Virtual vehicle route planning method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a virtual carrier route planning method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: carrying out the road condition event perception in a game process through various virtual carriers, and packaging the event information of each road condition event into an information node; when the virtual carrier sends a road condition query request, determining a road condition influence value of a current road section according to all target information nodes corresponding to the current road section of the virtual carrier, and providing the road condition influence value to the virtual carrier; if the virtual carrier determines that the road condition influence value is greater than or equal to a preset threshold value, when the virtual carrier sends a query request again, providing all the target information nodes to the virtual carrier, and planning a new driving route by the virtual carrier according to all the target information nodes; otherwise, not processing. According to the invention, the road condition information sensed by each virtual vehicle can be shared, so that any virtual vehicle can autonomously decide route planning in advance, and the intelligence and driving safety of the virtual vehicle are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of games, in particular to a virtual vehicle route planning method and device, electronic equipment, storage medium and program product. BACKGROUND

[0002] With the rapid development of Massively Multiplayer Online Role-Playing Games (MMORPG) and open-world games, the scale of virtual environments in games is continuously expanding, and the complexity of interactions is continuously improving. Under such a background, the vehicle system, as an important element to enhance the immersion and interactivity of games, its intelligent degree directly affects the game experience of players.

[0003] In current game development, the vehicle system can provide player vehicles and AI-controlled non-player vehicles, and can adopt a route planning scheme based on A-star pathfinding algorithm combined with local collision detection, which has high running efficiency. However, with the increasing demand of players for the reality and interactivity of the game world, the limitations of this traditional method in complex dynamic environments are increasingly apparent: on the one hand, due to the lack of global environmental perception ability, the vehicle can only react to immediate collision threats; on the other hand, the independently operating vehicle system cannot form a synergistic effect, resulting in a lack of overall coordination in traffic flow performance. Some existing solutions attempt to introduce server-side global path calculation or machine learning-based prediction models, but these solutions are often limited by network latency and computational overhead, making it difficult to meet the high requirements of open-world games for real-time interaction. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a virtual vehicle route planning method and device, electronic equipment, storage medium and program product, which can share road condition information perceived by each virtual vehicle, so that any virtual vehicle can make autonomous decisions on route planning in advance, improving the intelligence and driving safety of virtual vehicles. In order to achieve the above purpose, the technical solutions adopted by the present application are as follows: In a first aspect, the present application provides a virtual vehicle route planning method, which comprises: utilizing various virtual vehicles to perceive road condition events during game play, and packaging event information of each road condition event into an information node; when a virtual vehicle sends a road condition query request, determining a road condition influence value of the current road segment where the virtual vehicle is located according to all target information nodes corresponding to the current road segment, and providing the road condition influence value to the virtual vehicle; if the virtual vehicle determines that the road condition influence value is greater than or equal to a preset threshold, when the virtual vehicle sends a query request again, providing all target information nodes to the virtual vehicle, and the virtual vehicle plans a new driving route according to all target information nodes; otherwise, no processing is performed.

[0005] Secondly, the present invention provides a virtual vehicle route planning device, comprising: a perception module, used to perceive road condition events using various virtual vehicles during gameplay, and package the event information of each road condition event into information nodes to form an information node queue; a determination module, used to determine the road condition impact value of the current road segment based on all target information nodes corresponding to the current road segment of the virtual vehicle when the virtual vehicle issues a road condition query request, and provide it to the virtual vehicle; and a decision module, used to provide all target information nodes to the virtual vehicle when the virtual vehicle sends a query request again if the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, so that the virtual vehicle plans a new driving route based on all target information nodes; otherwise, no processing is performed.

[0006] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing machine-executable instructions executable by the processor, the processor executing the machine-executable instructions to implement the virtual vehicle route planning method described in the first aspect.

[0007] Fourthly, the present invention provides a storage medium storing machine-executable instructions thereon, which, when executed by a processor, implement the virtual vehicle route planning method described in the first aspect.

[0008] Fifthly, the present invention provides a program product on which machine-executable instructions are executed, and when the machine-executable instructions are executed by a processor, the virtual vehicle route planning method described in the first aspect is implemented.

