Service point management method and apparatus, device, storage medium, and program product
By acquiring travel service requests and determining suitable stops based on the attributes of candidate location units, the problem of insufficient real-time response of autonomous vehicles in complex traffic environments is solved, enabling precise stopping and convenient travel services for autonomous vehicles.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- BEIJING VOYAGER TECH CO LTD
- Filing Date
- 2025-10-27
- Publication Date
- 2026-06-11
AI Technical Summary
Existing autonomous vehicles lack the ability to respond and make judgments in real time in complex traffic environments, resulting in low flexibility and efficiency in parking restriction strategies, making them unable to compete with experienced human drivers.
By acquiring travel service requests, and based on the stopping constraints, permitted stopping, and boarding/alighting convenience attributes of candidate location units, suitable stopping stations are determined, and candidate stations are provided to improve the quality of travel services.
It enables autonomous vehicles to accurately select stopping points in complex traffic environments, improving the safety and service quality of the autonomous driving process and providing a more convenient and comfortable passenger experience.
Smart Images
Figure CN2025130187_11062026_PF_FP_ABST
Abstract
Description
A method, apparatus, device, storage medium, and program product for site management.
[0001] This application claims priority to Chinese Patent Application No. 202411793465.7, filed on December 6, 2024, entitled "A Method, Apparatus, Device, Storage Medium and Program Product for Site Management", the entire contents of which are incorporated herein by reference. Technical Field
[0002] The exemplary embodiments disclosed herein generally relate to the field of computers, and particularly to a method, apparatus, device, computer-readable storage medium, and computer program product for site management. Background Technology
[0003] With the rapid development of autonomous driving technology, autonomous vehicles face a series of challenges in practical applications, especially in terms of parking infrastructure, convenience, and site strategies. Existing autonomous vehicles still lack the real-time response and judgment capabilities to match experienced human drivers, particularly in complex traffic environments. This limits the flexibility and efficiency of autonomous vehicles in implementing parking restriction strategies. Summary of the Invention
[0004] In a first aspect of this disclosure, a method for site management is provided. The method includes: obtaining a request for a site for a mobility service associated with an autonomous vehicle; determining a set of location units based on a first attribute and a second attribute of a plurality of candidate location units, the first attribute indicating docking constraints corresponding to the plurality of candidate location units and the second attribute indicating whether selection as a site is permitted; determining at least one location unit from the set of location units based on a third attribute of the set of location units, the third attribute indicating the ease of boarding and alighting for the set of location units; and providing at least one location unit as a candidate site for the mobility service.
[0005] In a second aspect of this disclosure, an apparatus for site management is provided. The apparatus includes: a request acquisition module configured to acquire requests for sites for a mobility service associated with an autonomous vehicle; a first determination module configured to determine a set of location units based on a first attribute and a second attribute of a plurality of candidate location units, the first attribute indicating stopping constraints corresponding to the plurality of candidate location units and the second attribute indicating whether selection as a site is permitted; a second determination module configured to determine at least one location unit from the set of location units based on a third attribute of the set of location units, the third attribute indicating the ease of boarding and alighting for the set of location units; and a site provision module configured to provide at least one location unit as a candidate site for the mobility service.
[0006] In a third aspect of this disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit. When executed by the at least one processing unit, the instructions cause the device to perform the method of the first aspect.
[0007] In a fourth aspect of this disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program that can be executed by a processor to implement the method of the first aspect.
[0008] In a fifth aspect of this disclosure, a computer program product is provided. The computer program product includes computer-executable instructions that, when executed by a processor, implement the method of the first aspect.
