Driving decision generation method and device, electronic equipment and storage medium

Abstract

The invention provides a driving decision generation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining path information which is a navigation path between a starting point and a terminal point; obtaining visual perception information, wherein the visual perception information is used for representing environment information around the vehicle; according to the path information and the visual perception information, a driving decision is generated, and the driving decision is used for controlling the vehicle to drive in the corresponding lane. In the embodiment of the invention, the driving decision is generated according to the navigation path and the visual perception information, the navigation path in the embodiment of the invention is low-precision navigation, and the visual perception information is the environment information obtained by the vehicle-mounted camera, that is, the embodiment of the invention does not need a high-precision map and a high-precision sensor, so that the driving decision is more accurate. Only a low-cost navigation program and a camera of the vehicle are needed, so that the vehicle use cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of assisted driving technology, and specifically to a driving decision-making method, device, electronic device and storage medium. Background Art

[0002] With the continuous development of automotive technology, more and more cars are equipped with assisted driving functions to enhance the vehicle's safe driving ability. The city navigation function in assisted driving is inseparable from effective path planning, which includes but is not limited to intersection lane selection and lane change decisions.

[0003] In related technologies, effective lane selection and lane change control is achieved based on the route data provided by navigation and combined with lidar perception information, thereby realizing path planning.

[0004] However, the path planning solutions in related technologies have high requirements for sensors and require the use of customized navigation maps, which increases the cost of using the vehicle.

[0005] It should be pointed out that the information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or suggestion in any form that the information constitutes prior art already known to those skilled in the art. Summary of the invention

[0006] In view of this, the present application provides a driving decision-making method, device, electronic device and storage medium to help solve the problem that the path planning scheme in the prior art has high requirements for sensors and requires the use of customized navigation maps, which increases the cost of using the vehicle.

[0007] In a first aspect, an embodiment of the present application provides a driving decision making method, comprising: Acquire path information, where the path information is a navigation path between a starting point and an end point; Acquiring visual perception information, where the visual perception information is used to represent environmental information around the vehicle; A driving decision is generated according to the path information and the visual perception information, and the driving decision is used to control the vehicle to drive in a corresponding lane.

[0008] In an embodiment of the present application, driving decisions are generated based on the navigation path and visual perception information. The navigation path in the embodiment of the present application is low-precision navigation, and the visual perception information is environmental information obtained by the vehicle-mounted camera. That is to say, the embodiment of the present application does not require a high-precision map or a high-precision sensor. It only requires a low-cost navigation program and the vehicle's own camera, thereby reducing the cost of using the vehicle.

[0009] In a possible implementation, the acquiring path information includes: Get the navigation route between the starting point and the end point; The navigation route is divided according to the turning information to obtain path information, wherein the turning information is at least one turning node in the navigation route.

[0010] In the embodiment of the present application, the navigation route between the starting point and the end point is divided according to the turning information to obtain the path information, and the turning information is at least one turning node in the navigation route. It can be understood that by dividing the navigation route, accurate path information and turning nodes can be obtained, so that the vehicle can perform the intersection lane selection decision at the turning node.

[0011] In a possible implementation, generating a driving decision according to the path information and the visual perception information includes: Obtaining a set of vehicle driving trajectories according to the visual perception information; Selecting a target driving trajectory from the driving trajectory set according to the path information and the preset driving rules; A driving decision is generated according to the target driving trajectory.

[0012] In the embodiment of the present application, a driving trajectory set of the vehicle is obtained according to visual perception information, and a target driving trajectory is selected from the driving trajectory set according to the path information and the preset driving rules. It can be understood that the visual perception information can be used to determine which trajectories can be driven ahead, and the set of these trajectories is the driving trajectory set, and then the best driving trajectory can be selected from the driving trajectory set according to the path information and the preset driving rules.

[0013] In a possible implementation, obtaining a set of driving trajectories of a vehicle according to the visual perception information includes: The probability of the vehicle traveling on each driving trajectory is calculated based on the visual perception information, and a driving trajectory set of the vehicle is generated.

[0014] In an embodiment of the present application, after determining which trajectories are possible ahead through visual perception information, the probability of the vehicle traveling on each driving trajectory can be calculated, and a set of vehicle driving trajectories can be obtained based on the probability.

