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Path inference of low-frequency GPS probes for urban networks
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.ORCID iD: 0000-0001-8750-8242
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
2012 (English)In: Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on, IEEE , 2012, 1698-1701 p.Conference paper, Published paper (Refereed)
Abstract [en]

The use of probe vehicles in traffic management is growing rapidly. The reason is that the required data collection infrastructure is increasingly in place in urban areas with significant number of mobile sensors moving around covering expansive areas of the road network. The data is usually sparse in time and location. It usually includes only geo-location and timestamp. Extracting the paths taken by the vehicles is an important step in using this data. Such methods are referred to as map-matching or path inference. This paper introduces a path inference method for low-frequency probes and evaluates its accuracy in comparison to a recent method.

Place, publisher, year, edition, pages
IEEE , 2012. 1698-1701 p.
Series
IEEE International Conference on Intelligent Transportation Systems-ITSC, ISSN 2153-0009
Keyword [en]
Data collection, Geolocations, Inference methods, Map matching, Mobile sensors, Probe vehicles, Road network, Time-stamp, Traffic management, Urban areas, Urban networks
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-116026DOI: 10.1109/ITSC.2012.6338667ISI: 000312599600281Scopus ID: 2-s2.0-84871211805ISBN: 978-146733064-0 (print)OAI: oai:DiVA.org:kth-116026DiVA: diva2:588608
Conference
2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012; Anchorage, AK; 16 September 2012 through 19 September 2012
Note

 QC 20130116

Available from: 2013-01-15 Created: 2013-01-15 Last updated: 2013-09-06Bibliographically approved
In thesis
1. Path Inference of Sparse GPS Probes for Urban Networks: Methods and Applications
Open this publication in new window or tab >>Path Inference of Sparse GPS Probes for Urban Networks: Methods and Applications
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The application of GPS probes in traffic management is growing rapidly as the required data collection infrastructure is increasingly in place in urban areas with significant number of mobile sensors moving around covering expansive areas of the road network. Most travelers carry with them at least one device with a built-in GPS receiver. Furthermore, vehicles are becoming more and more location aware. Currently, systems that collect floating car data are designed to transmit the data in a limited form and relatively infrequently due to the cost of data transmission. That means the reported locations of vehicles are far apart in time and space. In order to extract traffic information from the data, it first needs to be matched to the underlying digital road network. Matching such sparse data to the network, especially in dense urban, area is challenging.

This thesis introduces a map-matching and path inference algorithm for sparse GPS probes in urban networks. The method is utilized in a case study in Stockholm and showed robustness and high accuracy compared to a number of other methods in the literature. The method is used to process floating car data from 1500 taxis in Stockholm City. The taxi data had been ignored because of its low frequency and minimal information. The proposed method showed that the data can be processed and transformed into information that is suitable for traffic studies.

The thesis implemented the main components of an experimental ITS laboratory, called iMobility Lab. It is designed to explore GPS and other emerging traffic and traffic-related data for traffic monitoring and control.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xi, 53 p.
Series
Trita-TSC-LIC, ISSN 1653-445X ; 12:010
Keyword
map-matching, path inference, sparse GPS probes, FCD, urban area, digital road network, Stockholm, taxi, iMobility Lab, MapViz, travel time
National Category
Transport Systems and Logistics
Research subject
SRA - Transport
Identifiers
urn:nbn:se:kth:diva-104524 (URN)978-91-85539-98-7 (ISBN)
Presentation
2012-11-26, V2, Teknikringen 76, KTH, Stockholm, 14:30 (English)
Opponent
Supervisors
Funder
TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20121107

Available from: 2012-11-07 Created: 2012-11-05 Last updated: 2013-09-06Bibliographically approved

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Rahmani, Mahmood

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  • apa
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Output format
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