Output

All of the tools described below exist in tools/output directory.

attributeStats.py#

Computes statistics on arbitrary numerical attributes in an xml document. (eg. attribute timeLoss for element tripinfo in tripinfo-output) and writes the results to standard output. When the attribute contains time data in HH:MM:SS format, the values will automatically be converted to seconds.

python tools/output/attributeStats --element tripinfo --attribute timeLoss input.xml
  • If option --element (-e) is set to a comma-separated list of elements, only these elements will be read. Otherwise all elements will be parsed
  • If option --attribute (-a) is set to a comma-separated list of attributes, only these attributes will be read. Otherwise all attributes will be parsed
  • It is also possible to give multiple files as input as a space separated list or via shell expenasion (i.e. *.input.xml)
  • If option --id-attribute (-i) is set, the minimum and maximum values of each attribute will be annotated with the corresponding id value
  • With option --hist-output <FILE>, a histogram data file (e.g. for plotting with gnuplot) is generated.
    • option --binwidth INT (-b) defines the binning width for the histogram
  • With option --xml-output <FILE>, A file with statistical measures for all processed attributes is written
  • With option --full-output <FILE>, A collected attribute values are recorded with their corresponnding ids
  • Output precision can be set with option --precision (-p)

attributeDiff.py#

Computes difference between numerical attributes in two xml files with the same structure (eg. attribute timeLoss for element vehicleTripStatistics in statistic-output) and writes the results to standard output. When the attribute contains time data in HH:MM:SS format, the values will automatically be converted to seconds.

python tools/output/attributeDiff file1.xml file2.xml --xml-output differences.xml
  • If option --element (-e) is set to a comma-separated list of elements, only these elements will be read. Otherwise all elements will be parsed
  • If option --attribute (-a) is set to a comma-separated list of attributes, only these attributes will be read. Otherwise all attributes will be parsed
  • If option --id-attribute (-i) is set, the minimum and maximum values of each attribute will be annotated with the corresponding id value
  • With option --xml-output <FILE>, A file with statistical measures for all processed attributes is written

generateITetrisIntersectionMetrics.py#

Tool used for generating the intersection metrics, including (but not limited to):

  • CO emission
  • CO2 emission
  • HC emission
  • PMx emission
  • NOx emission
  • fuel consumption

Execute the generateITetrisIntersectionMetrics.py script with --help option to get details about usage and available options.

generateITetrisNetworkMetrics.py#

Tool used for generating the network metrics, including (but not limited to):

  • CO emission
  • CO2 emission
  • HC emission
  • PMx emission
  • NOx emission
  • fuel consumption

Execute the generateITetrisINetworkMetrics.py script with --help option to get details about usage and available options.

generateMeanDataDefinitions.py#

Script for generating mean data definitions from detector definitions.

Execute the generateITetrisINetworkMetrics.py script with --help option to get details about usage and available options.

generateTLSE1Detectors.py#

Script for generating E1 detectors (induction loops) for each junction in the supplied network file.

Example usage:

python tools\output\generateTLSE1Detectors.py -n .net.net.xml -o detectors.add.xml

Execute the generateTLSE1Detectors.pyscript with --help option to get details about additional options.

generateTLSE2Detectors.py#

Script for generating E2 detectors (lanearea detectors) for each junction in the supplied network file.

Example usage:

python tools\output\generateTLSE2Detectors.py -n .net.net.xml -o detectors.add.xml

Execute the generateTLSE2Detectors.py script with --help option to get details about additional options.

generateTLSE3Detectors.py#

Script for generating E3 detectors (multi-entry/multi-exit detectors) around all TLS-controlled intersections (default) or for an arbitrary list of intersections (--junction-ids). By default each entry edge gets its own detector. When setting option --joined there will be one detector per junction instead. When setting option --interior, delays within the intersection will be included as well.

Example usage:

python tools\output\generateTLSE3Detectors.py -n .net.net.xml -o detectors.add.xml

Execute the generateTLSE3Detectors.py script with --help option to get details about additional options.

netdumpdiff.py#

Script creating a diff of two netdump files.

Execute the netdumpdiff.py script with --help option to get details about usage and available options.

netdumpmean.py#

Script calculating the mean values from two netdump files.

Execute the netdumpmean.py script with --help option to get details about usage and available options.

timingStats.py#

Script for gathering statistics from several SUMO runs.

Execute the timingStats.py script with --help option to get details about usage and available options.

accelerations.py#

Script for computing aggregate statistics about vehicle accelerations based on --netstate-dump output.

vehLanes.py#

Script for computing vehroute-like output for lanes based on --netstate-dump output. Output data also includes information about the number of lane changes for each vehicle.

usage:

python vehLanes.py <netstate_dump.xml> <output_file>

edgeDataDiff.py#

Computes the numerical difference of edgeData values for each edge and interval. The resulting file can be used to visualize changes between two traffic scenarios. Both input files must contain the same edges and intervals.

usage:

python edgeDataDiff.py <edgeData1.xml> <edgeData2.xml> <diffFile.xml>

vehrouteDiff.py#

Computes the difference in travel times between two sets of --vehroute-output files. The files must contain the same vehicles and the same routes and may only differ in travel times. The must have been generated with the option --vehroute-output.exit-times for the script to work.

