add action logic

selfdrive/controls/lib/drive_helpers.py

@@ -1,7 +1,7 @@
 import numpy as np
 from cereal import log
 from opendbc.car.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
-from openpilot.common.realtime import DT_CTRL
+from openpilot.common.realtime import DT_CTRL, DT_MDL
 
 MIN_SPEED = 1.0
 CONTROL_N = 17
@@ -43,3 +43,19 @@ def get_speed_error(modelV2: log.ModelDataV2, v_ego: float) -> float:
     vel_err = np.clip(modelV2.temporalPose.trans[0] - v_ego, -MAX_VEL_ERR, MAX_VEL_ERR)
     return float(vel_err)
   return 0.0
+
+
+def get_accel_from_plan(speeds, accels, t_idxs, action_t=DT_MDL, vEgoStopping=0.05):
+  if len(speeds) == len(t_idxs):
+    v_now = speeds[0]
+    a_now = accels[0]
+    v_target = np.interp(action_t, t_idxs, speeds)
+    a_target = 2 * (v_target - v_now) / (action_t) - a_now
+    v_target_1sec = np.interp(action_t + 1.0, t_idxs, speeds)
+  else:
+    v_target = 0.0
+    v_target_1sec = 0.0
+    a_target = 0.0
+  should_stop = (v_target < vEgoStopping and
+                 v_target_1sec < vEgoStopping)
+  return a_target, should_stop

selfdrive/controls/lib/longitudinal_planner.py

@@ -11,7 +11,7 @@ from openpilot.selfdrive.modeld.constants import ModelConstants
 from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
 from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc
 from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC
-from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, get_speed_error
+from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, get_speed_error, get_accel_from_plan
 from openpilot.selfdrive.car.cruise import V_CRUISE_MAX, V_CRUISE_UNSET
 from openpilot.common.swaglog import cloudlog
 
@@ -48,23 +48,6 @@ def limit_accel_in_turns(v_ego, angle_steers, a_target, CP):
   return [a_target[0], min(a_target[1], a_x_allowed)]
 
 
-def get_accel_from_plan(speeds, accels, action_t=DT_MDL, vEgoStopping=0.05):
-  if len(speeds) == CONTROL_N:
-    v_now = speeds[0]
-    a_now = accels[0]
-
-    v_target = np.interp(action_t, CONTROL_N_T_IDX, speeds)
-    a_target = 2 * (v_target - v_now) / (action_t) - a_now
-    v_target_1sec = np.interp(action_t + 1.0, CONTROL_N_T_IDX, speeds)
-  else:
-    v_target = 0.0
-    v_target_1sec = 0.0
-    a_target = 0.0
-  should_stop = (v_target < vEgoStopping and
-                 v_target_1sec < vEgoStopping)
-  return a_target, should_stop
-
-
 class LongitudinalPlanner:
   def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL):
     self.CP = CP
@@ -176,7 +159,7 @@ class LongitudinalPlanner:
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.a_desired + a_prev) / 2.0
 
     action_t =  self.CP.longitudinalActuatorDelay + DT_MDL
-    output_a_target, self.output_should_stop = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory,
+    output_a_target, self.output_should_stop = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
                                                                         action_t=action_t, vEgoStopping=self.CP.vEgoStopping)
 
     for idx in range(2):

selfdrive/modeld/constants.py

@@ -1,4 +1,5 @@
 import numpy as np
+from dataclasses import dataclass
 
 def index_function(idx, max_val=192, max_idx=32):
   return (max_val) * ((idx/max_idx)**2)

selfdrive/modeld/fill_model_msg.py

@@ -56,7 +56,7 @@ def fill_lane_line_meta(builder, lane_lines, lane_line_probs):
   builder.rightProb = lane_line_probs[2]
 
 def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._DynamicStructBuilder,
-                   net_output_data: dict[str, np.ndarray], v_ego: float, delay: float,
+                   net_output_data: dict[str, np.ndarray], action: log.ModelDataV2.Action,
                    publish_state: PublishState, vipc_frame_id: int, vipc_frame_id_extra: int,
                    frame_id: int, frame_drop: float, timestamp_eof: int, model_execution_time: float,
                    valid: bool) -> None:
@@ -71,7 +71,8 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
   driving_model_data.frameIdExtra = vipc_frame_id_extra
   driving_model_data.frameDropPerc = frame_drop_perc
   driving_model_data.modelExecutionTime = model_execution_time
-  driving_model_data.action.desiredCurvature = float(net_output_data['desired_curvature'][0,0])
+
+  driving_model_data.action = action
 
   modelV2 = extended_msg.modelV2
   modelV2.frameId = vipc_frame_id
@@ -98,8 +99,8 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
   # poly path
   fill_xyz_poly(driving_model_data.path, ModelConstants.POLY_PATH_DEGREE, *net_output_data['plan'][0,:,Plan.POSITION].T)
 
