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4. Weight for Road Network

The present model will introduce how to design a road system, or graph, based on the road GIS data and provide each edge a weight representing the destruction level of the road.


  • Add a destruction_coeff variable to the road agent. The value of this variable is higher or equal to 1 or lower or equal to 2. At initialization, the value of this variable is randomly defined between 1 and 2.
  • In the road network graph, more a road is worn out (destruction_coeff high), more a people agent takes time to go all over it. Then the value of the arc representing the road in the graph is equal to "length of the road * destruction_coeff".
  • The color of the road depends on the destruction_coeff. If "destruction_coeff = 1", the road is green, if "destruction_coeff = 2", the road is red.

Model Definition

road agent

We add a destruction_coeff variable which initial value is randomly defined between 1 and 2 and which have a max of 2. The color of the agent will depend on this variable. In order to simplify the GAML code, we define a new variable colorValue that represents the value of red color and that will be defined between 0 and 255.

species road  {
float destruction_coeff <- rnd(1.0,2.0) max: 2.0;
int colorValue <- int(255*(destruction_coeff - 1)) update: int(255*(destruction_coeff - 1));
rgb color <- rgb(min([255, colorValue]),max ([0, 255 - colorValue]),0) update: rgb(min([255, colorValue]),max ([0, 255 - colorValue]),0) ;

weighted road network

In GAMA, adding a weight for a graph is very simple, we use the with_weights operator with the graph for left-operand and a weight map for the right-operand. The weight map contains the weight of each edge: [edge1::weight1, edge2:: weight2,...]. In this model, the weight will be equal to the length of the road (perimeter of the polyline) its destruction coefficient.

    init {
create road from: shape_file_roads ;
map<road,float> weights_map <- road as_map (each:: (each.destruction_coeff * each.shape.perimeter));
the_graph <- as_edge_graph(road) with_weights weights_map;

Complete Model