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annotate python/events.py @ 341:2f39c4ed0b62

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first version of indicator saving to sqlite
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 20 Jun 2013 14:31:24 -0400
parents 1046b7346886
children e5fe0e6d48a1
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1 #! /usr/bin/env python
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2 '''Libraries for events
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3 Interactions, pedestrian crossing...'''
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4
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5 import numpy as np
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6 from numpy import arccos
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7
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8 import multiprocessing
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9 import itertools
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10
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11 import moving, prediction, indicators, utils
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12
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13 __metaclass__ = type
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14
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15 class Interaction(moving.STObject):
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16 '''Class for an interaction between two road users
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17 or a road user and an obstacle
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18
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19 link to the moving objects
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20 contains the indicators in a dictionary with the names as keys
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21 '''
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22
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23 categories = {'Head On': 0,
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24 'rearend': 1,
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25 'side': 2,
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26 'parallel': 3}
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27
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28 indicatorNames = ['Collision Course Dot Product',
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29 'Collision Course Angle',
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30 'Distance',
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31 'Minimum Distance',
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32 'Velocity Angle',
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33 'Speed Differential',
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34 'Collision Probability',
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35 'Time to Collision',
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36 'Probability of Successful Evasive Action',
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37 'predicted Post Encroachment Time']
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38
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39 indicatorNameToIndices = utils.inverseEnumeration(indicatorNames)
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40
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41 indicatorShortNames = ['',
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42 'CCAng',
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43 'Dist',
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44 'MinDist',
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45 'VA',
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46 'SD',
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47 'PoC',
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48 'TTC',
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49 'P(SEA)',
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50 'pPET']
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51
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52 def __init__(self, num = None, timeInterval = None, roaduserNum1 = None, roaduserNum2 = None, roadUser1 = None, roadUser2 = None, categoryNum = None):
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53 moving.STObject.__init__(self, num, timeInterval)
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54 self.roadUserNumbers = set([roaduserNum1, roaduserNum2])
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55 self.roadUser1 = roadUser1
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56 self.roadUser2 = roadUser2
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57 self.categoryNum = categoryNum
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58 self.indicators = {}
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59
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60 def getRoadUserNumbers(self):
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61 return self.roadUserNumbers
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62
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63 def getIndicator(self, indicatorName):
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64 return self.indicators.get(indicatorName, None)
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65
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66 def addIndicator(self, indicator):
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67 if indicator:
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68 self.indicators[indicator.name] = indicator
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69
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70 def computeIndicators(self):
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71 '''Computes the collision course cosine only if the cosine is positive'''
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72 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length())
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73 collisionCourseAngles = {}
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74 velocityAngles = {}
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75 distances = {}#[0]*int(self.timeInterval.length())
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76 speedDifferentials = {}
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77 for instant in self.timeInterval:
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78 deltap = self.roadUser1.getPositionAtInstant(instant)-self.roadUser2.getPositionAtInstant(instant)
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79 v1 = self.roadUser1.getVelocityAtInstant(instant)
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80 v2 = self.roadUser2.getVelocityAtInstant(instant)
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81 deltav = v2-v1
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82 velocityAngles[instant] = arccos(moving.Point.dot(v1, v2)/(v1.norm2()*v2.norm2()))
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83 collisionCourseDotProducts[instant] = moving.Point.dot(deltap, deltav)
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84 distances[instant] = deltap.norm2()
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85 speedDifferentials[instant] = deltav.norm2()
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86 #if collisionCourseDotProducts[instant] > 0:
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87 collisionCourseAngles[instant] = arccos(collisionCourseDotProducts[instant]/(distances[instant]*speedDifferentials[instant]))
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88
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89 # todo shorten the time intervals based on the interaction definition
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90 self.addIndicator(indicators.SeverityIndicator('Collision Course Dot Product', collisionCourseDotProducts))
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91 self.addIndicator(indicators.SeverityIndicator('Collision Course Angle', collisionCourseAngles))
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92 self.addIndicator(indicators.SeverityIndicator('Distance', distances))
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93 self.addIndicator(indicators.SeverityIndicator('Velocity Angle', velocityAngles))
