Giter Club home page Giter Club logo

lane-keeping-assist-on-carla's Introduction

Lane-Keeping-Assist-on-CARLA

Introduction

This is a module assgnment from Motion Planning for Self-Driving Cars course of Self-Driving Cars Specialization on Coursera.org.

This assginment implements Lane Keeping Assist function by applying pure pursuit and Stanley methods for lateral control and PID controller for longitudinal control using Python as the programming language.

The waypoints and corresponding velocities for the track are pre-defined.

To realize this function, the open sourse simulator CARLA is introduced.

Prerequisites

First CARLA must be installed on your machine, the CARLA loader requires Ubuntu 16.04 or later to run

Please go through CARLA-Setup-Guide-Ubuntu.pdf and install CARLA and all other dependencies properly.

CARLA Simulator can be downloaded here

How to run it

First clone this repository and put it under PythonClient directory.

1. Load the simulator

Open a terminal and do cd ~/opt/CarlaSimulator.

Then do ./CarlaUE4.sh /Game/Maps/RaceTrack -windowed -carla-server -benchmark -quality-level=Low -fps=30

2. Run the LKA controller

Open another terminal and do cd ~/opt/CarlaSimulator/PythonClient/Lane-Keeping-Assist-on-CARLA.

(optional) do sudo apt-get install python3-tk in case you do not have Tkinter module.

Run python3 module_7.py to execute the controller(default is MPC control method)

To select 3 different control methods:

MPC - python3 module_7.py --control-method MPC

Stanley - python3 module_7.py --control-method Stanley

Pure Pursuit - python3 module_7.py --control-method PurePursuit

The vehicle should starting driving and following the track.

Simulation results

The images shown below is the result of vehicle trajectory(MPC, Stanley and Pure Pursuit method).

The green line is the track(ground truth) and the orange line is the trajectory.

MPC Method

Stanley Method

Pure Pursuit Method

lane-keeping-assist-on-carla's People

Contributors

paulyehtw avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.