diff --git a/selfdrive/controls/lib/longitudinal_planner.py b/selfdrive/controls/lib/longitudinal_planner.py
index 714e182..6dd102a 100755
--- a/selfdrive/controls/lib/longitudinal_planner.py
+++ b/selfdrive/controls/lib/longitudinal_planner.py
@@ -61,7 +61,7 @@ class LongitudinalPlanner:
     self.solverExecutionTime = 0.0
 
   @staticmethod
-  def parse_model(model_msg, model_error):
+  def parse_model(model_msg, model_error, v_ego, taco_tune):
     if (len(model_msg.position.x) == 33 and
        len(model_msg.velocity.x) == 33 and
        len(model_msg.acceleration.x) == 33):
@@ -74,6 +74,13 @@ class LongitudinalPlanner:
       v = np.zeros(len(T_IDXS_MPC))
       a = np.zeros(len(T_IDXS_MPC))
       j = np.zeros(len(T_IDXS_MPC))
+
+    if taco_tune:
+      max_lat_accel = interp(v_ego, [5, 10, 20], [1.5, 2.0, 3.0])
+      curvatures = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.orientationRate.z) / np.clip(v, 0.3, 100.0)
+      max_v = np.sqrt(max_lat_accel / (np.abs(curvatures) + 1e-3)) - 2.0
+      v = np.minimum(max_v, v)
+
     return x, v, a, j
 
   def update(self, sm, frogpilot_toggles):
@@ -118,7 +125,7 @@ class LongitudinalPlanner:
     self.mpc.set_weights(sm['frogpilotPlan'].accelerationJerk, sm['frogpilotPlan'].speedJerk, prev_accel_constraint, personality=sm['controlsState'].personality)
     self.mpc.set_accel_limits(accel_limits_turns[0], accel_limits_turns[1])
     self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
-    x, v, a, j = self.parse_model(sm['modelV2'], self.v_model_error)
+    x, v, a, j = self.parse_model(sm['modelV2'], self.v_model_error, v_ego, frogpilot_toggles.taco_tune)
     self.mpc.update(sm['radarState'], sm['frogpilotPlan'].vCruise, x, v, a, j, sm['frogpilotPlan'].tFollow,
                     frogpilot_toggles, personality=sm['controlsState'].personality)