International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 06 | Jun 2024
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FUTURE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN AUTOMOTIVE INDUSTRY: A REVIEW Anand Gautam1, Dipti Ranjan Tiwari2 1Master of Technology, Computer Science and Engineering, Lucknow Institute of Technology, Lucknow, India 2Assistant Professor, Department of Computer Science and Engineering, Lucknow Institute of Technology,
Lucknow, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - In recent years, the automotive sector has
meantime, ML algorithms empowered autonomous vehicles to glean insights from vast amounts of data, refining their decision-making capabilities and navigating intricate surroundings. Companies such as Tesla, Google (Waymo), and traditional automakers made significant investments in AI and ML research, pushing the boundaries of what was achievable on the road. Presently, AI and ML are fundamental components of contemporary vehicles, propelling advancements in safety, efficiency, and the overall driving experience. As the automotive industry continues to adopt these technologies, the future holds the promise of even more exhilarating progress, with fully autonomous vehicles poised to redefine our perception of transportation.
experienced a significant shift, driven by the rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies. These progressions are not only altering traditional manufacturing methods but also revolutionizing the operation, maintenance, and overall experience of vehicles. One of the most notable applications of AI and ML in the automotive industry is the creation of autonomous driving systems. These systems utilize intricate algorithms and sensor technologies to perceive the environment, make instantaneous decisions, and navigate autonomously without human intervention. Additionally, AI and ML are fostering advancements in predictive maintenance, allowing vehicles to predict and address mechanical issues before they worsen, thereby increasing reliability and minimizing downtime. Furthermore, AI-driven safety features, such as collision avoidance systems and driver assistance programs, are becoming standard across vehicle models, enhancing human capabilities and reducing the likelihood of accidents. Moreover, AI-powered personalization is reshaping the in-car experience, with intelligent assistants, voice recognition, and adaptive entertainment systems tailoring interactions to individual preferences. As the automotive industry rapidly adopts AI and ML technologies, it is on the brink of a profound transformation, ushering in an era of safer, more efficient, and personalized transportation.
2.AUTOMATIVE INDUSTRY The automotive sector boasts a rich and dynamic history characterized by technological advancements, evolving consumer preferences, and fluctuations in the global economy. Originating in the late 19th century, visionaries such as Karl Benz and Henry Ford laid the groundwork for what would emerge as a fundamental element of contemporary society: the automobile. Over the years, the industry underwent rapid transformation, with innovations like assembly line manufacturing, mass-produced vehicles, and safety enhancements becoming standard practice. From the post-war economic upsurge to the oil crises of the 1970s and the globalization of production, the automotive field has confronted numerous obstacles while consistently pushing the boundaries of engineering and design. In recent times, the sector has encountered new disruptions such as the emergence of electric vehicles (EVs), autonomous driving technology, and the emphasis on sustainability. Pioneering companies like Tesla have reshaped conventional notions of automotive capabilities, while conventional automakers have raced to adjust to evolving consumer preferences and regulatory demands. The automotive industry finds itself at a critical juncture, striving to strike a balance between honoring its historical legacy and the necessity to innovate for a sustainable and interconnected future. With the increasing prevalence of electric and autonomous vehicles, the industry's landscape is undergoing significant metamorphosis, not only influencing our modes of transportation but also shaping broader societal and environmental ramifications of mobility.
Key Words: Artificial intelligence, machine learning, automotive industry, autonomous driving, predictive maintenance, vehicle safety, personalized user experiences, deep learning
1.HISTORY The history of artificial intelligence (AI) and machine learning (ML) in the automotive industry is a narrative of technological progression intertwined with the pursuit of safer, more effective transportation solutions. The roots of AI in automobiles were planted in the mid-20th century, with initial advancements like cruise control and anti-lock braking systems. However, it was not until the late 20th and early 21st centuries that AI and ML truly began to transform the automotive sector. Innovations in computer vision facilitated the creation of advanced driver-assistance systems (ADAS), capable of detecting pedestrians, identifying traffic signs, and even aiding in parking. In the
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