Method for processing dynamic event of intelligent connected vehicle, vehicle and medium

Abstract

This application provides a method for processing dynamic events in intelligent connected vehicles, a vehicle, and a medium. The method includes: a cloud server responding to a dynamic event reception request sent by a vehicle, retrieving at least one target event associated with the vehicle from a dynamic event information database; the dynamic event information database storing blacklists and whitelists of events based on map data; and sending the at least one target event to the vehicle, so that the vehicle formulates a control strategy based on the at least one target event. This method aims to improve the vehicle's response speed to sudden dynamic events, thereby improving overall traffic safety and smoothness.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method for processing dynamic events of intelligent connected vehicles, a vehicle, and a medium. Background Technology

[0002] With the rapid development of intelligent connected vehicles, urban transportation systems face the challenge of frequent complex and dynamic events, such as sudden traffic accidents, temporary road construction, abnormal traffic light conditions, and special vehicle passage needs (such as priority passage for ambulances). These events require real-time perception, rapid response, and precise targeting of relevant vehicles to ensure traffic safety and efficiency.

[0003] Existing traffic management systems typically focus on traffic light control, collecting macroscopic traffic flow data through roadside equipment and uploading it to the cloud for signal timing optimization.

[0004] However, in this mode where control commands only act on traffic lights rather than directly reach vehicles, vehicles cannot perceive potential risks in advance, and the long decision-making chain makes it difficult to cope with sudden dynamic events, which has significant limitations. Therefore, there is an urgent need for a vehicle-centric dynamic event handling method to build a safer and more efficient intelligent transportation ecosystem. Summary of the Invention

[0005] This application provides a method for handling dynamic events in intelligent connected vehicles, as well as a vehicle and a medium, to improve the vehicle's response speed to sudden dynamic events, thereby enhancing overall traffic safety and smoothness.

[0006] In a first aspect, embodiments of this application provide a method for processing dynamic events of intelligent connected vehicles, applied to a cloud server, including:

[0007] In response to a dynamic event receiving request sent by a vehicle, at least one target event associated with the vehicle is retrieved from a dynamic event information database; the dynamic event information database stores blacklist and whitelist events of map data;

[0008] The at least one target event is sent to the vehicle so that the vehicle can formulate a control strategy based on the at least one target event.

[0009] In one possible implementation, the dynamic event receiving request includes the vehicle's location data; the step of acquiring at least one target event associated with the vehicle in response to the dynamic event receiving request sent by the vehicle includes:

[0010] Based on the location data in the dynamic event reception request sent by the vehicle, at least one target event matching the location data is queried from the dynamic event information database.

[0011] In one possible implementation, the location data includes the vehicle's current latitude and longitude coordinates; the step of querying at least one target event matching the location data from a pre-stored dynamic event information database based on the location data in the dynamic event reception request sent by the vehicle includes:

[0012] Convert the latitude and longitude coordinates into Tile 15 grid identifiers;

[0013] The nine-square grid neighbor area corresponding to the grid identifier is determined as the first target retrieval area;

[0014] In the dynamic event information database, events whose occurrence location is within the first target retrieval area are queried, and the queried events are identified as target events.

[0015] In one possible implementation, the location data further includes the vehicle's navigation path Link list, which includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's currently planned path.

[0016] The step of querying at least one target event matching the location data from a pre-stored dynamic event information database based on the location data in the dynamic event reception request sent by the vehicle further includes:

[0017] The road segment area corresponding to the navigation path Link list is determined as the second target retrieval area;

[0018] In the dynamic event information database, events whose occurrence location is within the second target retrieval area are queried, and the queried events are identified as target events.

[0019] In one possible implementation, the dynamic event receiving request further includes the vehicle's first map version; determining the road segment area corresponding to the navigation path Link list as the second target retrieval area includes:

[0020] Obtain the second map version from the cloud server;

[0021] If the first map version is the same as the second map version, then the road segment area corresponding to the navigation path Link list is determined as the second target retrieval area.

[0022] In one possible implementation, the dynamic event receiving request further includes the vehicle identifier of the vehicle; sending the at least one target event to the vehicle includes:

[0023] Based on the dynamic event receiving request, obtain the vehicle identifier of the vehicle;

[0024] Send the at least one target event to the vehicle corresponding to the vehicle identifier.

[0025] In one possible implementation, sending the at least one target event to the vehicle corresponding to the vehicle identifier includes:

[0026] The at least one target event is sorted according to the importance of the event indicated by the event type of each target event to obtain the sending priority of each target event;

[0027] In descending order of priority, the at least one target event is sent sequentially to the vehicle corresponding to the vehicle identifier.

[0028] In one possible implementation, the method further includes:

[0029] The system monitors the data changes of each event in the dynamic event information database in real time, and when a data change event is detected in the dynamic event information database, it retrieves at least one target vehicle associated with the change event from the vehicle list.

[0030] The updated change event is sent to the at least one target vehicle so that the at least one target vehicle adjusts its control strategy according to the updated change event;

[0031] The vehicle list includes vehicle identifiers of vehicles that have sent dynamic event reception requests to the cloud server within a preset time period, as well as the latest location data corresponding to each vehicle identifier.

[0032] In one possible implementation, the method further includes:

[0033] In response to a dynamic event reception request sent by a vehicle, the vehicle list is updated based on the vehicle identifier and location data in the dynamic event reception request.

[0034] In one possible implementation, retrieving at least one target vehicle associated with the change event from the vehicle list includes:

[0035] Obtain the location where the change event occurred;

[0036] Search the vehicle list to obtain at least one target vehicle whose location data is associated with the location where the event occurred.

[0037] In one possible implementation, sending the updated change event to the at least one target vehicle includes:

[0038] Obtain the distance between each target vehicle and the location where the change event occurred;

[0039] The updated change events are sent to the at least one target vehicle in order of increasing distance.

[0040] In one possible implementation, the dynamic event information database also includes high-speed dynamic events reported by users.

[0041] Secondly, embodiments of this application provide a method for processing dynamic events of intelligent connected vehicles, applied to the vehicle side, including:

[0042] Send a dynamic event reception request to the cloud server;

[0043] The system retrieves at least one target event associated with a vehicle, obtained from a dynamic event information database and returned by the cloud server; the dynamic event information database stores blacklist and whitelist events based on map data.

[0044] Based on the at least one target event, a control strategy for the vehicle is formulated.

[0045] In one possible implementation, the dynamic event receiving request includes vehicle location data; the location data includes the vehicle's current latitude and longitude coordinates;

[0046] The at least one target event includes events in the dynamic event information database whose occurrence location is within the first target retrieval query area; the first target retrieval query area is the nine-square grid neighbor area corresponding to the grid identifier of the Tile 15 grid obtained by converting the latitude and longitude coordinates.

[0047] In one possible implementation, the dynamic event receiving request further includes the vehicle's navigation path Link list; the navigation path Link list includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's currently planned path;

[0048] The target events also include events in the dynamic event information database whose location is within the second target retrieval query area; the second target retrieval query area is the road segment area corresponding to the navigation path Link list.

