Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI: 10.5937/jaes0-28642 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 20 article 988 pages: 821-830

Etinosa Noma-Osaghae*
Department of Electrical and Information Engineering, Covenant University, Ota, Ogun State, Nigeria

Kennedy Okokpujie
Department of Electrical and Information Engineering, Covenant University, Ota, Ogun State, Nigeria

Famoroti Daniel
Department of Electrical and Information Engineering, Covenant University, Ota, Ogun State, Nigeria

Samuel N. John
Department of Electrical and Electronic Engineering, Nigerian Defence Academy, Kaduna, Nigeria

Intelligent transport systems are cheaper and easier to implement than other forms of solutions to road traffic congestion. Intelligent Transport Systems (ITS) allow information about road traffic to be collected and transmitted to the Traffic Controllers to respond to traffic congestion appropriately. This research study aims to design and test a simulation-based intelligent transport system for predicting traffic flow patterns. The simulation-based system proposed has a decentralised configuration. Road sections are isolated digitally in a decentralised structure and fed relevant information to predict future traffic states and transmit predicted information to other road sections. Two models of control configuration are created based on the same road network, the first is a decentralised model, and the second is a centralised model (no isolated road sections) to be used as a data source for the decentralised model. The simulated system used decentralised model configurations to predict traffic patterns at road intersections. Due to the lack of actual traffic data, a centralised model serves as the digital twin for the designed decentralised model. The two models were simulated using Anylogic Personal Learning Edition 8.5.2. simulation software, and after testing and result extraction, it was discovered that the decentralised model configuration was not valid for representing the non-uniformity of actual-world traffic patterns. The decentralised model had too few similar inflow and outflow rates to the centralised model in both the complex and straightforward road network cases. However, the decentralised model scored 89% in vehicle population density compared to the centralised model in the simple road network case but could not replicate the good result when the road network becomes complex.

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The authors acknowledge the sponsorship of the Covenant University Centre for Research, Innovation and Discovery (CUCRID), Ota, Ogun State, Nigeria.

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