular coordinates, Measurement and MeasurementNoise are reported in the rectangular coordinate system specified by the DetectionCoordinates property of the idealGroundTruthSensor object.

For spherical coordinates, Measurement and MeasurementNoise are reported in the spherical coordinate system, which is based on the sensor rectangular coordinate system.

Measurement and MeasurementNoise

DetectionCoordinates Value	Measurement and MeasurementNoise Coordinates
'Body'	Coordinate Dependence on HasRangeRate HasRangeRate Coordinates true [x;y;z;vx;vy;vz] false [x;y;z]
'Sensor rectangular'
'Sensor spherical'	Coordinate Dependence on HasRangeRate and HasElevation HasRangeRate HasElevation Coordinates true true [az;el;rng;rr] true false [az;rng;rr] false true [az;el;rng] false false [az;rng]

For ObjectAttributes, this table describes the additional information used for tracking.

ObjectAttributes

Attribute	Definition
TargetIndex	Identifier of the actor, ActorID, that generated the detection. For false alarms, this value is negative.
SNR	Detection signal-to-noise ratio, in dB.

For MeasurementParameters, the measurements are relative to the parent frame. When you set the DetectionCoordinates property to 'Body', the parent frame is the ego vehicle body. When you set DetectionCoordinates to 'Sensor rectangular' or 'Sensor spherical', the parent frame is the sensor.

MeasurementParameters

Parameter	Definition
Frame	Enumerated type indicating the frame used to report measurements. When Frame is set to 'rectangular', detections are reported in rectangular coordinates. When Frame is set to 'spherical', detections are reported in spherical coordinates.
OriginPosition	3-D vector offset of the sensor origin from the parent frame origin.
OriginVelocity	Velocity of the sensor coordinate system with respect to the parent frame.
Orientation	Orientation of the radar sensor coordinate system with respect to the parent frame.
IsParentToChild	Logical scalar indicating if Orientation performs a frame rotation from the parent coordinate frame to the child coordinate frame. When IsParentToChild is false, then Orientation performs a frame rotation from the child coordinate frame to the parent coordinate frame.
HasAzimuth	Indicates whether measurements contain azimuth components.
HasElevation	Indicates whether measurements contain elevation components.
HasRange	Indicates whether measurements contain range components.
HasVelocity	Indicates whether measurements contain velocity or range rate components.

tracks — Generated tracks

cell array of objectTrack objects | structure array

Generated tracks, returned as an objectTrack array in MATLAB^® and a structure array in generated code. In generated code, the field names of the returned structure are same as the property names of the objectTrack object.

poses — Target poses

structure | array of structures

Target poses, in ego vehicle coordinates, returned as a structure or as an array of structures. The pose of the ego vehicle actor is not included.

A target pose defines the position, velocity, and orientation of a target in ego vehicle coordinates. Target poses also include the rates of change in actor position and orientation.

Each pose structure has these fields.

Field	Description
ActorID	Scenario-defined actor identifier, specified as a positive integer.
ClassID	Classification identifier, specified as a nonnegative integer. 0 represents an object of an unknown or unassigned class.
Position	Position of actor, specified as a real-valued vector of the form [x y z]. Units are in meters.
Velocity	Velocity (v) of actor in the x-, y-, and z-directions, specified as a real-valued vector of the form [vx vy vz]. Units are in meters per second.
Roll	Roll angle of actor, specified as a real scalar. Units are in degrees.
Pitch	Pitch angle of actor, specified as a real scalar. Units are in degrees.
Yaw	Yaw angle of actor, specified as a real scalar. Units are in degrees.
AngularVelocity	Angular velocity (ω) of actor in the x-, y-, and z-directions, specified as a real-valued vector of the form [ωx ωy ωz]. Units are in degrees per second.

For full definitions of these structure fields, see the actor and vehicle functions.

numReports — Number of reported detections or tracks

nonnegative integer

Number of reported detections or tracks, returned as a nonnegative integer. numReports is equal to the length of dets when generating detections and tracks when generating tracks.

