From 3d09a47a4754c6960bceb7d9f2cb0b5a5e537867 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Harald=20Sch=C3=A4fer?= <harald.the.engineer@gmail.com>
Date: Tue, 18 Aug 2026 14:15:20 -0700
Subject: [PATCH] cruise planner: fix decel jerk from cruise (#38653)

* cruise planner: fix decel jerk from cruise

* dead variable
---
 .../controls/lib/longitudinal_planner.py       | 18 ++++++++----------
 1 file changed, 8 insertions(+), 10 deletions(-)

diff --git a/openpilot/selfdrive/controls/lib/longitudinal_planner.py b/openpilot/selfdrive/controls/lib/longitudinal_planner.py
index c2b8b94abb..cc1345a6ae 100755
--- a/openpilot/selfdrive/controls/lib/longitudinal_planner.py
+++ b/openpilot/selfdrive/controls/lib/longitudinal_planner.py
@@ -47,9 +47,8 @@ def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt,
       max_accel = min(max_accel, coast_limit)
 
   target_accel = np.clip(v_cruise - v_ego, A_CRUISE_MIN, max_accel)
-  if not e2e:
-    j_cruise = np.interp(v_ego, A_CRUISE_MAX_BP, J_CRUISE_VALS)
-    target_accel = float(np.clip(target_accel, a_cruise_prev - j_cruise * dt, a_cruise_prev + j_cruise * dt))
+  j_cruise = np.interp(v_ego, A_CRUISE_MAX_BP, J_CRUISE_VALS)
+  target_accel = float(np.clip(target_accel, a_cruise_prev - j_cruise * dt, a_cruise_prev + j_cruise * dt))
 
   return target_accel
 
@@ -62,10 +61,9 @@ class LongitudinalPlanner:
     self.dt = dt
     self.allow_throttle = True
 
-    self.a_desired = init_a
     self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
-    self.a_cruise = 0.0
-    self.output_a_target = 0.0
+    self.a_cruise = init_a
+    self.output_a_target = init_a
     self.output_should_stop = False
 
     self.v_desired_trajectory = np.zeros(CONTROL_N)
@@ -100,7 +98,8 @@ class LongitudinalPlanner:
 
     if reset_state:
       self.v_desired_filter.x = v_ego
-      self.a_desired = np.clip(sm['carState'].aEgo, ACCEL_MIN, ACCEL_MAX)
+      self.output_a_target = np.clip(sm['carState'].aEgo, ACCEL_MIN, ACCEL_MAX)
+      self.a_cruise = self.output_a_target
 
     # Prevent divergence, smooth in current v_ego
     self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
@@ -109,7 +108,7 @@ class LongitudinalPlanner:
     prev_accel_constraint = not (reset_state or sm['carState'].standstill)
 
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
-    self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
+    self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
     self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
@@ -122,7 +121,7 @@ class LongitudinalPlanner:
       cloudlog.info("FCW triggered")
 
     # Save starting point for next iteration
-    a_prev = self.a_desired
+    a_prev = self.output_a_target
 
     action_t =  self.CP.longitudinalActuatorDelay + DT_MDL
     output_a_target_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
@@ -145,7 +144,6 @@ class LongitudinalPlanner:
     self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
     self.output_a_target = np.clip(output_a_target, ACCEL_MIN, ACCEL_MAX)
 
-    self.a_desired = float(self.output_a_target)
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.output_a_target + a_prev) / 2.0
 
   def publish(self, sm, pm):