def reward_function(params):
    '''
    Example of rewarding the agent to follow center line
    '''
    import math
    # Read input parameters
    track_width = params['track_width']
    distance_from_center = params['distance_from_center']
    steering = abs(params['steering_angle'])
    all_wheels_on_track = params['all_wheels_on_track']
    steering_angle = params['steering_angle']
    is_left_of_center = params['is_left_of_center']
    waypoints = params['waypoints']
    closest_waypoints = params['closest_waypoints']
    heading = params['heading']

    # Calculate 3 markers that are at varying distances away from the center line
    marker_1 = 0.1 * track_width
    marker_2 = 0.25 * track_width
    marker_3 = 0.4 * track_width

    # Give higher reward if the car is closer to center line and vice versa
    if distance_from_center <= marker_1:
        reward = 1.0
    elif distance_from_center <= marker_2:
        reward = 0.75
    elif distance_from_center <= marker_3:
        reward = 0.3
    else:
        reward = 0.1  # likely crashed/ close to off track

    # Steering penality threshold, change the number based on your action space setting
    ABS_STEERING_THRESHOLD = 10

    # Penalize reward if the agent is steering too much
    if steering > ABS_STEERING_THRESHOLD:
        reward *= 0.8

    # Give a high reward if no wheels go off the track and
    # the agent is somewhere in between the track borders
    distance_from_border = (0.5*track_width) - distance_from_center
    if all_wheels_on_track and  distance_from_border >= 0.15:
        reward *= 1.2
    if not all_wheels_on_track:
        reward *= -1

    # 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)

    # Cacluate the difference between the track direction and the heading direction of the car
    direction_diff = abs(track_direction - heading)

    # Penalize the reward if the difference is too large
    DIRECTION_THRESHOLD = 10.0
    if direction_diff > DIRECTION_THRESHOLD:
        reward *= -1

    return float(reward)