Movement planning method, apparatus, and electronic equipment based on an intelligent drive system

Abstract

The embodiments of this disclosure relate to the technical field of intelligent drives, and more particularly to motion planning methods, apparatus and electronic devices based on intelligent drive systems. [Solution] A travel planning method based on an intelligent drive system includes the steps of: acquiring a first voice from a user; determining at least one travel requirement of the user for the current trip based on the first voice; determining at least one travel task to be planned during the current trip based on the at least one travel requirement; determining at least one item to be planned for each travel task; and planning the at least one item to be planned for each travel task and obtaining the planning result for the corresponding travel task.

Description

Technical Field

[0001] The present disclosure relates to the technical field of intelligent driving, and particularly to a travel planning method, apparatus, and electronic device based on an intelligent driving system.

Background Art

[0002] An intelligent driving system is a system for realizing intelligent driving of a vehicle. The intelligent driving system can provide a travel planning function, whereby a travel plan can be made for a user when the user drives or rides in the vehicle.

[0003] When providing a travel planning function to a user, the intelligent driving system needs to perform multiple interactions with the user. In each interaction, the intelligent driving system obtains the user's voice command, which indicates the item to be planned for this travel or includes instruction information for completing the item to be planned. Accordingly, the intelligent driving system plans the item to be planned based on multiple voice commands between the intelligent driving system and the user, thereby meeting the user's travel requirements for this travel. That is, the user needs to determine the item to be planned for this travel based on the travel requirements to be met in this travel and assist the intelligent driving system to complete the plan for the item to be planned. The intelligent driving system can only passively plan the item to be planned indicated by the user and complete the travel plan.

Summary of the Invention

Problems to be Solved by the Invention

[0004] Current intelligent drive systems can only plan travel based on the user's voice commands for each planned item. This method requires the user to clearly specify the particular items to be planned and to gradually complete the travel plan through multiple interactions, resulting in a cumbersome process and a poor user experience. [Means for solving the problem]

[0005] To address the technical challenges described above, this disclosure provides a motion planning method, apparatus, and electronic equipment based on an intelligent drive system, thereby solving the problem of the current intelligent drive system's complicated planning process, which requires the user to determine and instruct the items to be planned themselves.

[0006] A travel planning method based on an intelligent drive system according to a first aspect of the present disclosure includes the steps of: acquiring a first voice of a user; determining at least one travel requirement of the user for the current travel based on the first voice; determining at least one travel task to be planned during the current travel based on the at least one travel requirement; determining at least one planning item included in each travel task; and planning the at least one planning item included in each travel task to obtain a planning result for the corresponding travel task.

[0007] A travel planning device based on an intelligent drive system according to a second aspect of the present disclosure includes: an interaction module used to acquire a first voice from a user; a strategizing module used to determine at least one travel requirement of the user for the current travel based on the first voice; and a planning module used to plan at least one planning item included in each travel task and to acquire a planning result for the corresponding travel task, wherein the strategizing module is further used to determine at least one travel task to be planned during the current travel based on at least one travel requirement, and the strategizing module is further used to determine at least one planning item included in each travel task.

[0008] A computer-readable storage medium according to a third aspect of this disclosure stores a computer program for executing a movement planning method based on the intelligent drive system according to the first aspect described above.

[0009] An electronic device according to a fourth aspect of this disclosure comprises a processor and a memory for storing instructions that can be executed by the processor, wherein the processor reads and executes the executable instructions from the memory and is used to realize a motion planning method based on an intelligent drive system according to the first aspect. [Effects of the Invention]

[0010] According to the travel planning method based on the intelligent drive system described herein, the system understands the user's travel intention by acquiring the user's first voice command and determines at least one travel requirement for the current trip based on the travel intention. Next, based on these travel requirements, it determines at least one travel task to be planned during the current trip and at least one planning item included in each travel task. Finally, it plans each planning item to obtain the planning result for the corresponding travel task. In this process, the user only needs to give a complex command (i.e., the first voice command) containing multiple travel requirements at once, and does not need to give instructions for each planning item individually, thus simplifying the user's operation procedure. Furthermore, since the intelligent drive system can automatically determine and plan planning items for each travel task without requiring explicit specification from the user, it can avoid incomplete travel plans due to the user forgetting a planning item, thereby improving the accuracy and practicality of the travel plan. [Brief explanation of the drawing]

[0011] [Figure 1] This is a structural block diagram of an intelligent drive system according to one exemplary embodiment of the present disclosure. [Figure 2] This is a flowchart of a motion planning method based on an intelligent drive system according to one exemplary embodiment of the present disclosure. [Figure 3] This is a schematic diagram of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 4] This is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 5] This is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 6] This is a schematic diagram of a flow chart for voluntarily determining the purpose of movement according to one exemplary embodiment of the present disclosure. [Figure 7] This is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 8] This is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 9] This is a schematic diagram of a flow that triggers a planning operation for a planned item based on temporary information relating to one exemplary embodiment of the present disclosure. [Figure 10] This is a schematic diagram of a flow that triggers a planning operation for a planned item based on temporary information relating to another exemplary embodiment of this disclosure. [Figure 11] This is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 12] This is a schematic diagram of a flow chart for determining the planned results of objectives related to one exemplary embodiment of the present disclosure. [Figure 13] This is a schematic diagram of the flow for determining the planned results of objectives related to another exemplary embodiment of this disclosure. [Figure 14] This is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure. [Figure 15] This is a schematic diagram of the structure of a motion planning device based on an intelligent drive system according to one exemplary embodiment of the present disclosure. [Figure 16] This is a structural diagram of an electronic device relating to one exemplary embodiment of the present disclosure. [Modes for carrying out the invention]

[0012] To illustrate this disclosure, exemplary embodiments of this disclosure will be described in detail below with reference to the drawings. Clearly, the embodiments described are only a selection of embodiments of this disclosure, not all embodiments, and it should be understood that this disclosure is not limited to exemplary embodiments.

[0013] It should be noted that the relative arrangements, mathematical formulas, and numerical values of the components and steps described in these embodiments do not limit the scope of the present disclosure unless specifically described otherwise.

[0014] Application Summary In an intelligent driving system, the system can plan the matters to be planned in the command based on the user's voice command. However, current intelligent driving systems need to interact with the user multiple times to obtain the user's voice commands for each matter to be planned in order to create a complete travel plan. For example, the user inputs a voice command "Please navigate to Company B in City A" to the intelligent driving system. The intelligent driving system analyzes key information such as the starting point and destination, and based on this, creates a travel route from the user's current location to Company B in City A. Then, considering the need to refuel on the way, the user issues a voice command "Please add Gas Station C as a route point" to the intelligent driving system again. The intelligent driving system analyzes the user's voice command again and adds the matter to be planned, namely Gas Station C, to the original travel route. This is repeated until the user determines that all matters to be planned for this trip are planned. After that, the intelligent driving system can finally provide the user with a complete travel plan.

