CN111091295A - Urban area boundary control system - Google Patents
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Abstract
An urban area boundary control system comprising: the data module is used for selecting various basic data representing the traffic state, preprocessing the basic data and transmitting the processed basic data to the state evaluation module; the state evaluation module is used for performing off-line training on historical data to obtain the average speed of the traffic capacity road network, calculating real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module; the control scheme module is used for determining the starting or ending of the boundary control according to the judgment result of the state evaluation module, issuing a corresponding timing scheme to the signal system at the interception point position of the calculation region, and transmitting various information to the interactive visualization module; the signal system is used for controlling the traffic signals according to the timing scheme; and the interactive visualization module is used for displaying various information and manually determining the ending of the boundary control.
Description
Technical Field
The invention belongs to the field of intelligent traffic, and relates to an urban area boundary control system.
Background
The development of national economy and the progress of science and technology promote the expansion of urban areas, large-scale new cities, groups and the like appear around more and more big cities, the connection between city areas and city groups is increasingly close, the traffic demand in cities and among cities is rapidly increased, in addition, the motorization degree of urban vehicles enters a higher level, traffic jam often occurs not only at intersections or road sections, but also evolves to lines of a plurality of road sections from points of the intersections or the road sections, even influences crossed routes and develops into the traffic problem of regional level. According to research, regional traffic congestion is closely related to traffic demand within a region. The concept of traffic capacity also exists in the area category, and when the traffic demand of the area exceeds the traffic capacity, congestion can occur. Therefore, according to the traffic capacity of the region, the demand of the regional road network is effectively regulated, and the key of relieving and even preventing regional traffic jam is realized by controlling the traffic volume of the vehicle, particularly the traffic volume of the vehicle entering the core region of the region, in the time period with large demand.
In the aspect of regional-oriented traffic management, domestic experience is used for reference, and macroscopic policy means such as automobile tail number restriction, congestion pricing and peak shifting are generally adopted to limit the total traffic of regional road networks, so that a series of effects are obtained. However, the time interval and the range of the macro policy means are not suitable for frequent change and lack of flexibility, and meanwhile, the policy can not be elaborated, so that the supply and demand balance relation of the microscopic traffic flow and the difference between urban areas are difficult to consider, and the specific problem is difficult to solve.
At present, more and more cities recognize the function and importance of advanced urban traffic control systems, the urban traffic control systems are deployed or planned and deployed, and signal optimization services are also a basis for development, so that more traffic problems can be solved. Under the premise, the invention provides an urban area boundary control system, which analyzes the area traffic condition from the angle of the area, and utilizes the traffic control system to perform boundary control so as to improve the area traffic condition.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides an urban area boundary control system which can make a boundary control strategy according with the current area traffic state, identify signal point positions suitable for area boundary interception and adjust the signal timing of the boundary point positions.
The technical scheme adopted by the invention is as follows:
an urban area boundary control system, characterized by: the method comprises the following steps:
the data module is used for selecting various basic data representing the traffic state, preprocessing the basic data and transmitting the processed basic data to the state evaluation module, wherein the basic data comprises historical data and real-time data;
the state evaluation module is used for performing off-line training on historical data to obtain the average speed of the traffic capacity road network, calculating real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module;
the control scheme module is used for determining the starting or ending of the boundary control according to the judgment result of the state evaluation module, issuing a corresponding timing scheme to the signal system at the interception point position of the calculation region, and transmitting various information to the interactive visualization module;
the signal system is used for controlling the traffic signals according to the timing scheme;
and the interactive visualization module is used for displaying various information and manually determining the ending of the boundary control.
Further, the data module includes:
the basic data unit is used for defining basic data, classifying the basic data and calling the basic data;
and the data processing unit is used for preprocessing basic data, wherein the preprocessing comprises completion, repair, matching, fusion, standardization and analysis.
Further, the state evaluation module includes:
the regional property unit is used for performing off-line training on historical data to obtain the average speed of the traffic capacity road network;
and the real-time state unit is used for calculating the real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module.
Further, the regional property unit adopts a macroscopic traffic index-road network average speed V to represent regional requirements, and regional total outflow Qout_totalAs the representation of the region state, when the total regional outflow is highest in the history state, the average speed of the road network is calculated as the average speed of the road network reaching the traffic capacity through the history data, and is defined as the average speed V of the traffic capacity road networkcap。
Further, the control scheme module includes:
the system control unit is used for realizing the comparison between the real-time state unit evaluation information and the historical traffic capacity and determining the opening/closing state of the boundary control according to the property of a Macroscopic Fundamental Diagram (MFD);
the device comprises an intercepting point selecting unit, a traffic flow judging unit and a traffic flow judging unit, wherein the intercepting point selecting unit is used for selecting a limited number of intersections with large entering area flow and good traffic states of upstream road sections as intercepting points;
and the timing scheme unit is used for outputting a corresponding timing scheme according to the interception point position to perform boundary control.
