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Enhancing Transportation with Intelligent Solutions
Abstract
This paper explores the enhancement of transportation through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing transportation systems, including autonomous vehicles, traffic management, and logistics optimization. The study highlights the application of AI techniques such as predictive analytics, reinforcement learning, and computer vision in improving safety, efficiency, and sustainability in transportation networks. Additionally, it discusses the integration of AI with smart cities, connected vehicles, and urban mobility platforms to enable seamless mobility, reduce congestion, and mitigate environmental impact. The paper also addresses challenges such as regulatory frameworks, ethical considerations, and public acceptance in the adoption of AI-driven engineering solutions in transportation. It emphasizes the importance of interdisciplinary collaboration, policy innovation, and public engagement in harnessing AI's potential to transform the future of transportation.
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