Abstract
In recent years, various kinds of applications of artificial intelligence technology to the automatic driving vehicle were widely reported by the media, also aroused public interest. According to a survey by the Ministry of Public Security, there are more than 500 million motor vehicles in China in 2021 and more than 200 thousand traffic accidents occurred in 2021, which is a great challenge to traffic safety protection. Human reaction time, which consists of perception time and judgment time, is too long to take measures. Besides, human drivers may find it difficult to even make the right response in some complex road conditions. To improve this situation, the Intelligent Transportation System (ITS) may transform the traditional passive safety that takes protective measures after accidents into active safety that focuses on prevention. Deep learning network receives information through the vehicle-loaded sensor then makes judgments by its computing unit and prompts drivers the possible danger. This article reviewed the performance of different deep learning models in autonomous driving vehicles.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
