Urban traffic reliability index based on seepage analysis, and implementation method for urban traffic reliability index

Abstract

The invention discloses an urban traffic reliability index based on seepage analysis, and an implementation method for the urban traffic reliability index, and the method comprises the following steps: 1, carrying out the preprocessing of urban traffic data information; 2, building a traffic dynamic network based on the urban traffic data information, taking the traffic flow data of each segment in an actual urban traffic system as the basis, and carrying out the empowerment operation of a network; 3, analyzing the seepage attributes of the traffic dynamic network, finding the seepage threshold value of an urban traffic network, and obtaining the urban traffic reliability index based on the above; 4, determining a bottleneck road affecting the reliability of an urban traffic system. The method dynamically gives consideration to the operation efficiency of macroscopic traffic from the network layer of urban traffic, can solve an actual problem of the accurate and complete measurement of the congestion of a traffic network system, achieves the quantification and evaluation of the reliability of the urban traffic network system, and provides a powerful method support for the smooth project and the construction of a smart city.

Description

technical field [0001] The invention proposes a seepage analysis-based urban traffic reliability index and its realization method, which relates to a seepage theory-based urban traffic system reliability index and its realization method, and belongs to the cross-technical field of reliability and traffic science. Background technique [0002] Transportation has become one of the main infrastructures for the development of modern society, and it also plays a pivotal role in the current development model of "Internet + transportation". However, when urban traffic develops into a huge and complex traffic network system with the growth of the city, the problem of traffic congestion becomes more and more prominent. In fact, traffic congestion has caused great economic and environmental losses. Taking Beijing as an example, the "China Economic Survey" in 2013 showed that the average daily congestion time per person in Beijing was nearly 2 hours, and the loss caused by traffic con...

AI Technical Summary

Problems solved by technology

However, this indicator also has great limitations: the indicator depends on the selection of traffic trajectories, and the trajectories often only reflect part of the traffic demand, and the greater the demand, the greater the weight of the route; Contingency; the calculation of travel time needs to wait for the t

Images