Further, in the system control unit,
boundary control do not open/end conditions:
V≥Vter
or
Vact＜V＜Vter
Boundary control on condition:
V≤Vact
wherein v is the average speed of the road network,
V＝∑(vroadsect·qroadsect)/∑qroadsect
wherein v isroadsectThe speed of the road in the area is taken as the speed of the road; q. q.sroadsectIs the flow of the road section in the area; vactOpening threshold for boundary control, Vact＝0.85Vcap；VterFor boundary control of the end threshold, Vcat＝0.95Vcap。
Further, the intercepting point selecting process of the intercepting point selecting unit is as follows:
(1) sorting the boundary point positions from large to small according to the real-time inflow by means of real-time flow and speed data, selecting n boundary point positions with the largest real-time inflow,
n＝F(Lamp)
f (Lamp) is a function of Lamp, fitting is carried out by actual experience, and the Lamp is the number of intersections controlled by signals in the area;
(2) sequentially judging whether each selected point has an in-out region simultaneous-release phase, whether the ratio of the out-flow to the in-flow of the selected point is greater than a threshold value, and whether the speed state of an upstream road section is congested or severely congested;
(3) if the judgment is negative, selecting the selected point location as a cut-off point location; and if the same amplification phase exists but the upstream road section is blocked or seriously blocked or the same amplification phase does not exist but the ratio of the outflow to the inflow is less than or equal to the threshold value, the selected point cannot be used as the interception point, and the boundary point of the (n + 1) th position is selected for judgment.
Further, the timing scheme unit adopts a hierarchical control frame to perform boundary control and is divided into an upper control layer and a lower control layer;
the upper control layer adopts a PI regulator with multivariable feedback, and the control algorithm is as follows:
qin(t)＝qin(t-1)+Ki*[Vcap-V(t)]-Kp*[V(t)-V(t-1)]
wherein: t is the time granularity;
qin(t)、qin(t-1) total inflow at time t and time t-1, respectively;
Vcapv (t) and V (t-1) are respectively the historical maximum road network average speed, the t-time road network average speed and the t-1-time road network average speed;
Vcap-V (t): the deviation of the control quantity needs to be corrected, and when the traffic flow state in the area is worse, the larger the value is, the larger the traffic quantity needs to be reduced;
v (t) -V (t-1): representing the evolution of the state in the area, if V (t) -V (t-1) <0, the traffic state in the area continuously deteriorates, and the limited traffic volume needs to be increased; if V (t) -V (t-1) >0, the regional congestion is relieved, and the entering traffic volume can be relaxed;
Ki: non-negative parameter, control intensity, KiThe larger the control intensity is, the better the effect is; kiThe smaller the control quantity in unit time is, the slower the regional traffic flow state changes;
Kp: non-negative parameters evolve according to the state in the region, if congestion in the region begins to relieve, the compressed traffic volume can be reduced, and if the congestion still deteriorates, the compression volume needs to be increased;
for each interception point location n, distributing according to the traffic capacity of the road section and the traffic capacity of all the interception point locations, and transmitting the data to a lower control layer;
qn(t)＝qin(t)·Nn/Ntot
wherein q isn(t) is the calculated inflow of the interception point n at the time t;
Nnthe number of lanes in the direction of the current interception point entering the area is determined;
Ntotthe sum of the number of lanes in the direction of all the interception point positions entering the area;
the lower control layer adopts maximum pressure control on the main trunk network, and the control algorithm is as follows:
for the interception point n, introducing the state value s of each road section at the time tz(t) the state value is the speed v of the road section at the current time of the road sectionz(t) and historical maximum speed v over a monthz，maxA ratio of (i) to (ii)
sz(t)＝vz(t)/vz，max
For the interception point n, the road section in the entering area direction is set as z, and the set of z is set as InThen, the set flow rate of z is:
given historical data, real-time measured indicators or predicted speed, the pressure p exerted on the z road segment at the start of the cycle (time t)z(t) is calculated as follows;
where ω is the downstream section of the section in each direction of the entering area, onIs a set of omega;
vz，maxis the historical maximum speed for road segment z;
vz(k) is the set speed for the road segment z at time t,
vz(k)＝qz(t)·vz，max/qz，max
qz，maxhistorical maximum flow of the z road section;
vω(t) is the speed of the downstream road section omega at time t;
Lz，Lωthe lengths of the stretch z and the downstream stretch ω, respectively, so that the pressure of a short stretch at a certain speed is greater than the pressure of a stretch at a longer but same speed;
βz，ωgreen ratio, which is the phase of ω steered by road segment z;
calculating pressure of each inlet lane at intersection n (i.e. calculating)
) Each phase j of the crossing is applied with a pressure calculation as follows, and the indicator can be used to calculate different split ratios for the crossing;
wherein j is the phase of n intersections, FnIs a set of phases;
vjall inlet channels contained in phase j.
At the end of each cycle, the green time is assigned in proportion to the pressure calculated for each phase, the split calculation method:
wherein λ isn，jAnd (t) is the green signal ratio of the j phase at the n intersection at the time t.
Further, the signal system adopts a three-layer control strategy and a single-two-way trunk-coordinated adaptive control logic SCATS signal system, which comprises:
the signal control equipment is used for rolling an issued object of the optimization scheme;
an open interface for command transfer communications;
and the detector unit is used for returning the traffic state data.
