Speed and Accuracy Tradeoffs for LiDAR Based Road Boundary Detection (IEEE/CAA 2020) [paper]

An speed and accuracy tradeoff method for LiDAR-based road boundary detection in structured environments is proposed. The proposed method consists of three main stages:

1. a multi-feature based method is applied to extract feature points;
2. a road-segmentation-line-based method is proposed for classifying left and right feature points;
3. an iterative Gaussian process regression (GPR) is employed for filtering out false points and extracting boundary points.

To demonstrate the effectiveness of the proposed method, KITTI datasets is used for comprehensive experiments, and the performance of our approach is tested under different road conditions. Comprehensive experiments show the road-segmentation-line-based method can classify left, and right feature points on structured curved roads, and the proposed iterative Gaussian process regression can extract road boundary points on varied road shapes and traffic conditions. Meanwhile, the proposed road boundary detection method can achieve real-time performance with an average of 70.5 ms per frame.

Demo

Introduction

The proposed method consists of four main steps: Ground Points Segmentation,Feature Points Extraction,Feature Points Classification and Feature Points Filtering. It takes a frame of raw point cloud as input and outputs road boundary points.

Installation

1. Install proto3

Please check README.md for proto3 installation instructions.

2. Install glog

Please check INSTALL for glog installation instructions.

3. Install OpenCV 3.4.5++ and PCL 1.7++

4 Install Gaussian Processes library limbo

1. clone limbo

    cd LidarRoadBoundaryDetection 
    git clone https://github.com/resibots/limbo

2. Build limbo
   Then please check official documentation to build and intall limbo

5. Build This Project

    cd LidarRoadBoundaryDetection 
    mkdir build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release && make -j8

6. Run Video Demo

(Please modify binDir to your own bin file directory in boundary_detection.config)

    ./demo_video ../config/boundary_detection.config

7 Run Frame Demo

    ./demo_frame ../config/boundary_detection.config

Citation

If you find this work useful in your research, please consider cite:

@ARTICLE{9205694,
  author={Wang, Guojun and Wu, Jian and He, Rui and Tian, Bin},
  journal={IEEE/CAA Journal of Automatica Sinica}, 
  title={Speed and Accuracy Tradeoff for LiDAR Data Based Road Boundary Detection}, 
  year={2021},
  volume={8},
  number={6},
  pages={1210-1220},
  doi={10.1109/JAS.2020.1003414}}