Automated detection of entry and exit nodes in traffic networks of irregular shape Online publication date: Tue, 27-Apr-2021
by Simon Plakolb; Christian Hofer; Georg Jäger; Manfred Füllsack
International Journal of Computational Economics and Econometrics (IJCEE), Vol. 11, No. 2, 2021
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Economics and Econometrics (IJCEE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook