Intersection lane selection method and device based on decision matrix and electronic equipment

Abstract

The application relates to the technical field of automatic driving, in particular to a crossing road selection method and device based on a decision matrix and electronic equipment, wherein the method comprises the following steps: acquiring current vehicle information, road information where the current vehicle is located and vehicle information within a preset range of the current vehicle; judging whether the current vehicle information, the road information where the current vehicle is located and the vehicle information within the preset range of the current vehicle meet preset calculation trigger conditions; in the case that the current vehicle meets the preset calculation trigger conditions, constructing a decision matrix based on the current vehicle information, the road information where the current vehicle is located and the vehicle information within the preset range of the current vehicle; obtaining a comprehensive decision vector based on the decision matrix, and determining an optimal lane based on the comprehensive decision vector. Thus, the problems that automatic driving vehicles lack scientific decision-making when selecting lanes at crossings are solved, intelligent selection of the optimal lane is realized, and traffic efficiency and driving safety are improved.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a method, apparatus and electronic device for lane selection at intersections based on a decision matrix. Background Technology

[0002] When a car is approaching an intersection, choosing the right lane has a significant impact on its traffic efficiency. Factors such as traffic light status, the number of vehicles in different lanes, vehicle length, vehicle speed, and vehicle acceleration all affect the car's speed and the time it takes to cross the intersection.

[0003] In traditional methods, drivers typically rely on personal experience or intuition to choose lanes.

[0004] However, drivers' lack of scientific analysis of the overall traffic situation can easily lead to biased decision-making, affecting traffic efficiency and increasing safety hazards, which urgently needs to be addressed. Summary of the Invention

[0005] This application provides a method, device, and electronic device for lane selection at intersections based on a decision matrix, in order to solve the problem of lack of scientific decision-making when autonomous vehicles select lanes at intersections.

[0006] The first aspect of this application provides a lane selection method for intersections based on a decision matrix, comprising the following steps: Obtain current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle; Determine whether the current vehicle information, the road information where the current vehicle is located, and the vehicle information within a preset range of the current vehicle meet the preset calculation trigger conditions; If the current vehicle meets the preset calculation triggering conditions, a decision matrix is ​​constructed based on the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle; Based on the decision matrix, a comprehensive decision vector is obtained, and based on the comprehensive decision vector, the optimal lane is determined.

[0007] Optionally, the preset calculation trigger condition is: ; in, This is the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. The distance between the current vehicle's center point and the intersection stop line. This is the trigger coefficient.

[0008] Optionally, obtaining the comprehensive decision vector based on the decision matrix includes: Based on the decision matrix, calculate the traffic efficiency vector, lane change feasibility vector, and lane change safety vector; The comprehensive decision vector is obtained based on the traffic efficiency vector, the lane change feasibility vector, and the lane change safety vector.

[0009] Optionally, the integrated decision vector is: ; in, Let be the comprehensive decision vector. These are the weighting coefficients of the traffic efficiency vector. Let be the traffic efficiency vector. These are the weighting coefficients of the lane change feasibility vector. Let this be the lane change feasibility vector. These are the weighting coefficients of the lane change safety vector. This is the lane change safety vector.

[0010] Optionally, after determining the optimal lane based on the integrated decision vector, the method further includes: Based on the current vehicle information and the road information where the current vehicle is located, determine whether the current vehicle meets the preset calculation termination condition; The calculation stops when the current vehicle meets the preset calculation termination condition.

[0011] Optionally, determining whether the current vehicle meets the preset calculation termination condition based on the current vehicle information and the road information where the current vehicle is located includes: When the current vehicle does not meet the preset calculation termination condition, the steps of obtaining the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle are repeated until the preset calculation termination condition is met.

[0012] A second aspect of this application provides a lane selection device for intersections based on a decision matrix, comprising: The acquisition module is used to acquire current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle; The judgment module is used to determine whether the current vehicle information, the road information where the current vehicle is located, and the vehicle information within a preset range of the current vehicle meet the preset calculation trigger conditions. The construction module is used to construct a decision matrix based on the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle, when the current vehicle meets the preset calculation triggering conditions; The determination module is used to obtain a comprehensive decision vector based on the decision matrix, and to determine the optimal lane based on the comprehensive decision vector.

[0013] Optionally, the preset calculation trigger condition is: ; in, This is the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. The distance between the current vehicle's center point and the intersection stop line. This is the trigger coefficient.

[0014] Optionally, the determining module is specifically used for: Based on the decision matrix, calculate the traffic efficiency vector, lane change feasibility vector, and lane change safety vector; The comprehensive decision vector is obtained based on the traffic efficiency vector, the lane change feasibility vector, and the lane change safety vector.

[0015] Optionally, the integrated decision vector is: ; in, Let be the comprehensive decision vector. These are the weighting coefficients of the traffic efficiency vector. Let be the traffic efficiency vector. These are the weighting coefficients of the lane change feasibility vector. Let this be the lane change feasibility vector. These are the weighting coefficients of the lane change safety vector. This is the lane change safety vector.

[0016] Optionally, after determining the optimal lane based on the comprehensive decision vector, the determining module is further configured to: Based on the current vehicle information and the road information where the current vehicle is located, determine whether the current vehicle meets the preset calculation termination condition; The calculation stops when the current vehicle meets the preset calculation termination condition.

[0017] Optionally, the determining module is specifically used for: When the current vehicle does not meet the preset calculation termination condition, the steps of obtaining the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle are repeated until the preset calculation termination condition is met.

[0018] A third aspect of this application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the intersection lane selection method based on a decision matrix as described in the above embodiments.

[0019] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the intersection lane selection method based on a decision matrix as described in the above embodiments.

[0020] A fifth aspect of this application provides a computer program product storing a computer program that, when executed by a processor, implements the intersection lane selection method based on a decision matrix as described in the above embodiments.

[0021] Therefore, this embodiment of the application obtains current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle. When it is determined that the current vehicle information, road information, and vehicle information within the preset range of the current vehicle meet preset calculation trigger conditions, a decision matrix is ​​constructed based on the current vehicle information, road information, and vehicle information within the preset range of the current vehicle. A comprehensive decision vector is obtained based on the decision matrix, and the optimal lane is determined based on the comprehensive decision vector. This solves the problem of lack of scientific decision-making when autonomous vehicles select lanes at intersections, achieving intelligent selection of the optimal lane and improving traffic efficiency and driving safety.

[0022] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0023] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a lane selection method for intersections based on a decision matrix, according to an embodiment of this application. Figure 2 This is a flowchart illustrating a lane selection method for intersections based on a decision matrix, according to an embodiment of this application. Figure 3 This is a schematic diagram of an intersection scenario illustrating a lane selection method based on a decision matrix provided in one embodiment of this application. Figure 4This is a schematic diagram of a decision matrix for a lane selection method at an intersection based on a decision matrix according to an embodiment of this application; Figure 5 This is a schematic diagram of a decision matrix-based lane selection device for intersections provided according to an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0024] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0025] The following description, with reference to the accompanying drawings, describes a method, apparatus, and electronic device for lane selection at intersections based on a decision matrix, according to embodiments of this application. Addressing the problem mentioned in the background art of the lack of scientific decision-making in lane selection by autonomous vehicles at intersections, this application provides a method for lane selection at intersections based on a decision matrix. In this method, embodiments of this application acquire current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle. When it is determined that the current vehicle information, road information, and vehicle information within the preset range of the current vehicle meet preset calculation trigger conditions, a decision matrix is ​​constructed based on the current vehicle information, road information, and vehicle information within the preset range of the current vehicle. A comprehensive decision vector is obtained based on the decision matrix, and the optimal lane is determined based on the comprehensive decision vector. This solves the problem of the lack of scientific decision-making in lane selection by autonomous vehicles at intersections, achieving intelligent selection of the optimal lane and improving traffic efficiency and driving safety.

[0026] Specifically, Figure 1 This is a flowchart illustrating a lane selection method for intersections based on a decision matrix, provided in an embodiment of this application.

