Create 2nd Model.py

Made changes and updated the previous model

Author: harshagarwal94

Diff for: 2nd Model.py

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+import math
+def reward_function(params):
+    # Example of rewarding the agent to follow center line
+
+    # Read input parameters
+    
+    track_width = params['track_width']
+    distance_from_center = params['distance_from_center']
+    
+    abs_steering = abs(params['steering_angle'])
+    
+    all_wheels_on_track = params['all_wheels_on_track']
+    speed = params['speed']
+    
+    waypoints = params['waypoints']
+    closest_waypoints = params['closest_waypoints']
+    heading = params['heading']
+
+    # Calculate 3 markers that are at varying distances away from the center line
+    #Distance from centre
+    
+    marker_1 = 0.1 * track_width
+    marker_2 = 0.25 * track_width
+    marker_3 = 0.5 * track_width
+
+    # Give higher reward if the car is closer to center line and vice versa
+    if distance_from_center <= marker_1:
+        reward = 1.1
+    elif distance_from_center <= marker_2:
+        reward = 0.5
+    elif distance_from_center <= marker_3:
+        reward = 0.1
+    else:
+        reward = 1e-3 # likely crashed/ close to off track
+    
+    #steering angle     
+    ABS_STEERING_THRESHOLD = 7
+    if abs_steering > ABS_STEERING_THRESHOLD:
+        #penalty
+        reward *= 0.8
+    
+    ## Set the speed threshold based your action space
+    SPEED_THRESHOLD = 1.0
+
+    if not all_wheels_on_track:
+        # Penalize if the car goes off track
+        reward = 1e-3
+    elif speed < SPEED_THRESHOLD:
+        # Penalize if the car goes too slow
+        reward = 0.7
+    else:
+        # High reward if the car stays on track and goes fast
+        reward = 1.6
+        
+        
+        
+# Initialize the reward with typical value
+    reward = 1.0
+
+    # Calculate the direction of the center line based on the closest waypoints
+    next_point = waypoints[closest_waypoints[1]]
+    prev_point = waypoints[closest_waypoints[0]]
+
+    # Calculate the direction in radius, arctan2(dy, dx), the result is (-pi, pi) in radians
+    track_direction = math.atan2(next_point[1] - prev_point[1], next_point[0] - prev_point[0])
+    # Convert to degree
+    track_direction = math.degrees(track_direction)
+
+    # Calculate the difference between the track direction and the heading direction of the car
+    direction_diff = abs(track_direction - heading)
+    if direction_diff > 180:
+        direction_diff = 360 - direction_diff
+
+    # Penalize the reward if the difference is too large
+    DIRECTION_THRESHOLD = 5.0
+    if direction_diff > DIRECTION_THRESHOLD:
+        reward *= 0.5
+## Calculate the distance from each border
+    distance_from_border = 0.5 * track_width - distance_from_center
+
+    # Reward higher if the car stays inside the track borders
+    if distance_from_border >= 0.2:
+        reward = 1.5
+    else:
+        reward = 1e-3 # Low reward if too close to the border or goes off the track
+
+    return float(reward)
+