Article: Intelligent scheduling and optimisation system: a big data-cloud framework for adaptive urban traffic management Journal: International Journal of Systems, Control and Communications (IJSCC) 2026 Vol.17 No.7 pp.21 - 42 Abstract: This paper proposes an intelligent scheduling and optimisation system (ISOS) to facilitate the traffic flow, reduce congestion, and safety. The suggested system will integrate the technology of big data analytics and cloud computing to process the vast amount of traffic-related data that sensors, cameras, GPS devices retrieve. The genetic algorithm (GA) is the optimisation tool employed in the optimisation of the traffic light and the controls the traffic dynamically based on the parameters of the various performance measures, such as travel time, length of queues, and fuel consumption. The system enables storage of the data, parallel processing and the rapid calculation at the scale with the assistance of the cloud infrastructure, thus, enabling the real-time decision-making in the numerous traffic networks. It is demonstrated based on the simulation results that the offered framework would significantly increase the efficiency of traffic, minimise delays, and optimise signal timing under various traffic scenarios. Inderscience Publishers - linking academia, business and industry through research

Title: Intelligent scheduling and optimisation system: a big data-cloud framework for adaptive urban traffic management

Authors: Wenran Zhou

Addresses: School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100080, China

Abstract: This paper proposes an intelligent scheduling and optimisation system (ISOS) to facilitate the traffic flow, reduce congestion, and safety. The suggested system will integrate the technology of big data analytics and cloud computing to process the vast amount of traffic-related data that sensors, cameras, GPS devices retrieve. The genetic algorithm (GA) is the optimisation tool employed in the optimisation of the traffic light and the controls the traffic dynamically based on the parameters of the various performance measures, such as travel time, length of queues, and fuel consumption. The system enables storage of the data, parallel processing and the rapid calculation at the scale with the assistance of the cloud infrastructure, thus, enabling the real-time decision-making in the numerous traffic networks. It is demonstrated based on the simulation results that the offered framework would significantly increase the efficiency of traffic, minimise delays, and optimise signal timing under various traffic scenarios.

Keywords: urban traffic control; big data analytics; transportation; information and computing sciences.

DOI: 10.1504/IJSCC.2026.155797

International Journal of Systems, Control and Communications, 2026 Vol.17 No.7, pp.21 - 42

Received: 09 Oct 2025
Accepted: 25 Dec 2025
Published online: 14 Aug 2026 *

Title: Intelligent scheduling and optimisation system: a big data-cloud framework for adaptive urban traffic management

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