[0027] like Figure 1 As shown, the intersection lane selection method based on the decision matrix includes the following steps: In step S101, the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle are obtained. The preset range can be a threshold set by the user, a threshold obtained through a limited number of experiments, or a threshold obtained through a limited number of computer simulations; no specific limitation is made here.

[0028] Specifically, the current vehicle information includes the lane number where the vehicle is located. The distance between the center point of the vehicle and the stop line at the intersection Bicycle length and vehicle speed The current road information for the vehicle includes the number of lanes. The direction of travel for each lane, the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. Traffic light status at intersections; information on vehicles within the current vehicle's preset range (i.e., surrounding vehicles (SVs)) including the lane number of the SV. Distance between the center point of SV and the stop line of the intersection SV length SV speed SV starting acceleration Lane number Corresponding to the number from left to right lane, SV represents the first The first lane after the stop line at the intersection SV vehicles; among them, The estimated starting acceleration is obtained by taking the mean value of the normal distribution of starting acceleration in the natural driving data of this SV model. The remaining information can be obtained through V2X technology by enabling information sharing with other vehicles, infrastructure and networks.

[0029] In step S102, it is determined whether the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle meet the preset calculation trigger conditions.

[0030] Optionally, in some embodiments, the preset calculation trigger condition is: ; in, This is the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. This is the distance between the current center point of the vehicle and the stop line at the intersection. This is the trigger coefficient.

[0031] Specifically, when the acquired information satisfies the above inequality, the preset calculation trigger condition is met; otherwise, the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle are reacquired; among which, The trigger coefficient represents the distance relationship between the calculation trigger point and the intersection of the solid and dashed lane lines, and its value ranges from [value range missing]. .

[0032] In step S103, if the current vehicle meets the preset calculation triggering conditions, a decision matrix is ​​constructed based on the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle.

[0033] Specifically, when the preset calculation trigger conditions are met, the decision matrix... number of rows , number of columns , Each column vector corresponds to The road has three lanes, and three traffic vectors are divided according to the longitudinal space of the road along the lane direction. Let the distance between a point in the longitudinal space of the road and the stop line of the intersection be... , The road space corresponds to the first row of the decision matrix. The road space corresponds to the second row of the decision matrix. The road space corresponds to the 3rd row of the decision matrix; where... For a safe distance.

[0034] In step S104, a comprehensive decision vector is obtained based on the decision matrix, and the optimal lane is determined based on the comprehensive decision vector.

[0035] Specifically, a decision matrix is ​​constructed to structurally model the lane selection problem at intersections, generating a comprehensive decision vector. Each element in this vector represents the comprehensive evaluation score of the corresponding lane. Finally, the lane with the highest score in the comprehensive decision vector is selected as the optimal lane, thus realizing intelligent lane selection decision-making that comprehensively considers traffic efficiency, feasibility, and safety.

[0036] Optionally, in some embodiments, obtaining a comprehensive decision vector based on the decision matrix includes: calculating a traffic efficiency vector, a lane change feasibility vector, and a lane change safety vector based on the decision matrix; and obtaining a comprehensive decision vector based on the traffic efficiency vector, the lane change feasibility vector, and the lane change safety vector.

[0037] Optionally, in some embodiments, the integrated decision vector is: ; in, For the comprehensive decision vector, These are the weighting coefficients of the traffic efficiency vector. This is the traffic efficiency vector. These are the weighting coefficients for the lane change feasibility vector. This is the feasibility vector for changing lanes. These are the weighting coefficients of the lane change safety vector. This is the lane change safety vector.

[0038] It is understandable that the traffic efficiency vector is calculated, and the traffic efficiency vector is represented as: ; in, For the first The traffic efficiency score for each lane is calculated using the following formula: ; in, for The total number of SVs in the data. Decision matrix The first line of the middle The corresponding element of the column; For the first Lane number The time required for an SV to start moving and for the entire vehicle to cross the stop line at an intersection; For the first Maximum travel time for each lane; When the traffic light at the intersection is red.

