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Motion Pattern Method
author MohamedGomaa
date Tue, 15 Jul 2014 13:25:15 -0400
parents 727e3c529519
children
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rev   line source
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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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12
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13 it should also have a probability'''
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14
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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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47
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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 findNearestOrientation(initialPosition,prototypeTrajectory):
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52 distances=[]
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53 for p in prototypeTrajectory.positions:
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54 distances.append(moving.Point.distanceNorm2(initialPosition, p))
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55 t=np.argmin(distances)
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56 return moving.NormAngle.fromPoint(prototypeTrajectory.velocities[t]).angle
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57 #todo: merge with previous function
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58 def findNearestInstant(initialPosition,prototypeTrajectory):
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59 distances=[]
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60 for p in prototypeTrajectory.positions:
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61 distances.append(moving.Point.distanceNorm2(initialPosition, p))
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62 t=np.argmin(distances)
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63 return t
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64
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65 class PredictedTrajectoryPrototype(PredictedTrajectory):
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66 '''Predicted trajectory that follows a prototype trajectory
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67 The prototype is in the format of a moving.Trajectory: it could be
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68 1. an observed trajectory (extracted from video)
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69 2. a generic polyline (eg the road centerline) that a vehicle is supposed to follow
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70
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71 Prediction can be done
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72 1. at constant speed (the instantaneous user speed)
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73 2. following the trajectory path, at the speed of the user
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74 (applying a constant ratio equal
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75 to the ratio of the user instantaneous speed and the trajectory closest speed)'''
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76
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77 def __init__(self, initialPosition, initialVelocity, prototypeTrajectory, constantSpeed = True, speedList=[], probability = 1.):
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78 self.prototypeTrajectory = prototypeTrajectory
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79 self.constantSpeed = constantSpeed
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80 self.speedList = speedList
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81 self.probability = probability
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82 self.predictedPositions = {0: initialPosition}
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83 self.predictedSpeedOrientations = {0: moving.NormAngle(moving.NormAngle.fromPoint(initialVelocity).norm, findNearestOrientation(initialPosition,prototypeTrajectory))}#moving.NormAngle.fromPoint(initialVelocity)}
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84
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85 def predictPosition(self, nTimeSteps):
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86 if nTimeSteps > 0 and not nTimeSteps in self.predictedPositions.keys():
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87 if self.constantSpeed:
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88 # calculate cumulative distance
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89 speedNorm= self.predictedSpeedOrientations[0].norm #moving.NormAngle.fromPoint(initialVelocity).norm
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90 anglePrototype = findNearestOrientation(self.predictedPositions[nTimeSteps-1],self.prototypeTrajectory)
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91 self.predictedSpeedOrientations[nTimeSteps]= moving.NormAngle(speedNorm, anglePrototype)
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92 self.predictedPositions[nTimeSteps],tmp= moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], moving.NormAngle(0,0), None)
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93 #pass
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94 elif self.speedList!=[]:
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95 pass
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96 else: # see c++ code, calculate ratio
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97 speedNorm= self.predictedSpeedOrientations[0].norm
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98 instant=findNearestInstant(self.predictedPositions[0],self.prototypeTrajectory)
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99 prototypeSpeeds= self.prototypeTrajectory.getSpeeds()[instant:]
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100 ratio=float(speedNorm)/prototypeSpeeds[0]
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101 resampledSpeeds=[sp*ratio for sp in prototypeSpeeds]
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102 anglePrototype = findNearestOrientation(self.predictedPositions[nTimeSteps-1],self.prototypeTrajectory)
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103 if nTimeSteps<len(resampledSpeeds):
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104 self.predictedSpeedOrientations[nTimeSteps]= moving.NormAngle(resampledSpeeds[nTimeSteps], anglePrototype)
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105 self.predictedPositions[nTimeSteps],tmp= moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], moving.NormAngle(0,0), None)
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106 else:
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107 self.predictedSpeedOrientations[nTimeSteps]= moving.NormAngle(resampledSpeeds[-1], anglePrototype)
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108 self.predictedPositions[nTimeSteps],tmp= moving.predictPosition(self.predictedPositions[nTimeSteps-1], self.predictedSpeedOrientations[nTimeSteps-1], moving.NormAngle(0,0), None)
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109 # pass
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110 return self.predictedPositions[nTimeSteps]
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111
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112 class PredictedTrajectoryRandomControl(PredictedTrajectory):
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113 '''Random vehicle control: suitable for normal adaptation'''
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114 def __init__(self, initialPosition, initialVelocity, accelerationDistribution, steeringDistribution, probability = 1., maxSpeed = None):
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115 '''Constructor
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116 accelerationDistribution and steeringDistribution are distributions
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117 that return random numbers drawn from them'''
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118 self.accelerationDistribution = accelerationDistribution
