CN102938207A - On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved light water reactor (LWR) model - Google Patents

Abstract

The invention discloses an on-line traffic bottleneck control method based on a field programmable gate array (FPGA) and an improved light water reactor (LWR) model and aims to solve the technical problem that existing methods can not perform on-line predictive regulating and controlling for traffic bottlenecks in actual expressways or blocked roads. According to the on-line traffic bottleneck predictive control method, the LWR model is improved, a variable information display board is integrated into the LWR model, a whole predictive analysis is performed for the expressways or the blocked roads through the improved LWR model based on the FPGA platform, the road bottleneck is found out according to defined state variables, then control schemes of junction control and the variable information display board are provided, the control schemes can be taken into prediction models according to priority levels, a reasonable control scheme can be found out, the on-line control for the traffic bottleneck can be achieved, and thereby the traffic bottleneck in the expressways or the blocked roads can be effectively controlled.

Description

Online traffic bottlenecks forecast Control Algorithm based on FPGA and improvement LWR model

Technical field

The present invention relates to a kind of FPGA control method, particularly a kind of online traffic bottlenecks forecast Control Algorithm based on FPGA and improvement LWR macroscopic traffic flow.

Background technology

Traffic congestion has become the common focus of paying close attention in countries in the world and has been badly in need of the major issue solved, the traffic bottlenecks problem is one of main problem of the restriction magnitude of traffic flow, due to the restriction of hardware facility or the impact of emergency situations, make some highway sections become the bottleneck of whole road, if do not regulated and not controled, can accelerate the flow accumulation of bottleneck road, traffic is worsened, get congestion, even cause whole transportation network paralysis.

At present, the mode of freeway traffic regulation and control only has the variable information display board to carry out speed restriction and the circle mouth is controlled two kinds, in order effectively to relieve traffic congestion, improve the service efficiency of highway, often uses the means of information display board as transport information issue and control; Usually, information display board and variable speed-limit sign are as the important information issue of intelligent transportation system, carry out Long-distance Control by Surveillance center's computing machine by communication network, transmit and show various graph text informations, issue in time different road surfaces situation and all kinds of transport information of different sections of highway to the driver, carry out the publicity of traffic law, traffic knowledge, reach and reduce the impact that the highway reappearance is blocked, reduced the non-reappearance accident of highway, improve traffic safety; As described as document " Hai Yilatibala carries; the Expressway Information display board arranges Discussion on Technology; the land bridge visual field; in October, 2010; 139-140 ", the mechanism that arranges of information display board system is: (1) sensor information collection and disposal system, (2) information display board information provide, (3) communication system, (4) central control system; The setting of information display board should be from the angle of whole traffic navigation system Construction, takes into full account the associated of leading and control, takes the comprehensive benefit of surface road and overpass into consideration, formulates the leading scheme of globality, rationality, high efficiency; The information display board adopts different forms according to the difference of the place arranged and purpose; A kind of being mounted on main line, carry out that main line is induced and outlet is induced, and the traffic that shows highway section, the place ahead with character style is as unimpeded, crowded, delay etc., thereby make the driver can turn to surface road, avoids crowded district; Another kind is arranged near the ring road entrance, and the queue length of ring road porch and crowded prediction case are reported to the driver, also can be shown to the driver on the ring road entrance to the traffic conditions on contiguous main line, thereby induce for they provide reasonably; In addition, in the situation that the road congestion risk is very high, can control the input of circle mouth, even at road circle mouth, force some vehicles to roll highway away from, to avoid the generation of blocking up; Yet, these schemes, by the super expressway entrance induce, the road main line is induced, the road way outlet is only induced and demarcated according to information requirement, there is no the organic phase combination, particularly the demonstration information of information display board is not set automatically according to macro traffic model prediction output, be difficult to, from overall angle, bottleneck road is carried out to traffic control, the highway section that the result of regulation and control regulates and controls often is unimpeded, but the traffic jam phenomenon occurs in non-regulation and control highway section.

In order to analyse in depth traffic system, a large amount of scholar's research traffic flow model, wherein adopt the both macro and micro model analysis traffic characteristics person of hydromechanical viewpoint foundation in the majority both at home and abroad; In macroscopic traffic flow, traffic flow is regarded as the compressible continuous fluid medium be comprised of a large amount of vehicles, and the average behavior of research vehicle collective, the individual character of single unit vehicle do not highlight; Macroscopic traffic flow is portrayed traffic flow with average density ρ, average velocity v and the flow q of vehicle, studies their satisfied equations; 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; Aspect numerical evaluation, simulation Macro-traffic Flow required time study number of vehicles in traffic system with institute and is had nothing to do, with studied road, numerical method choose and the discrete steps of middle space x, time t relevant.So macroscopic traffic flow is suitable for processing the traffic flow problem of the traffic system that a large amount of vehicles form; This class model is used for discussing the traffic behavior of blocked road by Most scholars in the world.

