Mercurial Hosting > traffic-intelligence
annotate python/events.py @ 661:dc70d9e711f5
some method name change and new methods for features in objects (MovingObject) and methods to access indicator values in interactions
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Mon, 18 May 2015 13:53:25 +0200 |
| parents | 3058e00887bc |
| children | 72174e66aba5 |
| rev | line source |
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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, cvutils |
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12 __metaclass__ = type |
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13 |
| 613 | 14 def findRoute(prototypes,objects,i,j,noiseEntryNums,noiseExitNums,minSimilarity= 0.3, spatialThreshold=1.0, delta=180): |
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15 if i[0] not in noiseEntryNums: |
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16 prototypesRoutes= [ x for x in sorted(prototypes.keys()) if i[0]==x[0]] |
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17 elif i[1] not in noiseExitNums: |
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18 prototypesRoutes=[ x for x in sorted(prototypes.keys()) if i[1]==x[1]] |
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19 else: |
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20 prototypesRoutes=[x for x in sorted(prototypes.keys())] |
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21 routeSim={} |
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22 lcss = utils.LCSS(similarityFunc=lambda x,y: (distanceForLCSS(x,y) <= spatialThreshold),delta=delta) |
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23 for y in prototypesRoutes: |
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24 if y in prototypes.keys(): |
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25 prototypesIDs=prototypes[y] |
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26 similarity=[] |
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27 for x in prototypesIDs: |
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28 s=lcss.computeNormalized(objects[j].positions, objects[x].positions) |
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29 similarity.append(s) |
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30 routeSim[y]=max(similarity) |
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31 route=max(routeSim, key=routeSim.get) |
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32 if routeSim[route]>=minSimilarity: |
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33 return route |
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34 else: |
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35 return i |
| 613 | 36 |
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37 def getRoute(obj,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination=True): |
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38 route=(obj.startRouteID,obj.endRouteID) |
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39 if useDestination: |
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40 if route not in prototypes.keys(): |
| 613 | 41 route= findRoute(prototypes,objects,route,obj.getNum(),noiseEntryNums,noiseExitNums) |
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42 return route |
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43 |
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44 class Interaction(moving.STObject): |
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45 '''Class for an interaction between two road users |
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46 or a road user and an obstacle |
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47 |
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48 link to the moving objects |
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49 contains the indicators in a dictionary with the names as keys |
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50 ''' |
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51 |
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52 categories = {'Head On': 0, |
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53 'rearend': 1, |
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54 'side': 2, |
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55 'parallel': 3} |
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56 |
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57 indicatorNames = ['Collision Course Dot Product', |
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58 'Collision Course Angle', |
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59 'Distance', |
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60 'Minimum Distance', |
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61 'Velocity Angle', |
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62 'Speed Differential', |
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63 'Collision Probability', |
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64 'Time to Collision', # 7 |
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65 'Probability of Successful Evasive Action', |
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66 'predicted Post Encroachment Time'] |
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67 |
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68 indicatorNameToIndices = utils.inverseEnumeration(indicatorNames) |
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69 |
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70 indicatorShortNames = ['CCDP', |
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71 'CCA', |
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72 'Dist', |
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73 'MinDist', |
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74 'VA', |
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75 'SD', |
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76 'PoC', |
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77 'TTC', |
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78 'P(SEA)', |
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79 'pPET'] |
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80 |
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81 indicatorUnits = ['', |
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82 'rad', |
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83 'm', |
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84 'm', |
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85 'rad', |
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86 'm/s', |
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87 '', |
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88 's', |
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89 '', |
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90 ''] |
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91 |
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92 def __init__(self, num = None, timeInterval = None, roaduserNum1 = None, roaduserNum2 = None, roadUser1 = None, roadUser2 = None, categoryNum = None): |
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93 moving.STObject.__init__(self, num, timeInterval) |
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94 if timeInterval is None and roadUser1 is not None and roadUser2 is not None: |
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95 self.timeInterval = roadUser1.commonTimeInterval(roadUser2) |
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96 self.roadUser1 = roadUser1 |
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97 self.roadUser2 = roadUser2 |
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98 if roaduserNum1 is not None and roaduserNum2 is not None: |
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99 self.roadUserNumbers = set([roaduserNum1, roaduserNum2]) |
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100 elif roadUser1 is not None and roadUser2 is not None: |
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101 self.roadUserNumbers = set(roadUser1.getNum(), roadUser2.getNum()) |
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102 else: |
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103 self.roadUserNumbers = None |
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104 self.categoryNum = categoryNum |
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105 self.indicators = {} |
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106 self.interactionInterval = None |
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107 self.collisionPoints = None # distionary for collison points with different prediction methods |
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108 |
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109 def getRoadUserNumbers(self): |
