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helperClusterDetections.m
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helperClusterDetections.m
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classdef helperClusterDetections < driving.internal.SimulinkBusUtilities ...
& matlab.system.mixin.CustomIcon
% helperClusterDetections Clusters detections within a small area to a single detection
%
% This is a helper block for example purposes and may be removed or
% modified in the future.
%
% helperClusterDetections clusters all the detections created by a
% single sensor simulation (usually, radarDetectionGenerator) if they
% are within a certain distance, ClusterSize, from each other.
%
% See also: radarDetectionGenerator
% Copyright 2017 The MathWorks, Inc.
%#codegen
properties(Nontunable)
%ClusterSize The distance between detections for clustering
ClusterSize = 4.7;
end
properties(Constant, Access=protected)
pBusPrefix = 'BusClusterDetections'
end
methods
function obj = helperClusterDetections(varargin)
% Constructor
setProperties(obj,nargin,varargin{:});
end
end
methods(Access=protected)
function [out, argsToBus] = defaultOutput(obj)
busIn = propagatedInputBus(obj,1);
if ~isempty(busIn)
out = Simulink.Bus.createMATLABStruct(busIn);
else
out = repmat(struct,0,1);
end
numDets = 0;
isValidTime = 0;
argsToBus = {numDets, isValidTime};
end
% Currently only support simulink environment, so nothing to do
% here
function y = sendToBus(~,x,varargin)
y = x;
end
function detBusOut = stepImpl(obj,detBusIn)
numDetsIn = detBusIn.NumDetections;
detsIn = detBusIn.Detections(1:numDetsIn);
detsClust = localClusterDetections(detsIn, obj.ClusterSize);
numDetsOut = numel(detsClust);
detBusOut = detBusIn;
detBusOut.NumDetections = numDetsOut;
detBusOut.Detections(1:numDetsOut) = detsClust;
end
function loadObjectImpl(obj,s,wasLocked)
% Set properties in object obj to values in structure s
% Set private and protected properties
% obj.myproperty = s.myproperty;
% Set public properties and states
[email protected](obj,s,wasLocked);
end
function s = saveObjectImpl(obj)
% Set properties in structure s to values in object obj
% Set public properties and states
s = [email protected](obj);
% Set private and protected properties
%s.myproperty = obj.myproperty;
end
function dt = getOutputDataTypeImpl(obj)
dt = [email protected](obj);
end
function str = getIconImpl(~)
str = sprintf('Detection\nClustering');
end
function varargout = getInputNamesImpl(~)
varargout = {'In'};
end
function varargout = getOutputNamesImpl(~)
varargout = {sprintf('Out')};
end
end
methods(Static, Access=protected)
function header = getHeaderImpl
% Define header panel for System block dialog
header = matlab.system.display.Header(...
'Title', 'DetectionClustering', ...
'Text', getHeaderText());
end
function groups = getPropertyGroupsImpl
pList = {'ClusterSize'};
pSection = matlab.system.display.Section('PropertyList',pList);
slBusSection = [email protected];
groups = [pSection, slBusSection];
end
end
end
function detectionClusters = localClusterDetections(detections, vehicleSize)
N = numel(detections);
if N < 1
detectionClusters = detections;
return
end
distances = zeros(N);
for i = 1:N
for j = i+1:N
if detections(i).SensorIndex == detections(j).SensorIndex
distances(i,j) = norm(detections(i).Measurement(1:2) - detections(j).Measurement(1:2));
else
distances(i,j) = inf;
end
end
end
leftToCheck = 1:N;
i = 0;
detectionClusters = detections;
while ~isempty(leftToCheck)
% Remove the detections that are in the same cluster as the one under
% consideration
underConsideration = leftToCheck(1);
clusterInds = (distances(underConsideration, leftToCheck) < vehicleSize);
detInds = leftToCheck(clusterInds);
ind = detInds(1);
clusterMeas = detections(ind).Measurement;
for m = 2:numel(detInds)
ind = detInds(m);
clusterMeas = clusterMeas + detections(ind).Measurement;
end
meas = clusterMeas/numel(detInds);
i = i + 1;
detectionClusters(i) = detections(detInds(1));
detectionClusters(i).Measurement = meas;
leftToCheck(clusterInds) = [];
end
detectionClusters(i+1:end) = [];
% Since the detections are now for clusters, modify the noise to represent
% that they are of the whole car
for i = 1:numel(detectionClusters)
measNoise = detectionClusters(i).MeasurementNoise;
measNoise(1:2,1:2) = vehicleSize^2 * measNoise(1:2,1:2);
measNoise(4:5,4:5) = vehicleSize^2 * 100 * measNoise(4:5,4:5);
detectionClusters(i).MeasurementNoise = measNoise;
end
end
function str = getHeaderText
str = sprintf([...
'The Detections Clustering block clusters all the detections generated by a ',...
'sensor detection generator(usually, radarDetectionGenerator) if the ',...
'detections are within a certain distance, ClusterSize, from each other.\n\n',...
'The detection generator must use ''Ego Cartesian'' coordinates for ',...
'this block to work.']);
end