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ITS Deployment Evaluation Executive Briefing: Artificial Intelligence and Machine Learning for Transportation

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  • Abstract:
    Artificial Intelligence (AI) is revolutionizing every walk of life, allowing machines to learn from experience, adapt, and perform tasks that have historically required human cognition. Factors that have led to increased attention to AI in the last decade include increased computing power, mass data collection and storage, and innovations in AI algorithms, including Machine Learning (ML), a sub-field of AI that uses data to improve performance with experience [1]. In October 2016, the National Science and Technology Council published The National Artificial Intelligence Research and Development Strategic Plan, which outlines how federal agencies should prioritize federally funded research and development (R&D) in AI [2]. In February 2019, the White House issued Executive Order 13859, Maintaining American Leadership in Artificial Intelligence, which outlines federal government principles and objectives and prioritized AI as a key R&D area in the federal government [3]. The U.S. Department of Transportation (USDOT) Intelligent Transportation Systems (ITS) Joint Program Office (JPO) Strategic Plan 2020-2025 mentions that ML and AI “have the potential to transform ITS at every level of implementation” [4]. In 2020, the ITS JPO kicked off the AI for ITS Program with the mission of identifying, developing, implementing, evaluating, and coordinating technology and policy research to advance the integration of AI into the transportation system for safer, more efficient, and accessible movement of people and goods. The goal of the program is to cost effectively build and deploy AI for ITS capabilities in real-world modal use [5].
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    urn:sha-512:f4272b5a2fc9e039d242ef485ed4d511099787800552b5edccfc56cbdd5e6716d6cdb1b749485a2933e8aea3cba4dbf1b2ff913326a4fa1f54b4d826db52c98e
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File Language:
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