자동차안전학회지 (Journal of Auto-vehicle Safety Association)

한국자동차안전학회 (Korean Auto-vehicle Safety Association)
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자율주행을 위한 레이더 기반 인지 알고리즘의 정량적 분석

Quantitative Analysis of Automotive Radar-based Perception Algorithm for Autonomous Driving

  • 투고 : 2018.04.01
  • 심사 : 2018.05.15
  • 발행 : 2018.06.30
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초록

This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.

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참고문헌

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피인용 문헌

  1. 자율주행 제어를 위한 향상된 주변환경 인식 알고리즘 vol.11, pp.2, 2018, https://doi.org/10.22680/kasa2019.11.2.035