Research on the optimization of urban residents' travel structure based on big data visualization

Abstract

Abstract The travel patterns of urban inhabitants are not optimized and require improvement. By utilizing big data visualization, the optimization of urban residents' travel structure can be efficiently achieved, resulting in the reduction of urban traffic and the promotion of a healthier lifestyle for individuals. Through the utilization of big data visualization, the optimization of urban residents' travel structure can be comprehended by means of a mathematical model and the implementation of effective policies aimed at enhancing human settlement. This can also serve as a significant point of reference for exploring future studies in this field. The focus of this paper is to examine the influence of big data visualization technologies that offer insights into the routes of transportation and the movements of pedestrians, as captured by public cameras situated worldwide. In the course of transportation planning, conventional statistical methodologies and extensive data analysis techniques are employed to optimize the travel patterns of urban residents using a basic programming language such as Python. The research has confirmed the efficiency of big data visualization technologies in ameliorating the transportation framework of city dwellers.