Designing Data Visualization Using Artificial Intelligence for Urban Intelligent Transportation Scenarios

Abstract

Artificial intelligence refers to a simulation extension and expansion technology that has found its presence in various applications and research domains. Artificial intelligence allows the related theories to portray similar to human intelligence. It combines developments in several fields, including computer science, statistics, and linguistics. The research objects of data visualization can be divided into three aspects: data, visualization technology, and visualization performance. This paper aims to study the data visualization design of artificial intelligence in urban intelligent transportation scenarios. It predicts the traffic flow via the traffic control method using neural network. It provides an effective way for timely dredging and alleviating problems, such as traffic jams and establishing alternative routes. This paper firstly analyzes the methods of artificial intelligence, traffic control methods, and data visualization and then designs the visualization based on artificial intelligence in traffic scenarios. By comparing the accuracy analysis of different models, the experimental results show that the error of the peak traffic flow is less than 10% and the lowest error value is 2.2%.