#!/usr/bin/env python """ @file Assignment.py @author Yun-Pang.Wang@dlr.de @date 2008-03-28 @version $Id: Assignment.py 5774 2008-07-14 13:10:31Z behrisch $ This script is for executing the traffic assignment. Three assignment models are available: - incremental - c-logit - lohse The c-logit model are set as default. Copyright (C) 2008 DLR/TS, Germany All rights reserved """ import os, random, string, sys, datetime, math from xml.sax import saxutils, make_parser, handler from optparse import OptionParser from elements import Predecessor, Vertex, Edge, Path, Vehicle from network import Net, NetworkReader, DistrictsReader, ExtraSignalInformationReader from dijkstra import dijkstra from inputs import getMatrix, getConnectionTravelTime from outputs import timeForInput, outputODZone, outputNetwork, outputStatistics, sortedVehOutput from assign import doSUEAssign, doLohseStopCheck, doSUEVehAssign, doIncAssign from tables import updateCurveTable def main(): # for measuring the required time for reading input files inputreaderstart = datetime.datetime.now() foutlog = file('%s_log.txt' % options.type, 'w') foutlog.write('The stochastic user equilibrium traffic assignment will be executed with the %s model.\n' % options.type) foutlog.write('All vehicular releasing times are determined randomly(uniform).\n') matrices = options.mtxpsfile.split(",") parser = make_parser() if options.verbose: print "Reading net" net = Net() parser.setContentHandler(NetworkReader(net)) parser.parse(options.netfile) parser.setContentHandler(DistrictsReader(net)) parser.parse(options.confile) if options.sigfile: parser.setContentHandler(ExtraSignalInformationReader(net)) parser.parse(options.sigfile) foutlog.write('- Reading network: done.\n') foutlog.write('number of total startVertices:%s\n' %len(net._startVertices)) foutlog.write('number of total endVertices:%s\n' %len(net._endVertices)) if options.verbose: print len(net._edges), "edges read" if options.curvefile: updateCurveTable(options.curvefile) for edgeID in net._edges: edge = net._edges[edgeID] if options.type != "incremental" and options.kPaths > 1: net.removeUTurnEdge(edge) if edge.numberlane > 0.: edge.getCapacity() edge.getAdjustedCapacity(net) edge.getConflictLink() edge.getActualTravelTime(options.lamda) edge.helpacttime = edge.freeflowtime net.reduce() # calculate link travel time for all district connectors getConnectionTravelTime(net._startVertices, net._endVertices) foutlog.write('- Initial calculation of link parameters : done.\n') # the required time for reading the network timeForInput(inputreaderstart) if options.debug: outputNetwork(net) # initialize the map for recording the number of the assigned vehicles AssignedVeh = {} # initialize the map for recording the number of the assigned trips AssignedTrip = {} for startVertex in net._startVertices: AssignedVeh[startVertex]={} AssignedTrip[startVertex]={} for endVertex in net._endVertices: AssignedVeh[startVertex][endVertex] = 0 AssignedTrip[startVertex][endVertex] = 0. # initialization vehID = 0 matrixSum = 0.0 lohse = (options.type == "lohse") incremental = (options.type == "incremental") checkKPaths = False if not incremental and options.kPaths > 1: checkKPaths = True if not incremental: net.initialPathSet() starttime = datetime.datetime.now() # initialize the file for recording the routes foutroute = open('routes.rou.xml', 'w') print >> foutroute, """ """ % starttime for counter, matrix in enumerate(matrices): #for counter in range (0, len(matrices)): # delete all vehicle information related to the last matrix for saving the disk space vehicles = [] matrixPshort, startVertices, endVertices, Pshort_EffCells, matrixSum, CurrentMatrixSum, begintime = getMatrix(net, options.verbose, matrix, matrixSum) departtime = begintime * 3600 if options.verbose: print 'the analyzed matrices:', counter print 'Begintime:', begintime, "O'Clock" print 'departtime', departtime print 'Matrix und OD Zone already read for Interval', counter print 'CurrentMatrixSum:', CurrentMatrixSum foutlog.write('Reading matrix and O-D zones: done.