[0015] In this method, the user needs to interact with the intelligent driving system multiple times, the operation process is cumbersome, and the user's operation cost and time cost increase. Also, in the way the user instructs each matter to be planned, the user needs to have a high level of planning ability. If the user forgets a certain matter to be planned, the intelligent driving system cannot add this matter spontaneously, so the final travel plan may not be able to meet all the user's travel requirements.

[0016] Embodiments of this disclosure provide a travel planning method based on an intelligent drive system, in which the user can directly specify the travel requirements for the current trip, and the intelligent drive system automatically determines the planning items to fulfill these travel requirements. Furthermore, the user can specify all the travel requirements for the current trip at once, and the intelligent drive system automatically determines the specific planning items to fulfill each of the travel requirements. The intelligent drive system can then automatically plan the determined specific planning items and complete the travel plan. This effectively solves the problem of a complicated planning process that would otherwise require the user to determine the planning items themselves and then step-by step-by step-by-step to instruct the intelligent drive system to plan them.

[0017] Exemplary System Figure 1 is a structural block diagram of an intelligent drive system according to one exemplary embodiment of the present disclosure.

[0018] Here, the intelligent drive system can be applied to autonomous vehicles, and when a user is driving or riding in the vehicle, the intelligent drive system can create a travel plan based on the user's travel requirements.

[0019] As shown in Figure 1, in one embodiment, the intelligent drive system may include an interaction system 10, a decision-making system 20, and a driving control system 30. The decision-making system 20 can transmit data to the interaction system 10 and the driving control system 30, respectively. The interaction system 10 may include a touchscreen, buttons, a microphone, an external device interface, etc. This allows the interaction system 10 to receive commands entered by the user in various ways, for example, by receiving a first voice input from the user via the microphone. Based on the first voice acquired by the interaction system 10, the decision-making system 20 understands the user's travel intentions and specific requirements, determines the items to be planned, and further creates a corresponding travel plan for each item to obtain a complete travel plan result for the current trip. The driving control system 30 can control the vehicle's movement based on the planning result output from the decision-making system 20.

[0020] In one embodiment, the intelligent drive system may further include a sensing system 40. The sensing system 40 may include at least one sensor, such as an image sensor, which may include at least one of a monocular camera, a binocular camera, a trinocular camera, a wide-angle camera, and a fisheye camera. The sensing system 40 is used to collect environmental data around the vehicle, which may include, for example, real-time traffic information, road conditions, and weather conditions. The sensing system 40 can communicate data with the decision-making system 20, for example, by transmitting the collected environmental data around the vehicle to the decision-making system 20. This allows the decision-making system 20 to create a travel plan that is better suited to the actual driving environment based on the first voice and environmental data.

[0021] In one embodiment, the decision-making system 20 may include one or more processors 201. The processors 201 may include general-purpose processors such as a central processing unit (CPU) or a graphics processing unit (GPU), or they may include accelerated computing units designed for deep learning tasks, autonomous driving tasks, etc., such as a neural network processor (NPU).

[0022] In one embodiment, the decision-making system 20 may further include one or more memories 202 that can store program instructions executable by the processor 201, and the processor 201 can load and execute the program instructions in the memories 202 to realize the functions of the decision-making system 20.

[0023] Furthermore, memory 202 can also be used to cache or store intermediate or result data generated by the processor 201 during operation, and to store system files, application files, data files, etc. For example, memory 202 can store environmental data collected by the sensing system 40.

[0024] For example, memory 202 may include volatile memory devices such as dynamic random access memory (DRAM) and static random access memory (SRAM), and may also include non-volatile memory devices such as read-only memory (ROM) and flash memory (NVM).

[0025] In one embodiment, the driving control system 30 may include one or more electronic control units (ECUs). The driving control system 30 can execute commands of the decision-making system 20 via the one or more ECUs.

[0026] Exemplary Method Figure 2 is a flowchart of a motion planning method based on an intelligent drive system according to one exemplary embodiment of the present disclosure. This embodiment can be applied to electronic devices, and as shown in Figure 2, the method comprises the following steps 100 to 500.

[0027] In step 100, the user's first voice is obtained.

[0028] For example, the interaction system 10 of the intelligent drive system can acquire a first voice input from the user via a microphone or the like. Here, the first voice includes a travel command issued by the user based on the planned objectives of the current trip. In one example, compared to a concise and clear travel command such as "Please navigate me to Company B in City A" input by the user in a conventional travel planning method, the travel command included in the first voice in this disclosure can contain more information. For example, the first voice V1 may include the following: "Today, I am going on a business trip to Company B in City A and will be staying there for one night. After work, I would like to eat out with my colleagues and look for local specialty dishes."

[0029] Figure 3 is a schematic diagram of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0030] As shown in Figure 3, before inputting the first voice command, the user can activate the intelligent assistant application of the intelligent drive system by, for example, inputting "Hello, XX" by voice, thereby enabling interaction between the intelligent drive system and the user via the intelligent assistant application. For example, after activating the intelligent assistant application, the user can input the aforementioned first voice command V1 through the intelligent assistant application.

[0031] In step 200, based on the first voice, determine at least one of the user's travel requirements for this trip.

[0032] For example, an intelligent driving system uses natural language processing techniques such as the Whisper model and LLMs (Large Language Models) to analyze the first speech, understand the user's intention to move, and determine the user's movement requirements for the current trip.

[0033] Here, travel requirements refer to relevant descriptions provided by the user regarding the planned goals of the current trip, and include, but are not limited to, the user's desired destination, estimated arrival time, and special needs such as meals and accommodation during the trip. This disclosure shows that the first speech can be analyzed using the natural language processing techniques described above to obtain the corresponding travel requirements. In one example, if the first speech is relatively long, it can be determined that the first speech contains a lot of information, and in this case, multiple travel requirements can be extracted from the first speech. As shown in Figure 3, for the aforementioned first speech V1, by analyzing this first speech V1, several travel requirements can be extracted, such as the navigation-related travel requirement R1, "Business trip to Company B in City A," the hotel-related travel requirement R2, "Staying overnight," and the meal-related travel requirement R3, "Finding local specialty dishes."

[0034] In step 300, at least one travel task to be planned during the current travel is determined based on at least one travel requirement.

[0035] For example, an intelligent drive system can determine the travel tasks that need to be planned for the current trip based on each travel requirement, with each travel requirement corresponding to one travel task. For instance, based on the aforementioned travel request R1, it can determine travel task J1, "Go to company B in city A," based on the aforementioned travel requirement R2, it can determine travel task J2, "Go to a hotel," and based on the aforementioned travel request R3, it can determine travel task J3, "Go to a restaurant."

[0036] In step 400, determine at least one planning item to be included in each travel task.

