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Real-Time Overtaking Vehicle Detection Based on Optical Flow and Convolutional Neural Network

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Smart Cities, Green Technologies and Intelligent Transport Systems (SMARTGREENS 2018, VEHITS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 992))

Abstract

For the development of driver assistance systems, overtaking detection plays an important role in commercial vehicle applications. In this paper, we present a real-time overtaking vehicle detection system using a monocular camera mounted in the rear of a vehicle. It aims to assist the drivers or self-driving cars to perform safe lane change operations. In the proposed method, the possible overtaking vehicles are first located based on motion cues. The candidates are then identified using Convolutional Neural Network (CNN) and tracked for behavior analysis in a short period of time. We present an algorithm to solve the issue of repetitive patterns which is commonly appeared in highway driving. A series of experiments are carried out with real scene video sequences recorded by a dashcam. The objective is to detect other vehicles passing by so as to alert the driver and avoid the potential traffic accidents. The performance evaluation has demonstrated the effectiveness of the proposed technique.

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Acknowledgments

The support of this work in part by Create Electronic Optical Co., LTD, Taiwan and the Ministry of Science and Technology of Taiwan under Grant MOST 104-2221-E-194-058-MY2, is gratefully acknowledged.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Chung Cheng University, 168 University Road, Chiayi, 621, Taiwan

    Lu-Ting Wu, Van Luan Tran & Huei-Yung Lin

  2. Advanced Institute of Manufacturing with High-Tech Innovation, National Chung Cheng University, 168 University Road, Chiayi, 621, Taiwan

    Huei-Yung Lin

Authors
  1. Lu-Ting Wu
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  2. Van Luan Tran
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  3. Huei-Yung Lin
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Corresponding author

Correspondence to Huei-Yung Lin .

Editor information

Editors and Affiliations

  1. School of Business, Maynooth University, Maynooth, Ireland

    Brian Donnellan

  2. CT RDA SSI, Siemens AG, Munich, Bayern, Germany

    Cornel Klein

  3. Dublin City University, Dublin, Ireland

    Markus Helfert

  4. Ford Research and Advanced Engineer, Dearborn, MI, USA

    Oleg Gusikhin

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Wu, LT., Tran, V.L., Lin, HY. (2019). Real-Time Overtaking Vehicle Detection Based on Optical Flow and Convolutional Neural Network. In: Donnellan, B., Klein, C., Helfert, M., Gusikhin, O. (eds) Smart Cities, Green Technologies and Intelligent Transport Systems. SMARTGREENS VEHITS 2018 2018. Communications in Computer and Information Science, vol 992. Springer, Cham. https://doi.org/10.1007/978-3-030-26633-2_11

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  • DOI: https://doi.org/10.1007/978-3-030-26633-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26632-5

  • Online ISBN: 978-3-030-26633-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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