• Misc

createVehTypeDistribution.py#

Creates a vehicle type distribution by sampling from configurable value distributions for the desired vType-parameters. Example:

python tools/createVehTypeDistribution.py config.txt

The only required parameter is the configuration file in the format shown below (example config.txt):

tau; normal(0.8,0.1)
sigma; normal(0.5,0.2)
length; normal(4.9,0.2); [3.5,5.5]
param; myCustomParameter; normal(5, 2); [0, 12]
vClass; passenger
carFollowModel; Krauss

In the config file, one line is used per vehicle type attribute. The syntax is: [param; ] <AtrributeOrParameterName>; <ValueOrDistribution> [; <limits>]

If the prefix param is given at the beginning of a line, it is assumed that the values of a vehicle parameter (given as a param child element of the vehicle element) are to be sampled. Otherwise, values of an attribute of the vehicle element are sampled. ValueOrDistribution can be a string, a scalar value or a distribution definition. Available distributions and its syntax are:

• "normal(mu,sd)" with mu and sd being floating numbers: Normal distribution with mean mu and standard deviation sd.
• "normalCapped(mu, sd, min, max)" By default, no negative values are accepted but may be enabled by setting a negative lower limit.
• "lognormal(mu,sd)" with mu and sd being floating numbers: Normal distribution with mean mu and standard deviation sd.
• "uniform(a,b)" with limits a and b being floating numbers: Uniform distribution between a and b.
• "gamma(alpha,beta)" with parameters alpha and beta: Gamma distribution.

Additional options:

• --output-file configures the name of the output file to be written
• --name Name of the created distribution
• --size Number of s to be sampled for filling the distribution
• --seed Set the seed for the random number generator

Retrieving parameters from measurements of individual vehicles#

To obtain mean and deviation a number of values must be obtained from the data set. The following is recommenced:

• accel: the maximum (or high percentile) acceleration for each vehicle
• deccel: the maximum (or high percentile) deceleration for each vehicle
• speedFactor: the maximum (or high percentile) quotient of speed/speedLimit for each vehicle

createScreenshotSequence.py#

This script helps in the process of creating a movie by taking screenshots repeatedly and moving the viewport during the simulation. There are other ways to capture videos from sumo-gui such as using external screen capture software or using the internal screenshot feature. The screenshot sequence obtained from this script can be joined into a video using appropriate video software.

Example:

python tools/createScreenshotSequence.py --sumocfg test.sumocfg -o outDir --begin 600 --end 900 -p filePrefix --zoom 600:500;900:1000 --translate 800:100,100;900:150,100 --include-time

This will run the configuration file named by --sumocfg in sumo-gui and register a TraCI step listener for the screenshot process. The time interval when to take a screenshot of each time step can be limited to start only at --begin (s) or to end at --end (s). If the end time is not defined explicitly, the script runs the simulation either up to the end value from the configuration (if defined) or further to the technical system limits. The screenshots are written to the directory given by -o / --output-dir. Their file names can optionally start with the -p / --prefix value or contain the date/time when the simulation was started (--include-time). The standard file type is set to png but can be set via --image-format. The file name contains a zero-padded counter number such that it can be sorted easily in post-production.

The available attributes to animate are:

• Zoom using the --zoom option. The option value consists of pairs of time and zoom values (separator: colon) joined by semicolon.
• Angle using the --rotate option. The option value consists of pairs of time and angle values (in degrees, separator: colon) joined by semicolon.
• Offset/center position using the --translate option. The option value consists of pairs of time and position values (separator: colon, position dimensions separated by comma) joined by semicolon.

distributeChargingStations.py#

Charging stations are usually placed on (existing) parking spaces. This tool helps to equip a defined share of given parking spaces with charging infrastructure. In practice, this means generating the charging station definitions and eventually cut parking areas into two to reach the wanted number of charging points.