[0015] In a possible implementation, calculating the probability of the vehicle traveling on each driving trajectory according to the visual perception information includes: According to the formula , calculate the probability of the vehicle traveling on each driving trajectory, where p is the probability of the vehicle traveling on each driving trajectory, x is the possible trajectory of the vehicle in the future, y is one of the possible trajectories of the vehicle in the future, and t is the number of possible trajectories of the vehicle in the future.

[0016] In the embodiment of the present application, the probability of the vehicle traveling in each possible future trajectory is calculated according to the formula, which can speed up the calculation speed and improve the response speed.

[0017] In a possible implementation, generating a driving decision according to the path information and the visual perception information includes: Determining whether turning or changing lanes is required according to the path information and the visual perception information; If turning or changing lanes is required, a driving decision is generated based on the path information and the visual perception information.

[0018] In the embodiment of the present application, before generating a driving decision, it is first determined whether a turn or lane change is required. Only when a turn or lane change is required, a driving decision is generated based on the path information and visual perception information. It is understandable that when the vehicle can go straight in the current lane, there is no need to control the vehicle additionally. At this time, no driving decision is generated, which can save computing power without affecting driving safety.

[0019] In a possible implementation, judging whether turning or changing lanes is required according to the path information and the visual perception information includes: Determining a current lane of the vehicle and lane congestion according to the visual perception information; Whether turning or changing lanes is required is determined based on the path information, the current lane of the vehicle, and the congestion condition of the lane.

[0020] In the embodiment of the present application, the method for determining whether a turn or lane change is required is to determine the lane congestion according to the visual perception information, and then determine whether a turn or lane change is required according to the path information, the current lane of the vehicle, and the lane congestion. It can be understood that whether a turn or lane change is currently required can be determined by the road congestion and path information.

[0021] In a second aspect, an embodiment of the present application provides a driving decision making device, comprising: A path information acquisition module is used to acquire path information, wherein the path information is a navigation path between a starting point and an end point; A visual perception information acquisition module, used to acquire visual perception information, wherein the visual perception information is used to represent environmental information around the vehicle; The driving decision generating module is used to generate a driving decision according to the path information and the visual perception information, wherein the driving decision is used to control the vehicle to drive in a corresponding lane.

[0022] In a third aspect, an embodiment of the present application provides an electronic device, including: processor; Memory; A communication unit, used for establishing a communication channel; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes any one of the methods described in the first aspect.

[0023] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described in the first aspect.

[0024] It is understandable that the driving decision making device provided in the second aspect, the electronic device provided in the third aspect, and the computer-readable storage medium provided in the fourth aspect are used to execute the method provided in the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0026] Figure 1 A flowchart of a driving decision making method provided in an embodiment of the present application; Figure 2 A schematic diagram of path division provided in an embodiment of the present application; Figure 3 A schematic diagram of a set of driving trajectories for vehicle turning provided in an embodiment of the present application; Figure 4 A schematic diagram of a set of driving trajectories for a vehicle changing lanes provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of a driving decision making device provided in an embodiment of the present application; Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0028] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0029] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0030] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0031] With the continuous development of automotive technology, more and more cars are equipped with assisted driving functions to enhance the vehicle's safe driving ability. The city navigation function in assisted driving is inseparable from effective path planning, which includes but is not limited to intersection lane selection and lane change decisions.

[0032] In related technologies, effective lane selection and lane change control is achieved based on the route data provided by navigation and combined with lidar perception information, thereby realizing path planning.

[0033] However, the path planning solutions in related technologies have high requirements for sensors and require the use of customized navigation maps, which increases the cost of using the vehicle.

[0034] In view of the above problems, the embodiment of the present application provides a driving decision generation method, which generates driving decisions based on the navigation path and visual perception information. The navigation path in the embodiment of the present application is low-precision navigation, and the visual perception information is the environmental information obtained by the vehicle-mounted camera. In other words, the embodiment of the present application does not require a high-precision map or a high-precision sensor, but only requires a low-cost navigation program and a camera that comes with the vehicle, thereby reducing the cost of using the vehicle. This is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0035] See also Figure 1 , is a flow chart of a driving decision making method provided in an embodiment of the present application. Figure 1 As shown, it mainly includes the following steps.

[0036] Step S101: Acquire path information.

[0037] Specifically, the driving decision generating device obtains path information, which is a navigation path between a starting point and an end point, wherein the starting point is a starting point set by a user in a navigation map, and the end point is a destination set by a user in the navigation map.

[0038] In a possible implementation, the driving decision generating device obtains a navigation route between a starting point and an end point, divides the navigation route according to turning information, and obtains path information, wherein the turning information is at least one turning node in the navigation route.

[0039] For example, a navigation route (path) is from A to B, with the starting point A and the end point B. The entire navigation route contains m large sections (step), each of which is connected by the turning information (icon_type) of the section, and each large section contains n small sections (link), each of which is connected by basic navigation actions (main_action) and auxiliary navigation actions (assist_action). Among them, the basic navigation actions include turning left, turning right, going straight, etc., and the auxiliary navigation actions include entering the main road, entering the auxiliary road, entering the ramp, arriving at the service area, etc.

[0040] It can be understood that by dividing the navigation route according to the turning information, m large sections can be obtained, and then each large section can be divided according to the intersection information to obtain n small sections. The m large sections and n small sections can constitute the path information in the embodiment of this application.

[0041] To facilitate understanding, an embodiment of the present application also provides a path division schematic diagram.

[0042] See also Figure 2 , is a schematic diagram of path division provided in an embodiment of the present application. Figure 2 As shown in a in FIG, it is the navigation route between the starting point and the end point. The entire navigation route includes 4 turning nodes, and the 4 turning nodes constitute the turning information in the navigation route. By dividing the navigation route according to the turning information, 5 large sections can be obtained, such as Figure 2As shown in b, the entire navigation route is divided into 5 large sections, namely the first large section step0, the second large section step1, the third large section step2, the fourth large section step3 and the fifth large section step4. And each large section is divided into at least one small section, such as the first large section step0 is divided into 2 small sections link0-1 (i.e. link0 and link1), the second large section step1 is divided into 4 small sections link0-3 (i.e. link0, link1, link2 and link3), the third large section step2 is divided into 3 small sections link0-2 (i.e. link0, link1 and link2), the fourth large section step3 is divided into 3 small sections link0-2 (i.e. link0, link1 and link2), and the fifth large section step5 is divided into 2 small sections link0-1 (i.e. link0 and link1). That is to say, the first large road section step0 includes 2 intersections, the second large road section step1 includes 4 intersections, the third large road section step2 includes 3 intersections, the fourth large road section step3 includes 3 intersections, and the fifth large road section step5 includes 2 intersections.

[0043] In addition, the driving decision-making device can obtain real-time data of vehicle driving through navigation data, including the number of lanes on the road the vehicle is currently driving, traffic light information, etc., and can assist in determining the position of the vehicle through real-time data. In other words, the vehicle's driving route and the actual position of the vehicle in the entire driving route can be obtained through path information.

[0044] Step S102: Acquire visual perception information.

[0045] Specifically, during the driving process of the vehicle, the on-board camera on the vehicle obtains the surrounding information in real time, outputs a 2D image, and projects it in the bird's-eye view space, so that the driving decision-making device can obtain visual perception information from the on-board camera, and the visual perception information is used to characterize the environmental information around the vehicle. In a possible implementation, the environmental information around the vehicle includes but is not limited to information such as the driving environment and dynamic and static obstacles.

[0046] It can be understood that by acquiring the environmental information around the vehicle, it is possible to determine whether the area around the vehicle is safe, thereby controlling the vehicle's travel based on the environmental information around the vehicle while ensuring driving safety.

[0047] Step S103: Generate a driving decision based on the path information and visual perception information.

[0048] Specifically, the driving decision generating device generates a driving decision based on the obtained path information and visual perception information, and the driving decision is used to control the vehicle to drive in the corresponding lane. The lane in the embodiment of the present application is the lane between the two lane lines.

[0049] In a possible implementation, a set of driving trajectories of the vehicle is obtained based on visual perception information, a target driving trajectory is selected from the driving trajectory set based on path information and preset driving rules, and a driving decision is generated based on the target driving trajectory.

[0050] In a possible implementation, the driving decision generated by the driving decision generating device is used to control the steering of the vehicle.

[0051] Specifically, see Figure 3 , is a schematic diagram of a set of vehicle turning trajectories provided in an embodiment of the present application. Figure 3 As shown, the driving decision generating device can determine that the vehicle is currently located at the intersection based on the visual perception information, and the driving decision generating device can obtain a set of driving trajectories that the vehicle can drive based on the visual perception information at the intersection, and the driving trajectory set includes 6 trajectories, namely trajectory 1, trajectory 2, trajectory 3, trajectory 4, trajectory 5 and trajectory 6. In the above embodiment, the vehicle should turn right in the path information, so the trajectories of the vehicle turning right at the intersection are trajectory 5 and trajectory 6. However, the driving decision generating device stores safety rule constraints. For example, this scenario needs to be combined with the "no entry into the opposite lane" safety guarantee, exclude trajectory 5, and select trajectory 6, so as to complete the straight-right turn intersection path planning.

[0052] Similarly, if the path information shows that the vehicle should turn left, the trajectories of the vehicle turning left at the intersection are trajectory 1 and trajectory 2. However, the driving decision-making generation device stores safety rule constraints. For example, this scenario needs to be combined with the "no entry into the opposite lane" safety backup, excluding trajectory 1 and selecting trajectory 2 to complete the straight-left turn intersection path planning.

[0053] In addition, in a possible implementation, the driving decision generated by the driving decision generating device is used to control the vehicle to change lanes.

[0054] Specifically, see Figure 4 , is a schematic diagram of a set of driving trajectories for a vehicle changing lanes provided in an embodiment of the present application. Figure 4 As shown, the vehicle is currently traveling straight in the third lane on the left. Based on visual perception information, it can be determined that the third lane on the left is the rightmost lane. When the vehicle is at a preset distance from the intersection, the driving decision generating device can determine that a right turn is required ahead based on the path information and visual perception information. Based on traffic rules, it can be determined that the right-turn lane is the rightmost lane. Therefore, the vehicle can continue to travel on the current road, that is, travel according to trajectory 9, so as to turn right at the intersection.

[0055] Similarly, if the driving decision-making device determines that a left turn is required ahead based on the path information and visual perception information, then according to traffic rules, it can be determined that the left-turn lane is the leftmost lane. Because the vehicle is currently driving in the rightmost lane, it is necessary to control the vehicle to change lanes to the leftmost lane, that is, to drive according to trajectory 7, in order to turn left at the intersection.

[0056] In addition, in some possible implementations, if the current driving lane is relatively congested and the adjacent lane is relatively unobstructed, the driving decision generating device can control the vehicle to change lanes to the adjacent relatively unobstructed lane. Or when an obstacle suddenly appears in the current driving lane, the driving decision generating device can control the vehicle to change lanes under the premise of safety to avoid collision with the obstacle and ensure the safety of the driver and passengers.

[0057] In one possible implementation, according to the formula , calculate the probability of the vehicle traveling on each driving trajectory, where p is the probability of the vehicle traveling on each driving trajectory, x is all possible trajectories that the vehicle may travel in the future, y is one of the possible trajectories that the vehicle may travel in the future, and t is the number of possible trajectories that the vehicle may travel in the future.

[0058] Of course, in practical applications, since the traffic scene at the intersection is more complex than that on the road, the trajectory modes at the intersection will also increase compared to the trajectory modes on the road, and t is not limited to Figure 3 6 of them and Figure 4 The 3 types in it should be any defined multiple types.

[0059] In one possible implementation, before making a driving decision, whether turning or changing lanes is required is determined based on path information and visual perception information; if turning or changing lanes is required, a driving decision is made based on path information and visual perception information.

[0060] It is understandable that when the vehicle can go straight in the current lane, there is no need to control the vehicle additionally. At this time, no driving decision is generated, which can save computing power without affecting driving safety.

[0061] In one possible implementation, the method for determining whether turning or changing lanes is required is to determine the vehicle's current lane and lane congestion based on visual perception information; and determine whether turning or changing lanes is required based on path information, the vehicle's current lane and lane congestion.

[0062] It can be understood that whether turning or changing lanes is currently required can be determined through road congestion conditions and path information.

[0063] Corresponding to the above embodiments, the present application also provides a driving decision generating device.

[0064] See also Figure 5, which is a schematic diagram of the structure of a driving decision-making device provided in an embodiment of the present application. As shown in the figure, the driving decision-making device includes a path information acquisition module 501, a visual perception information acquisition module 502, and a driving decision-making module 503. These components communicate through one or more buses. Those skilled in the art can understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiment of the present application. It can be a bus structure or a star structure, and can also include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0065] The path information acquisition module 501 is used to acquire path information, where the path information is a navigation path between a starting point and an end point; A visual perception information acquisition module 502, used to acquire visual perception information, where the visual perception information is used to represent environmental information around the vehicle; The driving decision generating module 503 is used to generate a driving decision according to the path information and the visual perception information, wherein the driving decision is used to control the vehicle to drive in a corresponding lane.

