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LUND UNIVERSITY LIBRARIES

Untapping the potential of crowdsourcing app data to measure urban bicycle flow

Palomino Achulli, Sebastian LU (2024) VTVL01 20232
Transport and Roads
Abstract (Swedish)
De nuvarande metoderna som tillämpas av olika företag och forskare när det
gäller om att räkna cykelvolym i olika tätorter har förbättrats över tiden. Dock
har det aldrig varit felfri, vilket har lett till fortsatta studier och ännu mer
utrymme att förbättra de befintliga metoderna. Därför är syftet med rapporten
att ytterligare analysera det som redan har gjorts och hur man kan överträffa
nuvarande förväntningar.

En djupdykning i olika cyklisters beteende gjordes genom att analysera antal
fel som inträffade vid insamling av data, samt orsaken till att dessa
felaktigheter uppstår i första hand. Flera analyser gjordes i hela Lund stad,
med hjälp av kommunen och applikationen TravelVu, både i hjärtat av staden
och även i... (More)
De nuvarande metoderna som tillämpas av olika företag och forskare när det
gäller om att räkna cykelvolym i olika tätorter har förbättrats över tiden. Dock
har det aldrig varit felfri, vilket har lett till fortsatta studier och ännu mer
utrymme att förbättra de befintliga metoderna. Därför är syftet med rapporten
att ytterligare analysera det som redan har gjorts och hur man kan överträffa
nuvarande förväntningar.

En djupdykning i olika cyklisters beteende gjordes genom att analysera antal
fel som inträffade vid insamling av data, samt orsaken till att dessa
felaktigheter uppstår i första hand. Flera analyser gjordes i hela Lund stad,
med hjälp av kommunen och applikationen TravelVu, både i hjärtat av staden
och även i utkanten.

I hopp om att ta reda på varför dessa extremvärden inträffar i första hand
gjordes en jämförelse genom att göra en litteraturgenomgång på flera
vetenskapliga artiklar. Olika metoder användes av var och en, vissa var mer
lika än andra men de gav var och en tydlig inblick i hur de bedrev sin
forskning.

De flesta problemen är relaterade till kraftigt blandade trafikmiljöer som
uppstår, speciellt under rusningstid. Hindrandet av trafik samt andra faktorer
orsakar dessa brister under datainsamling, men som tidigare nämnt finns det
fortfarande mer att undersöka och förbättra på vad vi redan vet. (Less)
Abstract
The current methods employed by different companies and researchers when
it comes to measuring bike volume at different urban environments have been
improving over time. However, it has never been completely flawless, leading
to future studies and even more room to improve the existing methods. Which
is why, the purpose of this report is to further analyze what has already been
done and how to exceed current expectations.

A deep dive into different cyclists’ behavior was conducted by analyzing the
number of errors that occurred while gathering data, as well as the reason as to
why these inaccuracies arise in the first place. Multiple analyzes were done
throughout the town of Lund, with the help of the municipality and the app
... (More)
The current methods employed by different companies and researchers when
it comes to measuring bike volume at different urban environments have been
improving over time. However, it has never been completely flawless, leading
to future studies and even more room to improve the existing methods. Which
is why, the purpose of this report is to further analyze what has already been
done and how to exceed current expectations.

A deep dive into different cyclists’ behavior was conducted by analyzing the
number of errors that occurred while gathering data, as well as the reason as to
why these inaccuracies arise in the first place. Multiple analyzes were done
throughout the town of Lund, with the help of the municipality and the app
provided by TravelVu, both in the heart of the city and even on the outskirts.
The miscalculation of data across these different urban locations differs from
place to place but there’s also similarities between them.

In hopes of finding out why these outliers happen in the first place a
comparison was made by doing a literature review on multiple scientific
papers. Different methods were employed by each one, some were more
similar than others but they each provided a clear insight into how they
conducted their research.

Most of the problems are related to heavily mixed traffic environments that
occur, especially during peak hours. The obstruction of traffic as well as other
factors cause these deficiencies during data collection, but as previously
mentioned, there’s still more to research and improve on what we already
know. (Less)
Please use this url to cite or link to this publication:
author
Palomino Achulli, Sebastian LU
supervisor
organization
alternative title
Utnyttja potentialen med crowdsourcing av appdata för att mäta stadscykelflöde
course
VTVL01 20232
year
type
M3 - Professional qualifications ( - 4 Years)
subject
keywords
Crowdsourcing app data, GPS, bicycle flow, urban area, bike volume, mass volunteer
language
English
id
9168743
date added to LUP
2024-07-01 12:33:24
date last changed
2024-07-01 12:33:24
@misc{9168743,
  abstract     = {{The current methods employed by different companies and researchers when
it comes to measuring bike volume at different urban environments have been
improving over time. However, it has never been completely flawless, leading
to future studies and even more room to improve the existing methods. Which
is why, the purpose of this report is to further analyze what has already been
done and how to exceed current expectations.

A deep dive into different cyclists’ behavior was conducted by analyzing the
number of errors that occurred while gathering data, as well as the reason as to
why these inaccuracies arise in the first place. Multiple analyzes were done
throughout the town of Lund, with the help of the municipality and the app
provided by TravelVu, both in the heart of the city and even on the outskirts.
The miscalculation of data across these different urban locations differs from
place to place but there’s also similarities between them.

In hopes of finding out why these outliers happen in the first place a
comparison was made by doing a literature review on multiple scientific
papers. Different methods were employed by each one, some were more
similar than others but they each provided a clear insight into how they
conducted their research.

Most of the problems are related to heavily mixed traffic environments that
occur, especially during peak hours. The obstruction of traffic as well as other
factors cause these deficiencies during data collection, but as previously
mentioned, there’s still more to research and improve on what we already
know.}},
  author       = {{Palomino Achulli, Sebastian}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Untapping the potential of crowdsourcing app data to measure urban bicycle flow}},
  year         = {{2024}},
}