Further, the interaction visualization module includes:
a system information unit for outputting a trigger time and a duration;
the regional status information unit is used for displaying the change condition and the status level of the real-time regional status information index;
the control point location information unit is used for displaying point location information participating in control optimization in an image form, reflecting whether the intersection is optimized or not, and checking intersection number information, monitoring conditions and an optimization scheme by clicking; and displaying the number of the intersections participating in optimization and the proportion of the intersections participating in optimization to the total intersections.
The invention has the beneficial effects that: the boundary control strategy according with the current regional traffic state can be formulated, the signal point location suitable for regional boundary interception is identified, and the signal timing of the boundary point location is adjusted.
Drawings
Fig. 1 is a schematic view of the frame structure of the present invention.
FIG. 2 is a flow diagram of the control scheme module of the present invention.
Fig. 3 is a schematic flow diagram of the intercept point selection unit of the present invention.
Fig. 4 is a flow diagram of a timing scheme unit of the present invention.
Detailed Description
The present invention is further illustrated by the following examples, which are not intended to limit the invention to these embodiments. It will be appreciated by those skilled in the art that the present invention encompasses all alternatives, modifications and equivalents as may be included within the scope of the claims.
Referring to fig. 1 to 4, the present embodiment provides an urban area boundary control system, which can make a boundary control strategy according with a current area traffic state, identify a signal point location suitable for area boundary interception, and adjust the timing of a boundary point location signal, and includes five modules, namely a data module, a state evaluation module, a control scheme module, a signal system, and an interactive visualization module.
In order to realize a more scientific, reasonable and effective boundary control signal scheme, traffic state data and traffic state influence data need to be comprehensively considered, so that the regional state assessment and the control scheme are formulated by utilizing the integration of microscopic data. Since the evaluation is of the regional state, the integrity and accuracy of microscopic data have high requirements, and the data needs to be fully preprocessed.
The data module is used for selecting various basic data representing traffic states, preprocessing the basic data and transmitting the processed basic data to the state evaluation module, wherein the basic data comprises historical data and real-time data. The data module mainly comprises a basic data unit and a data processing unit. The basic data unit is used for defining basic data, classifying the basic data and calling the basic data; wherein the underlying data defines: the basic data unit stores various data capable of representing traffic states, including but not limited to signal system operation records of signal control intersections of cities, such as control scheme data, manual operation records, log data and the like in each period; detector data such as flow and saturation of all signal control intersections in a city; the system comprises internet data, wherein all data which are related to traffic operation and can be processed and return information representing traffic states are collectively called as traffic state data, such as speed data and track data of the city universe, and the data mainly come from internet companies, such as map operators, map navigation operators, trip operators and the like; geographic information data, which mainly comes from the traffic management department of cities.
Basic data categories: the basic data are divided into historical data and real-time data according to the using condition, the historical data are mainly used for off-line training, and the data storage amount is at least 3 months of data. The real-time data is mainly use data of the algorithm in the process of deploying the algorithm to the actual production environment or input data of the algorithm, the data must be real-time data, and the real-time performance is guaranteed to be less than 5 minutes. The database content and format of the historical data and the real-time data need to be consistent.
Calling of basic data: the data transmission and the data use of the invention generally adopt two modes, the mode of directly inquiring the database statement is generally adopted for the case of small data quantity of the data table, and the interface mode is adopted for data transmission for the case of large data quantity of the data table and the case of more data table connection, namely more requested times of the data.
The data processing unit is used for preprocessing basic data, and the preprocessing comprises completion, repair, matching, fusion, standardization and analysis. The process of data preprocessing is automatically completed by an algorithm no matter complete training data is constructed or real-time data of the online deployment application is constructed. For the abnormal condition of the offline historical data, the data preprocessing is mainly used for performing data availability processing on the integrated data; for any data abnormal condition occurring in the online process, the invention does the necessary elimination processing through the algorithm part.
The data completion mainly aims at the situation of data shortage caused by various reasons in short time, and the completion method is to use data with the same traffic situation, such as: the traffic situation of the same period of the last same day is considered to be the same.
The data restoration only can carry out restoration processing aiming at the condition that data are lost for a long time, such as the data are lost caused by the damage of a detector, the restoration method mainly calculates the flow rate of all upstream intersections flowing to the lane, analyzes and sets weights aiming at the level of the intersection, the level of the lane, the function of the lane and the flow rate born by the function of the lane, and calculates the flow rate of the lost lane.
And matching the data with different space-time dimensionality data according to the format of the training data. If the control scheme data and the speed data are matched, the time: the control scheme data is returned according to the intersection period, and the time delay is within 5 minutes. Speed data returns a set of data every 2 minutes; spatially: the control scheme data refers to the operation records of the intersection system, the speed data is link speed values which are defined by the operator according to a certain rule, the speed values are related to speed grade division, the data may be different in quantity, each physically significant road section may correspond to a plurality of link speeds, and according to the understanding of traffic service, the most important road section is close to the intersection, and then the most important road section is close to the intersection sequentially.
