Risk Management in the Construction of Intelligent Transportation Platform Based on Artificial Intelligence

Main Article Content

Hongxi Di

Abstract

The smoothness of a city's traffic is one of the signs that measure the development of a city. With the advent of the era of artificial intelligence and big data, the previously bloated and blocked motor vehicle transportation system is increasingly unable to adapt to this fast-paced society. The use of artificial intelligence technology to build a brand-new intelligent transportation platform is imminent, and reasonable planning of the risks in the construction of the transportation platform can effectively increase the transmission rate and reduce the frequency of accidents. The purpose of this paper is to study the risk management in the construction of intelligent transportation platform based on artificial intelligence. This article first summarizes the basic theory of artificial intelligence, and then extends the core technology of artificial intelligence. And combined with the current situation of my country's contemporary intelligent transportation, analysis of the existing problems and shortcomings, on this basis, combined with artificial intelligence technology to research and analyze the risk management in the construction of intelligent transportation platform. This research systematically expounds the risk construction principles, model construction and risk response measures of the intelligent transportation platform. This paper uses field surveys, interviews and other research methods to research and investigate traffic risk management in a certain place. The experimental research shows that risk management in the construction of intelligent transportation platforms based on artificial intelligence has higher feasibility than traditional traffic management.

Article Details

How to Cite
Di, H. (2021). Risk Management in the Construction of Intelligent Transportation Platform Based on Artificial Intelligence. CONVERTER, 543 - 549. https://doi.org/10.17762/converter.206
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Articles