Mercurial Hosting > traffic-intelligence
changeset 1148:eb88d2984637
corrected interaction classification
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Tue, 12 May 2020 01:16:54 -0400 |
parents | 8c0ec7e1eb8e |
children | 392db62ea1da |
files | trafficintelligence/events.py trafficintelligence/tests/events.txt |
diffstat | 2 files changed, 46 insertions(+), 7 deletions(-) [+] |
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--- a/trafficintelligence/events.py Wed May 06 00:58:21 2020 -0400 +++ b/trafficintelligence/events.py Tue May 12 01:16:54 2020 -0400 @@ -221,10 +221,13 @@ def categorize(self, velocityAngleTolerance, parallelAngleTolerance): '''Computes the interaction category by instant - velocityAngleTolerance and parallelAngleTolerance in radian''' + velocityAngleTolerance and parallelAngleTolerance in radian + velocityAngleTolerance: indicates the angle threshold for rear and head on (180-velocityAngleTolerance), as well as the maximum collision course angle for head on + velocityAngleTolerance: indicates the angle between velocity vector (average for parallel) and position vector''' parallelAngleToleranceCosine = np.cos(parallelAngleTolerance) self.categories = {} collisionCourseDotProducts = self.getIndicator(Interaction.indicatorNames[0]) + collisionCourseAngles = self.getIndicator(Interaction.indicatorNames[1]) velocityAngles = self.getIndicator(Interaction.indicatorNames[4]) for instant in self.timeInterval: if velocityAngles[instant] < velocityAngleTolerance: # parallel or rear end @@ -234,12 +237,10 @@ self.categories[instant] = Interaction.categories["parallel"] else: self.categories[instant] = Interaction.categories["rearend"] - elif velocityAngles[instant] > np.pi - velocityAngleTolerance: # head on - if collisionCourseDotProducts[instant] > 0: - self.categories[instant] = Interaction.categories["headon"] - else: - if collisionCourseDotProducts[instant] > 0: - self.categories[instant] = Interaction.categories["side"] + elif velocityAngles[instant] > np.pi - velocityAngleTolerance and collisionCourseAngles[instant] < velocityAngleTolerance: # head on + self.categories[instant] = Interaction.categories["headon"] + elif collisionCourseDotProducts[instant] > 0: + self.categories[instant] = Interaction.categories["side"] def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None): '''Computes all crossing and collision points at each common instant for two road users. '''
--- a/trafficintelligence/tests/events.txt Wed May 06 00:58:21 2020 -0400 +++ b/trafficintelligence/tests/events.txt Tue May 12 01:16:54 2020 -0400 @@ -32,3 +32,41 @@ True >>> inter.getIndicator(Interaction.indicatorNames[1])[6] # doctest:+ELLIPSIS 3.1415... + +>>> from collections import Counter +>>> from numpy import pi +>>> o1 = MovingObject.generate(0, Point(0,0), Point(1,0), TimeInterval(0,100)) +>>> o2 = MovingObject.generate(0, Point(100,1), Point(-1,0), TimeInterval(0,100)) +>>> inter12 = Interaction(roadUser1 = o1, roadUser2 = o2) +>>> inter12.computeIndicators() +>>> inter12.categorize(pi*20/180, pi*60/180) +>>> Counter(inter12.categories.values()).most_common()[0][0] # head on +0 +>>> inter12.categories[max(inter12.categories.keys())] # then side +2 +>>> o3 = MovingObject.generate(0, Point(0,2), Point(1,0), TimeInterval(0,100)) +>>> inter13 = Interaction(roadUser1 = o1, roadUser2 = o3) +>>> inter13.computeIndicators() +>>> inter13.categorize(pi*20/180, pi*60/180) +>>> Counter(inter13.categories.values()).most_common()[0][0] # parallel +3 +>>> len(Counter(inter13.categories.values())) +1 +>>> o4 = MovingObject.generate(0, Point(100,20), Point(-1,0), TimeInterval(0,100)) +>>> inter14 = Interaction(roadUser1 = o1, roadUser2 = o4) +>>> inter14.computeIndicators() +>>> inter14.categorize(pi*20/180, pi*60/180) +>>> Counter(inter14.categories.values()).most_common()[0][0] # side +2 +>>> inter12.categories[0] # first head one +0 +>>> inter12.categories[max(inter12.categories.keys())] # then side +2 +>>> o5 = MovingObject.generate(0, Point(50,50), Point(0,-1), TimeInterval(0,100)) +>>> inter15 = Interaction(roadUser1 = o1, roadUser2 = o5) +>>> inter15.computeIndicators() +>>> inter15.categorize(pi*20/180, pi*60/180) +>>> Counter(inter15.categories.values()).most_common()[0][0] # side +2 +>>> len(Counter(inter15.categories.values())) +1