The data fusion comprises data layer fusion and decision layer data fusion of feature layer data fusion. The data layer is the fusion directly carried out on the acquired original data layer, and the data is integrated and analyzed before the original acquisition of the detector data is preprocessed. The feature layer fusion belongs to the fusion of middle layers, and firstly performs feature extraction (features can be edges, directions, speeds and the like of targets) on original information from a sensor, and then performs comprehensive analysis and processing on the feature information. The decision layer fusion observes the same target through different types of sensors, and each sensor locally completes basic processing including preprocessing, feature extraction, recognition or judgment to establish a preliminary conclusion on the observed target. And then, performing decision layer fusion judgment through correlation processing to finally obtain a joint inference result.
And (4) standardizing data, including cleaning abnormal data, processing irregular data and constructing a training data set according to a data format required by an algorithm. The abnormal data comprises the conditions that the speed data is a negative value, the speed data is 0 for a long time, the number of phases of the control scheme data is abnormally changed, and the like, the control scheme data returns two groups of data at the same time, and the like, and for different conditions, the data is corrected according to different principles by data standardization. And if the speed data selects the same traffic situation data for correction, controlling the reason of the data analysis of the scheme, and deleting the irregular data. The training data is mainly from correct complete matching data, mainly comprising lane-level split and corresponding speed data.
In traffic control, the evaluation of the traffic state is a condition for making a control strategy, and reliable state evaluation can reduce control iteration and improve control efficiency. The state evaluation module is used for performing offline training on historical data to obtain the average speed of the traffic capacity road network, calculating real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module.
The invention carries out control optimization and adjustment based on the macroscopic basic graph of the regional road network. According to the research, the macroscopic road network traffic flow has the five attributes of time (t, time), space (s, space), type (ty, type), reason (r, reason) and degree (v, value), and determines the dynamic characteristics of the macroscopic traffic flow changing along with time. Although it is difficult to specifically describe such dynamic features in real time, the traffic flow distribution characteristics in the macro road network have certain regularity from a macro level. The traffic and occupancy data collected by all detectors in the whole road network are gathered to obtain a curve with low dispersion, and a similar parabolic relation exists between the weighted traffic completed by the traveling vehicles in the road network and the accumulated number of the vehicles in the network. The output quantity of the regional road network and the number of accumulated vehicles in the region are fitted to form an approximate quadratic curve relation, namely when the accumulated traffic quantity in the region is in an optimal critical range, the total output quantity of the region is maximum; if the accumulated vehicle number continues to increase and exceeds the optimal critical value, the road network outflow will rapidly decrease.
The state evaluation module of this embodiment includes: the regional property unit is used for performing off-line training on historical data to obtain the average speed of the traffic capacity road network; and the real-time state unit is used for calculating the real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module.
The influence factors of the macroscopic basic diagram mainly comprise traffic conditions, road conditions, control measures, selection behaviors and the like, so that in the application environment of the invention, the macroscopic basic diagram of the region is basically unchanged, and the specific properties of the macroscopic basic diagram can be obtained through data evaluation. The method mainly adopts an off-line training method, and utilizes historical data in the region to comprehensively obtain the indexes capable of obtaining the macroscopic basic diagram.
According to the principle of a macroscopic basic diagram, the number of vehicles in a region is taken as the region requirement, and the total region outflow (Q)out_total) As a zone state characterization. Calculating the total regional outflow and the number of vehicles in the region (N) in one month according to historical datatotal) The relationship of (1). When the total regional outflow is maximum, the number of vehicles in the road network is the traffic capacity of the road network (N)cap)。
It is worth noting that due to environmental limitations, data collected and transmitted by a data module usually has certain defects, such as serious data loss and the like, and has certain difficulties in application, multi-source data needs to be fused, physical meanings of existing data are deeply mined, the application range of a theory is expanded, state evaluation close to an ideal state evaluation is obtained as far as possible under limited external conditions, and the adopted state evaluation index may have a certain conversion relation with an index required by the theory. For example, the area flow data mostly comes from a detector of a signal system, and the detector is used to detect microscopic indexes such as flow of each road section, but the flow detection is affected by equipment hardware conditions, and more serious data loss may exist; at the same time, regional floating vehicle speed data provided by map providers is generally more comprehensive. In this case, it is difficult to obtain the number of vehicles in the road network, and other factors need to be considered.
Considering the relationship between the flow and the speed and popularizing the relationship into the road network, as the number of vehicles in the road network increases, the vehicles distributed to each road section gradually increase, and accordingly, the running speed of each road section decreases, so that the average speed of the road network decreases, and vice versa. Therefore, the regional property unit utilizes a macroscopic traffic index-road network average speed (V) to replace the number of vehicles in the road network to represent regional requirements, calculates the average speed of the road network when the total regional outflow is highest in a historical state, and defines the average speed of the road network with the traffic capacity as the average speed of the road network when the road network reaches the traffic capacity, namely the average speed (V) of the road network with the traffic capacitycap)。
The real-time status unit of the embodiment utilizes the real-time data to judge and output the control scheme. Calculating the average speed of the regional road network within a real-time certain time granularity range, taking 1 hour in the invention, comparing with the average speed of the traffic capacity road network, judging the range of the state, determining a control strategy according to the range, and calculating a control scheme to issue regulation and control.
