An auditory dataset of passing vehicles recorded with a smartphone

Conference Paper (2018)
Author(s)

P. Bazilinskyy (TU Delft - Intelligent Vehicles, TU Delft - Biomechatronics & Human-Machine Control)

Arne van der Aa (Student TU Delft)

Michael Schoustra (Student TU Delft)

John Spruit (Student TU Delft)

Laurens Staats (Student TU Delft)

Klaas Jan van der Vlist (Student TU Delft)

J.C.F. de Winter (TU Delft - Human-Robot Interaction, TU Delft - Biomechatronics & Human-Machine Control)

Research Group
Biomechatronics & Human-Machine Control
Copyright
© 2018 P. Bazilinskyy, Arne van der Aa, Michael Schoustra, John Spruit, Laurens Staats, Klaas Jan van der Vlist, J.C.F. de Winter
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 P. Bazilinskyy, Arne van der Aa, Michael Schoustra, John Spruit, Laurens Staats, Klaas Jan van der Vlist, J.C.F. de Winter
Research Group
Biomechatronics & Human-Machine Control
Pages (from-to)
417-422
ISBN (print)
978-94-6186-910-4
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

The increase of smartphones over the past decade has contributed to distraction in traffic. However, smartphones could potentially be turned into an advantage by being able to detect whether a motorized vehicle is passing the smartphone user (e.g., a pedestrian or cyclist). Herein, we present a dataset of audio recordings of passing vehicles, made with a smartphone. Recordings were made of a passing passenger car and a scooter in various conditions (windy weather vs. calm weather, approaching from the front vs. from behind, 1 m, 2 m, and 3 m distance between smartphone and vehicle, vehicle driving with 30 vs. 50 km/h, and smartphone being stationary vs. moving with the cyclist). Data from an 8-microphone array, video recordings, and GPS data of vehicle position and speed are provided as well. Our present dataset may prove useful in the development of mobile apps that detect a passing motorized vehicle, or for transportation research.

Link to 4TU.Centre for Research Data: https://doi.org/10.4121/uuid:bef54ab8-73ef-42f3-b6b7-54e011737e72

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