Data Types: double

isValidTime — Valid time for generating reports

0 | 1

Valid time for generating reports, returned as a logical 0 (false) or 1 (true).

If isValidTime is 0 (false), then the reports returned by dets (for generated detections) or tracks (for generated tracks) are invalid because the sensor generated them at a time that is inconsistent with the sensor update rate.

The sensor generates reports only when the current simulation time is an integer multiple of the time interval at which the sensor generates reports. This time interval is equal to the UpdateInterval property value.

Data Types: logical

laneDets — Lane boundary detections

lane boundary detection structure

Lane boundary detections, returned as an array structures. The fields of the structure are:

Field	Description
Coordinates	Lane boundary coordinates, returned as a real-valued N-by-3 matrix, where N is the number of lane boundary coordinates. Lane boundary coordinates define the position of points on the boundary at returned longitudinal distances away from the ego vehicle, along the center of the road. This matrix also includes the boundary coordinates at zero distance from the ego vehicle. These coordinates are to the left and right of the ego vehicle origin, which is located under the center of the rear axle. Units are in meters.
Curvature	Lane boundary curvature at each row of the Coordinates matrix, returned as a real-valued N-by-1 vector. N is the number of lane boundary coordinates. Units are in radians per meter.
CurvatureDerivative	Derivative of lane boundary curvature at each row of the Coordinates matrix, returned as a real-valued N-by-1 vector. N is the number of lane boundary coordinates. Units are in radians per square meter.
HeadingAngle	Initial lane boundary heading angle, returned as a real scalar. The heading angle of the lane boundary is relative to the ego vehicle heading. Units are in degrees.
LateralOffset	Lateral offset of the ego vehicle position from the lane boundary, returned as a real scalar. An offset to a lane boundary to the left of the ego vehicle is positive. An offset to the right of the ego vehicle is negative. Units are in meters. In this image, the ego vehicle is offset 1.5 meters from the left lane and 2.1 meters from the right lane.
BoundaryType	Type of lane boundary marking, returned as one of these values: 'Unmarked' — No physical lane marker exists 'Solid' — Single unbroken line 'Dashed' — Single line of dashed lane markers 'DoubleSolid' — Two unbroken lines 'DoubleDashed' — Two dashed lines 'SolidDashed' — Solid line on the left and a dashed line on the right 'DashedSolid' — Dashed line on the left and a solid line on the right
Strength	Saturation strength of the lane boundary marking, returned as a real scalar from 0 to 1. A value of 0 corresponds to a marking whose color is fully unsaturated. The marking is gray. A value of 1 corresponds to a marking whose color is fully saturated.
Width	Lane boundary width, returned as a positive real scalar. In a double-line lane marker, the same width is used for both lines and for the space between lines. Units are in meters.
Length	Length of dash in dashed lines, returned as a positive real scalar. In a double-line lane marker, the same length is used for both lines.
Space	Length of space between dashes in dashed lines, returned as a positive real scalar. In a dashed double-line lane marker, the same space is used for both lines.

numValidLaneDets — Number of detections

nonnegative integer

Number of lane detections returned, defined as a nonnegative integer. Maximum number of lane detections returned is based on the value specified in MaxNumLanesReported property.

Data Types: double

isValidLaneTime — Valid lane detection time

0 | 1

Valid lane detection time, returned as 0 or 1. isValidLaneTime is 0 when lane detection updates are requested at times that are between update intervals specified by LaneUpdateInterval.

Data Types: logical

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object named obj, use this syntax:

release(obj)

Specific to idealGroundTruthSensor

isLocked	Determine if System object is in use
clone	Create duplicate System object

Common to All System Objects

step	Run System object algorithm
release	Release resources and allow changes to System object property values and input characteristics
reset	Reset internal states of System object

Examples

Generate Ground Truth Detections and Tracks of Actors in Driving Scenario

Use an ideal ground truth sensor to generate detections and tracks for all driving scenario actors in the specified field of view. You can also use the ideal ground truth sensor to generate ground truth lane detections in the driving scenario.

