Macroscopic fundamental diagram-based road network key section identification method

A technology of macro basic map and recognition method, which is applied in the field of identification of key road sections of road network based on macro basic map

Active Publication Date: 2016-06-22
BEIHANG UNIV
View PDF4 Cites 36 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the practical problem is that the road network structure is static, but the road network traffic status is dynamically changing

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Macroscopic fundamental diagram-based road network key section identification method
  • Macroscopic fundamental diagram-based road network key section identification method
  • Macroscopic fundamental diagram-based road network key section identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0065] 1), select a road network A (a total of 35 road sections), set a microwave radar detector in the middle of each road section in road network A, and obtain the traffic flow, average vehicle speed and occupancy data of each microwave radar detector ,as follows:

[0066] (2427,34,0.39),(2789,31,0.45),...(4230,26,0.89),...(2638,34,0.43);

[0067] The statistical cycle is 1 hour, and a total of 840 groups of data are obtained in one day.

[0068] 2), according to the traffic flow and time occupancy rate and the length of the road section within one collection cycle (that is, 1h) of each road section in the road network, the weighted traffic flow and unweighted density data of road network A are calculated as follows:

[0069] (1893,67),(2473,79),...(3649,117),...(4131,166);

[0070] The statistical period is 1 hour, and a total of 24 pairs of data are obtained in one day.

[0071] 3) Take the weighted traffic flow and unweighted density corresponding to the road network o...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a macroscopic fundamental diagram-based road network key section identification method. The method comprises the steps of 1, acquiring the traffic flow, the average speed and the time occupancy data of each road section of an urban road network A; 2, calculating a weighted flow and a non-weighted density of the road network within each acquisition period; 3, getting a set of samples; 4, drawing a macroscopic fundamental scatter diagram; 5, calculating the critical weighted traffic flow of the road network MFD; 6, arbitrarily deleting one road section, and calculating the critical weighted traffic flow of the road network (-i)MFD without the above deleted road section and the floating value of the MFD critical weighted traffic flow of the road network A; 7, adopting the clustering analysis method for classification, and extracting a threshold r and a key road section. According to the technical scheme of the invention, the defect that the key section identification result based on the static topology structure of the road network is not consistent with the dynamic characteristics of the road network traffic flow can be overcome. Therefore, the method is more applicable to the change characteristics of the road network traffic flow. Therefore, the reliability of calculated data is ensured to be high.

Description

technical field [0001] The invention belongs to the field of identification and control of key road sections of urban road networks, and in particular relates to a method for identifying key road sections of road networks based on a macroscopic basic map. Background technique [0002] Traffic congestion is the contradiction between limited traffic supply and growing traffic demand. With the rapid growth of the number of motor vehicles, traffic congestion has gradually evolved from congestion on a single road section to congestion on the entire road network. The urban traffic environment is deteriorating and has become a worldwide phenomenon. problem. In order to avoid the overall traffic congestion in the urban road network, it is urgent to find out the key road sections that have an important impact on the traffic status of the road network. By optimizing the control of the key road sections, the traffic flow in the road network can be dredged and balanced, and the congesti...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
CPCG08G1/0116G08G1/0133
Inventor 王云鹏董婉丽于海洋吴志海杨帅
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products