Method, apparatus, and system for providing driving reference information

Abstract

An embodiment of this specification discloses a method, apparatus, and system for providing driving reference information. The solution may include: a data processing platform obtains dynamic traffic information, where the dynamic traffic information refers to traffic-related information that changes with at least one of time or space; according to the geographical location corresponding to the dynamic traffic information, the dynamic traffic information is matched to the latest version of the full-scale map data to obtain a second matching and fusion result; according to the difference result between the first matching and fusion result and the second matching and fusion result, driving reference information is obtained, where the first matching and fusion result is the result of the previous dynamic traffic information being matched with the previous full-scale map data; the driving reference information is sent to the vehicle terminal. Based on this solution, the process of matching and fusing information to obtain driving reference information is transferred to the cloud, which can reduce the computing power burden on the vehicle side.

Description

Technical Field

[0001] This application relates to the technical field of map navigation, and particularly to a method, device, and system for providing driving reference information. Background Art

[0002] With the continuous improvement of map navigation functions, especially the gradual implementation of autonomous driving functions, more input information is needed to support driving navigation. It is necessary to match and integrate various dynamic intelligence information into the static map to obtain information for driving navigation.

[0003] Currently, the process of information matching and integration is mostly carried out on the vehicle side, resulting in a heavy computing power burden on the vehicle side. Summary of the Invention

[0004] Embodiments of this specification provide a method, device, and system for providing driving reference information to solve the problem of heavy computing power burden on the vehicle side in the existing method for determining driving reference information.

[0005] To solve the above technical problems, the embodiments of this specification are implemented as follows:

[0006] A method for providing driving reference information provided by the embodiments of this specification is applied to a data processing platform, and the method includes:

[0007] Obtain dynamic traffic information; the dynamic traffic information refers to traffic-related information that changes with at least one of time or space;

[0008] According to the geographical location corresponding to the dynamic traffic information, match the dynamic traffic information to the latest version of the full-scale map data to obtain a second matching and integration result;

[0009] Obtain driving reference information according to the differential result between the first matching and integration result and the second matching and integration result; wherein, the first matching and integration result is the result of matching the previous dynamic traffic information with the previous full-scale map data;

[0010] Send the driving reference information to the vehicle terminal.

[0011] A device for providing driving reference information provided by the embodiments of this specification is applied to a data processing platform, and includes:

[0012] An information acquisition module, configured to obtain dynamic traffic information; the dynamic traffic information refers to traffic-related information that changes with at least one of time or space;

[0013] A matching and integration module, configured to match the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and integration result;

[0014] A difference module, configured to obtain driving reference information according to the difference result between the first matching and fusion result and the second matching and fusion result; wherein, the first matching and fusion result is the result of matching the previous dynamic traffic information with the previous full - scale map data;

[0015] An information sending module, configured to send the driving reference information to a vehicle terminal.

[0016] A driving reference information providing system provided by an embodiment of this specification, characterized by including a big data platform, a cloud data processing platform, and a vehicle terminal;

[0017] The big data platform is configured to determine dynamic traffic information;

[0018] The cloud data processing platform is configured to obtain dynamic traffic information from the big data platform, where the dynamic traffic information refers to traffic - related information that changes with at least one of time or space; to match the dynamic traffic information to the latest version of the full - scale map data according to the geographical location corresponding to the dynamic traffic information, obtain a second matching and fusion result, and obtain driving reference information according to the difference result between the first matching and fusion result and the second matching and fusion result, where the first matching and fusion result is the result of matching the previous dynamic traffic information with the previous full - scale map data; and to send the driving reference information to the vehicle terminal;

[0019] The vehicle terminal is configured to obtain driving reference information from the cloud data processing platform.

