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annotate python/prediction.py @ 571:a9c1d61a89b4

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corrected bug for segment intersection
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 07 Aug 2014 00:05:14 -0400
parents 806df5f61c03
children 84690dfe5560
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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
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8 class PredictedTrajectory:
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9 '''Class for predicted trajectories with lazy evaluation
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10 if the predicted position has not been already computed, compute it
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11
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12 it should also have a probability'''
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13
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14 def __init__(self):
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15 self.probability = 0.
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16 self.predictedPositions = {}
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17 self.predictedSpeedOrientations = {}
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18 #self.collisionPoints = {}
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19 #self.crossingZones = {}
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20
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21 def predictPosition(self, nTimeSteps):
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22 if nTimeSteps > 0 and not nTimeSteps in self.predictedPositions.keys():
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23 self.predictPosition(nTimeSteps-1)
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24 self.predictedPositions[nTimeSteps], self.predictedSpeedOrientations[nTimeSteps] = moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], self.getControl(), self.maxSpeed)
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25 return self.predictedPositions[nTimeSteps]
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26
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27 def getPredictedTrajectory(self):
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28 return moving.Trajectory.fromPointList(self.predictedPositions.values())
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29
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30 def getPredictedSpeeds(self):
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31 return [so.norm for so in self.predictedSpeedOrientations.values()]
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32
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33 def plot(self, options = '', withOrigin = False, timeStep = 1, **kwargs):
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34 self.getPredictedTrajectory().plot(options, withOrigin, timeStep, **kwargs)
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35
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36 class PredictedTrajectoryConstant(PredictedTrajectory):
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37 '''Predicted trajectory at constant speed or acceleration
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38 TODO generalize by passing a series of velocities/accelerations'''
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39
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40 def __init__(self, initialPosition, initialVelocity, control = moving.NormAngle(0,0), probability = 1., maxSpeed = None):
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41 self.control = control
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42 self.maxSpeed = maxSpeed
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43 self.probability = probability
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44 self.predictedPositions = {0: initialPosition}
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45 self.predictedSpeedOrientations = {0: moving.NormAngle.fromPoint(initialVelocity)}
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46
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47 def getControl(self):
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48 return self.control
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49
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50 class PredictedTrajectoryPrototype(PredictedTrajectory):
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51 '''Predicted trajectory that follows a prototype trajectory
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52 The prototype is in the format of a moving.Trajectory: it could be
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53 1. an observed trajectory (extracted from video)
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54 2. a generic polyline (eg the road centerline) that a vehicle is supposed to follow
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55
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56 Prediction can be done
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57 1. at constant speed (the instantaneous user speed)
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58 2. following the trajectory path, at the speed of the user
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59 (applying a constant ratio equal
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60 to the ratio of the user instantaneous speed and the trajectory closest speed)'''
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61
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62 def __init__(self, initialPosition, initialVelocity, prototypeTrajectory, constantSpeed = True, probability = 1.):
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63 self.prototypeTrajectory = prototypeTrajectory
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64 self.constantSpeed = constantSpeed
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65 self.probability = probability
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66 self.predictedPositions = {0: initialPosition}
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67 self.predictedSpeedOrientations = {0: moving.NormAngle.fromPoint(initialVelocity)}
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68
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69 def predictPosition(self, nTimeSteps):
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70 if nTimeSteps > 0 and not nTimeSteps in self.predictedPositions.keys():
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71 if constantSpeed:
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72 # calculate cumulative distance
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73 pass
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74 else: # see c++ code, calculate ratio
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75 pass
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76 return self.predictedPositions[nTimeSteps]
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77
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78 class PredictedTrajectoryRandomControl(PredictedTrajectory):
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79 '''Random vehicle control: suitable for normal adaptation'''
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80 def __init__(self, initialPosition, initialVelocity, accelerationDistribution, steeringDistribution, probability = 1., maxSpeed = None):
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81 '''Constructor
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82 accelerationDistribution and steeringDistribution are distributions
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83 that return random numbers drawn from them'''
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84 self.accelerationDistribution = accelerationDistribution
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85 self.steeringDistribution = steeringDistribution
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86 self.maxSpeed = maxSpeed
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87 self.probability = probability
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88 self.predictedPositions = {0: initialPosition}
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89 self.predictedSpeedOrientations = {0: moving.NormAngle.fromPoint(initialVelocity)}
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90
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91 def getControl(self):