Create Driving Scenario and Add Ideal Ground Truth Sensor

Create a driving scenario containing a three-lane road and three vehicles.

[scenario,egoVehicle] = helperCreateDrivingScenario;
targetProfiles = actorProfiles(scenario);

Create an ideal ground truth sensor mounted at the front of the ego vehicle and configure it with these options:

1. Output ground truth tracks of objects in its field of view.

2. Output ground truth lane boundaries in field of view.

frontIdealGTSensor = idealGroundTruthSensor(SensorIndex=1,DetectorOutput="Objects and Lanes",SensorLocation=[3.4 0 0.2],...
    PointOnTargetReported="Origin Point",LaneBoundariesReported="All Lanes",TargetOutputFormat="Tracks");

Add a radar sensor at the same location and configure it to show tracks of objects in its field of view.

frontRadar = drivingRadarDataGenerator(SensorIndex=2,UpdateRate=1/scenario.SampleTime,MountingLocation=[3.4 0 0.2], ...
                                   TargetReportFormat="Tracks",Profiles=targetProfiles);

Add a vision sensor at the front roof center of the ego vehicle.

frontVisionSensor = visionDetectionGenerator(SensorIndex=4,UpdateInterval=scenario.SampleTime,SensorLocation=[3.4 0],Height=1.1,Yaw=0, ...
    DetectorOutput="Lanes and objects",ActorProfiles=targetProfiles,MinObjectImageSize=[2 2]);

Create a second ideal ground truth sensor mounted on the left side of the ego vehicle. Add an ultrasonic sensor at the same location.

leftIdealGTSensor = idealGroundTruthSensor(SensorIndex=3,DetectorOutput="Objects Only",SensorLocation=[0.5 1 0.2],Yaw=90, ...
    PointOnTargetReported="Closest Point");

leftUltrasonicSensor = ultrasonicDetectionGenerator(SensorIndex=5,MountingLocation=[0.5 1 0.2],MountingAngles=[90 0 0], ...
    FieldOfView=[70 35],Profiles=targetProfiles);

Add all the sensors to the driving scenario.

sensorSuite = {frontIdealGTSensor,frontRadar,leftIdealGTSensor,frontVisionSensor,leftUltrasonicSensor};
addSensors(scenario,sensorSuite,egoVehicle.ActorID)

Create Bird's-Eye-Plot

bep = helperCreateBEP(sensorSuite);

Run the Simulation. Visualize the ideal gound truth measurements and actual sensor measurement using the created bird's-eye-plot.

while advance(scenario)
    
    % Get target poses
    targets = targetPoses(egoVehicle);
    
    % Ideal ground truth object and lane boundary detections
    [fIdGTTracks,~,fisValidTime,laneDets,numValidLaneDets,isValidLaneTime] = frontIdealGTSensor();
    [lIdGTDets,~,lisValidTime] = leftIdealGTSensor();

    % Radar tracks
    [radarTracks,~,risValidTime] = frontRadar(targets,scenario.SimulationTime);

    % Vision object and lane boundary detections
    [visionDets,~,visValidTime,visionLaneDets,~,isValidVisionLaneTime] = frontVisionSensor(targets,laneDets,scenario.SimulationTime);
    [ulDets,ulisValidTime] = leftUltrasonicSensor(targets,scenario.SimulationTime);
    
    % Plot vehicle outlines and lane markings
    [objposition,objyaw,objlength,objwidth,objoriginOffset,color] = targetOutlines(egoVehicle);
    plotOutline(bep.Plotters(6),objposition,objyaw,objlength,objwidth, ...
        OriginOffset=objoriginOffset,Color=color)

    [lmv,lmf] = laneMarkingVertices(egoVehicle);
    plotLaneMarking(bep.Plotters(7),lmv,lmf)
    
    % Plot ground truth lane boundaries
    if ~isempty(laneDets) && isValidLaneTime
        plotLaneBoundary(bep.Plotters(8),{laneDets.Coordinates})
    end
    
    % Plot ideal ground truth measurements
    if ~isempty(fIdGTTracks) && fisValidTime
        fIdGTDetPos = cell2mat(cellfun(@(t)t.State(1:2:end),fIdGTTracks,UniformOutput=false)')';
        plotTrack(bep.Plotters(9),fIdGTDetPos)
    end  

     if ~isempty(lIdGTDets) && lisValidTime
        lIdGTDetPos = cell2mat(cellfun(@(d)d.Measurement(1:2),lIdGTDets,UniformOutput=false)')';
        plotDetection(bep.Plotters(10),lIdGTDetPos)
    end

    % Plot radar tracks
    if ~isempty(radarTracks) && risValidTime
        trackPos = cell2mat(arrayfun(@(t)t.State(1:2:end),radarTracks,UniformOutput=false)')';
        plotTrack(bep.Plotters(11),trackPos(:,1:2))
    end
    
    % Plot vision object detections and lane boundaries 
    if visValidTime
        visionDetPos = cellfun(@(d)d.Measurement(1:2),visionDets,UniformOutput=false);
        visionDetPos = vertcat(zeros(0,2),cell2mat(visionDetPos')');
        plotDetection(bep.Plotters(12),visionDetPos)
    end

    if isValidVisionLaneTime
        plotLaneBoundary(bep.Plotters(13),vertcat(visionLaneDets.LaneBoundaries))
    end   
    
    % Plot ultrasonic range and point-on-target detections
    if ~isempty(ulDets) && ulisValidTime
        lranges = ulDets{1}.Measurement;
        plotRangeDetection(bep.Plotters(14),lranges,leftUltrasonicSensor.FieldOfView(1),leftUltrasonicSensor.MountingLocation,leftUltrasonicSensor.MountingAngles)
        plotDetection(bep.Plotters(15),ulDets{1}.ObjectAttributes{1}.PointOnTarget(1:2)')
    end
end

Supporting functions

helperCreateDrivingScenario function creates the driving scenario, adds roads and vehicles, and assigns trajectories to all the vehicles.

function [scenario,egovehicle] = helperCreateDrivingScenario
    scenario = drivingScenario;
    roadCenters = [-120 30 0;-60 0 0;0 0 0; 60 0 0; 120 30 0];
    lspc = lanespec(3);
    road(scenario,roadCenters,Lanes=lspc);
    %Create an ego vehicle that travels in the center lane at a velocity of 30 m/s.
    egovehicle = vehicle(scenario,ClassID=1);
    egopath = [1.5 0 0; 60 0 0; 111 25 0];
    egospeed = 30;
    smoothTrajectory(egovehicle,egopath,egospeed);
    % Add a target vehicle that travels ahead of the ego vehicle at 30.5 m/s in the right lane, and changes lanes close to the ego vehicle.
    ftargetcar = vehicle(scenario,ClassID=1);
    ftargetpath = [8 2; 60 -3.2; 120 33];
    ftargetspeed = 30.5;
    smoothTrajectory(ftargetcar,ftargetpath,ftargetspeed);
    % Add a second target vehicle that travels in the left lane at 32m/s.
    ltargetcar = vehicle(scenario,ClassID=1);
    ltargetpath = [-5.0 3.5 0; 60 3.5 0; 111 28.5 0];
    ltargetspeed = 32;
    smoothTrajectory(ltargetcar,ltargetpath,ltargetspeed);
end

helperCreateBEP function creates bird's-eye-plot which you use to visualize sensor data and field-of-view.

function bep = helperCreateBEP(sensorSuite)
    % Create bird's eye plot
    bep = birdsEyePlot(XLim=[-20 20],YLim=[-12 12]);
    
