diff --git a/src/environments/environments/CarTrackParentEnvironment.py b/src/environments/environments/CarTrackParentEnvironment.py
index ff87e7d2..7ae48a19 100644
--- a/src/environments/environments/CarTrackParentEnvironment.py
+++ b/src/environments/environments/CarTrackParentEnvironment.py
@@ -40,7 +40,6 @@ def __init__(self, car_name, reward_range=1, max_steps=50, collision_range=0.2,
 
         # Environment Details ----------------------------------------
         self.MAX_STEPS_PER_GOAL = max_steps
-        self.MIN_ACTIONS = np.asarray([0, -3.14])
         self.OBSERVATION_SIZE = 8 + 10  # Car position + Lidar rays
 
         self.check_goal = False
@@ -151,8 +150,11 @@ def compute_reward(self, state, next_state):
 
         goal_position = self.goal_position
 
+        prev_distance = math.dist(goal_position, state[:2])
         current_distance = math.dist(goal_position, next_state[:2])
-
+        
+        reward += prev_distance - current_distance
+        
         if current_distance < self.REWARD_RANGE:
             reward += 50
             self.goal_number += 1
diff --git a/src/environments/environments/ParentCarEnvironment.py b/src/environments/environments/ParentCarEnvironment.py
index b997678e..4135e23e 100644
--- a/src/environments/environments/ParentCarEnvironment.py
+++ b/src/environments/environments/ParentCarEnvironment.py
@@ -49,7 +49,7 @@ def __init__(self, env_name, car_name, reward_range, max_steps, collision_range,
         self.lidar_sub = Subscriber(
             self,
             LaserScan,
-            f'/lidar',
+            f'/{self.NAME}/scan',
         )
 
         self.message_filter = ApproximateTimeSynchronizer(
diff --git a/src/f1tenth b/src/f1tenth
index 017b2304..15ed4c6e 160000
--- a/src/f1tenth
+++ b/src/f1tenth
@@ -1 +1 @@
-Subproject commit 017b23043dbb07f6658c38839d39364c2f3085fe
+Subproject commit 15ed4c6ebafb0f110d67da51a68281bcb141df6d
diff --git a/src/reinforcement_learning/config/test.yaml b/src/reinforcement_learning/config/test.yaml
index 353b4476..ffcb9978 100644
--- a/src/reinforcement_learning/config/test.yaml
+++ b/src/reinforcement_learning/config/test.yaml
@@ -2,9 +2,9 @@ test:
   ros__parameters:
     environment: 'CarTrack1'
     max_steps_evaluation: 1000000
-    actor_path: models/cartrack_1_training-26-06-2023-06:50:49_150000_actor.pht
-    critic_path: models/cartrack_1_training-26-06-2023-06:50:49_150000_critic.pht
-    max_steps: 100
+    actor_path: models/23_07_05_03:52:58/models/actor_checkpoint.pht
+    critic_path: models/23_07_05_03:52:58/models/critic_checkpoint.pht
+    max_steps: 300
     step_length: 0.25
-    reward_range: 0.2
+    reward_range: 2.0
     collision_range: 0.2
\ No newline at end of file
diff --git a/src/reinforcement_learning/reinforcement_learning/train.py b/src/reinforcement_learning/reinforcement_learning/train.py
index 5dc07a5b..4642d64c 100644
--- a/src/reinforcement_learning/reinforcement_learning/train.py
+++ b/src/reinforcement_learning/reinforcement_learning/train.py
@@ -110,7 +110,7 @@ def main():
         'reward_range': REWARD_RANGE,
         'collision_range': COLLISION_RANGE
     }
-    record = Record(networks=networks, checkpoint_freq=MAX_STEPS_TRAINING / 10, config=config)
+    record = Record(networks=networks, checkpoint_freq=100, config=config)
 
     train(env=env, agent=agent, record=record)