\n') foutlog.write('Matrix und OD Zone already read for Interval:%s\n' %counter) foutlog.write('CurrentMatrixSum:%s\n' %CurrentMatrixSum) foutlog.write('number of current startVertices:%s\n' %len(startVertices)) foutlog.write('number of current endVertices:%s\n' %len(endVertices)) for edgeID in net._edges: edge = net._edges[edgeID] edge.flow = 0. edge.helpflow = 0. edge.actualtime = edge.freeflowtime if lohse: edge.resetLohseParameter() edge.helpacttime = edge.freeflowtime # the number of origins, the umber of destinations and the number of the OD pairs origins = len(startVertices) dests = len(endVertices) ODpairs = origins * dests # output the origin and destination zones and the number of effective OD pairs if options.debug: outputODZone(startVertices, endVertices, Pshort_EffCells, counter) # matrixCounter) if incremental: print 'begin the incremental assignment!' iter = 0 options.lamda = 0. while iter < options.maxiteration: foutlog.write('- Current iteration(not executed yet):%s\n' %iter) iter += 1 for start, startVertex in enumerate(startVertices): targets = set() for end, endVertex in enumerate(endVertices): if matrixPshort[start][end] > 0.: targets.add(endVertex) if len(targets) > 0: D,P = dijkstra(net, startVertex, targets) vehID = doIncAssign(vehicles, options.verbose, options.maxiteration, endVertices, start, startVertex, matrixPshort, D, P, AssignedVeh, AssignedTrip, vehID) for edgeID in net._edges: edge = net._edges[edgeID] edge.getActualTravelTime(options.lamda) else: print 'begin the', options.type, " assignment!" # initialization for the clogit and the lohse assignment model iter_outside = 1 newRoutes = 1 stable = False first = True # begin the traffic Assignment while newRoutes > 0: foutlog.write('- SUE iteration:%s\n' %iter_outside) # Generate the effective routes als intital path solutions, when considering k shortest paths (k is defined by the user.) if checkKPaths: checkPathStart = datetime.datetime.now() newRoutes = net.calcKPaths(options.verbose, options.kPaths, newRoutes, startVertices, endVertices, matrixPshort) checkPathEnd = datetime.datetime.now() - checkPathStart foutlog.write('- Time for finding the k-shortest paths: %s\n' %checkPathEnd) foutlog.write('- Finding the k-shortest paths for each OD pair: done.\n') if options.verbose: print 'iter_outside:', iter_outside print 'number of k shortest paths:', options.kPaths print 'number of new routes:', newRoutes elif not checkKPaths and iter_outside == 1 and counter == 0: print 'search for the new path' newRoutes = net.findNewPath(startVertices, endVertices, newRoutes, matrixPshort, lohse) checkKPaths = False if options.verbose: print 'iter_outside:', iter_outside print 'number of new routes:', newRoutes stable = False iter_inside = 1 while not stable: if options.verbose: print 'iter_inside:', iter_inside stable = doSUEAssign(net, options, startVertices, endVertices, matrixPshort, iter_inside, lohse, first) # The matrixPlong and the matrixTruck should be added when considering the long-distance trips and the truck trips. if lohse: stable = doLohseStopCheck(net, options, stable, iter_inside, options.maxiteration, foutlog) iter_inside += 1 if options.verbose: print 'stable:', stable # if (float(departtime)/3600.) < 10. or counter < 5: newRoutes = net.findNewPath(startVertices, endVertices, newRoutes, matrixPshort, lohse) # else: # newRoutes = 0 first = False iter_outside += 1 if newRoutes < 2 and iter_outside > int((options.maxiteration)/2): newRoutes = 0 if iter_outside > options.maxiteration: print 'The max. number of iterations is reached!' foutlog.write('The max. number of iterations is reached!\n') foutlog.write('The number of new routes and the parameter stable will be set to zero and True respectively.