Mercurial Hosting > traffic-intelligence
annotate python/extrapolation.py @ 251:4978b5baf8f1
Win32 version for traffic intelligence. Use the README-Win32.txt to know how to
fetch the dependencies. A batch file is included to automate most of the process
author | Jeep-Tour@Jeep-Tour-PC |
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date | Mon, 23 Jul 2012 12:27:50 -0400 |
parents | bd8ab323c198 |
children | 59f547aebaac |
rev | line source |
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1 #! /usr/bin/env python |
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2 '''Library for moving object extrapolation hypotheses''' |
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3 |
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4 import moving |
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5 |
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6 class ExtrapolatedTrajectory: |
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7 '''Class for extrapolated trajectories with lazy evaluation |
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8 if the predicted position has not been already computed, compute it |
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9 |
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10 it should also have a probability''' |
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11 def predictPosition(self, nTimeSteps): |
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12 return None |
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13 |
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14 class ExtrapolatedTrajectoryConstant(ExtrapolatedTrajectory): |
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15 '''Extrapolated trajectory at constant speed or acceleration |
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16 TODO add limits if acceleration |
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17 TODO generalize by passing a series of velocities/accelerations''' |
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18 |
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19 def __init__(self, initialPosition, initialVelocity, initialAccleration = 0, probability = 1): |
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20 self.initialPosition = initialPosition |
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21 self.initialVelocity = initialVelocity |
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22 self.initialAccleration = initialAccleration |
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23 self.probability = probability |
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24 self.predictedPositions = {} |
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25 self.predictedVelocities = {} |
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26 |
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27 def predictPosition(self, nTimeSteps): |
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28 if not nTimeSteps in self.predictedPositions.keys(): |
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29 self.predictedPositions[nTimeSteps] = moving.predictPosition(nTimeSteps, self.initialPosition, self.initialVelocity, self.initialAcceleration) |
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30 return self.predictedPositions[nTimeSteps] |
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31 |
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32 # Default values: to remove because we cannot tweak that from a script where the value may be different |
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33 FPS= 25 # No. of frame per second (FPS) |
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34 vLimit= 25/FPS #assume limit speed is 90km/hr = 25 m/sec |
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35 deltaT= FPS*5 # extrapolatation time Horizon = 5 second |
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36 |
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37 def motion (position, velocity, acceleration): |
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38 ''' extrapolation hypothesis: constant acceleration''' |
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39 from math import atan2,cos,sin |
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40 vInit= velocity |
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41 vInitial= velocity.norm2() |
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42 theta= atan2(velocity.y,velocity.x) |
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43 vFinal= vInitial+acceleration |
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44 |
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45 if acceleration<= 0: |
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46 v= max(0,vFinal) |
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47 velocity= moving.Point(v* cos(theta),v* sin(theta)) |
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48 position= position+ (velocity+vInit). multiply(0.5) |
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49 else: |
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50 v= min(vLimit,vFinal) |
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51 velocity= moving.Point(v* cos(theta),v* sin(theta)) |
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52 position= position+ (velocity+vInit). multiply(0.5) |
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53 return(position,velocity) |
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54 |
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55 def motionPET (position, velocity, acceleration, deltaT): |
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56 ''' extrapolation hypothesis: constant acceleration for calculating pPET ''' |
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57 from math import atan2,cos,sin,fabs |
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58 vInit= velocity |
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59 vInitial= velocity.norm2() |
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60 theta= atan2(velocity.y,velocity.x) |
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61 vFinal= vInitial+acceleration * deltaT |
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62 if acceleration< 0: |
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63 if vFinal> 0: |
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64 velocity= moving.Point(vFinal* cos(theta),vFinal* sin(theta)) |
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65 position= position+ (vInit+ velocity). multiply(0.5*deltaT) |
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66 else: |
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67 T= fabs(vInitial/acceleration) |
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68 position= position + vInit. multiply(0.5*T) |
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69 elif acceleration> 0 : |
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70 if vFinal<= vLimit: |
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71 velocity= moving.Point(vFinal* cos(theta),vFinal* sin(theta)) |
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72 position= position+ (vInit+ velocity). multiply(0.5*deltaT) |
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73 else: |
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74 time1= fabs((vLimit-vInitial)/acceleration) |
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75 velocity= moving.Point(vLimit* cos(theta),vLimit* sin(theta)) |
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76 position= (position+ (velocity+vInit). multiply(0.5*time1)) + (velocity.multiply (deltaT-time1)) |
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77 elif acceleration == 0: |
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78 position= position + velocity. multiply(deltaT) |
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79 |
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80 return position |
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81 |
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82 def timePET (position, velocity, acceleration, intersectedPoint ): |
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83 ''' extrapolation hypothesis: constant acceleration for calculating pPET ''' |
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84 from math import atan2,cos,sin,fabs |
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85 vInit= velocity |
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86 vInitial= velocity.norm2() |
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87 theta= atan2(velocity.y,velocity.x) |
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88 vFinal= vInitial+acceleration * deltaT |
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89 if acceleration< 0: |
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90 if vFinal> 0: |
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91 velocity= moving.Point(vFinal* cos(theta),vFinal* sin(theta)) |
