CN102938207B - On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved light water reactor (LWR) model - Google Patents
On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved light water reactor (LWR) model Download PDFInfo
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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
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 solving, 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 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 variable information display board to carry out two kinds of speed restriction and the controls of circle mouth, in order effectively to relieve traffic congestion, improve the service efficiency of highway, and the means that often use information display board to issue and control as transport information; Conventionally, information display board and variable speed-limit sign are issued as the important information 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 driver, carry out the publicity of traffic law, traffic knowledge, reach and reduce the impact that highway reappearance is blocked, reduced the non-reappearance accident of highway, improve traffic safety; Described in document " Hai Yilatibala carries; 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; Information display board adopts different forms according to the difference of the place arranging and object; One is mounted on main line, carries out main line induction and outlet induction, and the traffic that shows section, front with character style is as unimpeded, crowded, delay etc., thereby makes driver can turn to surface road, avoids crowded district; Another kind is arranged near ring road entrance, and the queue length of ring road porch and crowded prediction case are reported to driver, also the traffic conditions on contiguous main line can be shown to the driver on ring road entrance, thereby induce for they provide reasonably; In addition, in the situation that road congestion risk is very high, can control the input of circle mouth, even force some vehicles to roll highway away from road circle mouth, to avoid the generation of blocking up; But, these schemes, the induction of super expressway entrance, the induction of road main line, the induction of road way outlet are only demarcated according to information requirement, there is no 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 section that the result of regulation and control regulates and controls is often unimpeded, but traffic jam phenomenon occurs in non-regulation and control section.
In order to analyse in depth traffic system, a large amount of scholar's research traffic flow model both at home and abroad, 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 made up 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 with the average density of vehicle
, average velocity v and flow q portray traffic flow, 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 problem such as effect of road geometry modification provides 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 the choosing and middle space of studied road, numerical method
, the time
discrete steps relevant.So macroscopic traffic flow is suitable for the traffic flow problem of the traffic system of processing a large amount of vehicle compositions; This class model is used for discussing the traffic behavior of blocked road by Most scholars in the world.
Find through retrieval, number of patent application 200810117959.8, open day on January 14th, 2009, record in " a kind of control method at traffic bottlenecks place and device ", the method is by arranging buffer zone, the rule of travelling of vehicle in 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 section may become traffic bottlenecks, and therefore, the method has limitation; Document " Zeng Guangxiang. analysis, control and the simulation of road traffic bottleneck; 2010; Guangxi University's Master's thesis " take LWR model as basis, analyze 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 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 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 traffic section, not bottleneck forecasting and traffic control are not combined real-time monitoring is carried out in traffic 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
Be difficult in actual highway or blocked road, traffic bottlenecks be carried out the technological deficiency of 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 LWR model, variable information display board is dissolved in LWR model, by improved LWR model, highway or blocked road entirety are carried out to forecast analysis based on FPGA platform, find road bottleneck according to the state variable of definition, and then provide the control program of the control of circle mouth and variable information display board, and these control programs are according to priority brought into 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 on-line prediction regulation and control.
The technical solution adopted for the present invention to solve the technical problems: based on the online traffic bottlenecks forecast Control Algorithm of FPGA and improvement LWR model, be characterized in comprising the following steps:
Step 1, according to LWR model:
In formula, t is the time, and x is distance between current location and road starting point,
traffic flow density and the function for x, t,
, v is vehicle average velocity and the function for x, t,
,
the rate of change of the density function causing for the vehicle flowrate that enters or roll away from due to circle mouth,
the vehicle flowrate being entered by circle mouth for t moment, x section,
the vehicle flowrate being rolled away from by circle mouth for t moment, x section,
,
for sailed into the normal vehicle flowrate rolling away from by circle mouth,
for circle mouth control No entry flow reducing amount that expressway causes,
for the flow increment that causes of outgoing vehicles is forced in the control of circle mouth,
for equivalent speed and and free stream velocity
with traffic flow density
relevant;
Variable display board display speed is incorporated to LWR model, with variable display board display speed
replace the free stream velocity in equivalent speed
, the LWR model being improved is as follows:
In formula,
represent the speed that variable information display board shows;
Step 2, two new state variables of definition
,
, 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,
traffic flow density while occurring blocking for traffic;
The improved LWR model that step 3, a. obtain according to step 1, represents differential term and omits higher order term by difference scheme, obtains:
In formula:
for the step-length to t differential, i.e. sampling period, h is differential step-length to x, i.e. each road section length of dividing, o (
) be
high-order infinitesimal, the high-order infinitesimal that o (h) is h, is divided into multiple sections road,
be that i section is at [n
, (n+1)
] interior traffic flow density,
be that i section is at [n
, (n+1)
] average velocity of interior vehicle;
The difference form of the LWR model being improved is:
In formula,
represent that i section is at [n
, (n+1)
] the interior vehicle flowrate being entered by circle mouth,
represent that i section is at [n
, (n+1)
] the interior vehicle flowrate being rolled away from by circle mouth,
represent that i section is at [n
, (n+1)
] interior variable display board display speed;
B. set up equivalent speed model:
,
In formula, E is constant;
C. in FPGA, write the PREDICTIVE CONTROL module based on improving LWR model, as shown in Figure 1, comprise data reception module, control program is selected and data allocations module, computing module 1-computing module N, synchronization module, data outputting module, road is divided into N section, the corresponding computing module in each section, in figure, computing module 1-computing module N is the forecasting traffic flow computing module that uses floating point arithmetic device to combine according to the Difference Method of aforementioned partial differential equations, the data flow of PREDICTIVE CONTROL module is: the traffic flow data in each section that data reception module reception host computer transmits, wherein traffic flow data comprises traffic flow density, vehicle average velocity, then passing to control program selects and data allocations module, control program is selected and data allocations module is determined traffic bottlenecks according to these data, and formulate 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 calculates and finishes rear calculating end signal separately to be passed to synchronization module, 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
in, if traffic bottlenecks are removed, adopt this scheme to regulate and control actual traffic, if can not remove, control program select and 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 regulate and control traffic bottlenecks, and the section having regulated and controled is in the time
inside no longer regulate and control, then continue traffic to predict, find new traffic bottlenecks, and control,
In described step 3, determine that traffic bottlenecks the method that it is controlled are: solve
, when
be greater than given threshold value
time, section is described
?
moment will become traffic bottlenecks, exist
moment is to vehicle heading
front and back enter, go out circle mouth and variable information display board carries out speed limit section, bottleneck road front Speed Reduction, section, rear speed is improved, and restriction enters bottleneck road even forces to roll away from bottleneck road; Or solve
, when
be greater than given threshold value
time, section is described
?
moment will become traffic bottlenecks, exist
moment is to vehicle heading
front and back go out, enter circle mouth and variable information display board carries out speed limit section, bottleneck road front Speed Reduction, section, rear speed is improved, and restriction enters bottleneck road even forces to roll away from bottleneck road;
In formula
,
for the time that applies in advance control makes
,
,
,
be respectively the positive number making according to roading density maximum saturation, friction;
The priority principle of controlling is: 1. first adjust section speed by variable information display board, the car speed that enters bottleneck road is reduced, the car speed that rolls bottleneck road away from improves, 2. only can not reach control index by variable information display board adjustment section speed time, enter bottleneck road flow and adjust section speed with variable information display board and control simultaneously by the restriction of circle mouth, 3. adjust 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 point section vehicle by circle mouth and roll road away from, circle mouth restriction is entered to bottleneck road vehicle flowrate and variable information display board is adjusted section speed to reach control index request simultaneously.
The invention has the beneficial effects as follows: due to the equivalent speed of improving in LWR model, variable information display board display speed is dissolved in equivalent speed, by improved LWR model, highway or blocked road entirety are carried out to forecast analysis based on FPGA platform, find road bottleneck according to the state variable of definition, and then provide the control program of the control of circle mouth and variable information display board, and these control programs are according to priority brought into forecast model, to guarantee that regulation and control scheme is practical, and then solve the technical matters that existing method is difficult in actual highway or blocked road, traffic bottlenecks be carried out on-line prediction regulation and control.
