A method, device and electronic equipment for updating road travel information

Abstract

The application discloses a road driving information updating method and device and electronic equipment. The method comprises the following steps: determining a target road section and road driving information of the target road section; determining an actual speed limit value marked on a speed limit sign on an adjacent road section included in the target road section based on a road live video corresponding to the target road section; and updating a marked speed limit value in the road driving information to the actual speed limit value in response to the actual speed limit value being different from the marked speed limit value. Through the technical scheme provided by the embodiment of the application, the actual speed limit value is determined, and it is determined that the actual speed limit value is different from the marked speed limit value, so that the marked speed limit value in the road driving information is updated, manual determination of the actual speed limit value and manual determination of the difference between the actual speed limit value and the marked speed limit value are avoided, and the updating efficiency and updating accuracy of the road driving information are improved.

Description

A method, apparatus, and electronic device for updating road driving information. Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a method, apparatus and electronic device for updating road driving information. Background Technology

[0002] With the development of intelligent driving technology, autonomous driving is being widely applied in vehicles. In autonomous driving, based on high-precision maps, vehicles in autonomous driving mode can obtain information about the road ahead and speed limits in advance. This speed limit information includes the speed limit value, enabling the vehicle to perform various autonomous decision-making and control functions. Examples include automatic on / off ramp entry and exit, autonomous driving on sharp curves, and speed limit fusion. Therefore, high-precision maps have become a crucial component of autonomous driving.

[0003] However, due to frequent road maintenance and adjustments, high-precision maps are difficult to update in a timely manner, leading to errors in the corresponding road driving information. These errors include incorrect speed limits; that is, the marked speed limit for a certain road segment is inconsistent with the actual speed limit for that segment, meaning the marked speed limit for a particular road segment has not been updated in a timely manner.

[0004] For example, road segment designated 001 has a speed limit sign indicating a speed limit of 120 km / h. Therefore, the marked speed limit for road segment 001 on the high-precision map is 120 km / h. However, due to road maintenance or adjustments, the actual speed limit on the sign for road segment 001 may be adjusted to 80 km / h. In this case, the marked speed limit for road segment 001 is inconsistent with the actual speed limit.

[0005] To address the aforementioned issue of incorrect road driving information, the current approach primarily involves collecting real-time road condition videos of various road sections from high-precision maps. Test personnel then visually identify the actual speed limits marked on speed limit signs in the real-time road condition videos and compare them with the marked speed limits set for each road section in the high-precision map. This process determines whether the marked speed limits set for each road section in the high-precision map are correct, thereby updating the marked speed limit values ​​in the road driving information.

[0006] However, in the above methods, manually updating the marked speed limit values ​​in road driving information consumes a lot of manpower and resources, which makes the updating efficiency of road driving information low. Summary of the Invention

[0007] This application provides a method, apparatus, and electronic device for updating road driving information, to solve the problem of low update efficiency when manually updating road driving information. The specific implementation scheme is as follows:

[0008] Firstly, this application provides a method for updating road driving information, including:

[0009] Identify the target road segment and the road driving information of the target road segment; wherein the road driving information includes the marked speed limit value of the target road segment;

[0010] Based on the real-time video of the road conditions corresponding to the target road segment, determine the actual speed limit values ​​marked by the speed limit signs of the adjacent road segments included in the target road segment;

[0011] In response to the difference between the actual speed limit and the marked speed limit, the marked speed limit is updated to the actual speed limit.

[0012] The above method identifies and updates incorrectly marked speed limits by determining the marked speed limit value of the target road segment and the actual speed limit value marked by the speed limit signs of the adjacent road segments included in the target road segment. This avoids the need for manual determination of the actual speed limit value and the incorrectly marked speed limit value, thus effectively improving the efficiency and accuracy of updating road driving information.

[0013] In one possible implementation, determining the target road segment includes:

[0014] In the high-precision map, determine the marked speed limit value corresponding to each of the adjacent road segments;

[0015] Calculate the change between the marked speed limit values ​​corresponding to each of the adjacent road segments;

[0016] Determine whether the change value is greater than the preset threshold;

[0017] If so, mark the adjacent road segment and the N road segments before and after the adjacent road segment as the target road segment; where N is a natural number.

[0018] By using the above method, after determining the marked speed limit values ​​corresponding to each adjacent road segment, the relationship between the calculated change value between the marked speed limit values ​​corresponding to each adjacent road segment and the preset threshold is determined. When the change value is greater than the preset threshold, the adjacent road segment is marked as the target road segment, thereby determining the target road segment and providing the target road segment that needs to be updated for subsequent updates of the marked speed limit values.

[0019] In one possible implementation, determining the marked speed limit value corresponding to each of the adjacent road segments in the high-precision map includes:

[0020] In the high-precision map, determine the corresponding road segment identifier for each of the adjacent road segments;

[0021] The marked speed limit is determined based on the correspondence between the road segment identifier and the marked speed limit.

[0022] The above method identifies the corresponding road segment identifiers for each adjacent road segment. Because these road segment identifiers are unique, the cloud can efficiently and accurately retrieve the corresponding speed limit value using these identifiers. Furthermore, compared to directly determining the speed limit value from adjacent road segments, determining the road segment identifiers first, and then determining the speed limit value, enables the cloud to efficiently read the speed limit value.

[0023] In one possible implementation, determining the actual speed limit value marked by the speed limit signs of adjacent road segments included in the target road segment based on the real-time road video corresponding to the target road segment includes:

[0024] Send collection information to the vehicle, enabling the vehicle to collect real-time video of the road corresponding to the target road segment; wherein, the collection information includes the road segment identifier corresponding to the target road segment;

[0025] Receive the real-time video of the road conditions;

[0026] The real-time road video is input into the target algorithm to determine the actual speed limit value marked by the speed limit signs on the adjacent road segments included in the target road segment.

