Mercurial > hg > nsaunier > traffic-intelligence

comparison python/events.py @ 607:84690dfe5560

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add some functions for behaviour analysis
author MohamedGomaa
date Tue, 25 Nov 2014 22:49:47 -0500
parents 07b1bd0785cd
children 0dc36203973d
comparison
equal deleted inserted replaced
606:75ad9c0d6cc3 607:84690dfe5560
6 from numpy import arccos 6 from numpy import arccos
7 7
8 import multiprocessing 8 import multiprocessing
9 import itertools 9 import itertools
10 10
11 import sys
11 import moving, prediction, indicators, utils 12 import moving, prediction, indicators, utils
12 13 sys.path.append("D:/behaviourAnalysis/libs")
14 import trajLearning
13 __metaclass__ = type 15 __metaclass__ = type
14 16
15 class Interaction(moving.STObject): 17 class Interaction(moving.STObject):
16 '''Class for an interaction between two road users 18 '''Class for an interaction between two road users
17 or a road user and an obstacle 19 or a road user and an obstacle
145 for i in list(commonTimeInterval)[:-1]: 147 for i in list(commonTimeInterval)[:-1]:
146 if len(self.crossingZones[i]) > 0: 148 if len(self.crossingZones[i]) > 0:
147 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i]) 149 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i])
148 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs)) 150 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
149 151
152 def computeCrosssingCollisionsPrototypeAtInstant(self, instant,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity=0.1,mostMatched=None, computeCZ = False, debug = False,useDestination=True,useSpeedPrototype=True):
153 inter1=moving.Interval(self.roadUser1.timeInterval.first,instant)
154 inter2=moving.Interval(self.roadUser2.timeInterval.first,instant)
155 partialObjPositions1= self.roadUser1.getObjectInTimeInterval(inter1).positions
156 partialObjPositions2= self.roadUser2.getObjectInTimeInterval(inter2).positions
157 if useSpeedPrototype:
158 prototypeTrajectories1=trajLearning.findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route1,partialObjPositions1,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination)
159 prototypeTrajectories2=trajLearning.findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route2,partialObjPositions2,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination)
160 else:
161 prototypeTrajectories1=trajLearning.findPrototypes(prototypes,nMatching,objects,route1,partialObjPositions1,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched)
162 prototypeTrajectories2=trajLearning.findPrototypes(prototypes,nMatching,objects,route2,partialObjPositions2,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched)
163 if prototypeTrajectories1=={}:
164 print self.roadUser1.num, 'is abnormal at instant', str(instant)
165 return [],[]
166 elif prototypeTrajectories2=={}:
167 print self.roadUser2.num, 'is abnormal at instant', str(instant)
168 return [],[]
169 else:
170 currentInstant,collisionPoints, crossingZones = predictionParameters.computeCrossingsCollisionsAtInstant(instant, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)
171 return collisionPoints,crossingZones
172
173 def computeCrossingsCollisionsPrototype2stages(self, predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,step=10,minSimilarity=0.1,mostMatched=None, computeCZ = False, debug = False, timeInterval = None,acceptPartialLength=30,useDestination=True,useSpeedPrototype=True):
174 '''Computes all crossing and collision points at each common instant for two road users. '''
175 self.collisionPoints={}
176 self.crossingZones={}
177 TTCs = {}
178 route1=(self.roadUser1.startRouteID,self.roadUser1.endRouteID)
179 route2=(self.roadUser2.startRouteID,self.roadUser2.endRouteID)
180 if useDestination:
181 if route1 not in prototypes.keys():
182 route1= trajLearning.findRoute(prototypes,objects,route1,self.roadUser1.num,noiseEntryNums,noiseExitNums)
183 if route2 not in prototypes.keys():
184 route2= trajLearning.findRoute(prototypes,objects,route2,self.roadUser2.num,noiseEntryNums,noiseExitNums)
185
186 if timeInterval:
187 commonTimeInterval = timeInterval
188 else:
189 commonTimeInterval = self.timeInterval
190 reCompute=False
191 for i in xrange(commonTimeInterval.first,commonTimeInterval.last,step): # incremental calculation of CP,CZ to save time
192 if i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength:
193 self.collisionPoints[i], self.crossingZones[i] = self.computeCrosssingCollisionsPrototypeAtInstant(i,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched, computeCZ, debug,useDestination,useSpeedPrototype)
194 if len(self.collisionPoints[i]) >0 or len(self.crossingZones[i])>0:
195 reCompute=True
196 break
197 if reCompute:
198 for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
199 if i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength:
200 self.collisionPoints[i], self.crossingZones[i] = self.computeCrosssingCollisionsPrototypeAtInstant(i,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched, computeCZ, debug,useDestination,useSpeedPrototype)
201 if len(self.collisionPoints[i]) > 0:
202 TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.collisionPoints[i])
203 # add probability of collision, and probability of successful evasive action
204 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[7], TTCs))
205
206 if computeCZ:
207 pPETs = {}
208 for i in list(commonTimeInterval)[:-1]:
209 if i in self.crossingZones.keys() and len(self.crossingZones[i]) > 0:
210 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i])
211 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
212
150 def addVideoFilename(self,videoFilename): 213 def addVideoFilename(self,videoFilename):
151 self.videoFilename= videoFilename 214 self.videoFilename= videoFilename
152 215
153 def addInteractionType(self,interactionType): 216 def addInteractionType(self,interactionType):
154 ''' interaction types: conflict or collision if they are known''' 217 ''' interaction types: conflict or collision if they are known'''