Mercurial > hg > nsaunier > traffic-intelligence

comparison python/events.py @ 604:8ba4b8ad4c86

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Motion Pattern Method
author MohamedGomaa
date Tue, 15 Jul 2014 13:25:15 -0400
parents 21bdeb29f855
children
comparison
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548:e6ab4caf359c 604:8ba4b8ad4c86
1 #! /usr/bin/env python 1 #! /usr/bin/env python
2 '''Libraries for events 2 '''Libraries for events
3 Interactions, pedestrian crossing...''' 3 Interactions, pedestrian crossing...'''
4 4 import sys
5 import numpy as np 5 import numpy as np
6 from numpy import arccos 6 from numpy import arccos
7 7
8 import multiprocessing 8 import multiprocessing
9 import itertools 9 import itertools
136 136
137 if computeCZ: 137 if computeCZ:
138 pPETs = {} 138 pPETs = {}
139 for i in list(commonTimeInterval)[:-1]: 139 for i in list(commonTimeInterval)[:-1]:
140 if len(self.crossingZones[i]) > 0: 140 if len(self.crossingZones[i]) > 0:
141 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i])
142 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
143
144 def computeCrossingsCollisionsPrototype(self, predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,nMatching,objects,minSimilarity=0.5,index=None,mostMatched=None, computeCZ = False, debug = False, timeInterval = None,acceptPartialLength=30):
145 '''Computes all crossing and collision points at each common instant for two road users. '''
146 self.collisionPoints={}
147 self.crossingZones={}
148 TTCs = {}
149 route1=(self.roadUser1.startRouteID,self.roadUser1.endRouteID)
150 route2=(self.roadUser2.startRouteID,self.roadUser2.endRouteID)
151
152 if timeInterval:
153 commonTimeInterval = timeInterval
154 else:
155 commonTimeInterval = self.timeInterval
156 for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
157 sys.path.append("D:/behaviourAnalysis/libs")
158 import trajLearning
159 if i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength:
160 inter1=moving.Interval(self.roadUser1.timeInterval.first,i)
161 inter2=moving.Interval(self.roadUser2.timeInterval.first,i)
162 partialObjPositions1= self.roadUser1.getObjectInTimeInterval(inter1).positions
163 partialObjPositions2= self.roadUser2.getObjectInTimeInterval(inter2).positions
164 prototypeTrajectories1=trajLearning.findPrototypes(prototypes,nMatching,objects,route1,partialObjPositions1,minSimilarity,index,mostMatched)
165 prototypeTrajectories2=trajLearning.findPrototypes(prototypes,nMatching,objects,route2,partialObjPositions2,minSimilarity,index,mostMatched)
166 if prototypeTrajectories1=={}:
167 print self.roadUser1.num, 'is abnormal at instant', str(i)
168 elif prototypeTrajectories2=={}:
169 print self.roadUser2.num, 'is abnormal at instant', str(i)
170 else:
171 self.collisionPoints[i], self.crossingZones[i] = predictionParameters.computeCrossingsCollisionsAtInstant(i, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)
172 if len(self.collisionPoints[i]) > 0:
173 TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.collisionPoints[i])
174 # add probability of collision, and probability of successful evasive action
175 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[7], TTCs))
176
177 if computeCZ:
178 pPETs = {}
179 for i in list(commonTimeInterval)[:-1]:
180 if i in self.crossingZones.keys() and len(self.crossingZones[i]) > 0:
141 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i]) 181 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i])
142 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs)) 182 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
143 183
144 def addVideoFilename(self,videoFilename): 184 def addVideoFilename(self,videoFilename):
145 self.videoFilename= videoFilename 185 self.videoFilename= videoFilename