Through retrieval, find, number of patent application 200810117959.8, open day on January 14th, 2009, record " a kind of control method at the traffic bottlenecks place and device ", the method is by arranging buffer zone, the rule of travelling of vehicle in the restriction buffer zone, the vehicle number of controlling in buffer zone is controlled vehicle flowrate, there is certain effect, but the method could not point out how to detect traffic bottlenecks, in real road, traffic bottlenecks are not what fix, each highway section may become traffic bottlenecks, and therefore, the method has limitation; Document " Zeng Guangxiang. the analysis of road traffic bottleneck, control and simulation; 2010; Guangxi University's Master's thesis " take the LWR model as basis, analyzed the disturbance of the one-way traffic bottleneck generation of road minimizing generation, and propose based on this to improve the method for traffic bottlenecks in pedestrian traffic, and the harm that the road traffic bottleneck causes or economic loss are larger, the document is not analyzed its solution;

In highway or blocked road, can only control to regulate traffic by variable information display board or circle mouth, and each highway section all likely becomes traffic bottlenecks, current research mostly just produces the analysis of reason to traffic bottlenecks or is only how to solve specific road section traffic bottlenecks problem, just emulation is carried out in the traffic highway section, bottleneck forecasting and traffic control are not combined real-time monitoring is carried out in the traffic highway section, and mostly operate in computing machine and with upper mounting plate, bulky, there is the technical matters that is difficult in actual highway or blocked road, traffic bottlenecks be carried out on-line prediction and regulation and control in these researchs.

Summary of the invention

The technological deficiency that is difficult in actual highway or blocked road, traffic bottlenecks be carried out the on-line prediction regulation and control in order to overcome existing method, the invention provides a kind of online traffic bottlenecks control method based on FPGA and improvement LWR model, the method is improved the LWR model, the variable information display board is dissolved in the LWR model, by improved LWR model, highway or blocked road integral body are carried out to forecast analysis based on the FPGA platform, find the road bottleneck according to the state variable of definition, and then provide that the circle mouth is controlled and the control program of variable information display board, and these control programs are according to priority brought into to forecast model, find rational control program, thereby traffic bottlenecks are carried out to On-line Control, can effectively solve the technical matters that existing scheme is difficult in actual highway or blocked road, traffic bottlenecks be carried out the on-line prediction regulation and control.

The technical solution adopted for the present invention to solve the technical problems: the online traffic bottlenecks forecast Control Algorithm based on FPGA and improvement LWR model is characterized in comprising the following steps:

Step 1, according to the LWR model:

$\left\{\begin{array}{c}\frac{\∂\mathrm{\ρ}}{\∂t}+\frac{\∂\left(\mathrm{\ρv}\right)}{\∂x}=\mathrm{\π}[r(x,t),s(x,t)]\\ v(x.t)=V_e\left[\mathrm{\ρ}(x,t)\right]\end{array}\right.$

In formula, t is the time, and x is the distance with emulation road starting point, ρ is traffic flow density and is the function of x, t, ρ=ρ (x, t), v is vehicle average velocity and is the function of x, t, v=v (x, t), π [r (x, t), s (x, t)] the rate of change of the density function that causes for the vehicle flowrate that enters or roll away from due to the circle mouth, r (x, t)=r ₀(x, t)-r _qThe vehicle flowrate that (x, t) entered by the circle mouth for the t moment, x highway section, s (x, t)=s ₀(x, t)+s _qThe vehicle flowrate that (x, t) rolled away from by the circle mouth for the t moment, x highway section, r ₀(x, t), s ₀(x, t) for to sail by the circle mouth the normal vehicle flowrate rolled away from into, r _qThe flow reduction amount that (x, t) causes for the circle mouth expressway of controlling that No entry, s _q(x, t) controls the flow increment of forcing outgoing vehicles to cause, V for the circle mouth _e(ρ) be equivalent speed and with free stream velocity v _fRelevant with the traffic flow density p, full application form symbol definition is identical;

Variable display board display speed is incorporated to the LWR model, with variable display board display speed v _indReplace the free stream velocity v in equivalent speed _f, the LWR model be improved is as follows:

$\left\{\begin{array}{c}\frac{\∂\mathrm{\ρ}}{\∂t}+\frac{\∂\left(\mathrm{\ρv}\right)}{\∂x}=\mathrm{\π}[r(x,t),s(x,t)]\\ v(x.t)=V_e[\mathrm{\ρ}(x,t),v_{\mathrm{ind}}]\end{array}\right.$

In formula, v _indMean the speed that the variable information display board shows;

Step 2, define two new state variable η (x, t), σ (x, t), work as state variable

While being tending towards infinite, that represent traffic density is tending towards saturated traffic density, produces traffic congestion, works as state variable

While being tending towards infinite, represent that vehicle average velocity goes to zero, produce traffic congestion;

In formula, ρ _jamTraffic flow density while occurring blocking for traffic;

The improved LWR model that step 3, a. obtain according to step 1, mean differential term and omit higher order term by difference scheme, obtains:

$\frac{\∂\mathrm{\ρ}}{\∂t}=\frac{\mathrm{\ρ}(x,t+\mathrm{\ξ})-\mathrm{\ρ}(x,t)}{\mathrm{\ξ}}+o\left(\mathrm{\ξ}\right)=\frac{{\mathrm{\ρ}}_i^{n+1}-{\mathrm{\ρ}}_i^n}{\mathrm{\ξ}}$

$\frac{\∂\mathrm{\ρ}}{\∂x}=\frac{\mathrm{\ρ}(x+h,t)-\mathrm{\ρ}(x,t)}{h}+o\left(h\right)=\frac{{\mathrm{\ρ}}_{i+1}^n-{\mathrm{\ρ}}_i^n}{h}$

$\frac{\∂v}{\∂t}=\frac{v(x+h,t)-v(x,t)}{h}+o\left(h\right)=\frac{v_{i+1}^n-v_i^n}{h}$

In formula: the differential that ξ is t, the differential that h is x, the high-order infinitesimal that o (ξ) is ξ, the high-order infinitesimal that o (h) is h, be divided into a plurality of highway sections to road, and each road section length is h, and the sampling period is ξ,

Be the traffic flow density of i highway section in [n ξ, (n+1) ξ],

Be the average velocity of i highway section at [n ξ, (n+1) ξ] interior vehicle;

The difference form of the LWR model be improved is:

$\left\{\begin{array}{c}{\mathrm{\ρ}}_i^{n+1}=\mathrm{\ξ\π}(r_i^n,s_i^n)-\frac{\mathrm{\ξ}}{h}[v_i^n({\mathrm{\ρ}}_{i+1}^n-{\mathrm{\ρ}}_i^n)+{\mathrm{\ρ}}_i^n(v_{i+1}^n-v_i^n)]+{\mathrm{\ρ}}_i^n\\ v_i^{n+1}=V_e[{\mathrm{\ρ}}_i^n,v_{\mathrm{ind}}(i,n)]\end{array}\right.$

In formula,

Mean the vehicle flowrate that i highway section entered by the circle mouth in [n ξ, (n+1) ξ],

Mean the vehicle flowrate that i highway section rolled away from by the circle mouth in [n ξ, (n+1) ξ], v _ind(i, n) means i highway section variable display board display speed in [n ξ, (n+1) ξ];

B. set up the equivalent speed model: $V_e[{\mathrm{\ρ}}_i^n,v_{\mathrm{ind}}(i,n)]=\frac{v_{\mathrm{ind}}(i,n)(1-{\mathrm{\ρ}}_i^n/{\mathrm{\ρ}}_{\mathrm{jam}})}{1+E{({\mathrm{\ρ}}_i^n/{\mathrm{\ρ}}_{\mathrm{jam}})}^4},$

In formula, E is constant;

C. write the PREDICTIVE CONTROL module based on improving the LWR model in FPGA, as shown in Figure 1, comprise data reception module, control program is selected and the data allocations module, computing module 1-computing module N, synchronization module, data outputting module, road is divided into to N highway section, the corresponding computing module in each highway section, the forecasting traffic flow computing module that in figure, computing module 1-computing module N is used the floating point arithmetic device to combine for the Difference Method according to aforementioned partial differential equations, the data flow of PREDICTIVE CONTROL module is: traffic flow data (the traffic flow density in each highway section that data reception module reception host computer transmits, vehicle average velocity), then passing to control program selects and the data allocations module, control program is selected and the data allocations module is determined traffic bottlenecks according to these data, and formulation regulation and control scheme, then by enable signal, control program and traffic flow data are passed to each computing module, each computing module is predicted and result is deposited in to register traffic flow density and vehicle average velocity simultaneously after receiving enable signal, modules is passed to synchronization module to calculating end signal separately after calculating and finishing, synchronization module completes and calculates predicting the outcome of rear transmitted signal informing case selection and data allocations module reception traffic flow data at all computing modules, proceed prediction, at predicted time T _cin, if traffic bottlenecks are removed, adopt this scheme to be regulated and controled actual traffic, if can not remove, control program select and the data allocations module according to traffic flow data and last time regulation and control scheme formulate new regulation and control scheme, and traffic flow data and regulation and control scheme are passed to each computing module, re-start prediction, repeatedly predict and adjust regulation and control scheme after select a suitable regulation and control scheme output to be regulated and controled traffic bottlenecks, and the highway section regulated and controled is in time T _cinside no longer regulated and controled, then continue traffic is predicted, find new traffic bottlenecks, and controlled,