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110 return self.roadUserNumbers |
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111 |
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112 def setRoadUsers(self, objects): |
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113 nums = list(self.getRoadUserNumbers()) |
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114 if objects[nums[0]].getNum() == nums[0]: |
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115 self.roadUser1 = objects[nums[0]] |
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116 if objects[nums[1]].getNum() == nums[1]: |
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117 self.roadUser2 = objects[nums[1]] |
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118 |
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119 i = 0 |
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120 while i < len(objects) and self.roadUser2 is None: |
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121 if objects[i].getNum() in nums: |
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122 if self.roadUser1 is None: |
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123 self.roadUser1 = objects[i] |
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124 else: |
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125 self.roadUser2 = objects[i] |
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126 i += 1 |
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127 |
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128 def getIndicator(self, indicatorName): |
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129 return self.indicators.get(indicatorName, None) |
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130 |
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131 def addIndicator(self, indicator): |
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132 if indicator is not None: |
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133 self.indicators[indicator.name] = indicator |
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134 |
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135 def getIndicatorValueAtInstant(self, indicatorName, instant): |
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136 indicator = self.getIndicator(indicatorName) |
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137 if indicator is not None: |
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138 return indicator[instant] |
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139 else: |
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140 return None |
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141 |
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142 def getIndicatorValuesAtInstant(self, instant): |
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143 '''Returns list of indicator values at instant |
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144 as dict (with keys from indicators dict)''' |
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145 values = {} |
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146 for k, indicator in self.indicators.iteritems(): |
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147 values[k] = indicator[instant] |
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148 return values |
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149 |
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150 def plot(self, options = '', withOrigin = False, timeStep = 1, withFeatures = False, **kwargs): |
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151 self.roadUser1.plot(options, withOrigin, timeStep, withFeatures, **kwargs) |
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152 self.roadUser2.plot(options, withOrigin, timeStep, withFeatures, **kwargs) |
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153 |
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154 def plotOnWorldImage(self, nPixelsPerUnitDistance, options = '', withOrigin = False, timeStep = 1, **kwargs): |
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155 self.roadUser1.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs) |
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156 self.roadUser2.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs) |
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157 |
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158 def play(self, videoFilename, homography = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1.): |
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159 if self.roadUser1 is not None and self.roadUser2 is not None: |
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160 cvutils.displayTrajectories(videoFilename, [self.roadUser1, self.roadUser2], homography = homography, firstFrameNum = self.getFirstInstant(), lastFrameNumArg = self.getLastInstant(), undistort = undistort, intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication) |
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161 else: |
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162 print('Please set the interaction road user attributes roadUser1 and roadUser1 through the method setRoadUsers') |
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163 |
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164 def computeIndicators(self): |
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165 '''Computes the collision course cosine only if the cosine is positive''' |
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166 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length()) |
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167 collisionCourseAngles = {} |
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168 velocityAngles = {} |
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169 distances = {}#[0]*int(self.timeInterval.length()) |
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170 speedDifferentials = {} |
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171 interactionInstants = [] |
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172 for instant in self.timeInterval: |
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173 deltap = self.roadUser1.getPositionAtInstant(instant)-self.roadUser2.getPositionAtInstant(instant) |
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174 v1 = self.roadUser1.getVelocityAtInstant(instant) |
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175 v2 = self.roadUser2.getVelocityAtInstant(instant) |
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176 deltav = v2-v1 |
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177 velocityAngles[instant] = arccos(moving.Point.dot(v1, v2)/(v1.norm2()*v2.norm2())) |
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178 collisionCourseDotProducts[instant] = moving.Point.dot(deltap, deltav) |
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179 distances[instant] = deltap.norm2() |
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180 speedDifferentials[instant] = deltav.norm2() |
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181 if collisionCourseDotProducts[instant] > 0: |
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182 interactionInstants.append(instant) |
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183 collisionCourseAngles[instant] = arccos(collisionCourseDotProducts[instant]/(distances[instant]*speedDifferentials[instant])) |
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184 |
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185 if len(interactionInstants) >= 2: |
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186 self.interactionInterval = moving.TimeInterval(interactionInstants[0], interactionInstants[-1]) |
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187 else: |
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188 self.interactionInterval = moving.TimeInterval() |
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189 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[0], collisionCourseDotProducts)) |
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190 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[1], collisionCourseAngles)) |
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191 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[2], distances)) |
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192 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[4], velocityAngles)) |
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193 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[5], speedDifferentials)) |
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194 |
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195 # if we have features, compute other indicators |
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196 if self.roadUser1.hasFeatures() and self.roadUser2.hasFeatures(): |
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197 minDistance={} |
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198 for instant in self.timeInterval: |
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199 minDistance[instant] = moving.MovingObject.minDistance(self.roadUser1, self.roadUser2, instant) |
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200 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[3], minDistance)) |
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201 |
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202 def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1, usePrototypes=False, route1= (-1,-1), route2=(-1,-1), prototypes={}, secondStepPrototypes={}, nMatching={}, objects=[], noiseEntryNums=[], noiseExitNums=[], minSimilarity=0.1, mostMatched=None, useDestination=True, useSpeedPrototype=True, acceptPartialLength=30, step=1): |
|
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203 '''Computes all crossing and collision points at each common instant for two road users. ''' |
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204 self.collisionPoints={} |
| 339 | 205 self.crossingZones={} |
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206 TTCs = {} |
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207 if usePrototypes: |
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208 route1= getRoute(self.roadUser1,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination) |
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209 route2= getRoute(self.roadUser2,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination) |
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210 |
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211 if timeInterval is not None: |
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212 commonTimeInterval = timeInterval |
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213 else: |
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214 commonTimeInterval = self.timeInterval |
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215 self.collisionPoints[predictionParameters.name], crossingZones = predictionParameters.computeCrossingsCollisions(self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, commonTimeInterval, nProcesses,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype,acceptPartialLength, step) |
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216 if computeCZ: |
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217 self.crossingZones[predictionParameters.name] = crossingZones |
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218 for i, cp in self.collisionPoints.iteritems(): |
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219 TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(cp) |
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220 # add probability of collision, and probability of successful evasive action |
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221 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[7], TTCs, mostSevereIsMax=False)) |
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222 |
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223 if computeCZ: |
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224 pPETs = {} |
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225 for i, cz in self.crossingZones.iteritems(): |
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226 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(cz) |
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227 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs, mostSevereIsMax=False)) |
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228 |
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229 def computePET(self, collisionDistanceThreshold): |
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230 # TODO add crossing zone |
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231 self.pet = moving.MovingObject.computePET(self.roadUser1, self.roadUser2, collisionDistanceThreshold) |
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232 |
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233 def addVideoFilename(self,videoFilename): |
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234 self.videoFilename = videoFilename |
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235 |
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236 def addInteractionType(self,interactionType): |
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237 ''' interaction types: conflict or collision if they are known''' |
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238 self.interactionType = interactionType |
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239 |
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240 def getCrossingZones(self, predictionMethodName): |
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241 if self.hasattr(self, 'crossingZones'): |
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242 return self.crossingZones[predictionMethodName] |
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243 else: |
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244 return None |
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245 |
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246 def getCollisionPoints(self, predictionMethodName): |
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247 if self.collisionPoints is not None: |
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248 return self.collisionPoints[predictionMethodName] |
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249 else: |
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250 return None |
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251 |
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252 |
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253 def createInteractions(objects, _others = None): |
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254 '''Create all interactions of two co-existing road users''' |
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255 if _others is not None: |
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256 others = _others |
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257 |
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258 interactions = [] |
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259 num = 0 |
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260 for i in xrange(len(objects)): |
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261 if _others is None: |
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262 others = objects[:i] |
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263 for j in xrange(len(others)): |
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264 commonTimeInterval = objects[i].commonTimeInterval(others[j]) |
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265 if not commonTimeInterval.empty(): |
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266 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, others[j].num, objects[i], others[j])) |
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267 num += 1 |
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268 return interactions |
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269 |
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270 def findInteraction(interactions, roadUserNum1, roadUserNum2): |
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271 'Returns the right interaction in the set' |
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272 i=0 |
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273 while i<len(interactions) and set([roadUserNum1, roadUserNum2]) != interactions[i].getRoadUserNumbers(): |
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274 i+=1 |
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275 if i<len(interactions): |
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276 return interactions[i] |
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277 else: |
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278 return None |
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279 |
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280 def aggregateSafetyPoints(interactions, pointType = 'collision'): |
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281 '''Put all collision points or crossing zones in a list for display''' |
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282 allPoints = [] |
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283 if pointType == 'collision': |
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284 for i in interactions: |
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285 for points in i.collisionPoints.values(): |
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286 allPoints += points |
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287 elif pointType == 'crossing': |
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288 for i in interactions: |
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289 for points in i.crossingZones.values(): |
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290 allPoints += points |
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291 else: |
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292 print('unknown type of point '+pointType) |
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293 return allPoints |
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294 |
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295 def prototypeCluster(interactions, similarityMatrix, alignmentMatrix, indicatorName, minSimilarity): |
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296 '''Finds exemplar indicator time series for all interactions |
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297 Returns the prototype indices (in the interaction list) and the label of each indicator (interaction) |
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298 |
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299 if an indicator profile (time series) is different enough (<minSimilarity), |
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300 it will become a new prototype. |
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301 Non-prototype interactions will be assigned to an existing prototype''' |
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302 |
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303 # sort indicators based on length |
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304 indices = range(similarityMatrix.shape[0]) |
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305 def compare(i, j): |
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306 if len(interactions[i].getIndicator(indicatorName)) > len(interactions[j].getIndicator(indicatorName)): |
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307 return -1 |
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308 elif len(interactions[i].getIndicator(indicatorName)) == len(interactions[j].getIndicator(indicatorName)): |
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309 return 0 |
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310 else: |
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311 return 1 |
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312 indices.sort(compare) |
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313 # go through all indicators |
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314 prototypeIndices = [indices[0]] |
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315 for i in indices[1:]: |
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316 if similarityMatrix[i][prototypeIndices].max() < minSimilarity: |
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317 prototypeIndices.append(i) |
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318 |
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319 # assignment |
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320 labels = [-1]*similarityMatrix.shape[0] |
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321 indices = [i for i in range(similarityMatrix.shape[0]) if i not in prototypeIndices] |
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322 for i in prototypeIndices: |
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323 labels[i] = i |
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324 for i in indices: |
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325 prototypeIndex = similarityMatrix[i][prototypeIndices].argmax() |
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326 labels[i] = prototypeIndices[prototypeIndex] |
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327 |
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328 return prototypeIndices, labels |
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329 |
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330 def prototypeMultivariateCluster(interactions, similarityMatrics, indicatorNames, minSimilarities, minClusterSize): |
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331 '''Finds exmaple indicator time series (several indicators) for all interactions |
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332 |
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333 if any interaction indicator time series is different enough (<minSimilarity), |
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334 it will become a new prototype. |
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335 Non-prototype interactions will be assigned to an existing prototype if all indicators are similar enough''' |
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336 pass |
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337 |
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338 # TODO: |
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339 #http://stackoverflow.com/questions/3288595/multiprocessing-using-pool-map-on-a-function-defined-in-a-class |
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340 #http://www.rueckstiess.net/research/snippets/show/ca1d7d90 |
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341 def calculateIndicatorPipe(pairs, predParam, timeHorizon=75,collisionDistanceThreshold=1.8): |
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320
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342 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(pairs.roadUser1, pairs.roadUser2, predParam, collisionDistanceThreshold, timeHorizon) |
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343 #print pairs.num |
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344 # Ignore empty collision points |
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345 empty = 1 |
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346 for i in collisionPoints: |
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347 if(collisionPoints[i] != []): |
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348 empty = 0 |
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349 if(empty == 1): |
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350 pairs.hasCP = 0 |
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351 else: |
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352 pairs.hasCP = 1 |
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353 pairs.CP = collisionPoints |
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354 |
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355 # Ignore empty crossing zones |
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356 empty = 1 |
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357 for i in crossingZones: |
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358 if(crossingZones[i] != []): |
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359 empty = 0 |
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360 if(empty == 1): |
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361 pairs.hasCZ = 0 |
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362 else: |
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363 pairs.hasCZ = 1 |
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364 pairs.CZ = crossingZones |
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365 return pairs |
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366 |
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367 def calculateIndicatorPipe_star(a_b): |
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368 """Convert `f([1,2])` to `f(1,2)` call.""" |
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369 return calculateIndicatorPipe(*a_b) |
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370 |
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371 class VehPairs(): |
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372 '''Create a veh-pairs object from objects list''' |
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373 def __init__(self,objects): |
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374 self.pairs = createInteractions(objects) |
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375 self.interactionCount = 0 |
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376 self.CPcount = 0 |
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377 self.CZcount = 0 |
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378 |
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379 # Process indicator calculation with support for multi-threading |
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380 def calculateIndicators(self,predParam,threads=1,timeHorizon=75,collisionDistanceThreshold=1.8): |
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381 if(threads > 1): |