[0020] An embodiment of this specification can at least achieve the following beneficial effects: After obtaining dynamic traffic information in the cloud data processing platform, match the dynamic traffic information to the map data, fuse each dynamic traffic information to obtain a second matching and fusion result, then take the difference between the second matching and fusion result and the previously obtained first matching and fusion result to obtain driving reference information for driving assistance, and then send it to the vehicle terminal. Based on this solution, information matching and fusion operations are performed in the cloud, and the driving reference information for driving assistance is sent to the vehicle end for use, which can reduce the computing power burden of the vehicle end, and the information range fused in the cloud is wider, which can better assist driving. Description of the Drawings

[0021] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 A schematic diagram of an application scenario of a method for providing driving reference information in an embodiment of this specification;

[0023] Figure 2 A flowchart of a method for providing driving reference information provided in an embodiment of this specification;

[0024] Figure 3 A schematic diagram of a method for determining a differential data packet applied to a data processing platform provided in an embodiment of this specification;

[0025] Figure 4 A schematic diagram of a method for determining the latest full - volume data based on a differential data packet applied to a vehicle terminal provided in an embodiment of this specification;

[0026] Figure 5 Corresponding to Figure 2 A schematic diagram of the structure of a driving reference information providing device provided in an embodiment of this specification;

[0027] Figure 6 A schematic diagram of the structure of a driving reference information providing system provided in an embodiment of this specification. Detailed implementation manners

[0028] To make the objectives, technical solutions, and advantages of one or more embodiments of this specification clearer, the technical solutions of one or more embodiments of this specification will be clearly and completely described below in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope protected by one or more embodiments of this specification.

[0029] It should be understood that although terms such as first, second, and third may be used in this application document to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other.

[0030] The following will detail the technical solutions provided in each embodiment of this specification in conjunction with the drawings.

[0031] With the continuous improvement of the map navigation function, especially the gradual implementation of the autonomous driving function, more input information is needed to support driving navigation. It is necessary to integrate various dynamic intelligence information (for example, road friction coefficient, current weather conditions, traffic light information, certain high - precision event information, etc.) into the static map to obtain information for driving navigation.

[0032] In the prior art, the process of information fusion is mostly carried out on the vehicle side, which places a heavy computing burden on the vehicle side. Moreover, the range of data that the vehicle side can fuse by itself is limited.

[0033] In the embodiments of this specification, all functional operations for fusing information are completed in the cloud, which can reduce the computing burden on the vehicle side. Moreover, fusing in the cloud enables a wide range of fused data, which can provide real-time data for the vehicle side over a longer range, so as to better achieve driving navigation.

[0034] Figure 1 It is a schematic diagram of the application scenario of a method for providing driving reference information in the embodiments of this specification.

[0035] As Figure 1 shown, first, the data processing platform located in the cloud can obtain dynamic traffic information from the big data platform. Then, the data processing platform can calculate the driving reference information for vehicle navigation based on the dynamic traffic information. After that, the data processing platform can send the driving reference information to the vehicle terminal.

[0036] It can be understood that Figure 1 the data processing platform shown in Figure 1 can be any device, equipment, platform, device cluster, etc. with computing and processing capabilities. Although

[0037] Figure 2 It is a schematic flowchart of a method for providing driving reference information provided in the embodiments of this specification.

[0038] From a program perspective, the execution subject of the process can be a program running on an application server. In actual application, the execution subject of the process can be a data processing platform, which is used to process dynamic data to obtain information for assisting navigation.

[0039] As Figure 2 shown, the process can include the following steps:

[0040] Step 202: Obtain dynamic traffic information.

[0041] Among them, the dynamic traffic information can specifically refer to traffic-related information that changes with at least one of time or space, or in other words, information that may affect traffic and changes with at least one of time or space.

[0042] Specifically, the dynamic traffic information can include traffic light information, traffic flow information, traffic event information, dynamic speed limit information, traffic restriction information, real-time weather information, road friction coefficient, autonomous driving permission information, parking lot information, etc.

[0043] In actual application, the data processing platform can obtain real-time dynamic traffic information from the big data platform. The big data platform can store various real-time dynamic traffic information obtained from data collection devices or other data management platforms or systems. For example, the big data platform can store traffic light information, traffic flow information, traffic event information, dynamic speed limit information, traffic restriction information, etc. obtained from the real-time traffic information management platform, and real-time weather information obtained from the real-time weather information management system. The information in the big data platform can be updated in real time. For example, it can be reported in real time by various data collection devices.

[0044] Among them, the data in the big data platform can be information corresponding to a relatively large spatial range, where the relatively large spatial range can be relative to the relatively small spatial range to which the data directly accessible by the vehicle terminal through its own network belongs. For example, the relatively large spatial range can be the range of a district administrative region, a city administrative region, a provincial administrative region, a national administrative region, etc., while the relatively small spatial range can be the range of several square kilometers around the vehicle terminal. It can be understood that since the data processing platform obtains the dynamic traffic information corresponding to the relatively large spatial range from the big data platform, the subsequent processed driving reference information has a wider fusion range, and thus can provide real-time data for the vehicle end within a farther range.

[0045] In actual application, the data processing platform can regularly obtain dynamic traffic information from the big data platform. For example, it can obtain dynamic traffic information from the big data platform according to a preset frequency (such as every 1 minute, every 2 minutes, etc.). Thus, it can ensure that the data in the data processing platform is real-time.

[0046] Step 204: According to the geographical location corresponding to the dynamic traffic information, match the dynamic traffic information to the latest version of the full-scale map data to obtain a second matching and fusion result.

[0047] Specifically, the cloud data processing platform can first match the dynamic traffic information to the map data according to the geographical location corresponding to the dynamic traffic information; then, according to the matching result with the map data, fuse each piece of dynamic traffic information to obtain a matching and fusion result. In the embodiments of this specification, the matching and fusion result obtained by currently executing Step 204 is called the second matching and fusion result in order to distinguish it from the first matching and fusion result mentioned below. In the embodiments of this specification, terms such as "first" and "second" are only used to distinguish multiple pieces of information of the same type from each other and do not constitute a limitation on these information.

[0048] Step 206: Obtain driving reference information based on the differential result between the first matching fusion result and the second matching fusion result; wherein, the first matching fusion result is the result of matching the previous dynamic traffic information with the previous full-scale map data.

[0049] Among them, the latest version of the full-scale map data in step 204 may be the same as or different from the previous full-scale map data. Optionally, considering that the frequency of map data update is much lower than the frequency of the cloud updating the matching fusion information and the frequency of the vehicle terminal obtaining driving reference information from the cloud during the automatic driving process, generally, the latest version of the full-scale map data may be the same as the previous full-scale map data.

[0050] The dynamic traffic information in step 204 is the current dynamic traffic information, and the current dynamic traffic information may be the same as or different from the previous dynamic traffic information. Optionally, considering that the dynamic traffic information obtained by the cloud data processing platform is collected in real time by the big data platform, and since information such as real-time traffic information, real-time weather conditions, road friction coefficient, and traffic light services changes in real time, in most cases, the current dynamic traffic information may be different from the previous dynamic traffic information.

[0051] In view of this, in the embodiments of this specification, the second matching fusion result may be the same as or different from the first matching fusion result. And in practical applications, in most cases, the first matching fusion result may be different from the second matching fusion result.

[0052] In practical applications, to reduce the data transmission volume between the vehicle terminal and the cloud, the method of sending differential data can be adopted, that is, instead of sending the full-scale result of the matching fusion each time, the current matching fusion result is differentially compared with the previous matching fusion result each time, and the different matching fusion information is saved as the difference packet between the current data and the previous data. In addition, the versions of the full-scale data and the difference packet data can be marked, and the data version is iteratively incremented as the cloud data is updated.

[0053] Step 208: Send the driving reference information to the vehicle terminal.

[0054] Specifically, the data processing platform can regularly perform data acquisition and matching fusion processing to obtain driving reference information, and can regularly send the updated data to the vehicle terminal or send the updated data to the vehicle terminal in response to the request of the vehicle terminal.

[0055] It should be understood that in the method described in one or more embodiments of this specification, the order of some steps can be adjusted according to actual needs, or some steps can be omitted.