Determine in described step 3 that traffic bottlenecks the method that it is controlled are: solve || η (x, t) || _∞=η _m(x _m, t _m), work as η _mBe greater than given threshold value η _MThe time, highway section x is described _mAt t _mConstantly will become traffic bottlenecks, at t _m-T ₀The x of the moment to vehicle heading _mFront and back enter, go out that circle mouth and variable information display board carry out speed limit (highway section, bottleneck road the place ahead Speed Reduction, highway section, rear speed improves), restriction enters bottleneck road even forces to roll away from bottleneck road; Or solve || σ (x, t) || _∞=σ _m(x _m, t _m), work as σ _mBe greater than given threshold value σ _MThe time, highway section x is described _mAt t _mConstantly will become traffic bottlenecks, at t _m-T ₁The x of the moment to vehicle heading _mFront and back go out, enter that circle mouth and variable information display board carry out speed limit (highway section, bottleneck road the place ahead Speed Reduction, highway section, rear speed improves), restriction enters bottleneck road even forces to roll away from bottleneck road;

T in formula ₀, T ₁For the time that applies in advance control makes || η (x, t) || _∞=η _m(x _m, t _m)≤η _M, || σ (x, t) || _∞=σ _m(x _m, t _m)≤σ _M, η _M, σ _MBe respectively the positive number made according to roading density maximum saturation, friction;

The priority principle of controlling is: 1. at first by the variable information display board, adjust highway section speed, the car speed that enters bottleneck road is reduced, the car speed that rolls bottleneck road away from improves, 2. in the time of only by variable information display board adjustment highway section speed, can not reaching the control index, by the restriction of circle mouth, enter the bottleneck road flow and adjust highway section speed with the variable information display board and controlled simultaneously, 3. adjust highway section speed and control to reach simultaneously and control while requiring when enter bottleneck road flow and variable information display board by circle mouth restriction, be controlled at an interrupting time forced portion minute highway section vehicle by the circle mouth and roll road away from, circle mouth restriction is entered to the bottleneck road vehicle flowrate and the variable information display board is adjusted highway section speed to reach the control index request simultaneously.

The invention has the beneficial effects as follows: due to the equivalent speed of improving in the LWR model, variable information display board display speed is dissolved in equivalent speed, by improved LWR model, highway or blocked road integral body are carried out to forecast analysis based on the FPGA platform, find the road bottleneck according to the state variable of definition, and then provide that the circle mouth is controlled and the control program of variable information display board, and these control programs are according to priority brought into to forecast model, to guarantee that regulation and control scheme is practical, and then solution has the technical matters that method is difficult in actual highway or blocked road, traffic bottlenecks be carried out the on-line prediction regulation and control now.

The accompanying drawing explanation

Fig. 1 is that the FPGA that the present invention is based on the online traffic bottlenecks forecast Control Algorithm of FPGA and improvement LWR model realizes block diagram;

Fig. 2 is the control method process flow diagram that the present invention is based on FPGA and improve the online traffic bottlenecks forecast Control Algorithm of LWR model.

Embodiment

Describe the present invention in detail with reference to accompanying drawing 1,2.

Control method process flow diagram of the present invention as shown in Figure 2, in the situation that do not have traffic bottlenecks to produce, control program is that variable display board shows the free stream velocity that road allows, the circle mouth is controlled and is not limited input and output, traffic flow density and vehicle average velocity prediction a period of time T by traffic flow density, vehicle average velocity, variable display board display speed and circle mouth control program to each highway section _c(T _cGet T ₀, T ₁Between large value), and judge whether to occur traffic bottlenecks, if traffic bottlenecks do not occur, use current control program to be regulated and controled, according to aforementioned priority principle, adjust variable display board display speed and circle mouth control program if there is bottleneck, and continue prediction a period of time T _cIf traffic bottlenecks can not be removed, continue to adjust control program, until find a kind of control program can the transport solution bottleneck problem, and adopt this scheme to be controlled traffic bottlenecks, its detailed method is as follows:

1. according to the LWR model:

$\left\{\begin{array}{c}\frac{\∂\mathrm{\ρ}}{\∂t}+\frac{\∂\left(\mathrm{\ρv}\right)}{\∂x}=\mathrm{\π}[r(x,t),s(x,t)]\\ v(x.t)=V_e\left[\mathrm{\ρ}(x,t)\right]\end{array}\right.$

