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Author SHA1 Message Date
James Vecellio-Grant 02ef6e4ce0 modeld_v2: artifact parity with upstream tg (#2093)
* modeld_v2: artifact parity with upstream tg

* m

* m

* Update helpers.py

* ew

* Update convert_upstream_pkl.py

* Update test_convert_upstream_pkl.py

---------

Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
2026-11-05 16:11:27 -05:00
Nayan a1a28e467e [models] Support major.minor versioning (#2092)
support major.minor versioning, becase why not
2026-11-05 15:35:07 -05:00
James Vecellio-Grant 932ff06d93 modeld_v2: fix action curvature (#2091) 2026-11-04 14:32:06 -08:00
James Vecellio-Grant 8cf6ff9a33 controls: predictive accel boost (#2089)
* controls: predictive accel boost

* ew

* lower entry threshold for fade, pos still builds. brake_probs still triggers at same hyp

* ui: add MICI accel boost side-panel bar

* jason and kumar fought for hours to make this default so here we go

* controls: accel boost review fixes

* [MICI] ui: move accel boost ball swap out of stock

* ui: drop restating accel boost comments

* ui: drop accel boost onroad indicator

---------

Co-authored-by: rav4kumar <meetkumardesai@gmail.com>
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
2026-11-03 23:16:52 -05:00
royjr a86979d2b2 sunnylink: gate steering arc toggle on MICI (#2085)
sunnylink-hide-steering-arc-mici
2026-11-01 12:02:47 -05:00
21 changed files with 314 additions and 134 deletions
+17
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@@ -46,6 +46,23 @@ jobs:
CHECK_OOB: 0
GMMU: 0
run: tools/op.sh test -v openpilot/sunnypilot/modeld_v2/tests/test_convert_upstream_pkl.py
- name: Resolve commaai's tinygrad pin, which their precompiled chestnut model is built and converted with
id: upstream-tg
env:
GH_TOKEN: ${{ github.token }}
run: |
read -r sha url < <(gh api repos/commaai/openpilot/contents/tinygrad_repo --jq '.sha + " " + .submodule_git_url')
echo "commaai/openpilot master pins $url@$sha, ours is $(git rev-parse HEAD:tinygrad_repo)"
dir="$RUNNER_TEMP/upstream_tinygrad"
git init -q "$dir" && git -C "$dir" fetch -q --depth 1 "$url" "$sha" && git -C "$dir" checkout -q FETCH_HEAD
echo "path=$dir" >> "$GITHUB_OUTPUT"
- name: Convert a pickled USB+AMD jit under commaai's tinygrad, as the chestnut model build does
env:
DEV: MOCKUSB+AMD
CHECK_OOB: 0
GMMU: 0
PYTHONPATH: ${{ steps.upstream-tg.outputs.path }}:${{ github.workspace }}
run: tools/op.sh test -v openpilot/sunnypilot/modeld_v2/tests/test_convert_upstream_pkl.py
- name: Where tinygrad moved, for the helper or failure point named above
if: failure() && github.event_name == 'pull_request'
run: |
-38
View File
@@ -389,44 +389,6 @@ struct CarControlSP @0xa5cd762cd951a455 {
leadOne @2 :LeadData;
leadTwo @3 :LeadData;
intelligentCruiseButtonManagement @4 :IntelligentCruiseButtonManagement;
smartCruiseControl @5 :SmartCruiseControl;
speedLimit @6 :SpeedLimit;
laneChange @7 :LaneChange;
driverMonitoring @8 :DriverMonitoring;
leadFollowing @9 :Bool;
struct SmartCruiseControl {
visionState @0 :LongitudinalPlanSP.SmartCruiseControl.VisionState;
mapState @1 :LongitudinalPlanSP.SmartCruiseControl.MapState;
}
struct SpeedLimit {
assistState @0 :LongitudinalPlanSP.SpeedLimit.AssistState;
speedLimitFinalLast @1 :Float32;
}
struct DriverMonitoring {
alertLevel @0 :UInt8;
visionPolicy @1 :Bool;
}
struct LaneChange {
state @0 :State;
direction @1 :Direction;
enum State {
off @0;
preLaneChange @1;
laneChangeStarting @2;
laneChangeFinishing @3;
}
enum Direction {
none @0;
left @1;
right @2;
}
}
struct Param {
key @0 :Text;
+1
View File
@@ -149,6 +149,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"Version", {PERSISTENT, STRING}},
// --- sunnypilot params --- //
{"AccelBoostSP", {PERSISTENT | BACKUP, BOOL, "1"}},
{"ApiCache_DriveStats", {PERSISTENT, JSON}},
{"AutoLaneChangeBsmDelay", {PERSISTENT | BACKUP, BOOL, "0"}},
{"AutoLaneChangeTimer", {PERSISTENT | BACKUP, INT, "0"}},
-4
View File
@@ -63,9 +63,5 @@ def convert_carControlSP(struct: capnp.lib.capnp._DynamicStructReader) -> struct
struct_dataclass.intelligentCruiseButtonManagement = structs.IntelligentCruiseButtonManagement(
**remove_deprecated(struct_dict.get('intelligentCruiseButtonManagement', {}))
)
struct_dataclass.smartCruiseControl = structs.CarControlSP.SmartCruiseControl(**struct_dict.get('smartCruiseControl', {}))
struct_dataclass.speedLimit = structs.CarControlSP.SpeedLimit(**struct_dict.get('speedLimit', {}))
struct_dataclass.laneChange = structs.CarControlSP.LaneChange(**struct_dict.get('laneChange', {}))
struct_dataclass.driverMonitoring = structs.CarControlSP.DriverMonitoring(**struct_dict.get('driverMonitoring', {}))
return struct_dataclass
@@ -57,14 +57,6 @@ COMFORT_BRAKE = 2.5
STOP_DISTANCE = 6.0
MIN_X_LEAD_FACTOR = 0.5
# aggressive follows close to stock Hyundai SCC closest setting: 2.4 m stopped (stock 2.4), 16.3 m @ 31 mph (stock 14.8), 22 m @ 40 (20.2), 27.5 m @ 48 (25.2)
# the MPC settles ~0.8 m short of its target at standstill, so a 3.2 m target stops at ~2.4 m
# the short stop gap fades out by 10 m/s and moving gaps are ~0.1 s over stock: exact stock gaps crash in sim when the lead brakes 2 m/s^2 to a stop
AGGRESSIVE_STOP_DISTANCE_BP = [0., 3., 10.]
AGGRESSIVE_STOP_DISTANCE_V = [3.2, 3.2, STOP_DISTANCE]
AGGRESSIVE_T_FOLLOW_BP = [0., 10., 14., 16., 18., 20., 21.3, 30.]
AGGRESSIVE_T_FOLLOW_V = [0.74, 0.74, 0.74, 0.81, 0.90, 0.945, 1.0, 1.1]
def get_jerk_factor(personality=log.LongitudinalPersonality.standard):
if personality==log.LongitudinalPersonality.relaxed:
return 1.0
@@ -317,11 +309,6 @@ class LongitudinalMpc:
def update(self, radarstate, personality=log.LongitudinalPersonality.standard):
t_follow = get_T_FOLLOW(personality)
stop_distance_offset = 0.
if personality == log.LongitudinalPersonality.aggressive:
t_follow = float(np.interp(self.x0[1], AGGRESSIVE_T_FOLLOW_BP, AGGRESSIVE_T_FOLLOW_V))
# STOP_DISTANCE is compiled into the solver, so move the lead forward instead
stop_distance_offset = STOP_DISTANCE - float(np.interp(self.x0[1], AGGRESSIVE_STOP_DISTANCE_BP, AGGRESSIVE_STOP_DISTANCE_V))
lead_xv_0 = self.process_lead(radarstate.leadOne)
lead_xv_1 = self.process_lead(radarstate.leadTwo)
@@ -329,8 +316,8 @@ class LongitudinalMpc:
# To estimate a safe distance from a moving lead, we calculate how much stopping
# distance that lead needs as a minimum. We can add that to the current distance
# and then treat that as a stopped car/obstacle at this new distance.
lead_0_obstacle = lead_xv_0[:,0] + get_stopped_equivalence_factor(lead_xv_0[:,1]) + stop_distance_offset
lead_1_obstacle = lead_xv_1[:,0] + get_stopped_equivalence_factor(lead_xv_1[:,1]) + stop_distance_offset
lead_0_obstacle = lead_xv_0[:,0] + get_stopped_equivalence_factor(lead_xv_0[:,1])
lead_1_obstacle = lead_xv_1[:,0] + get_stopped_equivalence_factor(lead_xv_1[:,1])
x_obstacles = np.column_stack([lead_0_obstacle, lead_1_obstacle])
self.source = MPC_SOURCES[np.argmin(x_obstacles[0])]
@@ -2,7 +2,6 @@
import numpy as np
import openpilot.cereal.messaging as messaging
from openpilot.cereal import log
from opendbc.car.interfaces import ACCEL_MIN, ACCEL_MAX
from openpilot.common.constants import CV
from openpilot.common.filter_simple import FirstOrderFilter
@@ -21,7 +20,6 @@ from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import Lon
J_CRUISE_VALS = [1.6, 1.2, 0.8, 0.6]
J_CRUISE_BP = [0., 10.0, 25., 40.]
A_CRUISE_MIN = -0.5
AGGRESSIVE_LEAD_ONLY_DIST = 40. # m
CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
@@ -116,10 +114,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
(self.a_cruise, LongitudinalPlanSource.cruise, cruise_should_stop),
(output_a_target_e2e, LongitudinalPlanSource.e2e, output_should_stop_e2e)]
# aggressive: with a close radar lead, follow it like stock SCC instead of the model's larger stop gap
lead = sm['radarState'].leadOne
if sm['selfdriveState'].personality == log.LongitudinalPersonality.aggressive and lead.radar and lead.dRel < AGGRESSIVE_LEAD_ONLY_DIST:
candidates.pop()
output_a_target, self.mpc.source, _ = min(candidates, key=lambda c: c[0])
self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
@@ -4,9 +4,7 @@ from openpilot.common.parameterized import parameterized_class
from openpilot.cereal import log
import numpy as np
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import get_safe_obstacle_distance, get_stopped_equivalence_factor, get_T_FOLLOW, \
STOP_DISTANCE, AGGRESSIVE_STOP_DISTANCE_BP, AGGRESSIVE_STOP_DISTANCE_V, AGGRESSIVE_T_FOLLOW_BP, AGGRESSIVE_T_FOLLOW_V
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import get_safe_obstacle_distance, get_stopped_equivalence_factor, get_T_FOLLOW
from openpilot.selfdrive.test.longitudinal_maneuvers.maneuver import Maneuver
@@ -40,12 +38,7 @@ class TestFollowingDistance(OpenpilotTestCase):
def test_following_distance(self):
v_lead = float(self.speed)
simulation_steady_state = run_following_distance_simulation(v_lead, personality=self.personality)
if self.personality == log.LongitudinalPersonality.aggressive:
t_follow = float(np.interp(v_lead, AGGRESSIVE_T_FOLLOW_BP, AGGRESSIVE_T_FOLLOW_V))
stop_distance = float(np.interp(v_lead, AGGRESSIVE_STOP_DISTANCE_BP, AGGRESSIVE_STOP_DISTANCE_V))
correct_steady_state = desired_follow_distance(v_lead, v_lead, t_follow) - (STOP_DISTANCE - stop_distance)
else:
correct_steady_state = desired_follow_distance(v_lead, v_lead, get_T_FOLLOW(self.personality))
correct_steady_state = desired_follow_distance(v_lead, v_lead, get_T_FOLLOW(self.personality))
abs_err_margin = 0.5 if v_lead > 0.0 else 1.15
self.assertAlmostEqual(simulation_steady_state, correct_steady_state,
delta=0.2 * correct_steady_state + abs_err_margin)
@@ -57,6 +57,12 @@ class CruiseLayout(Widget):
description=tr("Use map data to estimate the appropriate speed to drive through turns ahead."),
param="SmartCruiseControlMap")
self.accel_boost_toggle = toggle_item_sp(
title=tr("Acceleration Boost"),
description=tr("Adds a small push on top of sunnypilot's own acceleration, stronger in Aggressive and gentler in Relaxed. " +
"Eases off in curves and when sunnypilot slows or stops. Never goes past your set speed, and lead-car following still comes first."),
param="AccelBoostSP")
self.custom_acc_toggle = toggle_item_sp(
title=tr("Custom ACC Speed Increments"),
description="",
@@ -86,6 +92,7 @@ class CruiseLayout(Widget):
self.icbm_toggle,
self.scc_v_toggle,
self.scc_m_toggle,
self.accel_boost_toggle,
self.custom_acc_toggle,
self.custom_acc_short_increment,
self.custom_acc_long_increment,
@@ -136,6 +143,8 @@ class CruiseLayout(Widget):
self.icbm_toggle.set_description(new_desc)
self.icbm_toggle.show_description(True)
self.accel_boost_toggle.action_item.set_enabled(has_long)
if has_long or has_icbm:
self.custom_acc_toggle.action_item.set_enabled(((has_long and not ui_state.CP.pcmCruise) or has_icbm) and ui_state.is_offroad())
self.scc_v_toggle.action_item.set_enabled(True)
@@ -151,6 +160,7 @@ class CruiseLayout(Widget):
else:
has_icbm = has_long = False
self.icbm_toggle.action_item.set_enabled(False)
self.accel_boost_toggle.action_item.set_enabled(False)
self.icbm_toggle.set_description(tr(ONROAD_ONLY_DESCRIPTION))
show_custom_acc_desc = False
@@ -66,47 +66,75 @@ def _patched(buf, topo) -> tuple[bytearray, dict]:
return blob, rows
def _evaluate(u, env):
def _packed_args(program) -> dict[int, int]:
from tinygrad.device import TinyELF
params = getattr(program.arg, "params", None) or ()
return {off: p.arg.slot for (off, _), p in zip(TinyELF.iter_sig(tuple((None, p.addrspace, p.dtype, ()) for p in params)), params, strict=True)}
def _outer_slot(u, packed: dict[int, int]) -> int | None:
from tinygrad.uop.ops import Ops
if u.op is Ops.PARAM:
return None if packed else u.arg.slot
if u.op.name == "REFPARAM":
return u.arg.slot
if packed and u.op is Ops.LOAD and u.src[0].op is Ops.INDEX and _root(u.src[0].src[0]).op is Ops.PARAM:
index = _evaluate(u.src[0].src[1], {}, packed)
return None if index is None else packed.get(index * u.dtype.itemsize)
return None
def _evaluate(u, env, packed: dict[int, int]):
from tinygrad.uop.ops import GroupOp, Ops, exec_alu
if u.op in (Ops.AFTER, Ops.CAST, Ops.BITCAST):
return _evaluate(u.src[0], env)
return _evaluate(u.src[0], env, packed)
if u.op is Ops.CONST:
return u.arg
if u.op in (Ops.PARAM, Ops.RANGE):
