Mining topological dependencies of recurrent congestion in road networks
- authored by
- Nicolas Tempelmeier, Udo Feuerhake, Oskar Wage, Elena Demidova
- Abstract
The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the scheduling of public transportation services. While most existing studies investigate temporal patterns of RC phenomena, the influence of the road network topology on RC is often over-looked. This article proposes the ST-DISCOVERY algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data. We factor out regularly reoccurring traffic phenomena, such as rush hours, mainly induced by the daytime, by modelling and systematically exploiting temporal traffic load outliers. We present an algorithm that first constructs connected subgraphs of the road network based on the traffic speed outliers. Second, the algorithm identifies pairs of subgraphs that indicate spatio-temporal correlations in their traffic load behaviour to identify topological dependencies within the road network. Finally, we rank the identified subgraph pairs based on the dependency score determined by our algorithm. Our experimental results demonstrate that ST-DISCOVERY can effectively reveal topological dependencies in urban road networks.
- Organisation(s)
-
L3S Research Centre
Institute of Cartography and Geoinformatics
- External Organisation(s)
-
University of Bonn
- Type
- Article
- Journal
- ISPRS International Journal of Geo-Information
- Volume
- 10
- ISSN
- 2220-9964
- Publication date
- 08.04.2021
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Geography, Planning and Development, Computers in Earth Sciences, Earth and Planetary Sciences (miscellaneous)
- Sustainable Development Goals
- SDG 9 - Industry, Innovation, and Infrastructure, SDG 11 - Sustainable Cities and Communities
- Electronic version(s)
-
https://doi.org/10.3390/ijgi10040248 (Access:
Open)
