Application of W-Band FMCW Radar for Road Curvature Estimation in Poor Visibility Conditions

Tae Yun Lee, Vladimir Skvortsov, Myung Sik Kim, Seung Hoon Han, Min Ho Ka

Research output: Contribution to journalArticle

2 Citations (Scopus)

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 languageEnglish
Pages (from-to)5300-5312
Number of pages13
JournalIEEE Sensors Journal
Volume18
Issue number13
DOIs
Publication statusPublished - 2018 Jul 1

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All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

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