The control scheme module described in this embodiment includes a system control unit, an intercept point selection unit, and a timing scheme unit, where the system control unit determines the start and end of boundary control, the intercept point selection unit selects an intercept point location according to a certain principle, and the timing scheme unit calculates a timing scheme of the intercept point location.
Specifically, the system control unit realizes comparison between real-time state evaluation information and historical traffic capacity, and determines the on/off state of the system according to the nature of the macroscopic basic graph of the regional road network.
Boundary control do not open/end conditions:
V≥Vter
or
Vact＜V＜Vter
Boundary control on condition:
V≤Vact
wherein v is the average speed of the road network,
V＝∑(vroadsect·qroadsect)/∑qroadsect
vroadsectthe speed of the road in the area is taken as the speed of the road;
qroadsectis the flow of the road section in the area;
Vactto control the turn-on threshold for the boundary, this implementation sets Vact＝0.85Vcap；
VterFor the boundary control end threshold value, the present embodiment sets Vact＝0.95Vcap。
Boundary control requires a reduction in the number of vehicles entering the area in the peripheral area, inevitably leading to the accumulation of peripheral vehicles, and thus, there is a certain limit to the selection of the intersection cut-off point in the boundary. Firstly, in order to avoid the formation of a congestion zone at the periphery, which affects normal traffic, the number of intersections at the interception point is not too large; secondly, the selected interception point is a key intersection with relatively large inflow, so that regional inflow can be effectively reduced, and interception reduction can be quickly realized; thirdly, the intercepting point should not be selected at the intersection with congestion at the upstream so as to avoid the serious consequences of congestion tracing and the like caused by the original congestion; and fourthly, the interception of the interception point is realized by reducing the timing of the inflow direction, for the intersections without the same release phase, the timing of the intersection in the direction of the area is correspondingly reduced, the influence effect of interception on the number of vehicles in the area is reduced by the reduction of outflow, and therefore, the intersections with the same release phase or the intersections with larger difference between outflow and inflow are selected.
In summary, the intercepting point selecting unit of the embodiment selects a limited intersection with large entering area flow and good traffic state of the upstream road segment as the intercepting point on the principle of effectiveness, convenience and relatively small influence on the periphery.
Firstly, with the help of data such as real-time flow, speed and the like, sequencing boundary points from large to small according to real-time inflow, and selecting n boundary points with the largest real-time inflow (calculating the range of n according to the size of the area scale).
n＝F(Lamp)
Wherein F (Lamp) is a function of Lamp, and is fit by practical experience, and Lamp is the number of intersections in the area controlled by signals. According to the experience of a certain urban area, the following formula can be considered,
n＝Lamp2/3.5*10-4+3.0714*(Lamp/50)+1。
and then, sequentially judging whether the selected point positions have the conditions of entering or exiting region simultaneous discharge phase, whether the ratio of the point position outflow (point position flow outside the point position region) to the inflow is greater than a threshold value, whether the speed state of the upstream road section is congested or severely congested and the like.
If the judgment is negative, selecting the point position as a cut-off point position; if the same discharge phase exists but the upstream road section is jammed or seriously jammed, or the same discharge phase does not exist but the ratio of the outflow to the inflow is smaller than or equal to the threshold value, the point cannot be used as the interception point. And selecting the boundary point position of the (n + 1) th bit for judgment.
The timing scheme unit adopts a hierarchical control frame to carry out boundary control and is divided into an upper control layer and a lower control layer. Each layer is a controller which works independently and only needs to transfer information from the upper layer to the lower layer. The same signal period is used for both layers. At each control cycle, the controller receives all required calculation indexes from the system for calculation. The two layers run in parallel, each with its own targets, which are related to the global (upper) or local (lower) performance of the network. For the upper layer and the lower layer, different output results (upper layer output control proportion and lower layer output) are calculated by using different types of input data (the upper layer uses the average speed of a road network, and the lower layer uses the speed of an inlet road).
For the upper control layer, a PI regulator using multivariable feedback keeps controlling the transition between the different states in an optimal way (i.e. the system reaches capacity, outflow is maximum, etc.). Traffic from one region may be diverted to all neighboring regions by the signal lights at the boundary based on the vehicle distribution for each region and objective indicators about the overall performance of the system. When the traffic state of the adjacent area is influenced, the lower control layer is adopted to uniformly transfer the traffic to the adjacent area, and the queuing condition and the congestion of the peripheral area are improved.
The boundary control of the upper control layer controls the core of the interception timing, and the regional state is maintained near the maximum traffic capacity. Theoretically, in order to avoid the efficiency reduction caused by the traffic jam, namely, the reduction of the average speed V of the road network, the critical value in the macroscopic basic graph (namely, the average speed V of the traffic capacity road network) is consideredcap) Is a set point for the controller.
