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evolution of indicators and their computation in interactions
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 08 Feb 2013 18:35:24 -0500
parents ee3302528cdc
children
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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
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7 import multiprocessing
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8 import itertools
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9
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f955e83da499 developed indicators in interactions
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10 import moving
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11 import prediction
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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 = {'headon': 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 def __init__(self, num = None, timeInterval = None, roaduserNum1 = None, roaduserNum2 = None, movingObject1 = None, movingObject2 = None, categoryNum = None):
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29 moving.STObject.__init__(self, num, timeInterval)
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30 self.roaduserNumbers = set([roaduserNum1, roaduserNum2])
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31 self.movingObject1 = movingObject1
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32 self.movingObject2 = movingObject2
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33 self.categoryNum = categoryNum
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34 self.indicators = {}
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35
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36 def getIndicator(self, indicatorName):
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37 return self.indicators[indicatorName]
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38
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39 def addIndicator(self, indicator):
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40 self.indicators[indicator.name] = indicator
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41
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42 def computeIndicators(self):
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43 '''Computes the collision course cosine only if the cosine is positive'''
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44 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length())
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45 collisionCourseCosines = {}
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46 distances = {}#[0]*int(self.timeInterval.length())
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47 speedDifferentials = {}
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48 for instant in self.timeInterval:
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49 deltap = self.movingObject1.getPositionAtInstant(instant)-self.movingObject2.getPositionAtInstant(instant)
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50 deltav = self.movingObject2.getVelocityAtInstant(instant)-self.movingObject1.getVelocityAtInstant(instant)
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51 collisionCourseDotProduct[instant] = moving.Point.dot(deltap, deltav)
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52 distances[instant] = deltap.norm2()
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53 speedDifferentials[instant] = deltav.norm2()
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54 if collisionCourseDotProduct[instant] > 0:
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55 collisionCourseCosine[instant] = collisionCourseDotProduct[instant]/(distances[instant]*speedDifferentials[instant])
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56 # todo shorten the time intervals based on the interaction definition
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57 self.addIndicator(moving.SeverityIndicator('Collision Course Dot Product', collisionCourseDotProducts))
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58 self.addIndicator(moving.SeverityIndicator('Distance', distances))
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59 self.addIndicator(moving.SeverityIndicator('Speed Differential', speedDifferentials))
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60 self.addIndicator(moving.SeverityIndicator('Collision Course Cosine', collisionCourseCosines))
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61
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62
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63 def createInteractions(objects):
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64 '''Create all interactions of two co-existing road users
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65
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66 todo add test to compute categories?'''
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67 interactions = []
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68 num = 0
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69 for i in xrange(len(objects)):
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70 for j in xrange(i):
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71 commonTimeInterval = objects[i].commonTimeInterval(objects[j])
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72 if not commonTimeInterval.empty():
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73 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, objects[j].num, objects[i], objects[j]))
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74 num += 1
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75 return interactions
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76
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77
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78 # TODO:
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79 #http://stackoverflow.com/questions/3288595/multiprocessing-using-pool-map-on-a-function-defined-in-a-class
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80 #http://www.rueckstiess.net/research/snippets/show/ca1d7d90
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81 def calculateIndicatorPipe(pairs, predParam, timeHorizon=75,collisionDistanceThreshold=1.8):
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82 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(pairs.movingObject1, pairs.movingObject2, predParam, collisionDistanceThreshold, timeHorizon)
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83 #print pairs.num
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84 # Ignore empty collision points
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85 empty = 1
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86 for i in collisionPoints:
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87 if(collisionPoints[i] != []):
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88 empty = 0
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89 if(empty == 1):
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90 pairs.hasCP = 0
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91 else:
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92 pairs.hasCP = 1
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93 pairs.CP = collisionPoints
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94
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95 # Ignore empty crossing zones
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96 empty = 1
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97 for i in crossingZones:
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98 if(crossingZones[i] != []):
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99 empty = 0
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100 if(empty == 1):
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101 pairs.hasCZ = 0
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102 else:
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103 pairs.hasCZ = 1
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104 pairs.CZ = crossingZones
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105 return pairs
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106
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107 def calculateIndicatorPipe_star(a_b):
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108 """Convert `f([1,2])` to `f(1,2)` call."""
