From 12597856dae9442357c45dd9857542ca6b4b8ada Mon Sep 17 00:00:00 2001
From: felsager <76905857+felsager@users.noreply.github.com>
Date: Fri, 6 Feb 2026 14:26:20 -0800
Subject: [PATCH] long mpc: state name before subscript (#37101)

---
 .../controls/lib/longitudinal_mpc_lib/long_mpc.py  | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
index e75705cb68..efdef9dd71 100755
--- a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
+++ b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
@@ -108,10 +108,10 @@ def gen_long_model():
   a_min = SX.sym('a_min')
   a_max = SX.sym('a_max')
   x_obstacle = SX.sym('x_obstacle')
-  prev_a = SX.sym('prev_a')
+  a_prev = SX.sym('a_prev')
   lead_t_follow = SX.sym('lead_t_follow')
   lead_danger_factor = SX.sym('lead_danger_factor')
-  model.p = vertcat(a_min, a_max, x_obstacle, prev_a, lead_t_follow, lead_danger_factor)
+  model.p = vertcat(a_min, a_max, x_obstacle, a_prev, lead_t_follow, lead_danger_factor)
 
   # dynamics model
   f_expl = vertcat(v_ego, a_ego, j_ego)
@@ -143,7 +143,7 @@ def gen_long_ocp():
 
   a_min, a_max = ocp.model.p[0], ocp.model.p[1]
   x_obstacle = ocp.model.p[2]
-  prev_a = ocp.model.p[3]
+  a_prev = ocp.model.p[3]
   lead_t_follow = ocp.model.p[4]
   lead_danger_factor = ocp.model.p[5]
 
@@ -160,7 +160,7 @@ def gen_long_ocp():
            x_ego,
            v_ego,
            a_ego,
-           a_ego - prev_a,
+           a_ego - a_prev,
            j_ego]
   ocp.model.cost_y_expr = vertcat(*costs)
   ocp.model.cost_y_expr_e = vertcat(*costs[:-1])
@@ -228,7 +228,7 @@ class LongitudinalMpc:
     self.v_solution = np.zeros(N+1)
     self.a_solution = np.zeros(N+1)
     self.j_solution = np.zeros(N)
-    self.prev_a = np.array(self.a_solution)
+    self.a_prev = np.array(self.a_solution)
     self.yref = np.zeros((N+1, COST_DIM))
 
     for i in range(N):
@@ -346,7 +346,7 @@ class LongitudinalMpc:
     self.params[:,0] = ACCEL_MIN
     self.params[:,1] = ACCEL_MAX
     self.params[:,2] = np.min(x_obstacles, axis=1)
-    self.params[:,3] = np.copy(self.prev_a)
+    self.params[:,3] = np.copy(self.a_prev)
     self.params[:,4] = t_follow
     self.params[:,5] = LEAD_DANGER_FACTOR
 
@@ -378,7 +378,7 @@ class LongitudinalMpc:
     self.a_solution = self.x_sol[:,2]
     self.j_solution = self.u_sol[:,0]
 
-    self.prev_a = np.interp(T_IDXS + self.dt, T_IDXS, self.a_solution)
+    self.a_prev = np.interp(T_IDXS + self.dt, T_IDXS, self.a_solution)
 
     t = time.monotonic()
     if self.solution_status != 0: