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Faraz cav challenge #22

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dd270f3
finished CAV challenge by changing road curvature and drive scenario
farazali7 Nov 22, 2018
7b4ba52
submission of completed cav challenge
farazali7 Nov 29, 2018
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Binary file added CAV Challenge - Faraz Ali.mat
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265 changes: 265 additions & 0 deletions CAVChallenge_FarazAli2.m
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Original file line number Diff line number Diff line change
@@ -0,0 +1,265 @@
function [allData, scenario, sensors] = CAVChallenge_FarazAli2()
%CAVChallenge_FarazAli - Returns sensor detections
% allData = CAVChallenge_FarazAli returns sensor detections in a structure
% with time for an internally defined scenario and sensor suite.
%
% [allData, scenario, sensors] = CAVChallenge_FarazAli optionally returns
% the drivingScenario and detection generator objects.

% Generated by MATLAB(R) 9.5 and Automated Driving System Toolbox 1.3.
% Generated on: 28-Nov-2018 19:52:00

% Create the drivingScenario object and ego car
[scenario, egoCar] = createDrivingScenario;

% Create all the sensors
[sensors, numSensors] = createSensors(scenario);

allData = struct('Time', {}, 'ActorPoses', {}, 'ObjectDetections', {}, 'LaneDetections', {});
running = true;
while running

% Generate the target poses of all actors relative to the ego car
poses = targetPoses(egoCar);
time = scenario.SimulationTime;

objectDetections = {};
laneDetections = [];
isValidTime = false(1, numSensors);

% Generate detections for each sensor
for sensorIndex = 1:numSensors
[objectDets, numObjects, isValidTime(sensorIndex)] = sensors{sensorIndex}(poses, time);
objectDetections = [objectDetections; objectDets(1:numObjects)]; %#ok<AGROW>
end

% Aggregate all detections into a structure for later use
if any(isValidTime)
allData(end + 1) = struct( ...
'Time', scenario.SimulationTime, ...
'ActorPoses', actorPoses(scenario), ...
'ObjectDetections', {objectDetections}, ...
'LaneDetections', {laneDetections}); %#ok<AGROW>
end

% Advance the scenario one time step and exit the loop if the scenario is complete
running = advance(scenario);
end

% Restart the driving scenario to return the actors to their initial positions.
restart(scenario);

% Release all the sensor objects so they can be used again.
for sensorIndex = 1:numSensors
release(sensors{sensorIndex});
end

%%%%%%%%%%%%%%%%%%%%
% Helper functions %
%%%%%%%%%%%%%%%%%%%%

% Units used in createSensors and createDrivingScenario
% Distance/Position - meters
% Speed - meters/second
% Angles - degrees
% RCS Pattern - dBsm

function [sensors, numSensors] = createSensors(scenario)
% createSensors Returns all sensor objects to generate detections

% Assign into each sensor the physical and radar profiles for all actors
profiles = actorProfiles(scenario);
sensors{1} = visionDetectionGenerator('SensorIndex', 1, ...
'SensorLocation', [1.9 0], ...
'DetectorOutput', 'Objects only', ...
'ActorProfiles', profiles);
sensors{2} = radarDetectionGenerator('SensorIndex', 2, ...
'SensorLocation', [2.8 -0.9], ...
'Yaw', -41.7689900996318, ...
'MaxRange', 50, ...
'FieldOfView', [90 5], ...
'ActorProfiles', profiles);
sensors{3} = visionDetectionGenerator('SensorIndex', 3, ...
'SensorLocation', [0 0], ...
'Yaw', -180, ...
'DetectorOutput', 'Objects only', ...
'ActorProfiles', profiles);
sensors{4} = radarDetectionGenerator('SensorIndex', 4, ...
'SensorLocation', [2.8 0.9], ...
'Yaw', 42.0390638658363, ...
'MaxRange', 50, ...
'FieldOfView', [90 5], ...
'ActorProfiles', profiles);
sensors{5} = radarDetectionGenerator('SensorIndex', 5, ...
'SensorLocation', [1.9 0], ...
'Yaw', 93.9301755457255, ...
'ActorProfiles', profiles);
sensors{6} = radarDetectionGenerator('SensorIndex', 6, ...
'SensorLocation', [1.9 0], ...
'Yaw', -92.3970285300596, ...
'ActorProfiles', profiles);
sensors{7} = radarDetectionGenerator('SensorIndex', 7, ...
'SensorLocation', [0 0.9], ...
'Yaw', 131.771352130364, ...
'MaxRange', 25, ...
'FieldOfView', [90 5], ...
'ActorProfiles', profiles);
sensors{8} = radarDetectionGenerator('SensorIndex', 8, ...
'SensorLocation', [0 -0.9], ...
'Yaw', -128.168994050648, ...
'MaxRange', 25, ...
'FieldOfView', [90 5], ...
'ActorProfiles', profiles);
numSensors = 8;

function [scenario, egoCar] = createDrivingScenario
% createDrivingScenario Returns the drivingScenario defined in the Designer

