annotate python/prediction.py @ 607:84690dfe5560

add some functions for behaviour analysis
author MohamedGomaa
date Tue, 25 Nov 2014 22:49:47 -0500
parents a9c1d61a89b4
children 0dc36203973d
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1 #! /usr/bin/env python
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2 '''Library for motion prediction methods'''
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3
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4 import moving
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5 import math
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6 import random
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7 import numpy as np
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8
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9 class PredictedTrajectory:
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10 '''Class for predicted trajectories with lazy evaluation
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11 if the predicted position has not been already computed, compute it
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13 it should also have a probability'''
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15 def __init__(self):
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16 self.probability = 0.
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17 self.predictedPositions = {}
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18 self.predictedSpeedOrientations = {}
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19 #self.collisionPoints = {}
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20 #self.crossingZones = {}
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21
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22 def predictPosition(self, nTimeSteps):
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23 if nTimeSteps > 0 and not nTimeSteps in self.predictedPositions.keys():
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24 self.predictPosition(nTimeSteps-1)
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25 self.predictedPositions[nTimeSteps], self.predictedSpeedOrientations[nTimeSteps] = moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], self.getControl(), self.maxSpeed)
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26 return self.predictedPositions[nTimeSteps]
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27
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28 def getPredictedTrajectory(self):
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29 return moving.Trajectory.fromPointList(self.predictedPositions.values())
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30
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31 def getPredictedSpeeds(self):
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32 return [so.norm for so in self.predictedSpeedOrientations.values()]
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33
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34 def plot(self, options = '', withOrigin = False, timeStep = 1, **kwargs):
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35 self.getPredictedTrajectory().plot(options, withOrigin, timeStep, **kwargs)
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36
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37 class PredictedTrajectoryConstant(PredictedTrajectory):
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38 '''Predicted trajectory at constant speed or acceleration
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39 TODO generalize by passing a series of velocities/accelerations'''
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40
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41 def __init__(self, initialPosition, initialVelocity, control = moving.NormAngle(0,0), probability = 1., maxSpeed = None):
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42 self.control = control
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43 self.maxSpeed = maxSpeed
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44 self.probability = probability
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45 self.predictedPositions = {0: initialPosition}
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46 self.predictedSpeedOrientations = {0: moving.NormAngle.fromPoint(initialVelocity)}
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48 def getControl(self):
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49 return self.control
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50
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51 def findNearestParams(initialPosition,prototypeTrajectory):
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52 ''' nearest parameters are the index of minDistance and the orientation '''
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53 distances=[]
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54 for position in prototypeTrajectory.positions:
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55 distances.append(moving.Point.distanceNorm2(initialPosition, position))
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56 minDistanceIndex= np.argmin(distances)
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57 return minDistanceIndex, moving.NormAngle.fromPoint(prototypeTrajectory.velocities[minDistanceIndex]).angle
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58
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59 class PredictedTrajectoryPrototype(PredictedTrajectory):
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60 '''Predicted trajectory that follows a prototype trajectory
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61 The prototype is in the format of a moving.Trajectory: it could be
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62 1. an observed trajectory (extracted from video)
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63 2. a generic polyline (eg the road centerline) that a vehicle is supposed to follow
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64
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65 Prediction can be done
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66 1. at constant speed (the instantaneous user speed)
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67 2. following the trajectory path, at the speed of the user
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68 (applying a constant ratio equal
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69 to the ratio of the user instantaneous speed and the trajectory closest speed)'''
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71 def __init__(self, initialPosition, initialVelocity, prototypeTrajectory, constantSpeed = True, probability = 1.):
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72 self.prototypeTrajectory = prototypeTrajectory
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73 self.constantSpeed = constantSpeed
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74 self.probability = probability
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75 self.predictedPositions = {0: initialPosition}
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76 self.predictedSpeedOrientations = {0: moving.NormAngle(moving.NormAngle.fromPoint(initialVelocity).norm, findNearestParams(initialPosition,prototypeTrajectory)[1])}#moving.NormAngle.fromPoint(initialVelocity)}
