This is the project repo for the final project of the Udacity Self-Driving Car Nanodegree: Programming a Real Self-Driving Car. For more information about the project, see the project introduction here.

Team FinishLine

• Team Leader:
  Tianzi Harrison
  [email protected]
• Team Members:
  Yusun Liu
  [email protected]
  Hiraku Shibuya
  [email protected]
  Davy Leggieri
  [email protected]

Video

You may see a video of our car driving the second lap in the simulator here: https://youtu.be/u-9C46mq8wY

Installation

Bare Metal

• Be sure that your workstation is running Ubuntu 16.04 Xenial Xerus or Ubuntu 14.04 Trusty Tahir. Ubuntu downloads can be found here.

• If using a Virtual Machine to install Ubuntu, use the following configuration as minimum:

  • 2 CPU
  • 2 GB system memory
  • 25 GB of free hard drive space

  The Udacity provided virtual machine has ROS and Dataspeed DBW already installed, so you can skip the next two steps if you are using this.

• Follow these instructions to install ROS

  • ROS Kinetic if you have Ubuntu 16.04.
  • ROS Indigo if you have Ubuntu 14.04.

• Dataspeed DBW

  • Use this option to install the SDK on a workstation that already has ROS installed: One Line SDK Install (binary)

• Download the Udacity Simulator.

Docker container

Install Docker on your host machine.

Usage

Bare Metal

1. Clone the project repository

git clone https://github.com/udacity/CarND-Capstone.git

2. Install python dependencies

cd CarND-Capstone
pip install -r requirements.txt

3. Install dbw_mkz ros package

bash <(wget -q -O - https://bitbucket.org/DataspeedInc/dbw_mkz_ros/raw/default/dbw_mkz/scripts/sdk_update.bash)

4. Make and run styx

cd ros
catkin_make
source devel/setup.sh
roslaunch launch/styx.launch

5. Run the simulator

Docker container

1. Clone the project repository

git clone https://github.com/udacity/CarND-Capstone.git

2. Start the container

./run.sh

4. Make and run styx

cd ros
catkin_make
source devel/setup.sh
roslaunch launch/styx.launch

5. Run the simulator

Real world testing

1. Download training bag that was recorded on the Udacity self-driving car
2. Unzip the file

unzip traffic_light_bag_files.zip

3. Play the bag file

rosbag play -l traffic_light_bag_files/loop_with_traffic_light.bag

4. Launch your project in site mode

cd CarND-Capstone/ros
roslaunch launch/site.launch

Credits

Thanks to the Kung Fu Panda Automotive team for their dummy traffic light detector we used during testing. It bought us some time before we had a working traffic light detector.