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92 return moving.NormAngle(self.accelerationDistribution(),self.steeringDistribution())
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93
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94 class SafetyPoint(moving.Point):
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95 '''Can represent a collision point or crossing zone
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96 with respective safety indicator, TTC or pPET'''
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97 def __init__(self, p, probability = 1., indicator = -1):
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98 self.x = p.x
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99 self.y = p.y
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100 self.probability = probability
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101 self.indicator = indicator
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102
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103 def __str__(self):
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104 return '{0} {1} {2} {3}'.format(self.x, self.y, self.probability, self.indicator)
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105
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106 @staticmethod
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107 def save(out, points, predictionInstant, objNum1, objNum2):
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108 for p in points:
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109 out.write('{0} {1} {2} {3}\n'.format(objNum1, objNum2, predictionInstant, p))
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110
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111 @staticmethod
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112 def computeExpectedIndicator(points):
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113 from numpy import sum
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114 return sum([p.indicator*p.probability for p in points])/sum([p.probability for p in points])
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115
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116 def computeCollisionTime(predictedTrajectory1, predictedTrajectory2, collisionDistanceThreshold, timeHorizon):
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117 '''Computes the first instant at which two predicted trajectories are within some distance threshold'''
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118 t = 1
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119 p1 = predictedTrajectory1.predictPosition(t)
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120 p2 = predictedTrajectory2.predictPosition(t)
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121 while t <= timeHorizon and (p1-p2).norm2() > collisionDistanceThreshold:
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122 p1 = predictedTrajectory1.predictPosition(t)
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123 p2 = predictedTrajectory2.predictPosition(t)
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124 t += 1
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125 return t, p1, p2
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126
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127 def savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon):
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128 from matplotlib.pyplot import figure, axis, title, close, savefig
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129 figure()
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130 for et in predictedTrajectories1:
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131 et.predictPosition(timeHorizon)
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132 et.plot('rx')
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133
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134 for et in predictedTrajectories2:
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135 et.predictPosition(timeHorizon)
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136 et.plot('bx')
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137 obj1.plot('r')
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138 obj2.plot('b')
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139 title('instant {0}'.format(currentInstant))
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140 axis('equal')
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141 savefig('predicted-trajectories-t-{0}.png'.format(currentInstant))
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142 close()
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143
556
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144 def computeCrossingsCollisionsAtInstant(predictionParams, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
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145 '''returns the lists of collision points and crossing zones'''
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146 predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant)
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147 predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant)
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148
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149 collisionPoints = []
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150 crossingZones = []
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151 for et1 in predictedTrajectories1:
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152 for et2 in predictedTrajectories2:
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153 t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
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154
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155 if t <= timeHorizon:
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156 collisionPoints.append(SafetyPoint((p1+p2).multiply(0.5), et1.probability*et2.probability, t))
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157 elif computeCZ: # check if there is a crossing zone
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158 # TODO? zone should be around the points at which the traj are the closest
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159 # look for CZ at different times, otherwise it would be a collision
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160 # an approximation would be to look for close points at different times, ie the complementary of collision points
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161 cz = None
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162 t1 = 0
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163 while not cz and t1 < timeHorizon: # t1 <= timeHorizon-1
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164 t2 = 0
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165 while not cz and t2 < timeHorizon:
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166 #if (et1.predictPosition(t1)-et2.predictPosition(t2)).norm2() < collisionDistanceThreshold:
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167 # cz = (et1.predictPosition(t1)+et2.predictPosition(t2)).multiply(0.5)
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168 cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1))
571
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169 if cz != None:
556
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170 crossingZones.append(SafetyPoint(cz, et1.probability*et2.probability, abs(t1-t2)))
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171 t2 += 1
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172 t1 += 1
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173
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174 if debug:
557
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175 savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon)
556
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176
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177 return currentInstant, collisionPoints, crossingZones
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178
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179 def computeCrossingsCollisions(predictionParams, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1):
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180 '''Computes all crossing and collision points at each common instant for two road users. '''
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181 collisionPoints={}
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182 crossingZones={}