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119 self.steeringDistribution = steeringDistribution
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120 self.maxSpeed = maxSpeed
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121 self.probability = probability
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122 self.predictedPositions = {0: initialPosition}
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123 self.predictedSpeedOrientations = {0: moving.NormAngle.fromPoint(initialVelocity)}
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124
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125 def getControl(self):
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126 return moving.NormAngle(self.accelerationDistribution(),self.steeringDistribution())
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127
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128 class SafetyPoint(moving.Point):
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129 '''Can represent a collision point or crossing zone
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130 with respective safety indicator, TTC or pPET'''
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131 def __init__(self, p, probability = 1., indicator = -1):
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132 self.x = p.x
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133 self.y = p.y
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134 self.probability = probability
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135 self.indicator = indicator
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136
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137 def __str__(self):
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138 return '{0} {1} {2} {3}'.format(self.x, self.y, self.probability, self.indicator)
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139
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140 @staticmethod
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141 def save(out, points, predictionInstant, objNum1, objNum2):
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142 for p in points:
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143 out.write('{0} {1} {2} {3}\n'.format(objNum1, objNum2, predictionInstant, p))
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144
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145 @staticmethod
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146 def computeExpectedIndicator(points):
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147 from numpy import sum
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148 return sum([p.indicator*p.probability for p in points])/sum([p.probability for p in points])
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149
358
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150 def computeCollisionTime(predictedTrajectory1, predictedTrajectory2, collisionDistanceThreshold, timeHorizon):
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151 '''Computes the first instant at which two predicted trajectories are within some distance threshold'''
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152 t = 1
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153 p1 = predictedTrajectory1.predictPosition(t)
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154 p2 = predictedTrajectory2.predictPosition(t)
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155 while t <= timeHorizon and (p1-p2).norm2() > collisionDistanceThreshold:
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156 p1 = predictedTrajectory1.predictPosition(t)
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157 p2 = predictedTrajectory2.predictPosition(t)
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158 t += 1
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159 return t, p1, p2
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160
271
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161 class PredictionParameters:
266
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162 def __init__(self, name, maxSpeed):
257
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163 self.name = name
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164 self.maxSpeed = maxSpeed
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165
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166 def __str__(self):
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167 return '{0} {1}'.format(self.name, self.maxSpeed)
257
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168
358
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169 def generatePredictedTrajectories(self, obj, instant):
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170 return []
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171
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172 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,prototypeTrajectories1=None,prototypeTrajectories2=None):
359
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173 '''returns the lists of collision points and crossing zones'''
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174 if prototypeTrajectories1==None:
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175 predictedTrajectories1 = self.generatePredictedTrajectories(obj1, currentInstant)
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176 predictedTrajectories2 = self.generatePredictedTrajectories(obj2, currentInstant)
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177 else:
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178 predictedTrajectories1 = self.generatePredictedTrajectories(obj1, currentInstant,prototypeTrajectories1)
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179 predictedTrajectories2 = self.generatePredictedTrajectories(obj2, currentInstant,prototypeTrajectories2)
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180
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181 collisionPoints = []
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182 crossingZones = []
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183 for et1 in predictedTrajectories1:
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184 for et2 in predictedTrajectories2:
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185 t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
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186
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187 if t <= timeHorizon:
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188 collisionPoints.append(SafetyPoint((p1+p2).multiply(0.5), et1.probability*et2.probability, t))
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189 elif computeCZ: # check if there is a crossing zone
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190 # TODO? zone should be around the points at which the traj are the closest
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191 # look for CZ at different times, otherwise it would be a collision
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192 # an approximation would be to look for close points at different times, ie the complementary of collision points
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193 cz = None
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194 t1 = 0
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195 while not cz and t1 < timeHorizon: # t1 <= timeHorizon-1
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196 t2 = 0
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197 while not cz and t2 < timeHorizon:
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198 #if (et1.predictPosition(t1)-et2.predictPosition(t2)).norm2() < collisionDistanceThreshold:
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199 # cz = (et1.predictPosition(t1)+et2.predictPosition(t2)).multiply(0.5)
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200 cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1))
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201 if cz:
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202 deltaV= (et1.predictPosition(t1)- et1.predictPosition(t1+1) - et2.predictPosition(t2)+ et2.predictPosition(t2+1)).norm2()
