Estimating parameters of demand for trips by public bicycle system using GPS data
Authors:
- Vitalii Naumov,
- Krystian Banet
Abstract
Bicycles become one of the main modes of public transport in modern cities. In many cases, they replace private cars and even public buses, especially in the cities with the developed bicycle infrastructure. However, designing and developing public transport systems should be implemented on the grounds of known parameters of demand for travels. The paper describes an approach to the travel demand estimation with the use of data obtained from GPS trackers. The article mainly focuses on data cleaning procedures and the estimations of the demand parameters on the base of the obtained dataset. The authors propose the software for reading raw records from GPX-files and cleaning the data. The case study of the bicycle share system in Kraków, Poland, is discussed in the paper: the results of the data cleansing and estimating demand parameters for recreational trips allocated from the obtained sample are shown.
- Record ID
- CUTcda47198ff56431abd984ab48ee3a849
- Publication categories
- ; ;
- Author
- Pages
- 213-224
- Other elements of collation
- tab.; wykr.; Bibliografia (na s.) - 223-224; Oznaczenie streszczenia - Abstr.
- Book
- Sierpiński Grzegorz Grzegorz Sierpiński (eds.): Smart and Green Solutions for Transport Systems : 16th Scientific and Technical Conference "Transport Systems. Theory and Practice 2019" : selected papers, Advances in Intelligent Systems and Computing, no. 1091, 2020, Cham, Springer, Springer, ISBN 978-3-030-35543-2 (online)
- Keywords in English
- public bicycle system, demand parameters, data cleansing, recreational trips
- DOI
- DOI:10.1007/978-3-030-35543-2_17 Opening in a new tab
- URL
- https://link.springer.com/chapter/10.1007/978-3-030-35543-2_17 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 20
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTcda47198ff56431abd984ab48ee3a849/
- URN
urn:pkr-prod:CUTcda47198ff56431abd984ab48ee3a849
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.