CN103021181B

CN103021181B - Traffic congestion monitoring and predicting method based on macro discrete traffic flow model

Info

Publication number: CN103021181B
Application number: CN201210593368.4A
Authority: CN
Inventors: 史忠科
Original assignee: Xian Feisida Automation Engineering Co Ltd
Current assignee: Xian Feisida Automation Engineering Co Ltd
Priority date: 2012-12-30
Filing date: 2012-12-30
Publication date: 2014-10-08
Anticipated expiration: 2032-12-30
Also published as: CN103021181A

Abstract

The invention aims to overcome the technical defect that a traffic flow model difficultly monitors and predicts traffic congestion directly and provides a traffic congestion monitoring and predicting method based on a macro discrete traffic flow model. The method includes acquiring information of vehicle speed, density and flow by monitoring video images of a camera, and predicting traffic congestion to occur according to a newly established traffic congestion model. The technical problem that traffic congestion cannot be predicted timely is solved.

Description

Traffic congestion monitoring forecasting procedure based on macroscopical discrete traffic model

Technical field

The present invention relates to a kind of modeling method, particularly a kind of traffic congestion monitoring forecasting procedure based on macroscopical discrete traffic model.

Background technology

In recent years, along with the quantity of the various vehicles increases greatly, the facility of a lot of countries, road, traffic control system have been difficult to adapt to this speed of development in the world, all many-sided reasons such as that particularly big or middle urban transportation infrastructure insufficiency, traffic signals are controlled is inharmonious, traffic dispersion system shortage, vehicle scheduling and the confusion of management, the friendship of traffic participant rule consciousness have caused urban transportation compared with crowding phenomenon, have caused again thus a series of socioeconomic problems such as traffic safety, environmental pollution;

Because traffic problems are complicated large system problems, it has related to the Comprehensive Control of urban traffic network, the synthetical collection of transport information and network transmission technology, traffic intelligent information fusion and treatment technology, traffic flow inductive technology, and vehicle transport intelligent dispatching method, municipal intelligent traffic planing method, traffic safety detects, many-sided contents such as traffic environment overall evaluation system, and influence each other between above-mentioned each factor, restriction mutually, the synthesis that correlativity is extremely strong, be difficult to adopt unified description form to portray this challenge, therefore, also of all kinds for the description of traffic system, the both macro and micro model analysis traffic characteristics person who wherein adopts hydromechanical viewpoint to set up is in the majority,

In macroscopic traffic flow, traffic flow is regarded as the compressible continuous fluid medium being comprised of a large amount of vehicles, the average behavior of research vehicle collective, and the individual character of single unit vehicle does not highlight; Macroscopic traffic flow is with the average density of vehicle , average velocity and flow portray traffic flow, study their satisfied equations; Compare with microvisual model, macromodel can be portrayed the collective behavior of traffic flow better, thereby for designing effective traffic control strategy, simulation and estimating that the traffic engineering problems such as effect of road geometry modification provide foundation;

Numerical evaluation aspect, simulation Macro-traffic Flow required time study number of vehicles in traffic system with institute and is had nothing to do, with the choosing and middle space of studied road, numerical method , the time discrete steps with relevant; So macroscopic traffic flow is suitable for processing the traffic flow problem of the traffic system that a large amount of vehicles form; Fluid mechanic model is by continuum Model, to simulate the traffic behavior of wagon flow; Than microvisual model, the collective behavior of wagon flow can better be described and understand to fluid mechanic model; More influential model has LWR model (1955), Payne model (1971), Papageorgiou model (1989) and Helbing model (1999); The D model that wherein Markos Papageorgiou proposed in 1989 has obtained more approval; This model is described the traffic behavior of highway wagon flow by three partial differential equation, discretization equation is for (to be shown in document M. Papageorgiou, J.M. Blosseville, H. Hadj-salem. Macroscopic modelling of traffic flow on the Boulevard P é riph é rique in Paris, [J]. Transportation Research Part B 1989,23B:29-47):

Dynamic density model

Dynamic flow model

Dynamic speed model

Or write as Unified Form

In formula, for interval ? density constantly, for from the time start the the vehicle number that section is rolled away from, for the time time, the the vehicle number that section is sailed into, be the length in section, for interval ? entrance ramp flow constantly, for interval ? exit ramp flow constantly, for interval ? overall speed constantly, for weighting coefficient, for correction factor, T is the sampling period, for changing retardation time,

or

In formula, for free travel speed, least density during for traffic jam, density (critical value) during for flow maximum, for constant parameter, according to actual measurement traffic data, obtain, same under symbol description.