[0066] Corresponding to the above embodiments, the present application also provides an electronic device.

[0067] See also Figure 6 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown, the electronic device 600 may include: a processor 601, a memory 602 and a communication unit 603. These components communicate via one or more buses. Those skilled in the art will appreciate that the structure of the electronic device shown in the figure does not limit the embodiments of the present application. It may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0068] The communication unit 603 is used to establish a communication channel so that the electronic device can communicate with other devices, receive user data sent by other devices or send user data to other devices.

[0069] The processor 601 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It runs or executes software programs, instructions, and / or modules stored in the memory 602, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 601 can include only a central processing unit (CPU). In the embodiment of the present application, the CPU can be a single computing core or multiple computing cores.

[0070] The memory 602 is used to store the execution instructions of the processor 601. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0071] When the execution instructions in the memory 602 are executed by the processor 601, the electronic device 600 can execute Figure 1 Some or all of the steps in the illustrated embodiments.

[0072] In a specific implementation, the embodiment of the present application further provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment of the simulation scene generation method provided in the embodiment of the present application. The storage medium may be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0073] In a specific implementation, an embodiment of the present application also provides a computer program product, wherein the computer program product includes executable instructions, and when the executable instructions are executed on a computer, the computer executes part or all of the steps in each embodiment of the simulation scene generation method provided in the embodiment of the present application.

[0074] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0075] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0076] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0077] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0078] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the device embodiment and the terminal embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

Claims

1. A driving decision making method, characterized in that: include: Acquire path information, where the path information is a navigation path between a starting point and an end point; Acquiring visual perception information, where the visual perception information is used to represent environmental information around the vehicle; A driving decision is generated according to the path information and the visual perception information, and the driving decision is used to control the vehicle to drive in a corresponding lane.

2. The method according to claim 1, characterized in that The obtaining of path information includes: Get the navigation route between the starting point and the end point; The navigation route is divided according to the turning information to obtain path information, wherein the turning information is at least one turning node in the navigation route.

3. The method according to claim 1, characterized in that: Generating a driving decision according to the path information and the visual perception information includes: Obtaining a set of vehicle driving trajectories according to the visual perception information; Selecting a target driving trajectory from the driving trajectory set according to the path information and the preset driving rules; A driving decision is generated according to the target driving trajectory.

4. The method according to claim 3, characterized in that The step of obtaining a set of vehicle driving trajectories according to the visual perception information includes: The probability of the vehicle traveling on each driving trajectory is calculated based on the visual perception information, and a driving trajectory set of the vehicle is generated.

5. The method according to claim 4, characterized in that The calculating the probability of the vehicle traveling on each driving trajectory according to the visual perception information includes: According to the formula , calculate the probability of the vehicle traveling on each driving trajectory, where p is the probability of the vehicle traveling on each driving trajectory, x is the possible trajectory of the vehicle in the future, y is one of the possible trajectories of the vehicle in the future, and t is the number of possible trajectories of the vehicle in the future.

6. The method according to claim 1, characterized in that Generating a driving decision according to the path information and the visual perception information includes: Determining whether turning or changing lanes is required according to the path information and the visual perception information; If turning or changing lanes is required, a driving decision is generated based on the path information and the visual perception information.

7. The method according to claim 6, characterized in that The determining whether turning or changing lanes is required according to the path information and the visual perception information includes: Determining a current lane of the vehicle and lane congestion according to the visual perception information; Whether turning or changing lanes is required is determined based on the path information, the current lane of the vehicle, and the congestion condition of the lane.

8. A driving decision making device, characterized in that: include: A path information acquisition module is used to acquire path information, wherein the path information is a navigation path between a starting point and an end point; A visual perception information acquisition module, used to acquire visual perception information, wherein the visual perception information is used to represent environmental information around the vehicle; The driving decision generating module is used to generate a driving decision according to the path information and the visual perception information, wherein the driving decision is used to control the vehicle to drive in a corresponding lane.

9. An electronic device, characterized in that: include: processor; Memory; A communication unit, used for establishing a communication channel; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

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