[0009] It should be understood that the content described in this summary section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description
[0010] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:
[0011] Figure 1 shows a schematic diagram of an example site management system according to an embodiment of the present disclosure;
[0012] Figure 2 illustrates a schematic diagram of an example process for site management according to some embodiments of the present disclosure;
[0013] Figure 3 illustrates a schematic diagram of an example process for determining docking time limits according to some embodiments of the present disclosure;
[0014] Figure 4 shows a schematic structural block diagram of an example apparatus for site management according to some embodiments of the present disclosure; and
[0015] Figure 5 shows a block diagram of an apparatus capable of implementing several embodiments of the present disclosure. Detailed Implementation
[0016] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.
[0017] It should be noted that the headings of any section / subsection provided herein are not limiting. Various embodiments are described throughout this document, and embodiments of any type may be included under any section / subsection. Furthermore, embodiments described in any section / subsection may be combined in any way with any other embodiments described in the same section / subsection and / or different sections / subsections.
[0018] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may also be included below. The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.
[0019] The embodiments of this disclosure may involve user data, data acquisition, and / or use. All of these aspects comply with applicable laws, regulations, and relevant provisions. In the embodiments of this disclosure, all data collection, acquisition, processing, manipulation, forwarding, and use are conducted with the user's knowledge and confirmation. Accordingly, in implementing the embodiments of this disclosure, the type, scope of use, and usage scenarios of any data or information that may be involved should be communicated to the user and their authorization obtained in accordance with relevant laws and regulations through appropriate means. The specific methods of notification and / or authorization may vary depending on the actual situation and application scenario, and the scope of this disclosure is not limited in this respect.
[0020] In this specification and the embodiments, any processing of personal information will be carried out only under the premise of legality (such as obtaining the consent of the personal information subject, or being necessary for the performance of a contract), and will only be carried out within the scope stipulated or agreed upon. A user's refusal to process personal information other than that necessary for basic functions will not affect the user's use of basic functions.
[0021] As briefly mentioned above, existing autonomous vehicles are still insufficient in terms of real-time response and judgment capabilities, and cannot compare with experienced human drivers, especially in complex traffic environments. This limits the flexibility and efficiency of autonomous vehicles in handling parking restrictions.
[0022] Embodiments of this disclosure propose a site management scheme. The scheme includes: obtaining a request for a site for a mobility service associated with an autonomous vehicle; determining a set of location units based on a first attribute and a second attribute of a plurality of candidate location units, the first attribute indicating stopping constraints corresponding to the plurality of candidate location units and the second attribute indicating whether selection as a site is permitted; determining at least one location unit from the set of location units based on a third attribute of the set of location units, the third attribute indicating the ease of boarding and alighting for the set of location units; and providing at least one location unit as a candidate site for the mobility service. In this manner, embodiments of this disclosure can improve the quality of the provided mobility service sites.
[0023] In this way, the embodiments of this disclosure can more accurately identify the vehicle's light status information, thereby increasing safety during autonomous driving.
[0024] Example System
[0025] Figure 1 shows a schematic diagram of an example site management system 100 according to an embodiment of the present disclosure. As shown in Figure 1, the site management system 100 may include a server 150, which may, for example, be deployed with an order service module 155 and a point-to-line service module 160.
[0026] In some embodiments, the order service unit 155 can be configured to manage travel service orders associated with the autonomous vehicle 140. For example, the order service unit 155 can receive service requests from a user's terminal device 110 and can allocate a corresponding autonomous vehicle 140 to the user.
[0027] In some embodiments, the dot-line service unit 160 provides basic data support for the order service unit 155. As will be described below, the dot-line service unit 160 may provide, for example, attribute information associated with a location unit (also called a cell) to assist the order service unit 155 in revealing the corresponding travel station to the terminal device 110.
[0028] Terminal device 110 may deploy a first notification module 115 to provide users with notification information related to travel services. For example, the first notification module 115 may present the user with service stations determined by the order service unit 155. Alternatively, the first notification module 115 may also provide reminders about the parking time limits of the autonomous vehicle 140 based on parking restriction information provided by the point-to-line service unit 160.
