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Travelled distance estimation for GPS-based round trips : car-sharing use case (CROSBI ID 647902)

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Lopez Aguirre, Angel Javier ; Semanjski, Ivana ; Gillis, Dominique ; Ochoa Donoso, Daniel ; Gautama, Sidharta Travelled distance estimation for GPS-based round trips : car-sharing use case // Fifth International Conference on Data Analytics / Bhulai, Sandjai ; Semanjski, Ivana (ur.). Wilmington (DE): The International Academy, Research and Industry Association (IARIA), 2016

Podaci o odgovornosti

Lopez Aguirre, Angel Javier ; Semanjski, Ivana ; Gillis, Dominique ; Ochoa Donoso, Daniel ; Gautama, Sidharta

engleski

Travelled distance estimation for GPS-based round trips : car-sharing use case

Traditional travel survey methods have been widely used for collecting information about urban mobility although, since middle of the 90’s Global Position System (GPS) has become an automatic option for collecting more precise data of the households. But how good is the collected data? many studies on mobility patterns have focused on the GPS advantages and leaving aside its issues. However, when it comes to extract the frequency of the trips and travelled distance this technology faces some gaps due to related issues, such as signal reception and time-to-first-fix location that turns out in missing observations and respectively unrecognised or over-segmented trips. In this study, we focus on two aspects of GPS data for a car-mode, (i) measurement of the gaps in the travelled distance and (ii) estimation of the travelled distance and the factors that influence the GPS gaps. To asses that, GPS tracks are compared to a ground truth source. Additionally, the trips are analysed based on the land use (e.g., urban and rural areas) and length (e.g., short, middle and long trips). Results from 170 participants and more than a year of GPS-tracking show that around 9% of the travelled distance is not captured by the GPS and it affects more to short trips than long ones. Moreover, we validate the importance of the time spent on the user activity and the land use as factors that influence the gaps on GPS.

Data quality ; travelled distance ; CAN-BUS data ; GPS data

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Podaci o prilogu

2016.

objavljeno

Podaci o matičnoj publikaciji

Fifth International Conference on Data Analytics

Bhulai, Sandjai ; Semanjski, Ivana

Wilmington (DE): The International Academy, Research and Industry Association (IARIA)

978-1-61208-510-4

Podaci o skupu

Data Analytics

poster

01.01.2016-01.01.2016

Venecija, Italija

Povezanost rada

Tehnologija prometa i transport