In formula, t is the time, and x is the distance with emulation road starting point, ρ is traffic flow density and is the function of x, t, ρ=ρ (x, t), v is vehicle average velocity and is the function of x, t, v=v (x, t), π [r (x, t), s (x, t)] the rate of change of the density function that causes for the vehicle flowrate that enters or roll away from due to the circle mouth, r (x, t)=r ₀(x, t)-r _qThe vehicle flowrate that (x, t) entered by the circle mouth for the t moment, x highway section, s (x, t)=s ₀(x, t)+s _qThe vehicle flowrate that (x, t) rolled away from by the circle mouth for the t moment, x highway section, r ₀(x, t), s ₀(x, t) for to sail by the circle mouth the normal vehicle flowrate rolled away from into, r _qThe flow reduction amount that (x, t) causes for the circle mouth expressway of controlling that No entry, s _q(x, t) controls the flow increment of forcing outgoing vehicles to cause, V for the circle mouth _e(ρ) be equivalent speed and with free stream velocity v _fRelevant with the traffic flow density p, full application form symbol definition is identical;

Variable display board display speed is incorporated to the LWR model, with variable display board display speed v _indReplace the free stream velocity v in equivalent speed _f, the LWR model be improved is as follows:

$\left\{\begin{array}{c}\frac{\∂\mathrm{\ρ}}{\∂t}+\frac{\∂\left(\mathrm{\ρv}\right)}{\∂x}=\mathrm{\π}[r(x,t),s(x,t)]\\ v(x.t)=V_e[\mathrm{\ρ}(x,t),v_{\mathrm{ind}}(x,t)]\end{array}\right.$

In formula, v _indThe speed that when (x, t) expression x is in time t, the variable information display board shows;

2. define two new state variable η (x, t), σ (x, t), work as state variable

While being tending towards infinite, that represent traffic density is tending towards saturated traffic density, produces traffic congestion, works as state variable While being tending towards infinite, represent that vehicle average velocity goes to zero, produce traffic congestion;

In formula, ρ _jamTraffic flow density while occurring blocking for traffic;

3. according to the improved LWR model obtained in 1, by difference scheme, mean differential term and omit higher order term, obtain:

$\frac{\∂\mathrm{\ρ}}{\∂t}=\frac{\mathrm{\ρ}(x,t+\mathrm{\ξ})-\mathrm{\ρ}(x,t)}{\mathrm{\ξ}}+o\left(\mathrm{\ξ}\right)=\frac{{\mathrm{\ρ}}_i^{n+1}-{\mathrm{\ρ}}_i^n}{\mathrm{\ξ}}$

$\frac{\∂\mathrm{\ρ}}{\∂x}=\frac{\mathrm{\ρ}(x+h,t)-\mathrm{\ρ}(x,t)}{h}+o\left(h\right)=\frac{{\mathrm{\ρ}}_{i+1}^n-{\mathrm{\ρ}}_i^n}{h}$

$\frac{\∂v}{\∂x}=\frac{v(x+h,t)-v(x,t)}{h}+o\left(h\right)=\frac{v_{i+1}^n-v_i^n}{h}$

In formula: the differential that ξ is t, the differential that h is x, the high-order infinitesimal that o (ξ) is ξ, the high-order infinitesimal that o (h) is h, ρ (x, t) be t x place traffic flow constantly density, v (x, t) is the t average velocity of x place vehicle constantly, road is divided into to a plurality of highway sections, each road section length is h, and the sampling period is ξ

Be i highway section in [n ξ, (n+1) ξ] interior average vehicle flow density,

Be the average velocity of i highway section at [n ξ, (n+1) ξ] interior vehicle;

The difference form of the LWR model be improved is:

$\left\{\begin{array}{c}{\mathrm{\ρ}}_i^{n+1}=\mathrm{\ξ\π}(r_i^n,s_i^n)-\frac{\mathrm{\ξ}}{h}[v_i^n({\mathrm{\ρ}}_{i+1}^n-{\mathrm{\ρ}}_i^n)+{\mathrm{\ρ}}_i^n(v_{i+1}^n-v_i^n)]+{\mathrm{\ρ}}_i^n\\ v_i^{n+1}=V_e[{\mathrm{\ρ}}_i^n,v_{\mathrm{ind}}(i,n)]\end{array}\right.$

In formula,

Mean the vehicle flowrate that i highway section entered by the circle mouth in [n ξ, (n+1) ξ],

