Mercurial Hosting > traffic-intelligence
changeset 338:f3aceea2afbb
first safety analysis script
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Mon, 17 Jun 2013 16:26:11 -0400 |
parents | dc2e68e936c7 |
children | 9c1818a71c9c |
files | python/events.py scripts/safety-analysis.py |
diffstat | 2 files changed, 66 insertions(+), 9 deletions(-) [+] |
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--- a/python/events.py Sun Jun 16 23:44:36 2013 -0400 +++ b/python/events.py Mon Jun 17 16:26:11 2013 -0400 @@ -87,12 +87,27 @@ minDistance[instant] = distance.min() self.addIndicator(indicators.SeverityIndicator('Minimum Distance', minDistance)) - def computeCollisionPoints(self, predictionParameters, collisionDistanceThreshold, timeHorizon): - if self.roadUser1.features and self.roadUser2.features: - collisionPoints = prediction.computeCollisions(self.roadUser1, self.roadUser2, predictionParameters, collisionDistanceThreshold, timeHorizon) - self.addIndicator(indicators.SeverityIndicator('Collision Points', collisionPoints)) + def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None): + '''Computes all crossing and collision points at each common instant for two road users. ''' + self.collisionPoints={} + TTCs = {} + if computeCZ: + self.crossingZones={} + + if timeInterval: + commonTimeInterval = timeInterval else: - print('Features not associated with objects') + commonTimeInterval = self.timeInterval + for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors + self.collisionPoints[i], self.crossingZones[i] = prediction.computeCrossingsCollisionsAtInstant(i, self.roadUser1, self.roadUser2, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ, debug) + TTCs[i] = prediction.computeExpectedIndicator(self.collisionPoints[i]) + self.addIndicator(indicators.SeverityIndicator('TTC', TTCs)) + + if computeCZ: + pPETs = {} + for i in list(commonTimeInterval)[:-1]: + pPETs[i] = prediction.computeExpectedIndicator(self.crossingZones[i]) + self.addIndicator(indicators.SeverityIndicator('pPET', pPETs)) def addVideoFilename(self,videoFilename): self.videoFilename= videoFilename
--- a/scripts/safety-analysis.py Sun Jun 16 23:44:36 2013 -0400 +++ b/scripts/safety-analysis.py Mon Jun 17 16:26:11 2013 -0400 @@ -1,5 +1,7 @@ #! /usr/bin/env python +import utils, storage, prediction, events + import sys, argparse import matplotlib.pyplot as plt @@ -8,17 +10,57 @@ from ConfigParser import ConfigParser parser = argparse.ArgumentParser(description='The program processes indicators for all pairs of road users in the scene') +parser.add_argument('configFilename', help = 'name of the configuration file') +# parser.add_argument('-c', help = 'name of the configuration file') # args = parser.parse_args() print(args) # TODO work on the way to indicate an interaction definition -if False:#len(args)>0: # consider there is a configuration file - params = utils.TrackingParameters() - params.loadConfigFile(args[0]) +# if False: # test if there is a configuration file? +params = utils.TrackingParameters() +params.loadConfigFile(args.configFilename) + +# configuration parameters # TODO from command line +frameRate = 15 # frame per second +maxSpeed = 90/3.6/frameRate # speed limit 50 km/h for urban envt, 90km/hr = 25 m/sec for highways +timeHorizon= frameRate*5 # prediction time Horizon = 1.5 s (reaction time) (5 second) +collisionDistanceThreshold= 1.8 # m +computeCZ = True + +# parameters for prediction methods +constantVelocityPredictionParameters = prediction.ConstantPredictionParameters(maxSpeed) + +normalAdaptationPredictionParameters = prediction.NormalAdaptationPredictionParameters(maxSpeed, 100, 2./frameRate**2, # m/s2 + 0.2/frameRate) # rad/s + +featurePredictionParameters = prediction.PointSetPredictionParameters(maxSpeed) + +evasiveActionPredictionParameters = prediction.EvasiveActionPredictionParameters(maxSpeed, 100, -9.1/frameRate**2, # m/s2 + 4.3/frameRate**2, # m/s2 + 0.5/frameRate, # rad/s + False) + +featureEvasiveActionPredictionParameters = prediction.EvasiveActionPredictionParameters(maxSpeed, 10, -9.1/frameRate**2, # m/s2 + 4.3/frameRate**2, # m/s2 + 0.5/frameRate, # rad/s + True) +objects = storage.loadTrajectoriesFromSqlite(params.databaseFilename,'object') +# features = storage.loadTrajectoriesFromSqlite('amherst-10.sqlite','feature') # needed if normal adaptation + +interactions = events.createInteractions(objects) +for inter in interactions[:2]: + inter.computeCrossingsCollisions(constantVelocityPredictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ) + +plt.figure() +plt.axis('equal') +for inter in interactions[:2]: + for collisionPoints in inter.collisionPoints.values(): + for cp in collisionPoints: + plot([cp.x], [cp.y], 'x') # for the demo, output automatically a map - +# possibility to process longitudinal coords only