[0049] In one possible implementation, the method further includes:

[0050] Receive updated change events sent by the cloud server; the change events are events in the dynamic event information database where data has changed;

[0051] The control strategy is adjusted based on the updated change events.

[0052] In one possible implementation, the dynamic event information database also includes high-speed dynamic events reported by users.

[0053] Thirdly, embodiments of this application provide a device for processing dynamic events of intelligent connected vehicles, comprising:

[0054] The first acquisition module is used to, in response to a dynamic event receiving request sent by the vehicle, acquire at least one target event associated with the vehicle from the dynamic event information database; the dynamic event information database stores blacklist and whitelist events of map data;

[0055] A first sending module is configured to send the at least one target event to the vehicle, so that the vehicle can formulate a control strategy based on the at least one target event.

[0056] In one possible implementation, the first acquisition module is specifically used for:

[0057] Based on the location data in the dynamic event reception request sent by the vehicle, at least one target event matching the location data is queried from the dynamic event information database.

[0058] In one possible implementation, the location data includes the vehicle's current latitude and longitude coordinates; the first acquisition module includes:

[0059] A conversion unit is used to convert the latitude and longitude coordinates into grid identifiers for a Tile 15 grid.

[0060] The first determining unit is used to determine the nine-square grid neighbor area corresponding to the grid identifier as the first target retrieval area;

[0061] The first query unit is used to query events in the dynamic event information database whose occurrence location is within the first target retrieval area, and to determine the queried events as target events.

[0062] In one possible implementation, the location data further includes the vehicle's navigation path Link list, which includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's currently planned path.

[0063] The first acquisition module includes:

[0064] The second determining unit is used to determine the road segment area corresponding to the navigation path Link list as the second target retrieval area;

[0065] The second query unit is used to query events in the dynamic event information database whose occurrence location is within the second target retrieval area, and to determine the queried events as target events.

[0066] In one possible implementation, the dynamic event receiving request further includes a first map version of the vehicle; the second query unit is specifically used for:

[0067] Obtain the second map version from the cloud server;

[0068] If the first map version is the same as the second map version, then the road segment area corresponding to the navigation path Link list is determined as the second target retrieval area.

[0069] In one possible implementation, the dynamic event receiving request further includes the vehicle identifier of the vehicle; the first sending module includes:

[0070] The first acquisition unit is used to receive a request based on the dynamic event and acquire the vehicle identifier of the vehicle.

[0071] A sending unit is used to send the at least one target event to the vehicle corresponding to the vehicle identifier.

[0072] In one possible implementation, the transmitting unit is specifically used for:

[0073] The at least one target event is sorted according to the importance of the event indicated by the event type of each target event to obtain the sending priority of each target event;

[0074] In descending order of priority, the at least one target event is sent sequentially to the vehicle corresponding to the vehicle identifier.

[0075] In one possible implementation, the device further includes:

[0076] The second acquisition module is used to monitor the data changes of each event in the dynamic event information database in real time, and when a data change event is detected in the dynamic event information database, it retrieves at least one target vehicle associated with the change event from the vehicle list.

[0077] The second sending module is used to send the updated change event to the at least one target vehicle, so that the at least one target vehicle adjusts its control strategy according to the updated change event;

[0078] The vehicle list includes vehicle identifiers of vehicles that have sent dynamic event reception requests to the cloud server within a preset time period, as well as the latest location data corresponding to each vehicle identifier.

[0079] In one possible implementation, the device further includes:

[0080] The update module is used to update the vehicle list in response to a dynamic event receiving request sent by a vehicle, based on the vehicle identifier and location data in the dynamic event receiving request.

[0081] In one possible implementation, the second acquisition module includes:

[0082] The second acquisition unit is used to acquire the location where the change event occurs;

[0083] The third query unit is used to query the vehicle list for at least one target vehicle whose location data is associated with the location where the event occurred.

[0084] In one possible implementation, the second transmitting module is specifically used for:

[0085] Obtain the distance between each target vehicle and the location where the change event occurred;

[0086] The updated change events are sent to the at least one target vehicle in order of increasing distance.

[0087] In one possible implementation, the dynamic event information database in the first acquisition module also includes high-speed dynamic events reported by the user.

[0088] Fourthly, embodiments of this application provide a processing apparatus for dynamic events of intelligent connected vehicles, comprising:

[0089] The sending module is used to send dynamic event reception requests to the cloud server;

[0090] The first receiving module is used to receive at least one target event associated with a vehicle, obtained from a dynamic event information database, returned by the cloud server; the dynamic event information database stores blacklist and whitelist events of map data.

[0091] A formulation module is used to formulate a control strategy for the vehicle based on the at least one target event.

[0092] In one possible implementation, the dynamic event receiving request in the first receiving module includes vehicle location data; the location data includes the vehicle's current latitude and longitude coordinates.

[0093] The at least one target event includes events in the dynamic event information database whose occurrence location is within the first target retrieval query area; the first target retrieval query area is the nine-square grid neighbor area corresponding to the grid identifier of the Tile 15 grid obtained by converting the latitude and longitude coordinates.

[0094] In one possible implementation, the dynamic event receiving request in the first receiving module further includes the vehicle's navigation path Link list; the navigation path Link list includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's current planned path;

[0095] The target events also include events in the dynamic event information database whose location is within the second target retrieval query area; the second target retrieval query area is the road segment area corresponding to the navigation path Link list.

[0096] In one possible implementation, the device further includes:

[0097] The second receiving module is used to receive updated change events sent by the cloud server; the change events are events in the dynamic event information database where data has changed.

[0098] An adjustment module is used to adjust the control strategy based on the updated change event.

[0099] In one possible implementation, the dynamic event information database in the first receiving module also includes high-speed dynamic events reported by the user.

[0100] Fifthly, embodiments of this application provide a cloud server, including: a memory and a processor;

[0101] The memory stores computer-executed instructions;

[0102] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0103] Fifthly, embodiments of this application provide a controller, including: a memory and a processor;

[0104] The memory stores computer-executed instructions;

[0105] The processor executes computer execution instructions stored in the memory, causing the processor to perform the second aspect and / or various possible implementations of the second aspect as described above.

[0106] Sixthly, embodiments of this application provide a vehicle, including a vehicle body and the controller described in the fifth aspect.

[0107] In a seventh aspect, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0108] Eighthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the second aspect and / or various possible implementations of the second aspect as described above.

[0109] Ninthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0110] In a tenth aspect, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the second aspect and / or various possible implementations of the second aspect as described above.

