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Version: 1.8.1

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.

Formulation

  • 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

model tutorial_gis_city_traffic

global {
file shape_file_buildings <- file("../includes/building.shp");
file shape_file_roads <- file("../includes/road.shp");
file shape_file_bounds <- file("../includes/bounds.shp");
geometry shape <- envelope(shape_file_bounds);
float step <- 10 #mn;
date starting_date <- date("2019-09-01-00-00-00");
int nb_people <- 100;
int min_work_start <- 6;
int max_work_start <- 8;
int min_work_end <- 16;
int max_work_end <- 20;
float min_speed <- 1.0 #km / #h;
float max_speed <- 5.0 #km / #h;
graph the_graph;

init {
create building from: shape_file_buildings with: [type::string(read ("NATURE"))] {
if type="Industrial" {
color <- #blue ;
}
}
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;

list<building> residential_buildings <- building where (each.type="Residential");
list<building> industrial_buildings <- building where (each.type="Industrial") ;
create people number: nb_people {
speed <- rnd(min_speed, max_speed);
start_work <- rnd (min_work_start, max_work_start);
end_work <- rnd(min_work_end, max_work_end);
living_place <- one_of(residential_buildings) ;
working_place <- one_of(industrial_buildings) ;
objective <- "resting";
location <- any_location_in (living_place);
}
}
}


species building {
string type;
rgb color <- #gray ;

aspect base {
draw shape color: color ;
}
}

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) ;

aspect base {
draw shape color: color ;
}
}

species people skills:[moving] {
rgb color <- #yellow ;
building living_place <- nil ;
building working_place <- nil ;
int start_work ;
int end_work ;
string objective ;
point the_target <- nil ;

reflex time_to_work when: current_date.hour = start_work and objective = "resting"{
objective <- "working" ;
the_target <- any_location_in (working_place);
}

reflex time_to_go_home when: current_date.hour = end_work and objective = "working"{
objective <- "resting" ;
the_target <- any_location_in (living_place);
}

reflex move when: the_target != nil {
do goto target: the_target on: the_graph ;
if the_target = location {
the_target <- nil ;
}
}

aspect base {
draw circle(10) color: color border: #black;
}
}


experiment road_traffic type: gui {
parameter "Shapefile for the buildings:" var: shape_file_buildings category: "GIS" ;
parameter "Shapefile for the roads:" var: shape_file_roads category: "GIS" ;
parameter "Shapefile for the bounds:" var: shape_file_bounds category: "GIS" ;
parameter "Number of people agents" var: nb_people category: "People" ;
parameter "Earliest hour to start work" var: min_work_start category: "People" min: 2 max: 8;
parameter "Latest hour to start work" var: max_work_start category: "People" min: 8 max: 12;
parameter "Earliest hour to end work" var: min_work_end category: "People" min: 12 max: 16;
parameter "Latest hour to end work" var: max_work_end category: "People" min: 16 max: 23;
parameter "minimal speed" var: min_speed category: "People" min: 0.1 #km/#h ;
parameter "maximal speed" var: max_speed category: "People" max: 10 #km/#h;

output {
display city_display type: opengl {
species building aspect: base ;
species road aspect: base ;
species people aspect: base ;
}
}
}