AI-Driven Digital Twins for Sustainable Urban Mobility: Integrating Generative Models for Traffic Optimization

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Framework integrates ai and generative models to optimize traffic in metropolitan cities, suggesting improved public services.

Integrating ai with digital twins improves urban traffic management and reduces emissions and resource consumption.
The system uses generative models to predict traffic flow, assisting in developing optimal routes and enhancing flexibility.
Assessment of policies through digital twins allows cities to dynamically evaluate and plan for future transportation needs.
This approach supports sustainable urban development by facilitating efficient public service management and reducing environmental impact.

Jishor et al. (2025) studied this question.

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