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77
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78 def predictPosition(self, nTimeSteps):
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79 if nTimeSteps > 0 and not nTimeSteps in self.predictedPositions.keys():
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80 if self.constantSpeed:
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81 # calculate cumulative distance
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82 speedNorm= self.predictedSpeedOrientations[0].norm #moving.NormAngle.fromPoint(initialVelocity).norm
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83 anglePrototype = findNearestParams(self.predictedPositions[nTimeSteps-1],self.prototypeTrajectory)[1]
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84 self.predictedSpeedOrientations[nTimeSteps]= moving.NormAngle(speedNorm, anglePrototype)
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85 self.predictedPositions[nTimeSteps],tmp= moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], moving.NormAngle(0,0), None)
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86
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87 else: # see c++ code, calculate ratio
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88 speedNorm= self.predictedSpeedOrientations[0].norm
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89 instant=findNearestParams(self.predictedPositions[0],self.prototypeTrajectory)[0]
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90 prototypeSpeeds= self.prototypeTrajectory.getSpeeds()[instant:]
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91 ratio=float(speedNorm)/prototypeSpeeds[0]
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92 resampledSpeeds=[sp*ratio for sp in prototypeSpeeds]
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93 anglePrototype = findNearestParams(self.predictedPositions[nTimeSteps-1],self.prototypeTrajectory)[1]
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94 if nTimeSteps<len(resampledSpeeds):
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95 self.predictedSpeedOrientations[nTimeSteps]= moving.NormAngle(resampledSpeeds[nTimeSteps], anglePrototype)
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96 self.predictedPositions[nTimeSteps],tmp= moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], moving.NormAngle(0,0), None)
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97 else:
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98 self.predictedSpeedOrientations[nTimeSteps]= moving.NormAngle(resampledSpeeds[-1], anglePrototype)
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99 self.predictedPositions[nTimeSteps],tmp= moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], moving.NormAngle(0,0), None)
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101 return self.predictedPositions[nTimeSteps]
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102
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103 class PredictedTrajectoryRandomControl(PredictedTrajectory):
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104 '''Random vehicle control: suitable for normal adaptation'''
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105 def __init__(self, initialPosition, initialVelocity, accelerationDistribution, steeringDistribution, probability = 1., maxSpeed = None):
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106 '''Constructor
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107 accelerationDistribution and steeringDistribution are distributions
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108 that return random numbers drawn from them'''
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109 self.accelerationDistribution = accelerationDistribution
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110 self.steeringDistribution = steeringDistribution
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111 self.maxSpeed = maxSpeed
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112 self.probability = probability
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113 self.predictedPositions = {0: initialPosition}
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114 self.predictedSpeedOrientations = {0: moving.NormAngle.fromPoint(initialVelocity)}
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115
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116 def getControl(self):
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117 return moving.NormAngle(self.accelerationDistribution(),self.steeringDistribution())
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118
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119 class SafetyPoint(moving.Point):
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120 '''Can represent a collision point or crossing zone
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121 with respective safety indicator, TTC or pPET'''
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122 def __init__(self, p, probability = 1., indicator = -1):
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123 self.x = p.x
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124 self.y = p.y
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125 self.probability = probability
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126 self.indicator = indicator
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127
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128 def __str__(self):
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129 return '{0} {1} {2} {3}'.format(self.x, self.y, self.probability, self.indicator)
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130
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131 @staticmethod
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132 def save(out, points, predictionInstant, objNum1, objNum2):
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133 for p in points:
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134 out.write('{0} {1} {2} {3}\n'.format(objNum1, objNum2, predictionInstant, p))
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135
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136 @staticmethod
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137 def computeExpectedIndicator(points):
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138 from numpy import sum
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139 return sum([p.indicator*p.probability for p in points])/sum([p.probability for p in points])
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140
358
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141 def computeCollisionTime(predictedTrajectory1, predictedTrajectory2, collisionDistanceThreshold, timeHorizon):
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142 '''Computes the first instant at which two predicted trajectories are within some distance threshold'''
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143 t = 1
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144 p1 = predictedTrajectory1.predictPosition(t)
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145 p2 = predictedTrajectory2.predictPosition(t)
