4D_Radar_MOT

The code for reproducing experiment results in the conference paper "Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?" in 35th IEEE Intelligent Vehicles Symposium (IV 2024), Oral Presentation (Top 5%).

Installation

• Clone the repository and enter the directory.

git clone https://github.com/dinggh0817/4D_Radar_MOT.git
cd 4D_Radar_MOT

• For conda users, create the python environment and install required packages.

conda create --name 4D_MOT python==3.8.16
conda activate 4D_MOT
pip install -r requirements.txt

Run Evaluation

• Run .py scripts to evaluate different tracking algorithms, e.g.,

python RUN_SMURF_GNN_PMB.py

• Note: The GNN-PMB and GGIW-PMBM filters rely on the Murty algorithm. The prebulit murty.dll and murty.so library files are provided. Change the library directory in mhtdaClink.py if you want to run evaluations on Windows platform. Please refer to fastmurty for source code and further information of Murty.

Acknowledgement

The code in this repository is developed based on the following projects:

• https://github.com/yuhsuansia/Extended-target-PMBM-and-PMB-filters
• https://github.com/JonathonLuiten/TrackEval
• https://github.com/tudelft-iv/view-of-delft-dataset
• https://github.com/motrom/fastmurty