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109 return calculateIndicatorPipe(*a_b)
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110
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111 class VehPairs():
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112 '''Create a veh-pairs object from objects list'''
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113 def __init__(self,objects):
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114 self.pairs = createInteractions(objects)
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115 self.interactionCount = 0
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116 self.CPcount = 0
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117 self.CZcount = 0
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118
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119 # Process indicator calculation with support for multi-threading
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120 def calculateIndicators(self,predParam,threads=1,timeHorizon=75,collisionDistanceThreshold=1.8):
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121 if(threads > 1):
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122 pool = multiprocessing.Pool(threads)
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123 self.pairs = pool.map(calculateIndicatorPipe_star, itertools.izip(self.pairs, itertools.repeat(predParam)))
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124 pool.close()
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125 else:
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126 #prog = Tools.ProgressBar(0, len(self.pairs), 77) #Removed in traffic-intelligenc port
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127 for j in xrange(len(self.pairs)):
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128 #prog.updateAmount(j) #Removed in traffic-intelligenc port
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129 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(self.pairs[j].movingObject1, self.pairs[j].movingObject2, predParam, collisionDistanceThreshold, timeHorizon)
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130
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131 # Ignore empty collision points
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132 empty = 1
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133 for i in collisionPoints:
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134 if(collisionPoints[i] != []):
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135 empty = 0
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136 if(empty == 1):
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137 self.pairs[j].hasCP = 0
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138 else:
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139 self.pairs[j].hasCP = 1
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140 self.pairs[j].CP = collisionPoints
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141
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142 # Ignore empty crossing zones
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143 empty = 1
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144 for i in crossingZones:
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145 if(crossingZones[i] != []):
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146 empty = 0
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147 if(empty == 1):
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148 self.pairs[j].hasCZ = 0
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149 else:
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150 self.pairs[j].hasCZ = 1
292
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151 self.pairs[j].CZ = crossingZones
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152
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153 for j in self.pairs:
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154 self.interactionCount = self.interactionCount + len(j.CP)
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155 self.CPcount = len(self.getCPlist())
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156 self.Czcount = len(self.getCZlist())
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157
292
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158
291
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159 def getPairsWCP(self):
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160 lists = []
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161 for j in self.pairs:
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162 if(j.hasCP):
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163 lists.append(j.num)
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164 return lists
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165
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166 def getPairsWCZ(self):
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167 lists = []
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168 for j in self.pairs:
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169 if(j.hasCZ):
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170 lists.append(j.num)
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171 return lists
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172
292
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173 def getCPlist(self,indicatorThreshold=99999):
291
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174 lists = []
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175 for j in self.pairs:
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176 if(j.hasCP):
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177 for k in j.CP:
292
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178 if(j.CP[k] != [] and j.CP[k][0].indicator < indicatorThreshold):
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179 lists.append([k,j.CP[k][0]])
291
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180 return lists
292
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181
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182 def getCZlist(self,indicatorThreshold=99999):
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183 lists = []
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184 for j in self.pairs:
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185 if(j.hasCZ):
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186 for k in j.CZ:
292
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187 if(j.CZ[k] != [] and j.CZ[k][0].indicator < indicatorThreshold):
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188 lists.append([k,j.CZ[k][0]])
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189 return lists
292
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190
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191 def genIndicatorHistogram(self, CPlist=False, bins=range(0,100,1)):
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192 if(not CPlist):
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193 CPlist = self.getCPlist()
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194 if(not CPlist):
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195 return False
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196 TTC_list = []
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197 for i in CPlist:
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198 TTC_list.append(i[1].indicator)
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199 histo = np.histogram(TTC_list,bins=bins)
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200 histo += (histo[0].astype(float)/np.sum(histo[0]),)
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201 return histo
291
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202
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203 class Crossing(moving.STObject):
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204 '''Class for the event of a street crossing
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205
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206 TODO: detecter passage sur la chaussee
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207 identifier origines et destination (ou uniquement chaussee dans FOV)
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208 carac traversee
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209 detecter proximite veh (retirer si trop similaire simultanement
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210 carac interaction'''
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211
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212 def __init__(self, roaduserNum = None, num = None, timeInterval = None):
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213 moving.STObject.__init__(self, num, timeInterval)
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214 self.roaduserNum = roaduserNum
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215
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216
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217
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218 if __name__ == "__main__":
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219 import doctest
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220 import unittest
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221 #suite = doctest.DocFileSuite('tests/moving.txt')
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222 suite = doctest.DocTestSuite()
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223 unittest.TextTestRunner().run(suite)
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224