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https://github.com/firestar5683/StarPilot.git
synced 2026-09-03 14:43:48 +08:00
test3
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@@ -4,7 +4,7 @@ import pytest
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from types import SimpleNamespace
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from openpilot.common.realtime import DT_MDL
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from openpilot.starpilot.common.starpilot_variables import DEFAULT_LATERAL_ACCELERATION, PLANNER_TIME
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from openpilot.starpilot.common.starpilot_variables import DEFAULT_LATERAL_ACCELERATION
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from openpilot.starpilot.controls.lib.curve_speed_controller import (
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CSC_APPROACH_DECEL,
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CSC_COMFORT_MARGIN,
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@@ -13,6 +13,7 @@ from openpilot.starpilot.controls.lib.curve_speed_controller import (
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CSC_LAT_ACCEL_MAX,
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CSC_MIN_SPEED,
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CSC_NUDGE_WEIGHT,
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CSC_TRAINING_SETTLE_TIME,
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CurveSpeedController,
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weighted_isotonic,
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)
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@@ -298,7 +299,7 @@ def test_legacy_off_grid_curvature_data_merges_into_buckets():
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def test_training_update_step_is_capped_by_ema_count():
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planner, controller = make_controller(curvature_data={"0.02": {"average": 2.0, "count": 10000}}, driving_in_curve=True)
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planner.lateral_acceleration = 3.0
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controller.training_timer = PLANNER_TIME
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controller.training_timer = CSC_TRAINING_SETTLE_TIME
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controller.log_data(10.0, make_sm(long_active=False))
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@@ -313,17 +314,67 @@ def test_no_passive_training_right_after_csc_limited_speed():
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converge(controller, 15.0, 30.0)
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assert controller.training_quiet_timer > 0.0
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controller.training_timer = PLANNER_TIME
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controller.training_timer = CSC_TRAINING_SETTLE_TIME
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controller.log_data(10.0, make_sm(long_active=False))
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assert "0.02" not in controller.curvature_data
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assert not controller.enable_training
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controller.training_quiet_timer = 0.0
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controller.training_timer = PLANNER_TIME
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controller.training_timer = CSC_TRAINING_SETTLE_TIME
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controller.log_data(10.0, make_sm(long_active=False))
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assert controller.curvature_data["0.02"]["count"] == 1
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def test_training_settles_within_a_couple_of_seconds():
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# a real drive rarely holds every eligibility condition for a whole model horizon,
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# so the settle time has to be short enough that ordinary curves still teach it
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planner, controller = make_controller(driving_in_curve=True)
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planner.lateral_acceleration = 2.4
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sm = make_sm(long_active=False)
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for _ in range(int(CSC_TRAINING_SETTLE_TIME / DT_MDL) - 2):
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controller.log_data(10.0, sm)
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assert "0.02" not in controller.curvature_data
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for _ in range(3):
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controller.log_data(10.0, sm)
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assert controller.curvature_data["0.02"]["count"] >= 1
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def test_brief_ineligibility_does_not_restart_the_settle_timer():
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planner, controller = make_controller(driving_in_curve=True)
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planner.lateral_acceleration = 2.4
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sm = make_sm(long_active=False)
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for _ in range(int(CSC_TRAINING_SETTLE_TIME / DT_MDL) + 1):
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controller.log_data(10.0, sm)
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trained = controller.curvature_data["0.02"]["count"]
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# a lead flickers into the tracker for two frames, then leaves
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planner.tracking_lead = True
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controller.log_data(10.0, sm)
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controller.log_data(10.0, sm)
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planner.tracking_lead = False
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controller.log_data(10.0, sm)
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assert controller.curvature_data["0.02"]["count"] == trained + 1
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def test_sustained_ineligibility_still_drains_the_settle_timer():
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planner, controller = make_controller(driving_in_curve=True)
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planner.lateral_acceleration = 2.4
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engaged = make_sm(long_active=True)
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manual = make_sm(long_active=False)
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for _ in range(int(CSC_TRAINING_SETTLE_TIME / DT_MDL) + 1):
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controller.log_data(10.0, manual)
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for _ in range(int(2 * CSC_TRAINING_SETTLE_TIME / DT_MDL)):
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controller.log_data(10.0, engaged)
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assert controller.training_timer == pytest.approx(0.0)
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controller.log_data(10.0, manual)
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assert not controller.enable_training
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def test_gas_override_nudges_bucket_up_once_per_episode():
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_, controller = make_controller()
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prior = controller.learned_lat_accel(0.02)
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@@ -75,12 +75,12 @@ def make_sm(*, standstill=True, min_steer_speed=0.0):
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}
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def update_vcruise(vcruise, sm, toggles, *, now, v_ego=0.0, controls_enabled=True):
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def update_vcruise(vcruise, sm, toggles, *, now, v_ego=0.0, v_cruise=20.0, controls_enabled=True):
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return vcruise.update(
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controls_enabled=controls_enabled,
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now=now,
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time_validated=True,
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v_cruise=20.0,
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v_cruise=v_cruise,
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v_ego=v_ego,
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sm=sm,
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starpilot_toggles=toggles,
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@@ -333,6 +333,49 @@ def test_csc_res_press_defers_to_slc_confirmation():
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assert vcruise.csc_controlling_speed
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def test_curve_speed_controller_glow_stays_off_while_the_target_is_above_v_ego():
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planner, vcruise = make_vcruise()
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sm = make_sm(standstill=False)
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toggles = make_toggles()
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toggles.curve_speed_controller = True
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# a highway sweeper trims the target well under the set speed but never under v_ego,
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# so the car keeps accelerating and the driver feels nothing
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def set_curve_target(_v_ego, _v_cruise):
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vcruise.csc.target = 26.0
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vcruise.csc.update_target = set_curve_target
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result = update_vcruise(vcruise, sm, toggles, now=90.0, v_ego=20.0, v_cruise=30.0)
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assert result == pytest.approx(26.0)
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assert not vcruise.csc_controlling_speed
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def test_curve_speed_controller_glow_holds_through_the_recovery_ramp():
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planner, vcruise = make_vcruise()
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sm = make_sm(standstill=False)
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toggles = make_toggles()
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toggles.curve_speed_controller = True
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curve_target = {"v": 14.0}
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def set_curve_target(_v_ego, _v_cruise):
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vcruise.csc.target = curve_target["v"]
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vcruise.csc.update_target = set_curve_target
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update_vcruise(vcruise, sm, toggles, now=100.0, v_ego=20.0)
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assert vcruise.csc_controlling_speed
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# past the apex the target climbs back above v_ego while the car is still cornering
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curve_target["v"] = 18.0
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update_vcruise(vcruise, sm, toggles, now=100.05, v_ego=15.0)
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assert vcruise.csc_controlling_speed
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curve_target["v"] = 20.0
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update_vcruise(vcruise, sm, toggles, now=100.1, v_ego=17.0)
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assert not vcruise.csc_controlling_speed
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def test_curve_speed_controller_hysteresis_keeps_glow_off_for_marginal_targets():
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planner, vcruise = make_vcruise()
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sm = make_sm(standstill=False)
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@@ -34,6 +34,7 @@ CSC_LAT_ACCEL_MAX = 3.2
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CSC_NUDGE = 0.15
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CSC_NUDGE_WEIGHT = 20 # counts a single override pseudo-sample is worth
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CSC_TRAINING_QUIET_TIME = 5.0 # blocks passive samples after CSC limited speed, so it can't learn its own cap
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CSC_TRAINING_SETTLE_TIME = 2.0 # driver-owned seconds before a sample counts, so it isn't openpilot's leftover speed
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# Learned values match the driver's own cornering, which alone would never slow them
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# below their habit. Speed scales as the square root, so 0.85 is ~8% slower.
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CSC_COMFORT_MARGIN = CSC_DEFAULT_MARGIN_PERCENT / 100.0
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@@ -207,7 +208,9 @@ class CurveSpeedController:
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if not eligible:
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self.flush_data()
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self.training_timer = 0.0
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# decay instead of resetting: a lead flickering in and out of the tracker used to
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# cost the full re-arm, which left almost nothing to learn from on a real drive
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self.training_timer = max(self.training_timer - DT_MDL, 0.0)
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self.persistence_timer = 0.0
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return
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@@ -216,7 +219,7 @@ class CurveSpeedController:
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self.persistence_timer += DT_MDL
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in_curve = (
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self.training_timer >= PLANNER_TIME and
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self.training_timer >= CSC_TRAINING_SETTLE_TIME and
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self.starpilot_planner.driving_in_curve and
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not (sm["carState"].leftBlinker or sm["carState"].rightBlinker)
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)
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@@ -568,7 +568,10 @@ class StarPilotVCruise:
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self.csc_target = v_cruise
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else:
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self.csc_target = self.csc.target
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if self.csc_target < v_cruise - CSC_ACTIVE_ON_DELTA:
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# a target under the set speed alone means nothing -- until it falls under v_ego
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# the car is still accelerating toward it. Release still waits for the set speed,
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# so the glow spans the whole recovery instead of clearing at the apex.
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if self.csc_target < min(v_cruise - CSC_ACTIVE_ON_DELTA, v_ego):
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self.csc_controlling_speed = True
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elif self.csc_target > v_cruise - CSC_ACTIVE_OFF_DELTA:
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self.csc_controlling_speed = False
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