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183 if timeInterval:
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184 commonTimeInterval = timeInterval
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185 else:
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186 commonTimeInterval = obj1.commonTimeInterval(obj2)
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187 if nProcesses == 1:
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188 for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
559
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189 i, cp, cz = computeCrossingsCollisionsAtInstant(predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug)
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190 if len(cp) != 0:
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191 collisionPoints[i] = cp
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192 if len(cz) != 0:
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193 crossingZones[i] = cz
556
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194 else:
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195 from multiprocessing import Pool
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196 pool = Pool(processes = nProcesses)
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197 jobs = [pool.apply_async(computeCrossingsCollisionsAtInstant, args = (predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug)) for i in list(commonTimeInterval)[:-1]]
556
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198 #results = [j.get() for j in jobs]
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199 #results.sort()
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200 for j in jobs:
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diff changeset
201 i, cp, cz = j.get()
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diff changeset
202 #if len(cp) != 0 or len(cz) != 0:
559
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203 if len(cp) != 0:
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204 collisionPoints[i] = cp
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205 if len(cz) != 0:
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diff changeset
206 crossingZones[i] = cz
556
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diff changeset
207 pool.close()
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diff changeset
208 return collisionPoints, crossingZones
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209
271
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210 class PredictionParameters:
266
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211 def __init__(self, name, maxSpeed):
257
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212 self.name = name
266
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213 self.maxSpeed = maxSpeed
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214
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215 def __str__(self):
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diff changeset
216 return '{0} {1}'.format(self.name, self.maxSpeed)
257
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217
358
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218 def generatePredictedTrajectories(self, obj, instant):
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219 return []
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220
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221 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
557
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diff changeset
222 return computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug)
358
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223
556
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224 def computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1):
557
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diff changeset
225 return computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, timeInterval, nProcesses)
358
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226
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diff changeset
227 def computeCollisionProbability(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, debug = False, timeInterval = None):
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228 '''Computes only collision probabilities
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diff changeset
229 Returns for each instant the collision probability and number of samples drawn'''
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diff changeset
230 collisionProbabilities = {}
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231 if timeInterval:
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232 commonTimeInterval = timeInterval
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233 else:
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diff changeset
234 commonTimeInterval = obj1.commonTimeInterval(obj2)
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diff changeset
235 for i in list(commonTimeInterval)[:-1]:
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
236 nCollisions = 0
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
237 predictedTrajectories1 = self.generatePredictedTrajectories(obj1, i)
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
238 predictedTrajectories2 = self.generatePredictedTrajectories(obj2, i)
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
239 for et1 in predictedTrajectories1:
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
240 for et2 in predictedTrajectories2:
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
241 t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
242 if t <= timeHorizon:
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
243 nCollisions += 1
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
244 # take into account probabilities ??
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
245 nSamples = float(len(predictedTrajectories1)*len(predictedTrajectories2))
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
246 collisionProbabilities[i] = [nSamples, float(nCollisions)/nSamples]
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
247
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
248 if debug:
557
b91f33e098ee refactored some more code in compute crossing and collisions (parallel code works)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 556
diff changeset
249 savePredictedTrajectoriesFigure(i, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon)
358
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
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parents: 357
diff changeset
250
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 357
diff changeset
251 return collisionProbabilities
c41ff9f3c263 moved current method for collision points and crossing zones computation into prediction parameters (put expectedindicator in SafetyPoint)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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252
271
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253 class ConstantPredictionParameters(PredictionParameters):
268
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254 def __init__(self, maxSpeed):
271
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255 PredictionParameters.__init__(self, 'constant velocity', maxSpeed)
268
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diff changeset
256
271
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257 def generatePredictedTrajectories(self, obj, instant):
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diff changeset
258 return [PredictedTrajectoryConstant(obj.getPositionAtInstant(instant), obj.getVelocityAtInstant(instant),
268
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parents: 267
diff changeset
259 maxSpeed = self.maxSpeed)]
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parents: 267
diff changeset
260
271
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diff changeset
261 class NormalAdaptationPredictionParameters(PredictionParameters):
460
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
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diff changeset
262 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False):
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263 '''An example of acceleration and steering distributions is
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diff changeset
264 lambda: random.triangular(-self.maxAcceleration, self.maxAcceleration, 0.)
