diff --git a/Scripts/modelsystem.py b/Scripts/modelsystem.py
index 4b8599b6..93384501 100644
--- a/Scripts/modelsystem.py
+++ b/Scripts/modelsystem.py
@@ -200,6 +200,7 @@ def assign_base_demand(self, use_fixed_transit_cost=False, is_end_assignment=Fal
             self._calculate_noise_areas()
             self.resultdata.flush()
         self.dtm.init_demand()
+        self.imptrans.average_car_impedance(impedance)
         return impedance
 
     def run_iteration(self, previous_iter_impedance, iteration=None):
@@ -311,6 +312,7 @@ def run_iteration(self, previous_iter_impedance, iteration=None):
         if iteration=="last":
             self.ass_model.aggregate_results(self.resultdata)
             self._calculate_noise_areas()
+        self.imptrans.average_car_impedance(impedance)
 
         # Reset time-period specific demand matrices (DTM), and empty result buffer
         self.dtm.init_demand()
diff --git a/Scripts/transform/impedance_transformer.py b/Scripts/transform/impedance_transformer.py
index 1180cf62..599905d0 100644
--- a/Scripts/transform/impedance_transformer.py
+++ b/Scripts/transform/impedance_transformer.py
@@ -6,7 +6,47 @@
 
 class ImpedanceTransformer:
     def __init__(self):
-        pass
+        self.iteration_counter = 0
+        self.averaged_impedance = dict.fromkeys(
+            ["aht", "pt", "iht"])
+        for time_period in self.averaged_impedance:
+            self.averaged_impedance[time_period] = dict.fromkeys(
+                ["time", "cost", "dist"])
+            for mtx_type in self.averaged_impedance[time_period]:
+                self.averaged_impedance[time_period][mtx_type] = dict.fromkeys(
+                    ["car_work", "car_leisure"])
+
+    def average_car_impedance(self, impedance):
+        """Perform averaging of car impedance matrices.
+        Parameters
+        ----------
+        impedance: dict
+            Time period (aht/pt/iht) : dict
+                Type (time/cost/dist) : dict
+                    Assignment class (car_work/transit/...) : numpy 2d matrix
+        Return 
+        ------
+        dict
+            Time period (aht/pt/iht) : dict
+                Type (time/cost/dist) : dict
+                    Assignment class (car_work/transit/...) : numpy 2d matrix
+        """
+        self.iteration_counter += 1
+        n = self.iteration_counter
+        for time_period in impedance:
+            for mtx_type in impedance[time_period]:
+                average_imp = self.averaged_impedance[time_period][mtx_type]
+                for ass_class in average_imp:
+                    imp = impedance[time_period][mtx_type][ass_class]
+                    if n == 1:
+                        average_imp[ass_class] = imp
+                    else:
+                        old_average = average_imp[ass_class]
+                        # Method of successive averages
+                        new_average = ((n-1)*old_average + imp) / n
+                        average_imp[ass_class] = new_average
+                        impedance[time_period][mtx_type][ass_class] = new_average
+        return impedance
 
     def transform(self, purpose, impedance):
         """Perform transformation from time period dependent matrices