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International Journal on Advances in Systems and Measurements, vol 5 no 3 & 4, year 2012, http://www.iariajournals.org/systems_and_measurements/
Figure 1. Examples of abstract road networks as built using
“netgenerate”; from left to right: grid (“manhattan”, spider, and random
network)
The road network importer netconvert converts networks
from other traffic simulators such as VISUM [5], Vissim, or
MATSim [6]. It also reads other common digital road
network formats, such as shapefiles or OpenStreetMap [7].
Besides these formats, netconvert is also capable to read less
known formats, such as OpenDRIVE or the RoboCup
network format. Figures 2 and 3 show the capabilities to
import road networks from OpenStreetMap by example,
comparing the original rendering on OpenStreetMap’s web
pages against SUMO rendering of the imported network.
Figure 2. Original OpenStreetMap network of Gothenborg.
Figure 3. Gothenborg network imported into SUMO.
Additionally, netconvert reads a native, SUMO-specific,
XML-representation of a road network graph referred to as
“plain” XML, which allows the highest degree of control for
describing a road network for SUMO. This XML
representation is broken into five file types, each for
description of nodes, edges, optionally edge types,
connections, and (fixed) traffic light plans. Edge types name
sets of default edge attributes, which can be referenced by
the later loaded edges. Nodes describe the intersections,
edges the road segments. Connections describe which lanes
incoming into an intersection are connected to which
outgoing lanes. The simulation network created by
netconvert contains heuristically computed values wherever
the inputs are incomplete as well as derived values such as
the exact geometry at junctions. It is also possible to convert
a simulation network back into the “plain” format. Multiple
input formats can be loaded at the same time and are
automatically merged. Since the “plain” format allows
specifying the removal of network elements and the adaption
of single edge and lane parameters, it can be used for a wide
range of network modifications. To support such
modifications SUMO additionally provides the python tool
netdiff.py, which computes the (human-readable) difference
D between two networks A and B. Loading A and D with
netconvert reproduces B.
Most of the available digital road networks are originally
meant to be used for routing (navigation) purposes. As such,
they often lack the grade of detail needed by microscopic
road traffic simulations: the number of lanes, especially in
front of intersections, information about which lanes
approach which consecutive ones, traffic light positions and
plans, etc., are missing. Sharing the same library for
preparing generated/imported road networks, see Figure 4,
both, netgenerate and netconvert, try to determine missing
values using heuristics. A coarse overview on this
preparation process can be found in [8]. However, most of
the algorithms described in [8] have been reworked since its
publication. Additional, optional heuristics guess locations of
highway on- and off-ramps, roundabouts, traffic lights, etc.
Figure 4. Common network preparation procedure in netconvert and
netgenerate.
Even with the given functionality, it should be stated that
preparing a real-world network for a microscopic simulation
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