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Beware the Sirens: Prototyping an Emergency Vehicle Detection System for Smart Cars

  • Conference paper
Applied Intelligence and Informatics (AII 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1724))

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Abstract

Vehicle drivers should be able to react coherently in anomalous circumstances, such as the quick arrival of an emergency vehicle with sirens wailing. This situation requires all regular vehicles to give way or slow down, depending on the road and traffic conditions. In this paper, we address an automatic system that assists the driver in reacting to the arrival of an emergency vehicle by employing audio and video algorithms based on Deep Learning. More specifically, by leveraging sound recognition algorithms, the vehicle is able to detect the arrival of the emergency vehicle by its siren sound. In such an event, by making use of computer vision algorithms, the vehicle intelligence can monitor the driver’s gaze and awareness towards the emergency vehicle and assess his/her awareness. The paper describes the process of integrating these technologies into a commercial car, the creation of new datasets and the challenges encountered.

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Notes

  1. 1.

    DAVIS346 Datasheet available at the following URL: https://inivation.com/wp-content/uploads/2019/08/DAVIS346.pdf.

  2. 2.

    https://kivy.org/.

  3. 3.

    http://www.portaudio.com/.

  4. 4.

    https://pytorch.org/.

  5. 5.

    Eyeware toolchain (public) https://github.com/eyeware.

  6. 6.

    SerpApi - Google Image API https://serpapi.com/.

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Acknowledgement

This work is supported by Marche Region in implementation of the financial programme POR MARCHE FESR 2014-2020, project “Miracle” (Marche Innovation and Research fAcilities for Connected and sustainable Living Environments), CUP B28I19000330007.

Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, via Brecce Bianche 12, 60131, Ancona, Italy

    Michela Cantarini, Leonardo Gabrielli, Lucia Migliorelli, Adriano Mancini & Stefano Squartini

Authors
  1. Michela Cantarini
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  2. Leonardo Gabrielli
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  3. Lucia Migliorelli
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  4. Adriano Mancini
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  5. Stefano Squartini
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Corresponding author

Correspondence to Leonardo Gabrielli .

Editor information

Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Cosimo Ieracitano

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Nadia Mammone

  5. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

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Cantarini, M., Gabrielli, L., Migliorelli, L., Mancini, A., Squartini, S. (2022). Beware the Sirens: Prototyping an Emergency Vehicle Detection System for Smart Cars. In: Mahmud, M., Ieracitano, C., Kaiser, M.S., Mammone, N., Morabito, F.C. (eds) Applied Intelligence and Informatics. AII 2022. Communications in Computer and Information Science, vol 1724. Springer, Cham. https://doi.org/10.1007/978-3-031-24801-6_31

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