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146 while t <= timeHorizon and (p1-p2).norm2() > collisionDistanceThreshold:
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147 p1 = predictedTrajectory1.predictPosition(t)
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148 p2 = predictedTrajectory2.predictPosition(t)
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149 t += 1
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150 return t, p1, p2
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151
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152 def savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon):
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153 from matplotlib.pyplot import figure, axis, title, close, savefig
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154 figure()
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155 for et in predictedTrajectories1:
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156 et.predictPosition(timeHorizon)
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157 et.plot('rx')
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158
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159 for et in predictedTrajectories2:
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160 et.predictPosition(timeHorizon)
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161 et.plot('bx')
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162 obj1.plot('r')
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163 obj2.plot('b')
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164 title('instant {0}'.format(currentInstant))
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165 axis('equal')
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166 savefig('predicted-trajectories-t-{0}.png'.format(currentInstant))
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167 close()
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168
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169 def computeCrossingsCollisionsAtInstant(predictionParams,currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,prototypeTrajectories1=None,prototypeTrajectories2=None):
556
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170 '''returns the lists of collision points and crossing zones'''
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171 if prototypeTrajectories1==None:
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172 predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant)
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173 predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant)
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174 else:
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175 predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant,prototypeTrajectories1)
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176 predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant,prototypeTrajectories2)
556
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177
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178 collisionPoints = []
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179 crossingZones = []
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180 for et1 in predictedTrajectories1:
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181 for et2 in predictedTrajectories2:
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182 t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
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183
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184 if t <= timeHorizon:
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185 collisionPoints.append(SafetyPoint((p1+p2).multiply(0.5), et1.probability*et2.probability, t))
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186 elif computeCZ: # check if there is a crossing zone
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187 # TODO? zone should be around the points at which the traj are the closest
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188 # look for CZ at different times, otherwise it would be a collision
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189 # an approximation would be to look for close points at different times, ie the complementary of collision points
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190 cz = None
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191 t1 = 0
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192 while not cz and t1 < timeHorizon: # t1 <= timeHorizon-1
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193 t2 = 0
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194 while not cz and t2 < timeHorizon:
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195 #if (et1.predictPosition(t1)-et2.predictPosition(t2)).norm2() < collisionDistanceThreshold:
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196 # cz = (et1.predictPosition(t1)+et2.predictPosition(t2)).multiply(0.5)
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197 cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1))
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198 if cz:
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199 deltaV= (et1.predictPosition(t1)- et1.predictPosition(t1+1) - et2.predictPosition(t2)+ et2.predictPosition(t2+1)).norm2()
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200 crossingZones.append(SafetyPoint(cz, et1.probability*et2.probability, abs(t1-t2)-(float(collisionDistanceThreshold)/deltaV)))
556
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201 t2 += 1
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202 t1 += 1
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203
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204 if debug:
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205 savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon)
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206 return currentInstant,collisionPoints, crossingZones
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207
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208 def computeCrossingsCollisions(predictionParams, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None,nProcesses = 1,prototypeTrajectories1=None,prototypeTrajectories2=None):
556
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209 '''Computes all crossing and collision points at each common instant for two road users. '''
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210 collisionPoints={}
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211 crossingZones={}
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diff changeset
212 if timeInterval:
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213 commonTimeInterval = timeInterval
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214 else:
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215 commonTimeInterval = obj1.commonTimeInterval(obj2)
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216 if nProcesses == 1:
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diff changeset
217 for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
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218 i, cp, cz = computeCrossingsCollisionsAtInstant(predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)
