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preprocess_data.m
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preprocess_data.m
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%% Process dataset into mat files %%
clear;
clc;
%% Inputs:
% Locations of raw input files:
us101_1 = 'raw/us101-0750-0805.txt';
us101_2 = 'raw/us101-0805-0820.txt';
us101_3 = 'raw/us101-0820-0835.txt';
i80_1 = 'raw/i80-1600-1615.txt';
i80_2 = 'raw/i80-1700-1715.txt';
i80_3 = 'raw/i80-1715-1730.txt';
%% Fields:
%{
1: Dataset Id
2: Vehicle Id
3: Frame Number
4: Local X
5: Local Y
6: Lane Id
7: Lateral maneuver
8: Longitudinal maneuver
9-47: Neighbor Car Ids at grid location
%}
%% Load data and add dataset id
disp('Loading data...')
traj{1} = load(us101_1);
traj{1} = single([ones(size(traj{1},1),1),traj{1}]);
traj{2} = load(us101_2);
traj{2} = single([2*ones(size(traj{2},1),1),traj{2}]);
traj{3} = load(us101_3);
traj{3} = single([3*ones(size(traj{3},1),1),traj{3}]);
traj{4} = load(i80_1);
traj{4} = single([4*ones(size(traj{4},1),1),traj{4}]);
traj{5} = load(i80_2);
traj{5} = single([5*ones(size(traj{5},1),1),traj{5}]);
traj{6} = load(i80_3);
traj{6} = single([6*ones(size(traj{6},1),1),traj{6}]);
for k = 1:6
traj{k} = traj{k}(:,[1,2,3,6,7,15]);
if k <=3
traj{k}(traj{k}(:,6)>=6,6) = 6;
end
end
vehTrajs{1} = containers.Map;
vehTrajs{2} = containers.Map;
vehTrajs{3} = containers.Map;
vehTrajs{4} = containers.Map;
vehTrajs{5} = containers.Map;
vehTrajs{6} = containers.Map;
vehTimes{1} = containers.Map;
vehTimes{2} = containers.Map;
vehTimes{3} = containers.Map;
vehTimes{4} = containers.Map;
vehTimes{5} = containers.Map;
vehTimes{6} = containers.Map;
%% Parse fields (listed above):
disp('Parsing fields...')
for ii = 1:6
vehIds = unique(traj{ii}(:,2));
for v = 1:length(vehIds)
vehTrajs{ii}(int2str(vehIds(v))) = traj{ii}(traj{ii}(:,2) == vehIds(v),:);
end
timeFrames = unique(traj{ii}(:,3));
for v = 1:length(timeFrames)
vehTimes{ii}(int2str(timeFrames(v))) = traj{ii}(traj{ii}(:,3) == timeFrames(v),:);
end
for k = 1:length(traj{ii}(:,1))
time = traj{ii}(k,3);
dsId = traj{ii}(k,1);
vehId = traj{ii}(k,2);
vehtraj = vehTrajs{ii}(int2str(vehId));
ind = find(vehtraj(:,3)==time);
ind = ind(1);
lane = traj{ii}(k,6);
% Get lateral maneuver:
ub = min(size(vehtraj,1),ind+40);
lb = max(1, ind-40);
if vehtraj(ub,6)>vehtraj(ind,6) || vehtraj(ind,6)>vehtraj(lb,6)
traj{ii}(k,7) = 3;
elseif vehtraj(ub,6)<vehtraj(ind,6) || vehtraj(ind,6)<vehtraj(lb,6)
traj{ii}(k,7) = 2;
else
traj{ii}(k,7) = 1;
end
% Get longitudinal maneuver:
ub = min(size(vehtraj,1),ind+50);
lb = max(1, ind-30);
if ub==ind || lb ==ind
traj{ii}(k,8) =1;
else
vHist = (vehtraj(ind,5)-vehtraj(lb,5))/(ind-lb);
vFut = (vehtraj(ub,5)-vehtraj(ind,5))/(ub-ind);
if vFut/vHist <0.8
traj{ii}(k,8) =2;
else
traj{ii}(k,8) =1;
end
end
% Get grid locations:
t = vehTimes{ii}(int2str(time));
frameEgo = t(t(:,6) == lane,:);
frameL = t(t(:,6) == lane-1,:);
frameR = t(t(:,6) == lane+1,:);
if ~isempty(frameL)
for l = 1:size(frameL,1)
y = frameL(l,5)-traj{ii}(k,5);
if abs(y) <90
gridInd = 1+round((y+90)/15);
traj{ii}(k,8+gridInd) = frameL(l,2);
end
end
end
for l = 1:size(frameEgo,1)
y = frameEgo(l,5)-traj{ii}(k,5);
if abs(y) <90 && y~=0
gridInd = 14+round((y+90)/15);
traj{ii}(k,8+gridInd) = frameEgo(l,2);
end
end
if ~isempty(frameR)
for l = 1:size(frameR,1)
y = frameR(l,5)-traj{ii}(k,5);
if abs(y) <90
gridInd = 27+round((y+90)/15);
traj{ii}(k,8+gridInd) = frameR(l,2);
end
end
end
end
end
%% Split train, validation, test
disp('Splitting into train, validation and test sets...')