[0009] The virtual vehicle route planning method, apparatus, electronic device, storage medium, and program product provided by this invention first utilize various virtual vehicles to perceive road conditions during gameplay, collecting rich road condition data and providing basic data support for subsequent information sharing and decision-making. When a virtual vehicle issues a road condition query request, the system determines the road condition impact value of the current road segment based on all target information nodes corresponding to the virtual vehicle's current location and provides this impact value to the virtual vehicle. If the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, it indicates that the current road segment has a high risk or congestion. At this time, when the virtual vehicle sends a query request again, all target information nodes are provided to the virtual vehicle. The virtual vehicle can plan a new driving route based on these detailed information nodes, thereby avoiding high-risk or congested road segments. If the road condition impact value is lower than the preset threshold, the current road condition is considered acceptable, and the system does not perform further processing. This avoids unnecessary route adjustments, reduces the waste of system resources, and maintains the normal operation of the virtual vehicle. The entire solution enables the sharing of road condition information and autonomous decision-making by virtual vehicles, effectively improving the intelligence and driving safety of virtual vehicles.

[0010] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A schematic flowchart illustrating the virtual vehicle route planning method provided in an embodiment of the present invention; Figure 2 A schematic flowchart of step S101 provided in an embodiment of the present invention; Figure 3 A functional block diagram of a virtual vehicle route planning device provided in an embodiment of the present invention; Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0014] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0015] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0016] Considering the problems of limited perception range, lack of road information sharing, and delayed route adjustment in existing vehicle route planning in games, this invention provides a virtual vehicle route planning method that can improve the realism and intelligence of virtual vehicle driving behavior.

[0017] It should be noted that the virtual vehicles in this embodiment of the invention can be AI vehicles or player vehicles in online games. AI vehicles are controlled by the game's AI system and can perform tasks according to the game's logic and preset objectives, such as automatic navigation and automatic attack. Player vehicles are vehicles whose movement, acceleration, steering, and braking are controlled by the player through input devices such as game controllers, keyboards, and mice. When a player vehicle is in automatic control, this embodiment of the invention can be applied. Furthermore, vehicles can be, but are not limited to, vehicles, ships, and aircraft.

[0018] Please see Figure 1 , Figure 1This is a schematic flowchart of a virtual vehicle route planning method provided in an embodiment of the present invention. The execution subject of this method can be an electronic device, which can be, but is not limited to, a game server, a terminal, etc. The method includes steps S101 to S103, as described below: S101: Utilize various vehicles to perceive road conditions during gameplay and package the event information of each road condition event into information nodes; S102: When a vehicle sends a road condition query request, the road condition impact value of the current road segment is determined based on all target information nodes corresponding to the current road segment of the vehicle, and provided to the vehicle. S103: If the vehicle determines that the road condition impact value is greater than or equal to the preset threshold, then when the vehicle sends a query request again, all target information nodes will be provided to the vehicle, and the vehicle will plan a new driving route based on all target information nodes; otherwise, no action will be taken.

[0019] The virtual vehicle route planning method provided in this invention first utilizes various virtual vehicles to perceive road conditions during gameplay, collecting rich road condition data and providing foundational data support for subsequent information sharing and decision-making. When a virtual vehicle issues a road condition query request, the system determines the road condition impact value of the current road segment based on all target information nodes corresponding to the virtual vehicle's current location and provides this impact value to the virtual vehicle. If the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, it indicates that the current road segment has a high risk or congestion. In this case, when the virtual vehicle sends another query request, all target information nodes are provided to the virtual vehicle. The virtual vehicle can then plan a new route based on these detailed information nodes, thereby avoiding high-risk or congested road segments. If the road condition impact value is lower than the preset threshold, the current road condition is considered acceptable, and the system does not perform further processing. This avoids unnecessary route adjustments, reduces waste of system resources, and maintains the normal operation of the virtual vehicle. The entire solution realizes the sharing of road condition information and the autonomous decision-making of virtual vehicles, effectively improving the intelligence and driving safety of virtual vehicles.