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94 self.addIndicator(indicators.SeverityIndicator('Speed Differential', speedDifferentials))
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95
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96 # todo test for interaction instants and interval, compute indicators
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97
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98 # if we have features, compute other indicators
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99 if self.roadUser1.features and self.roadUser2.features:
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100 from scipy.spatial.distance import cdist
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101 minDistance={}
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102 for instant in self.timeInterval:
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103 positions1 = [f.getPositionAtInstant(instant).astuple() for f in self.roadUser1.features if f.existsAtInstant(instant)]
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104 positions2 = [f.getPositionAtInstant(instant).astuple() for f in self.roadUser2.features if f.existsAtInstant(instant)]
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105 distance = cdist(positions1, positions2, metric = 'euclidean')
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106 minDistance[instant] = distance.min()
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107 self.addIndicator(indicators.SeverityIndicator('Minimum Distance', minDistance))
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108
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109 def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None):
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110 '''Computes all crossing and collision points at each common instant for two road users. '''
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111 self.collisionPoints={}
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112 self.crossingZones={}
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113 TTCs = {}
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114
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115 if timeInterval:
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116 commonTimeInterval = timeInterval
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117 else:
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118 commonTimeInterval = self.timeInterval
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119 for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
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120 self.collisionPoints[i], self.crossingZones[i] = prediction.computeCrossingsCollisionsAtInstant(i, self.roadUser1, self.roadUser2, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ, debug)
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121 TTCs[i] = prediction.computeExpectedIndicator(self.collisionPoints[i])
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122 # add probability of collision, and probability of successful evasive action
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123 self.addIndicator(indicators.SeverityIndicator('TTC', TTCs))
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124
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125 if computeCZ:
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126 pPETs = {}
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127 for i in list(commonTimeInterval)[:-1]:
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128 pPETs[i] = prediction.computeExpectedIndicator(self.crossingZones[i])
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129 self.addIndicator(indicators.SeverityIndicator('pPET', pPETs))
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130
310
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131 def addVideoFilename(self,videoFilename):
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132 self.videoFilename= videoFilename
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133
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134 def addInteractionType(self,interactionType):
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135 ''' interaction types: conflict or collision if they are known'''
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136 self.interactionType= interactionType
293
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137
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138 def createInteractions(objects):
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139 '''Create all interactions of two co-existing road users
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140
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141 todo add test to compute categories?'''
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142 interactions = []
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143 num = 0
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144 for i in xrange(len(objects)):
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145 for j in xrange(i):
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146 commonTimeInterval = objects[i].commonTimeInterval(objects[j])
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147 if not commonTimeInterval.empty():
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148 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, objects[j].num, objects[i], objects[j]))
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149 num += 1
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150 return interactions
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151
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152
292
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153 # TODO:
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154 #http://stackoverflow.com/questions/3288595/multiprocessing-using-pool-map-on-a-function-defined-in-a-class
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155 #http://www.rueckstiess.net/research/snippets/show/ca1d7d90
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156 def calculateIndicatorPipe(pairs, predParam, timeHorizon=75,collisionDistanceThreshold=1.8):
320
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157 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(pairs.roadUser1, pairs.roadUser2, predParam, collisionDistanceThreshold, timeHorizon)
292
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158 #print pairs.num
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159 # Ignore empty collision points
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160 empty = 1
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161 for i in collisionPoints:
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162 if(collisionPoints[i] != []):
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163 empty = 0
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164 if(empty == 1):
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165 pairs.hasCP = 0
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166 else:
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167 pairs.hasCP = 1
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168 pairs.CP = collisionPoints
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169
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170 # Ignore empty crossing zones
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171 empty = 1
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172 for i in crossingZones:
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173 if(crossingZones[i] != []):
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174 empty = 0
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175 if(empty == 1):
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176 pairs.hasCZ = 0
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177 else:
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178 pairs.hasCZ = 1
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179 pairs.CZ = crossingZones
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180 return pairs
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181
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182 def calculateIndicatorPipe_star(a_b):
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183 """Convert `f([1,2])` to `f(1,2)` call."""
