Mercurial Hosting > traffic-intelligence
view python/events.py @ 352:72aa44072093
safety analysis script with option for prediction method
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Thu, 27 Jun 2013 01:35:47 -0400 |
parents | 2f39c4ed0b62 |
children | e5fe0e6d48a1 |
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#! /usr/bin/env python '''Libraries for events Interactions, pedestrian crossing...''' import numpy as np from numpy import arccos import multiprocessing import itertools import moving, prediction, indicators, utils __metaclass__ = type class Interaction(moving.STObject): '''Class for an interaction between two road users or a road user and an obstacle link to the moving objects contains the indicators in a dictionary with the names as keys ''' categories = {'Head On': 0, 'rearend': 1, 'side': 2, 'parallel': 3} indicatorNames = ['Collision Course Dot Product', 'Collision Course Angle', 'Distance', 'Minimum Distance', 'Velocity Angle', 'Speed Differential', 'Collision Probability', 'Time to Collision', 'Probability of Successful Evasive Action', 'predicted Post Encroachment Time'] indicatorNameToIndices = utils.inverseEnumeration(indicatorNames) indicatorShortNames = ['', 'CCAng', 'Dist', 'MinDist', 'VA', 'SD', 'PoC', 'TTC', 'P(SEA)', 'pPET'] def __init__(self, num = None, timeInterval = None, roaduserNum1 = None, roaduserNum2 = None, roadUser1 = None, roadUser2 = None, categoryNum = None): moving.STObject.__init__(self, num, timeInterval) self.roadUserNumbers = set([roaduserNum1, roaduserNum2]) self.roadUser1 = roadUser1 self.roadUser2 = roadUser2 self.categoryNum = categoryNum self.indicators = {} def getRoadUserNumbers(self): return self.roadUserNumbers def getIndicator(self, indicatorName): return self.indicators.get(indicatorName, None) def addIndicator(self, indicator): if indicator: self.indicators[indicator.name] = indicator def computeIndicators(self): '''Computes the collision course cosine only if the cosine is positive''' collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length()) collisionCourseAngles = {} velocityAngles = {} distances = {}#[0]*int(self.timeInterval.length()) speedDifferentials = {} for instant in self.timeInterval: deltap = self.roadUser1.getPositionAtInstant(instant)-self.roadUser2.getPositionAtInstant(instant) v1 = self.roadUser1.getVelocityAtInstant(instant) v2 = self.roadUser2.getVelocityAtInstant(instant) deltav = v2-v1 velocityAngles[instant] = arccos(moving.Point.dot(v1, v2)/(v1.norm2()*v2.norm2())) collisionCourseDotProducts[instant] = moving.Point.dot(deltap, deltav) distances[instant] = deltap.norm2() speedDifferentials[instant] = deltav.norm2() #if collisionCourseDotProducts[instant] > 0: collisionCourseAngles[instant] = arccos(collisionCourseDotProducts[instant]/(distances[instant]*speedDifferentials[instant])) # todo shorten the time intervals based on the interaction definition self.addIndicator(indicators.SeverityIndicator('Collision Course Dot Product', collisionCourseDotProducts)) self.addIndicator(indicators.SeverityIndicator('Collision Course Angle', collisionCourseAngles)) self.addIndicator(indicators.SeverityIndicator('Distance', distances)) self.addIndicator(indicators.SeverityIndicator('Velocity Angle', velocityAngles)) self.addIndicator(indicators.SeverityIndicator('Speed Differential', speedDifferentials)) # todo test for interaction instants and interval, compute indicators # if we have features, compute other indicators if self.roadUser1.features and self.roadUser2.features: from scipy.spatial.distance import cdist minDistance={} for instant in self.timeInterval: positions1 = [f.getPositionAtInstant(instant).astuple() for f in self.roadUser1.features if f.existsAtInstant(instant)] positions2 = [f.getPositionAtInstant(instant).astuple() for f in self.roadUser2.features if f.existsAtInstant(instant)] distance = cdist(positions1, positions2, metric = 'euclidean') minDistance[instant] = distance.min() self.addIndicator(indicators.SeverityIndicator('Minimum Distance', minDistance)) 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={} self.crossingZones={} TTCs = {} if timeInterval: commonTimeInterval = timeInterval else: 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]) # add probability of collision, and probability of successful evasive action 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 def addInteractionType(self,interactionType): ''' interaction types: conflict or collision