Mean the vehicle flowrate that i highway section rolled away from by the circle mouth in [n ξ, (n+1) ξ], v _ind(i, n) means i highway section variable display board display speed in [n ξ, (n+1) ξ];

4. set up the equivalent speed model: $V_e[{\mathrm{\ρ}}_i^n,v_{\mathrm{ind}}(i,n)]=\frac{v_{\mathrm{ind}}(i,n)(1-{\mathrm{\ρ}}_i^n/{\mathrm{\ρ}}_{\mathrm{jam}})}{1+E{({\mathrm{\ρ}}_i^n/{\mathrm{\ρ}}_{\mathrm{jam}})}^4},$

In formula, E is constant;

5. write the PREDICTIVE CONTROL module based on improving the LWR model in FPGA, the traffic flow situation is predicted, find traffic bottlenecks, traffic bottlenecks are controlled, in the present embodiment, fpga chip is selected the EP4CE115F29C8 chip of altera corp, with other road information acquisition module (host computer), by wireless GPRS, communicate by letter, road is divided into to 40 highway sections, as shown in Figure 1, comprise data reception module, control program is selected and the data allocations module, in computing module 1-computing module 40(embodiment, N gets 40), synchronization module, data outputting module, the forecasting traffic flow computing module that computing module 1-computing module 40 is used the floating point arithmetic device to combine for the Difference Method according to aforementioned partial differential equations, the data flow of PREDICTIVE CONTROL module is: traffic flow data (the traffic flow density in each highway section that data reception module reception host computer transmits, vehicle average velocity), then passing to control program selects and the data allocations module, control program is selected and the data allocations module is determined traffic bottlenecks according to these data, and formulation regulation and control scheme, then by enable signal, control program and traffic flow data are passed to each computing module, each computing module is predicted and result is deposited in to register traffic flow density and vehicle average velocity simultaneously after receiving enable signal, modules is passed to synchronization module to calculating end signal separately after calculating and finishing, synchronization module completes and calculates predicting the outcome of rear transmitted signal informing case selection and data allocations module reception traffic flow data at all computing modules, proceed prediction, at predicted time T _cin, if traffic bottlenecks are removed, adopt this scheme to be regulated and controled actual traffic, if can not remove, control program select and the data allocations module according to traffic flow data and last time regulation and control scheme formulate new regulation and control scheme, and traffic flow data and regulation and control scheme are passed to each computing module, re-start prediction, repeatedly predict and adjust regulation and control scheme after select a suitable regulation and control scheme output to be regulated and controled traffic bottlenecks, and the highway section regulated and controled is in time T _cinside no longer regulated and controled, then continue traffic is predicted, find new traffic bottlenecks, and controlled,

6. the method for finding traffic bottlenecks in above-mentioned 5 and bottleneck being regulated and controled is: solve || η (x, t) || _∞=η _m(x _m, t _m), work as η _mBe greater than given threshold value η _MThe time, highway section x is described _mAt t _mConstantly will become traffic bottlenecks, at t _m-T ₀The x of the moment to vehicle heading _mFront and back enter, go out that circle mouth and variable information display board carry out speed limit (highway section, bottleneck road the place ahead Speed Reduction, highway section, rear speed improves), restriction enters bottleneck road even forces to roll away from bottleneck road; Or solve || σ (x, t) || _∞=σ _m(x _m, t _m), work as σ _mBe greater than given threshold value σ _MThe time, highway section x is described _mAt t _mConstantly will become traffic bottlenecks, at t _m-T ₁The x of the moment to vehicle heading _mFront and back go out, enter that circle mouth and variable information display board carry out speed limit (highway section, bottleneck road the place ahead Speed Reduction, highway section, rear speed improves), restriction enters bottleneck road even forces to roll away from bottleneck road;

T in formula ₀, T ₁For the time that applies in advance control makes || η (x, t) || _∞=η _m(x _m, t _m)≤η _M, || σ (x, t) || _∞=σ _m(x _m, t _m)≤σ _M, η _M, σ _MBe respectively the positive number made according to roading density maximum saturation, friction;

The priority principle of controlling is: 1. at first by the variable information display board, adjust highway section speed, the car speed that enters bottleneck road is reduced, the car speed that rolls bottleneck road away from improves, 2. in the time of only by variable information display board adjustment highway section speed, can not reaching the control index, by the restriction of circle mouth, enter the bottleneck road flow and adjust highway section speed with the variable information display board and controlled simultaneously, 3. adjust highway section speed and control to reach simultaneously and control while requiring when enter bottleneck road flow and variable information display board by circle mouth restriction, be controlled at an interrupting time forced portion minute highway section vehicle by the circle mouth and roll road away from, circle mouth restriction is entered to the bottleneck road vehicle flowrate and the variable information display board is adjusted highway section speed to reach the control index request simultaneously.