return env.get(u.arg.slot if u.op is Ops.PARAM else u)
if u.op is Ops.RANGE:
return env.get(u)
if (slot := _outer_slot(u, packed)) is not None:
return env.get(slot)
if u.op is Ops.LOAD:
table, index = _root(u.src[0].src[0]), _evaluate(u.src[0].src[1], env)
table, index = _root(u.src[0].src[0]), _evaluate(u.src[0].src[1], env, packed)
return struct.unpack_from(u.dtype.fmt, table.arg, index * u.dtype.itemsize)[0] if table.op is Ops.BINARY and index is not None else None
if u.op in GroupOp.ALU and None not in (values := [_evaluate(x, env) for x in u.src]):
if u.op in GroupOp.ALU and None not in (values := [_evaluate(x, env, packed) for x in u.src]):
return exec_alu(u.op, u.dtype, values, *([False] if "truncate_output" in inspect.signature(exec_alu).parameters else []))
return None
def _input_pokes(submit, kernargs) -> dict[int, tuple[int, int]]:
from tinygrad.uop.ops import Ops
outer = dict(enumerate(submit.src[1:]))
outer, packed = dict(enumerate(submit.src[1:])), _packed_args(submit.src[0])
kernargs_params = {i for i, a in outer.items() if a.op is Ops.GETADDR and _root(a.src[0]) is kernargs}
inputs = {i: _root(a.src[0]).arg.slot for i, a in outer.items() if a.op is Ops.GETADDR and _root(a.src[0]).op is Ops.PARAM}
pokes = {}
for call in (u for u in submit.src[0].src[0].toposort() if u.op is Ops.CALL and len(u.src) > 3):
_, address, value, *_ = call.src[1:]
used = list({x.arg.slot for x in value.toposort() if x.op is Ops.PARAM} & inputs.keys())
if len(used) != 1 or not kernargs_params & {x.arg.slot for x in address.toposort() if x.op is Ops.PARAM}:
used = list({slot for x in value.toposort() if (slot := _outer_slot(x, packed)) is not None} & inputs.keys())
if len(used) != 1 or not kernargs_params & {_outer_slot(x, packed) for x in address.toposort()}:
continue
ranges = list(dict.fromkeys(x for x in (*address.toposort(), *value.toposort()) if x.op is Ops.RANGE))
for trip in itertools.product(*[range(int(r.vmax) + 1) for r in ranges]):
env = dict.fromkeys(outer, 0) | dict(zip(ranges, trip, strict=True))
if (offset := _evaluate(address, env)) % 8 == 0:
pokes[offset] = (inputs[used[0]], _evaluate(value, env))
if (offset := _evaluate(address, env, packed)) % 8 == 0:
pokes[offset] = (inputs[used[0]], _evaluate(value, env, packed))
return pokes
def _elf(image: bytes, rodata: int) -> bytes:
names, offset, data, headers = b"\0.text\0.rodata\0.shstrtab\0", 64, b"", []
for name, kind, address, content in [(0, 0, 0, b""), (1, 1, ALIGNMENT, image[:rodata]), (7, 1, ALIGNMENT + rodata, image[rodata:]), (15, 3, 0, names)]:
headers.append(struct.pack("<IIQQQQIIQQ", name, kind, 2 if kind == 1 else 0, address, offset, len(content), 0, 0, 1, 0))
def _elf(image: bytes, rodata: int, entry: int) -> bytes:
spans = [(".text", 0, rodata), (".rodata", rodata, len(image))] if entry < rodata else \
[(".data", 0, rodata), (".rodata", rodata, entry), (".text", entry, len(image))]
sections, names = [(0, 0, 0, 0, b"")], b"\0"
for name, start, end in (span for span in spans if span[1] < span[2]):
sections.append((len(names), 1, 6 if name == ".text" else 2, ALIGNMENT + start, image[start:end]))
names += name.encode() + b"\0"
sections.append((len(names), 3, 0, 0, names + b".shstrtab\0"))
offset, data, headers = 64, b"", []
for name, kind, flags, address, content in sections:
headers.append(struct.pack("<IIQQQQIIQQ", name, kind, flags, address, offset, len(content), 0, 0, 1, 0))
data, offset = data + content, offset + len(content)
return b"\x7fELF\x02\x01\x01" + bytes(9) + struct.pack("<HHIQQQIHHHHHH", 1, 0xe0, 1, 0, 0, offset, 0, 64, 0, 0, 64, 4, 3) + data + b"".join(headers)
header = struct.pack("<HHIQQQIHHHHHH", 1, 0xe0, 1, 0, 0, offset, 0, 64, 0, 0, 64, len(sections), len(sections) - 1)
return b"\x7fELF\x02\x01\x01" + bytes(9) + header + data + b"".join(headers)
def convert(jit, kwargs: dict, frame: dict, target) -> tuple[dict, memoryview]:
@@ -155,7 +183,7 @@ def convert(jit, kwargs: dict, frame: dict, target) -> tuple[dict, memoryview]:
if image_alloc not in programs:
image = bytes(_patched(image_alloc, topo)[0])
