Solving method for intelligent connected vehicle traffic order at intersections based on time domain dynamic division

Abstract

The present invention relates to a method for solving the traffic order of intelligent networked vehicles at an intersection based on dynamic division of the time domain, comprising the following steps: S1, dividing the continuous time domain into different stages; S2, judging whether there is an intelligent networked vehicle leaving the intersection conflict zone, and if so, removing it from the conflicting vehicle set V cf , remove the related pass order from the pass order matrix D i ; S3, perform classification S4, use heuristic algorithm to solve the passage order between v0 and v1, and move v0 into the conflict vehicle set V cf , and the associated pass order d 01 Store in the pass order matrix D i ; S5, v2 related access order d2 calls access order matrix D i The results are stored; S6. Dynamically update the order of traffic for intelligent connected vehicles at intersections. The present invention's phased approach is more universal, and the phases are coupled to each other, more in line with actual conditions. This significantly reduces the complexity of the problem and is suitable for scenarios where vehicles dynamically enter and exit intersections.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent connected vehicle traffic order, and in particular to a method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic time domain division. Background Art

[0002] With the further development of communication and control technologies, intelligent connected vehicles will gradually become popular and are considered an emerging solution to traffic congestion and traffic safety. In the context of V2X, intelligent connected vehicles will be centrally dispatched by a central controller, eliminating the need for traffic lights. Therefore, efficient traffic order calculation methods are needed to meet the computing power requirements of the central controller.

[0003] Existing methods for solving the traffic order of intelligent connected vehicles generally assume that a central controller can predict the intelligent connected vehicles arriving at an intersection within a fixed time range and solve the traffic order based on the prediction results. Alternatively, they use a rolling time domain optimization method to detect existing vehicles in the intersection at fixed time intervals and solve the traffic order. However, the universality of the above two methods is not strong. The first method requires predicting vehicles entering the intersection in advance, and the prediction range is limited by the communication range of the central controller. The second method has no exact standard for determining the time domain length, but this parameter can significantly affect the solution efficiency and accuracy. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic division of the time domain. The method can divide the continuous time domain problem into different stages according to the time when the intelligent connected vehicles arrive at the intersection control area, and use dynamic programming theory to solve the traffic order in each stage, which has important theoretical value.

[0005] The technical solution adopted by the present invention to solve the technical problem is to provide a method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic division in the time domain, including the following steps:

[0006] S1. Divide the continuous time domain into different stages according to the time when the intelligent connected vehicle arrives at the intersection control area;

[0007] S2. At the initial moment of the current stage, determine whether there is an intelligent connected vehicle leaving the intersection conflict zone. If so, remove it from the conflict vehicle set V. cf , remove the related pass order from the pass order matrix D i ;

[0008] S3. At the initial moment of the current phase, the intelligent connected vehicles are classified according to their paths: newly entering intelligent connected vehicles in the current phase are recorded as v0, existing vehicles that conflict with the path of v0 are recorded as v1, and existing vehicles that do not conflict with the path of Type 0 vehicles are recorded as v2;

[0009] S4. At the initial moment of the current stage, a heuristic algorithm is used to solve the traffic order between v0 and v1, and v0 is moved into the conflicting vehicle set V. cf , and the associated pass order d 01 Store in the pass order matrix D i ;

[0010] S5. At the initial moment of the current stage, the pass order d2 associated with v2 calls the pass order matrix D i Store the results;

[0011] S6. Execute steps S2-S5 for each stage to dynamically update the traffic order of intelligent connected vehicles at the intersection.

[0012] According to the above scheme, step S1 includes the following steps:

[0013] S101. Obtaining the time when the intelligent connected vehicle arrives at a control zone at an intersection, where the control zone refers to the area enclosed by the warning lines and signal transmission boundaries of the four entrance lanes;

[0014] S102, dividing the continuous time domain at the time when the intelligent connected vehicle arrives at the intersection control area into two stages;

[0015] S103. Repeat steps S101-S102 until no more intelligent connected vehicles arrive at the intersection control area.

[0016] According to the above scheme, step S2 includes the following steps:

[0017] S201. Construct a traffic order matrix based on the driving paths of intelligent connected vehicles at the intersection. The number of rows and columns of the matrix is ​​equal to the number of paths. The matrix values ​​corresponding to non-intersecting paths are zero matrices, and the matrix values ​​corresponding to intersecting paths are non-zero matrices. When updating the matrix, only the non-zero matrix portion needs to be updated.

[0018]

[0019] S202: Determine the set of departure times of the intelligent connected vehicle in the continuous time domain of the previous stage when it exits the intersection conflict zone, where the conflict zone is the area enclosed by the warning lines of the four entrance lanes:

[0020] t s,i-1 ≤T d ≤t e,i-1

[0021] Where, t s,i-1 represents the starting time of the i-1th stage, t e,i-1 represents the end time of the i-1th stage, T d represents the set of moments when the intelligent connected vehicles leave the intersection conflict zone in the i-1th stage;

[0022] S203, if the set T in step S202 d If it is an empty set, it means that there is no vehicle leaving the intersection conflict zone in the previous stage. The conflict vehicle set V cf and the pass order matrix D i No updates required;

[0023] S204: If the set T in step S202 d If it is not empty, then T d The corresponding vehicle v in d Remove conflicting vehicle set V cf ,

[0024]

[0025] T d The corresponding pass order in is removed from the pass order matrix D i .

[0026] According to the above scheme, step S3 includes the following steps:

[0027] S301. Obtain the path of the newly entered intelligent connected vehicle v0 at the current stage;

[0028] S302: Determine the non-conflicting path set and the conflicting path set of the path where v0 is located, where the paths that intersect with the path where v0 is located belong to the conflicting path set, and the paths that do not intersect with the path where v0 is located belong to the non-conflicting path set;

[0029] S303: define the existing vehicle on the conflict path set at the current stage as the existing vehicle v1 that conflicts with the newly entered vehicle;

[0030] S304: Define the existing vehicle on the non-conflicting path set at the current stage as the existing vehicle v2 that conflicts with the newly entered vehicle.

[0031] According to the above scheme, step S4 includes the following steps:

[0032] S401. Establish a minimum average vehicle delay model. The specific mathematical expression of the objective function is as follows:

[0033]

[0034] Where, O 0,m,i1Indicates the order of passage of the mth vehicle in v0 and v1, 1 indicates that v0 has priority, and 0 indicates that the mth vehicle in v1 has priority; AD indicates the average delay of vehicles in the current stage; D m,i1 represents the delay of the mth vehicle in v1; D0 represents the delay of v0; N i1 represents the total number of vehicles in v1;

[0035] S402, using a heuristic algorithm to solve the minimum average vehicle delay model in step S401;

[0036] S403: The newly entered vehicle v0 at the current stage is stored in the conflict vehicle set V according to the formula cf :

[0037] V cf =V cf ∪v0

[0038] The passing order of v0 and v1 obtained in step S402 is stored in the passing order matrix.

[0039] The method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic time-domain division of the present invention has the following beneficial effects:

[0040] The present invention uses the moment when the intelligent connected vehicles arrive at the intersection control area to divide the continuous time domain problem into different stages, and constructs a traffic order matrix that is consistent with dynamic programming theory. When solving the traffic order in each stage, it is only necessary to pay attention to the traffic order of vehicles v0 and v1. The relevant traffic order of vehicle v2 only calls the stored result of the traffic order matrix. Under the premise of ensuring the solution quality, the problem scale is reduced from exponential order to linear order. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flowchart of a method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic division in the time domain;

[0042] Figure 2 Schematic diagram of the distribution of intersection control areas and conflict areas in an embodiment of the present invention;

[0043] Figure 3 Schematic diagram of a time domain dynamic division process in an embodiment of the present invention;

[0044] Figure 4 Schematic diagram of intersection path distribution in an embodiment of the present invention;

[0045] Figure 5 In the embodiment of the present invention, d Schematic diagram of the relevant pass order being moved out of the pass order matrix;

[0046] Figure 6Schematic diagram of storing the relevant passing order of v0 and v1 into the passing order matrix in an embodiment of the present invention;

[0047] Figure 7 This is a schematic diagram of calling the passing order storage result of the relevant passing order of v2 in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0049] like Figure 1-7 As shown, the method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic division of time domain of the present invention includes the following steps.

[0050] S1. Divide the problem in the continuous time domain into different stages based on the time when the intelligent connected vehicle arrives at the intersection control area;

[0051] S101. Obtaining the time when the intelligent connected vehicle arrives at a control zone at an intersection, where the control zone refers to the area enclosed by the warning lines and signal transmission boundaries of the four entrance lanes;

[0052] S102: Obtaining the time when the intelligent connected vehicle arrives at the intersection control zone, where the control zone refers to the area enclosed by the warning lines and signal transmission boundaries of the four entrance lanes;

[0053] S103, repeating steps S101 to S102 until no more intelligent connected vehicles arrive at the intersection control area;

[0054] In this embodiment, a total of 17 intelligent connected vehicles entered the intersection control area, and none of them drove out of the intersection. Their entrance lane numbers, vehicle numbers, and intersection entry times are shown below.

[0055]

[0056] The continuous time domain is divided into 18 different stages: 0-7, 7-8, 8-10, 10-11, 11-12, …, 25-27, 27-28, and 28-∞. In the first stage (0-7), no intelligent connected vehicles enter the intersection, and the traffic order does not need to be determined. In this example, there are a total of 17 stages in which the traffic order needs to be determined.

[0057] S2. At the initial moment of the current stage, determine whether there is an intelligent connected vehicle leaving the intersection conflict zone. If so, remove it from the conflict vehicle set V. cf , move the related pass order out of the pass order matrix;

[0058] S201. Construct a traffic order matrix based on the driving paths of intelligent connected vehicles at the intersection. The intersection path distribution is as shown in the attached figure. Figure 4 As shown, the number of rows and columns of the matrix is ​​equal to the number of paths. The matrix values ​​corresponding to the non-intersecting paths are zero matrices, and the matrix values ​​corresponding to the intersecting paths are non-zero matrices. When updating the matrix, only the non-zero matrix parts need to be updated.

[0059]

[0060] S202: Determine the set of departure times of the intelligent connected vehicle in the continuous time domain of the previous stage when it exits the intersection conflict zone, where the conflict zone is the area enclosed by the warning lines of the four entrance lanes:

[0061] t s,i-1 ≤T d ≤t e,i-1

[0062] Where, t s,i-1 represents the starting time of the i-1th stage, t e,i-1 represents the end time of the i-1th stage, T d represents the set of moments when the intelligent connected vehicles leave the intersection in the i-1th stage;

[0063] S203, if the set T in step S202 d If it is an empty set, it means that there is no vehicle leaving the intersection conflict zone in the previous stage. The conflict vehicle set V cf and the pass order matrix D i No updates required;

[0064] S204: If the set T in step S202 d If it is not empty, then T d The corresponding vehicle v in d Remove conflicting vehicle set V cf , T d The corresponding pass order in is removed from the pass order matrix D i ;

[0065] Taking the 16th stage (25-27) as an example, 23≤T d Set T ≤ 25 d It is an empty set, and the conflicting vehicle set and the passage order matrix do not need to be updated.

[0066] S3. At the initial moment of the current stage, the intelligent connected vehicles are classified according to their paths: newly entered intelligent connected vehicles in the current stage (denoted as v0), existing vehicles that conflict with the path of v0 (denoted as v1), and existing vehicles that do not conflict with the path of v0 (denoted as v2). The following uses stage 16 (25-27) as an example for explanation;

[0067] S301. Obtain the path of the newly entered intelligent connected vehicle v0 at the current stage;

[0068] In this example, the path number of the newly entered intelligent connected vehicle in stage 16 (25-27) is 7;

[0069] S302: Determine the non-conflicting path set and the conflicting path set of the path where v0 is located, where the paths that intersect with the path where v0 is located belong to the conflicting path set, and the paths that do not intersect with the path where v0 is located belong to the non-conflicting path set;

[0070] In this example, the non-conflicting path set corresponding to path 7 is {4,5,8}, and the conflicting path set is {1,2,3,6}

[0071] S303: define the existing vehicle on the conflict path set at the current stage as the existing vehicle v1 that conflicts with the newly entered vehicle;

[0072] In this embodiment, there are P vehicles on the conflicting path set {1, 2, 3, 6}. 1,1 、P 2,1 、P 2,2 、P 2,3 、P 3,1 、P 3,2 、P 6,1 、P 6,2 、P 6,3 、P 6,4 A total of 10 vehicles;

[0073] S304: define the existing vehicle on the non-conflicting path set at the current stage as the existing vehicle v2 that conflicts with the newly entered vehicle;

[0074] In this embodiment, there are P vehicles on the non-conflicting path set {4,5,8}. 4,1 、P 5,1 、P 5,2 There are 3 vehicles in total.

[0075] S4. At the initial moment of the current stage, a heuristic algorithm (such as a genetic algorithm) is used to solve the traffic order between v0 and v1, and v0 is moved into the conflicting vehicle set V. cf , and the associated pass order d 01 Store in the pass order matrix D i ;

[0076] The following explanation is based on the 16th stage (25-27) as an example.

[0077] S401. Establish a minimum average vehicle delay model. The specific mathematical expression of the objective function is as follows:

[0078]

[0079] Where, O 0,m,i1 Indicates the order of passage of the mth vehicle in v0 and v1, 1 indicates that v0 has priority, and 0 indicates that the mth vehicle in v1 has priority; AD indicates the average delay of vehicles in the current stage; D m,i1 represents the delay of the mth vehicle in v1; D0 represents the delay of v0; N i1 =10 represents the total number of vehicles in v1;

[0080] S402, using a heuristic algorithm to solve the minimum average vehicle delay model in step S401;

[0081] In this embodiment, the solution is 0 0,m,i1 =[0,0,0,0,0,0,0,0,1,1];

[0082] S403, storing the newly entered vehicles in the current stage into the conflicting vehicle set, and storing the solution of step S402 into the traffic order matrix; in this embodiment,

[0083] The solution is stored in the pass order matrix as follows:

[0084]

[0085] S5. At the initial moment of the current stage, the pass order d2 related to v2 calls the pass order matrix D of the previous stage i-1 Store the results;

[0086] Taking the 16th stage (25-27) as an example, the existing vehicles that do not conflict with the new vehicles entering the current stage have their relevant passing order call the stored values ​​in the passing order matrix, as shown in step 4.3. As shown in the figure, the matrix value of the path without conflict is 0.

[0087] S6. Execute steps S2 to S5 for each phase to dynamically update the order of traffic for intelligent connected vehicles at the intersection. The final statistical results are shown below, with a total enumeration calculation count of only 3494 times.

[0088]

[0089]

[0090] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic time domain division, characterized in that: It is characterized in that it includes the following steps: S1. Divide the continuous time domain into different stages according to the time when the intelligent connected vehicle arrives at the intersection control area; S2. At the initial moment of the current stage, determine whether there is an intelligent connected vehicle leaving the intersection conflict zone. If so, remove it from the conflict vehicle set V. cf , remove the related pass order from the pass order matrix D i ; S3. At the initial moment of the current phase, classify the intelligent connected vehicles according to their paths: the newly entered intelligent connected vehicle in the current phase is recorded as v0, the existing vehicle that conflicts with the path of v0 is recorded as v1, and the existing vehicle that does not conflict with the path of v0 is recorded as v2; S4. At the initial moment of the current stage, a heuristic algorithm is used to solve the traffic order between v0 and v1, and v0 is moved into the conflicting vehicle set V. cf , and the associated pass order d 01 Store in the pass order matrix D i ; S5. At the initial moment of the current stage, the pass order d2 associated with v2 calls the pass order matrix D i Store the results; S6. Execute steps S2-S5 for each stage to dynamically update the traffic order of intelligent connected vehicles at the intersection.

2. The method for solving the traffic order of intelligent connected vehicles at intersections based on time-domain dynamic division according to claim 1 is characterized in that: The step S1 comprises the following steps: S101. Obtaining the time when the intelligent connected vehicle arrives at a control zone at an intersection, where the control zone refers to the area enclosed by the warning lines and signal transmission boundaries of the four entrance lanes; S102, dividing the continuous time domain at the time when the intelligent connected vehicle arrives at the intersection control area into two stages; S103. Repeat steps S101-S102 until no more intelligent connected vehicles arrive at the intersection control area.

3. The method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic time domain division according to claim 1 is characterized in that: The step S2 comprises the following steps: S201. Construct a traffic order matrix based on the driving paths of intelligent connected vehicles at the intersection. The number of rows and columns of the matrix is ​​equal to the number of paths. The matrix values ​​corresponding to non-intersecting paths are zero matrices, and the matrix values ​​corresponding to intersecting paths are non-zero matrices. When updating the matrix, only the non-zero matrix portion needs to be updated. S202: Determine the set of departure times of the intelligent connected vehicle in the continuous time domain of the previous stage when it exits the intersection conflict zone, where the conflict zone is the area enclosed by the warning lines of the four entrance lanes: t s,i-1 ≤T d ≤t e,i-1 Where, t s,i-1 represents the starting time of the i-1th stage, t e,i-1 represents the end time of the i-1th stage, T d represents the set of moments when the intelligent connected vehicles leave the intersection conflict zone in the i-1th stage; S203, if the set T in step S202 d If it is an empty set, it means that there is no vehicle leaving the intersection conflict zone in the previous stage. The conflict vehicle set V cf and the pass order matrix D i No updates required; S204: If the set T in step S202 d If it is not empty, then T d The corresponding vehicle v in d Remove conflicting vehicle set V cf , T d The corresponding pass order in is removed from the pass order matrix D i .

4. The method for solving the traffic order of intelligent connected vehicles at intersections based on dynamic time domain division according to claim 1 is characterized in that: The step S3 comprises the following steps: S301. Obtain the path of the newly entered intelligent connected vehicle v0 at the current stage; S302: Determine the non-conflicting path set and the conflicting path set of the path where v0 is located, where the paths that intersect with the path where v0 is located belong to the conflicting path set, and the paths that do not intersect with the path where v0 is located belong to the non-conflicting path set; S303: define the existing vehicle on the conflict path set at the current stage as the existing vehicle v1 that conflicts with the newly entered vehicle; S304: Define the existing vehicle on the non-conflicting path set at the current stage as the existing vehicle v2 that conflicts with the newly entered vehicle.

5. The method for solving the traffic order of intelligent connected vehicles at intersections based on time domain dynamic division according to claim 1 is characterized in that: The step S4 comprises the following steps: S401. Establish a minimum average vehicle delay model. The specific mathematical expression of the objective function is as follows: Where, O 0,m,i1 Indicates the order of passage of the mth vehicle in v0 and v1, 1 indicates that v0 has priority, and 0 indicates that the mth vehicle in v1 has priority; AD indicates the average delay of vehicles in the current stage; D m,i1 represents the delay of the mth vehicle in v1; D0 represents the delay of v0; N i1 represents the total number of vehicles in v1; S402, using a heuristic algorithm to solve the minimum average vehicle delay model in step S401; S403: The newly entered vehicle v0 at the current stage is stored in the conflict vehicle set V according to the formula cf : V cf =V cf ∪v0 The passing order of v0 and v1 obtained in step S402 is stored in the passing order matrix.

Images