Self Driving Car

Authors- Sudiksha Asati, Assistant Professor Dr Priyanka Dubey

Abstract-AI in driving is introduced as a self-driving in automobile industries. This research paper is p resents a scient metric and bibliometric analysis on self-driving cars. A self-driving car (sometimes called an autonomous car or driverless car) is a vehicle that uses a combination of senso rs, cameras, radar and artificial intelligence (AI) to travel between destinations without a hum an operator. To qualify as fully autonomous, a vehicle must be able to navigate without huma n intervention to a predetermined destination over roads that have not been adapted for its use. Companies developing and/or testing autonomous cars include Audi, BMW, Ford, Google, G eneral Motors, Tesla, Volkswagen and Volvo, Tata Motors and Mahindra. Google\’s test invol ved a fleet of self-driving cars — including Toyota Prii and an Audi TT — navigating over 140,000 miles of California streets and highways. Through an examination of quantitative empiri cal evidence, we explore the importance of Artificial Intelligence (AI) as machine learning, de ep learning and data mining on self-driving car research and development as measured by pat ents and papers. Alongside the exponential growth in the rate of inventive activities and schol arly efforts, we find evidence for a rapid and meaningful shift in the application of the technol ogies related to data gathering and processing for the purpose of self-driving cars after 2009. We show that this shift mirrors major changes in the landscape of innovators as well as increa sing scholarly attention to the ethical, legal and social aspects of self-driving cars.

DOI: /10.61463/ijset.vol.12.issue2.138