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265 '''
352
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266 if useFeatures:
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parents: 350
diff changeset
267 name = 'point set normal adaptation'
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parents: 350
diff changeset
268 else:
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parents: 350
diff changeset
269 name = 'normal adaptation'
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diff changeset
270 PredictionParameters.__init__(self, name, maxSpeed)
271
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parents: 270
diff changeset
271 self.nPredictedTrajectories = nPredictedTrajectories
352
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diff changeset
272 self.useFeatures = useFeatures
460
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
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diff changeset
273 self.accelerationDistribution = accelerationDistribution
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diff changeset
274 self.steeringDistribution = steeringDistribution
268
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parents: 267
diff changeset
275
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parents: 267
diff changeset
276 def __str__(self):
271
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parents: 270
diff changeset
277 return PredictionParameters.__str__(self)+' {0} {1} {2}'.format(self.nPredictedTrajectories,
352
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parents: 350
diff changeset
278 self.maxAcceleration,
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parents: 350
diff changeset
279 self.maxSteering)
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
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parents: 267
diff changeset
280
271
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diff changeset
281 def generatePredictedTrajectories(self, obj, instant):
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parents: 270
diff changeset
282 predictedTrajectories = []
352
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diff changeset
283 if self.useFeatures:
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diff changeset
284 features = [f for f in obj.features if f.existsAtInstant(instant)]
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diff changeset
285 positions = [f.getPositionAtInstant(instant) for f in features]
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diff changeset
286 velocities = [f.getVelocityAtInstant(instant) for f in features]
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diff changeset
287 else:
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diff changeset
288 positions = [obj.getPositionAtInstant(instant)]
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diff changeset
289 velocities = [obj.getVelocityAtInstant(instant)]
271
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parents: 270
diff changeset
290 for i in xrange(self.nPredictedTrajectories):
352
72aa44072093 safety analysis script with option for prediction method
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parents: 350
diff changeset
291 for initialPosition,initialVelocity in zip(positions, velocities):
466
e891a41c6c75 name change in prediction.py
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parents: 464
diff changeset
292 predictedTrajectories.append(PredictedTrajectoryRandomControl(initialPosition,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 464
diff changeset
293 initialVelocity,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 464
diff changeset
294 self.accelerationDistribution,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 464
diff changeset
295 self.steeringDistribution,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 464
diff changeset
296 maxSpeed = self.maxSpeed))
271
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parents: 270
diff changeset
297 return predictedTrajectories
268
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parents: 267
diff changeset
298
271
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diff changeset
299 class PointSetPredictionParameters(PredictionParameters):
269
a9988971aac8 removed legacy code + tweaks
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parents: 268
diff changeset
300 # todo generate several trajectories with normal adaptatoins from each position (feature)
489
000bddf84ad0 corrected bugs in safety analysis
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parents: 484
diff changeset
301 def __init__(self, maxSpeed):
271
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diff changeset
302 PredictionParameters.__init__(self, 'point set', maxSpeed)
489
000bddf84ad0 corrected bugs in safety analysis
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
303 #self.nPredictedTrajectories = nPredictedTrajectories
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
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parents: 267
diff changeset
304
271
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diff changeset
305 def generatePredictedTrajectories(self, obj, instant):
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parents: 270
diff changeset
306 predictedTrajectories = []
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
307 features = [f for f in obj.features if f.existsAtInstant(instant)]
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parents: 267
diff changeset
308 positions = [f.getPositionAtInstant(instant) for f in features]
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
309 velocities = [f.getVelocityAtInstant(instant) for f in features]
489
000bddf84ad0 corrected bugs in safety analysis
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
310 #for i in xrange(self.nPredictedTrajectories):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
311 for initialPosition,initialVelocity in zip(positions, velocities):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
312 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition, initialVelocity,
000bddf84ad0 corrected bugs in safety analysis
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
313 maxSpeed = self.maxSpeed))
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
314 return predictedTrajectories
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
315
271
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diff changeset
316 class EvasiveActionPredictionParameters(PredictionParameters):
460
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 387
diff changeset
317 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False):
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 387
diff changeset
318 '''Suggested acceleration distribution may not be symmetric, eg
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
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parents: 387
diff changeset
319 lambda: random.triangular(self.minAcceleration, self.maxAcceleration, 0.)'''
