Mercurial Hosting > traffic-intelligence
changeset 887:e2452abba0e7
added option to compute PET in safety analysis script, and save in database
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Wed, 22 Mar 2017 10:44:24 -0400 |
| parents | d2eb8c93f7de |
| children | 40994bb43148 |
| files | python/events.py python/moving.py python/tests/moving.txt scripts/safety-analysis.py |
| diffstat | 4 files changed, 31 insertions(+), 17 deletions(-) [+] |
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--- a/python/events.py Tue Mar 21 17:51:38 2017 -0400 +++ b/python/events.py Wed Mar 22 10:44:24 2017 -0400 @@ -165,9 +165,15 @@ self.roadUser1.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs) self.roadUser2.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs) - def play(self, videoFilename, homography = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1.): + def play(self, videoFilename, homography = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1., allUserInstants = False): if self.roadUser1 is not None and self.roadUser2 is not None: - cvutils.displayTrajectories(videoFilename, [self.roadUser1, self.roadUser2], homography = homography, firstFrameNum = self.getFirstInstant(), lastFrameNumArg = self.getLastInstant(), undistort = undistort, intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication) + if allUserInstants: + firstFrameNum = min(self.roadUser1.getFirstInstant(), self.roadUser2.getFirstInstant()) + lastFrameNum = max(self.roadUser1.getLastInstant(), self.roadUser2.getLastInstant()) + else: + firstFrameNum = self.getFirstInstant() + lastFrameNum = self.getLastInstant() + cvutils.displayTrajectories(videoFilename, [self.roadUser1, self.roadUser2], homography = homography, firstFrameNum = firstFrameNum, lastFrameNumArg = lastFrameNum, undistort = undistort, intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication) else: print('Please set the interaction road user attributes roadUser1 and roadUser1 through the method setRoadUsers') @@ -237,10 +243,9 @@ # TODO add probability of collision, and probability of successful evasive action def computePET(self, collisionDistanceThreshold): - # TODO add crossing zone - pet = moving.MovingObject.computePET(self.roadUser1, self.roadUser2, collisionDistanceThreshold) - if pet is not None: # TODO get crossing zone and time - self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[10], {0: pet}, mostSevereIsMax = False)) + pet, t1, t2= moving.MovingObject.computePET(self.roadUser1, self.roadUser2, collisionDistanceThreshold) + if pet is not None: + self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[10], {min(t1, t2): pet}, mostSevereIsMax = False)) def setCollision(self, collision): '''indicates if it is a collision: argument should be boolean'''
--- a/python/moving.py Tue Mar 21 17:51:38 2017 -0400 +++ b/python/moving.py Wed Mar 22 10:44:24 2017 -0400 @@ -5,7 +5,7 @@ from base import VideoFilenameAddable from math import sqrt, atan2, cos, sin -from numpy import median, array, zeros, hypot, NaN, std, floor, float32 +from numpy import median, array, zeros, hypot, NaN, std, floor, float32, argwhere from matplotlib.pyplot import plot, text from scipy.stats import scoreatpercentile from scipy.spatial.distance import cdist @@ -1426,19 +1426,25 @@ def computePET(obj1, obj2, collisionDistanceThreshold): '''Post-encroachment time based on distance threshold - Returns the smallest time difference when the object positions are within collisionDistanceThreshold''' + Returns the smallest time difference when the object positions are within collisionDistanceThreshold + and the instants at which each object is passing through its corresponding position''' positions1 = [p.astuple() for p in obj1.getPositions()] positions2 = [p.astuple() for p in obj2.getPositions()] - pets = zeros((int(obj1.length()), int(obj2.length()))) + n1 = len(positions1) + n2 = len(positions2) + pets = zeros((n1, n2)) for i,t1 in enumerate(obj1.getTimeInterval()): for j,t2 in enumerate(obj2.getTimeInterval()): pets[i,j] = abs(t1-t2) distances = cdist(positions1, positions2, metric = 'euclidean') - if distances.min() <= collisionDistanceThreshold: - #idx = distances.argmin() - return pets[distances <= collisionDistanceThreshold].min() + smallDistances = (distances <= collisionDistanceThreshold) + if smallDistances.any(): + smallPets = pets[smallDistances] + petIdx = smallPets.argmin() + distanceIndices = argwhere(smallDistances)[petIdx] + return smallPets[petIdx], obj1.getFirstInstant()+distanceIndices[0], obj2.getFirstInstant()+distanceIndices[1] else: - return None + return None, None, None def predictPosition(self, instant, nTimeSteps, externalAcceleration = Point(0,0)): '''Predicts the position of object at instant+deltaT,
--- a/python/tests/moving.txt Tue Mar 21 17:51:38 2017 -0400 +++ b/python/tests/moving.txt Wed Mar 22 10:44:24 2017 -0400 @@ -174,10 +174,13 @@ >>> o1 = MovingObject.generate(Point(-5.,0.), Point(1.,0.), TimeInterval(0,10)) >>> o2 = MovingObject.generate(Point(0.,-5.), Point(0.,1.), TimeInterval(0,10)) >>> MovingObject.computePET(o1, o2, 0.1) -0.0 +(0.0, 5, 5) >>> o2 = MovingObject.generate(Point(0.,-5.), Point(0.,1.), TimeInterval(5,15)) >>> MovingObject.computePET(o1, o2, 0.1) -5.0 +(5.0, 5, 10) +>>> o2 = MovingObject.generate(Point(0.,-5.), Point(0.,1.), TimeInterval(15,30)) +>>> MovingObject.computePET(o1, o2, 0.1) +(15.0, 5, 20) >>> t = CurvilinearTrajectory(S = [1., 2., 3., 5.], Y = [0.5, 0.5, 0.6, 0.7], lanes = ['1']*4) >>> t.differentiate() # doctest:+ELLIPSIS
--- a/scripts/safety-analysis.py Tue Mar 21 17:51:38 2017 -0400 +++ b/scripts/safety-analysis.py Wed Mar 22 10:44:24 2017 -0400 @@ -68,8 +68,8 @@ inter.computeCrossingsCollisions(predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, nProcesses = args.nProcesses) if args.computePET: - for inter in Interactions: - inter.computePET() + for inter in interactions: + inter.computePET(params.collisionDistance) storage.saveIndicators(params.databaseFilename, interactions)