Thus the tool writes additional files with charging stations and parking areas. It needs at least the net file (--net-file) and an additional file (--add-files) to work. It provides the following options:

• --net-file: The network file the charging stations belong to (to keep an overview on the amount of charging stations and whether the wanted share of charging points has been reached)
• --add-files: Files containing parking area and possibly charging station definitions (define the situation where and how many new charging stations shall be placed)
• --selection-file: Network selection file to restrict the area where charging stations shall be created to the referenced edges
• --vclass: Only use edges which allow the given vehicle class
• --output-file: The new additional file with charging station and parking area definitions
• --output-parking-file: Additional output file where parking area definitions are separated from charging stations
• --include-existing: Consider existing charging stations from additional files in the computation of needed ones using --probability and --density and output them again
• --skip-equipped-edges: Place new charging stations only on edges which do not yet have one (given the definitions loaded with --add-files)
• --only-roadside: Only consider roadside parking to place charging stations (cannot be used together with --only-parking-lot)
• --only-parking-lot: Only consider parking lot spaces to place charging stations (cannot be used together with --only-roadside)
• --entire-parkings: Select only one parking area per edge which fits best the wanted number of charging points
• --separate-unused-parkings: Write parking definitions not referenced by charging stations to the path from --output-parking-file but referenced ones to --output-file
• --probability: Probability for parking areas along an edge to receive charging infrastructure
• --density: Share of the total parking spaces along an edge to be equipped with charging points
• --power: Power attribute of charging stations to create (see charging station attributes)
• --efficiency: Efficiency attribute of charging stations to create (see charging station attributes)
• --min: Minimum number of charging points to create per edge
• --max: Maximum number of charging points to create per edge
• --prefix: Prefix of generated charging station IDs
• --suffix: Suffix to append to splitted parking area
• --seed: Random seed (used for random probability, see --probability)

extractTest.py#

This scripts extracts test scenarios if you like to run a simulation scenario which is included in the test folder /tests. In order to do so, you can either: - download the complete sumo package and call:

python tools/extractTest.py <path to test directory>

• or use the online test extraction. In the online tool you enter the path to the test you like (e.g. <SUMO_HOME>/tests/sumo/extended/rerouter/use_routing_device) into the form and get a zip containing all the files.

generateParkingAreas.py#

This tool generates parking areas for a network, and saves them in an additional file. If the output filename is not defined (using -o or --output-file), it will use as default parkingareas.add.xml.

Most basic call:

python tools/generateParkingAreas.py -n <my network>

Other Example:

python tools/generateParkingAreas.py -n <my network> -o <name of output file> --space-length <visual length per parking space> --min <minimum capacity> --max <maximum capacity>

The required parameter is the network (-n or --net-file). More options can be obtained by calling python tools/generateParkingAreas.py --help.

Additional options:

• --selection-file restrict the generation to the edges mentioned in this selection file
• --output-file define the output filename
• --probability probability for an edge to receive a parkingArea
• --length length required per parking space
• --space-length visual length of each parking space
• --width visual width of each parking space
• --random-capacity randomize roadsideCapacity
• --min minimum capacity for parkingAreas
• --max maximum capacity for parkingAreas
• --angle parking area angle
• --lefthand create parking areas to the left of the edge (only where no neighbor lane is marked, see opposite direction driving)
• --on-road will force the parking area to be created on the road (vehicles will stop directly on the lane)
• --on-road.lane-offset sets the lane(s) on-road parking areas will be created (either use a negative value for all lanes or enter a lane index)
• --prefix prefix for the parkingArea ids
• --seed random seed
• --random use a random seed to initialize the random number generator
• --vclass only use edges which permit the given vehicle class
• --verbose tell me what you are doing

generateParkingLots.py#

This script generates parking lots. Example:

python tools/generateParkingLots.py -b <xmin, ymin, xmax, ymax> -c <connecting edge>
 [-i <parking-id> -n <number of parking spaces> -l <space-length> -a <space-angle> ...]

or

python tools/generateParkingLots.py -x <x-pos> -y <y-pos> -c <connecting edge>
 [-i <parking-id> -n <number of parking spaces> -l <space-length> -a <space-angle> ...]

The required parameter are the shape (--bounding-box) or the position (--x-axis and --y-axis) of the parking lot and the connecting edge (--connecting-edge). More options can be obtained by calling python tools/generateParkingLots.py --help.

