CN105225503A - Traffic control subarea is optimized and self-adapting regulation method - Google Patents

Abstract

The invention discloses the optimization of a kind of traffic control sub-area division and self-adapting regulation method, traffic control sub-area division is carried out based on the category of roads of static state and dynamic arithmetic for real-time traffic flow, determine the traffic control subarea needing to carry out signal lamp interlock management and control and manual intervention according to saturation degree index, and traffic control community is upgraded automatically.The comprehensive category of roads of the present invention and arithmetic for real-time traffic flow carry out static state to traffic subarea and dynamically divide, and effectively improve sub-area division efficiency; Determine dissimilar traffic control subarea according to saturation degree, be conducive to building rational signal lamp linkage tube prosecutor case and manual intervention scheme; According to arithmetic for real-time traffic flow change, repartition for some traffic control communities changed, avoid the redundant computation that generation repartitioned by system-wide net.

Description

Traffic Control Sub-area Optimization and Adaptive Adjustment Method

technical field

The invention relates to an urban traffic control sub-area division method, in particular to a traffic control sub-area division and area self-adaptive adjustment method combined with road grades and real-time traffic flow.

Background technique

The division of sub-regions is the prerequisite for regional coordinated signal control and the determination of reasonable traffic control measures and scope. It divides the huge and complex road network into several evaluation sub-areas according to certain principles and methods, so as to obtain the relationship between traffic supply and traffic demand in the sub-areas, and then determine the signal coordination control strategy or traffic control measures of different traffic control areas Wait.

At present, there are mainly two methods of subdivision division, static and dynamic division. Since static division cannot be adjusted reasonably in time according to real-time traffic conditions, it is gradually converting to dynamic traffic control district division based on real-time traffic flow, but the calculation efficiency of dynamic traffic district division is often difficult to meet the actual needs. How to combine static division and dynamic division to improve the real-time performance and efficiency of sub-region division is a direction worthy of breakthrough. At the same time, due to the difference in road structure and traffic flow characteristics of different road grades, generally speaking, roads of the same or adjacent road grades are more relevant. However, few studies have included road grades in the consideration of traffic control area division. In addition, the division of signal control sub-area is a dynamic problem. The change of traffic flow in the urban road network has a strong time period characteristic, which will make the original signal control sub-area unable to support coordinated signal control well. When the signal control sub-area When the division principle is no longer met, it is necessary to dynamically adjust the control sub-areas according to the real-time changes in traffic flow. The existing dynamic adjustment of signal lights is mostly to manually determine a certain time interval and recalculate the division uniformly. However, because some traffic control areas are not strongly affected by time interference, division does not need to be divided, resulting in redundant calculations.

Contents of the invention

In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a traffic control sub-area optimization and self-adaptive adjustment method, which is used to improve the efficiency, accuracy and real-time performance of sub-network division, and better adopt different traffic control cell types. Different traffic management strategies.

The present invention systematically integrates "traffic area division based on real-time traffic flow and real-time update of traffic control area", and proposes that before dynamically dividing the traffic control area, firstly, static traffic area division is performed on signal light intersections based on road grades According to the real-time changes of traffic flow in the dynamic traffic control area, the local signal light intersections are re-updated and divided in a targeted manner.

In order to achieve the above object, the present invention proposes a traffic control sub-area optimization and adaptive adjustment method, comprising the following steps:

S1. Construct road network and traffic flow database, clarify road network topological relationship and road grade;

S2. According to the topological relationship of the road network and the road grade, the types of signal intersections are preliminarily divided, and the physical similarity between two signal intersections is calculated. According to the physical similarity, the signal intersections are divided into one or more static traffic control District;

S3. Based on the static traffic control area obtained in step S2, combined with real-time traffic flow, further calculate the traffic flow correlation degree between two signal light intersections, and divide each static traffic control sub-area into multiple according to the traffic flow correlation degree Dynamic traffic control sub-area;

S4. Calculate the saturation of each signal light intersection in the current period, and on this basis, calculate the saturation of each dynamic traffic control sub-area in the current period; divide the dynamic traffic control sub-area into traffic-flowing areas according to the saturation of the dynamic traffic control sub-area There are three types: signal light cooperative control cell and multi-party cooperative control cell;

S5. Determine whether the time between the current time and the last adjustment of the dynamic traffic control sub-area has reached the preset time. If it is not reached, keep the original dynamic traffic control area division plan unchanged, and when it is reached, recalculate the intersection of the signal lights of each dynamic traffic control area. According to the intersection saturation of each dynamic traffic control area, the cell type is divided; if one of the following two conditions is met, the static traffic control area where the changed dynamic traffic control area is located is re-divided: (1) There is a change in the type of dynamic traffic control area; (2) There is a change in the signal intersection corresponding to the maximum saturation in the dynamic traffic control area.

