Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists

Andrii Matviienko; Florian Heller; Bastian Pfleging

doi:10.1145/3411763.3451678

Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists

Andrii Matviienko
, Florian Heller
, Bastian Pfleging

EAISI Mobility

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

21 Citations (Scopus)

136 Downloads (Pure)

Abstract

Today's level of cyclists' road safety is primarily estimated using accident reports and self-reported measures. However, the former is focused on post-accident situations and the latter relies on subjective input. In our work, we aim to extend the landscape of cyclists' safety assessment methods via a two-dimensional taxonomy, which covers data source (internal/external) and type of measurement (objective/subjective). Based on this taxonomy, we classify existing methods and present a mobile sensing concept for quantified cycling safety that fills the identified methodological gap by collecting data about body movements and physiological data. Finally, we outline a list of use cases and future research directions within the scope of the proposed taxonomy and sensing concept.

Original language	English
Title of host publication	CHI EA '21
Subtitle of host publication	Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
Editors	Yoshifumi Kitamura, Aaron Quigley, Katherine Isbister, Takeo Igarashi
Place of Publication	New York
Publisher	Association for Computing Machinery, Inc.
Number of pages	6
ISBN (Electronic)	978-1-4503-8095-9
DOIs	https://doi.org/10.1145/3411763.3451678
Publication status	Published - 8 May 2021
Event	2021 CHI Conference on Human Factors in Computing Systems, CHI 2021 - Virtual, Online, Yokohama, Japan Duration: 8 May 2021 → 13 May 2021 https://chi2021.acm.org/

Conference

Conference	2021 CHI Conference on Human Factors in Computing Systems, CHI 2021
Abbreviated title	CHI 2021
Country/Territory	Japan
City	Yokohama
Period	8/05/21 → 13/05/21
Other	"Making Waves, Combining Strengths"
Internet address	https://chi2021.acm.org/

Keywords

Cyclist safety taxonomy
head movements
on-body sensing
perceived road safety

Access to Document

10.1145/3411763.3451678

Quantified Cycling Safety - Author-prepared versionFinal author version , 1.17 MBLicence: Other
pdfFinal published version, 1.48 MBLicence: TAVERNE

Cite this

Matviienko, A., Heller, F., & Pfleging, B. (2021). Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists. In Y. Kitamura, A. Quigley, K. Isbister, & T. Igarashi (Eds.), CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems Article 262 Association for Computing Machinery, Inc.. https://doi.org/10.1145/3411763.3451678

Matviienko, Andrii ; Heller, Florian ; Pfleging, Bastian. / Quantified Cycling Safety : Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists. CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. editor / Yoshifumi Kitamura ; Aaron Quigley ; Katherine Isbister ; Takeo Igarashi. New York : Association for Computing Machinery, Inc., 2021.

@inproceedings{84e5f912af4547bf835fc4aad2ad5cc1,

title = "Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists",

abstract = "Today's level of cyclists' road safety is primarily estimated using accident reports and self-reported measures. However, the former is focused on post-accident situations and the latter relies on subjective input. In our work, we aim to extend the landscape of cyclists' safety assessment methods via a two-dimensional taxonomy, which covers data source (internal/external) and type of measurement (objective/subjective). Based on this taxonomy, we classify existing methods and present a mobile sensing concept for quantified cycling safety that fills the identified methodological gap by collecting data about body movements and physiological data. Finally, we outline a list of use cases and future research directions within the scope of the proposed taxonomy and sensing concept.",

keywords = "Cyclist safety taxonomy, head movements, on-body sensing, perceived road safety",

author = "Andrii Matviienko and Florian Heller and Bastian Pfleging",

year = "2021",

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doi = "10.1145/3411763.3451678",

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editor = "Yoshifumi Kitamura and Aaron Quigley and Katherine Isbister and Takeo Igarashi",

booktitle = "CHI EA '21",

publisher = "Association for Computing Machinery, Inc.",

address = "United States",

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Matviienko, A, Heller, F & Pfleging, B 2021, Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists. in Y Kitamura, A Quigley, K Isbister & T Igarashi (eds), CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems., 262, Association for Computing Machinery, Inc., New York, 2021 CHI Conference on Human Factors in Computing Systems, CHI 2021, Yokohama, Japan, 8/05/21. https://doi.org/10.1145/3411763.3451678

Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists. / Matviienko, Andrii; Heller, Florian; Pfleging, Bastian.
CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. ed. / Yoshifumi Kitamura; Aaron Quigley; Katherine Isbister; Takeo Igarashi. New York: Association for Computing Machinery, Inc., 2021. 262.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Quantified Cycling Safety

T2 - 2021 CHI Conference on Human Factors in Computing Systems, CHI 2021

AU - Matviienko, Andrii

AU - Heller, Florian

AU - Pfleging, Bastian

PY - 2021/5/8

Y1 - 2021/5/8

N2 - Today's level of cyclists' road safety is primarily estimated using accident reports and self-reported measures. However, the former is focused on post-accident situations and the latter relies on subjective input. In our work, we aim to extend the landscape of cyclists' safety assessment methods via a two-dimensional taxonomy, which covers data source (internal/external) and type of measurement (objective/subjective). Based on this taxonomy, we classify existing methods and present a mobile sensing concept for quantified cycling safety that fills the identified methodological gap by collecting data about body movements and physiological data. Finally, we outline a list of use cases and future research directions within the scope of the proposed taxonomy and sensing concept.

AB - Today's level of cyclists' road safety is primarily estimated using accident reports and self-reported measures. However, the former is focused on post-accident situations and the latter relies on subjective input. In our work, we aim to extend the landscape of cyclists' safety assessment methods via a two-dimensional taxonomy, which covers data source (internal/external) and type of measurement (objective/subjective). Based on this taxonomy, we classify existing methods and present a mobile sensing concept for quantified cycling safety that fills the identified methodological gap by collecting data about body movements and physiological data. Finally, we outline a list of use cases and future research directions within the scope of the proposed taxonomy and sensing concept.

KW - Cyclist safety taxonomy

KW - head movements

KW - on-body sensing

KW - perceived road safety

UR - https://www.scopus.com/pages/publications/85105817627

U2 - 10.1145/3411763.3451678

DO - 10.1145/3411763.3451678

M3 - Conference contribution

BT - CHI EA '21

A2 - Kitamura, Yoshifumi

A2 - Quigley, Aaron

A2 - Isbister, Katherine

A2 - Igarashi, Takeo

PB - Association for Computing Machinery, Inc.

CY - New York

Y2 - 8 May 2021 through 13 May 2021

ER -

Matviienko A, Heller F, Pfleging B. Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists. In Kitamura Y, Quigley A, Isbister K, Igarashi T, editors, CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. New York: Association for Computing Machinery, Inc. 2021. 262 doi: 10.1145/3411763.3451678

Quantified Cycling Safety: Towards a Mobile Sensing Platform to Understand Perceived Safety of Cyclists

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