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parents: 387
diff changeset
320
268
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parents: 267
diff changeset
321 if useFeatures:
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
322 name = 'point set evasive action'
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
323 else:
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parents: 267
diff changeset
324 name = 'evasive action'
271
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diff changeset
325 PredictionParameters.__init__(self, name, maxSpeed)
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parents: 270
diff changeset
326 self.nPredictedTrajectories = nPredictedTrajectories
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
327 self.useFeatures = useFeatures
460
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 387
diff changeset
328 self.accelerationDistribution = accelerationDistribution
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 387
diff changeset
329 self.steeringDistribution = steeringDistribution
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
330
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
331 def __str__(self):
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
332 return PredictionParameters.__str__(self)+' {0} {1} {2} {3}'.format(self.nPredictedTrajectories, self.minAcceleration, self.maxAcceleration, self.maxSteering)
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
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parents: 267
diff changeset
333
271
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parents: 270
diff changeset
334 def generatePredictedTrajectories(self, obj, instant):
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parents: 270
diff changeset
335 predictedTrajectories = []
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
336 if self.useFeatures:
267
32e88b513f5c added code to compute probability of collision
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 266
diff changeset
337 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
338 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
339 velocities = [f.getVelocityAtInstant(instant) for f in features]
268
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
340 else:
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parents: 267
diff changeset
341 positions = [obj.getPositionAtInstant(instant)]
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parents: 267
diff changeset
342 velocities = [obj.getVelocityAtInstant(instant)]
271
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
343 for i in xrange(self.nPredictedTrajectories):
267
32e88b513f5c added code to compute probability of collision
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parents: 266
diff changeset
344 for initialPosition,initialVelocity in zip(positions, velocities):
271
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parents: 270
diff changeset
345 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition,
350
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
346 initialVelocity,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
347 moving.NormAngle(self.accelerationDistribution(),
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
348 self.steeringDistribution()),
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
349 maxSpeed = self.maxSpeed))
271
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
350 return predictedTrajectories
257
9281878ff19e untested collision/crossing computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 256
diff changeset
351
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
352
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
353 class CVDirectPredictionParameters(PredictionParameters):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
354 '''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
355 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
356
387
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
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diff changeset
357 def __init__(self):
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358 PredictionParameters.__init__(self, 'constant velocity (direct computation)', None)
359
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359
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360 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
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361 collisionPoints = []
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362 crossingZones = []
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363
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364 p1 = obj1.getPositionAtInstant(currentInstant)
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365 p2 = obj2.getPositionAtInstant(currentInstant)
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366 if (p1-p2).norm2() <= collisionDistanceThreshold:
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diff changeset
367 collisionPoints = [SafetyPoint((p1+p1).multiply(0.5), 1., 0.)]
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368 else:
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369 v1 = obj1.getVelocityAtInstant(currentInstant)
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370 v2 = obj2.getVelocityAtInstant(currentInstant)
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371 intersection = moving.intersection(p1, p2, v1, v2)
258
d90be3c02267 reasonably efficient computation of collision points and crossing zones
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372
359
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373 if intersection != None:
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374 dp1 = intersection-p1
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375 dp2 = intersection-p2
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376 if moving.Point.dot(dp1, v1) > 0 and moving.Point.dot(dp2, v2) > 0: # if the road users are moving towards the intersection
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377 dist1 = dp1.norm2()
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378 dist2 = dp2.norm2()
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379 s1 = v1.norm2()
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380 s2 = v2.norm2()
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381 halfCollisionDistanceThreshold = collisionDistanceThreshold/2.
