Change search
ReferencesLink to record
Permanent link

Direct link
Scalable Detection of Traffic Congestion from Massive Floating Car Data Streams
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.ORCID iD: 0000-0003-1164-8403
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.ORCID iD: 0000-0001-5361-6034
2015 (English)Conference paper (Refereed)
Abstract [en]

Motivated by the high utility and growing availability of Floating Car Data (FCD) streams for traffic congestion modeling and subsequent traffic congestion-related intelligent traffic management tasks, this paper proposes a grid-based, time-inhomogeneous model and method for the detection of congestion from large FCD streams. Furthermore, the paper proposes a simple but effective, high-level implementation of the method using off-the-shelf relational database technology that can readily be ported to Big Data processing frameworks. Empirical evaluations on millions of real-world taxi trajectories show that 1) the spatio-temporal distribution and clustering of the detected congestions are reasonable and 2) the method and its prototype implementation scale linearly with the input size and the geographical level of detail / spatio-temporal resolution of the model.

Place, publisher, year, edition, pages
ACM Press, 2015.
Keyword [en]
Congestion Detection, FCD, Trajectory Data Mining, Intelligent Transport Systems
National Category
Computer Science Information Systems
Research subject
Computer Science; Transport Science; Geodesy and Geoinformatics
Identifiers
URN: urn:nbn:se:kth:diva-184250ISBN: 978-1-4503-3973-5/15/11OAI: oai:DiVA.org:kth-184250DiVA: diva2:916036
Conference
The First International Workshop on Smart Cities and Urban Analytics (UrbanGIS) 2015, Bellevue, WA, USA, NOVEMBER 3, 2015
Note

QC 20160407

Available from: 2016-03-31 Created: 2016-03-31 Last updated: 2016-04-07

Open Access in DiVA

No full text

Other links

http://engineering.nyu.edu/urbangis2015/

Search in DiVA

By author/editor
Gidofalvi, GyözöYang, Can
By organisation
Geoinformatics
Computer ScienceInformation Systems

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 7 hits
ReferencesLink to record
Permanent link

Direct link