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IQ.Pilot/iqpilot/selfdrive/controls/lib/helpers/lateral_edge_guard.py
2026-08-23 11:32:03 -05:00

244 lines
10 KiB
Python

"""
Lateral Edge Guard uses the model's lateral road-edge geometry to withhold lane
changes that lack room for a target lane. The model standard deviation remains
in metres: measurements above the validity limit are rejected, while valid
measurements use a one-sigma lower confidence bound for conservative clearance.
Unavailable geometry briefly holds the last output, then fails open because a
model dropout is not geometric evidence of a nearby edge. A visible outer lane
line on the target side is direct evidence that a lane exists and overrides the
edge-distance inference.
"""
from __future__ import annotations
import math
from dataclasses import dataclass, replace
from enum import IntEnum
from typing import Any
from iqpilot.cereal import custom, log
from iqpilot.common.constants import CV
from iqpilot.common.swaglog import cloudlog
MIN_ACTIVE_SPEED_MPS = 20.0 * CV.MPH_TO_MS # Matches the lane-change speed gate and excludes parking manoeuvres.
MAX_VALID_ROAD_EDGE_STD_M = 1.0 # A 2-sigma bound beyond 2 m cannot distinguish an adjacent 3.5 m lane reliably.
# roadEdgeStd describes a single edge point, but it is applied to a 5-40 m minimum that already absorbs the
# spatial worst case; 1 sigma covers ~1.1x the measured p99 frame-to-frame spread of that minimum, 2 sigma 2.2x.
EDGE_CONFIDENCE_SIGMA = 1.0
ROAD_EDGE_LOOKAHEAD_MIN_M = 5.0 # Ignore near-field edge points dominated by vehicle-body perspective.
ROAD_EDGE_LOOKAHEAD_MAX_M = 40.0 # Covers about 2 s at the 20 m/s model-training reference speed.
LANE_CENTER_OFFSET_M = 3.5 # Typical freeway lane width and the target-centre lateral displacement.
# CarParams exposes neither width nor track; 0.95 m is half of an assumed conservative 1.90 m body width.
VEHICLE_LATERAL_HALF_WIDTH_M = 1.90 / 2.0
EDGE_CLEARANCE_MARGIN_M = 0.25 # Additional lateral separation between the vehicle body and detected road edge.
ADJACENT_LANE_LINE_PROB = 0.5
EGO_LANE_LINE_PROB_MIN = 0.5
MIN_MEASURED_LANE_WIDTH_M = 2.5
MAX_MEASURED_LANE_WIDTH_M = 4.5
# modelV2 lane lines are ordered outer-left, ego-left, ego-right, outer-right.
OUTER_LANE_LINE_INDEX = (0, 3)
EGO_LANE_LINE_INDEX = (1, 2)
REQUIRED_ROAD_EDGE_DISTANCE_M = LANE_CENTER_OFFSET_M + VEHICLE_LATERAL_HALF_WIDTH_M + EDGE_CLEARANCE_MARGIN_M
BLOCK_DEBOUNCE_S = 0.30 # Six model frames reject a transient close-edge prediction before blocking.
CLEAR_DEBOUNCE_S = 0.50 # Ten model frames make release slower than assertion for conservative hysteresis.
UNAVAILABLE_HOLD_S = 0.50 # Ten model frames bridge a short model-data dropout before failing open.
TIMER_EPSILON_S = 1e-9 # Floating-point comparison tolerance, far below one model tick.