trajAll = [traj{1};traj{2};traj{3};traj{4};traj{5};traj{6}];
clear traj;
trajTr = [];
trajVal = [];
trajTs = [];
for k = 1:6
ul1 = round(0.7*max(trajAll(trajAll(:,1)==k,2)));
ul2 = round(0.8*max(trajAll(trajAll(:,1)==k,2)));
trajTr = [trajTr;trajAll(trajAll(:,1)==k & trajAll(:,2)<=ul1, :)];
trajVal = [trajVal;trajAll(trajAll(:,1)==k & trajAll(:,2)>ul1 & trajAll(:,2)<=ul2, :)];
trajTs = [trajTs;trajAll(trajAll(:,1)==k & trajAll(:,2)>ul2, :)];
end
tracksTr = {};
for k = 1:6
trajSet = trajTr(trajTr(:,1)==k,:);
carIds = unique(trajSet(:,2));
for l = 1:length(carIds)
vehtrack = trajSet(trajSet(:,2) ==carIds(l),3:5)';
tracksTr{k,carIds(l)} = vehtrack;
end
end
tracksVal = {};
for k = 1:6
trajSet = trajVal(trajVal(:,1)==k,:);
carIds = unique(trajSet(:,2));
for l = 1:length(carIds)
vehtrack = trajSet(trajSet(:,2) ==carIds(l),3:5)';
tracksVal{k,carIds(l)} = vehtrack;
end
end
tracksTs = {};
for k = 1:6
trajSet = trajTs(trajTs(:,1)==k,:);
carIds = unique(trajSet(:,2));
for l = 1:length(carIds)
vehtrack = trajSet(trajSet(:,2) ==carIds(l),3:5)';
tracksTs{k,carIds(l)} = vehtrack;
end
end
%% Filter edge cases:
% Since the model uses 3 sec of trajectory history for prediction, the initial 3 seconds of each trajectory is not used for training/testing
disp('Filtering edge cases...')
indsTr = zeros(size(trajTr,1),1);
for k = 1: size(trajTr,1)
t = trajTr(k,3);
if tracksTr{trajTr(k,1),trajTr(k,2)}(1,31) <= t && tracksTr{trajTr(k,1),trajTr(k,2)}(1,end)>t+1
indsTr(k) = 1;
end
end
trajTr = trajTr(find(indsTr),:);
indsVal = zeros(size(trajVal,1),1);
for k = 1: size(trajVal,1)
t = trajVal(k,3);
if tracksVal{trajVal(k,1),trajVal(k,2)}(1,31) <= t && tracksVal{trajVal(k,1),trajVal(k,2)}(1,end)>t+1
indsVal(k) = 1;
end
end
trajVal = trajVal(find(indsVal),:);
indsTs = zeros(size(trajTs,1),1);
for k = 1: size(trajTs,1)
t = trajTs(k,3);
if tracksTs{trajTs(k,1),trajTs(k,2)}(1,31) <= t && tracksTs{trajTs(k,1),trajTs(k,2)}(1,end)>t+1
indsTs(k) = 1;
end
end
trajTs = trajTs(find(indsTs),:);
%% Save mat files:
disp('Saving mat files...')
traj = trajTr;
tracks = tracksTr;
save('TrainSet','traj','tracks');
traj = trajVal;
tracks = tracksVal;
save('ValSet','traj','tracks');
traj = trajTs;
tracks = tracksTs;
save('TestSet','traj','tracks');