Article: Automated detection of entry and exit nodes in traffic networks of irregular shape Journal: International Journal of Computational Economics and Econometrics (IJCEE) 2021 Vol.11 No.2 pp.143 - 160 Abstract: We devise an algorithm that can automatically identify entry and exit nodes of an arbitrary traffic network. It is applicable even if the network is of irregular shape, which is the case for many cities. Additionally, the method can calculate the nodes' attractiveness to commuters. This technique is then used to improve a traffic model, so that it is no longer dependent on expert knowledge and manual steps and can thus be used to analyse arbitrary traffic systems. Evaluation of the algorithm is performed twofold: the positions of the identified entry nodes are compared to existing traffic data. A more in-depth analysis uses the traffic model to simulate a city in two ways: once with hand-picked entry nodes and once with automatically detected ones. The evaluation shows that the simulation yields a good match to the real world data, substantiating the claim that the algorithm can fully replace a manual identification process. Inderscience Publishers - linking academia, business and industry through research

Title: Automated detection of entry and exit nodes in traffic networks of irregular shape

Authors: Simon Plakolb; Christian Hofer; Georg Jäger; Manfred Füllsack

Addresses: Institute of Systems Sciences, Innovation and Sustainability Research, University of Graz, Graz, Austria ' Information Technologies and Business Informatics, CAMPUS 02 University of Applied Sciences, Graz, Austria ' Institute of Systems Sciences, Innovation and Sustainability Research, University of Graz, Graz, Austria ' Institute of Systems Sciences, Innovation and Sustainability Research, University of Graz, Graz, Austria

Abstract: We devise an algorithm that can automatically identify entry and exit nodes of an arbitrary traffic network. It is applicable even if the network is of irregular shape, which is the case for many cities. Additionally, the method can calculate the nodes' attractiveness to commuters. This technique is then used to improve a traffic model, so that it is no longer dependent on expert knowledge and manual steps and can thus be used to analyse arbitrary traffic systems. Evaluation of the algorithm is performed twofold: the positions of the identified entry nodes are compared to existing traffic data. A more in-depth analysis uses the traffic model to simulate a city in two ways: once with hand-picked entry nodes and once with automatically detected ones. The evaluation shows that the simulation yields a good match to the real world data, substantiating the claim that the algorithm can fully replace a manual identification process.

Keywords: traffic modelling; network analysis; commuting; automated detection; entry nodes; exit nodes; traffic simulation; mobility behaviour; agent-based model; road usage; congestion.

DOI: 10.1504/IJCEE.2021.114548

International Journal of Computational Economics and Econometrics, 2021 Vol.11 No.2, pp.143 - 160

Received: 11 Feb 2019
Accepted: 24 Jul 2019
Published online: 27 Apr 2021 *

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Title: Automated detection of entry and exit nodes in traffic networks of irregular shape

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