Red-and-green area identifying and evaluating method for urban road network operation state

Abstract

The invention provides a red-and-green area identifying and evaluating method for an urban road network operation state. The method comprises the following steps of A, identifying red-and-green sidesin the urban road network; B, digging red-and-green areas in the urban road network operation state; C, presenting a road network operation reliability index based on the red-and-green areas; and D, analyzing emerging and evolution characteristics of the red-and-green areas. For aiming at restrictions such as abstractness, static state, relatively low statistics property and relatively low stability in road network reliability management decision according to an existing road network operation state evaluation method, a concept of dynamic sub-picture connecting is introduced, and the red-and-green area identifying and evaluating method for the urban road network operation state is constructed. According to the method of the invention, the road network is divided into areas with different operation states; through analyzing the emerging and evolution characteristics, a manager can accurately master the real-time road network operation state for preparing a scientific and high-efficiencytraffic management solution. The red-and-green area identifying and evaluating method for the urban road network operation state has advantages of high wholeness, high stability, easy determining, wide application, etc.

Description

technical field [0001] The present invention proposes a "red and green" area identification and evaluation method of urban road network operating status, which relates to a "red and green" area identification and evaluation method of urban road network operating status, which belongs to the intersection of reliability and traffic science technology field. Background technique [0002] Today's urban traffic volume is growing rapidly, and the increasing traffic congestion has brought great inconvenience to the work and life of residents and hindered the development of the city. According to AutoNavi's "2018 Annual Traffic Analysis Report of China's Major Cities", among the 361 cities monitored by AutoNavi's traffic big data, 15% of the cities are congested during peak hours, 59% of the cities are in a slow state, and only 26% of urban commutes are not threatened by congestion. Due to the limited urban road traffic resources, the key to solving congestion is how to rationally...

AI Technical Summary

Problems solved by technology

The "red and green" area identification and evaluation method of the urban road network operating state adopted by the present invention solves the problems of the existing road network operating state evaluation methods such as abstraction, static, statistical deviation, and poor stability in the reliability management of the road network. limitations in decision making

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