[0056] Figure 2 In the method, after obtaining dynamic traffic information in the data processing platform in the cloud, the dynamic traffic information is matched to the map data and each piece of dynamic traffic information is fused to obtain a second matching and fusion result. Then, the second matching and fusion result is differentiated from the previously obtained first matching and fusion result to obtain driving reference information that can be used for driving assistance, and then sent to the vehicle terminal. Based on this solution, information matching and fusion operations are performed in the cloud, and the driving reference information for driving assistance is sent to the vehicle side for use, which can reduce the computing power burden on the vehicle side, and the information range fused in the cloud is wider, which can better assist driving.

[0057] Based on Figure 2 the method, the embodiments of this specification also provide some specific implementation manners of this method, which will be described below.

[0058] In the embodiments of this specification, in step 206, according to the difference result between the first matching and fusion result and the second matching and fusion result, driving reference information is obtained, which may specifically include: performing a difference calculation on the first matching and fusion result and the second matching and fusion result to obtain a difference data packet; storing the difference data packet and the second matching and fusion result; marking the version of the difference data packet and the version of the second matching and fusion result, the version of the difference data packet is consistent with the version of the first matching and fusion result, and the version of the second matching and fusion result is the next version of the first matching and fusion result. For example, if the version of the first matching and fusion result is denoted as m, the version of the second matching and fusion result may be denoted as m + 1, and the version of the difference data packet obtained based on the second matching and fusion result and the first matching and fusion result may be denoted as m.

[0059] For ease of understanding, Figure 3 shows the method for determining a difference data packet applied to the data processing platform in the embodiments of this specification.

[0060] As Figure 3 , the previous full amount of data (version m) is stored in the data processing platform, and the latest full amount of data (version m + 1) obtained according to the method of the embodiments of this specification, and then differential comparison can be performed to obtain differential data (version m). In the Figure 3 and Figure 4 , the full amount of data corresponds to the differential data, and the full amount of data specifically refers to the full amount of matching and fusion result data.

[0061] In Figure 3Among them, different pattern filling conditions are used to represent different dynamic traffic conditions. For example, when the dynamic traffic information is traffic flow information, blank can represent smooth traffic (such as road numbers 1, 2, and 6 in the m+1 version), sparse dots can represent slightly congested traffic (such as road numbers 3 and 4 in the m+1 version), dense dots can represent severely congested traffic (such as road number 5 in the m+1 version), etc. As Figure 3 , for the data with changed dynamic traffic conditions, differential data can be obtained and used for subsequent distribution to the vehicle terminal.

[0062] In the embodiments of this specification, the vehicle terminal can obtain updated driving reference information from the cloud regularly or at intervals of a certain driving distance. When the vehicle terminal requests data, it can upload the version number of its cached data. If the version of the cached data uploaded by the terminal is consistent with the version of the differential packet data, the differential packet is distributed; otherwise, the full amount of data or an empty data packet can be distributed.

[0063] Specifically, corresponding to the specific implementation manner of the foregoing step 206, when it is actually used, in step 208, sending the driving reference information to the vehicle terminal may specifically include: receiving a data acquisition request sent by the vehicle terminal, where the data acquisition request carries the version number of the cached data of the third matching and fusion result currently cached by the vehicle terminal; and determining whether the version number of the cached data is consistent with the version of the differential data packet or the version of the second matching and fusion result, to obtain a version determination result. Optionally, if the version determination result indicates that the version number of the cached data is consistent with the version of the differential data packet, the differential data packet is sent to the vehicle terminal as the driving reference information. Optionally, if the version determination result indicates that the version number of the cached data is consistent with the version of the second matching and fusion result, an empty data packet is sent to the vehicle terminal as the driving reference information. Optionally, if the version determination result indicates that the version number of the cached data is inconsistent with the version of the differential data packet and is inconsistent with the version of the second matching and fusion result, the second matching and fusion result is sent to the vehicle terminal as the driving reference information.

