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Title	Safety And Security In Autonomous Traffic Systems Management With Ai: Economic Implications Of Traffic Optimization In Smart Cities
ID_Doc	47215
Authors	Jain A.
Year	2025
Published	Machine Learning and Robotics in Urban Planning and Management
DOI	http://dx.doi.org/10.4018/979-8-3693-9410-6.ch008
Abstract	Safety and security are critical pillars in managing autonomous traffic systems with AI, particularly in the context of smart cities. These systems integrate advanced technologies such as IoT, V2X communication, and machine learning to enhance traffic flow, reduce accidents, and optimize urban mobility. However, ensuring the reliability of these systems demands robust safety protocols to address challenges like mixed-traffic scenarios and unexpected system failures. Concurrently, cybersecurity measures are vital to counter threats such as hacking and data breaches that could compromise vehicle and infrastructure integrity. Economically the AI-driven traffic optimization reduces congestion, cuts fuel consumption, and improves productivity by minimizing travel delays. The shift to autonomous traffic systems fosters urban sustainability by decreasing emissions and promoting energy efficiency. While challenges remain in terms of public trust and regulatory frameworks, the economic and environmental benefits position these systems as transformative solutions for the future of urban mobility. © 2025, IGI Global Scientific Publishing. All rights reserved.
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