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annotate scripts/safety-analysis.py @ 939:a2f3f3ca241e

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work in progress
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 17 Jul 2017 17:56:52 -0400
parents 063d1267585d
children b1e8453c207c
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1 #! /usr/bin/env python
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3 import storage, prediction, events, moving
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5 import sys, argparse, random
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6
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7 import matplotlib.pyplot as plt
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8 import numpy as np
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10 # todo: very slow if too many predicted trajectories
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11 # add computation of probality of unsucessful evasive action
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12
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13 parser = argparse.ArgumentParser(description='The program processes indicators for all pairs of road users in the scene')
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14 parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file', required = True)
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15 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects to analyse', type = int)
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16 # TODO analyze only
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17 parser.add_argument('--prediction-method', dest = 'predictionMethod', help = 'prediction method (constant velocity (cvd: vector computation (approximate); cve: equation solving; cv: discrete time (approximate)), normal adaptation, point set prediction)', choices = ['cvd', 'cve', 'cv', 'na', 'ps', 'proto'])
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18 parser.add_argument('--cfg', dest = 'prototypeDatabaseFilename', help = 'name of the database containing the prototypes')
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19 parser.add_argument('--pet', dest = 'computePET', help = 'computes PET', action = 'store_true')
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20 parser.add_argument('--display-cp', dest = 'displayCollisionPoints', help = 'display collision points', action = 'store_true')
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21 parser.add_argument('--nthreads', dest = 'nProcesses', help = 'number of processes to run in parallel', type = int, default = 1)
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22 args = parser.parse_args()
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23
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24 params = storage.ProcessParameters(args.configFilename)
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26 # parameters for prediction methods
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27 if args.predictionMethod is not None:
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28 predictionMethod = args.predictionMethod
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29 else:
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30 predictionMethod = params.predictionMethod
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32 def accelerationDistribution():
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33 return random.triangular(-params.maxNormalAcceleration, params.maxNormalAcceleration, 0.)
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34 def steeringDistribution():
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35 return random.triangular(-params.maxNormalSteering, params.maxNormalSteering, 0.)
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37 if predictionMethod == 'cvd':
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38 predictionParameters = prediction.CVDirectPredictionParameters()
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39 if predictionMethod == 'cve':
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40 predictionParameters = prediction.CVExactPredictionParameters()
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41 elif predictionMethod == 'cv':
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42 predictionParameters = prediction.ConstantPredictionParameters(params.maxPredictedSpeed)
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43 elif predictionMethod == 'na':
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44 predictionParameters = prediction.NormalAdaptationPredictionParameters(params.maxPredictedSpeed,
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45 params.nPredictedTrajectories,
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46 accelerationDistribution,
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47 steeringDistribution,
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48 params.useFeaturesForPrediction)
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49 elif predictionMethod == 'ps':
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50 predictionParameters = prediction.PointSetPredictionParameters(params.maxPredictedSpeed)
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51 elif predictionMethod == 'proto':
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52 prototypes = storage.loadPrototypesFromSqlite(args.prototypeDatabaseFilename)
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53 for p in prototypes:
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54 p.getMovingObject().getPositions().computeCumulativeDistances()
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55 # no else required, since parameters is required as argument
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57 # evasiveActionPredictionParameters = prediction.EvasiveActionPredictionParameters(params.maxPredictedSpeed,
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58 # params.nPredictedTrajectories,
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59 # params.minExtremeAcceleration,
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60 # params.maxExtremeAcceleration,
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61 # params.maxExtremeSteering,
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62 # params.useFeaturesForPrediction)
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64 objects = storage.loadTrajectoriesFromSqlite(params.databaseFilename, 'object', args.nObjects, withFeatures = (params.useFeaturesForPrediction or (predictionMethod == 'ps')))
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65 # if params.useFeaturesForPrediction:
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66 # features = storage.loadTrajectoriesFromSqlite(params.databaseFilename,'feature') # needed if normal adaptation
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67 # for obj in objects:
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68 # obj.setFeatures(features)
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70 interactions = events.createInteractions(objects)
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71 for inter in interactions:
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72 inter.computeIndicators()
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73 inter.computeCrossingsCollisions(predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, nProcesses = args.nProcesses)
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75 if args.computePET:
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76 for inter in interactions:
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77 inter.computePET(params.collisionDistance)
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79 storage.saveIndicatorsToSqlite(params.databaseFilename, interactions)
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81 if args.displayCollisionPoints:
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82 plt.figure()
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83 allCollisionPoints = []
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84 for inter in interactions:
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85 for collisionPoints in inter.collisionPoints.values():
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86 allCollisionPoints += collisionPoints
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87 moving.Point.plotAll(allCollisionPoints)
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88 plt.axis('equal')
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