International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Urban mobility is a major concern for large metropolitan areas. Cloud-enabled Artificial Intelligence (AI) technology may help to manage travel demand and offer a more sustainable urban mobility model for smart cities. An AI-driven, cloud-enabled architectural framework applied to traffic management and control business processes is proposed. It integrates four AI-based predictive models with real-time traffic control and incident-response systems. Different data-driven use cases, proved in two metropolitan areas, illustrate the applicability of this framework in real operational environments. Results show that this approach is capable of managing urban traffic in real time. In addition, it demonstrates how AI-based models can be developed, deployed, and operated within cloud environments, offering a decision-support capability.
The central role of predictive traffic management systems in the cloud-enabled AI model for smart cities is assessed. Demand management processes and the integration of Mobility-as-a-Service platforms are also analyzed. These are mandatory steps to offer a sustainable traffic model for large metropolitan areas. Finally, other aspects such as environmental protection and energy consumption in urban mobility are examined. Traffic management by predictive systems enables a more accurate confrontation of real traffic conditions, improving the energy, environmental, and resilience contexts.

Keywords: Smart City Traffic Management, Cloud-Enabled Artificial Intelligence, AI-Driven Urban Mobility, Predictive Traffic Management Systems, Real-Time Traffic Control, Intelligent Incident Response, Urban Demand Management, Mobility-as-a-Service (MaaS), Cloud-Based Decision Support Systems, Data-Driven Traffic Optimization, Sustainable Urban Mobility Models, Metropolitan Traffic Analytics, AI Deployment in Cloud Environments, Traffic Prediction Models, Smart Transportation Architectures, Energy-Efficient Urban Mobility, Environmental Impact Reduction, Resilient Transportation Systems, Integrated Traffic Control Frameworks, AI-Enabled Smart Cities.

Downloads: | DOI: 10.17148/IJARCCE.2023.121233