Additional options:

• --parking-id defines the name/id of the parking lot
• --parking-spaces defines the number of the parking spaces
• --start-position defines the begin position of the entrance/exit of the parking lot
• --end-position defines the end position of the entrance/exit of the parking lot
• --space-length defines the length of each parking space
• --space-angle defines the angle of the parking spaces
• --x-space-distance defines the lateral distance (x-direction) between the locations of two parking spaces
• --y-space-distance defines the longitudinal distance (y-direction) between the locations of two parking spaces
• --rotation-degree defines the rotation degree of the parking lot
• --adjustrate-x defines the modification rate of x-axis if the rotation exists
• --adjustrate-y defines the modification rate of y-axis if the rotation exists
• --output-suffix output suffix
• --fullname full name of parking area
• --verbose tell me what you are doing

generateStationEdges.py#

This script generates a pedestrian edge for each public transport stop (in the form of .nod.xml and .edg.xml files). The output is suitable for extending rail-only networks with the bare minimum of pedestrian infrastructure for departing, changing trains and arriving. Example:

python tools/generateStationEdges.py rail.net.xml stops.xml
 netconvert -s rail.net.xml -e stops.access.edg.xml -n stops.access.nod.xml --ptstop-files stops.xml -o railForPersons.net.xml --ptstop-output stopsWithAccess.xml

generateRerouters.py#

This script generates rerouter for closing a given list of roads. It will automatically identify where to place the notification signs to facilitate rerouting.

python tools/generateRerouters.py -n <net-file> -o <output-file> -x CLOSED_EDGE1,CLOSED_EDGE2

generateContinuousRerouters.py#

This script generates rerouter definitions for a continuously running simulation. Rerouters are placed ahead of each intersection with routes leading up to the next intersection and configurable turning ratios. Vehicles that enter the simulation will circulate continuously (unless hitting a dead-end). Example:

python tools/generateContinuousRerouters.py -n <net-file> -o <output-file>

generateParkingAreaRerouters.py#

This script generates parking area rerouters from a parking area definition. Example:

python tools/generateParkingAreaRerouters.py -n <net-file> -a <parkingArea-file> -o <output-file>

averageTripStatistics.py#

This script runs a given sumo configuration multiple times with different random seeds and averages the trip statistics output (see trip statistics).

Example:

python tools/averageTripStatistics.py <sumocfg-file>

As default, the simulation will be run 10 times with an initial seed for random seed generation of 42. These values can be changed with the options -n and -s respectively.

ptlines2flows.py#

This script determines feasible stop-to-stop travel times and creates a public transport schedule (regular interval timetable) for all lines. The stop-to-stop travel times are determined by running a background simulation on an empty network using either a given route or shortest paths between stops. Example:

python tools/ptlines2flows.py -n <net-file> -s <ptstops-file> -l <ptlines-file> -o <output-file>

As output, the public transport lines are written as flows. By default a period of 600 seconds is adopted as regular interval, which can be changed with the -p option.

With the option --use-osm-routes, public transport routes from the given osm ptlines-file will be used, rather than creating new shortest path routes between stops.

A ptlines-file is typically created by netconvert option --ptline-output when importing OSM data. However it can also be customized or created from scratch for a non OSM network.

Example Input#

A minimal description for a bus line looks like this:

<additional>
    <ptLine id="0" line="123" type="bus">
        <busStop id="stopA"/>
        <busStop id="stopB"/>
        <busStop id="stopC"/>
    </ptLine>
</additional>

Example Output#

The used busStops must be defined in an additional file and passed with option -s when running the tool. The resulting bus definition may look like this:

<routes xmlns:xsi="https://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="https://sumo.dlr.de/xsd/routes_file.xsd">
    <vType id="bus" vClass="bus"/>
    <route id="bus_123:0" edges="110450334#1 110450334#2 338412122 391493949 391493947 391493950#0 391493950#1 391493952#0 391493952#1 391493952#2 391493954#0 391493954#1 391493954#2 391493954#3">
        <stop busStop="stopA" duration="20" until="35.0"/>
        <stop busStop="stopB" duration="20" until="101.0"/>
        <stop busStop="stopC" duration="20" until="221.0"/>
    </route>
    <flow id="bus_123:0" type="bus" route="bus_123:0" begin="0.0" end="3600.0" period="600" line="123:0" />
</routes>