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203 crossingZones.append(SafetyPoint(cz, et1.probability*et2.probability, abs(t1-t2)-(float(collisionDistanceThreshold)/deltaV)))
358
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204 t2 += 1
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205 t1 += 1
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206
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207 if debug:
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208 from matplotlib.pyplot import figure, axis, title
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209 figure()
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210 for et in predictedTrajectories1:
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211 et.predictPosition(timeHorizon)
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212 et.plot('rx')
358
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213
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214 for et in predictedTrajectories2:
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215 et.predictPosition(timeHorizon)
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216 et.plot('bx')
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217 obj1.plot('r')
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218 obj2.plot('b')
358
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219 title('instant {0}'.format(currentInstant))
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220 axis('equal')
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221
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222 return collisionPoints, crossingZones
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223
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224 def computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None,prototypeTrajectories1=None,prototypeTrajectories2=None):
358
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225 '''Computes all crossing and collision points at each common instant for two road users. '''
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226 collisionPoints={}
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227 crossingZones={}
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228 if timeInterval:
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229 commonTimeInterval = timeInterval
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230 else:
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231 commonTimeInterval = obj1.commonTimeInterval(obj2)
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232 for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
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233 collisionPoints[i], crossingZones[i] = self.computeCrossingsCollisionsAtInstant(i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)
358
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234
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235 return collisionPoints, crossingZones
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236
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237 def computeCollisionProbability(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, debug = False, timeInterval = None):
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238 '''Computes only collision probabilities
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diff changeset
239 Returns for each instant the collision probability and number of samples drawn'''
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diff changeset
240 collisionProbabilities = {}
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241 if timeInterval:
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242 commonTimeInterval = timeInterval
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243 else:
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244 commonTimeInterval = obj1.commonTimeInterval(obj2)
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245 for i in list(commonTimeInterval)[:-1]:
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diff changeset
246 nCollisions = 0
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diff changeset
247 print(obj1.num, obj2.num, i)
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diff changeset
248 predictedTrajectories1 = self.generatePredictedTrajectories(obj1, i)
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diff changeset
249 predictedTrajectories2 = self.generatePredictedTrajectories(obj2, i)
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diff changeset
250 for et1 in predictedTrajectories1:
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diff changeset
251 for et2 in predictedTrajectories2:
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diff changeset
252 t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
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diff changeset
253 if t <= timeHorizon:
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diff changeset
254 nCollisions += 1
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255 # take into account probabilities ??
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diff changeset
256 nSamples = float(len(predictedTrajectories1)*len(predictedTrajectories2))
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diff changeset
257 collisionProbabilities[i] = [nSamples, float(nCollisions)/nSamples]
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258
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259 if debug:
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
260 from matplotlib.pyplot import figure, axis, title
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261 figure()
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diff changeset
262 for et in predictedTrajectories1:
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
263 et.predictPosition(timeHorizon)
515
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
264 et.plot('rx')
358
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265
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266 for et in predictedTrajectories2:
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diff changeset
267 et.predictPosition(timeHorizon)
515
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268 et.plot('bx')
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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269 obj1.plot('r')
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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270 obj2.plot('b')
358
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271 title('instant {0}'.format(i))
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272 axis('equal')
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273
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274 return collisionProbabilities
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275
271
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276 class ConstantPredictionParameters(PredictionParameters):
268
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277 def __init__(self, maxSpeed):
271
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278 PredictionParameters.__init__(self, 'constant velocity', maxSpeed)
268
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279
271
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280 def generatePredictedTrajectories(self, obj, instant):
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281 return [PredictedTrajectoryConstant(obj.getPositionAtInstant(instant), obj.getVelocityAtInstant(instant),
268
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diff changeset
282 maxSpeed = self.maxSpeed)]
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283
271
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284 class NormalAdaptationPredictionParameters(PredictionParameters):
460
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
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285 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False):
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286 '''An example of acceleration and steering distributions is
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287 lambda: random.triangular(-self.maxAcceleration, self.maxAcceleration, 0.)
