FPGA Design for Autonomous Vehicle Driving Using Binarized Neural Networks

Kaijie Wei, Koki Honda, Hideharu Amano

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

We propose an autonomous vehicle controlled by FPGAs. In our design, considering embedded systems, we apply the binarized neural networks (BNNs) which can realize a satis-fying result in high speed and accuracy to recognize pedestrians and some obstacles on a given road. To detect the traffic light, a passive camera-based pipeline is applied. Furthermore, the implementation of road lane detection is based on color selection algorithm, Canny Edge Detection, and Hough Transformation. The proposed design is realized by two Xilinx boards: PYNQ-Z1 and Zynq-Xc7Z010. These two FPGA boards cooperate with each other through a shared network cable. In the proposed design, the resource used by Zynq-Xc7Z010 can be greatly reduced and the inference time on the FPGA has been thousands times faster than the software implementation.

本文言語English
ホスト出版物のタイトルProceedings - 2018 International Conference on Field-Programmable Technology, FPT 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ428-431
ページ数4
ISBN(電子版)9781728102139
DOI
出版ステータスPublished - 2018 12月
イベント17th International Conference on Field-Programmable Technology, FPT 2018 - Naha, Okinawa, Japan
継続期間: 2018 12月 102018 12月 14

出版物シリーズ

名前Proceedings - 2018 International Conference on Field-Programmable Technology, FPT 2018

Conference

Conference17th International Conference on Field-Programmable Technology, FPT 2018
国/地域Japan
CityNaha, Okinawa
Period18/12/1018/12/14

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ サイエンスの応用
  • ハードウェアとアーキテクチャ

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