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The controller deliberately keeps SUMO-specific concerns here. Generic
decision, safety, fallback, demand, topology and prediction modules remain
unchanged and are composed by this runtime.
"""
import os
import shutil
import sys
import math
import argparse
from types import SimpleNamespace
import numpy as np
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
SRC_ROOT = os.path.join(PROJECT_ROOT, "src")
if SRC_ROOT not in sys.path:
sys.path.insert(0, SRC_ROOT)
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
try:
import traci
except ImportError:
traci = None
from integration.controller import TrafficController
from integration.decision_engine import DecisionEngine
from integration.emergency import EmergencyCorridorManager
from integration.phase_generator import PhaseGenerator
from integration.prediction_adapter import TrafficPredictionAdapter
from integration.sumo_conflict_adapter import SUMOConflictAdapter
from integration.sumo_demand import SUMODemandCalculator
from integration.sumo_phase_adapter import SUMOPhaseAdapter
from integration.sumo_safety import SUMOSafetyRiskAdapter
from integration.sumo_topology_adapter import SUMOTopologyAdapter
from integration.traffic_history import TrafficHistory
from integration.sumo_prediction_controller import SUMOTrafficStateBuilder
SUMO_CONFIG = os.path.join(PROJECT_ROOT, "simulation", "configs", "corridor.sumocfg")
EMERGENCY_SUMO_CONFIG = os.path.join(
PROJECT_ROOT, "simulation", "configs", "corridor_emergency.sumocfg"
)
def _find_sumo_executable():
"""Find SUMO through configuration, PATH, or standard Windows install."""
candidates = []
if os.environ.get("SUMO_HOME"):
candidates.append(os.path.join(os.environ["SUMO_HOME"], "bin", "sumo.exe"))
path_executable = shutil.which("sumo")
if path_executable:
candidates.append(path_executable)
if os.environ.get("ProgramFiles(x86)"):
candidates.append(
os.path.join(
os.environ["ProgramFiles(x86)"], "Eclipse", "Sumo", "bin", "sumo.exe"
)
)
if os.environ.get("ProgramW6432"):
candidates.append(
os.path.join(
os.environ["ProgramW6432"], "Eclipse", "Sumo", "bin", "sumo.exe"
)
)
for candidate in candidates:
if os.path.isfile(candidate):
if not os.environ.get("SUMO_HOME"):
sumo_bin = os.path.dirname(os.path.abspath(candidate))
os.environ["SUMO_HOME"] = os.path.dirname(sumo_bin)
return candidate
return "sumo"
SUMO_CMD = [_find_sumo_executable(), "-c", SUMO_CONFIG]
NUM_SENSORS = 36
HISTORY_LENGTH = 10
CONTROL_INTERVAL = 10.0
PREDICTION_INTERVAL = 10
MIN_GREEN_SECONDS = 10.0
WARMUP_STEPS = 10
TOTAL_STEPS = 200
# Emergency preemption is intentionally proactive. The ambulance must not
# reach a red light and then wait for the controller to react. Once the
# predicted arrival is inside this window, the controller requests the safe
# green phase for the ambulance's movement before the vehicle reaches the
# junction. The vehicle never receives SUMO's special red-light bypass.
EMERGENCY_PREEMPT_ETA_SECONDS = 30.0
EMERGENCY_PREEMPT_DISTANCE_METERS = 350.0
def _clamp(value):
return max(0.0, min(1.0, float(value)))
def _phase_objects(phase_representations):
"""Adapt existing dict representations to SUMODemandCalculator's API."""
return [
SimpleNamespace(
phase_id=phase["phase_id"],
movement_ids=phase["movements"],
)
for phase in phase_representations
]
def _phase_sensor_ids(phase, sensor_builder, topology):
"""Map a phase's incoming roads to the deployment sensor zones."""
roads = {topology.movements[m].from_road for m in phase["movements"]}
return [
sensor_id
for sensor_id, info in sensor_builder.sensor_mapping.items()
if info["junction_id"] == phase["junction_id"]
and info["road_id"] in roads
]
def _safe_transition_index(program, target_index):
"""Return the transition immediately before a target green phase."""
phases = program["phases"]
target_position = next(
i for i, phase in enumerate(phases)
if phase["phase_index"] == target_index
)
if target_position == 0:
return target_index
previous = phases[target_position - 1]
if "y" in previous["state"].lower() or "r" in previous["state"].lower():
return previous["phase_index"]
return target_index
class Phase2SUMOController:
"""Run adaptive decisions independently for each discovered corridor signal."""
def __init__(
self,
sumo_cmd=None,
total_steps=TOTAL_STEPS,
control_interval=CONTROL_INTERVAL,
prediction_interval=PREDICTION_INTERVAL,
warmup_steps=WARMUP_STEPS,
traci_connection=None,
step_observer=None,
emergency_enabled=False,
decision_observer=None,
):
self.sumo_cmd = sumo_cmd or SUMO_CMD
self.total_steps = int(total_steps)
self.control_interval = float(control_interval)
self.prediction_interval = max(1, int(prediction_interval))
self.warmup_steps = int(warmup_steps)
self.traci = traci_connection or traci
self.step_observer = step_observer
self.emergency_enabled = bool(emergency_enabled)
self.decision_observer = decision_observer
self._observe_steps = False
self.decisions = []
def _simulation_step(self):
self.traci.simulationStep()
if self.step_observer is not None and self._observe_steps:
self.step_observer()
def _build_runtime(self):
topology_adapter = SUMOTopologyAdapter(self.traci)
phase_adapter = SUMOPhaseAdapter(self.traci)
conflict_adapter = SUMOConflictAdapter(phase_adapter)
demand_calculator = SUMODemandCalculator()
traffic_controller = TrafficController()
decision_engine = DecisionEngine()
signalized_ids = topology_adapter.discover_signalized_junctions()
topologies = {
junction_id: topology_adapter.discover_junction(junction_id)
for junction_id in signalized_ids
}
print(f"Signalized corridor junctions: {signalized_ids}")
runtimes = {}
for junction_id, topology in topologies.items():
conflict_graph = conflict_adapter.build_conflict_graph(
junction_id, topology, topology_adapter.sumo_metadata
)
generator = PhaseGenerator(conflict_graph)
generated = generator.generate_maximal_phases()
representations = phase_adapter.build_phase_representation(
junction_id, topology_adapter.sumo_metadata
)
if not representations:
continue
runtimes[junction_id] = {
"topology": topology,
"generator": generator,
"generated": generated,
"phases": representations,
"phase_objects": _phase_objects(representations),
"phase_by_id": {p["phase_id"]: p for p in representations},
"last_control": -float("inf"),
"last_phase": None,
"emergency_hold_phase": None,
"emergency_vehicle_id": None,
}
print(
f"Topology: {junction_id} roads={len(topology.roads)} "
f"movements={len(topology.movements)} "
f"generated_maximal_phases={len(generated)}"
)
if not runtimes:
raise RuntimeError("No usable green signal phases were discovered")
return (
topology_adapter,
traffic_controller,
decision_engine,
demand_calculator,
runtimes,
)
def _execute(self, junction_id, target_phase, phase_adapter):
current = phase_adapter.get_current_phase(junction_id)
current_state = phase_adapter.get_phase_state(junction_id, current)
program = phase_adapter.get_current_program(junction_id)
transition = _safe_transition_index(program, target_phase)
print(
f"EXECUTE time={self.traci.simulation.getTime():.1f} "
f"junction={junction_id} current_phase={current} "
f"current_state={current_state} target_phase={target_phase} "
f"transition_phase={transition}"
)
if current != target_phase:
self.traci.trafficlight.setPhase(junction_id, transition)
transition_duration = next(
(
phase["duration"]
for phase in program["phases"]
if phase["phase_index"] == transition
),
1.0,
)
max_transition_steps = max(
1,
int(math.ceil(float(transition_duration))) + 1,
)
for _ in range(max_transition_steps):
self._simulation_step()
if phase_adapter.get_current_phase(junction_id) == target_phase:
break
executed = phase_adapter.get_current_phase(junction_id)
executed_state = phase_adapter.get_phase_state(junction_id, executed)
print(
f"READBACK junction={junction_id} executed_phase={executed} "
f"resulting_state={executed_state}"
)
return {"phase": executed, "state": executed_state, "requested": target_phase}
@staticmethod
def _emergency_requires_preemption(emergency_plan):
"""Return True when the ambulance is close enough to pre-open its green."""