% Construct a drivingScenario object.
scenario = drivingScenario;

% Add all road segments
roadCenters = [-7.50000000000001 -18.8 0;
12.4 0.2 0;
29.3 2.9 0;
42.4 10.5 0;
54.1 17.1 0;
74.4 25.6 0;
91.2 32 0;
135.4 20.9 0;
142.2 -32 0;
105.2 -98 0;
71.3 -130.8 0;
8.3 -123.1 0;
-19.1 -79.5 0;
-7.50000000000001 -18.8 0];
marking = [laneMarking('Solid', 'Color', [0.98 0.86 0.36])
laneMarking('DoubleSolid', 'Color', [0.98 0.86 0.36])
laneMarking('Dashed')
laneMarking('Solid')];
laneSpecification = lanespec(3, 'Width', [4.425 4.425 3.6], 'Marking', marking);
road(scenario, roadCenters, 'Lanes', laneSpecification);

roadCenters = [133 -46.5 0;
95.7 -58.7 0;
66 -75.4 0;
54.9 -88.5 0];
road(scenario, roadCenters);

roadCenters = [11.9 -71 0;
29.2 -1.3 0];
road(scenario, roadCenters);

% Add the ego car
egoCar = vehicle(scenario, ...
'ClassID', 1, ...
'Position', [-1.1 -11.7 0]);
waypoints = [-1.1 -11.7 0;
2.6 -6.3 0;
7.2 -2.7 0;
12.9 -0.300000000000001 0;
19.4 1 0;
25 1.6 0;
30.5 2.5 0;
35.1 5 0;
40.1 8.5 0;
45.6 12.3 0;
47.5 13.8 0;
54 17 0;
66.2 22.1 0;
79.4 27.4 0;
92.6 32.4 0;
107.2 33.5 0;
121.5 31.3 0;
127.9 27.1 0;
134.3 22.8 0;
137.9 16.7 0;
142.5 7.1 0;
144.4 0.8 0;
145.3 -11 0;
140.8 -17.9 0;
139.2 -25.9 0;
136.3 -34.5 0;
133.4 -43.2 0;
130.4 -47.7 0;
124.6 -48.9 0;
115.2 -52 0;
103.3 -56.3 0;
90.2 -61 0;
87.1 -62.9 0;
78.9 -66.3 0;
61.8 -80.4 0;
55.4 -87.5 0];
speed = [60;60;60;60;60;60;60;60;60;60;60;60;60;60;60;60;60;60;80;80;80;80;80;80;60;60;60;60;60;60;60;60;60;60;60;60];
trajectory(egoCar, waypoints, speed);

% Add the non-ego actors
car1 = vehicle(scenario, ...
'ClassID', 1, ...
'Position', [50.5 19.5 0]);
waypoints = [50.5 19.5 0;
41 14.3 0;
36.5 11 0;
30.1 7.7 0;
23.2 5.6 0;
15.3 4.3 0;
8.2 2.8 0;
2.2 -0.9 0;
-1.2 -4.4 0;
-10.2 -15.4 0;
-16.9 -25.6 0;
-19.1 -33.6 0;
-24 -47.3 0;
-24.9 -70.8 0;
-21.8 -87.6 0;
-13.4 -106.2 0;
-1 -120 0;
8.8 -128.8 0;
19.7 -133.7 0;
43.2 -141 0;
54.1 -141 0;
67.3 -136.9 0;
85.4 -126.4 0;
92 -121.2 0;
122.1 -82.7 0;
141.6 -48.6 0;
143 -44.8 0];
speed = 40;
trajectory(car1, waypoints, speed);

truck = vehicle(scenario, ...
'ClassID', 2, ...
'Length', 8.2, ...
'Width', 2.5, ...
'Height', 3.5, ...
'Position', [17.7 -47.4 0]);
waypoints = [17.7 -47.4 0;
24.5 -19.3 0;
27.2 -9.5 0;
30 -1.8 0;
35.4 0.9 0;
39.9 3.3 0;
46.6 7.8 0;
56.2 12.6 0;
70.2 19 0;
84.7 25.3 0;
97.3 28.4 0;
108.7 28.8 0;
121.6 25.4 0;
127.1 22.4 0;
133.8 15.3 0;
137.8 9.2 0;
140.7 -0.9 0;
141.3 -10.7 0;
140.7 -16.1 0;
139.2 -23.8 0;
137.4 -30.3 0;
132.7 -44.1 0;
129.9 -49 0;
127.5 -56.3 0;
116.6 -73.1 0;
109.9 -84 0;
102.3 -93.8 0];
speed = 60;
trajectory(truck, waypoints, speed);