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288 '''
352
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289 if useFeatures:
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290 name = 'point set normal adaptation'
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291 else:
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292 name = 'normal adaptation'
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293 PredictionParameters.__init__(self, name, maxSpeed)
271
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294 self.nPredictedTrajectories = nPredictedTrajectories
352
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diff changeset
295 self.useFeatures = useFeatures
460
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296 self.accelerationDistribution = accelerationDistribution
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297 self.steeringDistribution = steeringDistribution
268
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298
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299 def __str__(self):
271
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300 return PredictionParameters.__str__(self)+' {0} {1} {2}'.format(self.nPredictedTrajectories,
352
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diff changeset
301 self.maxAcceleration,
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diff changeset
302 self.maxSteering)
268
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diff changeset
303
271
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diff changeset
304 def generatePredictedTrajectories(self, obj, instant):
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diff changeset
305 predictedTrajectories = []
352
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306 if self.useFeatures:
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307 features = [f for f in obj.features if f.existsAtInstant(instant)]
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diff changeset
308 positions = [f.getPositionAtInstant(instant) for f in features]
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diff changeset
309 velocities = [f.getVelocityAtInstant(instant) for f in features]
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310 else:
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311 positions = [obj.getPositionAtInstant(instant)]
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312 velocities = [obj.getVelocityAtInstant(instant)]
271
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diff changeset
313 for i in xrange(self.nPredictedTrajectories):
352
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diff changeset
314 for initialPosition,initialVelocity in zip(positions, velocities):
466
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parents: 464
diff changeset
315 predictedTrajectories.append(PredictedTrajectoryRandomControl(initialPosition,
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diff changeset
316 initialVelocity,
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diff changeset
317 self.accelerationDistribution,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
318 self.steeringDistribution,
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diff changeset
319 maxSpeed = self.maxSpeed))
271
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diff changeset
320 return predictedTrajectories
268
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diff changeset
321
271
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diff changeset
322 class PointSetPredictionParameters(PredictionParameters):
269
a9988971aac8 removed legacy code + tweaks
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diff changeset
323 # todo generate several trajectories with normal adaptatoins from each position (feature)
489
000bddf84ad0 corrected bugs in safety analysis
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diff changeset
324 def __init__(self, maxSpeed):
271
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diff changeset
325 PredictionParameters.__init__(self, 'point set', maxSpeed)
489
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diff changeset
326 #self.nPredictedTrajectories = nPredictedTrajectories
268
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diff changeset
327
271
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diff changeset
328 def generatePredictedTrajectories(self, obj, instant):
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diff changeset
329 predictedTrajectories = []
268
0c0b92f621f6 reorganized to compute evasive action for multiple positions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 267
diff changeset
330 features = [f for f in obj.features if f.existsAtInstant(instant)]
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diff changeset
331 positions = [f.getPositionAtInstant(instant) for f in features]
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parents: 267
diff changeset
332 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
333 #for i in xrange(self.nPredictedTrajectories):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
334 for initialPosition,initialVelocity in zip(positions, velocities):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 484
diff changeset
335 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition, initialVelocity,
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
336 maxSpeed = self.maxSpeed))
271
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diff changeset
337 return predictedTrajectories
268
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diff changeset
338
271
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diff changeset
339 class EvasiveActionPredictionParameters(PredictionParameters):
460
55b424d98b68 change of interface, distributions are now passed to the prediction paramters constructors if needed
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diff changeset
340 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False):
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diff changeset
341 '''Suggested acceleration distribution may not be symmetric, eg
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diff changeset
342 lambda: random.triangular(self.minAcceleration, self.maxAcceleration, 0.)'''
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diff changeset
343
268
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diff changeset
344 if useFeatures:
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diff changeset
345 name = 'point set evasive action'
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diff changeset
346 else:
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diff changeset
347 name = 'evasive action'
271
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diff changeset
348 PredictionParameters.__init__(self, name, maxSpeed)
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diff changeset
349 self.nPredictedTrajectories = nPredictedTrajectories
268
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diff changeset
350 self.useFeatures = useFeatures
460
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diff changeset
351 self.accelerationDistribution = accelerationDistribution
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diff changeset
352 self.steeringDistribution = steeringDistribution
268
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diff changeset
353
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diff changeset
354 def __str__(self):
271
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diff changeset
355 return PredictionParameters.__str__(self)+' {0} {1} {2} {3}'.format(self.nPredictedTrajectories, self.minAcceleration, self.maxAcceleration, self.maxSteering)
268
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diff changeset
356
271
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diff changeset
357 def generatePredictedTrajectories(self, obj, instant):
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diff changeset
358 predictedTrajectories = []
268
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diff changeset
359 if self.useFeatures:
267
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diff changeset
360 features = [f for f in obj.features if f.existsAtInstant(instant)]
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parents: 266
diff changeset
361 positions = [f.getPositionAtInstant(instant) for f in features]
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diff changeset
362 velocities = [f.getVelocityAtInstant(instant) for f in features]
268
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diff changeset
363 else:
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diff changeset
364 positions = [obj.getPositionAtInstant(instant)]
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diff changeset
365 velocities = [obj.getVelocityAtInstant(instant)]
271
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diff changeset
366 for i in xrange(self.nPredictedTrajectories):
267
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diff changeset
367 for initialPosition,initialVelocity in zip(positions, velocities):
271
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diff changeset
368 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition,
350
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parents: 336
diff changeset
369 initialVelocity,
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parents: 336
diff changeset
370 moving.NormAngle(self.accelerationDistribution(),
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parents: 336
diff changeset
371 self.steeringDistribution()),
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 336
diff changeset
372 maxSpeed = self.maxSpeed))
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
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parents: 270
diff changeset
373 return predictedTrajectories
257
9281878ff19e untested collision/crossing computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 256
diff changeset
374
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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375
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diff changeset
376 class CVDirectPredictionParameters(PredictionParameters):
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377 '''Prediction parameters of prediction at constant velocity
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diff changeset
378 using direct computation of the intersecting point'''
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parents: 358
diff changeset
379
387
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
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diff changeset
380 def __init__(self):
91679eb2ff2c cleaning up safety analysis and the new traditional constant velocity method
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diff changeset
381 PredictionParameters.__init__(self, 'constant velocity (direct computation)', None)
359
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382
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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parents: 358
diff changeset
383 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
384 collisionPoints = []
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
385 crossingZones = []
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parents: 358
diff changeset
386
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parents: 358
diff changeset
387 p1 = obj1.getPositionAtInstant(currentInstant)
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parents: 358
diff changeset
388 p2 = obj2.getPositionAtInstant(currentInstant)
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parents: 358
diff changeset
389 if (p1-p2).norm2() <= collisionDistanceThreshold:
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parents: 358
diff changeset
390 collisionPoints = [SafetyPoint((p1+p1).multiply(0.5), 1., 0.)]
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parents: 358
diff changeset
391 else:
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diff changeset
392 v1 = obj1.getVelocityAtInstant(currentInstant)
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parents: 358
diff changeset
393 v2 = obj2.getVelocityAtInstant(currentInstant)
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parents: 358
diff changeset
394 intersection = moving.intersection(p1, p2, v1, v2)
258
d90be3c02267 reasonably efficient computation of collision points and crossing zones
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parents: 257
diff changeset
395
359
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diff changeset
396 if intersection != None:
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
397 dp1 = intersection-p1
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diff changeset
398 dp2 = intersection-p2
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parents: 358
diff changeset
399 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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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
400 dist1 = dp1.norm2()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
401 dist2 = dp2.norm2()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
402 s1 = v1.norm2()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
403 s2 = v2.norm2()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
404 halfCollisionDistanceThreshold = collisionDistanceThreshold/2.
