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comparison python/extrapolation.py @ 259:8ab76b95ee72

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added code to save collision points and crossing zones in txt files
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 24 Jul 2012 15:18:12 -0400
parents d90be3c02267
children 36cb40c51a5e
comparison
equal deleted inserted replaced
258:d90be3c02267 259:8ab76b95ee72
74 return [ExtrapolatedTrajectoryConstant(initialPosition, initialVelocity, maxSpeed = maxSpeed)] 74 return [ExtrapolatedTrajectoryConstant(initialPosition, initialVelocity, maxSpeed = maxSpeed)]
75 else: 75 else:
76 print('Unknown extrapolation hypothesis') 76 print('Unknown extrapolation hypothesis')
77 return [] 77 return []
78 78
79 class CollisionPoint(moving.Point): 79 class SafetyPoint(moving.Point):
80 def __init__(self, p, probability = 1., TTC = -1): 80 '''Can represent a collision point or crossing zone
81 with respective safety indicator, TTC or pPET'''
82 def __init__(self, p, probability = 1., indicator = -1):
81 self.x = p.x 83 self.x = p.x
82 self.y = p.y 84 self.y = p.y
83 self.probability = probability 85 self.probability = probability
84 self.TTC = TTC 86 self.indicator = indicator
85 87
86 class CrossingZone(moving.Point): 88 def computeExpectedIndicator(points):
87 def __init__(self, p, probability = 1., pPET = -1): 89 from numpy import sum
88 self.x = p.x 90 return sum([p.indicator*p.probability for p in points])/sum([p.probability for p in points])
89 self.y = p.y
90 self.probability = probability
91 self.pPET = pPET
92 91
93 def computeCrossingsCollisions(extrapolatedTrajectories1, extrapolatedTrajectories2, collisionDistanceThreshold, timeHorizon): 92 def computeCrossingsCollisions(extrapolatedTrajectories1, extrapolatedTrajectories2, collisionDistanceThreshold, timeHorizon):
94 '''returns the lists of collision points and crossing zones ''' 93 '''returns the lists of collision points and crossing zones '''
95 collisionPoints = [] 94 collisionPoints = []
96 crossingZones = [] 95 crossingZones = []
104 p1 = et1.predictPosition(t) 103 p1 = et1.predictPosition(t)
105 p2 = et2.predictPosition(t) 104 p2 = et2.predictPosition(t)
106 t += 1 105 t += 1
107 106
108 if t <= timeHorizon: 107 if t <= timeHorizon:
109 collisionPoints.append(CollisionPoint((p1+p2).multiply(0.5), et1.probability*et2.probability, t)) 108 collisionPoints.append(SafetyPoint((p1+p2).multiply(0.5), et1.probability*et2.probability, t))
110 else: # check if there is a crossing zone 109 else: # check if there is a crossing zone
111 # TODO? zone should be around the points at which the traj are the closest 110 # TODO? zone should be around the points at which the traj are the closest
112 # look for CZ at different times, otherwise it would be a collision 111 # look for CZ at different times, otherwise it would be a collision
113 # an approximation would be to look for close points at different times, ie the complementary of collision points 112 # an approximation would be to look for close points at different times, ie the complementary of collision points
114 cz = None 113 cz = None
118 while not cz and t2 < timeHorizon: 117 while not cz and t2 < timeHorizon:
119 #if (et1.predictPosition(t1)-et2.predictPosition(t2)).norm2() < collisionDistanceThreshold: 118 #if (et1.predictPosition(t1)-et2.predictPosition(t2)).norm2() < collisionDistanceThreshold:
120 # cz = (et1.predictPosition(t1)+et2.predictPosition(t2)).multiply(0.5) 119 # cz = (et1.predictPosition(t1)+et2.predictPosition(t2)).multiply(0.5)
121 cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1)) 120 cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1))
122 if cz: 121 if cz:
123 crossingZones.append(CrossingZone(cz, et1.probability*et2.probability, abs(t1-t2))) 122 crossingZones.append(SafetyPoint(cz, et1.probability*et2.probability, abs(t1-t2)))
124 t2 += 1 123 t2 += 1
125 t1 += 1 124 t1 += 1
126 return collisionPoints, crossingZones 125 return collisionPoints, crossingZones
127 126
128 127