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382 timeInterval1 = moving.TimeInterval(max(0,dist1-halfCollisionDistanceThreshold)/s1, (dist1+halfCollisionDistanceThreshold)/s1)
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383 timeInterval2 = moving.TimeInterval(max(0,dist2-halfCollisionDistanceThreshold)/s2, (dist2+halfCollisionDistanceThreshold)/s2)
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diff changeset
384 collisionTimeInterval = moving.TimeInterval.intersection(timeInterval1, timeInterval2)
387
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diff changeset
385 if computeCZ and collisionTimeInterval.empty():
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386 crossingZones = [SafetyPoint(intersection, 1., timeInterval1.distance(timeInterval2))]
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diff changeset
387 else:
359
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388 collisionPoints = [SafetyPoint(intersection, 1., collisionTimeInterval.center())]
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389
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390 if debug and intersection!= None:
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diff changeset
391 from matplotlib.pyplot import plot, figure, axis, title
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392 figure()
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393 plot([p1.x, intersection.x], [p1.y, intersection.y], 'r')
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diff changeset
394 plot([p2.x, intersection.x], [p2.y, intersection.y], 'b')
515
727e3c529519 renamed all draw functions to plot for consistency
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diff changeset
395 intersection.plot()
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parents: 489
diff changeset
396 obj1.plot('r')
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diff changeset
397 obj2.plot('b')
359
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diff changeset
398 title('instant {0}'.format(currentInstant))
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diff changeset
399 axis('equal')
289
e56c34c1ebac refactored and commented functions (saving data is now outside of the computation functions)
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diff changeset
400
359
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diff changeset
401 return collisionPoints, crossingZones
260
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diff changeset
402
464
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diff changeset
403 class CVExactPredictionParameters(PredictionParameters):
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diff changeset
404 '''Prediction parameters of prediction at constant velocity
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diff changeset
405 using direct computation of the intersecting point (solving for the equation'''
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parents: 460
diff changeset
406
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diff changeset
407 def __init__(self):
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
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diff changeset
408 PredictionParameters.__init__(self, 'constant velocity (direct exact computation)', None)
359
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parents: 358
diff changeset
409
464
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diff changeset
410 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
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diff changeset
411 'TODO add collision point coordinates, compute pPET'
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diff changeset
412 #collisionPoints = []
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diff changeset
413 #crossingZones = []
269
a9988971aac8 removed legacy code + tweaks
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diff changeset
414
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
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diff changeset
415 p1 = obj1.getPositionAtInstant(currentInstant)
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parents: 460
diff changeset
416 p2 = obj2.getPositionAtInstant(currentInstant)
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parents: 460
diff changeset
417 v1 = obj1.getVelocityAtInstant(currentInstant)
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parents: 460
diff changeset
418 v2 = obj2.getVelocityAtInstant(currentInstant)
484
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
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parents: 470
diff changeset
419 intersection = moving.intersection(p1, p2, v1, v2)
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parents: 470
diff changeset
420
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diff changeset
421 if intersection != None:
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parents: 470
diff changeset
422 ttc = moving.Point.timeToCollision(p1, p2, v1, v2, collisionDistanceThreshold)
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diff changeset
423 if ttc:
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diff changeset
424 return [SafetyPoint(intersection, 1., ttc)], [] # (p1+v1.multiply(ttc)+p2+v2.multiply(ttc)).multiply(0.5)
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
425 else:
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diff changeset
426 return [],[]
260
36cb40c51a5e modified the organization of the code
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diff changeset
427
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
428 ####
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
429 # Other Methods
e5fe0e6d48a1 corrected bug computing TTC (resp. pPET) if there is no collision point (resp. crossing zone)
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parents: 355
diff changeset
430 ####
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
431
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
432
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
433
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
434
243
e0988a8ace0c started adapting and moving to other modules Mohamed's work
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 240
diff changeset
435
255
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
436 if __name__ == "__main__":
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
437 import doctest
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
438 import unittest
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
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parents: 270
diff changeset
439 suite = doctest.DocFileSuite('tests/prediction.txt')
255
13ec22bec5d4 corrected typos and bugs and added a test
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parents: 250
diff changeset
440 #suite = doctest.DocTestSuite()
13ec22bec5d4 corrected typos and bugs and added a test
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parents: 250
diff changeset
441 unittest.TextTestRunner().run(suite)
13ec22bec5d4 corrected typos and bugs and added a test
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parents: 250
diff changeset
442 #doctest.testmod()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
443 #doctest.testfile("example.txt")
13ec22bec5d4 corrected typos and bugs and added a test
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parents: 250
diff changeset
444