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219 if len(cp) != 0:
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220 collisionPoints[i] = cp
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221 if len(cz) != 0:
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222 crossingZones[i] = cz
556
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223 else:
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diff changeset
224 from multiprocessing import Pool
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225 pool = Pool(processes = nProcesses)
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226 jobs = [pool.apply_async(computeCrossingsCollisionsAtInstant, args = (predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)) for i in list(commonTimeInterval)[:-1]]
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diff changeset
227 #results = [j.get() for j in jobs]
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228 #results.sort()
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229 for j in jobs:
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230 i, cp, cz = j.get()
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231 #if len(cp) != 0 or len(cz) != 0:
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232 if len(cp) != 0:
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233 collisionPoints[i] = cp
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234 if len(cz) != 0:
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235 crossingZones[i] = cz
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236 pool.close()
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237 return collisionPoints, crossingZones
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238
271
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239 class PredictionParameters:
266
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240 def __init__(self, name, maxSpeed):
257
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diff changeset
241 self.name = name
266
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242 self.maxSpeed = maxSpeed
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243
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244 def __str__(self):
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diff changeset
245 return '{0} {1}'.format(self.name, self.maxSpeed)
257
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246
358
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247 def generatePredictedTrajectories(self, obj, instant):
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248 return []
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249
607
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250 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,prototypeTrajectories1=None,prototypeTrajectories2=None):
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251 return computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)
358
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252
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253 def computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1,prototypeTrajectories1=None,prototypeTrajectories2=None):
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254 return computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, timeInterval, nProcesses,prototypeTrajectories1,prototypeTrajectories2)
358
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255
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256 def computeCollisionProbability(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, debug = False, timeInterval = None):
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257 '''Computes only collision probabilities
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258 Returns for each instant the collision probability and number of samples drawn'''
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259 collisionProbabilities = {}
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260 if timeInterval:
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261 commonTimeInterval = timeInterval
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262 else:
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263 commonTimeInterval = obj1.commonTimeInterval(obj2)
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264 for i in list(commonTimeInterval)[:-1]:
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265 nCollisions = 0
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266 predictedTrajectories1 = self.generatePredictedTrajectories(obj1, i)
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267 predictedTrajectories2 = self.generatePredictedTrajectories(obj2, i)
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268 for et1 in predictedTrajectories1:
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269 for et2 in predictedTrajectories2:
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270 t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
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271 if t <= timeHorizon:
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272 nCollisions += 1
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273 # take into account probabilities ??
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274 nSamples = float(len(predictedTrajectories1)*len(predictedTrajectories2))
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275 collisionProbabilities[i] = [nSamples, float(nCollisions)/nSamples]
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276
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277 if debug:
557
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278 savePredictedTrajectoriesFigure(i, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon)
358
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279
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280 return collisionProbabilities
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281
271
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282 class ConstantPredictionParameters(PredictionParameters):
268
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283 def __init__(self, maxSpeed):
271
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284 PredictionParameters.__init__(self, 'constant velocity', maxSpeed)
268
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285
271
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286 def generatePredictedTrajectories(self, obj, instant):
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287 return [PredictedTrajectoryConstant(obj.getPositionAtInstant(instant), obj.getVelocityAtInstant(instant),
268
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288 maxSpeed = self.maxSpeed)]
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289
271
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290 class NormalAdaptationPredictionParameters(PredictionParameters):
460
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291 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False):
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292 '''An example of acceleration and steering distributions is
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293 lambda: random.triangular(-self.maxAcceleration, self.maxAcceleration, 0.)