if they are known''' self.interactionType= interactionType def createInteractions(objects): '''Create all interactions of two co-existing road users todo add test to compute categories?''' interactions = [] num = 0 for i in xrange(len(objects)): for j in xrange(i): commonTimeInterval = objects[i].commonTimeInterval(objects[j]) if not commonTimeInterval.empty(): interactions.append(Interaction(num, commonTimeInterval, objects[i].num, objects[j].num, objects[i], objects[j])) num += 1 return interactions # TODO: #http://stackoverflow.com/questions/3288595/multiprocessing-using-pool-map-on-a-function-defined-in-a-class #http://www.rueckstiess.net/research/snippets/show/ca1d7d90 def calculateIndicatorPipe(pairs, predParam, timeHorizon=75,collisionDistanceThreshold=1.8): collisionPoints, crossingZones = prediction.computeCrossingsCollisions(pairs.roadUser1, pairs.roadUser2, predParam, collisionDistanceThreshold, timeHorizon) #print pairs.num # Ignore empty collision points empty = 1 for i in collisionPoints: if(collisionPoints[i] != []): empty = 0 if(empty == 1): pairs.hasCP = 0 else: pairs.hasCP = 1 pairs.CP = collisionPoints # Ignore empty crossing zones empty = 1 for i in crossingZones: if(crossingZones[i] != []): empty = 0 if(empty == 1): pairs.hasCZ = 0 else: pairs.hasCZ = 1 pairs.CZ = crossingZones return pairs def calculateIndicatorPipe_star(a_b): """Convert `f([1,2])` to `f(1,2)` call.""" return calculateIndicatorPipe(*a_b) class VehPairs(): '''Create a veh-pairs object from objects list''' def __init__(self,objects): self.pairs = createInteractions(objects) self.interactionCount = 0 self.CPcount = 0 self.CZcount = 0 # Process indicator calculation with support for multi-threading def calculateIndicators(self,predParam,threads=1,timeHorizon=75,collisionDistanceThreshold=1.8): if(threads > 1): pool = multiprocessing.Pool(threads) self.pairs = pool.map(calculateIndicatorPipe_star, itertools.izip(self.pairs, itertools.repeat(predParam))) pool.close() else: #prog = Tools.ProgressBar(0, len(self.pairs), 77) #Removed in traffic-intelligenc port for j in xrange(len(self.pairs)): #prog.updateAmount(j) #Removed in traffic-intelligenc port collisionPoints, crossingZones = prediction.computeCrossingsCollisions(self.pairs[j].roadUser1, self.pairs[j].roadUser2, predParam, collisionDistanceThreshold, timeHorizon) # Ignore empty collision points empty = 1 for i in collisionPoints: if(collisionPoints[i] != []): empty = 0 if(empty == 1): self.pairs[j].hasCP = 0 else: self.pairs[j].hasCP = 1 self.pairs[j].CP = collisionPoints # Ignore empty crossing zones empty = 1 for i in crossingZones: if(crossingZones[i] != []): empty = 0 if(empty == 1): self.pairs[j].hasCZ = 0 else: self.pairs[j].hasCZ = 1 self.pairs[j].CZ = crossingZones for j in self.pairs: self.interactionCount = self.interactionCount + len(j.CP) self.CPcount = len(self.getCPlist()) self.Czcount = len(self.getCZlist()) def getPairsWCP(self): lists = [] for j in self.pairs: if(j.hasCP): lists.append(j.num) return lists def getPairsWCZ(self): lists = [] for j in self.pairs: if(j.hasCZ): lists.append(j.num) return lists def getCPlist(self,indicatorThreshold=99999): lists = [] for j in self.pairs: if(j.hasCP): for k in j.CP: if(j.CP[k] != [] and j.CP[k][0].indicator < indicatorThreshold): lists.append([k,j.CP[k][0]]) return lists def getCZlist(self,indicatorThreshold=99999): lists = [] for j in self.pairs: if(j.hasCZ): for k in j.CZ: if(j.CZ[k] != [] and j.CZ[k][0].indicator < indicatorThreshold): lists.append([k,j.CZ[k][0]]) return lists def genIndicatorHistogram(self, CPlist=False, bins=range(0,100,1)): if(not CPlist): CPlist = self.getCPlist() if(not CPlist): return False TTC_list = [] for i in CPlist: TTC_list.append(i[1].indicator) histo = np.histogram(TTC_list,bins=bins) histo += (histo[0].astype(float)/np.sum(histo[0]),) return histo class Crossing(moving.STObject): '''Class for the event of a street crossing TODO: detecter passage sur la chaussee identifier origines et destination (ou uniquement chaussee dans FOV) carac traversee detecter proximite veh (retirer si trop similaire simultanement carac interaction''' def __init__(self, roaduserNum = None, num = None, timeInterval = None): moving.STObject.__init__(self, num, timeInterval) self.roaduserNum = roaduserNum if __name__ == "__main__": import doctest import unittest #suite = doctest.DocFileSuite('tests/moving.txt') suite = doctest.DocTestSuite() unittest.TextTestRunner().run(suite)