Further Options#

• --types: only export lines with the given list of types
• --bus.parking: let busses clear the road while stopping
• --vtype-prefix: prefix for generated vehicle types (to allow combining multiple runs in the same simulation)
• --stop-duration: minimum duration for stops (default 20)
• --stop-duration.slack: time to reserve in the schedule per stop (default 10)
• --speedfactor.bus: assumed relative travel speed of busses (default 0.95)
• --speedfactor.tram: assumed relative travel speed of trams (default 1)
• --night: only export lines that run during the night (by default, only lines running during the day are used)
• --begin: flow begin time in output (default 0)
• --end: flow end time in output (default 3600)
• --min-stops: minimum number of stops to use a line (default 2)
• --flow-attribute: additional attributes to include in the flows (i.e. "departSpeed=\"max\"")
• --extend-to-fringe: whether vehicles should start on the first route edge rather than the first stop
• --random-begin: whether to set the flow begin time to a random value between options --begin and the period of the line
• --no-vtypes: whether to skip writing vTypes for the output
• --seed: set random seed
• --ignore-errors: ignore various input errors
• --human-readable-time: write all times as (H:M:S)
• --verbose: more output

Available ptLine Attributes#

These values have the following meanings:

tileGet.py#

This script retrieves background images from ESRI ArcGIS tile servers and other imaging APIs such as Google Maps and MapQuest. The simplest usage is to call it with a SUMO network file only. It will generate a visualization settings file containing the coordinates which can be loaded with sumo-gui or netedit. The most useful options are -t for the (maximum) number of tiles to retrieve and -u to give the URL of the tile server. Examples:

• Retrieving data from the public ArcGIS online instance:

python tools/tileGet.py -n test.net.xml -t 10

• Retrieving satellite data from Google or MapQuest (Requires obtaining an API-key first):

python tools/tileGet.py -n test.net.xml -t 10 --url maps.googleapis.com/maps/api/staticmap --key YOURKEY
python tools/tileGet.py -n test.net.xml -t 10 --url www.mapquestapi.com/staticmap/v5/map --key YOURKEY

The generated setting file can be loaded in sumo-gui with:

sumo-gui -n test.net.xml -g settings.xml

stateReplay.py#

Synchronizes saved state files from a (remote) simulation and replays them in a local sumo-gui instance to observe the remote simulation.

To observe every step in a simulation with step length 1s, the remote simulation must be started with option --save-state.period 1. In order to conserve disk space, the option --save-state.period.keep 3 is recommended. (i.e. to retain only the last 3 simulation state files at any time).

To replay the state files the following call can be used:

python tools/stateReplay --sumo-config replay.sumocfg --src REMOTE_FOLDER --dst LOCAL_FOLDER

The given .sumocfg file only needs to include the network and any additional infrastructure referenced by the remote simulation. The value of REMOTE_FOLDER can be any folder as understood by rsync (i.e. remotehost:~/myfolder). If you use ssh make sure that you can access the remote folder without a password by creating a public-private key pair.

If you need to pass additional options to rsync you can append them to the command line, e.g. for a custom ssh port and verbose output:

python tools/stateReplay --sumo-config replay.sumocfg --src REMOTE_FOLDER --dst LOCAL_FOLDER -v -e "ssh -p PORT"

runSeeds.py#

Run a (sumo) configuration multiple times with different seeds.

Example:

python tools/runSeeds.py -k test.sumocfg --seeds 7,11,13

• option --seeds can either be given as a list or as a range (0:100).
• the application path can be set with option --application (-a). Default is sumo.
  • by passing a comma-separated list of applications, each one will be run with all seeds and results will be put into a subfolder
• the application config path must be set with with option --configuration (-k)
  • by passing a comma-separated list of configs, each one will be run with all seeds and results will be put into a subfolder
• option --output-prefix (-p) can be used to define a prefix for all written output files. The string "SEED" is replaced by the current seed. (default prefix is "SEED.")
• option --threads INT can be used to perform application runs in parallel
• any additional options are forwarded to the application