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92 time= fabs((intersectedPoint.x-position.x)/(0.5*(vInit.x+ velocity.x))) |
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93 else: |
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94 time= fabs((intersectedPoint.x-position.x)/(0.5*(vInit.x))) |
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95 elif acceleration> 0 : |
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96 if vFinal<= vLimit: |
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97 velocity= moving.Point(vFinal* cos(theta),vFinal* sin(theta)) |
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98 time= fabs((intersectedPoint.x-position.x)/(0.5*(vInit.x+ velocity.x))) |
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99 else: |
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100 time1= fabs((vLimit-vInitial)/acceleration) |
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101 velocity= moving.Point(vLimit* cos(theta),vLimit* sin(theta)) |
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102 time2= fabs((intersectedPoint.x-position.x)/(0.5*(vInit.x+ velocity.x))) |
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103 if time2<=time1: |
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104 time= time2 |
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105 else: |
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106 position2= (position+ (velocity+vInit). multiply(0.5*time1)) |
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107 time= time1+fabs((intersectedPoint.x-position2.x)/( velocity.x)) |
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108 elif acceleration == 0: |
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109 time= fabs((intersectedPoint.x-position.x)/(velocity.x)) |
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110 |
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111 return time |
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112 |
243
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113 def motionSteering (position, velocity, deltaTheta, deltaT ): |
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114 ''' extrapolation hypothesis: steering with deltaTheta''' |
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115 from math import atan2,cos,sin |
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116 vInitial= velocity.norm2() |
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117 theta= atan2(velocity.y,velocity.x) |
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118 newTheta= theta + deltaTheta |
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119 velocity= moving.Point(vInitial* cos(newTheta),vInitial* sin(newTheta)) |
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120 position= position+ (velocity). multiply(deltaT) |
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121 return position |
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122 |
243
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123 def MonteCarlo(movingObject1,movingObject2, instant): |
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124 ''' Monte Carlo Simulation : estimate the probability of collision''' |
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125 from random import uniform |
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126 from math import pow, sqrt, sin, cos,atan2 |
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127 N=1000 |
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128 ProbOfCollision = 0 |
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129 for n in range (1, N): |
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130 # acceleration limit |
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131 acc1 = uniform(-0.040444,0) |
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132 acc2 = uniform(-0.040444,0) |
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133 p1= movingObject1.getPositionAtInstant(instant) |
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134 p2= movingObject2.getPositionAtInstant(instant) |
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135 v1= movingObject1.getVelocityAtInstant(instant) |
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136 v2= movingObject2.getVelocityAtInstant(instant) |
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137 distance= (p1-p2).norm2() |
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138 distanceThreshold= 1.8 |
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139 t=1 |
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140 while distance > distanceThreshold and t <= deltaT: |
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141 # Extrapolation position |
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142 (p1,v1) = motion(p1,v1,acc1) |
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143 (p2,v2) = motion(p2,v2,acc2) |
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144 distance= (p1-p2).norm2() |
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145 if distance <=distanceThreshold: |
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146 ProbOfCollision= ProbOfCollision+1 |
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147 t+=1 |
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148 POC= float(ProbOfCollision)/N |
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149 return POC |
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150 |
243
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151 def velocitySteering(velocity,steering): |
244
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152 from math import atan2,cos,sin |
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153 vInitial= velocity.norm2() |
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154 theta= atan2(velocity.y,velocity.x) |
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155 newTheta= theta + steering |
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156 v= moving.Point(vInitial* cos(newTheta),vInitial* sin(newTheta)) |
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157 return v |
243
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158 |
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159 def MonteCarloSteering(movingObject1,movingObject2, instant,steering1,steering2): |
244
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160 ''' Monte Carlo Simulation : estimate the probability of collision in case of steering''' |
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161 from random import uniform |
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162 from math import pow, sqrt, sin, cos,atan2 |
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163 N=1000 |
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164 L= 2.4 |
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165 ProbOfCollision = 0 |
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166 for n in range (1, N): |
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167 # acceleration limit |
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168 acc1 = uniform(-0.040444,0) |
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169 acc2 = uniform(-0.040444,0) |
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170 p1= movingObject1.getPositionAtInstant(instant) |
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171 p2= movingObject2.getPositionAtInstant(instant) |
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172 vInit1= movingObject1.getVelocityAtInstant(instant) |
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173 v1= velocitySteering (vInit1,steering1) |
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174 vInit2= movingObject2.getVelocityAtInstant(instant) |
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175 v2= velocitySteering (vInit2,steering2) |
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176 distance= (p1-p2).norm2() |
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177 distanceThreshold= 1.8 |
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178 t=1 |
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179 while distance > distanceThreshold and t <= deltaT: |
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180 # Extrapolation position |
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181 (p1,v1) = motion(p1,v1,acc1) |
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182 (p2,v2) = motion(p2,v2,acc2) |
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183 distance= (p1-p2).norm2() |
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184 if distance <=distanceThreshold: |
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185 ProbOfCollision= ProbOfCollision+1 |
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186 t+=1 |
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187 POC= float(ProbOfCollision)/N |
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188 return POC |
243
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189 |
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190 |