\n') print 'newRoutes:', newRoutes stable = True newRoutes = 0 # update the path choice probability and the path flows as well as generate vehicle data vehID = doSUEVehAssign(net, vehicles, options, counter, matrixPshort, startVertices, endVertices, AssignedVeh, AssignedTrip, vehID, lohse) # output the generated vehicular releasing times and routes, based on the current matrix sortedVehOutput(vehicles, departtime, foutroute) foutroute.write('\n') foutroute.close() # output the global performance indices assigntime = outputStatistics(net, starttime, len(matrices)) foutlog.write('- Assignment is completed and all vehicular information is generated. ') foutlog.close() print 'Duration for traffic assignment:', assigntime print 'Total assigned vehicles:', vehID print 'Total number of the assigned trips:', matrixSum optParser = OptionParser() optParser.add_option("-m", "--matrix-file", dest="mtxpsfile", help="read OD matrix for passenger vehicles(long dist.) from FILE (mandatory)", metavar="FILE") optParser.add_option("-n", "--net-file", dest="netfile", help="read SUMO network from FILE (mandatory)", metavar="FILE") optParser.add_option("-d", "--district-file", dest="confile", help="read OD Zones from FILE (mandatory)", metavar="FILE") optParser.add_option("-s", "--extrasignal-file", dest="sigfile", help="read extra/updated signal timing plans from FILE", metavar="FILE") optParser.add_option("-u", "--crCurve-file", dest="curvefile", help="read parameters used in cost functions from FILE", metavar="FILE") optParser.add_option("-k", "--k-shortest-paths", dest="kPaths", type="int", default=4, help="number of the paths should be found at the first iteration") optParser.add_option("-i", "--max-sue-iteration", dest="maxiteration", type="int", default=20, help="maximum number of the assignment iterations") optParser.add_option("-t", "--sue-tolerance", dest="sueTolerance", type="float", default=0.001, help="difference tolerance for the convergence in the c-logit model") optParser.add_option("-a", "--alpha", dest="alpha", type="float", default=0.15, help="alpha value to determine the commonality factor") optParser.add_option("-g", "--gamma", dest="gamma", type="float", default=1., help="gamma value to determine the commonality factor") optParser.add_option("-l", "--lambda", dest="lamda", type="float", default=0.3, help="lambda value to determine the penalty time due to queue") optParser.add_option("-U", "--under-value", dest="under", type="float", default=0.15, help="parameter 'under' to determine auxiliary link cost") optParser.add_option("-p", "--upper-value", dest="upper", type="float", default=0.5, help="parameter 'upper' to determine auxiliary link cost") optParser.add_option("-x", "--parameter-1", dest="v1", type="float", default=2.5, help="parameter 'v1' to determine auxiliary link cost in the lohse model") optParser.add_option("-y", "--parameter-2", dest="v2", type="float", default=4., help="parameter 'v2' to determine auxiliary link cost in the lohse model") optParser.add_option("-z", "--parameter-3", dest="v3", type="float", default=0.002, help="parameter 'v3' to determine auxiliary link cost in the lohse model") optParser.add_option("-c", "--convergence-parameter-1", dest="cvg1", type="float", default=1., help="parameter 'cvg1' to calculate the convergence value in the lohse model") optParser.add_option("-o", "--convergence-parameter-2", dest="cvg2", type="float", default=1., help="parameter 'cvg2' to calculate the convergence value in the lohse model") optParser.add_option("-q", "--convergence-parameter-3", dest="cvg3", type="float", default=10., help="parameter 'cvg3' to calculate the convergence value in the lohse model") optParser.add_option("-v", "--verbose", action="store_true", dest="verbose", default=False, help="tell me what you are doing") optParser.add_option("-b", "--debug", action="store_true", dest="debug", default=False, help="debug the program") optParser.add_option("-e", "--type", dest="type", type="choice", choices=('clogit', 'lohse', 'incremental'), default="clogit", help="type of assignment [default: %default]") optParser.add_option("-r", "--profile", action="store_true", dest="profile", default=False, help="writing profiling info") (options, args) = optParser.parse_args() if not options.netfile or not options.confile or not options.mtxpsfile: optParser.print_help() sys.exit() if options.profile: import hotshot, hotshot.stats hotshotFile = "hotshot_%s_stats" % options.type prof = hotshot.Profile(hotshotFile) prof.runcall(main) prof.close() s = hotshot.stats.load(hotshotFile) s.strip_dirs().sort_stats("time").print_stats(20) else: main()