rodata = next(r for r in range(0, len(image) - 24, 64) if r + struct.unpack_from("<q", image, r + 16)[0] == entry)
programs[image_alloc] = blob.add(_elf(image, rodata))
programs[image_alloc] = blob.add(_elf(image, rodata, entry))
start, size = _view(arguments.src[0])
args = []
for slot in range(start, start + unwrap(size), 8):
+2 -2
View File
@@ -264,8 +264,8 @@ def _program_uop(call: dict, lib: bytes):
parameter = UOp.param(call["globals"][compact_slot], _dtype(dtype), math.prod(shape))
image = (shape[0], shape[1]) if len(shape) == 3 and shape[2] == 4 else None
parameters.append(parameter.replace(arg=_fields(parameter.arg, name=name, image=image)))
info = _fields(ProgramInfo, global_size=tuple(call["global_size"]), local_size=tuple(call["local_size"]), globals=tuple(call["globals"]),
outs=tuple(call["outs"]), ins=tuple(call["ins"]), target=_fields(Target, **call["target"]))
info = _fields(ProgramInfo, global_size=tuple(call["global_size"]), local_size=tuple(call["local_size"]), params=tuple(parameters),
globals=tuple(call["globals"]), outs=tuple(call["outs"]), ins=tuple(call["ins"]), target=_fields(Target, **call["target"]))
return UOp(Ops.PROGRAM, src=(UOp(Ops.SINK, arg=KernelInfo(name=call["name"])), UOp(Ops.LINEAR, src=tuple(parameters)),
UOp(Ops.SOURCE, arg=""), UOp(Ops.BINARY, arg=lib)), arg=info)
+1 -1
View File
@@ -242,7 +242,7 @@ class ModelState(ModelStateBase):
desired_curvature = get_curvature_from_output(model_output, curvature_plan, v_ego, lat_action_t, self.mlsim)
else:
desired_accel = model_output['action'][0, 1]
desired_curvature = model_output['action'][0, 0] / (max(1.0, v_ego))**2
desired_curvature = model_output['action'][0, 0] / (max(2.5, v_ego))**2
if blendful is not None:
desired_curvature += blendful(desired_curvature)
@@ -6,6 +6,7 @@ See the LICENSE.md file in the root directory for more details.
"""
import os
import re
import struct
import sys
import tempfile
import unittest
@@ -25,8 +26,8 @@ if sys.platform == "darwin" and os.environ.get("DEV", "").startswith("MOCKUSB"):
from openpilot.common.test import OpenpilotTestCase
from openpilot.sunnypilot.modeld_v2 import convert_upstream_pkl
from openpilot.sunnypilot.modeld_v2.convert_upstream_pkl import convert
from openpilot.sunnypilot.modeld_v2.helpers import PlainJit, load_model
from openpilot.sunnypilot.modeld_v2.convert_upstream_pkl import _elf, convert
from openpilot.sunnypilot.modeld_v2.helpers import ALIGNMENT, PlainJit, load_model
from openpilot.sunnypilot.modeld_v2.plain_artifact_compiler import capture_frame
IMG, DESIRE, STATE, OUT = (6, 8, 8), (8,), (4, 16), (1, 32)
@@ -119,3 +120,18 @@ class TestConvertUpstreamPkl(OpenpilotTestCase):
bundle = load_model(out, cache=False, verify=True)
assert bundle["metadata"] == {"name": "tiny"} and bundle["input_specs"] == self.input_specs and bundle["output_specs"] == self.output_specs
self.assert_matches_eager(bundle["run"], 6)
class TestKernelElf(OpenpilotTestCase):
def test_sections_follow_the_code(self):
from tinygrad.runtime.support.elf import elf_loader
code = bytes(range(1, 129))
for rodata, entry in ((len(code), 0), (0, 256)):
image = bytearray(code + bytes(64) if entry < rodata else bytes(256) + code)
struct.pack_into("<q", image, rodata + 16, entry - rodata)
loaded, sections, _ = elf_loader(_elf(bytes(image), rodata, entry))
headers = {section.name: section.header for section in sections}
assert bytes(loaded[ALIGNMENT:]) == bytes(image), "the uploaded program differs from the pickle's"
assert headers[".rodata"].sh_addr == ALIGNMENT + rodata, "the loader reads the kernel descriptor at .rodata"
text = headers[".text"]
assert text.sh_addr <= ALIGNMENT + entry < text.sh_addr + text.sh_size, "the amd mock sizes the code from the entry to the end of .text"
@@ -31,7 +31,7 @@ class ControlsExt(ModelStateBase):
self.CP_SP = messaging.log_from_bytes(params.get("CarParamsSP", block=True), custom.CarParamsSP)
cloudlog.info("controlsd_ext got CarParamsSP")
self.sm_services_ext = ['radarState', 'selfdriveStateSP', 'longitudinalPlanSP']
self.sm_services_ext = ['radarState', 'selfdriveStateSP']
self.pm_services_ext = ['carControlSP']
