Environmental change detection method, device, server, storage medium and program product

Abstract

The disclosed embodiments relate to an environmental change detection method, device, server, storage medium and program product, wherein the method obtains a plurality of motion trajectories within a preset time period to obtain a motion trajectory group belonging to the same motion area and the same prior map, and obtains the environmental change relative to the prior map in the same motion area after a preset time period based on the environmental change information of the trajectory points of all motion trajectories in the motion trajectory group. By merging and mutually verifying the environmental change information of the trajectory points between the plurality of motion trajectories in the same motion area and the same prior map, the actual location of the change can be determined, and the false detection information of the single-cycle single-lap change detection can be eliminated, thereby reducing the false detection probability of the detection, thereby obtaining a more accurate environmental change detection result, and improving the accuracy of environmental change detection.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of intelligent driving technology, and in particular, to an environment change detection method, device, server, storage medium, and program product. Background Art

[0002] The autonomous driving solutions provided by related technologies are generally based on pre-established maps for positioning and route planning. Figure 1 Generally, it is a snapshot of the physical world at a specific time. As time goes by, once the physical world changes, it may cause the physical world to not match the map, which in turn leads to reduced accuracy of positioning and route planning. Therefore, how to detect environmental changes in a timely and accurate manner is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In order to solve the above technical problems or at least partially solve the above technical problems, the embodiments of the present disclosure provide an environment change detection method, device, server, storage medium and program product.

[0004] A first aspect of an embodiment of the present disclosure provides an environment change detection method, the method comprising:

[0005] Acquire multiple motion trajectories within a preset time period, wherein the motion trajectories include a motion area, a priori map, and environmental change information of the trajectory points;

[0006] Among the plurality of motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map is obtained;

[0007] According to the environment change information of the trajectory points of all the motion trajectories in the motion trajectory group, the environment change relative to the priori map in the same motion area after the preset time period is obtained.

[0008] A second aspect of an embodiment of the present disclosure provides an environment change detection device, the device comprising:

[0009] An information acquisition module, used to acquire multiple motion trajectories within a preset time period, wherein the motion trajectories include the motion area, the prior map, and the environmental change information of the trajectory points;

[0010] A motion trajectory group module, used to obtain, from the plurality of motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map;

[0011] The change determination module is used to obtain the environmental change relative to the priori map in the same motion area after the preset time period based on the environmental change information of the trajectory points of all motion trajectories in the motion trajectory group.

[0012] A third aspect of an embodiment of the present disclosure provides a cloud server, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method of the first aspect can be implemented.

[0013] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the method of the first aspect described above can be implemented.

[0014] The fifth aspect of an embodiment of the present disclosure provides a computer program product, which includes: a computer program, the computer program is stored in a computer-readable storage medium, a processor reads and executes the computer program from the computer-readable storage medium, and when the computer program is executed by the processor, the method of the above-mentioned first aspect can be implemented.

[0015] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:

[0016] In the disclosed embodiment, multiple motion trajectories within a preset time period are obtained, wherein the motion trajectories include the motion area, the prior map, and the environmental change information of the trajectory points. Among the multiple motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map is obtained, and the environmental change relative to the prior map in the same motion area over the preset time period is obtained based on the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group. Since the acquired motion trajectories may be from different vehicles or the same vehicle, and there are multiple motion trajectories, the actual location of the change can be determined by merging and mutually verifying the environmental change information of the trajectory points between multiple motion trajectories in the same motion area and belonging to the same prior map, which can eliminate the false detection information of the single-vehicle single-lap change detection, reduce the false detection probability of the detection, and thus obtain a more accurate environmental change detection result, thereby improving the accuracy of environmental change detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1is a schematic diagram of an environmental change detection scenario provided by an embodiment of the present disclosure;

[0020] Figure 2 is a flow chart of an environmental change detection method provided by an embodiment of the present disclosure;

[0021] Figure 3 is a flow chart of another environmental change detection method provided by an embodiment of the present disclosure;

[0022] Figure 4 is a schematic diagram of environmental change information verification provided by an embodiment of the present disclosure;

[0023] Figure 5 is a schematic diagram of another environmental change information verification provided by an embodiment of the present disclosure;

