AI for Transportation refers to the application of artificial intelligence techniques to improve the efficiency, safety, and reliability of transportation systems. It includes methods such as machine learning, computer vision, and optimization to support tasks like traffic prediction, route planning, autonomous driving, and infrastructure monitoring. These systems analyze large-scale data from vehicles, sensors, and networks to enable real-time decision making and enhance mobility across urban and regional environments.

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Driving the Future of Scene Editing with HorizonForge

HorizonForge introduces a new approach to driving scene generation, enabling precise control over both vehicle behavior and identity. By allowing arbitrary trajectories and flexible vehicle insertion, it creates realistic, scalable simulations for autonomous driving, digital twins, and advanced AI development.