Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Distributed model predictive control method for urban road network system based on neighborhood optimization

A technology of model predictive control and control method, which is applied in the direction of traffic signal control, etc., and can solve the problems of high complexity of centralized control, strong coupling relationship between adjacent intersections, non-real-time timing control, etc.

Active Publication Date: 2015-04-29
ZHEJIANG UNIV OF TECH
View PDF5 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problems of non-real-time timing control, centralized control complexity, and strong coupling relationship between adjacent intersections in the urban road network system, the present invention provides a simple, easy-to-implement, and better control effect based A real-time distributed predictive control method for macroscopic road network topology models to improve traffic congestion in urban road network systems under saturated or oversaturated conditions

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
  • Distributed model predictive control method for urban road network system based on neighborhood optimization
  • Distributed model predictive control method for urban road network system based on neighborhood optimization
  • Distributed model predictive control method for urban road network system based on neighborhood optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] The present invention will be further described below in conjunction with the accompanying drawings.

[0066] refer to figure 1 , 2 , 3, 4, a distributed model predictive control method for urban road network systems based on neighborhood optimization, comprising the following steps:

[0067] 1) Establish a road section mathematical model (refer to figure 1 ):

[0068] x z (k+1)=x z (k)+T[q z (k)-s z (k)+d z (k)-u z (k)] (1)

[0069] Among them, T represents the sampling period, which is equal to the period C of the signal lamp; x z (k) represents the number of vehicles in road section z at kT time; q z (k) and u z (k) respectively represent the flow velocity of entering road section z from intersection M and leaving road section z from intersection N at time kT; d z (k) and s z (k) represent the flow speed of vehicles entering and exiting from road section z at time kT, respectively.

[0070] Now define the upstream section of an intersection j as I j ,...

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 relates to a distributed model predictive control method for an urban road network system based on neighborhood optimization. The distributed model predictive control method comprises the following steps: 1) establishing a road section mathematical model; 2) establishing an urban traffic network system model and an urban traffic road network system distributed model: introducing a control component G (k) on the basis of the road section model and performing decomposition and deformation on the road network system model to obtain the road network system distributed model; 3) establishing performance indexes and constraint conditions of each subsystem and constructing subsystem performance indexes based on the neighborhood optimization; 4) firstly calculating a local optimal control variable through each subsystem, continuously iterating through performing information exchange with a neighborhood subsystem according to a Nash game theory principle to enable the whole system to converge Nash equilibrium points at last and obtaining a Nash optimal control input quantity at the same time. The distributed model predictive control method is simple and clear, convenient to realize and better in control effect and improves the traffic congestion conditions in the urban road network system under a saturated or supersaturated state.

Description

technical field [0001] The invention relates to the field of urban road networks, in particular to an optimization method for saturated or oversaturated large-scale urban road network systems. Background technique [0002] Transportation has become an important feature of human civilization. But since the second half of the 20th century, with the increase of the number of vehicles and the improvement of transportation requirements, traffic congestion has become an important factor hindering social and economic development. Traffic congestion will bring a series of problems: the extension of vehicle waiting time; the reduction of driving safety factor; the aggravation of environmental pollution. The congestion problem is especially prominent in the urban road network system, and due to the non-scalability of urban infrastructure, the traditional solution (road expansion) will become more and more difficult. Therefore, we need to use an effective control method to control th...

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): G08G1/07
Inventor 刘安东李佳张文安俞立
Owner ZHEJIANG UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products