C++/ROS Source Codes for "Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method" published in IEEE Trans. Intelligent Transportation Systems by Bai Li, Yakun Ouyang, Li Li, and Youmin Zhang.
Requirements
- ROS Melodic or later
- Python3
Install packages required by Ipopt
sudo apt-get install gcc g++ gfortran git patch wget pkg-config liblapack-dev libmetis-dev
Clone repository to any catkin workspace and compile workspace
cd ~/catkin_ws/src
git clone https://github.com/libai1943/CartesianPlanner.git cartesian_planner
cd .. && catkin_make
source devel/setup.bash
OPTIONAL: build and install Harwell Subroutine Library (HSL) (recommended for better performance)
git clone https://github.com/coin-or-tools/ThirdParty-HSL.git
# Obtain a tarball with HSL source code from http://www.hsl.rl.ac.uk/ipopt/ and unpack this tarball
tar -zxvf coinhsl-x.y.z.tar
# Rename the directory `coinhsl-x.y.z` to `coinhsl`, or set a symbolic link:
ln -s coinhsl-x.y.z coinhsl
./configure
make
sudo make install
# create symlink for Ipopt
sudo ln -s /usr/local/lib/libcoinhsl.so /usr/local/lib/libhsl.so
# Re-build workspace
cd ~/catkin_ws && catkin_make -DWITH_HSL=ON
tits_pedestrian_static_dynamic_3.mp4
Example test case with 6 pedestrians, 3 moving vehicles and 2 static vehicles.
roslaunch cartesian_planner pedestrian_test.launch
Click anywhere in Rviz window with the 2D Nav Goal
Tool to start planning.
Generate and run new random case:
roslaunch cartesian_planner random_pedestrian_test.launch
Special thanks to Baidu Apollo for common math libraries
Copyright (C) 2022 Bai Li and Yakun Ouyang
Users must cite the following article if they use the source codes to conduct simulations in their new publications. Bai Li, Yakun Ouyang, Li Li, and Youmin Zhang, “Autonomous driving on curvy roads without reliance on Frenet frame: A Cartesian-based trajectory planning method,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 9, pp. 15729 - 15741, 2022. available at https://doi.org/10.1109/TITS.2022.3145389