if emergency_plan is None or not emergency_plan.selected_phase:
return False
eta = emergency_plan.eta_seconds
distance = emergency_plan.distance_to_junction
eta_trigger = eta is not None and eta <= EMERGENCY_PREEMPT_ETA_SECONDS
distance_trigger = (
distance is not None
and distance <= EMERGENCY_PREEMPT_DISTANCE_METERS
)
return bool(eta_trigger or distance_trigger)
def _record_decision(self, record):
self.decisions.append(record)
if self.decision_observer is not None:
self.decision_observer(record)
def run(self):
command = list(self.sumo_cmd)
if self.emergency_enabled and command == SUMO_CMD:
command = [command[0], "-c", EMERGENCY_SUMO_CONFIG]
print(f"Starting SUMO: {command[2] if len(command) > 2 else command}")
self.traci.start(command)
try:
(
topology_adapter,
traffic_controller,
decision_engine,
demand_calculator,
runtimes,
) = self._build_runtime()
phase_adapter = SUMOPhaseAdapter(self.traci)
sensor_builder = SUMOTrafficStateBuilder(
num_sensors=NUM_SENSORS,
target_junctions=list(runtimes),
)
history = TrafficHistory(HISTORY_LENGTH, NUM_SENSORS)
safety_adapter = SUMOSafetyRiskAdapter(self.traci)
emergency_manager = (
EmergencyCorridorManager(self.traci)
if self.emergency_enabled else None
)
predictor = None
try:
predictor = TrafficPredictionAdapter()
except Exception as exc:
print(f"PREDICTION unavailable: {exc}; using safe baseline")
for _ in range(self.warmup_steps):
self._simulation_step()
self._observe_steps = True
predictions = np.zeros(NUM_SENSORS, dtype=np.float32)
safety_assessment = None
last_safety_assessment = -float("inf")
for step in range(self.total_steps):
self._simulation_step()
now = self.traci.simulation.getTime()
history.add_state(sensor_builder.build_state())
if now - last_safety_assessment >= self.control_interval:
safety_assessment = safety_adapter.assess()
last_safety_assessment = now
emergency_states = []
emergency_plans = {}
if emergency_manager is not None:
topology_map = {
key: value["topology"] for key, value in runtimes.items()
}
emergency_states = emergency_manager.discover(topology_map)
released_emergency_ids = emergency_manager.release_completed(
emergency_states
)
for released_vehicle_id in sorted(released_emergency_ids):
print(
f"[EMERGENCY_RELEASE] time={now:.1f} "
f"vehicle={released_vehicle_id} "
"emergency_active=False normal_ai_resumed=True"
)
emergency_plans = emergency_manager.plans(
emergency_states,
topology_map,
runtimes,
)
if predictor is not None and step % self.prediction_interval == 0:
predictions = predictor.predict(history.get_padded_history())
predictions = np.asarray(predictions, dtype=np.float32).reshape(NUM_SENSORS)
for junction_id, runtime in runtimes.items():
emergency_plan = emergency_plans.get(junction_id)
emergency_preempt = self._emergency_requires_preemption(emergency_plan)
# Normal AI decisions remain rate-limited. Emergency
# preemption is intentionally allowed to bypass that
# scheduling interval because waiting for the next normal
# control tick can make the ambulance reach a red light.
if not emergency_preempt and now - runtime["last_control"] < self.control_interval:
continue
# Once preemption starts, remember the requested green.
# While the same emergency is still approaching this
# junction, normal AI is not allowed to take the green away.
if emergency_preempt:
target_phase_id = emergency_plan.selected_phase
target_phase = runtime["phase_by_id"].get(target_phase_id)
if target_phase is None:
print(
f"[EMERGENCY_REJECT] time={now:.1f} "
f"junction={junction_id} vehicle={emergency_plan.vehicle_id} "
"reason=selected_phase_not_available"
)
continue
target_index = target_phase["phase_index"]
current_phase = phase_adapter.get_current_phase(junction_id)
if current_phase != target_index:
print(
f"[EMERGENCY_PREEMPT] time={now:.1f} "
f"junction={junction_id} "
f"vehicle={emergency_plan.vehicle_id} "
f"distance={emergency_plan.distance_to_junction} "
f"ETA={emergency_plan.eta_seconds} "
f"required_movement={emergency_plan.required_movement} "
f"open_phase={target_phase_id} "
"action=OPEN_EARLY"
)
executed = self._execute(
junction_id,
target_index,
phase_adapter,
)
runtime["emergency_hold_phase"] = target_phase_id
runtime["emergency_vehicle_id"] = emergency_plan.vehicle_id
runtime["last_control"] = self.traci.simulation.getTime()
runtime["last_phase"] = target_phase_id
self._record_decision(
{
"time": now,
"junction": junction_id,
"selected": target_phase_id,
"method": "emergency_preemption",
"safety": {
"approved": True,
"mode": "proactive_emergency_preemption",
},
"emergency_active": True,
"emergency_vehicle_id": emergency_plan.vehicle_id,
"emergency_eta": emergency_plan.eta_seconds,
"emergency_priority": emergency_plan.urgency,
"emergency_distance": emergency_plan.distance_to_junction,
"executed": executed,
}
)
else:
runtime["emergency_hold_phase"] = target_phase_id
runtime["emergency_vehicle_id"] = emergency_plan.vehicle_id
print(
f"[EMERGENCY_HOLD] time={now:.1f} "
f"junction={junction_id} "
f"vehicle={emergency_plan.vehicle_id} "
f"distance={emergency_plan.distance_to_junction} "
f"ETA={emergency_plan.eta_seconds} "
f"phase={target_phase_id} "
"action=KEEP_GREEN"
)