[0111] The intelligent connected vehicle dynamic event processing method, vehicle, and medium provided in this application embodiment, in response to a dynamic event receiving request sent by the vehicle, query at least one target event associated with the vehicle from a dynamic event information database containing blacklist and whitelist events of map data, and send the at least one target event to the vehicle so that the vehicle can control itself based on the at least one target event. This means that the vehicle can directly obtain target event information associated with itself, and predict potential traffic risks in advance based on this information, thereby improving the vehicle's response speed to sudden dynamic events, and thus achieving the effects of optimizing vehicle driving decision efficiency, reducing the probability of accidents caused by sudden dynamic events, and improving the overall traffic safety and smoothness of the road network. Attached Figure Description

[0112] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0113] Figure 1 A flowchart illustrating a method for processing dynamic events of intelligent connected vehicles provided in Embodiment 1 of this application;

[0114] Figure 2 This is a flowchart illustrating a method for processing dynamic events of intelligent connected vehicles, as provided in Embodiment 3 of this application.

[0115] Figure 3This is a schematic diagram of the architecture of a specific intelligent connected vehicle dynamic event processing system provided in Embodiment 4 of this application;

[0116] Figure 4 This is a schematic diagram of the structure of a device for processing dynamic events of an intelligent connected vehicle provided in Embodiment 5 of this application;

[0117] Figure 5 This is a schematic diagram of the structure of a device for processing dynamic events of an intelligent connected vehicle provided in Embodiment Six of this application;

[0118] Figure 6 A schematic diagram of the structure of a device for processing dynamic events of an intelligent connected vehicle provided in Embodiment 7 of this application;

[0119] Figure 7 A schematic diagram of the structure of a device for processing dynamic events of an intelligent connected vehicle provided in Embodiment 8 of this application;

[0120] Figure 8 This is a schematic diagram of the cloud server structure provided in this application;

[0121] Figure 9 A schematic diagram of the controller provided in this application.

[0122] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0123] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0124] Based on the aforementioned background technology, the inventors discovered during their research that they could break the traditional one-way control mode of traffic lights and shift the decision-making point of traffic management from the "intersection" to the "vehicle". By searching for dynamic events associated with vehicles in the cloud and sending the events directly to the vehicle, the vehicle can directly implement vehicle control based on the events. This improves the vehicle's response speed to sudden dynamic events, thereby enhancing the overall traffic safety and smoothness, and ultimately building a safer and more efficient intelligent transportation ecosystem.

[0125] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0126] Figure 1 This is a flowchart illustrating a method for processing dynamic events of intelligent connected vehicles according to Embodiment 1 of this application. Figure 1 As shown, the method for handling dynamic events of intelligent connected vehicles provided in this embodiment includes:

[0127] S101, Send a dynamic event receiving request to the cloud server.

[0128] In this step, after the vehicle is started, in order to achieve active control of the vehicle based on associated events, a dynamic event reception request will be sent to the cloud server based on the communication link between the vehicle and the cloud.

[0129] It should be noted that the communication link between the vehicle and the cloud can be, for example, a Vehicle to Everything (V2X) or a three-level communication link between the vehicle, roadside unit (RSU), and cloud. This application does not impose specific restrictions on the communication connection method between the vehicle and the cloud. For example, if the communication link between the vehicle and the cloud is a three-level link between the vehicle, roadside unit, and cloud, when the vehicle sends a dynamic event reception request to the cloud, it can first send the request to the roadside edge device, and then the roadside edge device can upload the data to the cloud. Similarly, when the cloud sends relevant data to the vehicle, it can first send the data to the roadside edge device, and then the roadside edge device can send the data to the vehicle.

[0130] S102. In response to a dynamic event receiving request sent by the vehicle, retrieve at least one target event associated with the vehicle from the dynamic event information database.

[0131] In this step, in response to the dynamic event acceptance request sent by the vehicle, the cloud server will query and retrieve at least one target event associated with the vehicle from the pre-stored dynamic event information database in the cloud.

[0132] It should be understood that "vehicle-related" refers to events that will have a direct or indirect impact on the vehicle's current driving behavior.

[0133] The dynamic event information database stores blacklisted and whitelisted events from map data. Specifically, blacklisted and whitelisted events from map data refer to events recorded in high-precision maps that affect the normal passage of vehicles, such as road construction, sudden accidents, and temporary traffic control.

[0134] Optionally, the dynamic event information database also includes user-reported high-speed dynamic events. High-speed dynamic events refer to sudden, temporary traffic-related events that occur on highway sections and affect vehicle safety or efficiency. Examples include road construction, road collapses, traffic accidents, hazardous chemical leaks, intrusions by non-motorized vehicles, pedestrians, or animals, abnormal congestion, vehicle smoke and fire, emergency lane obstruction, road flooding, and the presence of hazardous materials transport vehicles on highway sections.

[0135] It should be understood that although the blacklist and whitelist events in the map data also include dynamic events occurring on highways, the map data may be outdated due to the high time sensitivity of highways. Therefore, the dynamic event information database can also include highway dynamic events reported by users through relevant vehicle software as a supplement to the map data, thereby improving the comprehensiveness of the dynamic event information database and thus improving the accuracy of vehicle control.

[0136] In practical applications, events are stored in the dynamic event information database in the form of an event data model. This event data model is a standardized data model that defines attributes such as event identifier, event location, event effective time window, and event type. The event location can be indicated by latitude and longitude coordinates and / or the Link ID of the road associated with the event; the event window refers to the effective time range of the event.

[0137] S103. Send at least one target event to the vehicle.

[0138] In this step, the cloud server needs to send the event information of each target event obtained from the search to the vehicle corresponding to the dynamic event receiving request through the communication link between the cloud and the vehicle.

[0139] In one possible implementation, the dynamic event receiving request includes the vehicle's vehicle identifier; sending at least one target event to the vehicle includes steps 3.1 to 3.2 below:

[0140] Step 3.1: Obtain the vehicle identifier based on the dynamic event receiving request.

[0141] Among them, vehicle identification refers to the identifier that can uniquely identify a vehicle, such as the vehicle identification number (VIN).

[0142] In this step, the vehicle identifier will be extracted from the dynamic event reception request sent by the vehicle.

[0143] Step 3.2: Send at least one target event to the vehicle corresponding to the vehicle identifier.

[0144] In this step, at least one target event will be sent to the vehicle corresponding to the vehicle identifier through the communication link between the vehicle and the cloud to ensure the accurate delivery of event information.

[0145] As a preferred implementation method, in order to further improve the overall traffic safety, step 3.2 can be implemented using the following steps 3.2.1 to 3.2.2:

[0146] Step 3.2.1: Sort the at least one target event according to the importance of the event indicated by the event type of each target event to obtain the sending priority of each target event.

[0147] Specifically, different event types can be pre-sorted by importance. Then, based on the importance of each target event's event type, the target events are sorted to obtain the sending priority for each target event. The higher the importance of an event, the higher its sending priority.

[0148] Step 3.2.2: Send at least one target event to the vehicle corresponding to the vehicle identifier in descending order of sending priority.

[0149] In this step, target events will be sent in descending order of priority to ensure that events of higher importance are sent first.

[0150] It should be understood that steps 3.2.1 and 3.2.2, by sorting the importance of events according to the type of the target event, determining the sending priority, and sending the target events to the vehicle in descending order of priority, ensure that the order of target event pushes is accurately matched with the importance of the events. This effectively avoids the problem of information overload caused by indiscriminate pushes, while also enabling the vehicle to receive high-importance events first, thereby quickly responding to critical scenario needs and further improving the vehicle's ability to respond to emergencies and driving safety.

[0151] The method described in steps 3.1 to 3.2 above, provided by this implementation, achieves precise delivery of target events from the cloud to the vehicle by using vehicle identifiers to send target events, thereby improving the accuracy and transmission efficiency of event sending in vehicle-cloud collaborative scenarios.

[0152] S104. Receive at least one target event associated with the vehicle from the dynamic event information database returned by the cloud server.

[0153] In this step, the vehicle will receive at least one target event associated with the vehicle from the dynamic event information database, which is retrieved by the cloud server through the communication link between the vehicle and the cloud.

[0154] S105. Develop a vehicle control strategy based on at least one target event.

[0155] In this step, the vehicle will implement corresponding active control commands or driving strategies based on the target events associated with the vehicle.

[0156] For example, a vehicle may implement deceleration or acceleration commands and / or replan the navigation route based on the target event.

[0157] The method for processing dynamic events of intelligent connected vehicles provided in this application embodiment involves the vehicle sending a dynamic event reception request to a cloud server. In response to the request, the cloud queries a dynamic event information database containing blacklists and whitelists of map data to identify at least one target event associated with the vehicle and sends the at least one target event to the vehicle. This allows the vehicle to control itself based on the at least one target event. The method enables the vehicle to directly obtain target event information associated with itself and to predict potential traffic risks in advance based on this information. This improves the vehicle's response speed to sudden dynamic events, thereby optimizing the efficiency of vehicle driving decisions, reducing the probability of accidents caused by sudden dynamic events, and improving the overall traffic safety and smoothness of the road network.

[0158] Furthermore, Embodiment 2 of this application provides a method for processing dynamic events of intelligent connected vehicles. Based on the above embodiments, this embodiment provides a specific implementation method for the aforementioned step of "obtaining at least one target event associated with the vehicle from the dynamic event information database". In this embodiment, the dynamic event receiving request sent by the vehicle includes the vehicle's location data. Accordingly, this step can be implemented in the following way:

[0159] Based on the location data in the dynamic event reception request sent by the vehicle, query the dynamic event information database for at least one target event that matches the location data.

[0160] In detail, when a vehicle reports a dynamic event reception request, it will simultaneously provide its own location information to the cloud server so that the cloud server can send target events associated with its location to it.

[0161] Location data refers to the location information involved in driving a vehicle.

[0162] In one possible implementation, the location data reported by the vehicle includes the vehicle's current latitude and longitude coordinates. Accordingly, this step specifically includes steps 2.1.1 to 2.2.3 as follows:

[0163] Step 2.1.1: Convert latitude and longitude coordinates to grid identifiers for Tile 15 map tiles.

[0164] It should be understood that Tile 15 refers to the 15th level tile grid system in the map tile pyramid model in fields such as high-precision maps and navigation maps. That is, the spatial grid formed by cutting the Earth's surface into standard 256×256 pixel square tiles according to the 15th scaling level, and each tile in the grid corresponds to a unique grid identifier.

[0165] In this step, to facilitate accurate searching for target events associated with vehicles, latitude and longitude coordinates can be converted into the grid identifier of the corresponding grid in Tile 15.

[0166] For example, the spherical latitude and longitude coordinates can be converted to Mercator plane projection coordinates through Mercator projection. Then, according to the segmentation rules corresponding to the 15 scaling levels, the tile row and column number to which the Mercator plane projection coordinates belong can be calculated to obtain the grid identifier corresponding to the latitude and longitude coordinates.

[0167] Step 2.1.2: Determine the nine-square grid neighbor area corresponding to the grid identifier as the first target retrieval area.

[0168] The nine-grid neighbor area corresponding to the grid identifier refers to the location area formed by the grid corresponding to the grid identifier as the center, together with the eight adjacent grids of the same level above, below, left, right and four diagonals.

[0169] In this step, the area consisting of the grid corresponding to the grid and the eight adjacent grids surrounding the grid is determined as the first target retrieval area.

[0170] Step 2.1.3: In the dynamic event information database, query the events whose occurrence location is within the first target retrieval area, and determine the queried events as the target events.

[0171] In this step, events in the dynamic event database whose location (such as the latitude and longitude coordinates of the event) falls within the first target retrieval area will be queried, and the queried events will be identified as target events.

[0172] Correspondingly, the vehicle acquires at least one target event, which includes events in the dynamic event information database whose location is within the first target retrieval query area; the first target retrieval query area is the nine-grid neighbor area corresponding to the grid identifier of the Tile 15 grid obtained by converting latitude and longitude coordinates.

[0173] The method provided in this implementation first accurately converts latitude and longitude coordinates into Tile 15 grid identifiers, then delineates a nine-square grid neighborhood area as the first target retrieval area using this grid as the core, and finally performs targeted queries on events within this area in the dynamic event information database and filters target events. This achieves a dual improvement in the efficiency and accuracy of dynamic event retrieval. Specifically, in terms of efficiency, relying on the standardized spatial division of the Tile 15 grid, the overall retrieval scope is precisely narrowed to a limited nine-square grid area, significantly reducing the traversal and query volume of invalid data, avoiding the resource consumption of overall retrieval, and significantly improving the retrieval response speed of dynamic events. In terms of accuracy, the Tile 15 grid provides a standardized spatial positioning benchmark for latitude and longitude coordinates, effectively avoiding the omission of surrounding related dynamic events and the redundant distribution of events from irrelevant areas, greatly improving the accuracy of target event filtering.

[0174] In another implementation, the location data reported by the vehicle may also include a list of navigation routes (Links). Accordingly, this step may also include steps 2.2.1 to 2.2.2:

[0175] Step 2.2.1: Determine the road segment area corresponding to the navigation path (Map Positioning Point, MPP) Link list as the second target retrieval area.

[0176] The navigation path Link list includes road segment identifiers for at least one road segment within a preset distance ahead in the vehicle's currently planned route. It should be noted that the preset distance can be determined based on the actual application of the solution; for example, the preset distance could be 150m, 200m, 230m, 300m, etc. This application does not impose a specific limitation on this.

[0177] In this step, the road segment area corresponding to each road segment identifier in the navigation path Link list needs to be identified as the second target retrieval area.

[0178] For example, the entire road segment area within 200 meters ahead of the vehicle's current planned path can be determined as the second target retrieval area.

[0179] Optionally, the dynamic event receiving request may also include the vehicle's first map version. In this case, step 2.2.2 can be implemented as follows: obtain the second map version from the cloud server; if the first map version is the same as the second map version, then determine the road segment area corresponding to the navigation path Link list as the second target retrieval area.

[0180] In detail, when a vehicle sends a dynamic event receiving request, it can also simultaneously report the first map version on the vehicle's end. The cloud server compares the local second map version obtained from the query with the first map version to see if they are consistent. Only when the versions are consistent (meaning that the Link ID (i.e., road segment identifier) ​​in the corresponding map on the vehicle's end and the cloud is consistent) will the event query operation based on the Link list of the navigation path be performed.

[0181] It should be understood that this optional solution effectively ensures the accuracy of dynamic event delivery by only performing event query operations based on the navigation path Link list when the map versions in the cloud and on the vehicle are consistent.

[0182] Step 2.2.2: In the dynamic event information database, query the events whose occurrence location is within the second target retrieval area, and determine the queried events as the target events.

[0183] In this step, events that occur within the first target retrieval area will be searched in the dynamic event database, and the retrieved events will be identified as target events.

[0184] In practical applications, events whose Link ID is any road identifier in the navigation path Link list can be identified as target events in the dynamic event library.

[0185] Correspondingly, the at least one target event acquired by the vehicle may also include events in the dynamic event information database whose location is within the second target retrieval query area; the second target retrieval query area is the road segment area corresponding to the navigation path Link list.

[0186] The method provided in this implementation involves the vehicle reporting a list of navigation path links to the cloud. The cloud then designates the corresponding road segments in the navigation path link list as the second target retrieval area and performs a targeted retrieval of events within this area from a dynamic event information database to determine the target event. This allows for precise binding between the dynamic event retrieval scope and the vehicle's future planned driving route, extending event querying from real-time retrieval of the vehicle's current location to predictive retrieval of future routes. This enables predictive event push based on the vehicle's future navigation route, providing more sufficient decision-making basis for subsequent vehicle-side decision control.

[0187] In addition, it should be understood that in practical applications, location data may include the vehicle's current latitude and longitude coordinates and / or a list of navigation paths (Links). When the vehicle's location data changes (such as when the vehicle moves and / or the navigation path changes), the vehicle will resend a dynamic event receiving request carrying the new location data to the cloud server, so that the cloud server can send the associated target events to the vehicle based on the latest location data, ensuring the accuracy of event delivery.

[0188] The method for processing dynamic events of intelligent connected vehicles provided in this application embodiment uses location data from the dynamic event reception request sent by the vehicle to perform targeted matching and querying of at least one target event in the dynamic event information database. This allows the event query to accurately anchor the spatial range associated with the vehicle, achieve precise spatial positioning of the vehicle's current location based on latitude and longitude coordinates, and simultaneously lock the road segment area that the vehicle plans to drive in the future by combining the navigation path Link list. This ensures that the query range is highly consistent with the actual spatial needs of the vehicle's driving, achieving lane-level and path-based precise services. This significantly improves the accuracy and retrieval efficiency of dynamic event queries, ensuring that relevant information can reach the vehicle within seconds.

[0189] Furthermore, Figure 2 This is a flowchart illustrating a method for processing dynamic events of intelligent connected vehicles according to Embodiment 3 of this application. Based on the above embodiments, the method provided in this embodiment offers a proactive cloud-based distribution mechanism to further improve the real-time performance and reliability of target event distribution. Specifically, it also includes:

[0190] S201. Monitor the data changes of each event in the dynamic event information database in real time, and when a data change event is detected in the dynamic event information database, retrieve at least one target vehicle associated with the change event from the vehicle list.

[0191] Specifically, a change event refers to an event in the dynamic event information database where the event information changes. This event information includes, for example, the event's effective time window and the event type.

[0192] In addition, the vehicle list includes vehicle identifiers of vehicles that have sent dynamic event reception requests to the cloud server within a preset time period, as well as the latest location data corresponding to each vehicle identifier. It should be noted that the preset time period can be determined according to the specific application of this solution, for example, 12h, 24h, etc., and this application does not impose specific restrictions on it.

[0193] In this solution, the cloud server monitors the data changes of each event in the dynamic event information database in real time, and sends the monitored changes to at least one target vehicle associated with the change time through the communication link between the cloud and the vehicle.

[0194] In this step, the cloud server will identify at least one target vehicle associated with the change event it has been monitoring. Specifically, vehicles whose data changes will affect the original driving plan will be identified as target vehicles.

[0195] In one possible implementation, this step can be achieved using steps 1.1 to 1.2 as follows:

[0196] Step 1.1: Obtain the location where the change event occurred.

[0197] In this step, for each change event, the cloud server will retrieve the location of the event occurrence from the event information corresponding to the change event in the dynamic event information database.

[0198] Step 1.2: Query the vehicle list to obtain at least one target vehicle whose location data is associated with the location where the event occurred.

[0199] In this step, it is necessary to query the vehicle list to obtain the latest location data of the vehicle associated with the location where the event occurred, and identify that vehicle as the target vehicle.

[0200] For example, if the location data includes the vehicle's latest latitude and longitude coordinates, the first query area corresponding to the latitude and longitude coordinates, which includes the vehicle with the latitude and longitude coordinates corresponding to the change event, can be identified as the target vehicle; and / or, if the location data includes the vehicle's latest navigation path Link list, the second query area corresponding to the navigation path Link list, which includes the vehicle with the Link ID of the road segment associated with the change event, can be identified as the target vehicle.

[0201] The method provided in this implementation achieves a precise association and matching between the event location and the vehicle location by obtaining the location of the change event and performing a targeted query in the vehicle list to find at least one target vehicle whose location data is associated with the location of the event. This results in the technical effect of quickly and accurately locating the target vehicle affected by the change event.

[0202] Accordingly, to ensure the real-time nature of the vehicle list, in one possible implementation, the method provided in this embodiment further includes:

[0203] The cloud server responds to the dynamic event reception request sent by the vehicle and updates the vehicle list based on the vehicle identifier and location data in the dynamic event reception request.

[0204] In detail, each time the cloud server receives a dynamic event reception request, it needs to update the vehicle list based on the vehicle identifier and location data in the dynamic event reception request. For example, each time the cloud server receives a dynamic event reception request, it will first check whether the vehicle list includes the vehicle identifier in the dynamic event reception request; if it does not include it, it will add the vehicle identifier and its corresponding location data to the vehicle list; if it does include it, it will update the location data corresponding to the vehicle identifier in the vehicle list based on the location data in the dynamic event reception request.

[0205] The method provided in this implementation updates the vehicle list based on the vehicle identifier and location data in the dynamic event reception request sent by the vehicle. This allows the vehicle list to synchronize the vehicle's identity and latest location data in real time with the vehicle's active request, realizing dynamic and real-time updates of the vehicle list data. This effectively avoids problems such as lagging location information and invalid identifier data in the vehicle list, and achieves the technical effect of ensuring the timeliness and accuracy of the vehicle list data.

[0206] S202, Send the updated change event to at least one target vehicle.

[0207] In this step, for each target vehicle found, the cloud server needs to send the updated information corresponding to the change event to the vehicle through the communication link between the cloud and the vehicle.

[0208] In one possible implementation, this step can be achieved using steps 4.1 to 4.2 as follows:

[0209] Step 4.1: Obtain the distance between each target vehicle and the location where the change event occurred.

