revert modeld/controlsd/plannerd/locationd to first-commit baseline

Starting point for rebuilding self-drive from a known-good baseline.
Reverts the following to their state at f46339c:
- selfdrive/modeld/modeld.py (constant 20fps, no variable-rate / standby skip)
- selfdrive/modeld/dmonitoringmodeld.py (no carState sub, no standstill skip)
- selfdrive/controls/controlsd.py (no parked-cycle skip, no FPCC hoisting, no MDPS split)
- selfdrive/controls/lib/longitudinal_planner.py
- selfdrive/locationd/calibrationd.py (valid = sm.all_checks again)
- selfdrive/locationd/paramsd.py
- selfdrive/locationd/torqued.py

All non-self-drive features (thermald fan control, speed limit controller,
cruise warning signs, UI state transitions, GPS fixes, ClearPilot menu,
dashcamd, telemetry, etc.) remain as-is on this branch — only the 4 core
self-drive processes are reverted.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

selfdrive/controls/lib/longitudinal_planner.py

@@ -143,10 +143,6 @@ class LongitudinalPlanner:
     self.params = Params()
     self.params_memory = Params("/dev/shm/params")
 
-    # CLEARPILOT: track model FPS for dynamic dt adjustment
-    self.model_fps = 20
-    self._dbg_prev_valid = True  # CLEARPILOT: diagnostic logging on valid transitions
-
     self.radarless_model = self.params.get("Model", encoding='utf-8') in RADARLESS_MODELS
 
     self.release = get_short_branch() == "clearpilot"
@@ -177,19 +173,6 @@ class LongitudinalPlanner:
     return x, v, a, j
 
   def update(self, sm):
-    # CLEARPILOT: read actual model FPS and adjust dt accordingly
-    model_fps_raw = self.params_memory.get("ModelFps")
-    if model_fps_raw is not None:
-      try:
-        fps = int(model_fps_raw)
-        if fps > 0 and fps != self.model_fps:
-          self.model_fps = fps
-          self.dt = 1.0 / fps
-          self.v_desired_filter.dt = self.dt
-          self.v_desired_filter.update_alpha(2.0)  # rc=2.0, same as __init__
-      except (ValueError, ZeroDivisionError):
-        pass
-
     self.mpc.mode = 'blended' if sm['controlsState'].experimentalMode else 'acc'
 
     v_ego = sm['carState'].vEgo
@@ -256,10 +239,7 @@ class LongitudinalPlanner:
     self.j_desired_trajectory = np.interp(ModelConstants.T_IDXS[:CONTROL_N], T_IDXS_MPC[:-1], self.mpc.j_solution)
 
     # TODO counter is only needed because radar is glitchy, remove once radar is gone
-    # CLEARPILOT: scale crash_cnt threshold by FPS — at 20fps need 3 frames (0.15s),
-    # at 4fps need 1 frame (0.25s already exceeds 0.15s window)
-    fcw_threshold = max(0, int(0.15 * self.model_fps) - 1)  # 20fps->2, 4fps->0
-    self.fcw = self.mpc.crash_cnt > fcw_threshold and not sm['carState'].standstill
+    self.fcw = self.mpc.crash_cnt > 2 and not sm['carState'].standstill
     if self.fcw:
       cloudlog.info("FCW triggered")
 
@@ -278,18 +258,7 @@ class LongitudinalPlanner:
   def publish(self, sm, pm):
     plan_send = messaging.new_message('longitudinalPlan')
 
-    valid = sm.all_checks(service_list=['carState', 'controlsState'])
-    # CLEARPILOT: log on transition into invalid — stderr goes to our plannerd.log
-    if valid != self._dbg_prev_valid and not valid:
-      import sys
-      print(
-        "CLP longitudinalPlan valid=False: "
-        f"carState(a={sm.alive['carState']},v={sm.valid['carState']},f={sm.freq_ok['carState']}) "
-        f"controlsState(a={sm.alive['controlsState']},v={sm.valid['controlsState']},f={sm.freq_ok['controlsState']})",
-        file=sys.stderr, flush=True
-      )
-    self._dbg_prev_valid = valid
-    plan_send.valid = valid
+    plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState'])
 
     longitudinalPlan = plan_send.longitudinalPlan
     longitudinalPlan.modelMonoTime = sm.logMonoTime['modelV2']