[0039] ; in, The influence coefficient represents the degree of influence of the preceding vehicle's start on the following vehicle, and its value ranges from [value range missing]. ,when A value of 0 indicates that the starting of the vehicle in front has no effect on the vehicle behind. The larger the value, the greater the impact of the vehicle in front starting on the vehicle behind. for The minimum starting acceleration among all SVs.

[0040] When the traffic light at the intersection is green.

[0041]

[0042] ; in, for The average velocity of all SVs in the range.

[0043] The feasibility vector for lane changing is represented as: ; in, For the first The formula for calculating the lane change feasibility score for each lane is as follows: ; in, For the first The directional effect of each lane; For the first Lateral spatial utility of a lane; For the vehicle to change lanes from its current lane to the next lane The number of lane changes in a lane;

[0044]

[0045] ; The lane change safety matrix (lane change safety vector) is represented as: ; in, For the first The lane-changing safety score for each lane is calculated using the following formula: ; in, This represents the relative distance between SV and the vehicle. ; Finally, based on the traffic efficiency vector, lane change feasibility vector, and lane change safety vector, and combined with their respective weighting coefficients, where the weighting coefficients are... , and The range of values ​​is This yields the comprehensive decision vector.

[0046] Optionally, in some embodiments, after determining the optimal lane based on the comprehensive decision vector, the method further includes: determining whether the current vehicle meets a preset calculation termination condition based on the current vehicle information and the road information where the current vehicle is located; and stopping the calculation when the current vehicle meets the preset calculation termination condition.

[0047] Optionally, in some embodiments, based on the current vehicle information and the road information where the current vehicle is located, it is determined whether the current vehicle meets the preset calculation termination condition, including: when the current vehicle does not meet the preset calculation termination condition, repeatedly executing the steps of obtaining the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle, until the preset calculation termination condition is met.

[0048] Understandably, the preset calculation termination condition is expressed as follows: When the current vehicle meets the preset calculation termination condition, the calculation stops; when the current vehicle does not meet the preset calculation termination condition, the above steps are repeated until the preset calculation termination condition is met, and then the calculation stops. This ensures the continuous optimization of the decision-making system on key road sections and avoids the consumption of ineffective computing resources.

[0049] Therefore, the decision matrix constructed by this invention transforms the road space in the real scene into a simplified mathematical matrix model, filters redundant information, and reduces computational complexity. The comprehensive decision vector calculated by this invention includes a traffic efficiency vector, a lane change feasibility vector, and a lane change safety vector. It considers not only the impact of the selected lane on the traffic efficiency of the vehicle passing through the intersection, but also the feasibility and safety of the decision, thus enabling a comprehensive decision-making process.

[0050] To facilitate those skilled in the art to further understand the intersection lane selection method based on decision matrix of the embodiments of this application, the following is combined with Figures 2 to 4 The embodiments shown will be described in detail.

[0051] Specifically, such as Figure 2 As shown, Figure 2 A flowchart of a lane selection method for intersections based on a decision matrix according to one embodiment of this application is shown, including the following steps: Step 1: Obtain road information, vehicle information, and surrounding vehicle information; Step 2: Determine if the calculation trigger condition is met. If not, repeat Step 1 until the calculation trigger condition is met, then continue to Step 3. Step 3: Based on the data obtained in Step 1, construct a decision matrix; Step 4: Based on the decision matrix, calculate the traffic efficiency vector, lane change feasibility vector, and lane change safety vector respectively; Step 5: Calculate the comprehensive decision vector, and based on the mapping of the comprehensive decision vector to the lanes, make the optimal lane selection.

[0052] Step 6: Determine if the calculation termination condition is met. If not, repeat steps 1 to 5 to continuously update the optimal lane selection until the calculation termination condition is met and the calculation stops.

[0053] Furthermore, for example, Figure 3 This is a schematic diagram of an intersection scenario illustrating a lane selection method based on a decision matrix for intersections according to an embodiment of this application. The diagram shows the following settings: Figure 3 The intersection scene shown has 10 lanes. From left to right, lane 1 is a dedicated left-turn lane, lanes 2 and 3 are straight-ahead lanes, and lane 4 is a shared lane for both straight-ahead and right-turn traffic; the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. The traffic light at the intersection is red. Information about the vehicle and surrounding vehicles is shown in Table 1. The vehicle's lane number is... The distance between the center point of the vehicle and the stop line at the intersection ; Vehicle length Bicycle speed There is one SV in lane 1. , , , There are 3 SVs in lane 2. , , , , , , , , , , , There is one SV in lane 3. , , , There are 2 SVs in lane 4. , , , , , , , .

[0054] Table 1

[0055] In this embodiment, , , , The calculation triggering condition is met; such as Figure 4 As shown, Figure 4 This is a schematic diagram of a decision matrix for an intersection lane selection method based on a decision matrix according to an embodiment of this application. number of rows , number of columns The four column vectors correspond to the four lanes; ,but The road space corresponds to the first row of the decision matrix. The road space corresponds to the second row of the decision matrix. The road space corresponds to the 3rd row of the decision matrix.

[0056] Furthermore, the traffic efficiency vector is calculated, where the intersection traffic light status is red. , , , , , , , , , , , , ;but , , , ;but Secondly, calculate the lane change feasibility vector, where the vehicle is going straight. , ; SV exists in it. , , SV does not exist in the middle. , ; , , , ;but , , , ;but Next, the lane change safety vector is calculated, where, , , SV does not exist in the middle. SV exists in it. ;but , , , ;but Ultimately, based on the weight coefficients of each vector... , , ;but Based on the results of the comprehensive decision vector, it is determined that the vehicle should change lanes to lane 3.

[0057] Finally, based on , ,get If the calculation termination condition is not met, steps 1 through 5 will be repeated until... The calculation terminates at that time.

[0058] According to the intersection lane selection method based on a decision matrix proposed in this application, this application obtains current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle. When it is determined that the current vehicle information, road information, and vehicle information within the preset range of the current vehicle meet preset calculation trigger conditions, a decision matrix is ​​constructed based on the current vehicle information, road information, and vehicle information within the preset range of the current vehicle. A comprehensive decision vector is obtained based on the decision matrix, and the optimal lane is determined based on the comprehensive decision vector. This solves the problem of lack of scientific decision-making when autonomous vehicles select lanes at intersections, achieving intelligent selection of the optimal lane and improving traffic efficiency and driving safety.

[0059] Next, referring to the accompanying drawings, a decision matrix-based lane selection device for intersections is described according to an embodiment of this application.

[0060] Figure 5 This is a block diagram of a decision matrix-based lane selection device for intersections according to an embodiment of this application.

[0061] like Figure 5 As shown, the intersection lane selection device 10 based on the decision matrix includes: an acquisition module 100, a judgment module 200, a construction module 300, and a determination module 400.

[0062] The acquisition module 100 is used to acquire current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle. The judgment module 200 is used to determine whether the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle meet the preset calculation trigger conditions. The construction module 300 is used to construct a decision matrix based on the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle, when the current vehicle meets the preset calculation trigger conditions. The determination module 400 is used to obtain a comprehensive decision vector based on the decision matrix, and to determine the optimal lane based on the comprehensive decision vector.

[0063] Optionally, the preset calculation trigger condition is: ; in, This is the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. This is the distance between the current center point of the vehicle and the stop line at the intersection. This is the trigger coefficient.

[0064] Optionally, module 400 is specifically used to: calculate the traffic efficiency vector, lane change feasibility vector, and lane change safety vector based on the decision matrix; and obtain the comprehensive decision vector based on the traffic efficiency vector, lane change feasibility vector, and lane change safety vector.

[0065] Optionally, the integrated decision vector is:

[0066] in, For the comprehensive decision vector, These are the weighting coefficients of the traffic efficiency vector. This is the traffic efficiency vector. These are the weighting coefficients for the lane change feasibility vector. This is the feasibility vector for changing lanes. These are the weighting coefficients of the lane change safety vector. This is the lane change safety vector.

[0067] Optionally, after determining the optimal lane based on the comprehensive decision vector, the determination module 400 is further configured to: determine whether the current vehicle meets the preset calculation termination condition based on the current vehicle information and the road information where the current vehicle is located; and stop the calculation when the current vehicle meets the preset calculation termination condition.

[0068] Optionally, the determination module 400 is specifically used to: when the current vehicle does not meet the preset calculation termination condition, repeatedly execute the steps of obtaining the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle, until the preset calculation termination condition is met.

[0069] It should be noted that the foregoing explanation of the intersection lane selection method embodiment based on decision matrix also applies to the intersection lane selection device based on decision matrix in this embodiment, and will not be repeated here.

[0070] According to the intersection lane selection device based on a decision matrix proposed in this application, the device acquires current vehicle information, road information where the vehicle is located, and vehicle information within a preset range. When the current vehicle information, road information, and vehicle information within the preset range meet preset calculation trigger conditions, a decision matrix is ​​constructed based on these three factors. A comprehensive decision vector is obtained based on the decision matrix, and the optimal lane is determined based on this comprehensive decision vector. This solves the problem of lack of scientific decision-making in lane selection at intersections for autonomous vehicles, achieving intelligent selection of the optimal lane and improving traffic efficiency and driving safety.

[0071] Figure 6A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0072] When the processor 602 executes the program, it implements the intersection lane selection method based on the decision matrix provided in the above embodiments.

[0073] Furthermore, electronic devices also include: Communication interface 603 is used for communication between memory 601 and processor 602.

[0074] The memory 601 is used to store computer programs that can run on the processor 602.

[0075] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0076] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0077] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0078] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0079] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described intersection lane selection method based on a decision matrix.

[0080] This application also provides a computer program product, which stores a computer program that, when executed by a processor, implements the above-described intersection lane selection method based on a decision matrix.

[0081] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0082] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0083] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0084] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0085] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A lane selection method for intersections based on a decision matrix, characterized in that, Includes the following steps: Obtain current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle; Determine whether the current vehicle information, the road information where the current vehicle is located, and the vehicle information within a preset range of the current vehicle meet the preset calculation trigger conditions; If the current vehicle meets the preset calculation triggering conditions, a decision matrix is ​​constructed based on the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle; Based on the decision matrix, a comprehensive decision vector is obtained, and based on the comprehensive decision vector, the optimal lane is determined; The process of obtaining the comprehensive decision vector based on the decision matrix includes: Based on the decision matrix, calculate the traffic efficiency vector, lane change feasibility vector, and lane change safety vector; Based on the traffic efficiency vector, the lane change feasibility vector, and the lane change safety vector, the comprehensive decision vector is obtained; The traffic efficiency vector is represented as: ； in, For the first The traffic efficiency score for each lane is calculated using the following formula: ； in, for The total number of SVs, where SV (Surrounding Vehicle) refers to the surrounding vehicles. Decision matrix The first line of the middle The corresponding element of the column; For the first Lane number The time required for an SV to start moving and for the entire vehicle to cross the stop line at an intersection; For the first Maximum travel time for each lane; The feasibility vector for lane changing is represented as: ； in, For the first The formula for calculating the lane change feasibility score for each lane is as follows: ； in, For the first The directional effect of each lane; For the first Lateral spatial utility of a lane; For the vehicle to change lanes from its current lane to the next lane The number of lane changes in a lane; ； in, The lane number where the vehicle is located; Lane change safety vector representation is: ； in, For the first The lane-changing safety score for each lane is calculated using the following formula: ； in, This represents the relative distance between SV and the vehicle. The comprehensive decision vector is: ； in, Let be the comprehensive decision vector. These are the weighting coefficients of the traffic efficiency vector. Let be the traffic efficiency vector. These are the weighting coefficients of the lane change feasibility vector. Let this be the lane change feasibility vector. These are the weighting coefficients of the lane change safety vector. This is the lane change safety vector; When the preset calculation trigger conditions are met, the decision matrix number of rows , number of columns , Each column vector corresponds to The road has three lanes, and three traffic vectors are divided according to the longitudinal space of the road along the lane direction. Let the distance between a point in the longitudinal space of the road and the stop line of the intersection be... , The road space corresponds to the first row of the decision matrix, where, The lane number where the vehicle is located. For the length of the vehicle, The road space corresponds to the second row of the decision matrix. The road space corresponds to the 3rd row of the decision matrix; where... For a safe distance.

2. The method according to claim 1, characterized in that, The preset calculation trigger condition is: ； in, This is the distance between the intersection of the solid and dashed lane lines and the stop line at the intersection. This is the trigger coefficient.

3. The method according to claim 1, characterized in that, After determining the optimal lane based on the comprehensive decision vector, the method further includes: Based on the current vehicle information and the road information where the current vehicle is located, determine whether the current vehicle meets the preset calculation termination condition; The calculation stops when the current vehicle meets the preset calculation termination condition.

4. The method according to claim 3, characterized in that, The step of determining whether the current vehicle meets the preset calculation termination condition based on the current vehicle information and the road information where the current vehicle is located includes: When the current vehicle does not meet the preset calculation termination condition, the steps of obtaining the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle are repeated until the preset calculation termination condition is met.

5. A lane selection device for intersections based on a decision matrix, characterized in that, include: The acquisition module is used to acquire current vehicle information, road information where the current vehicle is located, and vehicle information within a preset range of the current vehicle; The judgment module is used to determine whether the current vehicle information, the road information where the current vehicle is located, and the vehicle information within a preset range of the current vehicle meet the preset calculation trigger conditions. The construction module is used to construct a decision matrix based on the current vehicle information, the road information where the current vehicle is located, and the vehicle information within the preset range of the current vehicle, when the current vehicle meets the preset calculation triggering conditions; The determination module is used to obtain a comprehensive decision vector based on the decision matrix, and to determine the optimal lane based on the comprehensive decision vector; The process of obtaining the comprehensive decision vector based on the decision matrix includes: Based on the decision matrix, calculate the traffic efficiency vector, lane change feasibility vector, and lane change safety vector; Based on the traffic efficiency vector, the lane change feasibility vector, and the lane change safety vector, the comprehensive decision vector is obtained; The traffic efficiency vector is represented as: ； in, For the first The traffic efficiency score for each lane is calculated using the following formula: ； in, for The total number of SVs, where SV (Surrounding Vehicle) refers to the surrounding vehicles. Decision matrix The first line of the middle The corresponding element of the column; For the first Lane number The time required for an SV to start moving and for the entire vehicle to cross the stop line at an intersection; For the first Maximum travel time for each lane; The feasibility vector for lane changing is represented as: ； in, For the first The formula for calculating the lane change feasibility score for each lane is as follows: ； in, For the first The directional effect of each lane; For the first Lateral spatial utility of a lane; For the vehicle to change lanes from its current lane to the next lane The number of lane changes in a lane; ； in, The lane number where the vehicle is located; Lane change safety vector representation is: ； in, For the first The lane-changing safety score for each lane is calculated using the following formula: ； in, This represents the relative distance between SV and the vehicle. The comprehensive decision vector is: ； in, Let be the comprehensive decision vector. These are the weighting coefficients of the traffic efficiency vector. Let be the traffic efficiency vector. These are the weighting coefficients of the lane change feasibility vector. Let this be the lane change feasibility vector. These are the weighting coefficients of the lane change safety vector. This is the lane change safety vector; When the preset calculation trigger conditions are met, the decision matrix number of rows , number of columns , Each column vector corresponds to The road has three lanes, and three traffic vectors are divided according to the longitudinal space of the road along the lane direction. Let the distance between a point in the longitudinal space of the road and the stop line of the intersection be... , The road space corresponds to the first row of the decision matrix, where, The lane number where the vehicle is located. For the length of the vehicle, The road space corresponds to the second row of the decision matrix. The road space corresponds to the 3rd row of the decision matrix; where... For a safe distance.

6. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the intersection lane selection method based on a decision matrix as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the intersection lane selection method based on the decision matrix as described in any one of claims 1-4.

8. A computer program product, said computer program product storing a computer program, characterized in that, When the program is executed by the processor, it implements the intersection lane selection method based on the decision matrix as described in any one of claims 1-4.

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