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http://dx.doi.org/10.12812/ksms.2019.22.1.009

A Review of AI-based Automobile Accident Prevention Systems  

Choi, Jae Gyeong (School of Management Engineering, Ulsan National Institute of Science and Technology)
Kong, Chan Woo (School of Management Engineering, Ulsan National Institute of Science and Technology)
Lim, Sunghoon (School of Management Engineering, Ulsan National Institute of Science and Technology)
Publication Information
Journal of the Korea Safety Management & Science / v.22, no.1, 2020 , pp. 9-14 More about this Journal
Abstract
Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.
Keywords
Automobile Accident Prevention System; Artificial Intelligence; Machine Learning; Deep Learning; e-Call Service;
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