runtime["last_control"] = now
runtime["last_phase"] = target_phase_id
continue
# The emergency is no longer close enough to this junction.
# Release only this junction's hold; another downstream
# junction can independently enter preemption later.
if runtime["emergency_hold_phase"] is not None:
print(
f"[EMERGENCY_JUNCTION_RELEASE] time={now:.1f} "
f"junction={junction_id} "
f"vehicle={runtime['emergency_vehicle_id']} "
"action=RESUME_NORMAL_AI"
)
runtime["emergency_hold_phase"] = None
runtime["emergency_vehicle_id"] = None
topology = runtime["topology"]
movement_demand = demand_calculator.calculate_movement_demand(
topology, topology_adapter.sumo_metadata
)
phase_demand = demand_calculator.calculate_phase_demand(
runtime["phase_objects"], movement_demand
)
normalized_demand = demand_calculator.normalize_phase_demand(
phase_demand
)
prediction_values = {}
for phase in runtime["phases"]:
ids = _phase_sensor_ids(phase, sensor_builder, topology)
prediction_values[phase["phase_id"]] = (
decision_engine.calculate_phase_prediction(predictions, ids)
if ids else 0.0
)
max_prediction = max(prediction_values.values(), default=0.0)
phase_risks = {
phase["phase_id"]: safety_adapter.phase_risk(
phase, topology, safety_assessment
)
for phase in runtime["phases"]
}
phase_scores = {}
for phase in runtime["phases"]:
phase_id = phase["phase_id"]
phase_scores[phase_id] = decision_engine.calculate_phase_score(
demand=_clamp(normalized_demand.get(phase_id, 0.0)),
prediction=_clamp(
prediction_values[phase_id] / max_prediction
if max_prediction > 0 else 0.0
),
priority=0.5,
fairness=0.5,
risk=_clamp(1.0 - phase_risks[phase_id]),
)
checks = {}
current_phase = phase_adapter.get_current_phase(junction_id)
current_type = phase_adapter.get_phase_type(junction_id, current_phase)
for phase in runtime["phases"]:
phase_id = phase["phase_id"]
compatible = runtime["generator"].is_compatible(phase["movements"])
timing_valid = (
phase["phase_index"] == current_phase
or current_type != "green"
or self.control_interval >= MIN_GREEN_SECONDS
)
checks[phase_id] = {
"topology_valid": bool(topology.roads and topology.movements),
"conflict_free": compatible,
"timing_valid": timing_valid,
"pedestrian_clear": True,
"downstream_available": True,
"emergency_safe": True,
"confidence": _clamp(phase_scores[phase_id]),
"safety_risk": phase_risks[phase_id],
"accident_detected": (
safety_assessment["accident_status"] == "confirmed"
),
"safety_confidence": safety_assessment["safety_confidence"],
}
phase_ids = list(phase_scores)
current_index = next(
(
i for i, p in enumerate(runtime["phases"])
if p["phase_index"] == current_phase
),
0,
)
result = traffic_controller.decide_and_validate(
phase_scores,
checks,
phase_densities=phase_demand,
phases=phase_ids,
current_index=current_index,
)
selected = result["selected_phase"]
print(
f"DECISION time={now:.1f} junction={junction_id} "
f"current_phase={current_phase} candidates={phase_ids} "
f"movement_demand={movement_demand} phase_demand={phase_demand} "
f"prediction_available={predictor is not None} "
f"prediction_contribution={prediction_values} "
f"risk_score={phase_risks} "
f"near_miss_risk={safety_assessment['near_miss_risk']} "
f"accident_status={safety_assessment['accident_status']} "
f"accident_confidence={safety_assessment['accident_confidence']} "
f"safety_confidence={safety_assessment['safety_confidence']} "
"emergency_active=False "
f"scores={phase_scores} selected={selected} "
f"safety={'APPROVED' if result['execute'] else 'REJECTED'} "
f"reasons={result['safety'].get('reasons', [])} method={result['method']}"
)
if result["execute"] and selected is not None:
executed = self._execute(
junction_id,
runtime["phase_by_id"][selected]["phase_index"],
phase_adapter,
)
runtime["last_control"] = self.traci.simulation.getTime()
runtime["last_phase"] = selected
self._record_decision(
{
"time": now,
"junction": junction_id,
"selected": selected,
"method": result["method"],
"safety": result["safety"],
"emergency_active": False,
"emergency_vehicle_id": None,
"emergency_eta": None,
"emergency_priority": None,
"executed": executed,
}
)
finally:
self.traci.close()
print("SUMO closed safely")
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--emergency", action="store_true")
parser.add_argument("--steps", type=int, default=TOTAL_STEPS)
args = parser.parse_args()
Phase2SUMOController(
total_steps=args.steps,
emergency_enabled=args.emergency,
).run()
if __name__ == "__main__":
main()
|