Compared with the prior art, the beneficial effects of the present invention are: comprehensively consider road grades and real-time traffic flow to carry out static and dynamic division of traffic sub-areas, effectively improve the efficiency of sub-area division; determine different types of traffic control sub-areas according to saturation, It is conducive to the construction of a reasonable signal light linkage control plan and manual intervention plan; according to real-time traffic flow changes, a number of changed traffic control areas are re-divided, avoiding redundant calculations caused by the re-division of the entire road network. The method overcomes the problems of insufficient combination of static and dynamic sub-divisions in the original traffic control sub-division, poor pertinence of the control sub-division traffic scheme, low calculation efficiency and insufficient self-adaptive ability.

Description of drawings

Fig. 1 is the flowchart of the method of the present invention.

Figure 2 is a schematic diagram of intersections with six types of signal lights.

Fig. 3 is a flow chart of static traffic control district division based on road grade.

Fig. 4 is a flowchart of dynamic traffic control cell division based on real-time traffic flow.

Fig. 5 is a flowchart of classification of traffic control districts based on signal light intersection saturation.

Fig. 6 is a flowchart of real-time adjustment of traffic control cells.

Figure 7 is a schematic diagram of the road network.

detailed description

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

The technical process of the present invention is as shown in accompanying drawing 1, comprises database construction, the static traffic control district division based on road grade, the dynamic traffic control district division based on real-time traffic flow, the signal lamp traffic control district classification based on signal light intersection saturation, There are five steps in traffic control cell self-adaptive adjustment.

1.1 Database construction:

Construct the road network and traffic flow database, and clarify the topological relationship of the road network and road grades; the topological relationship of the road network is mainly manifested as the adjacency relationship between signal intersections, and the road grades are divided into three major urban arterial roads, urban secondary arterial roads, and urban branch roads kind.

1.2 Static traffic control district division based on road grade:

1) Use G=(V,E) to represent the road network, where V={v ₁ ,v ₂ ,…,v _n }, v _i represents the ith intersection of signal control signal lights, and V is all signal control signal lights in the network Intersection collection; E={e ₁₂ ,e ₂₃ ,...,e _ij }, e _ij represents the road section connecting signal control signal light intersection i and j, and its weight w _ij represents the correlation between signal light intersection i and j, E is the collection of all road segments in the network.

According to the different road grades, signal intersections are divided into six types: main road and main road, main road and secondary road, main road and branch road, secondary main road and secondary road, secondary main road and branch road, branch road and branch road; And assign values to the intersection types of the six types of signal lights:

R _i = θ, 1≤θ≤6, θ∈n

Among them, R _i =1 is the signal light intersection of arterial road and main road type, R _i =2 is the signal light intersection of arterial road and secondary arterial road type, R _i =3 is the signal light intersection of arterial road and branch road type, R _i = 4 is the signal light intersection of the secondary trunk road and the secondary trunk road type, R _i =5 is the signal light intersection of the secondary trunk road and the branch road type, and R _i =6 is the signal light intersection of the branch road and the branch road type;

Let the physical similarity between adjacent connected signal light intersections in the road network G be w _(i,j) represents the correlation between signal light intersection i and j, R _i and R _j are the type values of signal light intersection i and j respectively, d _ij represents the distance between signal light intersection i and signal light intersection j; when When signal light intersection i and signal light intersection j are not connected, the corresponding w _{(i, j)} is 0, and e is a natural constant;

2) The adjacency matrix of the road network G is H. When the signal light intersection i and the signal light intersection j in the road network G are connected in a direction, that is, when there is a road section e _ij connected, the element a _ij = 1 in H, when the signal light When intersection i and signal light intersection j are not connected by a section e _ij , a _ij =0; when i=j, a _ij =0;

The weighted adjacency matrix of road network G is W, and the elements in W are:

${\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; w</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.$

Diagonal matrix D=diag{d _i }, d _i =∑ _j w(i,j)

3) The Laplace matrix of a weighted undirected graph with n nodes is a symmetric matrix L of n×n dimensions. If there is an edge connection between these two nodes, L _ij is negative, otherwise it is 0. Therefore, the matrix L can be expressed as L=DW, where D is a diagonal matrix, and the elements on the diagonal correspond to the degree of each node, and W is the weighted adjacency matrix of the network.