Claims (1)

1. one kind based on FPGA and improve the online traffic bottlenecks forecast Control Algorithm of LWR model, it is characterized in that comprising the following steps:

Step 1, according to the LWR model:

$\left\{\begin{array}{c}\frac{\∂\mathrm{\ρ}}{\∂t}+\frac{\∂\left(\mathrm{\ρv}\right)}{\∂x}=\mathrm{\π}[r(x,t),s(x,t)]\\ v(x.t)=V_e\left[\mathrm{\ρ}(x,t)\right]\end{array}\right.$

In formula, t is the time, and x is the distance with emulation road starting point, ρ is traffic flow density and is the function of x, t, ρ=ρ (x, t), v is vehicle average velocity and is the function of x, t, v=v (x, t), π [r (x, t), s (x, t)] the rate of change of the density function that causes for the vehicle flowrate that enters or roll away from due to the circle mouth, r (x, t)=r ₀(x, t)-r _qThe vehicle flowrate that (x, t) entered by the circle mouth for the t moment, x highway section, s (x, t)=s ₀(x, t)+s _qThe vehicle flowrate that (x, t) rolled away from by the circle mouth for the t moment, x highway section, r ₀(x, t), s ₀(x, t) for to sail by the circle mouth the normal vehicle flowrate rolled away from into, r _qThe flow reduction amount that (x, t) causes for the circle mouth expressway of controlling that No entry, s _q(x, t) controls the flow increment of forcing outgoing vehicles to cause, V for the circle mouth _e(ρ) be equivalent speed and with free stream velocity v _fRelevant with the traffic flow density p, full application form symbol definition is identical;

Variable display board display speed is incorporated to the LWR model, with variable display board display speed v _indReplace the free stream velocity v in equivalent speed _f, the LWR model be improved is as follows:

$\left\{\begin{array}{c}\frac{\∂\mathrm{\ρ}}{\∂t}+\frac{\∂\left(\mathrm{\ρv}\right)}{\∂x}=\mathrm{\π}[r(x,t),s(x,t)]\\ v(x.t)=V_e[\mathrm{\ρ}(x,t),v_{\mathrm{ind}}]\end{array}\right.$

In formula, v _indMean the speed that the variable information display board shows;

Step 2, define two new state variable η (x, t), σ (x, t), work as state variable While being tending towards infinite, that represent traffic density is tending towards saturated traffic density, produces traffic congestion, works as state variable

While being tending towards infinite, represent that vehicle average velocity goes to zero, produce traffic congestion;

In formula, ρ _jamTraffic flow density while occurring blocking for traffic;

The improved LWR model that step 3, a. obtain according to step 1, mean differential term and omit higher order term by difference scheme, obtains:

$\frac{\∂\mathrm{\ρ}}{\∂t}=\frac{\mathrm{\ρ}(x,t+\mathrm{\ξ})-\mathrm{\ρ}(x,t)}{\mathrm{\ξ}}+o\left(\mathrm{\ξ}\right)=\frac{{\mathrm{\ρ}}_i^{n+1}-{\mathrm{\ρ}}_i^n}{\mathrm{\ξ}}$

$\frac{\∂\mathrm{\ρ}}{\∂x}=\frac{\mathrm{\ρ}(x+h,t)-\mathrm{\ρ}(x,t)}{h}+o\left(h\right)=\frac{{\mathrm{\ρ}}_{i+1}^n-{\mathrm{\ρ}}_i^n}{h}$

$\frac{\∂v}{\∂x}=\frac{v(x+h,t)-v(x,t)}{h}+o\left(h\right)=\frac{v_{i+1}^n-v_i^n}{h}$

In formula: the differential that ξ is t, the differential that h is x, the high-order infinitesimal that o (ξ) is ξ, the high-order infinitesimal that o (h) is h, be divided into a plurality of highway sections to road, and each road section length is h, and the sampling period is ξ,

Be the traffic flow density of i highway section in [n ξ, (n+1) ξ],

Be the average velocity of i highway section at [n ξ, (n+1) ξ] interior vehicle;

The difference form of the LWR model be improved is:

$\left\{\begin{array}{c}{\mathrm{\ρ}}_i^{n+1}=\mathrm{\ξ\π}(r_i^n,s_i^n)-\frac{\mathrm{\ξ}}{h}[v_i^n({\mathrm{\ρ}}_{i+1}^n-{\mathrm{\ρ}}_i^n)+{\mathrm{\ρ}}_i^n(v_{i+1}^n-v_i^n)]+{\mathrm{\ρ}}_i^n\\ v_i^{n+1}=V_e[{\mathrm{\ρ}}_i^n,v_{\mathrm{ind}}(i,n)]\end{array}\right.$

