Abstract
This paper discusses radar-based technologies that provide drivers with information about road curves under conditions in which optical sensors are unable to perform. The development of a task capable of estimating road curves has become a popular challenge since the commencement of the active development of advanced driver assistance systems and autonomous vehicles. Although the hardware implementation of a road curvature measurement system may have many variations, including cameras, we consider microwave sensors to be a reasonable alternative that offers many benefits. Road curvature measurement requires fast acquisition of the necessary data from a moving vehicle followed by efficient postprocessing of the data to identify a sufficient number of reliable featured points in the local environment. These points would enable a hypothesis about the dimensions and shape of the probable road geometry to be built. Different studies attempted to solve this problem using specialized equipment and custom-built algorithms. Our solution is to use a commercially available radar and some preprocessing and postprocessing algorithms for data conditioning and analysis to obtain reliable results in both day- and night-time environments and under various weather conditions in a relatively short time using a simplified approach based on circle-fitting algorithms. We confirmed the effectiveness of the proposed approach by conducting multiple road experiments with a commercially available microwave sensor. Considering that the road infrastructure is currently not optimized for road curvature measurements, the results we obtained with our proposed method (within 10%-17% of those on the actual map) are acceptable.
Original language | English |
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Pages (from-to) | 5300-5312 |
Number of pages | 13 |
Journal | IEEE Sensors Journal |
Volume | 18 |
Issue number | 13 |
DOIs | |
Publication status | Published - 2018 Jul 1 |
Bibliographical note
Funding Information:Manuscript received April 3, 2018; accepted May 1, 2018. Date of publication May 17, 2018; date of current version June 12, 2018. This work was supported in part by the Ministry of Science and ICT, South Korea, through the ICT Consilience Creative Program supervised by the Institute for Information and communications Technology Promotion under Grant IITP-2018-2017-0-01015, in part by Samsung Electronics Co., Ltd., through the Development of Environment Sensing Technology Based on Radar Project, and in part by IITP funded by the Korea Government (MSIT) under Grant 2017-0-00678 (A Development of SAR for small sized UAV). The associate editor coordinating the review of this paper and approving it for publication was Dr. Piotr J. Samczynski. (Corresponding author: Min-Ho Ka.) T.-Y. Lee, V. Skvortsov, and M.-H. Ka are with the School of Integrated Technology, Yonsei Institute of Convergence Technology, Yonsei University, Seoul 03722, South Korea (e-mail: kaminho@yonsei.ac.kr).
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All Science Journal Classification (ASJC) codes
- Instrumentation
- Electrical and Electronic Engineering