University of Oulu

A. Keskinarkaus et al., "Revealing reliable information from taxi traces: from raw data to information discovery," 2022 IEEE 38th International Conference on Data Engineering Workshops (ICDEW), 2022, pp. 46-53, doi: 10.1109/ICDEW55742.2022.00011.

Revealing reliable information from taxi traces : from raw data to information discovery

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Author: Keskinarkaus, Anja1; Gilman, Ekaterina2; Loven, Lauri2;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
2Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
3Biomimetics and Intelligent Systems Group, University of Oulu, Oulu, Finland
4Meteorological Institute, Helsinki, Finland
5Cloud Computing Center, Chinese Academy of Sciences, Dongguan, China
6Institute of Automation, Chinese Academy of Sciences, Beijing, China
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2022-12-16


In this paper we present procedures for processing raw data collected with moving vehicles and for fusing this data with digital map data. The goal is to have a better understanding of the city traffic via quantitative research on collected taxi data in relation to digital map properties. Map attributes are provided by Digiroad, which is a database of Finnish road and street network. We define methods to clean up data that has been collected with taxis equipped with on-board vehicle tracking devices from real customer service situations. Consequently, the driving behavior may be inconsistent and sensor data can be limited and contain errors. We explain procedures of preparing data; filtering the most obvious errors from the data set, map-matching moving object data, and fetching map attributes along the routes of the moving vehicles. The fetched properties, as well as other measurement data, are used for deriving statistics and illustrations to study driving behavior in downtown Oulu, Finland.

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Series: IEEE International Conference on Data Engineering workshop
ISSN: 1943-2895
ISSN-E: 2473-3490
ISSN-L: 1943-2895
ISBN: 978-1-6654-8104-5
ISBN Print: 978-1-6654-8105-2
Pages: 46 - 53
DOI: 10.1109/icdew55742.2022.00011
Host publication: 2022 IEEE 38th international conference on data engineering workshops (ICDEW)
Conference: IEEE International Conference on Data Engineering Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
113 Computer and information sciences
Funding: This research work has been financially supported by Academy of Finland UrBOT project (323630), by Academy of Finland 6Genesis Flagship (318927), NSFC (Natural Science Foundation of China) projects (71232006, 61233001, 61174172), and Chinese Dongguan’s Innovation Talents Project (Gang Xiong)
Academy of Finland Grant Number: 323630
Detailed Information: 323630 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
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