[0029] In some embodiments, the autonomous vehicle 140 may also integrate, for example, a cockpit PHMI 120 and / or a cockpit DHMI 130. The cockpit PHMI 120 is a human-machine interface for passengers, and the cockpit DHMI 130 is, for example, a human-machine interface for the safety operator of the autonomous vehicle 140.
[0030] In some embodiments, the cockpit PHMI 120 and cockpit DHMI 130 may be equipped with a second prompt module 125 and a third prompt module 135, respectively, to provide corresponding prompt information based on the order status.
[0031] As an example, the second prompt module 125 can provide prompts related to the start of the trip, such as a destination display prompt or a destination time limit prompt. As another example, the third prompt module 135 can provide prompts related to the order start point or to the arrival at the start and end points.
[0032] In some scenarios, server 150 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms. Server 130 may include, for example, computing systems / servers, such as mainframes, edge computing nodes, computing devices in a cloud environment, etc. Server 150 can provide backend services for travel applications in terminal device 110.
[0033] The following will describe the specific process of site management in detail with reference to Figures 2 and 3.
[0034] Example process
[0035] Figure 2 shows a flowchart of an example process 200 for site management according to some embodiments of the present disclosure. Process 200 can be implemented at server 150. Process 200 is described below with reference to Figure 1.
[0036] In some embodiments, server 150 receives requests for sites for mobility services associated with autonomous vehicles.
[0037] In some embodiments, server 150 may receive a request to obtain service sites from terminal device 110. As an example, before presenting the site selection interface, terminal device 110 may send a request to server 150 to obtain service sites and may present the corresponding travel sites in the site selection interface.
[0038] As an example, terminal device 110 may display corresponding service stations in a map component, allowing users to select the corresponding station as a pick-up or drop-off point. As another example, terminal device 110 may also receive user clicks on a station search control and present a set of candidate service stations in the station search control.
[0039] In box 220, server 150 determines a set of location units based on a first attribute and a second attribute of multiple candidate location units. The first attribute indicates the docking constraints corresponding to the multiple candidate location units, and the second attribute indicates whether they are allowed to be selected as stations.
[0040] Unlike the points of interest revealed in ordinary travel applications, service stations for driverless vehicles have higher requirements for dockability.
[0041] In some embodiments, the service stations exposed by server 150 may be determined based on location cells (i.e., cells) in map data. A location cell may represent an area of a predetermined size within a road. As an example, multiple location cells may be obtained by dividing the rightmost road into multiple areas according to geometric intervals and road structure based on map data.
[0042] In some embodiments, a location unit may be associated with a first attribute, also known as a docking attribute. The first attribute may indicate the docking constraints corresponding to the location unit. As an example, the first attribute may indicate the objective dockability of the location unit, such as whether parking is permitted in the area, or the permitted parking duration, etc.
[0043] In some embodiments, parking constraints can be divided into three types: no-parking, temporary parking, and long-term parking. No-parking means that this location unit is prohibited from being used as a pick-up or drop-off location, and autonomous vehicles cannot park at this location.
[0044] Temporary stop and long stop indicate the permitted duration of a location unit's parking. For example, temporary stop may indicate that the permitted parking duration is less than a preset duration. Conversely, long stop may indicate that the permitted parking duration is longer than a preset duration, or that there is no parking duration constraint.
[0045] In some embodiments, the parking constraints of a location unit can be automatically generated based on map data. For example, the parking constraints corresponding to each location unit can be determined based on the association between the location unit and no-parking zones, temporary parking zones, and long-term parking zones.
[0046] In some embodiments, a location unit may be associated with a second attribute, also known as an operational attribute. The second attribute may indicate whether the location unit is permitted to be exposed as a pick-up or drop-off location. In some embodiments, some location units, while permitted to be used for parking, may not be suitable as stops for autonomous vehicles.