[0020] Next, the embodiments of the present invention will describe each of the above steps in detail.

[0021] In step S101, this embodiment of the invention can utilize various virtual vehicles to perceive road conditions during gameplay. It should be understood that, in addition to virtual vehicles, other scene objects within the game can also be used for road condition perception. These scene objects can be intelligent agents controlled by an AI system, such as NPCs in the game, or environmental elements within the game, such as cameras. By integrating the perception capabilities of virtual vehicles, intelligent agents, and environmental elements, real-time surrounding road conditions can be provided to the virtual vehicles.

[0022] In this embodiment of the invention, each virtual vehicle or scene object can package the event information of perceived road condition events into information nodes. These road condition events may include, but are not limited to, slow-moving vehicles, fast-moving vehicles, disabled vehicles, dynamic obstacles, vehicle loss of control, and road occupancy. For each type of road condition event, a corresponding information node can be generated according to the following method.

[0023] Please see Figure 2 , Figure 2 A schematic flowchart of step S101 provided in the embodiment of the present invention includes steps S101-1 to S101-3, as described below: S101-1: For each road condition event, determine the event metadata.

[0024] In this embodiment of the invention, the event metadata includes the event type and the event perception source identifier, whereby the perception source identifier refers to the identifier of the virtual vehicle or scene object that perceived the road condition event.

[0025] S101-2: Based on the event type, query the spatial and temporal impact characteristics of each road condition event in the preset configuration table; among which, the spatial and temporal impact characteristics include: driving behavior impact weight, affected road segment range, event effective duration and estimated elimination time.

[0026] In this embodiment of the invention, those skilled in the art can pre-configure spatial and temporal impact characteristics for different road condition events, including driving behavior impact weight (the degree of impact of a certain road condition event on driving safety), affected road segment range (the range of road segments affected, in terms of road point spacing), effective duration of the event, and estimated elimination time.

[0027] When a virtual vehicle or scene object senses a certain road condition event, it can quickly read these spatial and temporal impact characteristics directly from the configuration table according to the event type, and package them into information nodes.

[0028] S101-3: Package event metadata and spatial and temporal impact characteristics into information nodes.

[0029] The information nodes in this embodiment of the invention can provide decision-making basis for the virtual vehicle to plan its route. In other words, these information nodes can be shared with each other virtual vehicle to make decisions in advance on whether to detour or slow down, rather than waiting until the last moment to react, thereby improving the intelligence level of the virtual vehicle.

[0030] In this embodiment of the invention, a dynamic tagging system can be pre-configured to uniformly manage some information nodes generated in step S101 above. When the virtual vehicle needs to perform route planning, the dynamic tagging system can provide relevant information nodes to the virtual vehicle, providing a basis for route planning decisions.

[0031] In one embodiment of the present invention, the dynamic tagging system can be deployed on a game server or client. To facilitate unified maintenance of each information node, the dynamic tagging system can create a data structure to store and manage these information nodes. For example, a hash table plus priority queue data structure can be created, allowing each information node to be managed uniformly, and all information nodes can form an information node queue according to the order of their reporting time.

[0032] In one embodiment of the present invention, when a virtual vehicle determines that the road condition event on its current road segment has ended or changed, it can send an indication message to the dynamic marking system, so that the dynamic marking system can delete the information node corresponding to the ended road condition event or the changed path event from the information node queue.

[0033] Furthermore, in this embodiment of the invention, the dynamic marking system can also periodically update the information nodes according to the event status of the road condition events corresponding to each information node in the information node queue.

[0034] Next, in step S102, when a virtual vehicle issues a traffic query request, the road segment where the virtual vehicle is located can be determined first, and then the road segment impact information corresponding to that road segment can be returned to the virtual vehicle for autonomous decision-making. Therefore, step S102 may include the following steps a1 to a3, as explained below: Step a1: When the virtual vehicle sends a query request through the first-level road condition information interface, it queries all target information nodes whose affected road segment range is the same as the current road segment. In this embodiment of the invention, a layered road condition information interface can be pre-designed. The dynamic marking system can provide different information to the virtual vehicle through different layer interfaces for the vehicle's autonomous decision-making.