-  # lateral planning
-  modelV2.action.desiredCurvature = float(net_output_data['desired_curvature'][0,0])
+  # action
+  modelV2.action = action
 
   # times at X_IDXS of edges and lines aren't used
   LINE_T_IDXS: list[float] = []

selfdrive/modeld/modeld.py

@@ -26,12 +26,15 @@ from openpilot.common.transformations.camera import DEVICE_CAMERAS
 from openpilot.common.transformations.model import get_warp_matrix
 from openpilot.system import sentry
 from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
+from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan
 from openpilot.selfdrive.modeld.parse_model_outputs import Parser
 from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState
-from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
 from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext
 
 
+
+
 PROCESS_NAME = "selfdrive.modeld.modeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 
@@ -40,6 +43,20 @@ POLICY_PKL_PATH = Path(__file__).parent / 'models/driving_policy_tinygrad.pkl'
 VISION_METADATA_PATH = Path(__file__).parent / 'models/driving_vision_metadata.pkl'
 POLICY_METADATA_PATH = Path(__file__).parent / 'models/driving_policy_metadata.pkl'
 
+
+
+def get_action_from_model(model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
+                          lat_action_t: float, long_action_t: float,) -> log.ModelDataV2.Action:
+    plan = model_output['plan'][0]
+    desired_accel, should_stop = get_accel_from_plan(plan[:,Plan.VELOCITY][:,0],
+                                                     plan[:,Plan.ACCELERATION][:,0],
+                                                     ModelConstants.T_IDXS,
+                                                     action_t=long_action_t)
+    desired_curvature = model_output['desired_curvature'][0, 0]
+    return log.ModelDataV2.Action(desiredCurvature=float(desired_curvature),
+                                  desiredAcceleration=float(desired_accel),
+                                  shouldStop=bool(should_stop))
+
 class FrameMeta:
   frame_id: int = 0
   timestamp_sof: int = 0
@@ -221,7 +238,9 @@ def main(demo=False):
   cloudlog.info("modeld got CarParams: %s", CP.brand)
 
   # TODO this needs more thought, use .2s extra for now to estimate other delays
-  steer_delay = CP.steerActuatorDelay + .2
+  lat_delay = CP.steerActuatorDelay + .2
+  long_delay = CP.longitudinalActuatorDelay
+  prev_action = log.ModelDataV2.Action()
 
   DH = DesireHelper()
 
@@ -263,7 +282,7 @@ def main(demo=False):
     is_rhd = sm["driverMonitoringState"].isRHD
     frame_id = sm["roadCameraState"].frameId
     v_ego = max(sm["carState"].vEgo, 0.)
-    lateral_control_params = np.array([v_ego, steer_delay], dtype=np.float32)
+    lateral_control_params = np.array([v_ego, lat_delay], dtype=np.float32)
     if sm.updated["liveCalibration"] and sm.seen['roadCameraState'] and sm.seen['deviceState']:
       device_from_calib_euler = np.array(sm["liveCalibration"].rpyCalib, dtype=np.float32)
       dc = DEVICE_CAMERAS[(str(sm['deviceState'].deviceType), str(sm['roadCameraState'].sensor))]
@@ -306,7 +325,9 @@ def main(demo=False):
       modelv2_send = messaging.new_message('modelV2')
       drivingdata_send = messaging.new_message('drivingModelData')
       posenet_send = messaging.new_message('cameraOdometry')
-      fill_model_msg(drivingdata_send, modelv2_send, model_output, v_ego, steer_delay,
+
+      action = get_action_from_model(model_output, prev_action, lat_delay + 0.05, long_delay + 0.05)
+      fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
                      publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
                      frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, live_calib_seen)