def initialize_lateral_control(self, lac, CI, dt):
@@ -104,31 +104,6 @@ class ControlsExt(ModelStateBase):
CC_SP.intelligentCruiseButtonManagement.sendButton = icbm_src.sendButton
CC_SP.intelligentCruiseButtonManagement.vTarget = icbm_src.vTarget
# Smart Cruise Control state
scc_src = sm['longitudinalPlanSP'].smartCruiseControl
CC_SP.smartCruiseControl.visionState = scc_src.vision.state
CC_SP.smartCruiseControl.mapState = scc_src.map.state
# Speed Limit Assist state
sl_src = sm['longitudinalPlanSP'].speedLimit
CC_SP.speedLimit.assistState = sl_src.assist.state
CC_SP.speedLimit.speedLimitFinalLast = sl_src.resolver.speedLimitFinalLast
# Lane change state
meta = sm['modelV2'].meta
CC_SP.laneChange.state = str(meta.laneChangeState)
CC_SP.laneChange.direction = str(meta.laneChangeDirection)
# Driver monitoring alert
dm = sm['driverMonitoringState']
CC_SP.driverMonitoring.alertLevel = dm.alertLevel.raw
CC_SP.driverMonitoring.visionPolicy = dm.activePolicy == 'vision'
# Planner following a lead, the model path (e2e) wins often while following so count it when there is a lead
long_plan = sm['longitudinalPlan']
CC_SP.leadFollowing = str(long_plan.longitudinalPlanSource) in ('lead0', 'lead1', 'lead2') or \
(str(long_plan.longitudinalPlanSource) == 'e2e' and long_plan.hasLead)
return CC_SP
@staticmethod
@@ -0,0 +1,67 @@
"""
Copyright (c) 2021-, sunnypilot, and a number of other contributors.
This file is part of sunnypilot and is licensed under the MIT License.
See the LICENSE.md file in the root directory for more details.
"""
import numpy as np
from openpilot.cereal import log
from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.sunnypilot import PARAMS_UPDATE_PERIOD
ACCEL_BOOST_MIN_SPEED = 1.0
ACCEL_BOOST_MAX = (0.4, 0.25, 0.1) # aggressive, standard, relaxed, m/s^2
ACCEL_BOOST_BUILD, ACCEL_BOOST_RELEASE = 0.2, 1.0 # m/s^3
BRAKE_PROB = (0.1, 0.3) # the model's brake press in 4 s: it wants to slow
GAS_PROB = (0.6, 0.8) # predicts a human gas press at this hypothesis at about 23%
CURVE_LAT_ACCEL = (1.5, 2.5)
def get_boost_max(personality=log.LongitudinalPersonality.standard):
if personality == log.LongitudinalPersonality.relaxed:
return ACCEL_BOOST_MAX[2]
elif personality == log.LongitudinalPersonality.standard:
return ACCEL_BOOST_MAX[1]
elif personality == log.LongitudinalPersonality.aggressive:
return ACCEL_BOOST_MAX[0]
else:
raise NotImplementedError("Longitudinal personality not supported")
class AccelBoostSP:
def __init__(self):
self.params = Params()
self.frame = -1
self.enabled = False
self.boost = 0.0
self.total_boost = 0.0
def update_params(self):
self.frame += 1
if self.frame % int(PARAMS_UPDATE_PERIOD / DT_MDL) != 0:
return False
enabled = self.params.get_bool("AccelBoostSP")
if enabled == self.enabled:
return False
self.enabled = enabled
self.boost = self.total_boost = 0.0
return True
def update(self, sm, output_a_target_e2e, output_a_target_mpc, a_cruise):
model = sm['modelV2']
brake_probs = model.meta.disengagePredictions.brakePressProbs
gas_probs = model.meta.disengagePredictions.gasPressProbs
if not sm['selfdriveState'].enabled or len(brake_probs) < 2 or len(gas_probs) < 2:
self.boost = self.total_boost = 0.0
return output_a_target_e2e
want = max(float(np.interp(brake_probs[1], BRAKE_PROB, [1.0, 0.0])), float(np.interp(gas_probs[1], GAS_PROB, [0.0, 1.0])))
want = 0.0 if model.action.shouldStop else want
want *= float(np.interp(abs(model.action.desiredCurvature) * sm['carState'].vEgo ** 2, CURVE_LAT_ACCEL, [1.0, 0.0]))
target = want * get_boost_max(sm['selfdriveState'].personality)
self.boost = float(np.clip(target, self.boost - ACCEL_BOOST_RELEASE * DT_MDL, self.boost + ACCEL_BOOST_BUILD * DT_MDL))
speed_scale = np.interp(sm['carState'].vEgo, [ACCEL_BOOST_MIN_SPEED, 2 * ACCEL_BOOST_MIN_SPEED], [0.0, 1.0])
self.total_boost = self.boost * speed_scale * np.interp(output_a_target_e2e, [-0.7, -0.2, 5.0], [0.0, 1.0, 1.0], right=0.0)
return output_a_target_e2e + self.total_boost
@@ -9,6 +9,8 @@ from openpilot.cereal import messaging, custom
from opendbc.car import structs
from openpilot.common.constants import CV
