Title: Integrating machine learning with ITS for effective traffic management under road development conditions

Authors: Kundan Meshram

Addresses: Department of Civil Engineering, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur-495009, C.G., India

Abstract: Intelligent transportation systems (ITS) have paved their way into modern day traffic management scenarios. These scenarios include but are not limited to diverting traffic, identifying routes, identifying accidents and propagating them over the network, etc. Due to a large number of road-based maintenance, repair and new road building works, there is a disruption in traffic flow. Proper maintenance and effective communication among these traffic nodes is of utmost importance for smooth traffic flow. This paper analyses different techniques for ITS communication that assist in maintaining optimum traffic flow under different road construction scenarios. The proposed algorithm devises a novel ITS workflow for organising traffic under different road development conditions. The machine learning algorithm uses extended drone-based imagery to identify best traffic routes for a given traffic area. The paper also extends the proposed algorithm and adds a machine learning layer to it to further optimise the performance of traffic flow.

Keywords: ITS; intelligent transportation system; machine learning; traffic flow; road works; big data; optimum; communication; vehicle management; drone image processing.

DOI: 10.1504/IJHVS.2023.134705

International Journal of Heavy Vehicle Systems, 2023 Vol.30 No.6, pp.718 - 733

Received: 29 Jun 2022
Accepted: 29 Dec 2022
Published online: 06 Nov 2023 *

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