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 not having traffic bottlenecks to produce, the free stream velocity that control program allows for variable display board demonstration road, the control of circle mouth does not limit input and output, the traffic flow density by traffic flow density, vehicle average velocity, variable display board display speed and circle mouth control program to each section and vehicle average velocity prediction a period of time
(
get
,
between large value), and judge whether to occur traffic bottlenecks, if there are not traffic bottlenecks, use current control program to regulate and control, adjust variable display board display speed and circle mouth control program according to aforementioned priority principle if there is bottleneck, and continue prediction a period of time
if traffic bottlenecks can not be removed, continue to adjust control program, until find a kind of control program can transport solution bottleneck problem, and adopt this scheme to control traffic bottlenecks, its detailed method is as follows:
1. according to LWR model:
In formula, t is the time, and x is distance between current location and road starting point,
traffic flow density and the function for x, t,
, v is vehicle average velocity and the function for x, t,
,
the rate of change of the density function causing for the vehicle flowrate that enters or roll away from due to circle mouth,
the vehicle flowrate being entered by circle mouth for t moment, x section,
the vehicle flowrate being rolled away from by circle mouth for t moment, x section,
,
for sailed into the normal vehicle flowrate rolling away from by circle mouth,
for circle mouth control No entry flow reducing amount that expressway causes,
for the flow increment that causes of outgoing vehicles is forced in the control of circle mouth,
for equivalent speed and and free stream velocity
with traffic flow density
relevant;
Variable display board display speed is incorporated to LWR model, with variable display board display speed
replace the free stream velocity in equivalent speed
, the LWR model being improved is as follows:
In formula,
represent the speed that when x is in time t, variable information display board shows;
2. two new state variables of definition
,
, 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,
traffic flow density while occurring blocking for traffic;
3. according to the improved LWR model obtaining in 1, represent differential term and omit higher order term by difference scheme, obtain:
In formula:
for the step-length to t differential, i.e. sampling period, h is differential step-length to x, i.e. each road section length of dividing, o (
) be
high-order infinitesimal, the high-order infinitesimal that o (h) is h,
(x, t) is t moment x place's traffic flow density, and v (x, t) is the average velocity of t moment x place vehicle, and road is divided into multiple sections,
be that i section is at [n
, (n+1)
] interior average vehicle flow density,
be that i section is at [n
, (n+1)
] average velocity of interior vehicle;
The difference form of the LWR model being improved is:
In formula,
represent that i section is at [n
, (n+1)
] the interior vehicle flowrate being entered by circle mouth,
represent that i section is at [n
, (n+1)
] the interior vehicle flowrate being rolled away from by circle mouth,
represent that i section is at [n
, (n+1)
] interior variable display board display speed;
4. set up equivalent speed model:
,
In formula, E is constant;
5. in FPGA, write the PREDICTIVE CONTROL module based on improving LWR model, 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, communicate by letter by wireless GPRS with other road information acquisition module (host computer), road is divided into 40 sections, as shown in Figure 1, comprise data reception module, control program is selected and 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 of computing module 1-computing module 40 for using floating point arithmetic device to combine according to the Difference Method of aforementioned partial differential equations, the data flow of PREDICTIVE CONTROL module is: the traffic flow data in each section that data reception module reception host computer transmits, wherein traffic flow data comprises traffic flow density, vehicle average velocity, then passing to control program selects and data allocations module, control program is selected and data allocations module is determined traffic bottlenecks according to these data, and formulate 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 calculates and finishes rear calculating end signal separately to be passed to synchronization module, 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
in, if traffic bottlenecks are removed, adopt this scheme to regulate and control actual traffic, if can not remove, control program select and 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 regulate and control traffic bottlenecks, and the section having regulated and controled is in the time
inside no longer regulate and control, then continue traffic to predict, find new traffic bottlenecks, and control,
6. the method for finding traffic bottlenecks in above-mentioned 5 and bottleneck is regulated and controled is: solve
, when
be greater than given threshold value
time, section is described
?
moment will become traffic bottlenecks, exist
moment is to vehicle heading
front and back enter, go out circle mouth and variable information display board carries out speed limit section, bottleneck road front Speed Reduction, section, rear speed is improved, and restriction enters bottleneck road even forces to roll away from bottleneck road; Or solve
, when
be greater than given threshold value
time, section is described
?
moment will become traffic bottlenecks, exist
moment is to vehicle heading
front and back go out, enter circle mouth and variable information display board carries out speed limit section, bottleneck road front Speed Reduction, section, rear speed is improved, and restriction enters bottleneck road even forces to roll away from bottleneck road;
In formula
,
for the time that applies in advance control makes
,
,
,
be respectively the positive number making according to roading density maximum saturation, friction;
The priority principle of controlling is: 1. first adjust section speed by variable information display board, the car speed that enters bottleneck road is reduced, the car speed that rolls bottleneck road away from improves, 2. only can not reach control index by variable information display board adjustment section speed time, enter bottleneck road flow and adjust section speed with variable information display board and control simultaneously by the restriction of circle mouth, 3. adjust 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 point section vehicle by circle mouth and roll road away from, circle mouth restriction is entered to bottleneck road vehicle flowrate and variable information display board is adjusted section speed to reach control index request simultaneously.