[0064] For example, assume that the differential package of version 1 and the full data of version 2 are stored in the cloud. If the version of the cached data on the vehicle side is version 1, the differential package of version 1 is sent down so that the vehicle side can obtain the second matching and fusing result of version 2 based on the third matching and fusing result of version 1 (which is actually the first matching and fusing result of version 1 sent by the cloud previously) and the differential package of version 1 obtained this time, and then store it. If the version of the cached data on the vehicle side is version 2, it means that the data on the vehicle side is as new as that on the cloud side and there is no need to update. The cloud can return an empty differential package to the vehicle side. If the version of the cached data is not version 1 or 2, for example, it may be version 0 or an earlier version, at this time, the cloud can send down the full data, that is, send down the second matching and fusing result of version 2.

[0065] For ease of understanding, a method for determining the latest full data based on differential data packets applied to the vehicle side is provided as Figure 4 follows.

[0066] As Figure 4 shown, the previous full data (version m) is stored locally on the vehicle side (this full data can be processed from differential data packets locally on the vehicle side previously or can be directly obtained from the cloud), and the vehicle side can obtain the latest differential data (version m) from the cloud. Thus, based on the previous full data (version m) and the latest differential data (version m) obtained this time, the latest full data (version m + 1) can be obtained for providing navigation for vehicle driving.

[0067] Based on the foregoing solution of the embodiments of this specification, in actual application, since the update frequency of the vehicle side is usually greater than or equal to that of the server side, thus, when the network communication is normal, only the full data packet needs to be sent down at the first request, and in most cases, only the differential data packet can be sent down, which can greatly reduce the network consumption.

[0068] In the embodiments of this specification, as Figure 2 shown, the dynamic traffic information obtained in step 202 all carries location information, which is used to represent the location where the dynamic traffic information belongs. More specifically, it can be used to represent map objects such as roads, lanes, and parking lots where the dynamic traffic information belongs.

[0069] In some embodiments, the geographical location information corresponding to the dynamic traffic information may include spatial attribution information, which may directly indicate the map object to which the dynamic traffic information belongs. As an example, the geographical location corresponding to traffic light information, traffic flow information, traffic event information, dynamic speed limit information, road friction coefficient, parking lot information, etc. may include spatial attribution information (e.g., Road 033, City A, Lane 01, Road 033, City A, Parking Lot 35, City A, etc.), which is used to indicate the map object to which the dynamic traffic information belongs. In actual application, the dynamic traffic information can be directly matched with the map object to which it belongs.

[0070] In other embodiments, the geographical location information corresponding to the dynamic traffic information may include spatial positioning information, which can be used to indicate the specific spatial location of the dynamic traffic information. As an example, the geographical location corresponding to traffic light information, traffic flow information, traffic event information, dynamic speed limit information, road friction coefficient, parking lot information, automatic driving permission information, etc. may be spatial positioning information (e.g., longitude and latitude information or GPS information, etc.), which is used to indicate the spatial positioning of these dynamic traffic information. In actual applications, the dynamic traffic information can be matched with the map objects in the map data (e.g., at least one of roads, lanes, and parking lots) based on the spatial positioning of the dynamic traffic information and the spatial positioning of each map object in the map data. For example, Open LR position reference technology can be used to match dynamic traffic information with map objects in the map data.

[0071] In other embodiments, the geographical location information corresponding to the dynamic traffic information may include spatial range information, which can be used to indicate the spatial range of the dynamic traffic information. As an example, the geographical location corresponding to the restriction information, real-time weather information, autonomous driving permission information, etc. may be administrative division information (e.g., District M of City A, Road 023 of City A, the Second Ring Road of City A and the roads within it, etc.), which is used to indicate the applicable scope of these dynamic traffic information. In actual applications, the dynamic traffic information can be matched with the map objects (e.g., at least one of roads, lanes, and parking lots) within the spatial range to which it belongs. For example, a polygon matching algorithm can be used to match the dynamic traffic information with the map objects in the map data.

[0072] In actual application, after matching the dynamic traffic information with the map object in the map data, an association relationship between the dynamic traffic information and the map object in the map data can be established. Optionally, the dynamic traffic information can be stored as attribute information of the matched map object.

