Issue |
SHS Web Conf.
Volume 144, 2022
2022 International Conference on Science and Technology Ethics and Human Future (STEHF 2022)
|
|
---|---|---|
Article Number | 03001 | |
Number of page(s) | 4 | |
Section | Application of Artificial Intelligence Technology and Machine Learning Algorithms | |
DOI | https://doi.org/10.1051/shsconf/202214403001 | |
Published online | 26 August 2022 |
The Application of Artificial Intelligence in the Field of Transportation
1
Beijing Technology and Business University
2
Beijing Technology and Business University
* Corresponding author. Email: mmss360@sina.com
Urban traffic is the lifeblood of urban economic activities and plays a very important role in the development of the urban economy and the improvement of people’s living standards. Although the automobile industry brings convenience, it also brings a heavy burden to urban traffic. The imbalance of urban traffic supply and demand has become a serious problem faced by major cities, especially in large cities, the phenomenon of traffic congestion. This not only affects the normal operation of the city, but also reduces the daily work efficiency of people. This paper is based on mature scientific principles and physical devices, such as dynamic Bayesian network, machine vision, machine learning, pattern recognition technology, temperature sensor, optical fiber sensor, etc. The application of artificial intelligence technology in highway traffic is discussed in detail, which lays a theoretical foundation for the development of intelligent traffic in the future.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.