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System and method for identifying urban expressway traffic bottlenecks

An expressway and traffic technology, applied in traffic flow detection and other directions, can solve the problems of no traffic bottleneck research, no consideration of road inherent attributes, single data source, etc., to achieve the effect of data fusion and utilization, and data mining.

Active Publication Date: 2016-08-03
北京数行健科技有限公司
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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

Method used

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  • System and method for identifying urban expressway traffic bottlenecks
  • System and method for identifying urban expressway traffic bottlenecks
  • System and method for identifying urban expressway traffic bottlenecks

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Embodiment approach 1

[0027] This embodiment mainly relates to a method for identifying road traffic bottlenecks. The method mainly includes the following steps: data acquisition step, data fusion step, calculation step, traffic bottleneck identification step (see attached figure 1 ). The following are the specific introductions:

[0028] 1. Data collection step: collect mobile navigation data of road vehicles and road fixed detector data.

[0029] The data sources collected in this step include two parts. The first part is the floating car data collected through the navigation software of the vehicle or mobile terminal. The data records the ID number of the vehicle and the position, time, speed and other information of each vehicle per minute, where the position includes longitude and latitude, time year, month, date, hour, minute, second and other information (as attached figure 2 shown). The second part is the microwave data collected by fixed detectors on the roads in the city. The dat...

Embodiment approach 2

[0059] This embodiment mainly relates to a method for verifying road traffic bottlenecks. This method can also be used to verify whether the level of supersaturation probability can represent the primary and secondary of the bottleneck, and can be used to determine the specific location and spread range of the traffic bottleneck in the detector area. The specific method is as follows:

[0060] According to the data obtained in the data collection step, make the speed space-time distribution map of the relevant road sections (such as Figure 10 shown). This graph can show the change of speed with space on a certain road in 24 hours a day, the horizontal axis is 24 hours, the vertical axis is position, and the color depth represents the size of the speed. From the space-time distribution diagram of speed, we can see the change of speed in time and space, so as to find the area with lower speed, that is, the area where congestion occurs, and we can also see the initial location...

Embodiment approach 3

[0064] This implementation mode mainly involves control countermeasures for different types of traffic bottlenecks, as follows.

[0065] For the different types of traffic bottlenecks identified in the first implementation mode, corresponding measures can be taken for governance:

[0066] (1) For the first type of typical bottleneck, it is mainly because the traffic bottleneck is an important destination and traffic fortress, and the upstream traffic flow is relatively large, so it is possible to divert the upstream traffic flow to the bottleneck in advance and divert a part of the traffic flow Guide to auxiliary roads or other urban roads to the destination, so as to reduce the pressure on the main road; or promote the construction of public transportation, and transfer some car users to public transportation to reduce the demand for urban expressways; The congestion charging policy of the government alleviates severe congestion in local areas.

[0067] (2) For the second ty...

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Abstract

The invention provides a method for identifying urban expressway traffic bottlenecks. The method comprises a step of collecting the mobile navigation data of a road vehicle and road fixed detector data, a step of carrying out pretreatment on the collected data, matching the data of different sources, and determining the flow-speed distribution of each detector section, a step of determining a supersaturation critical speed and a supersaturation probability according to the flow-speed distribution, a step of determining supersaturation probability and detector position distribution, and identifying traffic bottlenecks; and classifying the identified urban expressway traffic bottlenecks, and giving corresponding control measures for different types of traffic bottlenecks.

Description

technical field [0001] The invention relates to the field of road traffic, in particular to a system and method for identifying 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 relevant factors that may caus...

Claims

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Application Information

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IPC IPC(8): G08G1/01
Inventor 申作军李萌姜涵何方陈婕妤俞佳莹
Owner 北京数行健科技有限公司
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