With the inifile the simulation with jpscore can be controlled.

The typical structure of an inifile is as follows:

       <!-- seed , geometry, output format -->

      <!-- traffic information: e.g closed doors or smoked rooms -->

  <!-- goals (closed polygons) outside the geometry-->

          <!--persons information and distribution -->

      <model id="n" description="name">
          <!-- parameters of model (<n>, "name")  -->
      <!-- other models can be defined -->

      <router router_id="n" description="name">
          <!-- parameters of router (<n>, "name")  -->
      <!-- other routers can be defined -->


The header comprises the following elements:

  • <seed>s</seed>

    Set the seed value of the random number generator to s. If missing the current time (time(NULL)), is used i.e. random initial conditions.

  • <max_sim_time>t</max_sim_time> the maximal simulation time in seconds.

  • <num_threads>n</num_threads> the number of used cores.

  • <show_statistics>true</show_statistics> Show different aggregate statistics e.g. the usage of the doors. (default: false)

  • <logfile>log.txt</logfile> save relevant information about the simulation to a log file. Useful to keep track of warnings or errors that may rise during a simulation.

  • <progressbar/>: show a progress bar of the simulation.

  • The trajectory file

 <trajectories format="xml-plain" fps="8" color_mode="velocity">
    <file location="trajectories.xml" />   </trajectories>

The options for the format are

  • xml-plain: the default xml format. It can lead to large files. See section xml-plain.

  • plain: simple text format. See section plain.

  • The value fps defines the frame rate per second for the trajectories.

    • color_mode: coloring agents in the trajectories. Options are:
      • velocity (default): color is proportional to speed (slow –> red).
      • spotlight
      • group: color by group
      • knowledge
      • router
      • final_goal
      • intermediate_goal
    • file location defines the location of the trajectories. All paths are relative to the location of the project file.
  • <geometry>geometry.xml</geometry> The name and location of the geometry file. All file locations are relative to the actual location of the project file. See specification of the geometry format.

Traffic constraints

This section defines constraints related to the traffic. At the moment the state of the doors can be changed (open or close)

    <!-- doors states are: close or open -->
        <door trans_id="4" caption="Main-gate" state="open" />
        <door trans_id="6" caption="Rear-gate" state="close" />
  • trans_id: unique id of that specific door as defined in the geometry file. See geometry.

  • caption: optional parameter defining the caption of the door.

  • state defines the state of the door. Options are close or open.


Additional goals might be defined outside the geometry. They should NOT overlap with any walls or be inside rooms. It is recommended to position them near the exits.

Goals are defined with close polygons, with the last vertex is equal to the first one.

        <goal id="0" final="false" caption="goal 1">
                <vertex px="-5.0" py="-5.0" />
                <vertex px="-5.0" py="-2.0" />
                <vertex px="-3.0" py="-2.0" />
                <vertex px="-3.0" py="-5.0" />
                <vertex px="-5.0" py="-5.0" />
        <goal id="1" final="false" caption="goal 2">
                <vertex px="15.0" py="-5.0" />
                <vertex px="17.0" py="-5.0" />
                <vertex px="17.0" py="-7.0" />
                <vertex px="15.0" py="-7.0" />
                <vertex px="15.0" py="-5.0" />


There are two ways to distribute agents for a simulation:


An example how to define agent’s characteristics with different number of attributes is as follows

     <group group_id="1" room_id="0" number="10" />

     <group group_id="2" room_id="0" subroom_id="0" number="10"
           goal_id="" router_id="1" />

  • group_id: mandatory parameter defining the unique id of that group.

  • number: mandatory parameter defining the number of agents to distribute.

  • room_id: mandatory parameter defining the room where the agents should be randomly distributed.

  • subroom_id: defines the id of the subroom where the agents should be distributed. If omitted then the agents are homogeneously distributed in the room.

  • goal_id: should be one of the ids defined in the section goals. If omitted or is -1 then the shortest exit to the outside is chosen by the agent.

  • router_id: defines the route choice model to be used. See documentation of available routers.

  • age: not yet used by the operational models.

  • gender: not yet used.

  • height: not yet used.

  • patience: this parameter influences the route choice behavior when using the quickest path router. It basically defines how long a pedestrian stays in jams before attempting a rerouting.

  • pre_movement_mean and pre_movement_sigma: premovement time is Gauss-distributed .

  • Risk tolerance can be Gauss-distributed, or beta-distributed. If not specified then it is defined as :

    • risk_tolerance_mean and risk_tolerance_sigma: .

    • risk_tolerance_alpha and risk_tolerance_beta: .

  • x_min, x_max, y_min and y_max: define a bounding box where agents should be distributed.

  • startX, startY: define the initial coordinate of the agents. This might be useful for testing/debugging. Note that these two options are only considered if number=1.

  • agent_parameter_id: choose a set of parameters for the operational models.


Besides distributing agents randomly before the simulation starts, it is possible to define sources in order to “inject” new agents in the system during the simulation.

 <source id="1" frequency="2" agents_max="10" group_id="1" caption="caption" greedy="true"/>
 <source id="2" time="10" agent_id="50" group_id="1" caption="caption" greedy="true"/>
  • id: id of the source
  • frequency: number of pedestrians per second.
  • agents_max: maximal number of agents produced by that source.
  • group_id: group id of the agents. This id should match a predefined group in the section Agents_distribution.
  • caption: caption
  • greedy (default false): returns a Voronoi vertex randomly with respect to weights proportional to squared distances. For vertexes and distances to their surrounding seeds calculate the probabilities as

    If this attribute is set to true, the greedy approach is used. That means new agents will be placed on the vertex with the biggest distance to the surrounding seeds.

  • time: time of appearance of agent with id agent_id. Here agents_max=1.
  • startX, startY: Distribute one pedestrians at a fix position.

    Operational models

    One of the available operational models should be defined.


One of the available routers should be defined.