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Deep Learning Approach to Detection of Preceding Vehicle in Advanced Driver Assistance

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Challenge of Transport Telematics (TST 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 640))

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Abstract

In paper we propose a detection method for objects in video stream taken in front of a car by means of deep learning. The successful detection of preceding cars is a part of the analysis of current road situation including emergency and sudden braking, unintentional lane change, traffic jam, accident, etc. We include the results of preliminary experiments employing video stream captured by camera installed behind frontal wind screen. The detection and classification are performed using Convolutional Neural Network preceded by road lane detection. We performed several experiments on real-world data in order to check the accuracy of the proposed algorithm.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, 52 Zolnierska St., 71-210, Szczecin, Poland

    Paweł Forczmański & Adam Nowosielski

Authors
  1. Paweł Forczmański
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  2. Adam Nowosielski
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Corresponding author

Correspondence to Paweł Forczmański .

Editor information

Editors and Affiliations

  1. Polish Association of Transport Telem., Katowice, Poland

    Jerzy Mikulski

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Forczmański, P., Nowosielski, A. (2016). Deep Learning Approach to Detection of Preceding Vehicle in Advanced Driver Assistance. In: Mikulski, J. (eds) Challenge of Transport Telematics. TST 2016. Communications in Computer and Information Science, vol 640. Springer, Cham. https://doi.org/10.1007/978-3-319-49646-7_25

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  • DOI: https://doi.org/10.1007/978-3-319-49646-7_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49645-0

  • Online ISBN: 978-3-319-49646-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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