In formula,

Mean the vehicle flowrate that i highway section entered by the circle mouth in [n ξ, (n+1) ξ],

Mean the vehicle flowrate that i highway section rolled away from by the circle mouth in [n ξ, (n+1) ξ], v _ind(i, n) means i highway section variable display board display speed in [n ξ, (n+1) ξ];

B. set up the equivalent speed model: $V_e[{\mathrm{\ρ}}_i^n,v_{\mathrm{ind}}(i,n)]=\frac{v_{\mathrm{ind}}(i,n)(1-{\mathrm{\ρ}}_i^n/{\mathrm{\ρ}}_{\mathrm{jam}})}{1+E{({\mathrm{\ρ}}_i^n/{\mathrm{\ρ}}_{\mathrm{jam}})}^4},$

In formula, E is constant;

C. write the PREDICTIVE CONTROL module based on improving the LWR model in FPGA, comprise data reception module, control program is selected and the data allocations module, computing module 1-computing module N, synchronization module, data outputting module, road is divided into to N highway section, the forecasting traffic flow computing module that computing module 1-computing module N is used the floating point arithmetic device to combine for the Difference Method according to aforementioned partial differential equations, the data flow of PREDICTIVE CONTROL module is: traffic flow data (the traffic flow density in each highway section that data reception module reception host computer transmits, vehicle average velocity), then passing to control program selects and the data allocations module, control program is selected and the data allocations module is determined traffic bottlenecks according to these data, and formulation regulation and control scheme, then by enable signal, control program and traffic flow data are passed to each computing module, each computing module is predicted and result is deposited in to register traffic flow density and vehicle average velocity simultaneously after receiving enable signal, modules is passed to synchronization module to calculating end signal separately after calculating and finishing, synchronization module completes and calculates predicting the outcome of rear transmitted signal informing case selection and data allocations module reception traffic flow data at all computing modules, proceed prediction, at predicted time T _cin, if traffic bottlenecks are removed, adopt this scheme to be regulated and controled actual traffic, if can not remove, control program select and the data allocations module according to traffic flow data and last time regulation and control scheme formulate new regulation and control scheme, and traffic flow data and regulation and control scheme are passed to each computing module, re-start prediction, repeatedly predict and adjust regulation and control scheme after select a suitable regulation and control scheme output to be regulated and controled traffic bottlenecks, and the highway section regulated and controled is in time T _cinside no longer regulated and controled, then continue traffic is predicted, find new traffic bottlenecks, and controlled,

Determine in described step 3 that traffic bottlenecks the method that it is controlled are: solve || η (x, t) || _∞=η _m(x _m, t _m), work as η _mBe greater than given threshold value η _MThe time, highway section x is described _mAt t _mConstantly will become traffic bottlenecks, at t _m-T ₀The x of the moment to vehicle heading _mFront and back enter, go out that circle mouth and variable information display board carry out speed limit (highway section, bottleneck road the place ahead Speed Reduction, highway section, rear speed improves), restriction enters bottleneck road even forces to roll away from bottleneck road; Or solve || σ (x, t) || _∞=σ _m(x _m, t _m), work as σ _mBe greater than given threshold value σ _MThe time, highway section x is described _mAt t _mConstantly will become traffic bottlenecks, at t _m-T ₁The x of the moment to vehicle heading _mFront and back go out, enter that circle mouth and variable information display board carry out speed limit (highway section, bottleneck road the place ahead Speed Reduction, highway section, rear speed improves), restriction enters bottleneck road even forces to roll away from bottleneck road;

T in formula ₀, T ₁For the time that applies in advance control makes || η (x, t) || _∞=η _m(x _m, t _m)≤η _M, || σ (x, t) || _∞=σ _m(x _m, t _m)≤σ _M, η _M, σ _MBe respectively the positive number made according to roading density maximum saturation, friction;

The priority principle of controlling is: 1. at first by the variable information display board, adjust highway section speed, the car speed that enters bottleneck road is reduced, the car speed that rolls bottleneck road away from improves, 2. in the time of only by variable information display board adjustment highway section speed, can not reaching the control index, by the restriction of circle mouth, enter the bottleneck road flow and adjust highway section speed with the variable information display board and controlled simultaneously, 3. adjust highway section speed and control to reach simultaneously and control while requiring when enter bottleneck road flow and variable information display board by circle mouth restriction, be controlled at an interrupting time forced portion minute highway section vehicle by the circle mouth and roll road away from, circle mouth restriction is entered to the bottleneck road vehicle flowrate and the variable information display board is adjusted highway section speed to reach the control index request simultaneously.

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