However, according to the characteristics of the urban road network, the road network is difficult to enter the state with extremely low speed, so that the control target is to ensure that the area state is stabilized near the right side of the set value, and although the total outflow of the area does not reach the maximum at the moment, the traffic capacity is approached at the moment, and the situation that the area state enters the congested area and is irreversible can be avoided. Therefore, the algorithm is kept stable by adopting PI control.
qin(t)＝qin(t-1)+Ki*[Vcap-Vt)]-Kp*[V(t)-V(t-1)]
Wherein:
t is the time granularity;
qin(t)、qin(t-1) total inflow at time t and time t-1, respectively;
Vcapv (t) and V (t-1) are respectively the historical maximum road network average speed, the t-time road network average speed and the t-1-time road network average speed;
Vcap-V (t): the control amount needs to correct the deviation, and the larger the value, the larger the amount of incoming traffic needs to be reduced as the traffic flow state in the area is worse.
V (t) -V (t-1): representing the evolution of the state in the area, if V (t) -V (t-1) <0, the traffic state in the area continuously deteriorates, and the limited entering traffic needs to be increased; if V (t) -V (t-1) >0, the regional congestion is relieved, and the entering traffic volume can be relaxed;
Ki: non-negative parameter, control intensity, KiThe larger the control intensity is, the better the effect is; kiThe smaller, the unitThe smaller the control amount in time is, the slower the regional traffic flow state changes. In addition KiMaking too large may present an unstable situation. Initially set to 5 veh/km/lane.
Kp: non-negative parameters evolve according to the state in the region, if congestion in the region begins to relieve, the amount of compressed traffic can be reduced, and if the congestion still deteriorates, the amount of compression needs to be increased. Initially set to 20 veh/km/lane.
In practical use, KiAnd KpThe control coefficients can be found by manual adjustment using appropriate engineering methods. Or estimated by the relation between the actual data area entry amount and the area density. Research shows that the result is insensitive to the value of the coefficient, that is, the suitable parameter range is large, and as long as the adopted parameter is not excessively large (otherwise, the system has large oscillation and unstable control), the magnitude of the parameter influences the strength of the control and the time for obtaining the balance, but the control effect of the balance can be always obtained.
And for each interception point position n, distributing according to the traffic capacity of the road section and the traffic capacity of all the interception points. The data is passed to the lower control layer.
qn(t)＝qin(t)·Nn/Ntot
Wherein q isn(t) is the calculated inflow of the interception point n at the time t;
Nnthe number of lanes in the direction of the current interception point entering the area is determined;
Ntotthe sum of the number of lanes in the direction of all the interception point positions entering the area.
And for the lower control layer, the maximum pressure control is adopted for the main trunk network. Such decentralized controllers do not require the current or future average demand of the network (as compared to other model predictive control frameworks). If the demand is within a certain range, the maximum pressure can stabilize the network, thereby keeping the network traffic capacity to the maximum. It requires only local information for each intersection to maximize throughput.
For the interception point n, the state value s of each road section at the time t is introducedz(t) the state value is the road section at the current timeVelocity v of the sectionz(t) and historical maximum speed v over a monthz，maxA ratio of (i) to (ii)
sz(t)＝vz(t)/vz，max
For the interception point n, let the road segment in the entering area direction be z, and the set of z be InThen, the set flow rate of z is:
given historical data, real-time measured indicators or predicted speed, the pressure p exerted on the z road segment at the start of the cycle (time t)z(t) is calculated as follows.
Where ω is the downstream section of the section in each direction of the entering area, onIs a set of omega;
vz，maxis the historical maximum speed for road segment z;
vz(k) is the set speed for the road segment z at time t,
vz(k)＝qz(t)·vz，max/qz，max
qz，maxhistorical maximum flow of the z road section;
vω(t) is the speed of the downstream road section omega at time t;
Lz，Lωthe lengths of the stretch z and the downstream stretch ω, respectively, so that the pressure of a short stretch at a certain speed is greater than the pressure of a stretch at a longer but same speed;
βz，ωgreen ratio, which is the phase of ω steered by road segment z;
calculating pressure of each inlet lane at intersection n (i.e. calculating)
) Each phase j of the crossing is applied with a pressure calculation as follows, and the indicator can be used to calculate the non-compliance of the crossingThe same green signal ratio.
Wherein j is the phase of n intersections, FnIs a set of phases;
vjall inlet channels contained in phase j.
At the end of each cycle, the green time is assigned in proportion to the pressure calculated for each phase. The method for calculating the split comprises the following steps:
wherein λ isn，jAnd (t) is the green signal ratio of the j phase at the n intersection at the time t.
The signal system tested in this embodiment is a SCATS signal system of adaptive control logic. The SCATS signal system has a complete three-layer control strategy and single-direction and two-direction main line coordination. The system is matched with good timing optimization software, and the function of traffic signal control on improving traffic jam can be better played. As a system framework for optimizing timing, the system framework can adapt to advanced control systems and necessarily adapt to other control systems. The signal system of the embodiment necessarily comprises three parts, namely a signal control device, an open interface and a detector unit. The signal equipment is a down-sending object of the rolling optimization scheme, and the open interface is mainly used for communication such as command transmission. The detector units primarily return traffic status data such as flow and saturation.
