def create_scenario():
with temp_scenario(name="cycles",
map="maps/6lane.net.xml") as scenario_root:
actors = [
SocialAgentActor(
name=f"non-interactive-agent-{speed}-v0",
agent_locator="zoo.policies:non-interactive-agent-v0",
policy_kwargs={"speed": speed},
) for speed in [10, 30]
]
for name, (edge_start, edge_end) in [
("group-1", ("edge-north-NS", "edge-south-NS")),
("group-2", ("edge-west-WE", "edge-east-WE")),
("group-3", ("edge-east-EW", "edge-west-EW")),
("group-4", ("edge-south-SN", "edge-north-SN")),
]:
route = Route(begin=("edge-north-NS", 1, 0),
end=("edge-south-NS", 1, "max"))
missions = [Mission(route=route)] * 2
gen_social_agent_missions(
scenario_root,
social_agent_actor=actors,
name=name,
missions=missions,
)
yield scenario_root
def build_social_agent_actors(original_data):
agent_names, actors = [], []
agent_groups = {}
for group_name, agents in original_data.items():
agent_groups[group_name] = []
for agent in agents:
if "locator" in agent:
# local file-based agent
agent_locator = agent["locator"]
if "name" in agent:
agent_name = agent["name"]
else:
agent_name = agent_locator.split(":")[-1]
actor = SocialAgentActor(
name=agent_name,
agent_locator=agent_locator,
policy_kwargs=agent["params"] if "params" in agent else {},
)
else:
raise ValueError(
f"Agent {agent} configuration does not match the expected schema"
)
agent_names.append(agent_name)
actors.append(actor)
agent_groups[group_name].append(agent_name)
return agent_names, actors, agent_groups
def bubble():
"""
|(-7) |(-5) (0) (5)| (7)|
"""
return Bubble(
zone=PositionalZone(pos=(0, 0), size=(10, 10)),
margin=2,
actor=SocialAgentActor(name="zoo-car", agent_locator="come.find.me"),
)
def build_social_agent_actors(original_data):
agent_names, actors = [], []
agent_groups = {}
for group_name, agents in original_data.items():
agent_groups[group_name] = []
for agent in agents:
if "locator" in agent:
# local file-based agent
agent_locator = agent["locator"]
if "name" in agent:
agent_name = agent["name"]
else:
agent_name = agent_locator.split(":")[-1]
actor = SocialAgentActor(
name=agent_name,
agent_locator=agent_locator,
policy_kwargs=agent["params"] if "params" in agent else {},
)
elif "url" in agent:
# packaged agent, installed via pip
agent_name = f"{agent['package']}-{agent['version']}"
actor = SocialAgentActor.from_zoo(
name=agent_name,
url=agent["url"],
package=agent["package"],
version=agent["version"],
)
else:
raise ValueError(
f"Agent {agent} configuration does not match the expected schema"
)
agent_names.append(agent_name)
actors.append(actor)
agent_groups[group_name].append(agent_name)
return agent_names, actors, agent_groups
def scenario_root(scenario_parent_path):
# TODO: We may want to consider referencing to concrete scenarios in our tests
# rather than generating them. The benefit of generting however is that
# we can change the test criteria and scenario code in unison.
scenario = Path(scenario_parent_path) / "cycles"
scenario.mkdir()
shutil.copyfile(
Path(__file__).parent / "maps/6lane.net.xml", scenario / "map.net.xml")
generate_glb_from_sumo_network(str(scenario / "map.net.xml"),
str(scenario / "map.glb"))
actors = [
SocialAgentActor(
name=f"non-interactive-agent-{speed}-v0",
agent_locator="zoo.policies:non-interactive-agent-v0",
policy_kwargs={"speed": speed},
) for speed in [10, 30, 80]
]
for name, (edge_start, edge_end) in [
("group-1", ("edge-north-NS", "edge-south-NS")),
("group-2", ("edge-west-WE", "edge-east-WE")),
("group-3", ("edge-east-EW", "edge-west-EW")),
("group-4", ("edge-south-SN", "edge-north-SN")),
]:
route = Route(begin=("edge-north-NS", 1, 0),
end=("edge-south-NS", 1, "max"))
missions = [Mission(route=route)] * 2 # double up
gen_social_agent_missions(
scenario,
social_agent_actor=actors,
name=name,
missions=missions,
)
gen_missions(
scenario,
missions=[
Mission(
Route(begin=("edge-west-WE", 0, 0),
end=("edge-east-WE", 0, "max")))
],
)
return scenario
def scenario_root():