[0027] Using the above method, based on the target algorithm, the real-time road video of the target road segment collected by the vehicle is processed, and the actual speed limit values ​​corresponding to the adjacent road segments included in the target road segment are automatically output, avoiding manual determination of the actual speed limit values, thereby further improving the update efficiency and accuracy of road driving information. Furthermore, when sending collection information to vehicles, collection information can be sent to vehicles equipped with cameras whose routes include the target road segment, enabling those vehicles to collect real-time road video of the target road segment. This allows each vehicle equipped with a camera to become a data source in the cloud, expanding the data source and enabling the collection of real-time road video of the target road segment in a shorter time. Simultaneously, compared to vehicles collecting real-time road video of each road segment in a high-precision map and then uploading that video, in this application, the vehicle only needs to collect and upload the real-time road video of the target road segment, reducing vehicle bandwidth consumption.

[0028] In one possible implementation, after determining the target road segment and the driving information of the target road segment, the method further includes:

[0029] Generate first driving information; wherein, the first driving information includes the road segment identifier corresponding to the target road segment and the marked speed limit value;

[0030] The step of updating the marked speed limit value to the actual speed limit value includes:

[0031] Delete the road segment identifier and the marked speed limit value corresponding to the target road segment from the first driving information;

[0032] Generate second driving information that includes the road segment identifier corresponding to the target road segment and the actual speed limit value.

[0033] Through the above method, first driving information containing the road segment identifier and marked speed limit value corresponding to the target road segment is generated. Based on this first driving information, the cloud can clearly identify the relevant information of each target road segment. Furthermore, by generating second driving information containing the road segment identifier and actual speed limit value corresponding to the target road segment, the marked speed limit value is updated to the actual speed limit value. Simultaneously, since the marked speed limit value corresponding to each target road segment in the first driving information needs to be verified for correctness, the cloud stores the updated actual speed limit value in the newly generated second driving information, instead of directly replacing the marked speed limit value with the actual speed limit value in the first driving information. Furthermore, the road segment identifier and marked speed limit value corresponding to the target road segment are deleted from the first driving information. This avoids the cloud sending the target road segment collection information to the vehicle again after verifying the marked speed limit value, thus avoiding duplicate verification caused by repeated sending of collection information, and consequently avoiding data errors and efficiency reduction due to duplicate verification.

[0034] In one possible implementation, after updating the marked speed limit value to the actual speed limit value, the method further includes:

[0035] Receive a download request sent by the target vehicle; wherein the download request includes the road segment identifier corresponding to the target road segment;

[0036] Based on the download request, the road segment identifier corresponding to the target road segment and the actual speed limit value are encrypted into a data packet and sent to the target vehicle.

[0037] In this way, based on the download request received from the target vehicle, the cloud sends a data packet containing the road segment identifier and the actual speed limit value corresponding to the target road segment to the target vehicle. This allows the target vehicle to obtain the actual speed limit value before entering the target road segment, thereby enabling the target vehicle to drive on the target road segment according to the actual speed limit value. This avoids the safety problems that would occur if the target vehicle drove on the target road segment with the original marked speed limit value, thus further improving the safety of vehicle driving.

[0038] In one possible implementation, the target road segment includes road segments with abnormal road types; then determining the target road segment includes:

[0039] Based on the preset mapping relationship between road types and road segment identifiers, query the road segment identifiers corresponding to the road type to be verified;

[0040] Based on the high-precision map, the road marking type of each road segment is determined, and the road segment corresponding to the road marking type that is inconsistent with the road type is marked as the target road segment.

[0041] Using the above method, based on the preset mapping relationship between road types and road segment identifiers, the road segment identifiers corresponding to the road type to be verified were determined. Simultaneously, based on a high-precision map, the road marker type for each road segment identifier was determined. Then, based on the judgment result of whether the road marker type is the same as the road type to be verified, it was determined whether the road marker type was incorrect; subsequently, the incorrect road marker type was marked as the target road segment, thus identifying the target road segment.

[0042] In one possible implementation, after marking the road segment corresponding to the road marking type that is inconsistent with the road type as the target road segment, the method further includes:

[0043] In the road driving information of the target road segment, the road marking type is updated to the road type.

[0044] By updating each erroneous road marking type to the road type to be verified in the above manner, safety accidents caused by incorrect road type are avoided, thereby improving the safety of vehicle driving.

[0045] Secondly, this application also provides a road driving information updating device, comprising:

[0046] The first determining module is used to determine the target road segment and the road driving information of the target road segment; wherein, the road driving information includes the marked speed limit value of the target road segment;

[0047] The second determining module is used to determine the actual speed limit value marked by the speed limit signs of the adjacent road sections included in the target road section based on the real-time video of the road conditions corresponding to the target road section.

[0048] A processing module is configured to update the marked speed limit to the actual speed limit in response to a difference between the actual speed limit and the marked speed limit.

[0049] In one possible implementation, the first determining module is specifically used to determine the marked speed limit value corresponding to each of the adjacent road segments in the high-precision map; calculate the change value between the marked speed limit values ​​corresponding to each of the adjacent road segments; determine whether the change value is greater than the preset threshold; if so, mark the adjacent road segment and the N road segments before and after the adjacent road segment as the target road segment; where N is a natural number.

[0050] In one possible implementation, the first determining module is specifically used to determine the road segment identifier corresponding to each of the adjacent road segments in the high-precision map; and to determine the marked speed limit value based on the correspondence between the road segment identifier and the marked speed limit value.

[0051] In one possible implementation, the second determining module is specifically used to send collection information to the vehicle, so that the vehicle collects the real-time video of the road corresponding to the target road segment; wherein, the collection information includes the road segment identifier corresponding to the target road segment; receive the real-time video of the road segment; input the real-time video of the road segment into the target algorithm, and determine the actual speed limit value marked by the speed limit sign on the adjacent road segments included in the target road segment.

[0052] In one possible implementation, the first determining module is specifically used to generate first driving information; wherein the first driving information includes the road segment identifier corresponding to the target road segment and the marked speed limit value; then the processing module is specifically used to delete the road segment identifier corresponding to the target road segment and the marked speed limit value from the first driving information; and generate second driving information including the road segment identifier corresponding to the target road segment and the actual speed limit value.

[0053] In one possible implementation, the processing module is specifically configured to receive a download request sent by the target vehicle; wherein the download request includes a road segment identifier corresponding to the target road segment; based on the download request, the road segment identifier corresponding to the target road segment and the actual speed limit value are encrypted into a data packet and sent to the target vehicle.

[0054] In one possible implementation, the target road segment includes road segments with abnormal road types; then the first determining module is specifically used to query each road segment identifier corresponding to the road type to be verified based on a preset mapping relationship between road types and road segment identifiers; determine the road mark type of each road segment identifier based on a high-precision map; and mark the road segment corresponding to the road mark type that is inconsistent with the road type as the target road segment.

[0055] In one possible implementation, the road driving information updating device further includes a type module; the type module is specifically used to update the road mark type to the road type in the road driving information of the target road segment.

[0056] Thirdly, this application provides an electronic device, comprising:

[0057] Memory, used to store computer programs;

[0058] When the processor executes the computer program stored in the memory, it implements the above-described method steps for updating road driving information.

[0059] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method steps for updating road driving information.

[0060] For the various aspects of the second to fourth aspects mentioned above, and the technical effects that each aspect may achieve, please refer to the above description of the technical effects that can be achieved for the first aspect or the various possible solutions in the first aspect, which will not be repeated here. Attached Figure Description

[0061] Figure 1 is a flowchart illustrating a method for updating road driving information according to an embodiment of this application;

[0062] Figure 2 is a schematic diagram of the processing procedure of a road driving information updating method provided in an embodiment of this application;

[0063] Figure 3 is a schematic diagram of a road driving information updating device provided in an embodiment of this application;

[0064] Figure 4 is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The specific operational methods in the method embodiments can also be applied to the device embodiments or system embodiments. It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. A connected to B can represent: A and B directly connected, and A and B connected through C. Furthermore, in the description of this application, terms such as "first" and "second" are used only for distinguishing the purpose of description and should not be construed as indicating or implying relative importance or order.

[0066] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0067] To address errors in road driving information in high-definition maps, the current main method for updating this information is as follows: First, video footage of various road segments in the high-definition map is collected. Then, speed limit signs in the video are manually identified, and the actual speed limit value marked on each sign is read. Next, this is compared with the marked speed limit values ​​set for each road segment in the high-definition map to determine if the marked speed limit values ​​are correct, thereby updating the marked speed limit values ​​in the road driving information. However, while manually updating the marked speed limit values ​​in the road driving information solves the problem of errors in road driving information in high-definition maps, this method suffers from low update efficiency.

[0068] Based on this, this application proposes a method for updating road driving information, which can be applied to the cloud or to the vehicle. Preferably, it is applied to the cloud. The method includes: first, determining a target road segment and its road driving information, including the marked speed limit value of the target road segment; based on the real-time video of the road conditions corresponding to the target road segment, determining the actual speed limit values ​​marked by speed limit signs on adjacent road segments included in the target road segment; and updating the marked speed limit value to the actual speed limit value in response to a difference between the actual speed limit value and the marked speed limit value. According to this method, the actual speed limit value is determined, and the difference between the actual speed limit value and the marked speed limit value is confirmed, thereby updating the marked speed limit value in the road driving information. This avoids manually determining the actual speed limit value and the difference between the actual speed limit value and the marked speed limit value, thus improving the efficiency and accuracy of updating road driving information.

[0069] Referring to Figure 1, an embodiment of this application provides a flowchart of a method for updating road driving information, which specifically includes the following implementation steps:

[0070] S1, determine the target road segment and the road driving information for the target road segment.

[0071] Before updating road driving information, the cloud first needs to determine the target road segment, and then update the road driving information of the target road segment.

[0072] In this embodiment, the target road segment is not specifically limited. The target road segment may include all road segments in the target area; it may also include adjacent road segments where the change in the marked speed limit value exceeds a preset threshold; and it may also include road segments with abnormal road types. The following details the determination of the target road segment, which is not all road segments but includes the aforementioned adjacent road segments:

[0073] Step 101: In the high-precision map, determine the corresponding marked speed limit values ​​for each adjacent road segment.

[0074] In one possible implementation, when determining the marked speed limit value corresponding to each adjacent road segment, the road segment identifier corresponding to each adjacent road segment is first determined in the high-precision map; then, the marked speed limit value is determined based on the correspondence between the road segment identifier and the marked speed limit value.

[0075] In the embodiments of this application, the aforementioned road segment identifier can be a road segment identification code (ID); it can also be the latitude and longitude of the road segment; or it can be the coordinates of the road segment. However, regardless of whether the road segment identifier exists in the form of an ID, latitude and longitude, or coordinates, the road segment identifier corresponds one-to-one with the corresponding road segment and is therefore unique.

[0076] In the high-precision map, when determining the corresponding road segment identifiers for adjacent road segments, the adjacent road segments are determined first, and then the corresponding road segment identifiers for each adjacent road segment are determined.

[0077] When determining adjacent road segments, it can be based on the received road segment instructions, which indicate the target area; or it can be based on each adjacent road segment in a high-precision map.

[0078] Furthermore, since road segment identifiers are unique, when determining the aforementioned marked speed limits, one can directly query the marked speed limits corresponding to the road segment identifiers through the high-precision map provider.

[0079] It should be noted that each of the aforementioned adjacent road segments corresponds to a unique road segment identifier, and each road segment identifier corresponds to a marked speed limit value.

[0080] By using the above method, after determining the corresponding road segment identifiers of adjacent road segments in the high-precision map, the corresponding marked speed limit values ​​of adjacent road segments are determined based on the correspondence between the road segment identifiers and the marked speed limit values. Thus, based on the marked speed limit values, it can be determined whether adjacent road segments can be used as target road segments.

[0081] Step 102: Calculate the change between the marked speed limits of adjacent road segments.

[0082] In one possible implementation, when calculating the change value s between the marked speed limits of adjacent road segments, the change value s can be determined as a ratio, and the formula for calculating the change value s is as follows:

[0083]

[0084] Where A represents the maximum marked speed limit between adjacent road segments, and B represents the minimum marked speed limit between adjacent road segments.

[0085] In another possible implementation, when calculating the change value s' between the marked speed limit values ​​corresponding to each of the adjacent road segments, the change value s' can also be directly determined by the absolute value of the difference between the marked speed limit values ​​corresponding to each of the adjacent road segments.

[0086] Step 103: Determine whether the change value is greater than the preset threshold; if yes, proceed to step 104; if no, proceed to step 105.

[0087] When determining whether a change value exceeds a preset threshold, the preset threshold must first be determined. The preset threshold can vary depending on the road type and the method used to determine the change value. For example, when the road type is a ramp and the change value is determined using a ratio method, the preset threshold can be set to 20%.

[0088] In this application embodiment, the preset threshold can be adjusted according to the specific application scenario.

[0089] Step 104: Mark the adjacent road segment and the N road segments before and after the adjacent road segment as the target road segment.

[0090] When the change value exceeds a preset threshold, it indicates that the marked speed limit values ​​corresponding to the aforementioned adjacent road segments are abnormal. In this case, the adjacent road segment and the N road segments before and after it are marked as target road segments, where N is a natural number. This determines the road driving information for the target road segment, which includes the marked speed limit value and the corresponding road segment identifier. Preferably, N can be a positive integer, such as 1 or 2.

[0091] Furthermore, after determining the target road segment, first driving information can be generated, which includes the road segment identifier corresponding to the target road segment and the marked speed limit value corresponding to the target road segment.

[0092] In this embodiment of the application, the speed limit value corresponding to each road segment identifier in the first driving information needs to be determined to be correct.

[0093] Furthermore, since the road driving information for the target road segment also includes the corresponding road signs and speed limits, the first driving information actually includes the road driving information for the target road segment.

[0094] For example, the aforementioned first driving information exists in the form of a table. Such a first driving information table would at least include a road segment identifier and a marked speed limit. The road segment identifier is represented as an ID. The aforementioned first driving information table is shown in Table 1 below:

[0095] Table 1 First Driving Information Table

[0096]

[0097] The road segments with IDs 001 and 002 are adjacent road segments, which constitute the first target road segment. The road driving information for this first target road segment is that the marked speed limit for 001 is 120 km / h, and the marked speed limit for 002 is 80 km / h. The road segments with IDs 012 and 013 are another set of adjacent road segments, which constitute the second target road segment. The road driving information for this second target road segment is that the marked speed limit for 012 is 100 km / h, and the marked speed limit for 013 is 60 km / h.

[0098] Therefore, it can be seen that the above driving information table includes the road driving information of the first target road segment and the road driving information of the second target road segment. In other words, the first driving information includes the road driving information of the target road segment.

[0099] In this embodiment, the aforementioned first driving information includes, but is not limited to, storing the road driving information of the target road segment in the form of a table. For example, the road driving information of the target road segment can also be stored in the form of a graph. In this embodiment, the storage format can be adjusted according to the specific application scenario.

[0100] It should be noted that, in this embodiment of the application, the first driving information can be determined first, and then the target road segment can be determined according to each road segment identifier in the first driving information. Then, for each target road segment in the first driving information, steps S2 and S3 can be executed simultaneously. For example, in the driving information table shown in Table 1, there are two target road segments. For these two target road segments, steps S2 and S3 can be executed simultaneously.

[0101] Alternatively, after executing step 104 and determining the target road segment, steps S2 and S3 can be executed directly. That is, when executing steps 101, 102, 103, and 104 to determine a target road segment, steps S2 and S3 are executed once.

[0102] The above method generates first driving information containing the road segment identification and marked speed limit value corresponding to the target road segment. Based on this first driving information, the cloud can clearly identify the relevant information of each target road segment.

[0103] Step 105: Confirm that the speed limit values ​​marked on the adjacent road segments are normal.

[0104] By using the above method, after determining the marked speed limit values ​​corresponding to each adjacent road segment, the relationship between the calculated change value between the marked speed limit values ​​corresponding to each adjacent road segment and the preset threshold is determined. When the change value is greater than the preset threshold, the adjacent road segment is marked as the target road segment, thereby determining the target road segment and providing the target road segment that needs to be updated for subsequent updates of the marked speed limit values.

[0105] In another possible implementation, when determining the target road segment, the cloud directly obtains the first driving information from the high-precision map provider, and then determines the target road segment based on the road segment identifier in the first driving information. In this case, the high-precision map provider determines that there are adjacent road segments where the change in the marked speed limit value is greater than a preset threshold.

[0106] S2, based on the real-time video of the road conditions corresponding to the target road segment, determines the actual speed limit value marked by the speed limit signs of the adjacent road segments included in the target road segment.

[0107] Specifically, the system first sends a collection information to the vehicle, enabling it to collect real-time video of the target road segment; this collection information includes the road segment identifier corresponding to the target road segment.

[0108] When the aforementioned information is sent to a vehicle to collect real-time video of the target road segment, the information can be sent to the vehicle responsible for collecting the video of that segment.

[0109] Furthermore, vehicles whose routes include the target road segment can be identified first, and then the data collection information can be sent to those vehicles equipped with cameras. These vehicles can be any vehicle, not just the one responsible for collecting video footage of that segment. This allows each vehicle equipped with a camera to become a data source in the cloud, expanding the data source and enabling the collection of real-time road condition video of the target road segment in a shorter time. Moreover, compared to vehicles collecting real-time road condition video of each segment in a high-definition map and then uploading that video, in this application, the vehicle only needs to collect and upload the real-time road condition video of the target road segment, reducing vehicle bandwidth consumption.

[0110] Furthermore, after sending the collection information to the vehicle, the vehicle collects real-time video of the target road segment, and then the vehicle sends the real-time video of the road to the cloud.

[0111] Next, the cloud receives the real-time video of the road conditions sent by the vehicle.

[0112] After receiving the real-time road video, the cloud preprocesses the video to obtain an input sample that conforms to the input format of the target algorithm. This input sample is then fed into the target algorithm to output the actual speed limit value marked by the speed limit signs on adjacent road sections.

[0113] To ensure that the above-mentioned road condition video includes speed limit signs, when determining the target road segment in step S1, the cloud system marks the adjacent road segments and the N road segments before and after the adjacent road segments as the target road segments.

[0114] The above-mentioned preprocessing of road condition videos requires removing noise from the videos and performing preprocessing such as cutting, merging, and transformation to ensure that the processed input samples conform to the input format of the target algorithm.

[0115] Furthermore, the aforementioned target algorithm can be a deep learning algorithm based on neural networks, such as Convolutional Neural Networks (CNN) or Long Short-Term Memory (LSTM). In the embodiments of this application, the specific type of the target algorithm can be adjusted according to the specific application scenario.

[0116] Using the above method, based on the target algorithm, the real-time road condition video of the target road segment collected by the vehicle was processed, and the actual speed limit value corresponding to the adjacent road segments included in the target road segment was automatically output, avoiding the need for manual determination of the actual speed limit value, thereby further improving the update efficiency and accuracy of road driving information.

[0117] Furthermore, after outputting the actual speed limit value marked by the speed limit sign on the adjacent road segment, in order to ensure the accuracy of the actual speed limit value, the actual speed limit value marked by the speed limit sign in the road condition video can be checked to further confirm the actual speed limit value corresponding to each adjacent road segment.

[0118] S3, in response to the difference between the actual speed limit and the marked speed limit of the target road segment in the road driving information, updates the marked speed limit to the actual speed limit.

[0119] After determining the actual speed limit and the marked speed limit, it is then determined whether the actual speed limit and the marked speed limit are the same.

[0120] If the actual speed limit is different from the marked speed limit, the marked speed limit is determined to be incorrect, and the marked speed limit is updated to the actual speed limit.

[0121] In one possible implementation, when updating the marked speed limit to the actual speed limit, the road driving information of the target road segment is first deleted from the first driving information generated in step S1, that is, the road segment identifier and marked speed limit corresponding to the target road segment are deleted. Then, second driving information containing the road segment identifier and actual speed limit corresponding to the target road segment is generated, thereby achieving the purpose of updating the marked speed limit to the actual speed limit. This second driving information is also called functional information, indicating that the speed limit corresponding to each road segment identifier in this information is the updated actual speed limit.

[0122] Furthermore, since the marked speed limit value corresponding to each target road segment in the first driving information needs to be verified to be correct, the cloud stores the updated actual speed limit value through the newly generated second driving information, instead of directly replacing the marked speed limit value with the actual speed limit value in the first driving information. At the same time, the road segment identifier and marked speed limit value corresponding to the target road segment in the first driving information are deleted, avoiding sending the collection information of the target road segment to the vehicle after the marked speed limit value has been verified.

[0123] It should be noted that the second driving information mentioned above is the same as the first driving information in step S1. In this embodiment, it includes, but is not limited to, storing the road segment identifier and actual speed limit value corresponding to the target road segment in the form of a table. Similarly, it can also be stored in the form of a graph. In this embodiment, the storage format can be adjusted according to the specific application scenario.

[0124] If the actual speed limit is the same as the marked speed limit, then the marked speed limit is correct.

[0125] When the marked speed limit value is confirmed to be correct, the road driving information of the target road segment also needs to be deleted in the first driving information in step S1, that is, the road segment identifier and marked speed limit value corresponding to the target road segment need to be deleted, so as to avoid the cloud sending the collection information of the target road segment to the vehicle after verifying that the marked speed limit value is correct.

[0126] The scenarios where the actual speed limit is the same as the marked speed limit can be as follows:

[0127] The road condition video shows two speed limit signs on the target road segment, but the actual speed limits marked on these two signs are different. For example, the road segment marked 005 has one speed limit sign with an actual speed limit of 120 km / h; the road segment marked 006 also has one speed limit sign with an actual speed limit of 80 km / h. The road segments marked 005 and 006 are adjacent. Then, in the road driving information, the target road segment also has two marked speed limits: 120 km / h for road segment 005 and 80 km / h for road segment 006. The actual speed limit for road segment 005 is the same as the marked speed limit, and the actual speed limit for road segment 006 is also the same as the marked speed limit. Therefore, it can be confirmed that the actual speed limit matches the marked speed limit.

[0128] In one possible implementation, after updating the marked speed limit to the actual speed limit, the cloud can send a data packet containing the road segment identifier and the actual speed limit to the target vehicle according to the vehicle's needs, so that the target vehicle can drive on the target road segment according to the actual speed limit.

[0129] Specifically, the cloud can first send the updated information of the marked speed limit value corresponding to the target road segment to each vehicle, so that each vehicle can know that the marked speed limit value of the target road segment has been updated. Then, when the driving route of a target vehicle includes the target road segment, it can send a download request to the cloud in advance. The download request includes the road segment identifier corresponding to the target road segment.

[0130] Then, a download request is received from the target vehicle. Based on this download request, the road segment identifier and the actual speed limit value of the target road segment are encrypted into a data packet. This data packet is then sent to the target vehicle, for example, via Over-the-Air (OTA) technology.

[0131] When encrypting the road segment identifier and the actual speed limit value of the target road segment into a data packet, the data packet can be encrypted through an encrypted link or through an encryption algorithm. In this embodiment, the encryption method can be set according to the specific application scenario.

[0132] In this way, based on the download request received from the target vehicle, the cloud sends a data packet containing the road segment identifier and the actual speed limit value corresponding to the target road segment to the target vehicle. This allows the target vehicle to obtain the actual speed limit value before entering the target road segment, thereby enabling the target vehicle to drive on the target road segment according to the actual speed limit value. This avoids the safety problems that would occur if the target vehicle drove on the target road segment with the original marked speed limit value, thus further improving the safety of vehicle driving.

[0133] Furthermore, after receiving the data packet, the target vehicle can process the high-definition map data and the data in the aforementioned data packet based on the Electronic Horizon Provider (EHP) and Electronic Horizon Reconstructor (EHR), and then drive on the target road segment according to the actual speed limit. Alternatively, it can process the high-definition map data and the data in the aforementioned data packet based on the MAP Application Programming Interface (MAP-API), and then drive on the target road segment according to the actual speed limit.

[0134] Furthermore, it should be noted that in this embodiment, when determining the target road segment in step S1, if the target road segment includes a road segment with an abnormal road type, the steps for determining the target road segment by the cloud are as follows:

[0135] First, determine the type of road to be verified, for example, if the road type to be verified is a ramp.

[0136] Then, based on the preset mapping relationship between road type and road segment identifier, query the road segment identifiers corresponding to the road type to be verified.

[0137] It is worth noting that in the preset mapping relationship between the road types and road segment identifiers mentioned above, one road type can correspond to M road segment identifiers, where M is a non-negative integer; while one road segment identifier corresponds to only one road type.

[0138] In this embodiment of the application, when querying the road segment identifiers corresponding to the road type, the cloud can directly query the road segment identifiers corresponding to the road type through the high-precision map supplier.

[0139] Next, based on the high-precision map, the road marking type for each road segment will be determined.

[0140] Furthermore, for each road marking type, the following judgment operation is performed:

[0141] Determine whether the road marking type is the same as the road type.

[0142] If they are the same, the road marking type is correct. If they are different, the road marking type is abnormal, and the road segment corresponding to that road marking type is marked as the target road segment.

[0143] Once the above judgment operation has been performed for each road mark type, the target road segment can be determined. The target road segment contains K road segments, where K is a non-negative integer.

[0144] Using the above method, based on the preset mapping relationship between road types and road segment identifiers, the road segment identifiers corresponding to the road type to be verified were determined. Simultaneously, based on a high-precision map, the road marker type for each road segment identifier was determined. Then, based on the judgment result of whether the road marker type is the same as the road type to be verified, it was determined whether the road marker type was incorrect; subsequently, the incorrect road marker type was marked as the target road segment, thus identifying the target road segment.

[0145] Furthermore, after determining the target road segment, each road marking type in the road driving information of the target road segment is updated to the road type to be verified mentioned above.

[0146] By updating each erroneous road marking type to the road type to be verified in the above manner, safety accidents caused by incorrect road type are avoided, thereby improving the safety of vehicle driving.

[0147] In one possible implementation, since the first driving information includes road driving information, it also includes the road marking type of the target road segment. In this case, when updating each road marking type to the road type to be verified, the process is consistent with updating the marked speed limit value to the actual speed limit value. First, the road driving information of the target road segment is deleted from the first driving information; that is, the road marking type and the road segment identifier corresponding to the target road segment are deleted.

[0148] Then, add the road driving information of the target road segment to the second driving information, that is, add the road segment identifier and road type corresponding to the target road segment to the second driving information.

[0149] For example, the aforementioned second driving information exists in the form of a table, which includes road segment identification, speed limit, and road type. The road segment identification is represented by an ID. The aforementioned first driving information table is shown in Table 2 below:

[0150] Table 2 Second Driving Information Table

[0151]

[0152]

[0153] The road segments corresponding to IDs 007 and 008 are adjacent road segments, which is the third target road segment. This third target road segment is an adjacent road segment where the change in the marked speed limit value exceeds a preset threshold. After executing steps S1, S2, and S3, it is determined that the marked speed limit value of 120 km / h corresponding to 007 is incorrect. Therefore, the speed limit value corresponding to 007 is set to the actual speed limit value of 80 km / h in the second driving information table.

[0154] The road segment with ID 021 is the fourth target road segment. This fourth target road segment has an abnormal road type. In the high-precision map, the road segment corresponding to 021 is displayed as a main road, while the road type to be verified is a ramp. After querying the road segment identifiers corresponding to the ramps through the high-precision map provider, it was determined that the road segment identifiers corresponding to the ramps include ID 021. At this time, the road marker type corresponding to the road segment with ID 021 is inconsistent with the road type to be verified. Therefore, this road segment is marked as the fourth target road segment, and the road type corresponding to 021 is set to ramp in the second driving information table.

[0155] In one possible implementation, after the cloud adds the road segment identifier and road type corresponding to the target road segment to the second driving information, it can also send updated information containing the updated road marking type to each vehicle. Then, upon receiving a vehicle's download request, the cloud sends the encrypted road segment identifier and road type corresponding to the target road segment to that vehicle, ensuring the vehicle clearly understands the correct road marking type and avoids safety accidents. Alternatively, the update information can be sent to the high-precision map provider so that the provider can understand any errors in the high-precision map.

[0156] In summary, the road driving information updating method proposed in this application first determines the target road segment and its road driving information, including the marked speed limit value of the target road segment, in the cloud. Based on the real-time road video corresponding to the target road segment, it determines the actual speed limit values ​​marked by speed limit signs on adjacent road segments included in the target road segment. In response to a difference between the actual speed limit value and the marked speed limit value, the marked speed limit value is updated to the actual speed limit value. According to this method, the actual speed limit value is determined, and the difference between the actual speed limit value and the marked speed limit value is confirmed, thereby updating the marked speed limit value in the road driving information. This avoids the need for manual determination of the actual speed limit value and the need to manually determine the difference between the actual speed limit value and the marked speed limit value, thus improving the efficiency and accuracy of road driving information updates.

[0157] Furthermore, when receiving live road video, the cloud can send collection information to vehicles equipped with cameras whose routes include the target road segment, enabling those vehicles to collect live road video of the target segment. This allows each vehicle equipped with a camera to become a data source for the cloud, expanding the data source and enabling the collection of live road video of the target segment in a shorter time. Simultaneously, compared to vehicles collecting live road video of each segment in a high-precision map and then uploading that video, in this application, vehicles only need to collect live road video of the target segment and upload that video, reducing vehicle bandwidth consumption.

[0158] In addition, the cloud-based algorithm processes the real-time road condition video of the target road segment collected by the vehicle and automatically outputs the actual speed limit value marked by the speed limit sign on the target road segment, avoiding the need for manual determination of the actual speed limit value, thereby further improving the efficiency and accuracy of updating road driving information.

[0159] The technical solution of this application will be further explained below with reference to a specific application process.

[0160] Figure 2 illustrates the processing steps of the road driving information update method. First, the target road segment is determined. This target road segment may include adjacent road segments where the change in the marked speed limit value is greater than a preset threshold; it may also include road segments with abnormal road types.

[0161] When a target road segment includes adjacent road segments whose marked speed limit values ​​change more than a preset threshold, the abnormal speed limit segment determination module reads the corresponding road segment identifiers from the high-precision map and sends these identifiers to the high-precision map provider to obtain the marked speed limit values ​​corresponding to those identifiers. Then, it calculates the change between the marked speed limit values ​​of the adjacent road segments. If the change exceeds a preset threshold, the adjacent road segment is determined to be abnormal, and the adjacent road segment and the N road segments before and after it are marked as target road segments, where N is a natural number. Simultaneously, a first driving information table containing the road driving information of the target road segment is generated; this driving information includes the road segment identifier and marked speed limit value of the target road segment. This first driving information table is then sent to the trigger acquisition module.

[0162] In the trigger acquisition module, based on the road driving information of the target road segment received from the first driving information table, the vehicle whose driving route includes the target road segment is determined. Then, acquisition information is sent to the vehicle, enabling the vehicle to acquire real-time video of the target road segment based on the acquisition information; the acquisition information includes the road segment identifier corresponding to the target road segment, and the vehicle can be any vehicle equipped with a camera whose driving route includes the target road segment.

[0163] The video processing module receives real-time road condition video captured by vehicles. The processed video is then input into the target algorithm, which outputs the actual speed limit value marked by the speed limit sign on the target road segment, thereby determining the actual speed limit value corresponding to each adjacent road segment. This actual speed limit value is then sent to the anomaly detection module.

[0164] In the anomaly detection module, the actual speed limit value is received, and the marked speed limit value corresponding to the target road segment in the first driving information is read from the speed limit anomaly road segment determination module; it is determined whether the actual speed limit value and the marked speed limit value are the same; if they are not the same, the road segment identifier corresponding to the target road segment and the actual speed limit value are sent to the update module.

[0165] In the update module, the road segment identifier and actual speed limit value corresponding to the target road segment are added to the second driving information table. It also receives a download request from the target vehicle, encrypts the road segment identifier and actual speed limit value of the target road segment in the second driving information table, and sends it to the target vehicle so that the target vehicle can drive on the target road segment according to the actual speed limit value; the download request includes the road segment identifier corresponding to the target road segment.

[0166] When the target road segment includes road segments with abnormal road types, the abnormal road segment identification module first sends the road type to be verified to the high-precision map provider to obtain the segment identifiers corresponding to the road type to be verified. Then, it reads the road marker type of each segment identifier on the high-precision map. Next, it determines whether the road marker type is the same as the road type to be verified. If they are different, the road segment corresponding to that road marker type is identified as the target road segment. Finally, the segment identifier and road type corresponding to the target road segment are sent to the update module.

[0167] In the second driving information table of the update module, add the road segment identifier and road type corresponding to the target road segment. Then, receive the download request from the target vehicle, encrypt the road segment identifier and road type corresponding to the target road segment in the second driving information table, and send it to the target vehicle so that the target vehicle can clearly understand the road type of the target road segment.

[0168] In this way, the cloud-based anomaly detection module, based on the actual speed limit value received from the video processing module and the marked speed limit value corresponding to the target road segment in the abnormal speed limit segment determination module, determines whether the actual speed limit value and the marked speed limit value are consistent. If they are consistent, the marked speed limit value is updated to the actual speed limit value. This method determines the actual speed limit value and identifies discrepancies between the actual and marked speed limits, thereby updating the marked speed limit value in the driving information. This avoids manually determining the actual speed limit value and the discrepancy between the actual and marked speed limits, thus improving the efficiency and accuracy of driving information updates.

[0169] Furthermore, the trigger acquisition module can send acquisition information to vehicles equipped with cameras whose routes include the target road segment, enabling those vehicles to acquire real-time video of the target road segment. This allows each vehicle equipped with a camera to become a data source in the cloud, expanding the data source and enabling the acquisition of real-time video of the target road segment in a shorter time. Simultaneously, compared to vehicles acquiring real-time video of each road segment in a high-precision map and then uploading that video, in this application, vehicles only need to acquire and upload the real-time video of the target road segment, reducing vehicle bandwidth consumption.

[0170] In addition, in the video processing module, based on the target algorithm, the real-time road condition video of the target road segment collected by the vehicle is processed, and the actual speed limit value marked by the speed limit sign on the target road segment is automatically output, avoiding the need for manual determination of the actual speed limit value, thereby further improving the update efficiency and accuracy of road driving information.

[0171] Based on the same inventive concept, this application also provides a road driving information updating device. Figure 3 shows a schematic diagram of the structure of a road driving information updating device provided in this application. The device includes:

[0172] The first determining module 301 is used to determine the target road segment and the road driving information of the target road segment; wherein, the road driving information includes the marked speed limit value of the target road segment;

[0173] The second determining module 302 is used to determine the actual speed limit value marked by the speed limit signs of the adjacent road sections included in the target road section based on the real-time video of the road conditions corresponding to the target road section.

[0174] The processing module 303 is used to update the marked speed limit to the actual speed limit in response to a difference between the actual speed limit and the marked speed limit.

[0175] The first determining module 301 is specifically used to determine the marked speed limit value corresponding to each adjacent road segment in the high-precision map; calculate the change value between the marked speed limit values ​​corresponding to each adjacent road segment; determine whether the change value is greater than a preset threshold; if so, mark the adjacent road segment and the N road segments before and after the adjacent road segment as the target road segment; where N is a natural number.

[0176] The first determining module 301 is also used to determine the corresponding road segment identifiers of adjacent road segments in the high-precision map; and to determine the marked speed limit value based on the correspondence between the road segment identifier and the marked speed limit value.

[0177] The second determining module 302 is specifically used to send collection information to the vehicle, enabling the vehicle to collect real-time video of the road conditions corresponding to the target road segment; wherein, the collection information includes the road segment identifier corresponding to the target road segment; receive the real-time video of the road conditions; input the real-time video of the road conditions into the target algorithm to determine the actual speed limit value marked by the speed limit signs of the adjacent road segments included in the target road segment.

[0178] The first determining module 301 is also used to generate first driving information; wherein the first driving information includes the road segment identifier and marked speed limit value corresponding to the target road segment; then the processing module 303 is specifically used to delete the road segment identifier and marked speed limit value corresponding to the target road segment from the first driving information; and generate second driving information including the road segment identifier and actual speed limit value corresponding to the target road segment.

[0179] The processing module 303 is specifically used to receive a download request sent by the target vehicle; wherein the download request includes the road segment identifier corresponding to the target road segment; based on the download request, the road segment identifier corresponding to the target road segment and the actual speed limit value are encrypted into a data packet and sent to the target vehicle.

[0180] The aforementioned target road segment includes road segments with abnormal road types; then the first determining module 301 is further used to query each road segment identifier corresponding to the road type to be verified based on the preset mapping relationship between road type and road segment identifier; determine the road mark type of each road segment identifier based on the high-precision map; and mark the road segment corresponding to the road mark type that is inconsistent with the road type as the target road segment.

[0181] The road information updating device also includes a type module, which is specifically used to update the road marking type to the road type in the road driving information of the target road segment.

[0182] Based on the same inventive concept, this application also provides an electronic device that can realize the function of the aforementioned road driving information updating device. Referring to FIG4, the electronic device includes:

[0183] At least one processor 401 and a memory 402 connected to at least one processor 401 are included. In this embodiment, the specific connection medium between the processor 401 and the memory 402 is not limited. Figure 4 illustrates an example where the processor 401 and the memory 402 are connected via a bus 400. The bus 400 is represented by a thick line in Figure 4. The connection methods between other components are for illustrative purposes only and are not intended to be limiting. The bus 400 can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in Figure 4, but this does not indicate that there is only one bus or one type of bus. Alternatively, the processor 401 can also be called a controller; the name is not limited.

[0184] In this embodiment, the memory 402 stores instructions executable by at least one processor 401. By executing the instructions stored in the memory 402, the at least one processor 401 can perform the road driving information update method described above. The processor 401 can implement the functions of each module in the device shown in FIG3.

[0185] The processor 401 is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory 402 and calling data stored in memory 402, the processor can perform various functions and process data, thereby monitoring the device as a whole.

[0186] In one possible design, processor 401 may include one or more processing units. Processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 401. In some embodiments, processor 401 and memory 402 may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0187] Processor 401 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the road driving information update method disclosed in the embodiments of this application can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0188] Memory 402, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 402 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage, magnetic disk, optical disk, etc. Memory 402 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, memory 402 can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0189] By designing and programming the processor 401, the code corresponding to the road driving information update method described in the foregoing embodiments can be embedded into the chip, thereby enabling the chip to execute the steps of the road driving information update method of the embodiment shown in FIG1 during operation. How to design and program the processor 401 is a technique known to those skilled in the art, and will not be described in detail here.

[0190] Based on the same inventive concept, embodiments of this application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the road driving information update method described above.

[0191] In some possible implementations, various aspects of the road driving information updating method provided in this application can also be implemented in the form of a program product, which includes program code that, when the program product is run on a device, causes the control device to perform the steps in the road driving information updating method according to the various exemplary embodiments of this application described above.

[0192] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0193] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.

[0194] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0195] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0196] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for updating road driving information, characterized in that, include: The method involves identifying a target road segment and its road driving information, including the marked speed limit value of the target road segment. Identifying the target road segment includes: determining the marked speed limit value corresponding to each adjacent road segment in a high-precision map; calculating the change value between the marked speed limits of each adjacent road segment; determining whether the change value is greater than a preset threshold; if so, marking the adjacent road segment and the N road segments before and after it as the target road segment; where N is a natural number; the change value is the ratio of the difference between the maximum and minimum marked speed limits of each adjacent road segment to the maximum marked speed limit value; or, the change value is a value determined based on the absolute difference between the marked speed limits of each adjacent road segment; determining the actual speed limit value marked by the speed limit signs of the adjacent road segments included in the target road segment based on the real-time road video corresponding to the target road segment; and updating the marked speed limit value of the target road segment to the actual speed limit value in response to a difference between the actual speed limit value and the marked speed limit value of the target road segment.

2. The method as described in claim 1, characterized in that, The step of determining the marked speed limit value corresponding to each adjacent road segment in the high-precision map includes: determining the road segment identifier corresponding to each adjacent road segment in the high-precision map; and determining the marked speed limit value corresponding to each adjacent road segment based on the correspondence between the road segment identifier and the marked speed limit value.

3. The method according to any one of claims 1-2, characterized in that, The step of determining the actual speed limit value marked by the speed limit signs on the adjacent road segments included in the target road segment based on the real-time road video corresponding to the target road segment includes: sending collection information to the vehicle to collect the real-time road video corresponding to the target road segment; wherein, the collection information includes the road segment identifier corresponding to the target road segment; receiving the real-time road video; and inputting the real-time road video into a target algorithm to determine the actual speed limit value marked by the speed limit signs on the adjacent road segments included in the target road segment.

4. The method as described in claim 1, characterized in that, After determining the target road segment and the road driving information of the target road segment, the method further includes: generating first driving information; wherein the first driving information includes the road segment identifier and marked speed limit value corresponding to the target road segment; then updating the marked speed limit value of the target road segment to the actual speed limit value includes: deleting the road segment identifier and marked speed limit value corresponding to the target road segment from the first driving information; and generating second driving information including the road segment identifier corresponding to the target road segment and the actual speed limit value.

5. The method according to any one of claims 1-2, 4, characterized in that, The target road segment includes road segments with abnormal road types; therefore, determining the target road segment includes: querying each road segment identifier corresponding to the road type to be verified based on a preset mapping relationship between road types and road segment identifiers; determining the road mark type of each road segment identifier based on a high-precision map, and marking the road segment corresponding to the road mark type that is inconsistent with the road type as the target road segment.

6. The method as described in claim 5, characterized in that, After marking the road segment corresponding to the road mark type that is inconsistent with the road type as the target road segment, the method further includes: updating the road mark type to the road type in the road driving information of the target road segment.

7. A road driving information updating device, characterized in that, include: The first determining module is used to determine a target road segment and road driving information of the target road segment; wherein, the road driving information includes the marked speed limit value of the target road segment; determining the target road segment includes: determining the marked speed limit value corresponding to each of adjacent road segments in a high-precision map; calculating the change value between the marked speed limit values ​​corresponding to each of the adjacent road segments; determining whether the change value is greater than a preset threshold; if so, marking the adjacent road segment and the N road segments before and after the adjacent road segment as the target road segment; wherein, N is a natural number; the change value is the speed limit value corresponding to each of the adjacent road segments. The difference between the maximum and minimum marked speed limits is the ratio of the difference to the maximum marked speed limit; or, the change value is a value determined based on the absolute difference between the marked speed limits corresponding to each of the adjacent road segments; the second determining module is used to determine the actual speed limit value marked by the speed limit signs of the adjacent road segments included in the target road segment based on the real-time road video corresponding to the target road segment; the processing module is used to update the marked speed limit value of the target road segment to the actual speed limit value in response to the difference between the actual speed limit value and the marked speed limit value of the target road segment.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, when executing a computer program stored in the memory, implements the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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