Enhancing Transportation Systems with Intelligent Mobility Solutions
Abstract
This paper explores the enhancement of transportation systems through intelligent mobility solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional transportation practices, including traffic management, vehicle automation, and urban mobility. The study highlights the application of AI techniques such as machine learning algorithms, traffic prediction models, and autonomous vehicle technology in improving safety, efficiency, and sustainability in transportation networks. Additionally, it discusses the integration of AI with smart transportation infrastructure, ride-sharing platforms, and electric mobility solutions to enable seamless connectivity, multimodal travel, and sustainable mobility options. The paper also addresses challenges such as data privacy, regulatory framework, and societal acceptance in the adoption of AI-driven engineering solutions in transportation. It emphasizes the importance of stakeholder engagement, policy support, and public trust in leveraging AI's potential to enhance transportation systems and create more inclusive and accessible mobility for all.
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References
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