Mercurial Hosting > traffic-intelligence
comparison python/prediction.py @ 489:000bddf84ad0
corrected bugs in safety analysis
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Fri, 11 Apr 2014 17:47:38 -0400 |
parents | 6464e4f0cc26 |
children | 727e3c529519 |
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487:e04b22ce2fcd | 489:000bddf84ad0 |
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280 maxSpeed = self.maxSpeed)) | 280 maxSpeed = self.maxSpeed)) |
281 return predictedTrajectories | 281 return predictedTrajectories |
282 | 282 |
283 class PointSetPredictionParameters(PredictionParameters): | 283 class PointSetPredictionParameters(PredictionParameters): |
284 # todo generate several trajectories with normal adaptatoins from each position (feature) | 284 # todo generate several trajectories with normal adaptatoins from each position (feature) |
285 def __init__(self, nPredictedTrajectories, maxSpeed): | 285 def __init__(self, maxSpeed): |
286 PredictionParameters.__init__(self, 'point set', maxSpeed) | 286 PredictionParameters.__init__(self, 'point set', maxSpeed) |
287 self.nPredictedTrajectories = nPredictedTrajectories | 287 #self.nPredictedTrajectories = nPredictedTrajectories |
288 | 288 |
289 def generatePredictedTrajectories(self, obj, instant): | 289 def generatePredictedTrajectories(self, obj, instant): |
290 predictedTrajectories = [] | 290 predictedTrajectories = [] |
291 features = [f for f in obj.features if f.existsAtInstant(instant)] | 291 features = [f for f in obj.features if f.existsAtInstant(instant)] |
292 positions = [f.getPositionAtInstant(instant) for f in features] | 292 positions = [f.getPositionAtInstant(instant) for f in features] |
293 velocities = [f.getVelocityAtInstant(instant) for f in features] | 293 velocities = [f.getVelocityAtInstant(instant) for f in features] |
294 for i in xrange(self.nPredictedTrajectories): | 294 #for i in xrange(self.nPredictedTrajectories): |
295 for initialPosition,initialVelocity in zip(positions, velocities): | 295 for initialPosition,initialVelocity in zip(positions, velocities): |
296 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition, initialVelocity, | 296 predictedTrajectories.append(PredictedTrajectoryConstant(initialPosition, initialVelocity, |
297 maxSpeed = self.maxSpeed)) | 297 maxSpeed = self.maxSpeed)) |
298 return predictedTrajectories | 298 return predictedTrajectories |
299 | 299 |
300 class EvasiveActionPredictionParameters(PredictionParameters): | 300 class EvasiveActionPredictionParameters(PredictionParameters): |
301 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False): | 301 def __init__(self, maxSpeed, nPredictedTrajectories, accelerationDistribution, steeringDistribution, useFeatures = False): |
302 '''Suggested acceleration distribution may not be symmetric, eg | 302 '''Suggested acceleration distribution may not be symmetric, eg |