[0047] In some embodiments, configuration operations by operators for a location unit can be received to determine a second attribute of the location unit. In some embodiments, such a second attribute can also be a time-sharing attribute. For example, the second attribute can indicate whether a location unit is allowed to be selected as a service station during multiple time periods. As an example, operators can instruct a location unit to be exposed as a service station during a first time period and not to be exposed as a service station during a second time period.
[0048] Accordingly, server 150 can filter location units based on the first and second attributes to select a set of location units that are allowed to show through and are not prohibited from stopping.
[0049] In box 230, server 150 determines at least one location unit from a set of location units based on a third attribute of the set of location units, the third attribute indicating the ease of getting on and off the vehicle for the set of location units.
[0050] In some embodiments, the location unit may also be associated with a third attribute, which may indicate the ease of getting on and off the location unit.
[0051] In some embodiments, ease of getting on and off can be categorized into several classes, such as non-traversable, normal, and convenient. Inconvenient may indicate, for example, that the location unit is inaccessible for getting on or off, such as when pedestrians cannot safely and easily reach the sidewalk. Normal may mean that the location unit is accessible for getting on and off, and pedestrians can reach the sidewalk, but it is inconvenient, for example, pedestrians need to cross traffic or there are obstacles. Convenient may indicate that the location unit is recommended for getting on and off, and pedestrians can quickly and safely reach the sidewalk or target building.
[0052] In some embodiments, the ease of getting on and off a location unit can be determined, for example, based on environmental information of the location unit. In some embodiments, server 150 can obtain environmental information associated with the location unit, such environmental information may characterize one or more traffic elements associated with the location unit, such as sidewalks, tunnels, pedestrian overpasses, motor vehicle lanes, etc.
[0053] Furthermore, server 150 can determine the ease of getting on and off the location unit based on environmental information. In some embodiments, the environmental information may be provided to a labeler to obtain labeling information regarding the ease of getting on and off the vehicle.
[0054] In some embodiments, server 150 may also utilize a classification model to automatically generate the ease of boarding and alighting for the location unit. Specifically, server 150 may generate a feature representation of environmental information. As an example, server 150 may encode the environmental information associated with the location unit to characterize the pedestrian access conditions associated with the location unit.
[0055] Furthermore, server 150 can utilize a classification model to process feature representations to determine the ease of boarding and alighting at location units. In some embodiments, the classification model may be trained, for example, based on a set of environmental information samples and corresponding annotation information.
[0056] It should be understood that such a classification model can be implemented based on any appropriate machine learning model, and this disclosure is not intended to limit it.
[0057] In some embodiments, server 150 may, for example, filter one or more location units rated "inconvenient" from a set of candidate location units to determine at least one location unit suitable as a service site. Alternatively, server 150 may also select at least one location unit rated "convenient" from a set of candidate location units to determine its suitability as a service site.
[0058] In box 240, server 150 may provide at least one location unit as a candidate site for travel services.
[0059] As an example, server 150 may send at least one determined location unit to terminal device 110, autonomous vehicle 140, or other suitable device. As an example, terminal device 110 may present the received at least one location unit to a user as a candidate station for a travel service.
[0060] Based on the process described above, through detailed classification and evaluation of multiple dimensions such as objective dockability, subjective dockability, risk level, and convenience, the embodiments of this disclosure can achieve accurate selection and recommendation of parking stations. Therefore, the embodiments of this disclosure make the determination of autonomous vehicle parking stations more scientific, reasonable, and safe, effectively improving the quality and reliability of autonomous vehicle services, while also providing passengers with a more convenient and comfortable travel experience.
[0061] In some embodiments, different stages of the trip may also correspond to different time limit determination strategies for the trip. Figure 3 illustrates a schematic diagram 300 of an example process for determining stop time limits according to some embodiments of the present disclosure.