from openpilot.selfdrive.car.cruise import V_CRUISE_MAX
from openpilot.selfdrive.controls.lib.accel_boost import AccelBoost
from openpilot.sunnypilot.selfdrive.controls.lib.accel_boost import AccelBoostSP
from openpilot.sunnypilot.selfdrive.controls.lib.e2e_alerts_helper import E2EAlertsHelper
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.smart_cruise_control import SmartCruiseControl
from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.speed_limit_assist import SpeedLimitAssist
@@ -29,6 +31,8 @@ class LongitudinalPlannerSP:
self.generation = int(model_bundle.generation) if (model_bundle := get_active_bundle()) else None
self.source = LongitudinalPlanSource.cruise
self.e2e_alerts_helper = E2EAlertsHelper()
self.accel_boost_sp = AccelBoostSP()
self.openpilot_longitudinal = CP.openpilotLongitudinalControl
self.output_v_target = 0.
self.output_a_target = 0.
@@ -64,6 +68,9 @@ class LongitudinalPlannerSP:
return self.output_v_target, self.output_a_target
def update(self, sm: messaging.SubMaster) -> None:
if self.accel_boost_sp.update_params():
self.accel_boost = self.accel_boost_sp if self.accel_boost_sp.enabled and self.openpilot_longitudinal else AccelBoost()
self.events_sp.clear()
self.e2e_alerts_helper.update(sm, self.events_sp)
@@ -0,0 +1,81 @@
"""
Copyright (c) 2021-, sunnypilot, and a number of other contributors.
This file is part of sunnypilot and is licensed under the MIT License.
See the LICENSE.md file in the root directory for more details.
"""
from types import SimpleNamespace
from openpilot.common.parameterized import parameterized
from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.common.test import OpenpilotTestCase
from openpilot.sunnypilot import PARAMS_UPDATE_PERIOD
from openpilot.sunnypilot.selfdrive.controls.lib.accel_boost import AccelBoostSP, ACCEL_BOOST_MAX
def make_sm(brake_prob=0.05, gas_prob=0.3, lat_accel=0.0, v_ego=30.0, personality=0, enabled=True, should_stop=False):
meta = SimpleNamespace(disengagePredictions=SimpleNamespace(brakePressProbs=[0.0, brake_prob, 0.0, 0.0, 0.0, 0.0],
gasPressProbs=[0.0, gas_prob, 0.0, 0.0, 0.0, 0.0]))
action = SimpleNamespace(shouldStop=should_stop, desiredCurvature=lat_accel / v_ego ** 2)
return {'modelV2': SimpleNamespace(meta=meta, action=action), 'carState': SimpleNamespace(vEgo=v_ego),
'selfdriveState': SimpleNamespace(enabled=enabled, personality=personality)}
def settle(sm, frames=100):
boost = AccelBoostSP()
for _ in range(frames):
boost.update(sm, 0.0, 9.0, 9.0)
return boost.total_boost
class TestAccelBoostSP(OpenpilotTestCase):
@parameterized.expand([(0,), (1,), (2,)])
def test_personality_max(self, personality):
assert abs(settle(make_sm(personality=personality)) - ACCEL_BOOST_MAX[personality]) < 1e-6
def test_brake_gate_closes(self):
assert settle(make_sm(brake_prob=0.5)) == 0.0
def test_gas_reopens(self):
assert abs(settle(make_sm(brake_prob=0.5, gas_prob=0.9)) - ACCEL_BOOST_MAX[0]) < 1e-6
def test_should_stop(self):
assert settle(make_sm(gas_prob=0.9, should_stop=True)) == 0.0
@parameterized.expand([(1.5, 1.0), (2.0, 0.5), (2.5, 0.0), (-2.0, 0.5)])
def test_curve_fade(self, lat_accel, scale):
assert abs(settle(make_sm(lat_accel=lat_accel)) - scale * ACCEL_BOOST_MAX[0]) < 1e-6
def test_low_speed(self):
assert settle(make_sm(v_ego=0.5)) == 0.0
def test_disabled_resets(self):
boost = AccelBoostSP()
for _ in range(100):
boost.update(make_sm(), 0.0, 9.0, 9.0)
assert boost.update(make_sm(enabled=False), 0.0, 9.0, 9.0) == 0.0
assert boost.boost == 0.0 and boost.total_boost == 0.0
def test_build_and_release_rates(self):
boost = AccelBoostSP()
boost.update(make_sm(), 0.0, 9.0, 9.0)
assert abs(boost.total_boost - 0.01) < 1e-6
for _ in range(100):
boost.update(make_sm(), 0.0, 9.0, 9.0)
boost.update(make_sm(brake_prob=0.5), 0.0, 9.0, 9.0)
assert abs(boost.total_boost - (ACCEL_BOOST_MAX[0] - 0.05)) < 1e-6
def test_param_switch(self):
params = Params()
boost = AccelBoostSP()
params.put_bool("AccelBoostSP", True, block=True)
assert boost.update_params() and boost.enabled
for _ in range(100):
boost.update(make_sm(), 0.0, 9.0, 9.0)
params.put_bool("AccelBoostSP", False, block=True)