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294 '''
352
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295 if useFeatures:
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296 name = 'point set normal adaptation'
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297 else:
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298 name = 'normal adaptation'
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299 PredictionParameters.__init__(self, name, maxSpeed)
271
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300 self.nPredictedTrajectories = nPredictedTrajectories
352
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301 self.useFeatures = useFeatures
460
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302 self.accelerationDistribution = accelerationDistribution
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303 self.steeringDistribution = steeringDistribution
268
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304
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305 def __str__(self):
271
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306 return PredictionParameters.__str__(self)+' {0} {1} {2}'.format(self.nPredictedTrajectories,
352
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307 self.maxAcceleration,
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308 self.maxSteering)
268
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309
271
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310 def generatePredictedTrajectories(self, obj, instant):
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311 predictedTrajectories = []
352
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312 if self.useFeatures:
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313 features = [f for f in obj.features if f.existsAtInstant(instant)]
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314 positions = [f.getPositionAtInstant(instant) for f in features]
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315 velocities = [f.getVelocityAtInstant(instant) for f in features]
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316 else:
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317 positions = [obj.getPositionAtInstant(instant)]
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318 velocities = [obj.getVelocityAtInstant(instant)]
271
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319 for i in xrange(self.nPredictedTrajectories):
352
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diff changeset
320 for initialPosition,initialVelocity in zip(positions, velocities):
466
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diff changeset
321 predictedTrajectories.append(PredictedTrajectoryRandomControl(initialPosition,
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diff changeset
322 initialVelocity,
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diff changeset
323 self.accelerationDistribution,
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324 self.steeringDistribution,
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325 maxSpeed = self.maxSpeed))
271
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diff changeset
326 return predictedTrajectories
268
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diff changeset
327
271
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diff changeset
328 class PointSetPredictionParameters(PredictionParameters):
269
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diff changeset
329 # todo generate several trajectories with normal adaptatoins from each position (feature)
489
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diff changeset
330 def __init__(self, maxSpeed):
271
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diff changeset
331 PredictionParameters.__init__(self, 'point set', maxSpeed)
489
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diff changeset
332 #self.nPredictedTrajectories = nPredictedTrajectories
268
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diff changeset
333
271
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diff changeset
334 def generatePredictedTrajectories(self, obj, instant):
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diff changeset
335 predictedTrajectories = []
268
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diff changeset
336 features = [f for f in obj.features if f.existsAtInstant(instant)]
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diff changeset
337 positions = [f.getPositionAtInstant(instant) for f in features]
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diff changeset
338 velocities = [f.getVelocityAtInstant(instant) for f in features]
489
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diff changeset
339 #for i in xrange(self.nPredictedTrajectories):
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diff changeset
340 for initialPosition,initialVelocity in zip(positions, velocities):
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diff changeset
341 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition, initialVelocity,
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diff changeset
342 maxSpeed = self.maxSpeed))
271
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diff changeset
343 return predictedTrajectories
268
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344
271
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345 class EvasiveActionPredictionParameters(PredictionParameters):
460
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diff changeset
346 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False):
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diff changeset
347 '''Suggested acceleration distribution may not be symmetric, eg
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diff changeset
348 lambda: random.triangular(self.minAcceleration, self.maxAcceleration, 0.)'''
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diff changeset
349
268
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350 if useFeatures:
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351 name = 'point set evasive action'
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diff changeset
352 else:
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353 name = 'evasive action'
271
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diff changeset
354 PredictionParameters.__init__(self, name, maxSpeed)
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diff changeset
355 self.nPredictedTrajectories = nPredictedTrajectories
268
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diff changeset
356 self.useFeatures = useFeatures
460
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diff changeset
357 self.accelerationDistribution = accelerationDistribution
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diff changeset
358 self.steeringDistribution = steeringDistribution
268
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diff changeset
359
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diff changeset
360 def __str__(self):
271
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diff changeset
361 return PredictionParameters.__str__(self)+' {0} {1} {2} {3}'.format(self.nPredictedTrajectories, self.minAcceleration, self.maxAcceleration, self.maxSteering)
268
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diff changeset
362
271
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diff changeset
363 def generatePredictedTrajectories(self, obj, instant):
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parents: 270
diff changeset
364 predictedTrajectories = []
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
365 if self.useFeatures:
267
32e88b513f5c added code to compute probability of collision
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 266
diff changeset
366 features = [f for f in obj.features if f.existsAtInstant(instant)]
32e88b513f5c added code to compute probability of collision
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 266
diff changeset
367 positions = [f.getPositionAtInstant(instant) for f in features]
32e88b513f5c added code to compute probability of collision
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 266
diff changeset
368 velocities = [f.getVelocityAtInstant(instant) for f in features]
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
369 else:
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
370 positions = [obj.getPositionAtInstant(instant)]
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
371 velocities = [obj.getVelocityAtInstant(instant)]
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
372 for i in xrange(self.nPredictedTrajectories):
267
32e88b513f5c added code to compute probability of collision
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 266
diff changeset
373 for initialPosition,initialVelocity in zip(positions, velocities):
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
374 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition,
350
7e9ad2d9d79c added new parameters in safety analysis script
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
375 initialVelocity,
7e9ad2d9d79c added new parameters in safety analysis script
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
376 moving.NormAngle(self.accelerationDistribution(),
7e9ad2d9d79c added new parameters in safety analysis script
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
377 self.steeringDistribution()),
7e9ad2d9d79c added new parameters in safety analysis script
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
378 maxSpeed = self.maxSpeed))
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
379 return predictedTrajectories
257
9281878ff19e untested collision/crossing computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 256
diff changeset
380
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
381
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
382 class CVDirectPredictionParameters(PredictionParameters):
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
383 '''Prediction parameters of prediction at constant velocity
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
384 using direct computation of the intersecting point'''
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
385
387
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 359
diff changeset
386 def __init__(self):
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 359
diff changeset
387 PredictionParameters.__init__(self, 'constant velocity (direct computation)', None)
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
388
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
389 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
390 collisionPoints = []
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
391 crossingZones = []
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
392
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
393 p1 = obj1.getPositionAtInstant(currentInstant)
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
394 p2 = obj2.getPositionAtInstant(currentInstant)
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
395 if (p1-p2).norm2() <= collisionDistanceThreshold:
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
396 collisionPoints = [SafetyPoint((p1+p1).multiply(0.5), 1., 0.)]
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
397 else:
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
398 v1 = obj1.getVelocityAtInstant(currentInstant)
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
399 v2 = obj2.getVelocityAtInstant(currentInstant)
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
400 intersection = moving.intersection(p1, p2, v1, v2)
258
d90be3c02267 reasonably efficient computation of collision points and crossing zones
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 257
diff changeset
401
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
402 if intersection != None:
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
403 dp1 = intersection-p1
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
404 dp2 = intersection-p2
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
405 if moving.Point.dot(dp1, v1) > 0 and moving.Point.dot(dp2, v2) > 0: # if the road users are moving towards the intersection
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
406 dist1 = dp1.norm2()
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
407 dist2 = dp2.norm2()
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
408 s1 = v1.norm2()
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
409 s2 = v2.norm2()
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
410 halfCollisionDistanceThreshold = collisionDistanceThreshold/2.
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
411 timeInterval1 = moving.TimeInterval(max(0,dist1-halfCollisionDistanceThreshold)/s1, (dist1+halfCollisionDistanceThreshold)/s1)
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
412 timeInterval2 = moving.TimeInterval(max(0,dist2-halfCollisionDistanceThreshold)/s2, (dist2+halfCollisionDistanceThreshold)/s2)
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
413 collisionTimeInterval = moving.TimeInterval.intersection(timeInterval1, timeInterval2)
387
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 359
diff changeset
414 if computeCZ and collisionTimeInterval.empty():
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 359
diff changeset
415 crossingZones = [SafetyPoint(intersection, 1., timeInterval1.distance(timeInterval2))]
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 359
diff changeset
416 else:
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
417 collisionPoints = [SafetyPoint(intersection, 1., collisionTimeInterval.center())]
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
418
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
419 if debug and intersection!= None:
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