Claims (1)
1. the online traffic bottlenecks forecast Control Algorithm based on FPGA and improvement LWR model, is characterized in that comprising the following steps:
Step 1, according to LWR model:
In formula, t is the time, and x is distance between current location and road starting point,
traffic flow density and the function for x, t,
, v is vehicle average velocity and the function for x, t,
,
the rate of change of the density function causing for the vehicle flowrate that enters or roll away from due to circle mouth,
the vehicle flowrate being entered by circle mouth for t moment, x section,
the vehicle flowrate being rolled away from by circle mouth for t moment, x section,
,
for sailed into the normal vehicle flowrate rolling away from by circle mouth,
for circle mouth control No entry flow reducing amount that expressway causes,
for the flow increment that causes of outgoing vehicles is forced in the control of circle mouth,
for equivalent speed and and free stream velocity
with traffic flow density
relevant;
Variable display board display speed is incorporated to LWR model, with variable display board display speed
replace the free stream velocity in equivalent speed
, the LWR model being improved is as follows:
In formula,
represent the speed that variable information display board shows;
Step 2, two new state variables of definition
,
, 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,
traffic flow density while occurring blocking for traffic;
The improved LWR model that step 3, a. obtain according to step 1, represents differential term and omits higher order term by difference scheme, obtains:
In formula:
for the step-length to t differential, i.e. sampling period, h is differential step-length to x, i.e. each road section length of dividing, o (
) be
high-order infinitesimal, the high-order infinitesimal that o (h) is h, is divided into multiple sections road,
be that i section is at [n
, (n+1)
] interior traffic flow density,
be that i section is at [n
, (n+1)
] average velocity of interior vehicle;
The difference form of the LWR model being improved is:
In formula,
represent that i section is at [n
, (n+1)
] the interior vehicle flowrate being entered by circle mouth,
represent that i section is at [n
, (n+1)
] the interior vehicle flowrate being rolled away from by circle mouth,
represent that i section is at [n
, (n+1)
] interior variable display board display speed;
B. set up equivalent speed model:
,
In formula, E is constant;
C. in FPGA, write the PREDICTIVE CONTROL module based on improving LWR model, comprise data reception module, control program is selected and data allocations module, computing module 1-computing module N, synchronization module, data outputting module, road is divided into N section, computing module 1-computing module N is the forecasting traffic flow computing module that uses floating point arithmetic device to combine according to the Difference Method of aforementioned partial differential equations, the data flow of PREDICTIVE CONTROL module is: the traffic flow data in each section that data reception module reception host computer transmits, wherein traffic flow data comprises traffic flow density, vehicle average velocity, then passing to control program selects and data allocations module, control program is selected and data allocations module is determined traffic bottlenecks according to these data, and formulate 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 calculates and finishes rear calculating end signal separately to be passed to synchronization module, 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
in, if traffic bottlenecks are removed, adopt this scheme to regulate and control actual traffic, if can not remove, control program select and 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 regulate and control traffic bottlenecks, and the section having regulated and controled is in the time
inside no longer regulate and control, then continue traffic to predict, find new traffic bottlenecks, and control,
In described step 3, determine that traffic bottlenecks the method that it is controlled are: solve
, when
be greater than given threshold value
time, section is described
?
moment will become traffic bottlenecks, exist
moment is to vehicle heading
front and back enter, go out circle mouth and variable information display board carries out speed limit section, bottleneck road front Speed Reduction, section, rear speed is improved, and restriction enters bottleneck road even forces to roll away from bottleneck road; Or solve
, when
be greater than given threshold value
time, section is described
?
moment will become traffic bottlenecks, exist
moment is to vehicle heading
front and back go out, enter circle mouth and variable information display board carries out speed limit section, bottleneck road front Speed Reduction, section, rear speed is improved, and restriction enters bottleneck road even forces to roll away from bottleneck road;
In formula
,
for the time that applies in advance control makes
,
,
,
be respectively the positive number making according to roading density maximum saturation, friction;
The priority principle of controlling is: 1. first adjust section speed by variable information display board, the car speed that enters bottleneck road is reduced, the car speed that rolls bottleneck road away from improves, 2. only can not reach control index by variable information display board adjustment section speed time, enter bottleneck road flow and adjust section speed with variable information display board and control simultaneously by the restriction of circle mouth, 3. adjust 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 point section vehicle by circle mouth and roll road away from, circle mouth restriction is entered to bottleneck road vehicle flowrate and variable information display board is adjusted section speed to reach control index request simultaneously.
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|---|---|---|---|
| CN201210470897.5A CN102938207B (en) | 2012-11-19 | 2012-11-19 | On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved light water reactor (LWR) model |
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|---|---|---|---|
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|---|---|
| CN102938207A CN102938207A (en) | 2013-02-20 |
| CN102938207B true CN102938207B (en) | 2014-07-02 |
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