for _ in range(int(PARAMS_UPDATE_PERIOD / DT_MDL) - 1):
assert not boost.update_params()
assert boost.update_params() and not boost.enabled
assert boost.boost == 0.0 and boost.total_boost == 0.0
@@ -620,6 +620,19 @@
}
]
},
{
"key": "AccelBoostSP",
"widget": "toggle",
"title": "Acceleration Boost",
"description": "Adds a small push on top of sunnypilot's own acceleration, stronger in Aggressive and gentler in Relaxed. Eases off in curves and when sunnypilot slows or stops. Never goes past your set speed, and lead-car following still comes first.",
"enablement": [
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
}
]
},
{
"key": "IntelligentCruiseButtonManagement",
"widget": "toggle",
@@ -1349,7 +1362,17 @@
"key": "TorqueBar",
"widget": "toggle",
"title": "Steering Arc",
"description": "Display steering arc on the driving screen when lateral control is enabled."
"description": "Display steering arc on the driving screen when lateral control is enabled.",
"visibility": [
{
"type": "not",
"condition": {
"type": "capability",
"field": "device_type",
"equals": "mici"
}
}
]
},
{
"key": "ShowTurnSignals",
@@ -30,6 +30,12 @@ sections:
label: Relaxed
enablement:
- $ref: '#/macros/longitudinal'
- key: AccelBoostSP
widget: toggle
title: Acceleration Boost
description: "Adds a small push on top of sunnypilot's own acceleration, stronger in Aggressive and gentler in Relaxed. Eases off in curves and when sunnypilot slows or stops. Never goes past your set speed, and lead-car following still comes first."
enablement:
- $ref: '#/macros/longitudinal'
- key: IntelligentCruiseButtonManagement
widget: toggle
title: Intelligent Cruise Button Management (ICBM) (Alpha)
@@ -20,6 +20,8 @@ sections:
widget: toggle
title: Steering Arc
description: Display steering arc on the driving screen when lateral control is enabled.
visibility:
- $ref: '#/macros/hide_on_mici'
- key: ShowTurnSignals
widget: toggle
title: Display Turn Signals
+27 -12
View File
@@ -13,26 +13,41 @@ from pathlib import Path
from datetime import datetime, UTC
_VERSION_REGEX = re.compile(r'^(?:\d+[a-zA-Z]+|\d+[vVbB]\d+|[vVbB]\d+|\d{4})$')
_DECIMAL_VERSION_REGEX = re.compile(r'^([vVbB]?)(\d+(?:\.\d+)+)$')
def _version(word: str) -> str | None:
match = _DECIMAL_VERSION_REGEX.match(word.strip('()[]{}.,;:'))
if match:
return match.group(1).upper() + match.group(2)
stripped = re.sub(r'[^a-zA-Z0-9]', '', word)
return stripped.upper() if _VERSION_REGEX.match(stripped) else None
def _truncate(short_name: str) -> str:
return short_name[:8].rstrip('.')
def create_short_name(full_name: str) -> str:
# Remove parentheses and extract alphanumeric words
# Remove parentheses and extract alphanumeric words, keeping decimals for versioning
clean_name = re.sub(r'\([^)]*\)', '', full_name)
words = [re.sub(r'[^a-zA-Z0-9]', '', word) for word in clean_name.split() if re.sub(r'[^a-zA-Z0-9]', '', word)]
words = [re.sub(r'[^a-zA-Z0-9.]', '', word) for word in clean_name.split()]
words = [word for word in words if word]
if len(words) == 1:
return words[0][:8].upper()
return _truncate((_version(words[0]) or words[0]).upper())
# Handle special case: Name + Version (e.g., "Word A1" -> "WordA1")
if len(words) == 2 and re.match(r'^[A-Za-z]\d+$', words[1]):
return (words[0] + words[1])[:8].upper()
# Handle special case: Name + Version (e.g., "Word A1" -> "WordA1", "Model v1.1" -> "ModelV1.1")
if len(words) == 2 and re.match(r'^[A-Za-z]?\d+$', words[1]):
return _truncate((words[0] + (_version(words[1]) or words[1])).upper())
result = ""
for word in words:
# Version or number patterns
if (re.match(r'^\d+[a-zA-Z]+$', word) or
re.match(r'^\d+[vVbB]\d+$', word) or
re.match(r'^[vVbB]\d+$', word) or
re.match(r'^\d{4}$', word)):
result += word.upper()
version = _version(word)
if version:
result += version
# All uppercase abbreviations (2-3 letters)
elif re.match(r'^[A-Z]{2,3}$', word):
result += word
@@ -45,7 +60,7 @@ def create_short_name(full_name: str) -> str:
result += word
else:
result += word[0].upper()
return result[:8]
return _truncate(result)
def create_pkl_name(full_name: str) -> str: