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annotate scripts/safety-analysis.py @ 352:72aa44072093

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safety analysis script with option for prediction method
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 27 Jun 2013 01:35:47 -0400
parents 891858351bcb
children e5fe0e6d48a1
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5e43b7389c25 script for safety analysis
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1 #! /usr/bin/env python
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3 import utils, storage, prediction, events
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5 import sys, argparse
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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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9
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10 parser = argparse.ArgumentParser(description='The program processes indicators for all pairs of road users in the scene')
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11 parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file')
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12 parser.add_argument('--prediction-method', dest = 'predictionMethod', help = 'prediction method (constant velocity, normal adaptation, point set prediction)', choices = ['cv', 'na', 'ps'])
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13 args = parser.parse_args()
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15 params = utils.TrackingParameters()
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16 params.loadConfigFile(args.configFilename)
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18 # parameters for prediction methods
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19 if args.predictionMethod:
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20 predictionMethod = args.predictionMethod
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21 else:
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22 predictionMethod = params.predictionMethod
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24 if predictionMethod == 'cv':
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25 predictionParameters = prediction.ConstantPredictionParameters(params.maxPredictedSpeed)
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26 elif predictionMethod == 'na':
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27 predictionParameters = prediction.NormalAdaptationPredictionParameters(params.maxPredictedSpeed,
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28 params.nPredictedTrajectories,
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29 params.maxAcceleration,
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30 params.maxSteering,
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31 params.useFeaturesForPrediction)
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32 elif predictionMethod == 'ps':
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33 predictionParameters = prediction.PointSetPredictionParameters(params.nPredictedTrajectories,
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34 params.maxPredictedSpeed)
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35 else:
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36 print('Prediction method {} is not valid. See help.'.format(predictionMethod))
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37 sys.exit()
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39 evasiveActionPredictionParameters = prediction.EvasiveActionPredictionParameters(params.maxPredictedSpeed,
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40 params.nPredictedTrajectories,
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41 params.minAcceleration,
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42 params.maxAcceleration,
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43 params.maxSteering,
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44 params.useFeaturesForPrediction)
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46 objects = storage.loadTrajectoriesFromSqlite(params.databaseFilename,'object')
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47 if params.useFeaturesForPrediction:
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48 features = storage.loadTrajectoriesFromSqlite(params.databaseFilename,'feature') # needed if normal adaptation
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49 for obj in objects:
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50 obj.setFeatures(features)
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52 interactions = events.createInteractions(objects)
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53 for inter in interactions[:1]:
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54 inter.computeIndicators()
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55 inter.computeCrossingsCollisions(predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones)
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57 storage.saveIndicators(params.databaseFilename, interactions)
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59 if False:
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60 plt.figure()
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61 plt.axis('equal')
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62 for inter in interactions:
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63 for collisionPoints in inter.collisionPoints.values():
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64 for cp in collisionPoints:
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65 plt.plot([cp.x], [cp.y], 'x')
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