[0037] Here, the planning items include specific steps that need to be planned and executed to complete a travel task, such as navigation to destination a, booking a hotel of type b, etc., and each travel task can correspond to at least one planning item. In one example, a travel task can be analyzed and broken down into one or more distinct steps, and the corresponding planning item can be obtained based on each step. As shown in Figure 3, for the aforementioned travel task J1, the planning item M15, "Determine the route to company B in city A," can be determined for the aforementioned travel task J2, the planning item M2, "Determine a hotel," can be determined for the aforementioned travel task J3, the planning item M3, "Determine a restaurant."

[0038] For example, an intelligent drive system can analyze a travel task and obtain multiple planning items. These planning items may include items that are strongly related to the content of the travel task and items that are obtained through association or other means and are less strongly related to the content of the travel task. Strongly related planning items are those that need to be planned and completed in order to complete the travel task, and failure to complete these items will result in the travel task failing. Less related planning items are those that address new needs indirectly caused by the travel task, and while planning and completing these items can improve the travel experience, failure to complete them will not directly lead to the failure of the travel task. For example, for the aforementioned travel task J1, in addition to deciding on planning item M15, "Determine the route to company B in city A," which is strongly related to the task content "Go to company B in city A," it is also possible to decide on planning item M11, "Determine the location of company B in city A," which is strongly related to the task content "Go to company B in city A." Furthermore, it is also possible to decide on planning items that are less strongly related to the task content "Go to company B in city A," such as M12, "Determine an energy refueling spot," and M13, "Determine a service area."

[0039] In step 500, plan at least one planning item included in each travel task and obtain the planning result for the corresponding travel task.

[0040] For example, by planning each item individually, a planning result corresponding to each travel task can be obtained. For instance, for the aforementioned travel task J1, item M11 can be planned, i.e., the location of company B in city A can be determined, and item M15 can be planned, i.e., the route from the user's location to company B in city A can be planned, thereby obtaining a navigation plan result from the user's location to company B in city A. Furthermore, after the planning result is obtained, the corresponding planning result can be displayed to the user through the interface until the execution of the planning result is complete.

[0041] As can be seen from the above technical proposal, the method according to the embodiment of this disclosure understands the user's travel intention by acquiring the user's first voice and determines at least one travel requirement for the current trip based on the travel intention. Next, based on these travel requirements, it determines at least one travel task to be planned during the current trip and at least one planning item to be included in each travel task. Finally, it plans each planning item to obtain the planning result for the corresponding travel task. In this process, the user only needs to give a complex command (i.e., the first voice) containing multiple travel requirements at once, and does not need to give instructions for each planning item one by one, thus simplifying the user's operation procedure. Furthermore, since the intelligent drive system can automatically determine and plan planning items for each travel task without requiring explicit specification from the user, it can prevent the user from forgetting a planning item and improve the completeness and practicality of the travel plan.

[0042] Figure 4 is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0043] As shown in Figure 4, based on the embodiment shown in Figure 2, step 200 may include the following steps 210 and 220.

[0044] In step 210, the first audio is converted to the first text.

[0045] For example, technologies such as Automatic Speech Recognition (ASR) can be used to convert a first speech into a first text in text format, which facilitates subsequent natural language understanding and analysis.

[0046] In step 220, a semantic analysis is performed on the first text to obtain at least one semantic result, where each semantic result corresponds to one movement requirement.

[0047] For example, techniques such as Natural Language Processing (NLP) can be used to perform semantic analysis on a first text to identify and extract key information within the text, such as destination, time requirements, and activity schedules, and to obtain corresponding semantic results based on this information. In some cases, because the first text contains a large amount of content, multiple semantic results can be obtained based on the first text to avoid information loss and ensure the completeness of the semantic analysis.

[0048] Here, each semantic result corresponds to one travel requirement; that is, each semantic result is a textual description of one travel requirement. For example, for the first speech V1 mentioned above, based on the first text T1 converted from this first speech V1, we can obtain several semantic results, such as S1, which corresponds to the aforementioned travel requirement R1, saying "Today I will be on a business trip to company B in city A"; S2, which corresponds to the aforementioned travel requirement R2, saying "I will be staying there for one night"; and S3, which corresponds to the aforementioned travel requirement R3, saying "After work I want to eat out with my colleagues and look for local specialty dishes."

[0049] As can be seen from the above technical proposal, the method according to the embodiment of this disclosure can convert the user's first speech into text through technologies such as automatic speech recognition and natural language processing, perform semantic analysis on the converted text to obtain semantic results, thereby accurately understanding the user's travel intentions and specific requirements based on the semantic results and providing a basis for creating a travel plan.

[0050] Figure 5 is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0051] As shown in Figure 5, based on the embodiment shown in Figure 2, step 300 may include the following steps 310, 320, and 330.

[0052] In step 310, a first task is determined from among at least one movement task based on at least one movement requirement.

[0053] For example, based on the clear planning instructions included in each travel requirement, a first task that needs to be planned for the current trip can be determined. In some embodiments, the first voice input from the user usually clearly indicates that navigation to a certain destination is required, so the travel requirement obtained based on the first text includes clear navigation route planning instructions, and therefore the first task can be a navigation-type task. For example, if the travel requirement is "to travel to City A on a business trip," then it can be determined that the travel requirement includes the clear planning instruction "to go to City A," and therefore the first task, which belongs to the navigation task category, can be determined to be "to navigate to City A."

[0054] In step 320, the purpose of the current move is determined based on at least one travel requirement.

[0055] The purpose of the trip is determined by analyzing the user's intent included in the travel requirements. Here, the purpose of the trip may be, but is not limited to, business trips, dropping off or picking up children, commuting, dropping off or picking up friends at the airport / station, self-drive tours, shopping, dining out, etc.

[0056] For example, given the aforementioned travel requirement of "traveling to City A on a business trip," the purpose of this trip can be determined to be "business travel."

[0057] For example, in a scene where the first audio corresponds to multiple travel requirements, the final travel objective can be obtained by comprehensively analyzing the multiple travel requirements contained in the first audio from an overall perspective, based on the dependencies between each travel requirement. For instance, the aforementioned travel requirements R1, R2, and R3 can be comprehensively analyzed. Travel requirements R2 and R3 depend on travel requirement R1; that is, in a tree structure, travel requirement R1 can be the parent node, and travel requirements R2 and R3 can be the child nodes. Therefore, instead of analyzing travel requirements R1, R2, and R3 individually to obtain the three travel objectives of "business trip," "hotel stay," and "dining out," the travel objective of this trip, "business trip," can be obtained based on travel requirement R1.

[0058] For example, if none of the movement requirements clearly indicate the purpose of movement, and it is not possible to deduce the purpose of movement suggested by the movement requirements through inference based on the movement requirements, the purpose of movement can be inferred based on environmental information inside and outside the vehicle collected by the sensing system 40.

[0059] Figure 6 is a schematic diagram of a flow chart for independently determining the purpose of movement according to one exemplary embodiment of the present disclosure.

[0060] As shown in Figure 6, in one embodiment, the purpose of the current trip can be determined based on the information collected by the sensing system 40. Here, the information collected by the sensing system 40 may include the number of passengers, luggage, and other in-vehicle environmental information collected by the in-vehicle cameras and sensors. In this way, the intelligent drive system can infer the purpose of the current trip, such as a business trip, dropping off or picking up children, going to or from the airport, or shopping, based on the information collected by the sensing system 40 and the self-inference capabilities of the large-scale model built into the system. In one example, the intelligent drive system can further infer a more accurate purpose of the trip by combining the travel requirements with the information collected by the sensing system.

[0061] In step 330, a second task is determined from at least one travel task based on the purpose of the travel.

[0062] For example, based on the purpose of the current trip, a second task can be determined through methods such as association. Here, the second task is a travel task related to the current trip, but it cannot be determined based on the clear planning instructions included in each travel requirement. For example, the first voice input from the user usually only clearly indicates that navigation to a certain destination is needed, and overlooks other actual needs related to the destination, such as needs related to lifestyle services such as accommodation and meals. Therefore, the second task can be a lifestyle service type task. For example, regarding the aforementioned purpose of travel, "business trip," the user does not explicitly indicate that a hotel needs to be booked, but considering that the event schedule related to the business trip may not be able to be completed in one day, the second task "book a hotel" can be derived.

[0063] Referring to Figure 6 above, after determining that the purpose of travel is airport transfer, the corresponding second task, such as "flight search" or "delay notification," can be determined. Furthermore, it can determine whether the final destination needs to be changed depending on the purpose of travel. For example, if the purpose of travel is "business trip," the system can determine whether to change the destination, "City A, Company B," to the hotel where the user is staying, and notify the user accordingly. In this way, the intelligent drive system can provide personalized services to the user based on the second task of the lifestyle service type.

[0064] As can be seen from the above technical proposal, the method according to the embodiment of this disclosure can acquire a first task based on clear planning instructions in the travel requirements, and further acquire the travel purpose based on the travel requirements and add a second task related to the current travel. In this way, based on the user's travel requirements and combined with the travel purpose, the actual needs of the user can be fully and deeply understood, and travel planning can be made more complete by considering not only the planning instructions that the user has clearly indicated, but also by inferring the planning instructions that the user may need based on the travel purpose but that have not been clearly indicated, thereby improving the degree of intelligence and personalization in the creation of travel plans and improving the user experience.

[0065] Figure 7 is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0066] As shown in Figure 7, based on the embodiment shown in Figure 2, step 400 may include the following steps 410, 420, and 430.

[0067] In step 410, the purpose of the current move is determined based on at least one travel requirement.

[0068] We will thoroughly understand the travel requirements and analyze the user's intent to determine the purpose of this trip. For a detailed explanation of step 410, please refer to step 320 mentioned above, and we will omit the redundant explanation here.

[0069] In step 420, determine the task type for each movement task.

[0070] To facilitate targeted planning based on different task types, taking into account the diversity of travel tasks, the task type of each travel task can be determined based on the specific content of each travel task.

[0071] In one embodiment, the types of travel tasks may include navigation tasks, lifestyle service tasks, and entertainment tasks. For example, regarding the aforementioned travel task J1, "Go to company B in city A," it can be determined that the task type is a navigation task; regarding the aforementioned travel task J2, "Go to a hotel," it can be determined that the task type is a lifestyle service task; and regarding the aforementioned travel task J3, "Go to a restaurant," it can be determined that the task type is a lifestyle service task.

[0072] In step 430, at least one planned item is determined to be included in each travel task, based on the first correspondence between the task type and the item, and the second correspondence between the travel purpose and the item.

[0073] Here, a task type may have a first correspondence with at least one item. The first correspondence between a task type and an item can be used to indicate the items that generally need to be planned for a travel task corresponding to that task type. For example, for a navigation-type task, the items that generally need to be planned may include route planning, i.e., a navigation-type task may have a first correspondence with route planning items. For a lifestyle services-type task, the items that generally need to be planned may include hotel reservations, restaurant reservations, ticket purchases, etc., i.e., a lifestyle services-type task may have a first correspondence with hotel reservations, restaurant reservations, ticket purchases, etc. The first correspondences in this disclosure are not limited to the task types and items described above.

[0074] Here, one purpose of travel can have a second correspondence with at least one item. The second correspondence between the purpose of travel and the item can be used to indicate the items that generally need to be planned for that purpose of travel. For example, for the purpose of travel "business trip," the items that generally need to be planned include hotel reservations and restaurant reservations, so a business trip can have a second correspondence with hotel reservations and restaurant reservations. Similarly, dropping off or picking up children can have a second correspondence with parking decisions, commuting can have a second correspondence with parking decisions and route selection, dropping off or picking up friends at the airport / station can have a second correspondence with inquiries about flight numbers / high-speed train numbers / subway train numbers, a self-drive tour can have a second correspondence with travel planning, hotel reservations, restaurant reservations, tourist attraction tickets, and refueling / charging, shopping can have a second correspondence with parking, and dining out can have a second correspondence with seat reservations and parking. The second correspondence of this disclosure is not limited to the above-mentioned purposes and matters of movement.

[0075] From the perspective of task type and travel purpose, the first and second correspondences can be integrated to determine the planning items included in each travel task. For example, regarding the aforementioned travel task J1, "Go to company B in city A," if it is determined that the task type is a navigation type task, then based on the first correspondence between navigation type tasks and route creation items, the planning item M11, "Determine the location of company B in city A," and the planning item M15, "Determine the route to company B in city A," can be determined. Furthermore, since the task type is determined to be a navigation type task and the travel purpose is "business trip" and not picking up or dropping off a friend at the airport / station, based on the second correspondence between navigation type tasks and the purpose of the business trip... If we can determine that the planning item M14 is "decide on a parking lot," and if we determine that the aforementioned travel task J2 is "go to a hotel," and that its task type is a lifestyle service type task and its purpose of travel is "business trip," then we can determine that the planning item M2 is "decide on a hotel" based on the first correspondence between lifestyle service type tasks and hotel reservation items, and the second correspondence between business trips and hotel reservation items. Similarly, if we determine that the planning item M3 is "decide on a restaurant" for the aforementioned travel task J3, "go to a restaurant," then we can determine that the planning item M3 is "decide on a restaurant."

[0076] As can be seen from the above technical proposals, the method according to the embodiments of this disclosure determines the task type and the travel purpose, and then determines the planning items to be included in each travel task by combining the first correspondence between the task type and the items, and the second correspondence between the travel purpose and the items. In this way, more accurate and practical planning items can be obtained, taking into account that different types of travel tasks correspond to different planning items, and different travel purposes correspond to different necessary / unnecessary planning items. This improves the accuracy and practicality of the travel plan, and makes the travel plan more in line with the actual needs of the user.

[0077] Figure 8 is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0078] As shown in Figure 8, based on the embodiment shown in Figure 2, step 500 may include the following steps 510, 520, 530, and 540.

[0079] In step 510, monitor the trigger events for each planned item included in each travel task.

[0080] After determining each planning item, the system monitors the trigger events for each planning item included in each travel task. Here, each planning item can correspond to at least one trigger event, which is an event that initiates a planning operation for the planning item. In this way, the intelligent drive system can respond to trigger events and perform planning operations on the planning item corresponding to the trigger event.

[0081] In one embodiment, if there is an execution order between each planned item, the trigger event can be the planning result of another planned item. For example, after planning item M2, "decide on a hotel," and obtaining the corresponding planning result, this planning result can be used as the trigger event for planned item M3, "decide on a restaurant." In other words, after the planning for planned item M2, "decide on a hotel," is completed, the planning for planned item M3, "decide on a restaurant," is triggered.

[0082] In another embodiment, the trigger event can be temporary information such as a user's temporary instruction, real-time vehicle status, real-time road conditions, the user's real-time state, or real-time driving behavior.

[0083] Figure 9 is a schematic diagram of a flow that triggers a planning operation for a planning target based on temporary information in one exemplary embodiment of the present disclosure.

[0084] Illustratively, as shown in Figure 9, the trigger events corresponding to the planned item M12, "Determine an energy refueling spot," can include system spontaneous judgment, changes in route / road conditions, energy refueling instructions included in a first voice input from the user, other temporary situations, and spontaneous associations of a large-scale model of the intelligent drive system, where system spontaneous judgment includes, for example, the intelligent drive system determining before starting the move that there is insufficient battery power to complete the entire move based on the vehicle's current battery level and the distance from the starting point to company B in city A; changes in route / road conditions include, for example, the vehicle missing an exit ramp on the way to company B in city A, resulting in a longer travel distance; energy refueling instructions included in a first voice input from the user include, for example, "I'd like to charge the vehicle on my way to XX"; and other temporary situations include, for example, the vehicle suddenly receiving instructions from the user while on its way to company B in city A. When any trigger event corresponding to planning item M12, "Determine an energy refueling spot," is monitored, a planning operation can be performed for planning item M12, "Determine an energy refueling spot," corresponding to this event. In this way, the intelligent drive system can perform dynamic planning in real time in response to user needs and environmental changes, thereby improving the practicality of the planning results.

[0085] Figure 10 is a schematic diagram of a flow that triggers a planning operation for a planning target based on temporary information relating to another exemplary embodiment of the present disclosure.

[0086] For example, as shown in Figure 10, the intelligent drive system can trigger the event "Determine service area" if it determines, based on user preferences, that the user prefers to take a break after a certain length of continuous driving time, or if it senses user fatigue through a camera or other means, or if there is another trigger based on association. This triggers the system to execute a planning operation for the corresponding planning item M13, "Determine service area."

[0087] In step 520, a trigger instruction is generated based on the trigger event.

[0088] After monitoring a trigger event, a corresponding trigger command can be generated. This trigger command is used to instruct the system to perform a planning operation on a planning target. Here, the trigger command may include the identification information of the planning target and the background information extracted from the trigger event. For example, for planning target M3, "Deciding on a restaurant," the trigger event is the planning result of planning target M2, "Deciding on a hotel." In this case, the trigger command may include the identification information of planning target M2 and background information such as the hotel's location and scheduled check-in time extracted from the trigger event (i.e., the planning result of planning target M2). Furthermore, when deciding on a restaurant, the system can comprehensively consider factors such as the distance from the hotel to the restaurant, the hotel's scheduled check-in time, and the restaurant's operating hours. This allows for a more considerate and personalized restaurant recommendation and reservation service for the user. As another example, regarding planning item M13, "Determine the service area," if the trigger event is the detection of user fatigue, the trigger command can include the fatigue detection result. This allows the system to prioritize selecting the service area closest to the current location when planning for planning item M13, "Determine the service area."

[0089] In step 530, the target items corresponding to the trigger event are determined from each planned item included in each travel task.

[0090] After monitoring trigger events, the target items corresponding to each trigger event can be determined from the planned items. Here, the target items are the planned items that are instructed by the trigger command and require planning operations to be performed. After the target items are determined, the planning operations can be performed on the target items to obtain the corresponding planning results.

[0091] In step 540, based on the trigger command, the objectives are planned and the results of the objective planning are obtained.

[0092] After a trigger command is generated and the objective is determined, the system can plan the objective based on the trigger command and obtain the corresponding planning result. Referring to Figure 9, the intelligent drive system performs a planning operation for the planning objective M12, "Determine an energy refueling spot," and autonomously selects an energy refueling spot based on reference information such as user profile / current status / route and road conditions / price and time consumption, obtains the corresponding planning result, displays it on the interface, adds the selected energy refueling spot as a waypoint to the navigation route, and then replans the navigation route so that the new navigation route can pass through the waypoint. Referring to Figure 10, the intelligent drive system performs a planning operation for the planning objective M13, "Determine a service area," and autonomously selects a service area, obtains the corresponding planning result, displays it on the interface, adds the selected service area as a waypoint to the navigation route, and then replans the navigation route so that the new navigation route can pass through the waypoint.

[0093] Here, if a single travel task includes only one item to be planned, the planning result of this item can be considered the planning result of the travel task. If a single travel task includes multiple items to be planned, the planning result of the last item among the multiple items to be planned is the planning result of the corresponding travel task. For example, the aforementioned travel task J1, "Go to Company B in City A," can include planning item M11, "Determine Company B in City A," M12, "Determine an energy refueling spot," M13, "Determine a service area," M14, "Determine a parking lot," and M15, "Determine a route to Company B in City A." In this case, first, the planning result of M11, i.e., the location of Company B in City A, is obtained. Next, the planning results of M12 and M13, i.e., the energy refueling spot and service area between the current location and Company B in City A, are obtained, respectively. The planning result of M13, i.e., a hotel near Company B in City A, is obtained. Finally, using the energy refueling spot of M12 and the service area of ​​M13 as waypoints and the parking lot of M14 as the route endpoint, the route plan of M11 is executed based on the waypoints and endpoint, and the planning result of M15, i.e., a navigation route and time plan to pass through the energy refueling spot and service area and finally arrive at the parking lot, can be obtained. By doing this, the planning result for M15 can be set to the planning result for travel task J1, which is "Go to company B in city A".

[0094] It should be noted that the planning results for a travel task are not immutable. After obtaining the planning results for a travel task, new objectives can be planned based on new trigger events monitored in real time, thereby updating the planning results for the travel task based on the planning results for the new objectives. For example, if the planning result for M15 is set to travel task J1, "Go to company B in city A," and the intelligent drive system receives a user instruction "I want to buy a bouquet of flowers along the way" while the vehicle is in motion, it will trigger an event called "Decide on a flower shop," and a planning operation will be performed for the planning target item corresponding to this event, "Decide on a flower shop." Based on the planning result for the planning target item "Decide on a flower shop," the navigation route and time plan will be updated, and the updated planning result for travel task J1, "Go to company B in city A," can be obtained.

[0095] As can be seen from the above technical proposal, the method according to the embodiment of this disclosure generates trigger commands based on planning results that monitor trigger events such as other planning targets, determines targets, and plans, thereby allowing consideration of the planning order between different planning targets, reducing redundant and invalid plans, and improving planning efficiency. Furthermore, by monitoring trigger events such as temporary instructions, real-time vehicle and road conditions, and user status, trigger commands are generated, targets are determined, and plans are made, thereby meeting dynamically changing needs and realizing dynamic travel planning. If the user suddenly changes destinations, needs to pass through a specific location, or there are changes in the driving environment and user status, the intelligent drive system can plan in real time, obtain corresponding planning results, and make the planning results more aligned with the actual needs in the current situation.

[0096] Figure 11 is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0097] As shown in Figure 11, based on the embodiment shown in Figure 8, step 540 may include the following steps 541, 542, and 543.

[0098] In step 541, reference information corresponding to the target is determined based on the trigger command.

[0099] For example, based on a trigger command, first, reference information corresponding to the objective is determined, and then a plan is made based on this reference information. Here, the reference information may include at least one of the following extracted from a first voice input from the user: user instructions (e.g., hotel type, budget range, etc.), user information (e.g., user profile / preferences, user status, etc.), and driving information (road conditions, weather, driving behavior, etc.), and may also include other information such as information on lifestyle service types related to the objective, and this disclosure is not limited thereto. Here, different items may correspond to different reference information.

[0100] For example, in Figure 9 mentioned above, the intelligent drive system can determine reference information such as user profile, current status, route and road conditions, price and time consumption in response to the planned item M12, "determining an energy refueling spot."

[0101] In step 542, the objectives are planned based on reference information corresponding to the objectives, and the initial planning results for the objectives are obtained.

[0102] Based on reference information corresponding to the objective, and further combined with information such as the task type of the travel task corresponding to the objective, the objective can be planned. For example, if the objective is to "determine a route to Company B in City A," then based on real-time road conditions, road restrictions, and other driving information, combined with a navigation algorithm, the optimal route from the current location to Company B in City A can be obtained as an initial planning result. As another example, if the objective is to "decide on a hotel," then based on user instructions such as hotel requirements including hotel brand, budget, date and time, distance from destination, and applicable scenes, and combined with user information such as the user's preferred hotel type and price range, as well as other information related to "deciding on a hotel," such as the hotel distribution in City A and hotel ratings, a hotel that meets the user's needs can be obtained as an initial planning result. Here, each hotel that meets the user's needs can be used as one initial planning result.

[0103] In step 543, the plan results for the objectives are obtained based on the initial plan results for the objectives.

[0104] If the intelligent drive system can obtain a uniquely determined initial planning result based on reference information, this initial planning result is determined as the planned result for the objective.

[0105] Figure 12 is a schematic diagram of the flow for determining the planned outcome of an objective item in one exemplary embodiment of the present disclosure.

[0106] As shown in Figure 12, regarding the aforementioned objective "to determine company B in city A," if searching for company B in city A on the map yields only one result, this search result can be designated as the planned outcome for the objective "to determine company B in city A." If searching for company B in city A on the map yields multiple results, one result can be automatically selected from the multiple results based on reference information to be the planned outcome for the objective "to determine company B in city A." For example, based on information such as upstream and downstream related companies of the company where the user works in the user profile, it is possible to determine which company B the user is most likely to visit from among the multiple companies B found. After the plan for the objective "to determine company B in city A" is completed, the plan results, i.e., the location and image of the determined company B in city A, can be displayed.

[0107] Figure 13 is a schematic diagram of a flow chart for determining the planned results of objectives in another exemplary embodiment of the present disclosure.

[0108] As shown in Figure 13, the objective, "to decide on a parking lot," can be planned before starting destination navigation, and the decided parking lot can be set as the new destination, or it can be planned just before arriving at the destination. In the specific planning process, it is first possible to determine whether there is a parking lot at the destination or waypoint. If there is a parking lot a, it is possible to check whether there is an available space in parking lot a, and if there is an available space, this parking lot a can be set as the planned outcome for the objective, "to decide on a parking lot." In this way, as the user approaches the parking lot, information and images of parking lot a can be displayed.

[0109] In one embodiment, if the intelligent drive system cannot obtain a uniquely determined initial planning result based on reference information, all of the multiple initial planning results can be fed back to the user, and the planning result for the target can be determined based on further instructions from the user regarding the initial planning results.

[0110] Referring again to Figure 12, regarding the aforementioned objective of "determining company B in city A," if multiple companies in city A and B are found and each company can be used as an initial plan result, an interface can pop up displaying multiple companies in city A and B with the message, "I cannot determine which company in city A and B is correct, please tell me." At this time, the user can select the Nth company in city A and B from the multiple companies in city A and B displayed on the interface by directly saying "Nth," manually clicking on option N, or pointing to the number "N." After that, the option corresponding to the Nth company in city A and B will be displayed on the interface for a certain period of time with a hit effect such as a sustained highlight effect for 0.5 seconds. If the user does not change to another option within this period, the Nth company in city A and B will be selected as the final plan result, and its location information and image information will be displayed.

[0111] Referring again to Figure 13, regarding the objective "to determine a parking space," if there are no available spaces in the destination parking lot a, the system can search for available spaces in parking lots a short distance away (e.g., within 500 meters). If parking lot b with available spaces within 500 meters is found, the interface can display information about parking lot b and ask the user if they can park there. Upon receiving confirmation from the user, parking lot b can be set as the initial plan result for the objective "to determine a parking space." In this way, as the user approaches the parking lot, information and images of parking lot b can be displayed.

[0112] Referring again to Figure 13, if no further instructions are received from the user, the system can display corresponding information to the user before they perform this objective, prompting them to take action themselves. For example, regarding the objective "determine a parking space," if there are no available spaces in parking lot a at the destination, and the user has not confirmed that they can park in parking lot b, the system can display information and images of the destination through the interface as the user drives their vehicle towards the destination and before parking, simultaneously displaying parking prompts such as "You will soon arrive at your destination. No parking information available. Please park in a safe place."

[0113] Furthermore, since the planning results for "deciding on a hotel" and "deciding on a restaurant" can also be obtained using the methods described above, we will omit redundant explanations here.

[0114] As can be seen from the above technical proposals, the method according to the embodiment of this disclosure obtains at least one possible initial plan result based on reference information of the target items, and if a unique initial plan result cannot be obtained, the user is allowed to select one initial plan result from multiple initial plan results as the final plan result through a method such as a user interaction interface. In this way, it is possible to take into account the uncertainty that may exist during the planning of the intelligent drive system and to ensure that the final plan result is more in line with the user's actual needs through interaction with the user, thereby improving the accuracy and practicality of the travel plan.

[0115] Figure 14 is a flowchart of a motion planning method based on an intelligent drive system according to another exemplary embodiment of the present disclosure.

[0116] As shown in Figure 14, based on the embodiment shown in Figure 8, step 540 may include the following steps 544, 545, 546, and 547.

[0117] In step 544, based on the trigger command, the target functions necessary to plan the objectives are determined.

[0118] For example, after generating a trigger command, the corresponding target function can be determined based on the trigger command. Here, a target function refers to the technologies and functions that the intelligent drive system relies on when performing a planned operation for a target item. Different target items can correspond to different target functions. For example, the target item "determine a route to company B in city A" may require target functions such as map point location calculation and navigation algorithms, while the targets "determine a hotel" and "book a hotel" may require target functions such as hotel search algorithms and user profile analysis.

[0119] In step 545, determine the target application for planning the objectives based on the target function.

[0120] Goal functions can be provided by corresponding goal applications. For example, functions such as destination location determination and navigation algorithms can be provided by a map application integrated into the intelligent drive system. If the application primarily used by the intelligent drive system (e.g., the map application) does not have goal planning functions, for example, if the goals are "to decide on a hotel" and "to book a hotel," and the map application of the intelligent drive system does not provide goal search and booking functions, then another application (e.g., a hotel application) can be called to plan.

[0121] In step 546, a call instruction is generated based on the target application.

[0122] After determining the target application, a corresponding call instruction can be generated. Here, a call instruction refers to an instruction that calls the target application and obtains the target function. For example, after determining that the target application is a hotel application, a call instruction C1 for calling the hotel application can be generated.

[0123] In step 547, based on the call instruction, the target application is invoked to obtain the planning results for the target item.

[0124] The intelligent drive system can generate a call command and then send it to a target application. Upon receiving the call command, the target application can plan the objectives based on the objective functions and obtain the planning results. This design allows the intelligent drive system to complete planning for different target objects by utilizing the different objective functions of different target applications based on the call command, thereby improving the overallness of the travel planning.

[0125] For example, based on the aforementioned call command C1, the intelligent drive system can call the hotel application, and further utilize the hotel application's objective functions, such as hotel search, to plan the objective "to decide on a hotel" and obtain the corresponding planning result. It can also plan the objective "to book a hotel," and in this way, hotel reservations can be automatically initiated based on the hotel application.

[0126] As can be seen from the above technical proposals, the method according to the embodiment of this disclosure determines the target functions required for the objective, determines the target application for planning the objective based on the target functions, generates a call command to call the target application and plan the objective. In this way, the shortcomings of the intelligent drive system in its ability to handle matters related to life services can be compensated for, and the comprehensiveness of mobility planning can be improved by making full use of the different functions of the intelligent drive system and other applications.

[0127] The technical proposals relating to this disclosure are not limited to the embodiments described above.

[0128] Exemplary device The above describes a motion planning method based on an intelligent drive system according to an embodiment of the present disclosure. It is understood that in order to realize each function of this motion planning method, the intelligent drive system may include corresponding hardware and software for realizing the hardware functions.

[0129] Those skilled in the art will readily realize that the steps of the motion planning method based on the intelligent drive system described through each embodiment of the present disclosure can be implemented in hardware form or by driving the hardware through software. Whether a function is performed by hardware or by driving the hardware through software depends on the specific application and design constraints of the proposed technique. Those skilled in the art may implement the described functions using different methods for each specific application, but such implementations should not be considered beyond the scope of the present disclosure.

[0130] Figure 15 is a schematic diagram of the structure of a motion planning device based on an intelligent drive system according to one exemplary embodiment of the present disclosure.

[0131] As shown in Figure 15, in one embodiment, the movement planning device 150 based on this intelligent drive system includes an interaction module 151, a strategy module 152, and a planning module 153.

[0132] The interaction module 151 is used to acquire the user's first voice.

[0133] The strategy module 152 is used to determine at least one of the user's travel requirements for the current travel based on the first voice.

[0134] The strategy module 152 is further used to determine at least one movement task to be planned during the current movement, based on at least one movement requirement.

[0135] The strategy module 152 is further used to determine at least one planning item to be included in each movement task.

[0136] The planning module 153 is used to plan at least one planning item included in each travel task and to obtain the planning result for the corresponding travel task.

[0137] In one embodiment, the strategy module 152 is used to convert a first audio to a first text, perform semantic analysis on the first text, and obtain at least one semantic result, where each semantic result corresponds to one movement requirement.

[0138] In one embodiment, the strategy module 152 is used to determine a first task from at least one movement task based on at least one movement requirement, to determine the movement objective of the current movement based on at least one movement requirement, and to determine a second task from at least one movement task based on the movement objective.

[0139] In one embodiment, the strategy module 152 is used to determine the purpose of the current move based on at least one move requirement, to determine the task type of each move task, and to determine at least one planned item to be included in each move task based on a first correspondence between the task type and the item, and a second correspondence between the purpose of the move and the item.

[0140] In one embodiment, the planning module 153 is used to monitor trigger events for each planning item included in each travel task, generate trigger commands based on the trigger events, determine target items corresponding to the trigger events from each planning item included in each travel task, plan the target items based on the trigger commands, and obtain the planning results for the target items, where the planning result for the last target item among the at least one planning item included in each travel task is the planning result for the corresponding travel task.

[0141] In one embodiment, the planning module 153 is used to determine reference information corresponding to the target item based on a trigger command, to plan the target item based on the reference information corresponding to the target item, to obtain an initial planning result for the target item, and to obtain a planning result for the target item based on the initial planning result for the target item.

[0142] In one embodiment, the planning module 153 is used to determine the target function necessary to plan the objective based on a trigger instruction, determine the target application for planning the objective based on the target function, generate a call instruction based on the target application, and call the target application based on the call instruction to obtain the planning result for the objective.

[0143] Beneficial technical effects corresponding to exemplary embodiments of this apparatus can be found by referring to the corresponding beneficial technical effects in the exemplary method section described above, and are therefore omitted from this explanation.

[0144] Exemplary electronic device Figure 16 is a structural diagram of an electronic device according to an embodiment of the present disclosure, the electronic device 160 comprising at least one processor 161 and a memory 162.

[0145] The processor 161 may be a central processing unit (CPU) or another form of processing unit having data processing capability and / or instruction execution capability, and can control other components in the electronic device 160 to perform a desired function.

[0146] Memory 162 may comprise one or more computer program products including various forms of computer-readable storage media such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disks, flash memory, etc. One or more computer program instructions may be stored in the computer-readable storage media, and the processor 161 can execute one or more program instructions to realize a movement planning method and / or other desired functions based on the intelligent drive system of each embodiment of the present disclosure described above.

[0147] In one example, the electronic device 160 may further include an input device 163 and an output device 164 connected to each other via a bus system and / or other form of connection mechanism (not shown).

[0148] The input device 163 may include a keyboard, mouse, or the like.

[0149] The output device 164 may include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and can output various information to the outside.

[0150] For simplicity, Figure 16 shows only some of the components in the electronic device 160 relevant to this disclosure, omitting components such as buses and input / output interfaces. Furthermore, depending on the specific application conditions, the electronic device 160 may further comprise any other suitable components.

[0151] Exemplary computer program products and computer-readable storage media Embodiments of this disclosure may provide a computer program product including computer program instructions in addition to the methods and apparatus described above. When these computer program instructions are executed by a processor, the processor is caused to perform steps of the motion planning method based on the intelligent drive system of each embodiment described in the “Exemplary Methods” portion of this disclosure.

[0152] Computer program products can be created using any combination of one or more programming languages ​​to produce program code for performing the operations of the embodiments of this disclosure, and the programming languages ​​include object-oriented programming languages ​​such as Java® and C++, and conventional procedural programming languages ​​such as the C language or similar programming languages. The program code may run entirely on the user's computing device, partially on the user's device, as separate software packages, partly on the user's computing device and partly on a remote computing device, or entirely on a remote computing device or server.

[0153] Furthermore, embodiments of the present disclosure may also be computer-readable storage media in which computer program instructions are stored. When these computer program instructions are executed by a processor, the processor is caused to perform steps of the movement planning method based on the intelligent drive system of each embodiment described in the “Exemplary Methods” portion of the present disclosure.

[0154] Computer-readable storage media can be any combination of one or more readable media. The readable media may be readable signal media or readable storage media. Readable storage media may include, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include electrical connections with one or more wires, mobile hard drives, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0155] While the basic principles of this disclosure have been explained above with reference to specific examples, the advantages, advantages, and effects mentioned herein are not limited to those mentioned above, but are merely illustrative, and these advantages, advantages, and effects are not necessarily present in every example of this disclosure. Furthermore, the specific details disclosed above are not limited to those mentioned above, but are merely illustrative and intended to facilitate understanding, and these details do not necessarily limit this disclosure to being realized by those specific details.

[0156] A person skilled in the art can make various changes and modifications to this disclosure without departing from the spirit and scope of this disclosure. If such changes and modifications to this disclosure fall within the scope of the claims of this disclosure and the equivalent art, then such changes and modifications are included in this disclosure.

Claims

1. A movement planning method based on an intelligent drive system, wherein each step is performed by a movement planning device based on an intelligent drive system, The steps include obtaining the user's first voice, A step of determining at least one travel requirement of the user for the current trip based on the first audio, A step of determining at least one travel task to be planned during the current travel based on the at least one travel requirement, The steps include determining at least one planning item included in each of the aforementioned movement tasks, A travel planning method based on an intelligent drive system, comprising the steps of planning each of the at least one planning items included in each of the travel tasks and obtaining a planning result for the corresponding travel task.

2. The step of determining at least one of the user's travel requirements for the current trip based on the first audio is: The steps include converting the first audio into a first text, A method for planning a journey based on an intelligent drive system according to claim 1, comprising the steps of performing semantic analysis on the first text and obtaining at least one semantic result, wherein each of the semantic results corresponds to one of the journey requirements.

3. The step of determining at least one travel task to be planned during the current travel based on the at least one travel requirement is: A step of determining a first task from among the at least one movement task based on the at least one movement requirement, A step of determining the purpose of the current move based on at least one of the aforementioned move requirements, A method for planning a move based on an intelligent drive system according to claim 1, comprising the step of determining a second task from among the at least one move task based on the purpose of the move.

4. The step of determining at least one planning item included in each of the aforementioned movement tasks is: A step of determining the purpose of the current move based on at least one of the aforementioned move requirements, The steps include determining the task type for each of the aforementioned movement tasks, A method for planning a move based on an intelligent drive system according to claim 1, comprising the step of determining at least one planned item to be included in each move task based on a first correspondence between the task type and the item, and a second correspondence between the move purpose and the item.

5. The step of planning each of the at least one planning item included in each of the aforementioned movement tasks and obtaining the planning result for the corresponding movement task is: The steps include monitoring the trigger event for each of the planned items included in the aforementioned movement task, The steps include generating a trigger instruction based on the aforementioned trigger event, A step of determining a target item corresponding to the trigger event from each of the planned items included in each of the aforementioned movement tasks, The steps include: planning the objectives based on the trigger command and obtaining the planning results for the objectives; A travel planning method based on an intelligent drive system according to claim 1, wherein the planning result of the last of the at least one planned items included in each travel task is the planning result of the corresponding travel task.

6. The steps of planning the target items and obtaining the planning results for the target items based on the trigger command are as follows: The steps include determining reference information corresponding to the target item based on the trigger command, The steps include: planning the objectives based on reference information corresponding to the objectives and obtaining the initial planning results for the objectives; A method for planning a movement based on an intelligent drive system according to claim 5, comprising the step of obtaining a planning result for the aforementioned objectives based on an initial planning result for the aforementioned objectives.

7. The steps of planning the target items and obtaining the planning results for the target items based on the trigger command are as follows: Based on the trigger command, the steps include determining the target function necessary to plan the target item, The steps include determining a target application for planning the target items based on the aforementioned target function, The steps include generating a call instruction based on the aforementioned target application, A method for planning a journey based on an intelligent drive system according to claim 5, comprising the steps of calling the target application based on the call command and obtaining the planning result for the target item.

8. An interaction module used to acquire the user's first voice, A strategy module used to determine, based on the first voice, at least one travel requirement of the user for the current trip, based on the at least one travel requirement, at least one travel task to be planned during the current trip, and at least one planned item to be included in each of the travel tasks, A motion planning device based on an intelligent drive system, comprising: a planning module used to plan each of the at least one planning items included in each of the motion tasks and to obtain a planning result for the corresponding motion task.

9. A computer-readable storage medium that stores a computer program for performing a movement planning method based on an intelligent drive system according to any one of claims 1 to 7, when executed by a processor.

10. Processor and The processor comprises a memory for storing instructions that can be executed by the processor, The processor is an electronic device used to read and execute the executable instructions from the memory to realize a motion planning method based on an intelligent drive system as described in any one of claims 1 to 7.

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