Method of identifying urban expressway recurrent traffic bottlenecks

Abstract

The invention discloses a method of identifying urban expressway recurrent traffic bottlenecks, which is applied to a road condition prediction system provided with a plurality of detectors. The method comprises the following steps: data acquisition is carried out; data fusion is carried out; a corresponding synthesis rule is selected for the traffic flow data of each road section; a saturation critical speed and a supersaturation probability are determined according to flow-speed distribution; traffic bottlenecks are identified; and corresponding countermeasures are proposed according to different types of traffic bottlenecks. Based on fusion of mobile navigation data and data monitored by fixed detectors, a new method of identifying urban expressway recurrent major traffic bottlenecks isdisclosed, data fusion utilization and data mining under the current computer processing capability can be effectively realized, the expressway traffic bottlenecks can be recognized from the urban level, and more accurate and scientific advice is provided for traffic congestion management and optimization.

Description

technical field [0001] The invention relates to the technical field of traffic information control, in particular to a method for identifying frequent traffic bottlenecks on urban expressways. Background technique [0002] With the acceleration of urbanization, the coverage of urban expressways is getting higher and higher, but the expressway load and congestion problems are becoming more and more prominent. Traffic bottlenecks are the direct cause of traffic congestion. How to find the key traffic bottlenecks and manage them in a targeted manner is an important issue in alleviating traffic congestion. [0003] For the identification of traffic bottlenecks in existing studies, most of the methods used are based on the speed or occupancy detected by fixed detectors on the road, and then combined with artificially set thresholds to judge congestion and non-congestion, which is completely based on a single data source. Other studies are based on empirical selection of relevan...

AI Technical Summary

Problems solved by technology

[0003] For the identification of traffic bottlenecks in existing studies, most of the methods used are based on the speed or occupancy detected by fixed detectors on the road, and then combined with artificially set thresholds to judge congestion and non-congestion, which is completely based on a single data source for

Other studies are based on empirical selection of relevant factors that may cause bottlenecks, but do not consider the contradiction between traffic supply and traffic demand, nor do they take into account the inherent attributes of roads

In addition, in terms of the scale of the research, most of the research objects at home and abroad are micro-studies on a section of expressway or urban roads, and there is no macro-study on the traffic bottleneck of a regional road network