420 from matplotlib.pyplot import plot, figure, axis, title
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
421 figure()
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
422 plot([p1.x, intersection.x], [p1.y, intersection.y], 'r')
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
423 plot([p2.x, intersection.x], [p2.y, intersection.y], 'b')
515
727e3c529519 renamed all draw functions to plot for consistency
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 489
diff changeset
424 intersection.plot()
727e3c529519 renamed all draw functions to plot for consistency
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 489
diff changeset
425 obj1.plot('r')
727e3c529519 renamed all draw functions to plot for consistency
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 489
diff changeset
426 obj2.plot('b')
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
427 title('instant {0}'.format(currentInstant))
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
428 axis('equal')
289
e56c34c1ebac refactored and commented functions (saving data is now outside of the computation functions)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 271
diff changeset
429
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
430 return collisionPoints, crossingZones
260
36cb40c51a5e modified the organization of the code
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 259
diff changeset
431
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
432 class CVExactPredictionParameters(PredictionParameters):
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
433 '''Prediction parameters of prediction at constant velocity
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
434 using direct computation of the intersecting point (solving for the equation'''
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
435
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
436 def __init__(self):
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
437 PredictionParameters.__init__(self, 'constant velocity (direct exact computation)', None)
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
438
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
439 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
440 'TODO add collision point coordinates, compute pPET'
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
441 #collisionPoints = []
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
442 #crossingZones = []
269
a9988971aac8 removed legacy code + tweaks
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 268
diff changeset
443
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
444 p1 = obj1.getPositionAtInstant(currentInstant)
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
445 p2 = obj2.getPositionAtInstant(currentInstant)
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
446 v1 = obj1.getVelocityAtInstant(currentInstant)
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
447 v2 = obj2.getVelocityAtInstant(currentInstant)
484
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
448 intersection = moving.intersection(p1, p2, v1, v2)
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
449
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
450 if intersection != None:
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
451 ttc = moving.Point.timeToCollision(p1, p2, v1, v2, collisionDistanceThreshold)
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
452 if ttc:
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
453 return [SafetyPoint(intersection, 1., ttc)], [] # (p1+v1.multiply(ttc)+p2+v2.multiply(ttc)).multiply(0.5)
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
454 else:
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
455 return [],[]
260
36cb40c51a5e modified the organization of the code
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 259
diff changeset
456
357
e5fe0e6d48a1 corrected bug computing TTC (resp. pPET) if there is no collision point (resp. crossing zone)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 355
diff changeset
457 ####
e5fe0e6d48a1 corrected bug computing TTC (resp. pPET) if there is no collision point (resp. crossing zone)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 355
diff changeset
458 # Other Methods
e5fe0e6d48a1 corrected bug computing TTC (resp. pPET) if there is no collision point (resp. crossing zone)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 355
diff changeset
459 ####
607
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
460 class prototypePredictionParameters(PredictionParameters):
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
461 def __init__(self, maxSpeed, nPredictedTrajectories,constantSpeed = True):
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
462 name = 'prototype'
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
463 PredictionParameters.__init__(self, name, maxSpeed)
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
464 self.nPredictedTrajectories = nPredictedTrajectories
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
465 self.constantSpeed = constantSpeed
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
466
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
467 def generatePredictedTrajectories(self, obj, instant,prototypeTrajectories):
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
468 predictedTrajectories = []
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
469 initialPosition = obj.getPositionAtInstant(instant)
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
470 initialVelocity = obj.getVelocityAtInstant(instant)
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
471 for prototypeTraj in prototypeTrajectories.keys():
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
472 predictedTrajectories.append(PredictedTrajectoryPrototype(initialPosition, initialVelocity, prototypeTraj, constantSpeed = self.constantSpeed, probability = prototypeTrajectories[prototypeTraj]))
84690dfe5560 add some functions for behaviour analysis
MohamedGomaa
parents: 571
diff changeset
473 return predictedTrajectories
243
e0988a8ace0c started adapting and moving to other modules Mohamed's work
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 240
diff changeset
474
255
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
475 if __name__ == "__main__":
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
476 import doctest
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
477 import unittest
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
478 suite = doctest.DocFileSuite('tests/prediction.txt')
255
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
479 #suite = doctest.DocTestSuite()
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
480 unittest.TextTestRunner().run(suite)
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
481 #doctest.testmod()
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
482 #doctest.testfile("example.txt")
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
483