The interactive visualization module of the embodiment has the main function of presenting relevant information of boundary control, so that a controller can intuitively know the state of the region, the system information of the boundary control and the control point position information, and can manually send a termination signal to the optimization of the region system by the controller so as to flexibly adjust. The information of the interactive visualization module comprises system information, area state information, control point location information and the like.
Specifically, the boundary control realized by the invention is an important component part of dynamic control aiming at the area, and is a timing optimization system with a specific function. The triggering and ending of the system are calculated through an algorithm, so that a system information unit is arranged in an interactive visualization module, the triggering time and the duration time are output, and the time period for optimizing the system work are reflected intuitively. The regional state information unit displays the change condition and the state level of the real-time regional state information indexes, visually represents the regional situation by comparing each macroscopic index of the region with the extreme value, the average value and the predicted value, reflects whether the traffic condition has problems and the severity of the problems, and can feed back the traffic condition through the macroscopic indexes when the optimization system works, so that the evaluation and the operation are facilitated. The boundary control scheme of the invention is to selectively screen the interception point location and set the timing scheme on the basis of the boundary point location. Therefore, in the point location information control unit, point location information participating in control optimization is displayed in an image form to reflect whether the intersection is optimized, and intersection number information, monitoring conditions and an optimization scheme can be checked by clicking; and displaying the number of the intersections participating in optimization and the proportion of the intersections participating in optimization to the total intersections, and embodying the influence range of control.
Claims (10)
1. An urban area boundary control system, characterized by: the method comprises the following steps:
the data module is used for selecting various basic data representing the traffic state, preprocessing the basic data and transmitting the processed basic data to the state evaluation module, wherein the basic data comprises historical data and real-time data;
the state evaluation module is used for performing off-line training on historical data to obtain the average speed of the traffic capacity road network, calculating real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module;
the control scheme module is used for determining the starting or ending of the boundary control according to the judgment result of the state evaluation module, issuing a corresponding timing scheme to the signal system at the interception point position of the calculation region, and transmitting various information to the interactive visualization module;
the signal system is used for controlling the traffic signals according to the timing scheme;
and the interactive visualization module is used for displaying various information and manually determining the ending of the boundary control.
2. The urban area boundary control system according to claim 1, wherein: the data module includes:
the basic data unit is used for defining basic data, classifying the basic data and calling the basic data;
and the data processing unit is used for preprocessing basic data, wherein the preprocessing comprises completion, repair, matching, fusion, standardization and analysis.
3. The urban area boundary control system according to claim 1, wherein: the state evaluation module includes:
the regional property unit is used for performing off-line training on historical data to obtain the average speed of the traffic capacity road network;
and the real-time state unit is used for calculating the real-time data to obtain the average speed of the regional road network within a certain time granularity range, comparing the average speed with the average speed of the traffic capacity road network, judging the range of the real-time data and transmitting the range to the control scheme module.
4. The urban area boundary control system according to claim 3, wherein: the regional property unit adopts a macroscopic traffic index-road network average speed V to represent regional requirements, and regional total outflow Qout_totalAs the representation of the region state, when the total regional outflow is highest in the history state, the average speed of the road network is calculated as the average speed of the road network reaching the traffic capacity through the history data, and is defined as the average speed V of the traffic capacity road networkcap。
5. The urban area boundary control system according to claim 4, wherein: the control scheme module includes:
the system control unit is used for realizing the comparison between the real-time state unit evaluation information and the historical traffic capacity and determining the opening/closing state of the boundary control according to the property of the macroscopic basic graph of the regional road network;
the device comprises an intercepting point selecting unit, a traffic flow judging unit and a traffic flow judging unit, wherein the intercepting point selecting unit is used for selecting a limited number of intersections with large entering area flow and good traffic states of upstream road sections as intercepting points;
and the timing scheme unit is used for outputting a corresponding timing scheme according to the interception point position to perform boundary control.
6. The urban area boundary control system according to claim 5, wherein: in the control unit of the system, the system control unit,
boundary control do not open/end conditions:
V≥Vter
or
Vact＜V＜Vter
Boundary control on condition:
V≤Vact
wherein v is the average speed of the road network,
V＝∑(vroadsect·qroadsect)/∑qroadsect
wherein v isroadsectThe speed of the road in the area is taken as the speed of the road; q. q.sroadsectIs the flow of the road section in the area; vactThreshold is turned on for boundary control; vterThe boundary control end threshold.
