Route Choice set generation

In this example, we show how to generate route choice sets for estimation of route choice models, using a a city in La Serena Metropolitan Area in Chile.

References

• Route Choice

See also

Several functions, methods, classes and modules are used in this example:

• aequilibrae.paths.RouteChoice()

# Imports
from uuid import uuid4
from tempfile import gettempdir
from os.path import join

import folium
import numpy as np
from aequilibrae.utils.create_example import create_example

# We create the example project inside our temp folder
fldr = join(gettempdir(), uuid4().hex)

project = create_example(fldr, "coquimbo")

Model parameters

Let’s select a set of nodes of interest

od_pairs_of_interest = [(71645, 79385), (77011, 74089)]
nodes_of_interest = (71645, 74089, 77011, 79385)

Let’s build all graphs

project.network.build_graphs()
# We get warnings that several fields in the project are filled with NaNs.
# This is true, but we won't use those fields.

/home/runner/work/aequilibrae/aequilibrae/aequilibrae/paths/graph.py:248: UserWarning: Found centroids not present in the graph!
[  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
 127 128 129 130 131 132 133]
  warnings.warn("Found centroids not present in the graph!\n" + str(centroids[~present_centroids]))
/home/runner/work/aequilibrae/aequilibrae/aequilibrae/paths/graph.py:248: UserWarning: Found centroids not present in the graph!
[  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
 127 128 129 130 131 132 133]
  warnings.warn("Found centroids not present in the graph!\n" + str(centroids[~present_centroids]))

We grab the graph for cars

graph = project.network.graphs["c"]

# we also see what graphs are available
project.network.graphs.keys()

graph.set_graph("distance")

# We set the nodes of interest as centroids to make sure they are not simplified away when we create the network
graph.prepare_graph(np.array(nodes_of_interest))

Route Choice class

Here we’ll construct and use the Route Choice class to generate our route sets

from aequilibrae.paths import RouteChoice

This object construct might take a minute depending on the size of the graph due to the construction of the compressed link to network link mapping that’s required. This is a one time operation per graph and is cached.

rc = RouteChoice(graph)

It is highly recommended to set either max_routes or max_depth to prevent runaway results.

We’ll also set a 5% penalty (penalty=1.05), which is likely a little too large, but it creates routes that are distinct enough to make this simple example more interesting.

rc.set_choice_set_generation("bfsle", max_routes=5, penalty=1.05)
rc.prepare(od_pairs_of_interest)
rc.execute(perform_assignment=True)

choice_set = rc.get_results()

If we were interested in storing the route choice result, we could also write them to disk using the save_path_files method.

# rc.save_path_files(path)

From those path files we could also preform a full assignment or select link analysis by using the execute_from_path_files method.

# rc.execute_from_path_files(path)

Or if we had externally computed route choice sets, we can use AequilibraEs assignment procedures by loading them with the ``execute_from_pandas` method.

# rc.execute_from_pandas(path_files_df)

Plotting choice sets

Now we will plot the paths we just created for the second OD pair

# We get the data we will use for the plot: links, nodes and the route choice set
plot_routes = choice_set[(choice_set["origin id"] == 77011)]["route set"].values

links = project.network.links.data

# For ease of plot, we create a GeoDataFrame for each route in the choice set
route_1 = links[links.link_id.isin(plot_routes[0])]
route_2 = links[links.link_id.isin(plot_routes[1])]
route_3 = links[links.link_id.isin(plot_routes[2])]
route_4 = links[links.link_id.isin(plot_routes[3])]
route_5 = links[links.link_id.isin(plot_routes[4])]

nodes = project.network.nodes.data
nodes = nodes[nodes["node_id"].isin([77011, 74089])]

map = route_1.explore(color="red", style_kwds={"weight": 3}, name="route_1")
map = route_2.explore(m=map, color="blue", style_kwds={"weight": 3}, name="route_2")
map = route_3.explore(m=map, color="green", style_kwds={"weight": 3}, name="route_3")
map = route_4.explore(m=map, color="purple", style_kwds={"weight": 3}, name="route_4")
map = route_5.explore(m=map, color="orange", style_kwds={"weight": 3}, name="route_5")

map = nodes.explore(m=map, color="black", style_kwds={"radius": 5, "fillOpacity": 1.0}, name="network_nodes")

folium.LayerControl().add_to(map)
map

Make this Notebook Trusted to load map: File -> Trust Notebook

project.close()

This project at /tmp/3c4b770e1fbc45b8aef85de426e95538 is already closed