    % Plotters for Coverage areas of two ultrasonic sensors
    fcaPlotter = coverageAreaPlotter(bep,DisplayName="Ideal Ground Truth Sensor FOV",FaceColor="k");
    plotCoverageArea(fcaPlotter,sensorSuite{1}.SensorLocation(1:2), ...
        sensorSuite{1}.MaxRange,sensorSuite{1}.Yaw,sensorSuite{1}.FieldOfView(1));
    
    lcaPlotter = coverageAreaPlotter(bep,FaceColor="k");
    plotCoverageArea(lcaPlotter,sensorSuite{3}.SensorLocation(1:2), ...
        sensorSuite{3}.MaxRange,sensorSuite{3}.Yaw,sensorSuite{3}.FieldOfView(1));

    rcaPlotter = coverageAreaPlotter(bep,DisplayName="Radar Sensor FOV",FaceColor="r");
    plotCoverageArea(rcaPlotter,sensorSuite{2}.MountingLocation(1:2), ...
        sensorSuite{2}.RangeLimits(2),sensorSuite{2}.MountingAngles(1),sensorSuite{2}.FieldOfView(1));

    vcaPlotter = coverageAreaPlotter(bep,DisplayName="Vision Sensor FOV",FaceColor="b");
    plotCoverageArea(vcaPlotter,sensorSuite{4}.SensorLocation(1:2), ...
        sensorSuite{4}.MaxRange,sensorSuite{4}.Yaw,sensorSuite{4}.FieldOfView(1));

    ulcaPlotter = coverageAreaPlotter(bep,DisplayName="Ultrasonic Sensor FOV",FaceColor="g");
    plotCoverageArea(ulcaPlotter,sensorSuite{5}.MountingLocation(1:2), ...
        sensorSuite{5}.DetectionRange(3),sensorSuite{5}.MountingAngles(1),sensorSuite{5}.FieldOfView(1));

    % Plotters for vehicle and target outlines, lane markings
    olPlotter = outlinePlotter(bep);
    lmPlotter = laneMarkingPlotter(bep,DisplayName="Lane markings");
   
    %  Lane boundary ground truth plotter
    lbGTPlotter = laneBoundaryPlotter(bep,'DisplayName','Lane boundary ground truth',LineStyle="-.",Color="y");
    
    % Detection or track plotters for Ideal Ground Truth Sensors
    ftrPlotter = trackPlotter(bep,DisplayName="Ground Truth track position (Closest Point)",MarkerFaceColor="k");
    %fdetPlotter = detectionPlotter(bep,DisplayName="Point-On-Target (Front IDGT)",MarkerFaceColor="r");
    ldetPlotter = detectionPlotter(bep,DisplayName="Ground Truth detection position (Vehicle Origin)",MarkerFaceColor="k");
    
    % Plotter for radar tracks
    tPlotter = trackPlotter(bep,DisplayName="Detected radar tracks",HistoryDepth=20,MarkerFaceColor="m");

    % Plotter for vision dets and lane boundaries
    vdPlotter = detectionPlotter(bep,DisplayName="Vision sensor detections",MarkerFaceColor="cyan");
    lbDetPlotter = laneBoundaryPlotter(bep,DisplayName="Lane boundary detections",LineStyle="-.",Color="r");

    % Plotter for ultrasonic detections and ranges
    ulRngPlotter = rangeDetectionPlotter(bep,DisplayName="Ultrasonic Range detection",LineWidth=2);
    ulDetPlotter = detectionPlotter(bep,DisplayName="Point on Target detected (Ultrasonic)",MarkerFaceColor="b");
end

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• For driving scenario workflows, the idealGroundTruthSensor System object supports standalone deployment using MATLAB Coder™, and also for Simulink^® Real-Time™ targets.

• See System Objects in MATLAB Code Generation (MATLAB Coder).

Version History

Introduced in R2025a