text: #!/usr/bin/env python
  
  import rospy
  from geometry_msgs.msg import PoseStamped
  from styx_msgs.msg import Lane, Waypoint
  from std_msgs.msg import Int32 , Float32
  from scipy.spatial import KDTree
  from std_msgs.msg import String
  import numpy as np
  import math
  
  
  '''
  This node will publish waypoints from the car's current position to some `x` distance ahead.
  As mentioned in the doc, you should ideally first implement a version which does not care
  about traffic lights or obstacles.
  Once you have created dbw_node, you will update this node to use the status of traffic lights too.
  Please note that our simulator also provides the exact location of traffic lights and their
  current status in `/vehicle/traffic_lights` message. You can use this message to build this node
  as well as to verify your TL classifier.
  TODO (for Yousuf and Aaron): Stopline location for each traffic light.
  '''
  
  LOOKAHEAD_WPS = 100 # Number of waypoints we will publish. You can change this number
  MAX_DECEL = 0.5
  STOP_LINE_COUNT_BEFORE = 5
  
  class WaypointUpdater(object):
      def __init__(self):
          rospy.init_node('waypoint_updater')
  
          self.base_lane = None
          self.pose = None
          self.waypoints_2d = None
          self.waypoint_tree = None
          self.track_waypoint_count = -1
          self.stopline_wp_idx = -1
          
          rospy.Subscriber('/current_pose', PoseStamped, self.pose_cb)
          rospy.Subscriber('/traffic_waypoint', Int32, self.traffic_cb)
          self.base_waypoints_subscriber = rospy.Subscriber('/base_waypoints', Lane, self.waypoints_cb)
          
          self.final_waypoints_pub = rospy.Publisher('final_waypoints', Lane, queue_size=1)
          self.loop()
  
      def loop(self):
          rate = rospy.Rate(10)
          while not rospy.is_shutdown():
              if self.pose and self.base_lane and self.waypoint_tree:
                  self.publish_waypoints()
              rate.sleep()
  
      def get_closest_waypoint_idx(self):
          x = self.pose.pose.position.x
          y = self.pose.pose.position.y
          closest_idx = self.waypoint_tree.query([x,y],1)[1]
  
          closest_coord = self.waypoints_2d[closest_idx]
          prev_cooord = self.waypoints_2d[closest_idx - 1]
  
          #Equation for hyperplane through CLosest Co-ordinates
          cl_vect = np.array(closest_coord)
          prev_vect = np.array(prev_cooord)
          pos_vect = np.array([x,y])
  
          val = np.dot(cl_vect - prev_vect, pos_vect - cl_vect)
  
          if val > 0:
              closest_idx = (closest_idx+1) % len(self.waypoints_2d)
  
          return closest_idx
  
      def publish_waypoints(self):
          lane = Lane()
          closest_index = self.get_closest_waypoint_idx()
          last_index = closest_index + LOOKAHEAD_WPS
          
          if last_index < self.track_waypoint_count:
              base_waypoints = self.base_lane.waypoints[closest_index:last_index]
          else:
              index_offset = last_index - self.track_waypoint_count
              last_index = self.track_waypoint_count - 2
              base_waypoints = self.base_lane.waypoints[closest_index:last_index]
              base_waypoints += self.base_lane.waypoints[0:index_offset]
          
          if self.stopline_wp_idx == -1 or self.stopline_wp_idx >= last_index:
              lane.waypoints = base_waypoints
          else:
              lane.waypoints = self.decelerate_waypoints(base_waypoints, closest_index)
          
          self.final_waypoints_pub.publish(lane)
   
      def decelerate_waypoints(self, waypoints, closest_index):
          result = []
          for i, wp in enumerate(waypoints):
              p = Waypoint()
              p.pose = wp.pose
              stop_index = max(self.stopline_wp_idx - closest_index - STOP_LINE_COUNT_BEFORE, 0)
              dist = self.distance(waypoints, i, stop_index)
              vel = math.sqrt(2 * MAX_DECEL * dist)
              if vel < 1.0:
                  vel = 0.0
              p.twist.twist.linear.x = min(vel, wp.twist.twist.linear.x)
              result.append(p)
              
          return result
  
      def pose_cb(self, msg):
          self.pose = msg
  
      def waypoints_cb(self, waypoints):
          self.base_lane = waypoints
          self.track_waypoint_count = len(waypoints.waypoints)
          
          if self.waypoints_2d == None:
              self.waypoints_2d = [[wp.pose.pose.position.x, wp.pose.pose.position.y] for wp in waypoints.waypoints]
              self.waypoint_tree = KDTree(self.waypoints_2d)
             
      def traffic_cb(self, msg):
          self.stopline_wp_idx = msg.data    
      pass
  
      def obstacle_cb(self, msg):
          # TODO: Callback for /obstacle_waypoint message. We will implement it later
          pass
  
      def get_waypoint_velocity(self, waypoint):
          return waypoint.twist.twist.linear.x
  
      def set_waypoint_velocity(self, waypoints, waypoint, velocity):
          waypoints[waypoint].twist.twist.linear.x = velocity
  
      def distance(self, waypoints, wp1, wp2):
          dist = 0
          dl = lambda a, b: math.sqrt((a.x-b.x)**2 + (a.y-b.y)**2  + (a.z-b.z)**2)
          for i in range(wp1, wp2+1):
              dist += dl(waypoints[wp1].pose.pose.position, waypoints[i].pose.pose.position)
              wp1 = i
          return dist
  
  if __name__ == '__main__':
      try:
          WaypointUpdater()
      except rospy.ROSInterruptException:
          rospy.logerr('Could not start waypoint updater node.')