[0035] In one implementation, a two-layer traffic information interface can be designed. The first-layer traffic information interface can return traffic impact values ​​to the virtual vehicle, allowing it to quickly determine whether to adjust its route. The second-layer traffic information interface can return all information nodes of the current road segment to the virtual vehicle, enabling it to make detailed judgments based on all information nodes for advanced intelligent strategy analysis.

[0036] Understandably, each virtual vehicle can periodically obtain the road condition impact value of its current road segment through the first-level road condition information interface, and then autonomously determine whether route adjustments are needed.

[0037] In this embodiment of the invention, a road segment is a line segment between pre-defined waypoints. In this embodiment of the invention, waypoints and their adjacency relationships can be pre-defined in the game map, thereby determining the current road segment of any virtual vehicle. When a virtual vehicle uses the first-level road condition information query interface, the road condition impact value of the current road segment can be quickly determined based on the information node corresponding to the current road segment of the virtual vehicle and returned to the virtual vehicle, as shown in step a2.

[0038] Step a2: Parse the behavior influence weights in the target information nodes and query the influence coefficients corresponding to the event types in the target information nodes from the configuration table; In this embodiment of the invention, multiple road condition events can occur on the same road segment. The road segment impact index for each segment can be determined by the influence weight of the driving behavior corresponding to that segment and the influence coefficient of the road condition events occurring on that segment. This influence coefficient can be pre-configured by relevant technical personnel based on the type of road condition event; for example, the influence coefficient of dynamic obstacles is greater than the influence coefficient of slow-moving vehicles.

[0039] Step a3: Calculate the road condition impact value of the current road segment by weighted summation based on the impact weight and impact coefficient, and return the road condition impact value to the virtual vehicle through the first-level road condition information interface.

[0040] As shown in the formula below:

[0041] in, This is the road condition impact value; N is the total number of information nodes corresponding to the same road segment; Is and These are the driving behavior influence weight corresponding to the i-th information node and the influence coefficient corresponding to the road condition event type, respectively.

[0042] After obtaining the road condition impact value of the current road segment of a virtual vehicle through the above implementation method, it can be returned to the virtual vehicle through the first-level road condition information query interface, so that the virtual vehicle can quickly determine whether the current path needs to be adjusted, that is, execute step S103.

[0043] In step S103, if the virtual vehicle determines that the road condition impact value is less than a preset threshold, no action is needed, and the vehicle continues along the current route. If the road condition impact value is greater than or equal to the preset threshold, a query request can be sent again through the second-layer road condition information interface. At this time, all information nodes located on the current road segment can be obtained and returned to the virtual vehicle through the second-layer road condition information interface, allowing the virtual vehicle to plan a new route based on all target information nodes.

[0044] To facilitate a comprehensive understanding of the virtual vehicle route planning process described above, consider this example: In an open-world role-playing game featuring vehicles, when AI vehicle A encounters a slow-moving, disabled vehicle 300 meters ahead on a certain road segment, an information node for this road condition event is generated and reported to the dynamic marking system. The system marks this event as a "slow-moving vehicle," sets its driving behavior impact weight to 0.6, and the affected road segment range to 100 meters. When AI vehicle B travels on the same road segment, it queries the dynamic marking system to learn in advance that the road condition impact value for that segment is high, thus starting to decelerate and choose a fork in the road 200 meters in advance to avoid a collision. Through testing, this embodiment of the invention can reduce the average collision rate of virtual vehicles by 45% and improve route adjustment reaction time by approximately 35%.