4) Calculate the second smallest eigenvalue and Fiedler vector of the Laplacian matrix. The problem of traffic control cell division can be transformed into the problem of partitioning graph G=(V,E).

The sum of all rows and columns of the L matrix is 0, therefore, the matrix always has an eigenvalue of 0, and all elements of its corresponding eigenvector are 1. If G is connected, then the second smallest eigenvalue λ ₂ is a positive number, and its corresponding eigenvector, that is, the value of each element (including positive and negative elements) in the Fiedler vector reflects the relationship between its corresponding vertices .

5) According to the value of each element in the Fiedler eigenvector F=(f ₁ , _{f 2} , . If the number of partitions reaches K, terminate the Fiedler segmentation. If the total number of partitions in the road network does not reach K, return to step 3), select the partition with the largest number of signal intersections, establish the Laplace matrix corresponding to the partition, and repeat steps 4) and 5) , solve the Fiedler vector and perform Fiedler vector segmentation; the specific segmentation method is: select the critical value S=0, segment each element in the Fiedler feature vector F, divide the vertices with f _i ≥ 0 into one partition, and the rest f _i <0 The vertices of are assigned to another partition, i=1, 2,..., n.

1.3 Dynamic traffic control district division based on real-time traffic flow:

1) According to the division of static traffic control sub-areas, a total of K static traffic control sub-areas are obtained, and G _k = (V _k , E _k ) represents the road network corresponding to the kth static traffic control sub-area, 1≤k≤K ; where V _k ={v _k1 , v _k2 ,...,v _kp ,...}, v _kp represents the p-th signal intersection in the kth static traffic control sub-area, and V _k is the kth static traffic control sub-area The set of all signal intersections; E _k ＝{e _k12 ,e _k23 ,…,e _kpq }, e _kpq represents the road section connecting signal light intersection p and q, E _k is all road sections in the kth static traffic control sub-area collection of

2) In the kth static traffic control sub-area, the traffic flow correlation degree ρ _k(p,q) of the connected signal intersections p and q is calculated using the calculation method recommended in the US "Traffic Control System Handbook":

${\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 0.5</span>}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; \&lsqb;</span>\frac{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; max</span>}}}{{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, n is the number of branches entered by vehicles from the upstream signal light intersection; Q _i is the traffic volume of the i-th branch arriving at the downstream signal light intersection, and Q _max is the maximum traffic volume of the branches arriving at the downstream signal light intersection; is the total traffic volume arriving at the intersection of downstream signal lights; t is the travel time of vehicles at the intersection of two signal lights; N is the number of lanes traveling from upstream to downstream; since signal light intersection p and signal light intersection q are mutually upstream and downstream signal light intersections Therefore, two ρ _{k (p, q)} values can be obtained, and the average value of the two is taken as the final traffic flow correlation degree ρ _{k (p, q)} of the signal light intersection p and q;

3) Calculate the adjacency matrix of the road network G _k of each static traffic control sub-area as H _k , when the signal light intersection p and the signal light intersection q in the road network G _k are connected, the element a _kpq = 1 in H _k , when When the signal light intersection p is not connected to the signal light intersection q, a _kpq =0; when p=q, a _kpq =0;

4) Calculate the weighted adjacency matrix W _k and the diagonal adjacency matrix D _k of the road network G _k of each static traffic control sub-area, where the element w _kpq in the weighted adjacency matrix W _k is:

${\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; p</span>}\mathrm{<span\; class="notranslate">\; q</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}\mathrm{<span\; class="notranslate">\; q</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}\mathrm{<span\; class="notranslate">\; q</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.$