68 changes: 3 additions & 65 deletions SensorFusionUsingSyntheticRadarandVisionDataWorkshop.m
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% Define an empty scenario.
scenario = drivingScenario;
scenario.SampleTime = 0.01;

roadCenters = [0 0; 50 0; 100 0; 250 20; 500 40];
road(scenario, roadCenters, 'lanes',lanespec(2));

% Create the ego vehicle that travels at 25 m/s along the road. Place the
% vehicle on the right lane by subtracting off half a lane width (1.8 m)
% from the centerline of the road.
egoCar = vehicle(scenario, 'ClassID', 1);
path(egoCar, roadCenters(2:end,:) - [0 1.8], 25); % On right lane

% Add a car in front of the ego vehicle
leadCar = vehicle(scenario, 'ClassID', 1);
path(leadCar, [70 0; roadCenters(3:end,:)] - [0 1.8], 25); % On right lane

% Add a car that travels at 35 m/s along the road and passes the ego vehicle
passingCar = vehicle(scenario, 'ClassID', 1);
waypoints = [0 -1.8; 50 1.8; 100 1.8; 250 21.8; 400 32.2; 500 38.2];
path(passingCar, waypoints, 35);

% Add a car behind the ego vehicle
chaseCar = vehicle(scenario, 'ClassID', 1);
path(chaseCar, [25 0; roadCenters(1:end,:)] - [0 1.8], 25); % On right lane

sensors = cell(8,1);
% Front-facing long-range radar sensor at the center of the front bumper of the car.
sensors{1} = radarDetectionGenerator('SensorIndex', 1, 'Height', 0.2, 'MaxRange', 174, ...
'SensorLocation', [egoCar.Wheelbase + egoCar.FrontOverhang, 0], 'FieldOfView', [20, 5]);

% Rear-facing long-range radar sensor at the center of the rear bumper of the car.
sensors{2} = radarDetectionGenerator('SensorIndex', 2, 'Height', 0.2, 'Yaw', 180, ...
'SensorLocation', [-egoCar.RearOverhang, 0], 'MaxRange', 174, 'FieldOfView', [20, 5]);

% Rear-left-facing short-range radar sensor at the left rear wheel well of the car.
sensors{3} = radarDetectionGenerator('SensorIndex', 3, 'Height', 0.2, 'Yaw', 120, ...
'SensorLocation', [0, egoCar.Width/2], 'MaxRange', 30, 'ReferenceRange', 50, ...
'FieldOfView', [90, 5], 'AzimuthResolution', 10, 'RangeResolution', 1.25);

% Rear-right-facing short-range radar sensor at the right rear wheel well of the car.
sensors{4} = radarDetectionGenerator('SensorIndex', 4, 'Height', 0.2, 'Yaw', -120, ...
'SensorLocation', [0, -egoCar.Width/2], 'MaxRange', 30, 'ReferenceRange', 50, ...
'FieldOfView', [90, 5], 'AzimuthResolution', 10, 'RangeResolution', 1.25);

% Front-left-facing short-range radar sensor at the left front wheel well of the car.
sensors{5} = radarDetectionGenerator('SensorIndex', 5, 'Height', 0.2, 'Yaw', 60, ...
'SensorLocation', [egoCar.Wheelbase, egoCar.Width/2], 'MaxRange', 30, ...
'ReferenceRange', 50, 'FieldOfView', [90, 5], 'AzimuthResolution', 10, ...
'RangeResolution', 1.25);

% Front-right-facing short-range radar sensor at the right front wheel well of the car.
sensors{6} = radarDetectionGenerator('SensorIndex', 6, 'Height', 0.2, 'Yaw', -60, ...
'SensorLocation', [egoCar.Wheelbase, -egoCar.Width/2], 'MaxRange', 30, ...
'ReferenceRange', 50, 'FieldOfView', [90, 5], 'AzimuthResolution', 10, ...
'RangeResolution', 1.25);

% Front-facing camera located at front windshield.
sensors{7} = visionDetectionGenerator('SensorIndex', 7, 'FalsePositivesPerImage', 0.1, ...
'SensorLocation', [0.75*egoCar.Wheelbase 0], 'Height', 1.1);

% Rear-facing camera located at rear windshield.
sensors{8} = visionDetectionGenerator('SensorIndex', 8, 'FalsePositivesPerImage', 0.1, ...
'SensorLocation', [0.2*egoCar.Wheelbase 0], 'Height', 1.1, 'Yaw', 180);
[allData, scenario, sensors] = CAVChallenge_FarazAli2();
egoCar = scenario.Actors(1);

% Initiate the tracker
tracker = multiObjectTracker('FilterInitializationFcn', @initSimDemoFilter, ...
Expand All @@ -79,7 +17,7 @@

% Get the position of the other vehicle in ego vehicle coordinates
ta = targetPoses(egoCar);

% Simulate the sensors
detections = {};
isValidTime = false(1,8);
Expand Down