After having generated a network, one could take a look at it using
sumo-gui, but no cars would be driving around.
One still needs some kind of description about the vehicles. This is
called the *traffic demand*. From now on we will use the following
nomenclature: A **trip** is a vehicle movement from one place to another
defined by the starting edge (street), the destination edge, and the
departure time. A **route** is an expanded trip, that means, that a
route definition contains not only the first and the last edge, but all
edges the vehicle will pass. sumo and
sumo-gui need routes as input for vehicle
movements. There are several ways to generate routes for SUMO. The
choice depends on your available input data:

## Using trip definitions#

As described above, each trip consists at least of the starting and
the ending edge and the departure time. This is useful for when you
want to create *demand* by hand or when writing your own scripts to
import custom data. You may either use
duarouter to turn your trips into routes.
See
Demand/Shortest_or_Optimal_Path_Routing
and
Demand/Dynamic_User_Assignment,
or you may load the trips directly into sumo
(more details).

## Using flow definitions#

This is mostly the same approach as using trip definitions, but one may join vehicles having the same departure and arrival edge using this method

## Using Randomization#

This is a quick way to get some traffic if you do not have access to any measurements but the results are highly unrealistic. See Tools/Trip#randomTrips.py

## Using OD-matrices#

Origin-Destination-Matrices (or OD-matrices) are often available from traffic authorities. They have to be converted to trips using od2trips. See Demand/Importing_O/D_Matrices, Demand/Shortest_or_Optimal_Path_Routing and Demand/Dynamic_User_Assignment.

## Using flow definitions and turning ratios#

One may also leave out the destination edges for flows and use turning ratios at junctions instead. See jtrrouter.

## Using detector data (observation points)#

Induction loops and similar devices are commonly used by authorities to measure traffic. Using dfrouter you may uses this data to generate demand. See Demand/Routes_from_Observation_Points.

## By hand#

You can of course generate route XML-files by hand. See Definition_of_Vehicles,_Vehicle_Types,_and_Routes.

## Using population statistics#

The program activitygen can be used to turn population statistics into traffic demand. See Demand/Activity-based Demand Generation.

## Using data from other sources#

see SUMO_User_Documentation#Demand_Modelling

By now, the SUMO-package contains four applications for generating routes. duarouter is responsible for importing routes or their definitions from other simulation packages and for computing routes using the shortest-path algorithm by Dijkstra. Additionally, in combination with the simulation, the duarouter can compute the dynamic user assignment formulated by C. Gawron. jtrrouter may be used if you want to model traffic statistically, using flows and turning percentages at junctions. od2trips helps you to convert OD-matrices (origin/destination-matrices) into trips. The dfrouter computes routes from given observation point measures.

## Notes#

- With use of netedit it is possible to observe the demand amount distribution of edge-based or TAZ-based relations network/TAZ related data.