# TODO: We may want to consider referencing to concrete scenarios in our tests
# rather than generating them. The benefit of generting however is that
# we can change the test criteria and scenario code in unison.
with temp_scenario(name="cycles",
map="maps/6lane.net.xml") as scenario_root:
actors = [
SocialAgentActor(
name=f"non-interactive-agent-{speed}-v0",
agent_locator="zoo.policies:non-interactive-agent-v0",
policy_kwargs={"speed": speed},
) for speed in [10, 30, 80]
]
for name, (edge_start, edge_end) in [
("group-1", ("edge-north-NS", "edge-south-NS")),
("group-2", ("edge-west-WE", "edge-east-WE")),
("group-3", ("edge-east-EW", "edge-west-EW")),
("group-4", ("edge-south-SN", "edge-north-SN")),
]:
route = Route(begin=("edge-north-NS", 1, 0),
end=("edge-south-NS", 1, "max"))
missions = [Mission(route=route)] * 2 # double up
gen_social_agent_missions(
scenario_root,
social_agent_actor=actors,
name=name,
missions=missions,
)
gen_missions(
scenario_root,
missions=[
Mission(
Route(begin=("edge-west-WE", 0, 0),
end=("edge-east-WE", 0, "max")))
],
)
yield scenario_root
# select it by sumo NETEDIT
starting_edges = ["-156328679", "gneE9", "179968249", "138566998"]
#########################################
# generate social agents with predefined policy
#########################################
#
# N.B. You need to have the agent_locator in a location where the left side can be resolved
# as a module in form:
# "this.resolved.module:attribute"
# In your own project you would place the prefabs script where python can reach it
social_agent1 = SocialAgentActor(
name="zoo-car1", agent_locator="agent_prefabs:zoo-agent1-v0",
)
social_agent2 = SocialAgentActor(
name="zoo-car2", agent_locator="agent_prefabs:zoo-agent2-v0",
)
social_agent3 = SocialAgentActor(
name="zoo-car3", agent_locator="agent_prefabs:zoo-agent2-v0",
)
# here define social agent type and numbers
social_agents = [social_agent2, social_agent3, social_agent1]
# generate social agent missisons and store social agents' information under social_agents/
for scenario, starting_edge in zip(scenario_paths, starting_edges):
import os
from smarts.sstudio import gen_social_agent_missions
from smarts.sstudio.types import Mission, Route, SocialAgentActor
scenario = os.path.dirname(os.path.realpath(__file__))
laner_agent = SocialAgentActor(
name="laner-agent",
agent_locator=
"scenarios.intersections.2lane_circle.agent_prefabs:laner-agent-v0",
)
buddha_agent = SocialAgentActor(
name="buddha-agent",
agent_locator=
"scenarios.intersections.2lane_circle.agent_prefabs:buddha-agent-v0",
)
gen_social_agent_missions(
scenario,
social_agent_actor=laner_agent,
name=f"s-agent-{laner_agent.name}",
missions=[
Mission(Route(begin=("edge-east-EW", 0, 5),
end=("edge-west-EW", 0, 5)))
],
)
gen_social_agent_missions(
scenario,
social_agent_actor=buddha_agent,
import os
from pathlib import Path
from smarts.sstudio import gen_scenario
from smarts.sstudio.types import Mission, Route, Scenario, SocialAgentActor
actors = [
SocialAgentActor(
name=f"non-interactive-agent-{speed}-v0",
agent_locator="zoo.policies:non-interactive-agent-v0",
policy_kwargs={"speed": speed},
)
for speed in [10, 30, 80]
]
def to_mission(start_edge, end_edge):
route = Route(begin=(start_edge, 1, 0), end=(end_edge, 1, "max"))
return Mission(route=route)
gen_scenario(
Scenario(
social_agent_missions={
"group-1": (actors, [to_mission("edge-north-NS", "edge-south-NS")]),
"group-2": (actors, [to_mission("edge-west-WE", "edge-east-WE")]),
"group-3": (actors, [to_mission("edge-east-EW", "edge-west-EW")]),
"group-4": (actors, [to_mission("edge-south-SN", "edge-north-SN")]),
}
),
output_dir=Path(__file__).parent,
def bubble_config_to_bubble_object(
scenario: str, bubble_config: Dict[str, Any], vehicles_to_not_hijack: Sequence[str]
) -> Bubble:
"""Converts a bubble config to a bubble object.
Args:
scenario:
A string representing the path to this scenario.
bubble_config:
A dictionary with 'location', 'actor_name', 'agent_locator', and
'agent_params' keys that is used to initialize the bubble.
vehicles_to_not_hijack:
A tuple of vehicle IDs that are passed to the bubble. The bubble will not
capture those vehicles that have an ID in this tuple.
Returns:
Bubble: The bubble object created from the bubble config.
"""
BUBBLE_MARGIN = 2
map_file = sumolib.net.readNet(f"{scenario}/map.net.xml")
location_name = bubble_config["location"][0]
location_data = bubble_config["location"][1:]
actor_name = bubble_config["actor_name"]
agent_locator = bubble_config["agent_locator"]
agent_params = bubble_config["agent_params"]
if location_name == "intersection":
# Create a bubble centered at the intersection.
assert len(location_data) == 2
bubble_length, bubble_width = location_data
bubble_coordinates = map_file.getNode("junction-intersection").getCoord()
zone = PositionalZone(
pos=bubble_coordinates, size=(bubble_length, bubble_width)
)
else:
# Create a bubble on one of the lanes.
assert len(location_data) == 4
lane_index, lane_offset, bubble_length, num_lanes_spanned = location_data
zone = MapZone(
start=("edge-" + location_name, lane_index, lane_offset),
length=bubble_length,
n_lanes=num_lanes_spanned,
)
bubble = Bubble(
zone=zone,
actor=SocialAgentActor(
name=actor_name,
agent_locator=agent_locator,
policy_kwargs=agent_params,
initial_speed=None,
),
margin=BUBBLE_MARGIN,
limit=None,
exclusion_prefixes=vehicles_to_not_hijack,
follow_actor_id=None,
follow_offset=None,
keep_alive=False,
)
return bubble
gen_traffic(
scenario,
traffic,
name=f"{name}-{seed}",
seed=seed,
)
# Social Agents
#
# N.B. You need to have the agent_locator in a location where the left side can be resolved
# as a module in form:
# "this.resolved.module:attribute"
# In your own project you would place the prefabs script where python can reach it
social_agent1 = SocialAgentActor(
name="zoo-car1",
agent_locator="scenarios.zoo_intersection.agent_prefabs:zoo-agent2-v0",
initial_speed=20,
)
social_agent2 = SocialAgentActor(
name="zoo-car2",
agent_locator="scenarios.zoo_intersection.agent_prefabs:zoo-agent2-v0",
initial_speed=20,
)
gen_social_agent_missions(
scenario,
social_agent_actor=social_agent2,
name=f"s-agent-{social_agent2.name}",
missions=[Mission(RandomRoute())],
)