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parents: 358
diff changeset
405 timeInterval1 = moving.TimeInterval(max(0,dist1-halfCollisionDistanceThreshold)/s1, (dist1+halfCollisionDistanceThreshold)/s1)
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parents: 358
diff changeset
406 timeInterval2 = moving.TimeInterval(max(0,dist2-halfCollisionDistanceThreshold)/s2, (dist2+halfCollisionDistanceThreshold)/s2)
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parents: 358
diff changeset
407 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
408 if computeCZ and collisionTimeInterval.empty():
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 359
diff changeset
409 crossingZones = [SafetyPoint(intersection, 1., timeInterval1.distance(timeInterval2))]
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parents: 359
diff changeset
410 else:
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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diff changeset
411 collisionPoints = [SafetyPoint(intersection, 1., collisionTimeInterval.center())]
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parents: 358
diff changeset
412
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
413 if debug and intersection!= None:
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
414 from matplotlib.pyplot import plot, figure, axis, title
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 358
diff changeset
415 figure()
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parents: 358
diff changeset
416 plot([p1.x, intersection.x], [p1.y, intersection.y], 'r')
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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parents: 358
diff changeset
417 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
418 intersection.plot()
727e3c529519 renamed all draw functions to plot for consistency
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 489
diff changeset
419 obj1.plot('r')
727e3c529519 renamed all draw functions to plot for consistency
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 489
diff changeset
420 obj2.plot('b')
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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parents: 358
diff changeset
421 title('instant {0}'.format(currentInstant))
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parents: 358
diff changeset
422 axis('equal')
289
e56c34c1ebac refactored and commented functions (saving data is now outside of the computation functions)
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parents: 271
diff changeset
423
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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parents: 358
diff changeset
424 return collisionPoints, crossingZones
260
36cb40c51a5e modified the organization of the code
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 259
diff changeset
425
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
426 class CVExactPredictionParameters(PredictionParameters):
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
427 '''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
428 using direct computation of the intersecting point (solving for the equation'''
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
429
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
430 def __init__(self):
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
431 PredictionParameters.__init__(self, 'constant velocity (direct exact computation)', None)
359
619ae9a9a788 implemented prediction method at constant velocity with direct intersection computation
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parents: 358
diff changeset
432
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
433 def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
434 '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
435 #collisionPoints = []
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
436 #crossingZones = []
269
a9988971aac8 removed legacy code + tweaks
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 268
diff changeset
437
464
dcc821b98efc integrated and reorganized Sohail s work on exact ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
438 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
439 p2 = obj2.getPositionAtInstant(currentInstant)
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
440 v1 = obj1.getVelocityAtInstant(currentInstant)
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 460
diff changeset
441 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
442 intersection = moving.intersection(p1, p2, v1, v2)
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
443
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
444 if intersection != None:
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
445 ttc = moving.Point.timeToCollision(p1, p2, v1, v2, collisionDistanceThreshold)
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
446 if ttc:
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
447 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
448 else:
6464e4f0cc26 integrated Sohail direct computation of TTC (need to add pPET)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 470
diff changeset
449 return [],[]
260
36cb40c51a5e modified the organization of the code
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 259
diff changeset
450
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
451 ####
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
452 # 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
453 ####
604
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
454 class prototypePredictionParameters(PredictionParameters):
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
455 def __init__(self, maxSpeed, nPredictedTrajectories,constantSpeed = True, speedList=[]):
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
456 #TODO speed profiles integration
8ba4b8ad4c86 Motion Pattern Method
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parents: 515
diff changeset
457 name = 'prototype'
8ba4b8ad4c86 Motion Pattern Method
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parents: 515
diff changeset
458 PredictionParameters.__init__(self, name, maxSpeed)
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
459 self.nPredictedTrajectories = nPredictedTrajectories
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
460 #self.prototypeTrajectory = prototypeTrajectory
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
461 self.constantSpeed = constantSpeed
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
462 self.speedList = speedList
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
463 #self.probability=probability
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
464
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
465 def generatePredictedTrajectories(self, obj, instant,prototypeTrajectories):
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
466 predictedTrajectories = []
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
467 initialPosition = obj.getPositionAtInstant(instant)
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
468 initialVelocity = obj.getVelocityAtInstant(instant)
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
469 for prototypeTraj in prototypeTrajectories.keys():
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
470 predictedTrajectories.append(PredictedTrajectoryPrototype(initialPosition, initialVelocity, prototypeTraj, constantSpeed = self.constantSpeed, speedList=self.speedList, probability = prototypeTrajectories[prototypeTraj]))
8ba4b8ad4c86 Motion Pattern Method
MohamedGomaa
parents: 515
diff changeset
471 return predictedTrajectories
243
e0988a8ace0c started adapting and moving to other modules Mohamed's work
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 240
diff changeset
472
255
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
473 if __name__ == "__main__":
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
474 import doctest
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
475 import unittest
271
bbd9c09e6869 changed the names to prediction methods and predicted trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 270
diff changeset
476 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
477 #suite = doctest.DocTestSuite()
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
478 unittest.TextTestRunner().run(suite)
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
479 #doctest.testmod()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
480 #doctest.testfile("example.txt")
13ec22bec5d4 corrected typos and bugs and added a test
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 250
diff changeset
481