Urban congestion area diagnosis method and system and storage medium

Abstract

The invention relates to the field of urban planning and traffic, in particular to an urban congestion area diagnosis method, the following scheme is put forward, the method comprises the steps: inputting road condition data, mobile phone positioning data and basic space data of a city into a geographic information platform in real time, and unifying coordinates and elevations of all the data in real time; constructing a congested road section database and a crowd database of the congested road section, and hooking the congested road section database and the crowd database; extracting personal positioning data of all people in the crowd database from the mobile phone positioning data, and sequentially connecting the personal positioning data of different time periods according to a time sequence to form personal behavior track data; and classifying crowds in a crowd database according to the behavior track data of the individuals, and sorting classification results to distinguish crowds causing congestion. According to the invention, accurate and intelligent diagnosis of the congestion section is realized, and the purposes of reducing traffic congestion and optimizing transportation are achieved.

Description

technical field [0001] The invention relates to the field of urban planning and transportation, in particular to a diagnosis method, system and storage medium for urban congestion areas. Background technique [0002] With the rapid development of my country's economy and the continuous growth of urban motor vehicle ownership, urban traffic congestion has become more and more serious, and has caused negative problems such as the decline in the quality of residents' daily travel, energy waste, environmental pollution, and economic losses. In addition, due to the propagation effect of traffic congestion, if the source of urban congestion is not effectively controlled, it will cause congestion in nearby road sections, which in turn will affect the regional transportation capacity. Therefore, it is necessary to identify, diagnose and respond to traffic congestion in this traffic bottleneck area of ​​the road network, so as to minimize the negative impact of congestion. [0003] ...

AI Technical Summary

Problems solved by technology

[0003] At present, there are existing methods for diagnosing the causes of urban traffic congestion. One is to collect traffic information by analyzing multi-source traffic data, and then analyze the causes of road congestion from the aspects of road network structure, traffic flow distribution, intersection canalization, and signal light control. Most of the methods are based on local area road information and subjective experience to analyze the causes of congestion after the congestion occurs. The degree of automation is low, the subjectivity is strong, and the real-time performance is poor. It is difficult to perform dynamic real-time automatic diagnosis of urban traffic congestion from a global perspective.

The other is to use big data representing the characteristics of human activities such as mobile phone movement and shared cars to mine trajectory data, and then calculate the congested areas of the city. Although this method pays attention to which road sections the flow of people leads to road congestion, it fails to pay attention. Due to the differences in the needs and preferences of the population, it is difficult to accurately diagnose the characteristics of typical population groups that cause traffic congestion, and it is difficult to provide a basis for the optimization of traffic congestion problems from the perspective of people, from the dimensions of urban functions and public facility configuration, so it has a certain value. Limitation, for this reason, the present invention proposes a kind of diagnosis method, system and storage medium of urban congested area

Images