7. The urban area boundary control system according to claim 6, wherein: the intercepting point selecting process of the intercepting point selecting unit is as follows:
(1) sorting the boundary point positions from large to small according to the real-time inflow by means of real-time flow and speed data, selecting n boundary point positions with the largest real-time inflow,
n＝F(Lamp)
f (Lamp) is a function of Lamp, fitting is carried out by actual experience, and the Lamp is the number of intersections controlled by signals in the area;
(2) sequentially judging whether each selected point has an in-out region simultaneous-release phase, whether the ratio of the out-flow to the in-flow of the selected point is greater than a threshold value, and whether the speed state of an upstream road section is congested or severely congested;
(3) if the judgment is negative, selecting the selected point location as a cut-off point location; and if the same amplification phase exists but the upstream road section is blocked or seriously blocked or the same amplification phase does not exist but the ratio of the outflow to the inflow is less than or equal to the threshold value, the selected point cannot be used as the interception point, and the boundary point of the (n + 1) th position is selected for judgment.
8. The urban area boundary control system according to claim 7, wherein: the timing scheme unit adopts a hierarchical control frame to carry out boundary control and is divided into an upper control layer and a lower control layer;
the upper control layer adopts a PI regulator with multivariable feedback, and the control algorithm is as follows:
qin(t)＝qin(t-1)+Ki*[Vcap-V(t)]-Kp*[V(t)-V(t-1)]
wherein: t is the time granularity;
qin(t)、qin(t-1) total inflow at time t and time t-1, respectively;
Vcapv (t) and V (t-1) are respectively the historical maximum road network average speed, the t-time road network average speed and the t-1-time road network average speed;
Vcap-V (t): the deviation of the control quantity needs to be corrected, and when the traffic flow state in the area is worse, the larger the value is, the larger the traffic quantity needs to be reduced;
v (t) -V (t-1): representing the evolution of the state in the area, if V (t) -V (t-1) <0, the traffic state in the area continuously deteriorates, and the limited traffic volume needs to be increased; if V (t) -V (t-1) >0, the regional congestion is relieved, and the entering traffic volume can be relaxed;
Ki: non-negative parameter, control intensity, KiThe larger the control intensity is, the better the effect is; kiThe smaller, in unit timeThe smaller the control quantity is, the slower the regional traffic flow state changes;
Kp: non-negative parameters evolve according to the state in the region, if congestion in the region begins to relieve, the compressed traffic volume can be reduced, and if the congestion still deteriorates, the compression volume needs to be increased;
for each interception point location n, distributing according to the traffic capacity of the road section and the traffic capacity of all the interception point locations, and transmitting the data to a lower control layer;
qn(t)＝qin(t)·Nn/Ntot
wherein q isn(t) is the calculated inflow of the interception point n at the time t;
Nnthe number of lanes in the direction of the current interception point entering the area is determined;
Ntotthe sum of the number of lanes in the direction of all the interception point positions entering the area;
the lower control layer adopts maximum pressure control on the main trunk network, and the control algorithm is as follows:
for the interception point n, introducing the state value s of each road section at the time tz(t) the state value is the speed v of the road section at the current time of the road sectionz(t) and historical maximum speed v over a monthz，maxA ratio of (i) to (ii)
sz(t)＝vz(t)/vz，max
For the interception point n, the road section in the entering area direction is set as z, and the set of z is set as InThen, the set flow rate of z is:
given historical data, real-time measured indicators or predicted speed, the pressure p exerted on the z road segment at the start of the cycle (time t)z(t) is calculated as follows;
where ω is the distance below the road segment in each direction of the entering areaTravel section, onIs a set of omega;
vz，maxis the historical maximum speed for road segment z;
vz(k) is the set speed for the road segment z at time t,
vz(k)＝qz(t)·vz，max/qz，max
qz，maxhistorical maximum flow of the z road section;
vω(t) is the speed of the downstream road section omega at time t;
Lz，Lωthe lengths of the stretch z and the downstream stretch ω, respectively, so that the pressure of a short stretch at a certain speed is greater than the pressure of a stretch at a longer but same speed;
βz，ωgreen ratio, which is the phase of ω steered by road segment z;
calculating pressure of each inlet lane at intersection n (i.e. calculating)
) Each phase j of the crossing is applied with a pressure calculation as follows, and the indicator can be used to calculate different split ratios for the crossing;
wherein j is the phase of n intersections, FnIs a set of phases;
vjall inlet channels contained for phase j;
at the end of each cycle, the green time is assigned in proportion to the pressure calculated for each phase, the split calculation method:
wherein λ isn，jAnd (t) is the green signal ratio of the j phase at the n intersection at the time t.
9. The urban area boundary control system according to claim 1, wherein: the signal system adopts a three-layer control strategy and a single-direction and two-direction main line coordinated adaptive control logic SCATS signal system, which comprises:
the signal control equipment is used for rolling an issued object of the optimization scheme;
an open interface for command transfer communications;
and the detector unit is used for returning the traffic state data.
10. The urban area boundary control system according to claim 1, wherein: the interaction visualization module includes:
a system information unit for outputting a trigger time and a duration;
the regional status information unit is used for displaying the change condition and the status level of the real-time regional status information index;
the control point location information unit is used for displaying point location information participating in control optimization in an image form, reflecting whether the intersection is optimized or not, and checking intersection number information, monitoring conditions and an optimization scheme by clicking; and displaying the number of the intersections participating in optimization and the proportion of the intersections participating in optimization to the total intersections.
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