example_05en_gridlock_and_prevention.py

from uxsim import *

print("####"*10)
print("# gridlock scenario")
# simulation world
W = World(
    name="gridlock",
    deltan=5,
    tmax=6000,
    print_mode=1, save_mode=1, show_mode=1,
    random_seed=0
)

# scenario
#circular network for gridlock: load from CSV
W.load_scenario_from_csv("dat/uroboros_nodes.csv", "dat/uroboros_links.csv", "dat/uroboros_demand.csv")

# The following control prevents gridlock. Comment out to execute.
#W.get_link("NE").merge_priority = 2
#W.get_link("SW").merge_priority = 2

# execute simulation
W.exec_simulation()

# visualize results
W.analyzer.print_simple_stats()
W.analyzer.time_space_diagram_traj_links([["WN", "NE", "ES", "SW"]])    #trajectory of vehicles on circular roads
W.analyzer.macroscopic_fundamental_diagram()
W.analyzer.network_fancy(animation_speed_inverse=15, sample_ratio=1, interval=5, trace_length=5)
# here, you can see that two traffic congestion merges into one (like an uroboros), causing gridlock.

# output results as pandas.DataFrame
print(W.analyzer.basic_to_pandas())
print(W.analyzer.od_to_pandas())
print(W.analyzer.mfd_to_pandas())
print(W.analyzer.link_to_pandas())
print(W.analyzer.vehicles_to_pandas())



print("####"*10)
print("# no gridlock scenario")
# new simulation world
W = World(
    name="gridlock_prevented",
    deltan=5,
    tmax=6000,
    print_mode=1, save_mode=1, show_mode=1,
    random_seed=0
)

# scenario
#same network and demand as before
W.load_scenario_from_csv("dat/uroboros_nodes.csv", "dat/uroboros_links.csv", "dat/uroboros_demand.csv")

# The following control prevents gridlock.
W.get_link("NE").merge_priority = 2
W.get_link("SW").merge_priority = 2

# execute simulation
W.exec_simulation()

# visualize results
W.analyzer.print_simple_stats()
W.analyzer.time_space_diagram_traj_links([["WN", "NE", "ES", "SW"]])
W.analyzer.macroscopic_fundamental_diagram()
W.analyzer.network_fancy(animation_speed_inverse=15, sample_ratio=1, interval=5, trace_length=5)
# here, you can see that the gridlock is completely prevented by the merge priority control.


# output results as pandas.DataFrame
print(W.analyzer.basic_to_pandas())
print(W.analyzer.od_to_pandas())
print(W.analyzer.mfd_to_pandas())
print(W.analyzer.link_to_pandas())
print(W.analyzer.vehicles_to_pandas())