[0045] Through the above steps S101 to 103, the virtual vehicle route planning method provided by this embodiment of the invention has the following advantages: First, by simulating the behavior of virtual vehicles observing road conditions in advance, predicting and adjusting driving strategies, this embodiment of the invention makes the driving experience in the game more realistic and significantly enhances the game's realism. Second, different virtual vehicles in this embodiment of the invention can share road condition information, achieving an effect similar to "convoy communication." This information sharing mechanism makes the coordination between vehicles more efficient, further enhancing the game's fun and interactivity. Furthermore, in this embodiment of the invention, virtual vehicles can detour or slow down in advance, thereby reducing collisions caused by delayed reactions, lowering the collision rate, and greatly improving the game's safety and smoothness.

[0046] To perform the corresponding steps in the above embodiments and various possible methods, an implementation of a virtual vehicle route planning device is given below. Please refer to [link / reference needed]. Figure 3 , Figure 3 A functional block diagram of a virtual vehicle route planning device provided in an embodiment of the present invention includes: a perception module 301, a determination module 302, and a decision module 303.

[0047] The perception module 301 is used to perceive road conditions during the game using various virtual vehicles, and to package the event information of each road condition event into information nodes to form an information node queue. The determination module 302 is used to determine the road condition impact value of the current road segment based on all target information nodes corresponding to the current road segment of the virtual vehicle when the virtual vehicle issues a road condition query request, and provide it to the virtual vehicle. The decision module 303 is used to provide all target information nodes to the virtual vehicle when the virtual vehicle sends a query request again if the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, so that the virtual vehicle can plan a new driving route based on all target information nodes; otherwise, no processing is performed.

[0048] It is understandable that the perception module 301, the determination module 302, and the decision-making module 303 can execute collaboratively. Figure 1 Each step in the process is used to achieve the corresponding technical effect.

[0049] It should be noted that the virtual vehicle route planning device 30 provided in this embodiment of the invention can be specific hardware on the device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in this embodiment of the invention are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the device embodiments can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0050] Optionally, the above modules can be stored in the form of software or firmware. Figure 4 The memory shown is in the operating system (OS) of the electronic device 40, and can be... Figure 4 The processor executes the commands. Meanwhile, the data and program code required to execute these modules can be stored in memory.

[0051] Please see Figure 4 , Figure 4 The structural block diagram of the electronic device provided in the embodiment of the present invention includes a memory 401, a processor 402, and a communication interface 403. The memory 401, processor 402, and communication interface 403 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0052] Optionally, the bus can be 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 4 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.

[0053] In this embodiment of the invention, the processor 402 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in this embodiment of the invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in this embodiment of the invention can be directly manifested as execution by the hardware processor, or execution by a combination of hardware and software modules within the processor. The software modules may reside in the memory 401, and the processor 402 reads the program instructions from the memory 401 and, in conjunction with its hardware, completes the steps of the aforementioned methods.

[0054] In this embodiment of the invention, the memory 401 can be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), or it can be volatile memory, such as RAM. The memory can also be any other medium capable of carrying or storing desired executable program code having an instruction or data structure form and accessible by a computer, but is not limited thereto. The memory in this embodiment of the invention can also be a circuit or any other device capable of implementing a storage function for storing instructions and / or data.

[0055] The memory 401 can be used to store software programs and modules, such as the instructions / modules of the virtual vehicle route planning device 30 provided in this embodiment of the invention. These can be stored in the memory 401 in the form of software or firmware, or embedded in the operating system (OS) of the electronic device 40. The processor 402 executes various functional applications and data processing by executing the software programs and modules stored in the memory 401. The communication interface 403 can be used to communicate with other node devices for signaling or data.

[0056] Understandable. Figure 4 The structure shown is for illustrative purposes only; the electronic device 4 may also include more than [other components]. Figure 4 The more or fewer components shown, or having the same Figure 4 The different configurations shown. Figure 4 The components shown can be implemented using hardware, software, or a combination thereof.

[0057] Based on the above embodiments, the present invention also provides a readable storage medium storing a computer program. When the computer program is executed by a computer, it causes the computer to execute the virtual vehicle route planning method provided in the above embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0058] Based on the above embodiments, the present invention also provides a program product, which includes a computer program. The processor can execute the computer program to implement the virtual vehicle route planning method provided in the embodiments of the present invention. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0059] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0060] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs.

[0061] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0062] It should be noted that if the function is implemented as a software functional module 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 this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes: USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, and other media capable of storing program code.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A virtual vehicle route planning method, characterized in that, The method includes: Various virtual vehicles are used to perceive road conditions during the game, and the event information of each road condition event is packaged into information nodes; When a virtual vehicle sends a road condition query request, the road condition impact value of the current road segment is determined based on all target information nodes corresponding to the current road segment of the virtual vehicle, and provided to the virtual vehicle. If the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, then when the virtual vehicle sends a query request again, all the target information nodes will be provided to the virtual vehicle, and the virtual vehicle will plan a new driving route based on all the target information nodes; otherwise, no action will be taken.

2. The virtual vehicle route planning method according to claim 1, characterized in that, Various virtual vehicles are used to perceive road conditions during gameplay, and the event information of each road condition event is packaged into information nodes, including: For each of the aforementioned road condition events, event metadata is determined; wherein, the event metadata includes the event type and the event perception source identifier; Based on the event type, the spatial and temporal impact characteristics of each road condition event are queried from a preset configuration table; wherein, the spatial and temporal impact characteristics include: driving behavior impact weight, affected road segment range, event effective duration, and estimated elimination time; The event metadata and the spatial and temporal impact features are packaged into the information node.

3. The virtual vehicle route planning method according to claim 2, characterized in that, When a virtual vehicle issues a traffic condition query request, the traffic condition impact value of the current road segment is determined based on all target information nodes corresponding to the current road segment of the virtual vehicle, and provided to the virtual vehicle, including: When the virtual vehicle sends a query request through the first-layer road condition information interface, it queries all target information nodes whose affected road segment range is the same as the current road segment. The influence weight of driving behavior in the target information node is parsed out, and the influence coefficient corresponding to the event type in the target information node is queried from the configuration table; The road condition impact value of the current road segment is obtained by weighted summation of the impact weight and the impact coefficient, and the road condition impact value is returned to the virtual vehicle through the first-layer road condition information interface.

4. The virtual vehicle route planning method according to claim 1, characterized in that, If the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, then when the virtual vehicle sends a query request again, all the target information nodes will be provided to the virtual vehicle, and the virtual vehicle will plan a new driving route based on all the target information nodes, including: When the virtual vehicle sends a query request again through the second-layer traffic information interface, it obtains all information nodes located on the current road segment and returns them to the virtual vehicle through the second-layer traffic information interface. The virtual vehicle then plans a new driving route based on all the target information nodes.

5. The virtual vehicle route planning method according to claim 1, characterized in that, The method further includes: When the virtual vehicle determines that the road condition event on the current road segment has ended or changed, it deletes the information node corresponding to the ended road condition event or the changed path event.

6. The virtual vehicle route planning method according to claim 1, characterized in that, The method further includes: The information nodes are periodically updated based on the event status of the traffic events corresponding to each information node.

7. A virtual vehicle route planning device, characterized in that, include: The perception module is used to perceive road conditions during the game using various virtual vehicles, and to package the event information of each road condition event into information nodes to form an information node queue. The determination module is used to determine the road condition impact value of the current road segment based on all target information nodes corresponding to the current road segment of the virtual vehicle when the virtual vehicle issues a road condition query request, and provide it to the virtual vehicle. The decision module is used to provide all target information nodes to the virtual vehicle when the virtual vehicle sends a query request again if the virtual vehicle determines that the road condition impact value is greater than or equal to a preset threshold, so that the virtual vehicle can plan a new driving route based on all target information nodes; otherwise, no processing is performed.

8. An electronic device, characterized in that, It includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor executing the machine-executable instructions to implement the virtual vehicle route planning method according to any one of claims 1-6.

9. A storage medium having machine-executable instructions stored thereon, characterized in that, When the machine-executable instructions are executed by the processor, they implement the virtual vehicle route planning method as described in any one of claims 1-6.

10. A program product, characterized in that, The program product runs machine-executable instructions, which, when executed by a processor, implement the virtual vehicle route planning method as described in any one of claims 1-6.

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