usage:

python vehrouteDiff.py routes1.rou.xml routes2.rou.xml result.xml

vehrouteCountValidation.py#

Computes the mismatch between counting datay (in the same format as used by routeSampler.py) and --vehroute-output files. If the vehroute-output was generated with option --vehroute-output.exit-times, then time of passing the respective edges is used for the validation of counting data time lines (counting data with multiple time intervals). Since typically, the total count of vehicles provided in the simulation --route-files passes the desired edges, the main value of this tools lies in evaluating the impact of delays (or delayed insertion) on replicating time-dependent counting data.

usage (with turn counts):

python vehrouteCountValidation.py -r routes.rou.xml -t input_turns.xml

tripinfoDiff.py#

Computes the difference in travel times, route length, time loss, departure- and arrival times between two sets of --tripinfo-output files. The files should contain the same vehicles.

usage:

python tripinfoDiff.py tripinfos1.xml tripinfos2.xml result.xml

By default only <tripinfo> elements are considered. By setting option --persons, the difference for <personinfo> elements is computed instead.

tripinfoByTAZ.py#

Aggregates tripinfo data by origin/destination TAZ. The TAZ data can either by taken from the original input file (if it contains 'fromTaz' and 'toTaz' attributes) or from a TAZ file.

python tripinfoByTAZ.py -t tripinfos.xml -r trips.xml
python tripinfoByTAZ.py -t tripinfos.xml -z taz.axml

By default traveltime (tripinfo attribute 'duration') is aggregated. Other attributes can be selected using option --attribute (e.g. 'routeLength'). Output is given as plain text on the command line or in xml format if option --output is set.

tripinfoByType.py#

Aggregates tripinfo data by vType and person stage type for the given attribute

python tripinfoByType.py -t tripinfos.xml -a timeLoss

Output is given as plain text on the command line or in xml format if option --output is set.

computeCoordination.py#

This tool reads fcd-output and a corridor definition. It computes the fraction of vehicles that passed the corridor without significant slow-down.

Example:

python tools/output/computeCoordination.py --fcd-file fcd.xml --filter-route B,C,D,E --entry C --min-speed 5

This computes the fraction of vehicles that passed the edges B,C,D,E in order (possibly with gaps) and were delayed after passing edge C to less then 5m/s.

With option --full-output <FILE> Each vehicle that passed the corridor is recorded with entry time and the time at which it was delayed (-1 it it was not delayed).

tripStatistics.py#

This script is to calculate the global performance indices according to SUMO-based simulation results. The calculation functions are directly defined in this script. Basic statistics are delivered, such as:

  • average travel time (s)
  • average travel length (m)
  • average travel speed (m/s)
  • average departure delay (s)
  • average waiting time (s)

Besides, this script is also to execute a significance test for evaluating the results from different assignment methods. The t test and the Kruskal-Wallis test are available in this script. If not specified, the Kruskal-Wallis test will be applied with the assumption that data are not normally distributed.

In order to execute this script, the other two scripts, i.e. statisticsElements.py and tables.py, are required. They all should be in the same directory.

In the statisticsElements.py, classes regarding vehicles, their performance measures, t values, H values as well as functions for outputs are defined. The chi-square table and the t table are defined in the tables.py.

An exemplary command is shown below.

python tools/output/tripStatistics.py -t <tripinfo files> -o <output file> -e

where -t: name of output files containing vehicle information, generated by SUMO
      -o: define the output file name
      -e: set true for applying the t test (default: false)
      -k: set true for applying the Kruskal-Wallis test (default: false)

computeStoppingPlaceUsage.py#

This tool reads stop-output and generates occupancy-over-time for stopping places (i.e. parkingArea). A distinct output file will be created for each stopping place.

Example:

python tools/output/computeStoppingPlaceUsage.py -s stopinfos.xml

computePassengerCounts.py#

This tool reads stop-output and generates occupancy-over-time for vehicles A distinct output file will be created for each vehicle.

Example:

python tools/output/computePassengerCounts.py -s stopinfos.xml

parkingSearchTraffic.py#

This tool reads vehroute-output with exit-times and generates statistics for the time and the distance vehicles spent on searching parking locations as well as the length of the walking way back. It evaluates the time and distance between the first reroute and the arrival at the final stop. It currently outputs only basic statistics (mean, avg, quartiles etc.).

Example:

python tools/output/parkingSearchTraffic.py net.net.xml vehroutes.xml

aggregateBatteryOutput.py#

Script for aggregate battery outputs in intervals.

Example usage:

python tools\output\aggregateBatteryOutput.py -i battery.xml -o batteryAggregatedx.xml -t 60 -v veh0')

fcdDiff.py#

Computes difference between two fcd-output files with regard to their distance in space. Data points in the files are matched by time and by id (no time shifting is done).

Statistical outputs are printed on the console. It is also possible to write all error values to an xml file.

python tools/output/fcdDiff fcd.xml fcd2.xml 
  • If option --grouped is set, separate statistics for each vehicle will be printed
  • If option --tripId is set, vehicles will be matched by attribute tripId instead of id (requires --fcd-output.params tripId to be when generating the fcd-output)
  • With option --xml-output <FILE>, An annotated fcd file with error values is written