This model is single for number of lanes, discrepancy ring road is without the highway of especially big flow attack, the process of different traffics and phase co-conversion can be described with satisfied degree of accuracy, appearance and the elimination process of the normal property sent out and sporadic traffic jam are described, and amount of calculation is little, network minimal.

Yet, above-mentioned Macro-traffic Flow discrete model can not directly provide traffic congestion condition, the integral body that particularly directly provides traffic jam issue when various traffic parameters change is described, make traffic system research worker be not easy to direct use, make traffic system research worker be not easy to direct use, have the technical matters that is difficult to forecast traffic congestion.

Summary of the invention

In order to overcome traffic flow model, be difficult to the directly technological deficiency to traffic congestion monitoring forecast, the invention provides a kind of traffic congestion monitoring forecasting procedure based on macroscopical discrete traffic model, the method obtains car speed, density and flow information by the video image of CCTV camera, according to newly-established traffic congestion model, to the traffic congestion of generation is forecast, solved the technical matters that traffic congestion can not be forecast in time.

The technical solution adopted for the present invention to solve the technical problems is: a kind of traffic congestion monitoring forecasting procedure based on macroscopical discrete traffic model, is characterized in adopting following steps:

While 1, passing through video image acquisition car speed, density and the flow information of CCTV camera, consider that actual monitored video camera works at crossing throughout the year, the impossible artificial frequent correction image Processing Algorithm of mode, according to the composition error performance index of the overall process of processing with hypograph, select image processing algorithm:

In formula, for the global error of image extraction traffic parameter, for by selecting the image processing method of various combination to obtain minimum value, for image sampling error, for image and process errors, for vehicles segmentation error in image, for the error according to cutting apart image extraction traffic parameter;

2, set up the macroscopic traffic flow in given section

In formula, state variable , be individual section exists value constantly, for interval ? density constantly, be the length in section, for interval ? entrance ramp flow constantly, for interval ? exit ramp flow constantly, for interval ? overall speed constantly, for weighting coefficient, for correction factor, T is the sampling period, for changing retardation time, during for traffic congestion the saturated traffic density in individual section with identical, when traffic is normal , equivalent speed

Or

for free travel speed, least density during for traffic jam, the critical value of the density during for flow maximum, for constant parameter;

3, work as state variable or while being tending towards in time infinite, this section will be tending towards obstruction density and produce traffic congestion, and the traffic forecast of more blocking up is sent in this section;

4, adopt the restriction of discontinuity Induction Control to sail sending a car of this section into.

The invention has the beneficial effects as follows: all image method are done as a whole, according to the composition error performance index of the overall process of processing with hypograph, select image processing algorithm, and to the traffic congestion of generation is forecast, solved the technical matters that traffic congestion can not be forecast in time according to newly-established traffic congestion model.

Below in conjunction with embodiment, the present invention is elaborated.

Embodiment

In formula, for the global error of image extraction traffic parameter, for by selecting the image processing method of various combination to obtain minimum value, for image sampling error, for image and process errors, for vehicles segmentation error in image, for the error according to cutting apart image extraction traffic parameter, for image sampling error coefficient, for image and process errors coefficient, error coefficient for vehicles segmentation error in image;

2, set up the macroscopic traffic flow in given section

Or

Claims

1. the traffic congestion based on macroscopical discrete traffic model is monitored a forecasting procedure, is characterized in adopting following steps:

(1) while passing through video image acquisition car speed, density and the flow information of CCTV camera, consider that actual monitored video camera works at crossing throughout the year, the impossible artificial frequent correction image Processing Algorithm of mode, according to the composition error performance index of the overall process of processing with hypograph, select image processing algorithm:

(2) set up the macroscopic traffic flow in given section

Or

(3) work as state variable or while being tending towards in time infinite, this section will be tending towards obstruction density and produce traffic congestion, and the traffic forecast of more blocking up is sent in this section;

(4) adopt the restriction of discontinuity Induction Control to sail sending a car of this section into.