[0024] Figure 6 is a schematic diagram of an environmental change detection provided by an embodiment of the present disclosure;

[0025] Figure 7 is a structural schematic diagram of an environmental change detection device provided by an embodiment of the present disclosure;

[0026] Figure 8 It is a structural diagram of a cloud server provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0028] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0029] In the related art, one method of environmental change detection is to establish a distance histogram for each point in the 3D point cloud map based on the distance error between the point in the three-dimensional (3D) point cloud map and the point mapped to the point cloud map, update the distance histogram of each point in the point cloud map according to the distance between the point in the point cloud observed in real time and the point in the point cloud map, update the error distribution between each point on the map and the observed point through Dirichlet distribution, and finally determine whether each point in the map is a point where the environment has changed (hereinafter referred to as a change point) according to the error distribution; another method is to obtain a priori map, which is a 2D rasterized map, which contains the reflection value information and height value information of a single Gaussian, generate a map in the same format as the priori map according to the point cloud information observed online in real time, compare the reflection value and height value of each grid in the generated map and the priori map, and continuously update the degree of change of each grid according to the binary Bayesian filtering method, thereby realizing environmental change detection. The above two methods are both single-cycle single-circle change detection, with a large probability of false detection, that is, the accuracy of environmental change detection is low.

[0030] In view of the defects of the related technologies in terms of the accuracy of environmental change detection, the embodiments of the present disclosure provide a new environmental change detection solution. For example, Figure 1 is a schematic diagram of an environmental change detection scenario provided by an embodiment of the present disclosure, such as Figure 1 As shown, the cloud server can receive multiple motion trajectories within a preset time period sent by the vehicle, and the motion trajectories include the motion area, the prior map, and the environmental change information of the trajectory points. Among the multiple motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map is obtained. Then, the cloud server obtains the environmental changes relative to the prior map in the same motion area after a preset time period based on the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group. Since the acquired motion trajectories can come from different vehicles or the same vehicle, and the number of motion trajectories is multiple, the actual location of the change can be determined by merging and mutually verifying the environmental change information of the trajectory points between multiple motion trajectories in the same motion area and belonging to the same prior map, which can eliminate the false detection information of the single-vehicle single-circle change detection, reduce the probability of false detection, and thus obtain more accurate environmental change detection results, thereby improving the accuracy of environmental change detection.

[0031] The vehicle referred to in the embodiments of the present disclosure can be exemplarily understood as an autonomous driving vehicle, which may include a module for collecting motion trajectory and environmental change information, as well as an algorithm module for implementing other functions. Of course, these algorithm modules will vary depending on the type of autonomous driving vehicle. For example, different algorithm modules will be involved for logistics vehicles, public service vehicles, medical service vehicles, and terminal service vehicles. The following examples illustrate the algorithm modules for these four autonomous driving vehicles:

[0032] Among them, logistics vehicles refer to vehicles used in logistics scenarios, such as logistics vehicles with automatic sorting functions, logistics vehicles with refrigeration and insulation functions, and logistics vehicles with measurement functions. These logistics vehicles will involve different algorithm modules.

[0033] For example, a logistics vehicle may be equipped with an automated sorting device, which can automatically take out, transport, sort, and store the goods after the logistics vehicle arrives at the destination. This involves an algorithm module for goods sorting, which mainly implements logical control of goods taking out, transporting, sorting, and storing.

[0034] For another example, for cold chain logistics scenarios, logistics vehicles can also be equipped with refrigeration and heat preservation devices, which can refrigerate or keep warm the transported fruits, vegetables, aquatic products, frozen foods and other perishable foods, so that they are in a suitable temperature environment, solving the problem of long-distance transportation of perishable foods. This involves an algorithm module for refrigeration and heat preservation control, which is mainly used to dynamically and adaptively calculate the appropriate temperature for cold meals or heat preservation based on information such as the nature of the food (or item), perishability, transportation time, current season, climate, etc., and automatically adjust the refrigeration and heat preservation device according to the appropriate temperature. In this way, when the vehicle transports different foods or items, the transportation personnel do not need to manually adjust the temperature, freeing the transportation personnel from cumbersome temperature control and improving the efficiency of refrigerated and heat preservation transportation.

[0035] For another example, in most logistics scenarios, charges are based on the volume and / or weight of the package, but the number of logistics packages is very large. Simply relying on couriers to measure the volume and / or weight of the packages is very inefficient and has high labor costs. Therefore, in some logistics vehicles, measuring devices are added to automatically measure the volume and / or weight of logistics packages and calculate the cost of logistics packages. This involves an algorithm module for logistics package measurement, which is mainly used to identify the type of logistics package and determine the measurement method of the logistics package, such as volume measurement or weight measurement or a combination of volume and weight measurement at the same time. It can also complete the volume and / or weight measurement according to the determined measurement method, and complete the fee calculation based on the measurement results.

[0036] Among them, public service vehicles refer to vehicles that provide some public services, such as fire trucks, de-icing trucks, sprinkler trucks, snowplows, garbage disposal vehicles, traffic control vehicles, etc. These public service vehicles will involve different algorithm modules.

[0037] For example, for an autonomous fire truck, its main task is to carry out reasonable fire-fighting tasks at the fire scene, which involves an algorithm module for fire-fighting tasks. The algorithm module must at least implement logic such as fire condition identification, fire-fighting plan planning, and automatic control of fire-fighting equipment.

[0038] For another example, the main task of a de-icing vehicle is to clear ice and snow from the road surface, which involves a de-icing algorithm module. The algorithm module must at least be able to identify the ice and snow conditions on the road surface and develop a de-icing plan based on the ice and snow conditions, such as which sections of the road require de-icing and which sections do not, whether to use salt spreading and the number of grams of salt to spread, as well as automatic control of the de-icing device when the de-icing plan is determined.

[0039] Among them, medical service vehicles refer to self-driving vehicles that can provide one or more medical services. Such vehicles can provide medical services such as disinfection, temperature measurement, medication, and isolation. This involves algorithm modules that provide various self-service medical services. These algorithm modules mainly realize the identification of disinfection needs and the control of the disinfection device so that the disinfection device can disinfect the patient, or identify the patient's position and control the temperature measuring device to automatically approach the patient's forehead and other positions to measure the patient's temperature, or are used to realize the judgment of the disease, give a prescription based on the judgment result, and need to realize the identification of drugs / drug containers, as well as the control of the medicine-taking robot to grab medicines for the patient according to the prescription, etc.

[0040] Among them, terminal service vehicles refer to self-service autonomous driving vehicles that can replace some terminal devices to provide certain convenient services to users. For example, these vehicles can provide users with printing, attendance, scanning, unlocking, payment, retail and other services.

[0041] For example, in some application scenarios, users often need to go to a specific location to print or scan documents, which is time-consuming and laborious. Therefore, there is a terminal service vehicle that can provide printing / scanning services for users. These service vehicles can be interconnected with user terminal devices. Users issue printing instructions through terminal devices, and service vehicles respond to printing instructions, automatically print the documents required by users, and automatically send the printed documents to the user's location. Users do not need to queue up at the printer, which can greatly improve printing efficiency. Alternatively, it can respond to the scanning instructions issued by the user through the terminal device, move to the user's location, and the user places the document to be scanned on the scanning tool of the service vehicle to complete the scanning, without having to queue up at the printer / scanner, saving time and effort. This involves an algorithm module that provides printing / scanning services, which at least needs to identify the interconnection with the user's terminal device, the response to the printing / scanning instruction, the positioning of the user's location, and the travel control.

[0042] For another example, with the development of new retail services, more and more e-commerce companies use self-service vending machines to sell goods to major office buildings and public areas. However, these self-service vending machines are placed in fixed locations and cannot be moved. Users need to go to the self-service vending machines to buy the required goods, which is still inconvenient. Therefore, self-driving vehicles that can provide retail services have emerged. These service vehicles can carry goods and move automatically, and can provide corresponding self-service shopping apps or shopping portals. Users can place orders to self-driving vehicles that provide retail services through mobile phones and other terminals through apps or shopping portals. The order includes the name, quantity and user location of the goods to be purchased. After receiving the order request, the vehicle can determine whether the current remaining goods have the goods purchased by the user and whether the quantity is sufficient. If it is determined that the goods purchased by the user are sufficient, it can automatically move to the user's location with these goods and provide these goods to the user, further improving the convenience of user shopping, saving user time, and allowing users to spend their time on more important things. This involves algorithm modules that provide retail services. These algorithm modules mainly implement logic such as responding to user order requests, order processing, product information maintenance, user location positioning, and payment management.

[0043] Furthermore, in order to better understand the inventive concept of the embodiments of the present disclosure, the technical solutions of the embodiments of the present disclosure are described below in conjunction with exemplary embodiments.

[0044] Figure 2 is a flow chart of an environmental change detection method provided by an embodiment of the present disclosure. The method can be executed by a cloud server. Figure 2 As shown, the method provided in this embodiment includes the following steps:

[0045] Step 101: Acquire multiple motion trajectories within a preset time period.

[0046] Among them, the motion trajectory includes the motion area, the prior map and the environmental change information of the trajectory point. The motion area can be understood as the area where environmental change detection is currently required, and can be set as needed. For example, the motion area can be the automatic driving area of ​​the vehicle. Environmental change detection can be understood as detecting the changes in the current physical environment compared to the historical physical environment. The prior map can be a pre-established map, which can be a snapshot of the physical world at a specific time.

[0047] The motion trajectory in this embodiment can be trajectory data including environmental change information of trajectory points sent by the vehicle. The trajectory point refers to the minimum position point constituting the motion trajectory, and a motion trajectory can include multiple trajectory points. Environmental change information can be understood as specific information characterizing whether the environment has changed and the degree of change. For example, environmental change information can include annotation information for marking whether the environment of the trajectory point has changed and information on the degree of environmental change. The environmental change information in this embodiment can be obtained based on a priori map detection. For example, in one example, the vehicle can collect three-dimensional point cloud data around each mobile position while moving in the above-mentioned motion area, and then generate a map in the same format as the priori map based on the three-dimensional point cloud data around each mobile position, and the map corresponds to a grid in the priori map. The environmental change information around the mobile position is determined by comparing the generated map with the corresponding grid in the priori map. The above is only an example of determining environmental change information, and is not the only limitation.

[0048] In this embodiment, multiple motion trajectories collected by one or more vehicles within a preset time period can be stored in a preset database, and the cloud server can obtain multiple motion trajectories collected by one or more vehicles within the preset time period from the database. The preset time period can be set according to actual conditions, and this solution does not limit this.

[0049] Optionally, obtaining the multiple motion tracks within a preset time period is timed acquisition, that is, the cloud server can obtain the multiple motion tracks within a preset time period at a preset time point, and the preset time point can be set according to actual conditions and is not specifically limited.

[0050] Step 102: From the plurality of motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map is obtained.

[0051] The motion area can be distinguished by the information of the motion area, for example, the information of the motion area can be the area identification, which can be specifically represented by numbers, letters, etc. The prior maps constructed at different times are different. This solution can use the information of the prior map to distinguish the prior maps constructed at different times. For example, the map version number can be used to represent the information of the prior map, and the map version number can also be represented by numbers, letters, etc.

[0052] In this embodiment, after obtaining multiple motion trajectories within a preset time period, the cloud server can filter the multiple motion trajectories according to the information of the motion area and the information of the prior map, determine the multiple motion trajectories belonging to the same motion area and the same prior map, and form a motion trajectory group.

[0053] Step 103: Obtain the environmental change relative to the priori map in the same motion area over a preset time period according to the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group.

[0054] In a feasible implementation, after the cloud server obtains a motion trajectory group belonging to the same motion area and the same prior map, the cloud server verifies the environmental change information of the trajectory points on any acquired motion trajectory based on the environmental change information of the trajectory points of all motion trajectories in the motion trajectory group, and obtains the position of the environmental change relative to the prior map within the same motion area after a preset time period based on the verification result.

[0055] Specifically, for the verification of the environmental change information of any motion trajectory, the same trajectory point in different motion trajectories, that is, multiple trajectory points with the same coordinates in different motion trajectories, can be used to obtain the environmental change information of the same trajectory point in different motion trajectories and perform verification. The above verification method can be used to verify the environmental change information of the trajectory points of all motion trajectories in the motion trajectory group, determine the trajectory points where the environment has changed, and then obtain the trajectory points that have changed relative to the prior map environment in the same motion area after a preset time period.

[0056] Exemplarily, the specific verification method of the environmental change information of the trajectory point can be that if the number of trajectory points with the same environmental change information in the same trajectory point in different motion trajectories is greater than a preset number, then it is determined that the environment of the trajectory point has changed; otherwise, it is determined that the environment of the trajectory point has not changed. The preset number can be set according to actual conditions, for example, the preset number can be half of the total number of trajectory points with the same coordinates in different motion trajectories. It is understandable that the above verification method is only an example and is not the only limitation.

[0057] In the disclosed embodiment, multiple motion trajectories within a preset time period are obtained, wherein the motion trajectories include the motion area, the prior map, and the environmental change information of the trajectory points. Among the multiple motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map is obtained, and the environmental change relative to the prior map in the same motion area over the preset time period is obtained based on the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group. Since the acquired motion trajectories may be from different vehicles or the same vehicle, and there are multiple motion trajectories, the actual location of the change can be determined by merging and mutually verifying the environmental change information of the trajectory points between multiple motion trajectories in the same motion area and belonging to the same prior map, which can eliminate the false detection information of the single-vehicle single-lap change detection, reduce the false detection probability of the detection, and thus obtain a more accurate environmental change detection result, thereby improving the accuracy of environmental change detection.

[0058] For example, Figure 3 is a flow chart of another environmental change detection method provided by an embodiment of the present disclosure. Figure 3 As shown, in a feasible implementation manner, according to the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group, a method for obtaining the environmental change relative to the priori map within the same motion area after a preset time period may include:

[0059] Step 301: For the same trajectory point in different motion trajectories, calculate the confidence level of the change of the trajectory point.

[0060] The confidence level can be understood as the degree of trust that a parameter value is an accurate value. In this embodiment, the confidence level of a change in a trajectory point can be understood as the degree of trust in an environmental change of the trajectory point.

[0061] In a feasible embodiment, step 301 may include the following steps:

[0062] Step 3011: The same trajectory point in different motion trajectories is called the first trajectory point.

[0063] The same trajectory point may represent trajectory points with the same coordinates.

[0064] The cloud server can extract the trajectory points with the same coordinates in different motion trajectories according to the coordinates of the trajectory points in all motion trajectories in the motion trajectory group, which are called the first trajectory points. Since there can be multiple trajectory points with the same coordinates in different motion trajectories, there can be multiple first trajectory points.

[0065] Step 3012: Obtain multiple adjacent trajectory points of the first trajectory point on different motion trajectories that meet a preset range.

[0066] The preset range can be set according to actual needs, and in this embodiment, it can be understood as a preset range around the first track point. The cloud server can determine multiple adjacent track points located within the preset range around the first track point from multiple motion tracks for the first track point.

[0067] Since the trajectory points within the preset range around the first trajectory point are points that are closer to the first trajectory point, their surrounding environments are similar. Therefore, the environmental change information of the trajectory points within the preset range around the first trajectory point can be used as a reference for verifying the environmental change information of the first trajectory point.

[0068] Step 3013: Determine whether each adjacent trajectory point is a changed trajectory point or an unchanged trajectory point.

[0069] In this embodiment, the environment change information includes annotation information for marking whether the environment of the track point has changed. The annotation information can be one of the environment change information, and can be represented by numbers, letters, or Chinese characters, etc., without limitation.

[0070] In this embodiment, after the cloud server obtains multiple adjacent trajectory points of the first trajectory point on different motion trajectories that meet a preset range, it can determine whether each adjacent trajectory point is a changed trajectory point or an unchanged trajectory point based on the annotation information of the adjacent trajectory points.

[0071] Step 3014: Calculate the confidence level of the change of the first trajectory point according to the number of changed trajectory points and the number of unchanged trajectory points.

[0072] In this embodiment, the cloud server calculates the confidence value based on the number of changed trajectory points and the number of unchanged trajectory points. The confidence level of the change in the environment at the first trajectory point can be calculated, where c i Represents confidence, m i Indicates the number of change trajectory points, n i Indicates the number of unchanged trajectory points.

[0073] Step 302: The trajectory points whose confidence levels are higher than a preset threshold are regarded as changed trajectory points.

[0074] The preset threshold value may be determined according to actual conditions and is not limited to a specific one.

[0075] In this embodiment, after calculating the confidence of the change of the same trajectory point in different motion trajectories, the cloud server can compare the confidence with a preset threshold. If the confidence of a trajectory point is higher than the preset threshold, the trajectory point is a trajectory point where the environment has changed; otherwise, the trajectory point is a trajectory point where the environment has not changed.

[0076] For example, Figure 4 is a schematic diagram of an environmental change information verification provided by an embodiment of the present disclosure, such as Figure 4 As shown, the cloud server can obtain the motion trajectories with change information of multiple vehicles, calculate the confidence of the change of each trajectory point, and determine the trajectory points with high confidence, that is, the changed trajectory points.

[0077] Step 303: Obtain the environmental change relative to the priori map within the same motion area after a preset time period based on the environmental change information of the changed trajectory point.

[0078] In this embodiment, based on step 301 and step 302, the environmental change information of multiple first trajectory points of all motion trajectories in the motion trajectory group can be verified by calculating the confidence, and the environmental change information of the changed trajectory points can be determined, so as to obtain the trajectory points that have changed relative to the prior map environment in the same motion area after a preset time period.

[0079] For example, Figure 5 is a schematic diagram of another environmental change information verification provided by an embodiment of the present disclosure, Figure 5 In the figure, three motion trajectories are shown by way of example. The number of trajectory points included in the three motion trajectories is the same as the coordinates of each trajectory point. The trajectory points are represented by circles. The circle including the number 1 in the figure is a changed trajectory point marked by the vehicle as an environmental change, that is, the annotation information of the trajectory point is an environmental change. The circle including the number 2 in the figure is a changed trajectory point marked by the cloud server as an environmental change, that is, the trajectory point determined by the cloud server as an environmental change. Figure 5 The circles without numbers in the figure represent unchanged track points marked by the vehicle, that is, the annotation information of the track points indicates that the environment has not changed. Figure 5 As shown, the cloud server can determine whether the same trajectory point with the same multiple coordinates of the three motion trajectories and marked as a changed trajectory point by the vehicle is a changed trajectory point or an unchanged trajectory point based on the annotation information of the adjacent trajectory points within a preset range around the same trajectory point, and verify its own environmental change information based on the confidence determined by the number of changed trajectory points and the number of unchanged trajectory points, and finally determine whether the environment of the trajectory point has changed.

[0080] For example, Figure 6 is a schematic diagram of an environmental change detection provided by an embodiment of the present disclosure, such as Figure 6As shown, according to the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group, the environmental change relative to the prior map is obtained in the same motion area after a preset time period. The environmental change detection method may also include: updating the prior map to a new version according to the environmental change relative to the prior map.

[0081] Specifically, after the cloud server obtains the environmental changes relative to the prior map within the same movement area after a preset time period, it can send information about the location where the environmental changes occurred to the map update device, so that the map update device updates the prior map to a new version based on the information about the location where the environmental changes occurred. The cloud server can send the coordinates of the trajectory points where the environmental changes occurred to the map update device, and the map update device can update the prior map according to the coordinates of the trajectory points where the environmental changes occurred, so that the user can perform subsequent positioning and route planning according to the updated prior map, thereby improving the accuracy of positioning and route planning, and thus improving the safety of autonomous driving.

[0082] like Figure 6 As shown, this solution specifically includes two parts: vehicle change detection and cloud change detection. Among them, the change detection module in the vehicle compares the point cloud data observed in real time with the prior map, calculates the environmental change information of the track points on the motion trajectory, and sends multiple motion trajectories with the environmental change information of the motion area, the prior map and the track points to the cloud server through the vehicle message upload module. The cloud change detection module in the cloud server is responsible for continuously receiving the motion trajectories sent by different vehicles, storing the motion trajectories in the database, and triggering the query database at a fixed time to obtain multiple motion trajectories existing in the database within a preset time period; then the environmental change information of the track points of all motion trajectories belonging to the same motion area and the same prior map motion trajectory group is merged, and the false detection change information is filtered out, and then the trajectory information (including the information of the track points of the confirmed environmental change) in the same motion area after a preset time period relative to the prior map is stored in the database, so as to regularly send the information of the track points of the environmental change stored in the database to the map update device to guide the map update.

[0083] This solution provides an end-cloud integrated environmental change detection method, which collects environmental change information through one or more vehicles and sends it to a cloud server. The cloud server merges the environmental change detection results of multiple laps of a single vehicle or multiple laps of multiple vehicles, which can eliminate false detections in a single lap of a single vehicle to the greatest extent, thereby obtaining more accurate environmental change detection results.

[0084] Figure 7is a schematic diagram of the structure of an environmental change detection device provided by an embodiment of the present disclosure. The processing device can be understood as the above-mentioned cloud server or some functional modules in the above-mentioned cloud server. Figure 7 As shown, the environment change detection device 70 includes:

[0085] An information acquisition module 71 is used to acquire multiple motion trajectories within a preset time period, wherein the motion trajectories include the motion area, the prior map, and the environmental change information of the trajectory points;

[0086] A motion trajectory group module 72, configured to obtain, from the plurality of motion trajectories, a motion trajectory group that belongs to the same motion area and the same prior map;

[0087] The change determination module 73 is used to obtain the environmental change relative to the priori map in the same motion area after the preset time period according to the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group.

[0088] In one embodiment, the change determination module 73 includes:

[0089] A confidence unit, for calculating the confidence of a change in a same trajectory point in different motion trajectories;

[0090] A change verification unit, used to take the trajectory points with a confidence level higher than a preset threshold as the trajectory points that have changed;

[0091] The determination unit is used to obtain the environmental change relative to the priori map in the same motion area after the preset time period according to the environmental change information of the changed trajectory point.

[0092] In one embodiment, the confidence unit is specifically used to:

[0093] The same trajectory point in different motion trajectories is called the first trajectory point;

[0094] Obtaining a plurality of adjacent trajectory points of the first trajectory point on different motion trajectories that meet a preset range;

[0095] Determine whether each adjacent trajectory point is a changed trajectory point or an unchanged trajectory point;

[0096] The confidence level that the first trajectory point has changed is calculated according to the number of changed trajectory points and the number of unchanged trajectory points.

[0097] In one implementation, the acquiring of multiple motion trajectories within a preset time period is timed acquisition.

[0098] In one implementation, the environment change detection device 70 further includes a map update module, and the map update module is specifically configured to:

[0099] The a priori map is updated to a new version according to the environmental changes relative to the a priori map.

[0100] The device provided in this embodiment can perform the above Figure 2-Figure 3 The execution method and beneficial effects of the method in any embodiment are similar and will not be described in detail here.

[0101] The present disclosure also provides a cloud server, which includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the above-mentioned Figure 2-Figure 3 The method of any one of the embodiments.

[0102] For example, Figure 8 This is a schematic diagram of the structure of a cloud server provided by an embodiment of the present disclosure. Figure 8 , which shows a schematic diagram of a structure suitable for implementing the cloud server 800 in the embodiment of the present disclosure. The cloud server 800 in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The cloud server shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0103] like Figure 8 As shown, the cloud server 800 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 to a random access memory (RAM) 803. In RAM 803, various programs and data required for the operation of the cloud server 800 are also stored. The processing device 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0104] Typically, the following devices may be connected to the I / O interface 805: input devices 806 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 807 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 808 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 809. The communication devices 809 may allow the cloud server 800 to communicate with other devices wirelessly or by wire to exchange data. Figure 8 The cloud server 800 having various devices is shown, but it should be understood that it is not required to implement or have all the devices shown. More or fewer devices may be implemented or have instead.

[0105] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 809, or installed from a storage device 808, or installed from a ROM 802. When the computer program is executed by the processing device 801, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0106] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0107] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0108] The computer-readable medium may be included in the cloud server; or may exist independently without being installed in the cloud server.

[0109] The computer-readable medium carries one or more programs. When the one or more programs are executed by the cloud server, the cloud server obtains multiple motion trajectories within a preset time period, wherein the motion trajectories include a motion area, a priori map, and environmental change information of the trajectory points; among the multiple motion trajectories, a motion trajectory group belonging to the same motion area and the same priori map is obtained; based on the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group, the environmental changes relative to the priori map in the same motion area after the preset time period are obtained.

[0110] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0111] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0112] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0113] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0114] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] The present disclosure also provides a computer-readable storage medium in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned Figure 2-Figure 3 The method of any embodiment has similar execution mode and beneficial effects, which will not be described in detail here.

[0116] The present disclosure also provides a computer program product, which includes: a computer program, the computer program is stored in a computer-readable storage medium, a processor reads and executes the computer program from the computer-readable storage medium, and when the computer program is executed by the processor, the above-mentioned Figure 2-Figure 3 The method of any embodiment has similar execution mode and beneficial effects, which will not be described in detail here.

[0117] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0118] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting environmental changes, characterized in that: include: Acquire multiple motion trajectories within a preset time period, wherein the motion trajectories include a motion area, a priori map, and environmental change information of the trajectory points, wherein the environmental change information includes information on whether the environment has changed and the degree of change; Among the plurality of motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map is obtained; Obtaining, according to the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group, the environmental change relative to the priori map over the preset time period in the same motion area; The step of obtaining, based on the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group, the environmental change relative to the priori map within the same motion area after the preset time period, comprises: For the same trajectory point in different motion trajectories, calculate the confidence level of the change of the trajectory point; The trajectory points with confidence higher than a preset threshold are regarded as changed trajectory points; Obtaining, according to the environmental change information of the changed trajectory point, the environmental change relative to the priori map within the same motion area after the preset time period; The step of calculating the confidence level of a change in a same trajectory point in different motion trajectories includes: The same trajectory point in different motion trajectories is called the first trajectory point; Obtaining a plurality of adjacent trajectory points of the first trajectory point on different motion trajectories that meet a preset range; Determine whether each adjacent trajectory point is a changed trajectory point or an unchanged trajectory point; The confidence level that the first trajectory point has changed is calculated according to the number of changed trajectory points and the number of unchanged trajectory points.

2. The method according to claim 1, characterized in that The acquiring of multiple motion trajectories within a preset time period is timed acquisition.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: The a priori map is updated to a new version according to the environmental changes relative to the a priori map.

4. An environmental change detection device, characterized in that: include: An information acquisition module, used to acquire multiple motion trajectories within a preset time period, wherein the motion trajectories include the motion area, the prior map, and environmental change information of the trajectory points, wherein the environmental change information includes information on whether the environment has changed and the degree of change; A motion trajectory group module, used to obtain, from the plurality of motion trajectories, a motion trajectory group belonging to the same motion area and the same prior map; a change determination module, configured to obtain, based on the environmental change information of the trajectory points of all the motion trajectories in the motion trajectory group, an environmental change relative to the priori map within the same motion area after the preset time period; The change determination module is specifically used for: For the same trajectory point in different motion trajectories, calculate the confidence level of the change of the trajectory point; The trajectory points with confidence higher than a preset threshold are regarded as changed trajectory points; Obtaining, according to the environmental change information of the changed trajectory point, the environmental change relative to the priori map within the same motion area after the preset time period; The change determination module is specifically used for: The same trajectory point in different motion trajectories is called the first trajectory point; Obtaining a plurality of adjacent trajectory points of the first trajectory point on different motion trajectories that meet a preset range; Determine whether each adjacent trajectory point is a changed trajectory point or an unchanged trajectory point; The confidence level that the first trajectory point has changed is calculated according to the number of changed trajectory points and the number of unchanged trajectory points.

5. A cloud server, characterized in that: include: A memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method according to any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

7. A computer program product, characterized in that include: A computer program, wherein the computer program is stored in a computer-readable storage medium, a processor reads and executes the computer program from the computer-readable storage medium, and when the computer program is executed by the processor, the processor executes the method according to any one of claims 1 to 3.

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