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Title	Machine Learning For Safer Autonomous Vehicles: Tackling Traffic Detection And Collision In Smart Cities
ID_Doc	35975
Authors	Singh B.; Kaunert C.; Chandra S.
Year	2025
Published	Achieving Sustainability in Multi-Industry Settings With AI
DOI	http://dx.doi.org/10.4018/979-8-3373-2530-9.ch008
Abstract	Machine learning is enhancing the transportation system and the robotic process automation and artificial intelligence are used in autos to provide intelligent automation (IA), which allows autonomous vehicles to undergo digital transformation. Smart automation has the power to completely replace human interaction, guaranteeing enhanced safety and intelligent vehicle movement. With a comparative study, this article analyzes current approaches that use IoT, AI, and machine learning in autonomous cars. It is critical to comprehend risk-reduction technology as the sector transitions from manual to automated processes. The study outlines the theoretical drawbacks and advantages of autonomous technology, highlighting artificial intel-ligence’s crucial role in vehicle management going forward. It makes recommendations for future lines of inquiry to further the advancement of autonomous car technology. This chapter focuses on the requirements for safety and the difficulties associated with autonomous cars, specifically with regard to object detection, cybersecurity and V2X privacy. © 2025 by IGI Global Scientific Publishing. All rights reserved.
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