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382 pool = multiprocessing.Pool(threads) |
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383 self.pairs = pool.map(calculateIndicatorPipe_star, itertools.izip(self.pairs, itertools.repeat(predParam))) |
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384 pool.close() |
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385 else: |
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386 #prog = Tools.ProgressBar(0, len(self.pairs), 77) #Removed in traffic-intelligenc port |
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387 for j in xrange(len(self.pairs)): |
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388 #prog.updateAmount(j) #Removed in traffic-intelligenc port |
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320
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389 collisionPoints, crossingZones = prediction.computeCrossingsCollisions(self.pairs[j].roadUser1, self.pairs[j].roadUser2, predParam, collisionDistanceThreshold, timeHorizon) |
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390 |
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391 # Ignore empty collision points |
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392 empty = 1 |
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393 for i in collisionPoints: |
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394 if(collisionPoints[i] != []): |
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395 empty = 0 |
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396 if(empty == 1): |
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397 self.pairs[j].hasCP = 0 |
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398 else: |
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399 self.pairs[j].hasCP = 1 |
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400 self.pairs[j].CP = collisionPoints |
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401 |
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402 # Ignore empty crossing zones |
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403 empty = 1 |
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404 for i in crossingZones: |
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405 if(crossingZones[i] != []): |
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406 empty = 0 |
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407 if(empty == 1): |
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408 self.pairs[j].hasCZ = 0 |
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409 else: |
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410 self.pairs[j].hasCZ = 1 |
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411 self.pairs[j].CZ = crossingZones |
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412 |
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413 for j in self.pairs: |
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414 self.interactionCount = self.interactionCount + len(j.CP) |
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415 self.CPcount = len(self.getCPlist()) |
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416 self.Czcount = len(self.getCZlist()) |
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417 |
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418 |
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419 def getPairsWCP(self): |
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420 lists = [] |
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421 for j in self.pairs: |
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422 if(j.hasCP): |
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423 lists.append(j.num) |
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424 return lists |
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425 |
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426 def getPairsWCZ(self): |
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427 lists = [] |
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428 for j in self.pairs: |
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429 if(j.hasCZ): |
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430 lists.append(j.num) |
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431 return lists |
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432 |
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433 def getCPlist(self,indicatorThreshold=float('Inf')): |
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434 lists = [] |
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435 for j in self.pairs: |
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436 if(j.hasCP): |
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437 for k in j.CP: |
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438 if(j.CP[k] != [] and j.CP[k][0].indicator < indicatorThreshold): |
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439 lists.append([k,j.CP[k][0]]) |
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440 return lists |
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441 |
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442 def getCZlist(self,indicatorThreshold=float('Inf')): |
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443 lists = [] |
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444 for j in self.pairs: |
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445 if(j.hasCZ): |
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446 for k in j.CZ: |
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447 if(j.CZ[k] != [] and j.CZ[k][0].indicator < indicatorThreshold): |
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448 lists.append([k,j.CZ[k][0]]) |
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449 return lists |
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450 |
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451 def genIndicatorHistogram(self, CPlist=False, bins=range(0,100,1)): |
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452 if(not CPlist): |
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453 CPlist = self.getCPlist() |
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454 if(not CPlist): |
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455 return False |
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456 TTC_list = [] |
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457 for i in CPlist: |
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458 TTC_list.append(i[1].indicator) |
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459 histo = np.histogram(TTC_list,bins=bins) |
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460 histo += (histo[0].astype(float)/np.sum(histo[0]),) |
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461 return histo |
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462 |
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463 class Crossing(moving.STObject): |
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464 '''Class for the event of a street crossing |
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465 |
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466 TODO: detecter passage sur la chaussee |
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467 identifier origines et destination (ou uniquement chaussee dans FOV) |
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468 carac traversee |
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469 detecter proximite veh (retirer si trop similaire simultanement |
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470 carac interaction''' |
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471 |
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472 def __init__(self, roaduserNum = None, num = None, timeInterval = None): |
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473 moving.STObject.__init__(self, num, timeInterval) |
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474 self.roaduserNum = roaduserNum |
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475 |
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476 |
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477 |
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478 if __name__ == "__main__": |
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479 import doctest |
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480 import unittest |
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489
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481 suite = doctest.DocFileSuite('tests/events.txt') |
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482 #suite = doctest.DocTestSuite() |
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483 unittest.TextTestRunner().run(suite) |
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484 |