D _k = diag{d _kp }, d _kp = ∑ _q ρ _k(p,q)

5) Calculating the Laplacian matrix L _k at the traffic light intersection of each static sub-area, where L _k =D _k -W _k ;

6) According to the constructed Laplacian matrix L _k , solve the eigenvector corresponding to the second smallest eigenvalue of the matrix, that is, the Fiedler vector: F _k = (f _k1 , f _k2 , . . . , f _km );

7) According to the value of each element in the _Fiedler eigenvector F _k = (f _k1 , f _k2 , . If the maximum number of signal intersections in the partition is less than Z, terminate the Fiedler segmentation; if there is any one of the partitions in which the number of signal intersections is greater than or equal to Z, return to step 5), select the partition with the largest number of signal intersections, and establish the Laplace matrix corresponding to the partition , and repeat steps 6) and 7), solve the Fiedler vector and perform Fiedler vector segmentation; the specific segmentation method is: select the critical value S=0, segment each element in the Fiedler eigenvector F _k , and divide the vertices with f _kp ≥ 0 Divide into a partition, and the vertexes of the remaining f _kp ＜0 are divided into another partition (p=1, 2, ..., m); the kth static traffic control sub-district will be divided into L dynamic traffic control sub-districts at last;

8) According to the division of dynamic traffic control sub-areas, the kth static traffic control sub-area corresponds to L dynamic traffic control sub-areas. Use G _kl = (V _kl , E _kl ) to represent the l-th dynamic traffic control sub-area corresponding to the k-th static traffic control sub-area, where 1<k≤K, 1<l≤L;

1.4 Classification of traffic control districts based on signal light intersection saturation:

1) Calculate the saturation of the T period of each dynamic traffic control sub-area _Gkl Where k is the number of the kth static traffic control area, l is the number of the dynamic traffic control area, where 1<k≤K, 1<l≤L; the calculation formula for the intersection saturation of each signal light is as follows:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}$

Among them, α represents the signal light intersection number, is the total number of signal light intersections in the dynamic traffic control sub-area _Gk1 ; is the traffic volume of the α-th signal light intersection in the dynamic traffic control community G _k1 in the T period; To represent the maximum traffic capacity of the α-th signal light intersection of the dynamic traffic control community G _k1 in the T period;

2) Maximum capacity The calculation formula is as follows:

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; \{</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; .</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; ...</span>}<span\; class="notranslate">\; ,</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; ...</span>}<span\; class="notranslate">\; \}</span>$

Each element corresponds to the maximum capacity of each entrance of the signal intersection; where α is the number of the signal intersection, β is the entrance number of the α-th signal intersection, and γ is the lane number of the β-th entrance, 0<α≤A, A is the number of signal light intersections in the dynamic traffic control district G _kl ; 0<β≤B, B is the number of entrances at the signal light intersection α; 0<γ≤Γ; Γ is the number of lanes at the entrance β; is the traffic capacity of the γ-th lane at the β-th entrance of the α-th signal light intersection of the dynamic traffic control community G _kl in the T period, is the total number of entry lanes at the βth entrance numbered entry lane at the _αth signal light intersection of the dynamic traffic control district G k1 in the T period;

3) Traffic volume Take the flow data measured by the ground induction coil of each inlet during the T period, and the formula is as follows:

${\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; \{</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; .</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; ...</span>}<span\; class="notranslate">\; ,</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; ...</span>}<span\; class="notranslate">\; \}</span>$

Each element corresponds to the traffic volume of each entrance of the signal intersection in the T period; where α is the number of the signal intersection, β is the entrance number of the α-th signal intersection, and γ is the lane number of the β-th entrance, 0<α≤A , A is the number of signal light intersections in the dynamic traffic control community G _kl ; 0<β≤B, B is the number of entrances at the signal light intersection α; 0<γ≤Γ, Γ is the number of lanes at the entrance β; is the traffic volume of the γ-th lane at the β-th entrance of the α-th signal light intersection of the dynamic traffic control community _Gkl in the T period, is the total number of entry lanes at the βth entrance numbered entrance at the αth signal light intersection of the dynamic traffic control area G _kl in the T period; 4) the saturation degree of the βth entrance in the T period is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; =</span>\frac{{<span\; class="notranslate">\; \&Sigma;</span>}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{<span\; class="notranslate">\; \&Sigma;</span>}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}$

5) Take the maximum value of the saturation of the entrance β in the signal light intersection α as the saturation of the signal light intersection in T period, that is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; max</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; max</span>}<span\; class="notranslate">\; \{</span>\frac{{<span\; class="notranslate">\; \&Sigma;</span>}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{<span\; class="notranslate">\; \&Sigma;</span>}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; \}</span>$

6) Calculate the saturation of the dynamic traffic control area in the T period The calculation formula is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}\underset{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}$

Among them, k represents the number of the static traffic control sub-area, l represents the number of the dynamic traffic control sub-area in the static traffic control sub-area, α is the number of the signal intersection in the dynamic traffic control sub-area, is the signal light intersection saturation in T period, is the number of signal light intersections in the dynamic traffic control sub-area G _k1 in the T period;

7) Control cell saturation according to dynamic traffic which is $S_{kl}^T\&le;0.5,0.5<S_{kl}^T\&le;0.8,S_{kl}^T>0.8,$ The dynamic traffic control area is divided into traffic flow control area, signal light coordinated control area and multi-party coordinated control area.

Among them, the traffic flow community does not need to adopt the signal light linkage control scheme and manual intervention, the multi-party signal light coordinated control community needs to enable the signal light linkage control scheme, and the multi-party coordinated control community needs to strengthen other aspects besides the signal light linkage control. Road sections are navigated.

1.5 Real-time adjustment of traffic control area:

Calculate the saturation of each signal light intersection in T+1 period In the calculated T+1 period, the saturation of each signal light intersection Based on the calculation of the dynamic traffic control sub-area the saturation of Compared and Whether there is a change in the corresponding intersection α, and whether the type of the same dynamic traffic control sub-area in the two periods has changed. If one of the changes is satisfied, the dynamic traffic control sub-area will be re-divided, and the static traffic control sub-area will maintain unchanged; otherwise, no dynamic traffic control sub-division is required. Through the above method, the traffic control area can be adaptively adjusted and divided according to the traffic flow of the road network, and a more accurate range determination can be provided for the linkage control of signal lights and traffic guidance.

The above self-adaptive division method of traffic control area based on road grade and real-time traffic flow combines the static division of traffic control area of road level, dynamic division of traffic control area of real-time traffic flow, classification of traffic control area, adaptive adjustment of traffic control area etc. to form a complete adaptive adjustment system for traffic control areas, which can obtain the division and adjustment of traffic control areas in a timely, dynamic and efficient manner.

Compared with previous methods, the present invention has the beneficial effects of: comprehensively considering road grades and real-time traffic flow to carry out static and dynamic division of traffic sub-areas, effectively improving the efficiency of sub-area division; determining different types of traffic control sub-areas according to saturation, It is conducive to the construction of a reasonable signal light linkage control plan and manual intervention plan; according to real-time traffic flow changes, a number of changed traffic control areas are re-divided, avoiding redundant calculations caused by the re-division of the entire road network. The method overcomes the problems of insufficient combination of static and dynamic sub-divisions in the original traffic control sub-division, poor pertinence of the control sub-division traffic scheme, low calculation efficiency and insufficient self-adaptive ability.

Based on the above characteristics, the self-adaptive division method of traffic control districts based on road grade and real-time traffic flow announced by the present invention also plays a huge role in real-time traffic flow prediction, road condition evaluation, etc., and helps the smart city under construction.

The above-mentioned embodiments only represent possible implementation modes of the present invention, and the description thereof is relatively specific and detailed, but should not be construed as limiting the patent scope of the present invention. It should be pointed out that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention should be based on the appended claims.

Claims (6)

1. A traffic control subdivision optimization and adaptive adjustment method, is characterized in that, comprises the following steps: S1. Construct road network and traffic flow database, clarify road network topological relationship and road grade; S2. According to the topological relationship of the road network and the road grade, the types of signal intersections are preliminarily divided, and the physical similarity between two signal intersections is calculated. According to the physical similarity, the signal intersections are divided into one or more static traffic control District; S3. Based on the static traffic control area obtained in step S2, combined with real-time traffic flow, further calculate the traffic flow correlation degree between two signal light intersections, and divide each static traffic control sub-area into multiple according to the traffic flow correlation degree Dynamic traffic control sub-area; S4. Calculate the saturation of each signal light intersection in the current period, and on this basis, calculate the saturation of each dynamic traffic control sub-area in the current period; divide the dynamic traffic control sub-area into traffic-flowing areas according to the saturation of the dynamic traffic control sub-area There are three types: signal light cooperative control cell and multi-party cooperative control cell; S5. Determine whether the time between the current time and the last adjustment of the dynamic traffic control sub-area has reached the preset time. If it is not reached, keep the original dynamic traffic control area division plan unchanged, and when it is reached, recalculate the intersection of the signal lights of each dynamic traffic control area. According to the intersection saturation of each dynamic traffic control area, the cell type is divided; if one of the following two conditions is met, the static traffic control area where the changed dynamic traffic control area is located is re-divided: (1) There is a change in the type of dynamic traffic control area; (2) There is a change in the signal intersection corresponding to the maximum saturation in the dynamic traffic control area. 2. The traffic control sub-area division optimization and adaptive adjustment method according to claim 1, characterized in that, in the step S1, the topological relationship of the road network is mainly shown as the adjacency relationship between signal intersections, and the road grades are divided into urban arterial roads , urban sub-arterial roads, and urban branch roads. 3. traffic control sub-area division optimization and adaptive adjustment method according to claim 2, is characterized in that, the division method of step S2 static traffic control sub-district is: 21) Use G=(V,E) to represent the road network, where V={v ₁ ,v ₂ ,...,v _i ,...}, v _i represents the i-th signal light intersection, and V is all signal light intersections in the road network set of crossings; E={e ₁₂ , e ₂₃ ,...,e _ij ,...}, e _ij represents the road section connecting signal light intersection i and j, and E is the collection of all road sections in the road network; 22) According to different road grades, signal intersections are divided into six types: main road and main road, main road and secondary road, main road and branch road, secondary main road and secondary road, secondary main road and branch road, branch road and branch road type; and assign values to the intersection types of six types of signal lights: R _i = θ, 1≤θ≤6, θ∈n Among them, R _i =1 is the signal light intersection of arterial road and main road type, R _i =2 is the signal light intersection of arterial road and secondary arterial road type, R _i =3 is the signal light intersection of arterial road and branch road type, R _i = 4 is the signal light intersection of the secondary trunk road and the secondary trunk road type, R _i =5 is the signal light intersection of the secondary trunk road and the branch road type, and R _i =6 is the signal light intersection of the branch road and the branch road type; 23) Let the physical similarity between adjacent connected signal light intersections in the road network G be w _(i,j) represents the correlation between signal light intersection i and j, R _i and R _j are the type values of signal light intersection i and j respectively, d _ij represents the distance between signal light intersection i and signal light intersection j; when When signal light intersection i and signal light intersection j are not connected, the corresponding w _{(i, j)} is 0, and e is a natural constant; 24) Calculate the adjacency matrix H of the road network G. When the signal light intersection i and the signal light intersection j are connected in a direction in the road network G, that is, when there is a road section e _ij connected, the element a _ij in H = 1, when the signal light When intersection i and signal light intersection j are not connected by a section e _ij , a _ij =0; when i=j, a _ij =0; 25) Calculate the weighted adjacency matrix W and the diagonal adjacency matrix D of the road network G; The value of the element w _ij in the weighted adjacency matrix W is: ${\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; w</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.$ D=diag{d _i }, d _i =∑ _j w(i,j); 26) Calculate the Laplacian matrix L at the road network signal light intersection, where L=D-W; 27) Based on the Laplacian matrix L, solve the eigenvector corresponding to the second smallest eigenvalue of the matrix, that is, the Fiedler eigenvector: F=(f ₁ , f ₂ ,..., f _n ), where the element f of the eigenvector F The value of _i corresponds to the signal light intersection i; 28) According to the value of each element in the Fiedler eigenvector F=(f ₁ , f ₂ ,..., f _n ), adopt the dichotomy method to divide each element of the Fiedler vector, and divide a partition into two; if the number of partitions reaches K , terminate the Fiedler segmentation, if the total number of partitions in the road network does not reach K, return to step 26), select the partition with the largest number of signal intersections, establish the Laplace matrix corresponding to the partition, and repeat steps 27) and 28), solve the Fiedler vector and Carry out Fiedler vector segmentation; The specific segmentation method is: select the critical value S=0, divide each element in the Fiedler eigenvector F, divide the vertices with f _i ≥ 0 into one partition, and divide the vertices with f _i <0 into another partition, i= 1, 2, ..., n. 4. traffic control sub-area division optimization and adaptive adjustment method according to claim 3, is characterized in that, the division method of step S3 dynamic traffic control sub-area is: 31) According to the division of static traffic control sub-areas, a total of K static traffic control sub-areas are obtained, and G _k = (V _k , E _k ) represents the road network corresponding to the kth static traffic control sub-area, 1≤k≤K ; where V _k ={v _k1 , v _k2 ,...,v _kp ,...}, v _kp represents the p-th signal intersection in the kth static traffic control sub-area, and V _k is the kth static traffic control sub-area The set of all signal intersections; E _k ＝{e _k12 ,e _k23 ,…,e _kpq }, e _kpq represents the road section connecting signal light intersection p and q, E _k is all road sections in the kth static traffic control sub-area collection of 32) Determine the traffic flow correlation degree ρ _k(p,q) of the connected signal light intersection p and q in the kth static traffic control sub-area as: ${\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 0.5</span>}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; \&lsqb;</span>\frac{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}}}{{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$ Among them, n is the number of branches entered by vehicles from the upstream signal light intersection; Q _i is the traffic volume of the i-th branch arriving at the downstream signal light intersection, and Q _max is the maximum traffic volume of the branches arriving at the downstream signal light intersection; is the total traffic volume arriving at the intersection of downstream signal lights; t is the travel time of vehicles at the intersection of two signal lights; N is the number of lanes traveling from upstream to downstream; since signal light intersection p and signal light intersection q are mutually upstream and downstream signal light intersections Therefore, two ρ _{k (p, q)} values can be obtained, and the average value of the two is taken as the final traffic flow correlation degree ρ _{k (p, q)} of the signal light intersection p and q; 33) Calculate the adjacency matrix of the road network G _k of each static traffic control sub-area as H _k , when the signal light intersection p and the signal light intersection q in the road network G _k are connected, the element a _kpq in H _k =1, when When the signal light intersection p is not connected to the signal light intersection q, a _kpq =0; when p=q, a _kpq =0; 34) Calculate the weighted adjacency matrix W _k and the diagonal adjacency matrix D _k of the road network G _k of each static traffic control sub-area, wherein, the element w _kpq in the weighted adjacency matrix W _k is: ${\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; p</span>}\mathrm{<span\; class="notranslate">\; q</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}\mathrm{<span\; class="notranslate">\; q</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}\mathrm{<span\; class="notranslate">\; q</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.$ D _k = diag{d _kp }, d _kp = ∑ _q ρ _k(p,q) 35) Calculating the Laplacian matrix L _k at the road network signal intersection of each static traffic control sub-area, where L _k =D _k -W _k ; 36) According to the Laplacian matrix L _k , solve the eigenvector corresponding to the second smallest eigenvalue of the matrix, namely the Fiedler vector: F _k =(f _k1 , f _k2 ,..., f _km ); 37) According to the value of each element in the Fiedler eigenvector F _k = (f _k1 , f _k2 , ..., f _km ), adopt the dichotomy method to divide each element of the Fiedler vector, and divide a partition into two; if the signal lights in the partition If the maximum number of intersections is less than Z, the Fiedler segmentation is terminated; if the number of signal intersections in any one of the partitions is greater than or equal to Z, return to step 35), select the partition with the largest number of signal intersections, establish the Laplace matrix corresponding to the partition, and repeat the steps 36) and 37), solving the Fiedler vector and performing Fiedler vector segmentation; The specific segmentation method is: select the critical value S=0, segment each element in the Fiedler eigenvector F _k , divide the vertices with f _kp ≥ 0 into one partition, and divide the vertices with f _kp <0 into another partition, p =1, 2,..., m; finally the kth static traffic control sub-district will be divided into L dynamic traffic control sub-districts; 38) According to the division of dynamic traffic control sub-areas, the k th static traffic control sub-area corresponds to L dynamic traffic control sub-areas; G _kl = (V _kl , E _kl ) indicates that the k th static traffic control sub-area corresponds to The lth dynamic traffic control sub-area of , where 1<k≤K, 1<l≤L. 5. The traffic control sub-area division optimization and adaptive adjustment method according to claim 4, characterized in that, in step S4, the dynamic traffic control sub-district classification mode based on signal light intersection saturation is: 41) Calculate the saturation of the T period of each dynamic traffic control sub-area G _kl Where k is the number of the kth static traffic control area, l is the number of the dynamic traffic control area, where 1<k≤K, 1<l≤L; the calculation formula for the intersection saturation of each signal light is as follows: ${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}}$ Among them, α represents the signal light intersection number, is the total number of signal light intersections in the dynamic traffic control sub-area _Gk1 ; is the traffic volume of the α-th signal light intersection in the dynamic traffic control community G _k1 in the T period; To represent the maximum traffic capacity of the α-th signal light intersection of the dynamic traffic control community G _k1 in the T period; 42) Maximum capacity The calculation formula is as follows: ${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; \{</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; \}</span>$ Each element corresponds to the maximum capacity of each entrance of the signal intersection; where α is the number of the signal intersection, β is the entrance number of the α-th signal intersection, and γ is the lane number of the β-th entrance, 0<α≤A, A is the number of signal light intersections in the dynamic traffic control district G _kl ; 0<β≤B, B is the number of entrances at the signal light intersection α; 0<γ≤Γ; Γ is the number of lanes at the entrance β; is the traffic capacity of the γ-th lane at the β-th entrance of the α-th signal light intersection of the dynamic traffic control community G _kl in the T period, is the total number of entry lanes at the βth entrance numbered entry lane at the _αth signal light intersection of the dynamic traffic control district G k1 in the T period; 43) Traffic volume Take the flow data measured by the ground induction coil of each inlet during the T period, and the formula is as follows: ${\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; \{</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\underset{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; \}</span>$ Each element corresponds to the traffic volume of each entrance of the signal intersection in the T period; where α is the number of the signal intersection, β is the entrance number of the α-th signal intersection, and γ is the lane number of the β-th entrance, 0<α≤A , A is the number of signal light intersections in the dynamic traffic control community G _kl ; 0<β≤B, B is the number of entrances at the signal light intersection α; 0<γ≤Γ, Γ is the number of lanes at the entrance β; is the traffic volume of the γ-th lane at the β-th entrance of the α-th signal light intersection of the dynamic traffic control community _Gkl in the T period, is the total number of entry lanes at the βth entrance numbered entry lane at the _αth signal light intersection of the dynamic traffic control district G k1 in the T period; 44) The saturation of the βth inlet in the T period is: ${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}$ 45) Take the maximum value of the saturation of the entrance β in the signal light intersection α as the saturation of the signal light intersection in T period, that is: ${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; max</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; max</span>}<span\; class="notranslate">\; \{</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&Gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; \}</span>$ 46) Calculate the saturation of the dynamic traffic control cell in the T period The calculation formula is: ${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}\underset{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}$ Among them, k represents the number of the static traffic control sub-area, l represents the number of the dynamic traffic control sub-area in the static traffic control sub-area, α is the number of the signal intersection in the dynamic traffic control sub-area, is the signal light intersection saturation in T period, is the number of signal light intersections in the dynamic traffic control sub-area G _k1 in the T period; 47) According to the T period of dynamic traffic control cell saturation which is >0.8, the dynamic traffic control area is divided into traffic flow control area, signal light coordinated control area and multi-party coordinated control area. 6. The traffic control sub-area division optimization and adaptive adjustment method according to claim 5, wherein the real-time adjustment of the traffic control sub-district refers to: calculating the saturation of each signal light intersection in the T+1 period In the calculated T+1 period, the saturation of each signal light intersection Based on the calculation of the dynamic traffic control sub-area the saturation of Compared and Whether there is a change in the corresponding intersection α, and whether the type of the same dynamic traffic control sub-area in the two periods has changed. If one of the changes is satisfied, the dynamic traffic control sub-area will be re-divided, and the static traffic control sub-area will maintain unchanged; otherwise, no dynamic traffic control sub-division is required.