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184 return calculateIndicatorPipe(*a_b)
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185
291
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186 class VehPairs():
293
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187 '''Create a veh-pairs object from objects list'''
291
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188 def __init__(self,objects):
293
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189 self.pairs = createInteractions(objects)
292
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190 self.interactionCount = 0
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191 self.CPcount = 0
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192 self.CZcount = 0
291
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193
292
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194 # Process indicator calculation with support for multi-threading
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195 def calculateIndicators(self,predParam,threads=1,timeHorizon=75,collisionDistanceThreshold=1.8):
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196 if(threads > 1):
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197 pool = multiprocessing.Pool(threads)
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198 self.pairs = pool.map(calculateIndicatorPipe_star, itertools.izip(self.pairs, itertools.repeat(predParam)))
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199 pool.close()
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200 else:
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201 #prog = Tools.ProgressBar(0, len(self.pairs), 77) #Removed in traffic-intelligenc port
291
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202 for j in xrange(len(self.pairs)):
292
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203 #prog.updateAmount(j) #Removed in traffic-intelligenc port
320
419f30491a4b renamed fields movingObject to roadUser, etc
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204 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(self.pairs[j].roadUser1, self.pairs[j].roadUser2, predParam, collisionDistanceThreshold, timeHorizon)
291
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205
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206 # Ignore empty collision points
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207 empty = 1
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208 for i in collisionPoints:
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209 if(collisionPoints[i] != []):
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210 empty = 0
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211 if(empty == 1):
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212 self.pairs[j].hasCP = 0
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213 else:
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214 self.pairs[j].hasCP = 1
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215 self.pairs[j].CP = collisionPoints
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216
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217 # Ignore empty crossing zones
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218 empty = 1
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219 for i in crossingZones:
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220 if(crossingZones[i] != []):
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221 empty = 0
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222 if(empty == 1):
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223 self.pairs[j].hasCZ = 0
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224 else:
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225 self.pairs[j].hasCZ = 1
292
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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226 self.pairs[j].CZ = crossingZones
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227
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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228 for j in self.pairs:
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229 self.interactionCount = self.interactionCount + len(j.CP)
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230 self.CPcount = len(self.getCPlist())
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231 self.Czcount = len(self.getCZlist())
291
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232
292
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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233
291
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234 def getPairsWCP(self):
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235 lists = []
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236 for j in self.pairs:
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237 if(j.hasCP):
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238 lists.append(j.num)
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239 return lists
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240
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241 def getPairsWCZ(self):
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242 lists = []
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243 for j in self.pairs:
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244 if(j.hasCZ):
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245 lists.append(j.num)
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246 return lists
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247
292
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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diff changeset
248 def getCPlist(self,indicatorThreshold=99999):
291
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249 lists = []
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250 for j in self.pairs:
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251 if(j.hasCP):
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252 for k in j.CP:
292
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diff changeset
253 if(j.CP[k] != [] and j.CP[k][0].indicator < indicatorThreshold):
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diff changeset
254 lists.append([k,j.CP[k][0]])
291
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diff changeset
255 return lists
292
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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diff changeset
256
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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diff changeset
257 def getCZlist(self,indicatorThreshold=99999):
291
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258 lists = []
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259 for j in self.pairs:
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260 if(j.hasCZ):
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diff changeset
261 for k in j.CZ:
292
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diff changeset
262 if(j.CZ[k] != [] and j.CZ[k][0].indicator < indicatorThreshold):
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diff changeset
263 lists.append([k,j.CZ[k][0]])
291
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diff changeset
264 return lists
292
8b2c8a4015f1 class VehPairs updated. Now supports primitive multithreading.
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265
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diff changeset
266 def genIndicatorHistogram(self, CPlist=False, bins=range(0,100,1)):
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diff changeset
267 if(not CPlist):
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diff changeset
268 CPlist = self.getCPlist()
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diff changeset
269 if(not CPlist):
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diff changeset
270 return False
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diff changeset
271 TTC_list = []
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diff changeset
272 for i in CPlist:
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diff changeset
273 TTC_list.append(i[1].indicator)
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diff changeset
274 histo = np.histogram(TTC_list,bins=bins)
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275 histo += (histo[0].astype(float)/np.sum(histo[0]),)
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276 return histo
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277
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278 class Crossing(moving.STObject):
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279 '''Class for the event of a street crossing
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280
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281 TODO: detecter passage sur la chaussee
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282 identifier origines et destination (ou uniquement chaussee dans FOV)
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283 carac traversee
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284 detecter proximite veh (retirer si trop similaire simultanement
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285 carac interaction'''
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286
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287 def __init__(self, roaduserNum = None, num = None, timeInterval = None):
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288 moving.STObject.__init__(self, num, timeInterval)
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289 self.roaduserNum = roaduserNum
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290
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291
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292
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293 if __name__ == "__main__":
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294 import doctest
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295 import unittest
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296 #suite = doctest.DocFileSuite('tests/moving.txt')
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297 suite = doctest.DocTestSuite()
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298 unittest.TextTestRunner().run(suite)
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299