/CarND-Path-Planning-Project

Create a path planner that is able to navigate a car safely around a virtual highway

Primary LanguageC++

CarND-Path-Planning-Project

Self-Driving Car Engineer Nanodegree Program

The objective in this project is design a path planner that allows our simulated vehicle to safely navigate on a busy highway highway with traffic while keeping the speed below the threshold of 50MPH.

To run the simulator run the build process and then execute ./build/path_planning.

To see a video of the simulator go here

Structure

The code in this project has been divided into different classes that are responsible for different areas of the planner.

  • The main Planner class holds the entire logic and calls other classes such as Vehicle or HighwayMap
  • In HighwayMap I handle the loading of all our highway waypoint data which I use subsequently in the planner
  • The spline module is useful for spline fitting purposes
  • In Utils and State I hold useful utility functions and the different States the Finite State Machine is using that sits at the core of the simulator

Finite State Machine (FSM) and Planner Strategy

The path planner has 3 main states, keep lane, lane change right, lane change left. At every update the planner receives localisation information for our vehicle, sensor fusion data for all the rest of the traffic and uses that information to generate goal points, decide the next state and plot the trajectories.

The quintic polynomial is used to generate jerk minized trajectories. A spline fits the closest waypoints to our car's current position, a total of 30 waypoints. The JMT method is then used to select the right trajectory using the current vehicle state and goal state. The trajectory is in Frenet coordinates which are converted to Cartesian coordinates using the spline fitting from the waypoints.

The planner tries to stay in the keep_lane state and drive below the speed limit. If our vehicle encounters another vehicle in front of it, it will pass it by changing lane either to the right or to the left. A check is made before the changing lanes to ensure there isn't a car close to our proximity. If no vehicle is found in 15 meters range then the trajectory is used to make the change.

Simulator. You can download the Term3 Simulator BETA which contains the Path Planning Project from the releases tab.

The map of the highway is in data/highway_map.txt

Each waypoint in the list contains [x,y,s,dx,dy] values. x and y are the waypoint's map coordinate position, the s value is the distance along the road to get to that waypoint in meters, the dx and dy values define the unit normal vector pointing outward of the highway loop.

The highway's waypoints loop around so the frenet s value, distance along the road, goes from 0 to 6945.554.

Basic Build Instructions

  1. Clone this repo.
  2. Make a build directory: mkdir build && cd build
  3. Compile: cmake .. && make
  4. Run it: ./path_planning.

Here is the data provided from the Simulator to the C++ Program

Main car's localization Data (No Noise)

["x"] The car's x position in map coordinates

["y"] The car's y position in map coordinates

["s"] The car's s position in frenet coordinates

["d"] The car's d position in frenet coordinates

["yaw"] The car's yaw angle in the map

["speed"] The car's speed in MPH

Previous path data given to the Planner

//Note: Return the previous list but with processed points removed, can be a nice tool to show how far along the path has processed since last time.

["previous_path_x"] The previous list of x points previously given to the simulator

["previous_path_y"] The previous list of y points previously given to the simulator

Previous path's end s and d values

["end_path_s"] The previous list's last point's frenet s value

["end_path_d"] The previous list's last point's frenet d value

Sensor Fusion Data, a list of all other car's attributes on the same side of the road. (No Noise)

["sensor_fusion"] A 2d vector of cars and then that car's [car's unique ID, car's x position in map coordinates, car's y position in map coordinates, car's x velocity in m/s, car's y velocity in m/s, car's s position in frenet coordinates, car's d position in frenet coordinates.

Details

  1. The car uses a perfect controller and will visit every (x,y) point it recieves in the list every .02 seconds. The units for the (x,y) points are in meters and the spacing of the points determines the speed of the car. The vector going from a point to the next point in the list dictates the angle of the car. Acceleration both in the tangential and normal directions is measured along with the jerk, the rate of change of total Acceleration. The (x,y) point paths that the planner recieves should not have a total acceleration that goes over 10 m/s^2, also the jerk should not go over 50 m/s^3. (NOTE: As this is BETA, these requirements might change. Also currently jerk is over a .02 second interval, it would probably be better to average total acceleration over 1 second and measure jerk from that.

  2. There will be some latency between the simulator running and the path planner returning a path, with optimized code usually its not very long maybe just 1-3 time steps. During this delay the simulator will continue using points that it was last given, because of this its a good idea to store the last points you have used so you can have a smooth transition. previous_path_x, and previous_path_y can be helpful for this transition since they show the last points given to the simulator controller with the processed points already removed. You would either return a path that extends this previous path or make sure to create a new path that has a smooth transition with this last path.

Dependencies