[0062] As shown in Figure 3, during the bubbling phase 310, the terminal device 110 can display service stations associated with a preset area in the map component. Accordingly, the terminal device 110 can acquire at least one location unit associated with the preset area based on the process described above. Further, the terminal device 110 can determine a target location unit among the at least one location unit based on a first attribute of the at least one location unit, wherein the stop time limit of the target location unit is less than a threshold. Specifically, the terminal device 110 can, for example, select the location unit with the shortest stop time limit among the at least one location unit as the target location to avoid potential parking risks. Accordingly, the terminal device 110 can present the target location unit in the map component.
[0063] Furthermore, during the driving process of the autonomous vehicle 140, the autonomous vehicle 140 can also determine the parking constraint based on the position unit with the shortest parking time limit.
[0064] Furthermore, in the docking phase 330 or docking phase 340, in response to the distance from the autonomous vehicle 140 to the target location unit being less than a threshold, the server 150 can also obtain the pose information of the autonomous vehicle 140.
[0065] Furthermore, server 150 can determine at least one reference position cell that matches the pose information from the list of position cells associated with the target position cell. As an example, server 150 can determine at least one reference position cell that matches the projected area based on the projection of the pose information of autonomous vehicle 140 onto the list of position cells. As an example, the projection can indicate the mapping of the pose information in the lateral direction of autonomous vehicle 140.
[0066] Taking the docking phase 330 as an example, if the pose information of the autonomous vehicle 140 perfectly matches a position unit, then that position unit can be identified as a reference position unit. Taking the docking phase 340 as an example, if the pose information of the autonomous vehicle 140 matches two position units, then both of those position units can be identified as reference position units.
[0067] Furthermore, server 150 can determine the docking time limit of the autonomous vehicle based on a first attribute of at least one reference location unit. Taking docking phase 330 as an example, server 150 can determine the docking time limit of a matched single reference location unit as the docking time limit of the autonomous vehicle.
[0068] Conversely, for the docking phase 340, the pose information of the autonomous vehicle 140 is matched to multiple reference position units. The server 150 can then determine the docking time limit of the autonomous vehicle based on the multiple docking constraints corresponding to the multiple reference position units, whereby the docking time limit corresponds to the minimum time limit indicated by the multiple docking constraints.
[0069] For example, during the docking phase, if the two matched location units have a parking time limit of 3 minutes and a parking time limit of 5 minutes respectively, the server 150 can determine that the autonomous vehicle 140's parking time limit at the current location is 3 minutes, in order to reduce the parking risk of the autonomous vehicle.
[0070] Furthermore, the server 140 can send a stop time limit to the autonomous vehicle 140 and / or the terminal device 110, for example, to remind passengers to get off the vehicle as soon as possible within the stop time limit, or to control the autonomous vehicle 140 to leave within the stop time limit.
[0071] Example devices and equipment
[0072] Figure 4 shows a schematic structural block diagram of a device 400 for identifying vehicle turn signals according to certain embodiments of the present disclosure. The device 400 may be implemented as or included in server 150. The various modules / components in the device 400 may be implemented by hardware, software, firmware, or any combination thereof.
[0073] As shown in the figure, the device 400 includes a request acquisition module 410 configured to acquire a request for a station for a travel service associated with an autonomous vehicle; a first determination module 420 configured to determine a set of location units based on a first attribute and a second attribute of a plurality of candidate location units, wherein the first attribute indicates the stopping constraints corresponding to the plurality of candidate location units and the second attribute indicates whether it is allowed to be selected as a station; a second determination module 430 configured to determine at least one location unit from the set of location units based on a third attribute of the set of location units, wherein the third attribute indicates the ease of getting on and off the set of location units; and a station provision module 440 configured to provide at least one location unit as a candidate station for the travel service.
[0074] In some embodiments, the docking constraint is associated with the duration for which the location unit is allowed to dock.
[0075] In some embodiments, the second attribute indicates whether a location unit is allowed to be selected as a site within a plurality of time periods, and the second attribute is determined based on configuration operations performed on the location unit.
[0076] In some embodiments, the third attribute is determined based on the following process: determining environmental information associated with the location unit; and based on the environmental information, determining the ease of getting on and off the location unit.
[0077] In some embodiments, determining the ease of getting on and off a location unit based on environmental information includes: generating a feature representation of the environmental information; and processing the feature representation using a classification model to determine the ease of getting on and off a location unit.
[0078] In some embodiments, the request is associated with a preset area in a map component displayed by the terminal device, and the terminal device is further configured to: acquire at least one location unit associated with the preset area; determine a target location unit in the at least one location unit based on a first attribute of the at least one location unit, wherein the docking time limit of the target location unit is less than a threshold; and present the target location unit in the map component.
[0079] In some embodiments, the apparatus 400 further includes a sending module configured to: acquire pose information of the autonomous vehicle in response to the distance from the autonomous vehicle to the target location unit being less than a threshold; determine at least one reference location unit that matches the pose information from a list of location units associated with the target location unit; determine a parking time limit for the autonomous vehicle based on a first attribute of the at least one reference location unit; and send the parking time limit to the autonomous vehicle.
[0080] In some embodiments, determining the parking time limit of an autonomous vehicle based on a first attribute of at least one reference position unit includes: in response to pose information matching multiple reference position units, determining the parking time limit of the autonomous vehicle based on multiple parking constraints corresponding to the multiple reference position units, wherein the parking time limit corresponds to the minimum time limit indicated by the multiple parking constraints.
[0081] Figure 5 shows a block diagram illustrating a computing device 500 in which one or more embodiments of the present disclosure may be implemented. It should be understood that the computing device 500 shown in Figure 5 is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein. The computing device 500 shown in Figure 5 can be used to implement the server 150 of Figure 1.
[0082] As shown in Figure 5, the computing device 500 is in the form of a general-purpose computing device. Components of the computing device 500 may include, but are not limited to, one or more processors or processing units 510, memory 520, storage devices 530, one or more communication units 540, one or more input devices 550, and one or more output devices 560. The processing unit 510 may be a physical or virtual processor and is capable of performing various processes according to programs stored in memory 520. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capability of the computing device 500.
[0083] Computing device 500 typically includes multiple computer storage media. Such media can be any accessible media that is accessible to computing device 500, including but not limited to volatile and non-volatile media, removable and non-removable media. Memory 520 can be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. Storage device 530 can be removable or non-removable media and can include machine-readable media, such as flash drives, disks, or any other media that can be used to store information and / or data (e.g., training data for training) and can be accessed within computing device 500.
[0084] The computing device 500 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not shown in FIG. 5, disk drives for reading from or writing to removable, non-volatile disks (e.g., "floppy disks") and optical disk drives for reading from or writing to removable, non-volatile optical disks may be provided. In these cases, each drive may be connected to a bus (not shown) via one or more data media interfaces. The memory 520 may include a computer program product 525 having one or more program modules configured to perform various methods or actions of various embodiments of the present disclosure.
[0085] The communication unit 440 enables communication with other computing devices via a communication medium. Additionally, the components of the computing device 400 can function as a single computing cluster or multiple computing machines capable of communicating via communication connections. Therefore, the computing device 400 can operate in a networked environment using logical connections to one or more other servers, networked personal computers (PCs), or another network node.
[0086] Input device 450 can be one or more input devices, such as a mouse, keyboard, trackball, etc. Output device 460 can be one or more output devices, such as a monitor, speaker, printer, etc. Computing device 400 can also communicate as needed with one or more external devices (not shown) via communication unit 440. These external devices, such as storage devices, display devices, etc., can communicate with one or more devices that enable user interaction with computing device 400, or with any device (e.g., network card, modem, etc.) that enables computing device 400 to communicate with one or more other computing devices. Such communication can be performed via input / output (I / O) interfaces (not shown).
[0087] According to an exemplary implementation of this disclosure, a computer-readable storage medium is provided that stores computer-executable instructions thereon, wherein the computer-executable instructions are executed by a processor to implement the methods described above. According to an exemplary implementation of this disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, which are executed by a processor to implement the methods described above.
[0088] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, devices, and computer program products implemented according to this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.
[0089] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.
[0090] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions that execute on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.
[0091] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
[0092] Various implementations of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed implementations. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described implementations. The terminology used herein is chosen to best explain the principles, practical applications, or improvements to technology in the market, or to enable others skilled in the art to understand the various implementations disclosed herein.
Claims
1. A method for site management, comprising: A request to obtain a site for a mobility service associated with an autonomous vehicle; Based on a first attribute and a second attribute of multiple candidate location units, a set of location units is determined, wherein the first attribute indicates the docking constraints corresponding to the multiple candidate location units, and the second attribute indicates whether they are allowed to be selected as stations. Based on a third attribute of the set of location units, at least one location unit is determined from the set of location units, the third attribute indicating the ease of getting on and off the vehicle for the set of location units; as well as The at least one location unit is provided as a candidate site for the travel service.
2. The method of claim 1, wherein the docking constraint is associated with the duration for which the location unit is allowed to dock.
3. The method of claim 1, wherein the second attribute indicates whether a location unit is allowed to be selected as a site within a plurality of time periods, and the second attribute is determined based on configuration operations performed on the location unit.
4. The method of claim 1, wherein the third attribute is determined based on the following process: Determine the environmental information associated with the location unit; and Based on the environmental information, the ease of getting on and off the vehicle at the location unit is determined.
5. The method according to claim 4, wherein determining the ease of getting on and off the location unit based on the environmental information includes: Generate a feature representation of the environmental information; as well as The feature representation is processed using a classification model to determine the ease of getting on and off the vehicle at the location unit.
6. The method of claim 1, wherein the request is associated with a preset area in a map component displayed by the terminal device, and the terminal device is further configured to: Obtain the at least one location unit associated with the preset region; Based on the first attribute of the at least one location unit, a target location unit among the at least one location unit is determined, wherein the docking time limit of the target location unit is less than a threshold; and The target location unit is presented in the map component.
7. The method according to claim 6, further comprising: In response to the distance from the autonomous vehicle to the target location unit being less than a threshold, the pose information of the autonomous vehicle is acquired; Determine at least one reference position unit that matches the pose information from the list of position units associated with the target position unit; as well as Based on the first attribute of the at least one reference position unit, the parking time limit of the autonomous vehicle is determined; as well as Send the parking time limit to the autonomous vehicle.
8. The method of claim 7, wherein determining the parking time limit of the autonomous vehicle based on the first attribute of the at least one reference position unit comprises: In response to the pose information matching multiple reference position units, the parking time limit of the autonomous vehicle is determined based on multiple parking constraints corresponding to the multiple reference position units, and the parking time limit corresponds to the minimum time limit indicated by the multiple parking constraints.
9. A method for site management, comprising: The request acquisition module is configured to acquire requests for sites used for travel services associated with autonomous vehicles; The first determining module is configured to determine a set of location units based on a first attribute and a second attribute of multiple candidate location units, wherein the first attribute indicates the docking constraints corresponding to the multiple candidate location units, and the second attribute indicates whether they are allowed to be selected as stations. The second determining module is configured to determine at least one location unit from the set of location units based on a third attribute of the set of location units, the third attribute indicating the ease of getting on and off the vehicle of the set of location units. as well as A site providing module is configured to provide the at least one location unit as a candidate site for the travel service.
10. An electronic device, comprising: At least one processing unit; as well as At least one memory is coupled to at least one processing unit and stores instructions for execution by the at least one processing unit, which, when executed by the at least one processing unit, cause the electronic device to perform the method according to any one of claims 1 to 8.
11. A computer-readable storage medium having a computer program stored thereon, the computer program being executable by a processor to implement the method according to any one of claims 1 to 8.
12. A computer program product comprising computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the method according to any one of claims 1 to 8.