diff --git a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
index bb6389179..12fe4b6d0 100644
--- a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
+++ b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
@@ -16,6 +16,8 @@ if __name__ == '__main__':  # generating code
 else:
   from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.c_generated_code.acados_ocp_solver_pyx import AcadosOcpSolverCython
 
+  from openpilot.selfdrive.frogpilot.controls.lib.frogpilot_variables import CITY_SPEED_LIMIT
+
 from casadi import SX, vertcat
 
 MODEL_NAME = 'long'
@@ -325,10 +327,10 @@ class LongitudinalMpc:
     lead_xv = np.column_stack((x_lead_traj, v_lead_traj))
     return lead_xv
 
-  def process_lead(self, lead):
+  def process_lead(self, lead, increased_stopping_distance=0):
     v_ego = self.x0[1]
     if lead is not None and lead.status:
-      x_lead = lead.dRel
+      x_lead = lead.dRel - increased_stopping_distance
       v_lead = lead.vLead
       a_lead = lead.aLeadK
       a_lead_tau = lead.aLeadTau
@@ -357,8 +359,9 @@ class LongitudinalMpc:
   def update(self, radarstate, v_cruise, x, v, a, j, t_follow, frogpilot_toggles, personality=log.LongitudinalPersonality.standard):
     v_ego = self.x0[1]
     self.status = radarstate.leadOne.status or radarstate.leadTwo.status
+    increased_distance = max(frogpilot_toggles.increased_stopping_distance + min(CITY_SPEED_LIMIT - v_ego, 0), 0)
 
-    lead_xv_0 = self.process_lead(radarstate.leadOne)
+    lead_xv_0 = self.process_lead(radarstate.leadOne, increased_distance)
     lead_xv_1 = self.process_lead(radarstate.leadTwo)
 
     # To estimate a safe distance from a moving lead, we calculate how much stopping
diff --git a/selfdrive/frogpilot/controls/frogpilot_planner.py b/selfdrive/frogpilot/controls/frogpilot_planner.py
index dd671a970..df200f2e3 100644
--- a/selfdrive/frogpilot/controls/frogpilot_planner.py
+++ b/selfdrive/frogpilot/controls/frogpilot_planner.py
@@ -54,8 +54,9 @@ class FrogPilotPlanner:
     v_ego = max(carState.vEgo, 0)
     v_lead = self.lead_one.vLead
 
-    lead_distance = self.lead_one.dRel
-    stopping_distance = STOP_DISTANCE
+    distance_offset = max(frogpilot_toggles.increased_stopping_distance + min(CITY_SPEED_LIMIT - v_ego, 0), 0)
+    lead_distance = self.lead_one.dRel - distance_offset
+    stopping_distance = STOP_DISTANCE + distance_offset
 
     if frogpilot_toggles.conditional_experimental_mode and controlsState.enabled:
       self.cem.update(carState, frogpilotNavigation, self.lead_one, modelData, self.model_length, self.road_curvature, self.slower_lead, self.tracking_lead, v_ego, v_lead, frogpilot_toggles)