[0210] In this step, the cloud server will calculate the distance between each target vehicle and the location where the event corresponding to the change event occurred.

[0211] For example, the distance between the change event and the vehicle can be calculated by using the latitude and longitude coordinates of the change event as the calculation reference. Alternatively, for each target vehicle, the distance between the change event and the vehicle can be calculated by using the latitude and longitude coordinates of the road segment closest to the target vehicle among at least one road segment associated with the change event as the reference.

[0212] Step 4.2: Send the updated change events to the at least one target vehicle in order of increasing distance.

[0213] In this step, the cloud server will send the updated information corresponding to the change event to the corresponding target vehicle in order of distance from nearest to farthest.

[0214] The method provided in this implementation obtains the distance between each target vehicle and the location where the change event occurs, and sends updated change events to the target vehicles in order of distance from near to far. This enables hierarchical and targeted precise distribution of change event information, allowing nearby vehicles with a higher spatial correlation to the event location and more direct impact to receive event information first, giving them more time to adjust their driving decisions. At the same time, it avoids the disorderly information distribution and vehicle-side information redundancy caused by indiscriminate push, thereby improving the technical effect of improving the targeting, timeliness and rationality of change event push, and ensuring that target vehicles at different distances can receive information at an appropriate pace according to their spatial distance from the event.

[0215] S203, Receive updated change events sent by the cloud server.

[0216] In this step, each target vehicle will receive an update from the cloud server corresponding to the change event.

[0217] S204. Adjust the control strategy based on the updated change events.

[0218] In this step, each target vehicle will make timely and targeted adjustments to its control strategy based on the newly acquired dynamic event information.

[0219] The method for processing dynamic events of intelligent connected vehicles provided in this application embodiment monitors changes in event data in the dynamic event information database in real time through a cloud server. Upon detecting a change, it accurately matches the associated target vehicle from a vehicle list containing vehicle identifiers and the latest location data, and proactively sends the updated change event to the target vehicle. This method breaks through the one-way interaction mode triggered solely by vehicle-side reporting in the aforementioned embodiments, constructing a real-time data collaborative computing model triggered by both vehicle-side state changes and cloud-based business data updates, achieving a rapid closed loop for information interaction between the vehicle and the cloud. Simultaneously, the cloud adopts a proactive push mode, eliminating the need for all vehicles to continuously report complete information, thus optimizing... The vehicle-side reporting strategy significantly reduces vehicle-to-cloud communication overhead, and the cloud centrally performs event matching and target vehicle selection calculations, effectively improving computing efficiency and significantly reducing the overall latency from event occurrence to vehicle-side perception. Furthermore, it realizes a dynamic, real-time, two-way intelligent interaction closed loop between the vehicle and the cloud. The vehicle-side status drives the cloud to provide targeted services, and changes in cloud data can reach the vehicle in real time and guide the vehicle to adjust its control strategy. This builds a complete vehicle-to-cloud intelligent agent collaborative network and establishes a high-concurrency, low-latency event delivery channel to ensure that dynamic event information influences vehicle driving decisions in a timely and accurate manner, ultimately achieving the technical effect of comprehensively improving overall traffic safety and operational efficiency.

[0220] Figure 3 This is a schematic diagram of the architecture of a specific intelligent connected vehicle dynamic event processing system provided in Embodiment 4 of this application, as shown below. Figure 3 As shown, the intelligent connected vehicle dynamic event processing system is deployed in a cloud server, including a data access and fusion layer, a real-time computing and decision-making layer, a data storage and management layer, and a two-way communication and distribution layer.

[0221] In detail, the data access and fusion layer is used to receive multi-source data sent from external sources, including a data bus and access gateway module, a data cleaning and standardization module, and a spatiotemporal alignment module. Specifically, this data access and fusion layer is used to uniformly access real-time data from roadside edge devices, vehicles, and traffic management platforms through the data bus and access gateway module, and to convert data of different formats into a unified model within the system through the data cleaning and standardization module. Finally, the spatiotemporal alignment module performs time synchronization and spatial gridding.

[0222] For example, the cloud server receives raw dynamic event data from the traffic management platform through the data access and fusion layer, and converts the raw dynamic event data into an event data model through the data cleaning and standardization module, storing it in the dynamic event information database. At the same time, the cloud server also receives dynamic event reception requests sent by vehicles and / or roadside edge facilities through the data access and fusion layer, and parses the dynamic event reception requests through the data cleaning and standardization module, storing the location data of different vehicles in the vehicle list. In addition, the cloud server will also use the spatiotemporal alignment module to synchronize the time information in the dynamic event information database with the time information of the vehicles sending dynamic event reception requests, and perform spatial gridding processing on the vehicle location data (spatial gridding).

[0223] Optionally, the cloud server can also receive raw dynamic event data collected from roadside edge facilities through the data access and fusion layer, and convert the raw dynamic event data into an event data model and store it in the dynamic event information database.

[0224] It should be understood that the data access and fusion layer acts as the "sensory nerves" of the processing system, used to translate and initially organize multi-source heterogeneous data into a "unified language," providing a solid foundation for subsequent efficient queries.

[0225] The data storage and management layer stores dynamic event information and vehicle lists to provide relevant data to the real-time computing and decision-making layers. It should be understood that the data storage and management layer is the "memory center" of the processing system, crucial for ensuring the freshness of the data required for computation and the speed of retrieval.

[0226] The real-time computing and decision-making layer is used to respond to dynamic event reception requests received by the data access and fusion layer, query the data storage and management layer to retrieve the target event corresponding to the request, and send the target event to the vehicle through bidirectional communication and the downlink layer. At the same time, the real-time computing and decision-making layer is also used to respond to change events monitored by the state change listener, and send the change events to the vehicle through bidirectional communication and the downlink layer. In addition, the real-time computing and decision-making layer is also used to update the vehicle list in the data storage and management layer based on the dynamic event reception requests received by the data access and fusion layer.

[0227] It should be understood that the real-time computing and decision-making layer, as the "brain" of the processing system, has a vehicle-event matching engine at its core, which can realize two-way, proactive collaboration from "vehicles looking for information" to "information looking for vehicles".

[0228] The bidirectional communication and downlink layer is used for bidirectional data transmission, including transmitting data from vehicles and roadside edge facilities to the cloud and pushing matching data from the cloud to vehicles and roadside edge facilities.

[0229] It should be understood that bidirectional communication and the lower-level layer, as a "circular system" of the processing system, ensure the bidirectional flow of information between vehicles, roads, and the cloud.

[0230] Optionally, this bidirectional communication with the lower-level layer can be based on the MQTT protocol. Specifically, the high efficiency and low latency of the MQTT protocol ensure efficient and reliable bidirectional flow of information between vehicles, infrastructure, and the cloud.

[0231] The intelligent connected vehicle dynamic event processing system provided in this application adopts a layered architecture design consisting of a data access and fusion layer, a real-time computing and decision-making layer, a data storage and management layer, and a two-way communication and distribution layer. This architecture enables unified access, fusion processing, efficient storage, and intelligent decision-making for multi-source dynamic event data. Simultaneously, it establishes a high-speed vehicle-cloud interaction channel based on the two-way communication and distribution layer, significantly improving the cloud's processing efficiency, decision-making accuracy, and distribution timeliness for intelligent connected vehicle dynamic events. This provides integrated and highly reliable cloud technology support for vehicle-cloud collaborative dynamic event response, effectively ensuring the efficient operation of the entire closed-loop process for intelligent connected vehicle dynamic event processing.

[0232] Figure 4 This is a schematic diagram of the structure of a device for processing dynamic events of an intelligent connected vehicle provided in Embodiment 5 of this application, as shown below. Figure 4 As shown, the intelligent connected vehicle dynamic event processing device 30 provided in this embodiment includes:

[0233] The first acquisition module 301 is used to, in response to a dynamic event receiving request sent by a vehicle, acquire at least one target event associated with the vehicle from the dynamic event information database; the dynamic event information database stores blacklist and whitelist events of map data;

[0234] The first sending module 302 is used to send at least one target event to the vehicle so that the vehicle can formulate a control strategy based on the at least one target event.

[0235] The intelligent connected vehicle dynamic event processing device 30 provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0236] Figure 5 This is a schematic diagram of the structure of a device for processing dynamic events of an intelligent connected vehicle provided in Embodiment Six of this application, as shown below. Figure 5 As shown, based on the above embodiments, the intelligent connected vehicle dynamic event processing device 30 provided in this embodiment further includes:

[0237] The second acquisition module 303 is used to monitor the data changes of each event in the dynamic event information database in real time, and when a data change event is detected in the dynamic event information database, it retrieves at least one target vehicle associated with the change event from the vehicle list.

[0238] The second sending module 304 is used to send the updated change event to at least one target vehicle, so that at least one target vehicle can adjust its control strategy according to the updated change event.

[0239] The vehicle list includes vehicle identifiers of vehicles that have sent dynamic event reception requests to the cloud server within a preset time period, as well as the latest location data corresponding to each vehicle identifier.

[0240] The update module 305 is used to update the vehicle list in response to a dynamic event receiving request sent by a vehicle, based on the vehicle identifier and location data in the dynamic event receiving request.

[0241] In one possible implementation, the first acquisition module 301 is specifically used for:

[0242] Based on the location data in the dynamic event reception request sent by the vehicle, query the dynamic event information database for at least one target event that matches the location data.

[0243] In one possible implementation, the location data includes the vehicle's current latitude and longitude coordinates; the first acquisition module 301 includes:

[0244] Transformation unit, used to convert latitude and longitude coordinates into grid identifiers for a Tile 15 grid;

[0245] The first determining unit is used to determine the nine-square grid neighbor area corresponding to the grid identifier as the first target retrieval area;

[0246] The first query unit is used to query events in the dynamic event information database that occur within the first target retrieval area, and to identify the queried events as target events.

[0247] In one possible implementation, the location data also includes a navigation path Link list for the vehicle, which includes segment identifiers for at least one road segment within a preset distance ahead in the vehicle's currently planned path.

[0248] The first acquisition module 301 includes:

[0249] The second determining unit is used to determine the road segment area corresponding to the navigation path Link list as the second target retrieval area;

[0250] The second query unit is used to query events in the dynamic event information database that occur in the second target retrieval area, and to identify the queried events as target events.

[0251] In one possible implementation, the dynamic event receiving request further includes a first map version for the vehicle; and a second query unit, specifically used for:

[0252] Obtain the second map version from the cloud server;

[0253] If the first map version is the same as the second map version, then the road segment area corresponding to the navigation path Link list will be determined as the second target retrieval area.

[0254] In one possible implementation, the dynamic event receiving request further includes the vehicle's vehicle identifier; the first sending module 302 includes:

[0255] The first acquisition unit is used to receive requests based on dynamic events and acquire the vehicle identifier of the vehicle.

[0256] The sending unit is used to send at least one target event to the vehicle corresponding to the vehicle identifier.

[0257] In one possible implementation, the transmitting unit is specifically used for:

[0258] At least one target event is sorted according to the importance of the event indicated by the event type of each target event to obtain the sending priority of each target event;

[0259] At least one target event is sent to the vehicle corresponding to the vehicle identifier in descending order of sending priority.

[0260] In one possible implementation, the second acquisition module 303 includes:

[0261] The second acquisition unit is used to acquire the location where the change event occurs;

[0262] The third query unit is used to query the vehicle list for at least one target vehicle whose location data is associated with the location where the event occurred.

[0263] In one possible implementation, the second transmitting module 304 is specifically used for:

[0264] Obtain the distance between each target vehicle and the location where the change event occurred;

[0265] The updated change events are sent to at least one target vehicle in order of increasing distance.

[0266] In one possible implementation, the dynamic event information database in the first acquisition module 301 also includes high-speed dynamic events reported by the user.

[0267] The intelligent connected vehicle dynamic event processing device 30 provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0268] Figure 6 This is a schematic diagram of the structure of a device for processing dynamic events of intelligent connected vehicles provided in Embodiment 7 of this application, as shown below. Figure 6 As shown, the intelligent connected vehicle dynamic event processing device 40 provided in this embodiment includes:

[0269] Sending module 401 is used to send dynamic event receiving requests to the cloud server;

[0270] The first receiving module 402 is used to receive at least one target event associated with the vehicle from the dynamic event information database returned by the cloud server; the dynamic event information database stores blacklist and whitelist events of map data;

[0271] The formulation module 403 is used to formulate a control strategy for the vehicle based on at least one target event.

[0272] The intelligent connected vehicle dynamic event processing device 40 provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0273] Figure 7 This is a schematic diagram of the structure of a device for processing dynamic events of intelligent connected vehicles provided in Embodiment 8 of this application, as shown below. Figure 7 As shown, based on the above embodiments, the intelligent connected vehicle dynamic event processing device 40 provided in this embodiment further includes:

[0274] The second receiving module 404 is used to receive updated change events sent by the cloud server; the change event is an event in the dynamic event information database where data has changed.

[0275] Adjustment module 405 is used to adjust the control strategy based on the updated change events.

[0276] In one possible implementation, the dynamic event information database in the first receiving module 402 also includes high-speed dynamic events reported by the user.

[0277] In one possible implementation, the dynamic event receiving request in the first receiving module 402 includes the vehicle's location data; the location data includes the vehicle's current latitude and longitude coordinates;

[0278] At least one target event includes an event in the dynamic event information database whose location is within the first target retrieval query area; the first target retrieval query area is the nine-grid neighbor area corresponding to the grid identifier of the Tile 15 grid obtained by converting latitude and longitude coordinates.

[0279] In one possible implementation, the dynamic event receiving request in the first receiving module 402 further includes a navigation path Link list for the vehicle; the navigation path Link list includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's currently planned path;

[0280] The target events also include events in the dynamic event information database that occur within the second target retrieval query area; the second target retrieval query area is the road segment area corresponding to the navigation path Link list.

[0281] The intelligent connected vehicle dynamic event processing device 40 provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0282] Figure 8 This is a schematic diagram of the cloud server structure provided in this application. Figure 8 As shown, the cloud server 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the cloud server 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0283] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0284] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0285] Figure 9 This is a schematic diagram of the controller provided in this application. Figure 9 As shown, the controller 60 provided in this embodiment includes at least one processor 601 and a memory 602. Optionally, the controller 60 further includes a communication component 603. The processor 601, memory 602, and communication component 603 are connected via a bus 604.

[0286] In a specific implementation, at least one processor 601 executes computer execution instructions stored in memory 602, causing at least one processor 601 to perform the above-described method.

[0287] The specific implementation process of processor 601 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0288] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0289] The memory may include read-only memory and random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Sync Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0290] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0291] This application also provides a vehicle, including a vehicle body and a controller for implementing the above-described method.

[0292] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0293] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0294] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as SRAM, EEPROM, EPROM, PROM, ROM, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0295] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside within an ASIC. Alternatively, the processor and the readable storage medium can exist as discrete components in a device.

[0296] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0297] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0298] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0299] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0300] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0301] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for processing dynamic events of intelligent connected vehicles, characterized in that, Applications to cloud servers include: In response to a dynamic event receiving request sent by a vehicle, at least one target event associated with the vehicle is retrieved from a dynamic event information database; the dynamic event information database stores blacklist and whitelist events of map data; The at least one target event is sent to the vehicle so that the vehicle can formulate a control strategy based on the at least one target event.

2. The method according to claim 1, characterized in that, The dynamic event receiving request includes the vehicle's location data; The step of acquiring at least one target event associated with the vehicle in response to a dynamic event reception request sent by the vehicle includes: Based on the location data in the dynamic event reception request sent by the vehicle, at least one target event matching the location data is queried from the dynamic event information database.

3. The method according to claim 2, characterized in that, The location data includes the vehicle's current latitude and longitude coordinates; the step of querying at least one target event matching the location data from a pre-stored dynamic event information database based on the location data in the dynamic event reception request sent by the vehicle includes: Convert the latitude and longitude coordinates into Tile 15 grid identifiers; The nine-square grid neighbor area corresponding to the grid identifier is determined as the first target retrieval area; In the dynamic event information database, events whose occurrence location is within the first target retrieval area are queried, and the queried events are identified as target events.

4. The method according to claim 2, characterized in that, The location data also includes the vehicle's navigation path Link list, which includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's current planned path; The step of querying at least one target event matching the location data from a pre-stored dynamic event information database based on the location data in the dynamic event reception request sent by the vehicle further includes: The road segment area corresponding to the navigation path Link list is determined as the second target retrieval area; In the dynamic event information database, events whose occurrence location is within the second target retrieval area are queried, and the queried events are identified as target events.

5. The method according to claim 4, characterized in that, The dynamic event receiving request also includes the vehicle's first map version; determining the road segment area corresponding to the navigation path Link list as the second target retrieval area includes: Obtain the second map version from the cloud server; If the first map version is the same as the second map version, then the road segment area corresponding to the navigation path Link list is determined as the second target retrieval area.

6. The method according to any one of claims 1 to 5, characterized in that, The dynamic event receiving request also includes the vehicle identifier of the vehicle; sending the at least one target event to the vehicle includes: Based on the dynamic event receiving request, obtain the vehicle identifier of the vehicle; Send the at least one target event to the vehicle corresponding to the vehicle identifier.

7. The method according to claim 6, characterized in that, Sending the at least one target event to the vehicle corresponding to the vehicle identifier includes: The at least one target event is sorted according to the importance of the event indicated by the event type of each target event to obtain the sending priority of each target event; In descending order of priority, the at least one target event is sent sequentially to the vehicle corresponding to the vehicle identifier.

8. The method according to any one of claims 1 to 5, characterized in that, The method further includes: The system monitors the data changes of each event in the dynamic event information database in real time, and when a data change event is detected in the dynamic event information database, it retrieves at least one target vehicle associated with the change event from the vehicle list. The updated change event is sent to the at least one target vehicle so that the at least one target vehicle adjusts its control strategy according to the updated change event; The vehicle list includes vehicle identifiers of vehicles that have sent dynamic event reception requests to the cloud server within a preset time period, as well as the latest location data corresponding to each vehicle identifier.

9. The method according to claim 8, characterized in that, The method further includes: In response to a dynamic event reception request sent by a vehicle, the vehicle list is updated based on the vehicle identifier and location data in the dynamic event reception request.

10. The method according to claim 8, characterized in that, Retrieving at least one target vehicle associated with the change event from the vehicle list includes: Obtain the location where the change event occurred; Search the vehicle list to obtain at least one target vehicle whose location data is associated with the location where the event occurred.

11. The method according to claim 8, characterized in that, Sending the updated change event to the at least one target vehicle includes: Obtain the distance between each target vehicle and the location where the change event occurred; The updated change events are sent to the at least one target vehicle in order of increasing distance.

12. The method according to any one of claims 1 to 5, characterized in that, The dynamic event information database also includes high-speed dynamic events reported by users.

13. A method for processing dynamic events of intelligent connected vehicles, characterized in that, Applications in vehicles include: Send a dynamic event reception request to the cloud server; The system receives at least one target event associated with a vehicle, retrieved from a dynamic event information database, returned by the cloud server; the dynamic event information database stores blacklist and whitelist events based on map data. Based on the at least one target event, a control strategy for the vehicle is formulated.

14. The method according to claim 13, characterized in that, The dynamic event receiving request includes the vehicle's location data; the location data includes the vehicle's current latitude and longitude coordinates. The at least one target event includes events in the dynamic event information database whose occurrence location is within the first target retrieval query area; The first target retrieval query area is the nine-square grid neighbor area corresponding to the grid identifier of the Tile 15 grid obtained by converting the latitude and longitude coordinates.

15. The method according to claim 13, characterized in that, The dynamic event receiving request also includes the vehicle's navigation path Link list; the navigation path Link list includes the segment identifiers of at least one road segment within a preset distance ahead in the vehicle's current planned path; The target events also include events in the dynamic event information database whose occurrence location is within the second target retrieval query area; The second target retrieval query area is the road segment area corresponding to the navigation path Link list.

16. The method according to any one of claims 13 to 15, characterized in that, The method further includes: Receive updated change events sent by the cloud server; the change events are events in the dynamic event information database where data has changed; The control strategy is adjusted based on the updated change events.

17. The method according to any one of claims 13 to 15, characterized in that, The dynamic event information database also includes high-speed dynamic events reported by users.

18. A cloud server, characterized in that, The including : memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1 to 12.

19. A controller, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 13 to 17.

20. A vehicle, characterized in that, The vehicle includes a vehicle body and the controller as described in claim 19.

21. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 12.

22. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 13 to 17.

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