LaneChangeDirection = log.LaneChangeDirection
LateralEdgeBlock = custom.IQLateralEdgeBlock
class RoadEdgeDataState(IntEnum):
VALID = 0
UNAVAILABLE = 1
INVALID = 2
@dataclass(frozen=True, slots=True)
class RoadEdgeMeasurement:
state: RoadEdgeDataState
lateral_distance_m: float | None = None
conservative_distance_m: float | None = None
should_block: bool | None = None
@dataclass(frozen=True, slots=True)
class _SideState:
blocked: bool = False
block_timer_s: float = 0.0
clear_timer_s: float = 0.0
unavailable_timer_s: float = 0.0
fallback_reported: bool = False
def evaluate_road_edge(edge: Any, std_m: Any, direction: int,
lane_width_m: float = LANE_CENTER_OFFSET_M) -> RoadEdgeMeasurement:
if edge is None or std_m is None:
return RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
try:
xs = edge.x
ys = edge.y
count = len(xs)
y_count = len(ys)
except (AttributeError, TypeError):
return RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
if count == 0 or y_count != count:
return RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
try:
std = float(std_m)
except (TypeError, ValueError):
return RoadEdgeMeasurement(RoadEdgeDataState.INVALID)
if not math.isfinite(std) or std < 0.0 or std > MAX_VALID_ROAD_EDGE_STD_M:
return RoadEdgeMeasurement(RoadEdgeDataState.INVALID)
lateral_distance_m: float | None = None
for idx in range(count):
try:
x_m = float(xs[idx])
y_m = float(ys[idx])
except (IndexError, TypeError, ValueError):
return RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
if not math.isfinite(x_m) or not math.isfinite(y_m):
return RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
if not ROAD_EDGE_LOOKAHEAD_MIN_M <= x_m <= ROAD_EDGE_LOOKAHEAD_MAX_M:
continue
if ((direction == LaneChangeDirection.left and y_m >= 0.0) or
(direction == LaneChangeDirection.right and y_m <= 0.0)):
return RoadEdgeMeasurement(RoadEdgeDataState.INVALID)
distance_m = abs(y_m)
lateral_distance_m = distance_m if lateral_distance_m is None else min(lateral_distance_m, distance_m)
if lateral_distance_m is None:
return RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
conservative_distance_m = lateral_distance_m - EDGE_CONFIDENCE_SIGMA * std
required_distance_m = lane_width_m + VEHICLE_LATERAL_HALF_WIDTH_M + EDGE_CLEARANCE_MARGIN_M
return RoadEdgeMeasurement(
RoadEdgeDataState.VALID,
lateral_distance_m,
conservative_distance_m,
conservative_distance_m < required_distance_m,
)
def step_side_guard(state: _SideState, measurement: RoadEdgeMeasurement, speed_active: bool,
dt_s: float) -> tuple[_SideState, bool]:
if not speed_active:
return _SideState(), False
if measurement.state == RoadEdgeDataState.UNAVAILABLE:
unavailable_timer_s = state.unavailable_timer_s + dt_s
if unavailable_timer_s < UNAVAILABLE_HOLD_S - TIMER_EPSILON_S:
return _SideState(state.blocked, unavailable_timer_s=unavailable_timer_s,
fallback_reported=state.fallback_reported), False
fallback_started = not state.fallback_reported
return _SideState(unavailable_timer_s=unavailable_timer_s, fallback_reported=True), fallback_started
should_block = bool(measurement.should_block) if measurement.state == RoadEdgeDataState.VALID else False
if should_block == state.blocked:
return _SideState(blocked=state.blocked), False
if should_block:
block_timer_s = state.block_timer_s + dt_s
if block_timer_s >= BLOCK_DEBOUNCE_S - TIMER_EPSILON_S:
return _SideState(blocked=True), False
return _SideState(block_timer_s=block_timer_s), False
clear_timer_s = state.clear_timer_s + dt_s
if clear_timer_s >= CLEAR_DEBOUNCE_S - TIMER_EPSILON_S:
return _SideState(), False
return _SideState(blocked=True, clear_timer_s=clear_timer_s), False
class LateralEdgeGuard:
def __init__(self) -> None:
self._left = _SideState()
self._right = _SideState()
self.left_measurement = RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
self.right_measurement = RoadEdgeMeasurement(RoadEdgeDataState.UNAVAILABLE)
@staticmethod
def _model_side(modeldata: Any, side_index: int) -> tuple[Any | None, Any | None]:
if modeldata is None:
return None, None
try:
edges = modeldata.roadEdges
stds = modeldata.roadEdgeStds
if len(edges) <= side_index or len(stds) <= side_index:
return None, None
return edges[side_index], stds[side_index]
except (AttributeError, TypeError):
return None, None
@staticmethod
def _lane_line_prob(modeldata: Any, index: int) -> float | None:
if modeldata is None:
return None
try:
probs = modeldata.laneLineProbs
if len(probs) <= index:
return None
value = float(probs[index])
except (AttributeError, TypeError, IndexError, ValueError):
return None
return value if math.isfinite(value) else None
@classmethod
def _adjacent_lane_visible(cls, modeldata: Any, side_index: int) -> bool:
prob = cls._lane_line_prob(modeldata, OUTER_LANE_LINE_INDEX[side_index])
return prob is not None and prob > ADJACENT_LANE_LINE_PROB
@classmethod
def _measured_lane_width(cls, modeldata: Any) -> float:
left_prob = cls._lane_line_prob(modeldata, EGO_LANE_LINE_INDEX[0])
right_prob = cls._lane_line_prob(modeldata, EGO_LANE_LINE_INDEX[1])
if left_prob is None or right_prob is None:
return LANE_CENTER_OFFSET_M
if left_prob <= EGO_LANE_LINE_PROB_MIN or right_prob <= EGO_LANE_LINE_PROB_MIN:
return LANE_CENTER_OFFSET_M
try:
lines = modeldata.laneLines
left_y = float(lines[EGO_LANE_LINE_INDEX[0]].y[0])
right_y = float(lines[EGO_LANE_LINE_INDEX[1]].y[0])
except (AttributeError, TypeError, IndexError, ValueError):
return LANE_CENTER_OFFSET_M
width = abs(right_y - left_y)
if not math.isfinite(width):
return LANE_CENTER_OFFSET_M
return min(max(width, MIN_MEASURED_LANE_WIDTH_M), MAX_MEASURED_LANE_WIDTH_M)
@staticmethod
def _apply_lane_evidence(measurement: RoadEdgeMeasurement, lane_visible: bool) -> RoadEdgeMeasurement:
if lane_visible and measurement.state == RoadEdgeDataState.VALID and measurement.should_block:
return replace(measurement, should_block=False)
return measurement
def update(self, modeldata: Any, v_ego_mps: float, dt_s: float) -> None:
dt = max(float(dt_s), 0.0)
left_edge, left_std = self._model_side(modeldata, 0)
right_edge, right_std = self._model_side(modeldata, 1)
lane_width_m = self._measured_lane_width(modeldata)
self.left_measurement = self._apply_lane_evidence(
evaluate_road_edge(left_edge, left_std, LaneChangeDirection.left, lane_width_m),
self._adjacent_lane_visible(modeldata, 0))
self.right_measurement = self._apply_lane_evidence(
evaluate_road_edge(right_edge, right_std, LaneChangeDirection.right, lane_width_m),
self._adjacent_lane_visible(modeldata, 1))
speed_active = math.isfinite(v_ego_mps) and v_ego_mps >= MIN_ACTIVE_SPEED_MPS
self._left, left_fallback = step_side_guard(self._left, self.left_measurement, speed_active, dt)
self._right, right_fallback = step_side_guard(self._right, self.right_measurement, speed_active, dt)
if left_fallback:
cloudlog.warning(f"lateral edge guard: left road edge unavailable for {UNAVAILABLE_HOLD_S:.2f} s; falling back to not blocking")
if right_fallback:
cloudlog.warning(f"lateral edge guard: right road edge unavailable for {UNAVAILABLE_HOLD_S:.2f} s; falling back to not blocking")
def block_for_direction(self, direction: int) -> custom.IQLateralEdgeBlock:
if direction == LaneChangeDirection.left and self._left.blocked:
return LateralEdgeBlock.left
if direction == LaneChangeDirection.right and self._right.blocked:
return LateralEdgeBlock.right
return LateralEdgeBlock.none