[0073] In the embodiments of this specification, the process of fusing each piece of dynamic traffic information according to the matching result with map data to obtain a matching and fusion result can also be referred to as the process of fusing dynamic traffic information. The driving reference information can be data used as driving reference that can be directly used in various functional scenarios.

[0074] In an alternative embodiment, the driving reference information obtained based on dynamic traffic information can be used in a route planning scenario, and the driving reference information can be the estimated travel time corresponding to each route.

[0075] Specifically, the process of matching the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result may include: First, according to the geographical location corresponding to the dynamic traffic information, match the dynamic traffic information to each route in the map data, where the route includes at least one of a road and a lane; then, according to the dynamic traffic information matched to each route, calculate the estimated travel time corresponding to each route, and the estimated travel time corresponding to each route is used to determine the driving route planning result. In this scenario, the dynamic traffic information may include, for example, traffic light information, traffic flow information, traffic event information, dynamic speed limit information, traffic restriction information, real-time weather information, etc.

[0076] Among them, the process of calculating the estimated travel time corresponding to each route according to the dynamic traffic information matched to each route may specifically include: determining the estimated travel speed of each route according to the dynamic traffic information matched to each route and the static speed limit value corresponding to each route; calculating the estimated travel time of each route according to the estimated travel speed of each route and the route length of each route.

[0077] Among them, the process of determining the estimated travel speed of each route according to the dynamic traffic information matched to each route and the static speed limit value corresponding to each route may specifically include: determining the passing speed limit value corresponding to each dynamic traffic information of the target route according to the dynamic traffic information matched to the target route; determining the estimated travel speed of the target route according to the passing speed limit value corresponding to each dynamic traffic information of the target route. For example, the lowest value among the passing speed limit values corresponding to each dynamic traffic information of the target route can be determined as the estimated travel speed of the target route.

[0078] For the sake of easy understanding, an example is given below.

[0079] For example, in a data processing platform, first, in the information extraction and refinement module, dynamic traffic information such as traffic flow, real-time weather, dynamic speed limits, and traffic restriction information can be fused and calculated to obtain a penalty value for the travel time at the road level and / or lane level (e.g., the expected travel time of the road), which is then provided to the route calculation module. Then, in the route calculation module, the route planning can be performed with reference to the penalty value of the travel time at the road level and / or lane level to obtain the optimal route for providing to the user. The fused penalty value of the travel time can be applied to both the standard (SD) navigation and high-precision (HD) navigation scenarios. After that, the optimal route can be sent to the vehicle terminal.

[0080] More specifically, as an example, the calculation of the expected travel time can refer to the following method: based on various dynamic traffic information, the maximum travel speed under each corresponding traffic state can be calculated; to ensure the safety of driving and self-driving, the lowest value among them can be taken as the expected travel speed; then multiplying it by the road length, the theoretical expected travel time can be obtained.

[0081] Regarding the determination of the maximum communication speed under different traffic states, the following are examples. Taking traffic flow information as an example, different traffic flow states can correspond to different maximum travel speeds. For example, the maximum travel speed in the normal state can be the static speed limit value of the road, and the maximum travel speed in the congested state can be 50% of the static speed limit value of the road. Taking real-time weather information as an example, different weather conditions can correspond to different maximum safe driving speeds. The maximum travel speed in strong wind weather can be 90% of the static speed limit value, and the maximum travel speed in heavy snow weather can be 60% of the static speed limit value. Taking traffic restriction information as an example, if the current road is restricted, the travel speed is 0, no penalty value is calculated, and it is marked as an impassable state. When planning the route, the restricted road can be directly avoided.

[0082] It can be understood that the above are only examples. In actual applications, the methods for calculating the expected travel time and performing route planning may not be limited to the foregoing examples.

[0083] In an alternative embodiment, the driving reference information obtained based on dynamic traffic information can be used in the autonomous driving scenario. More specifically, it can be used in scenarios such as determining whether to start autonomous driving and determining the autonomous driving speed. The driving reference information can be an autonomous driving feasible value.

[0084] Specifically, matching the dynamic traffic information to the full - volume map data of the latest version according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result may include: matching the dynamic traffic information to each path in the map data according to the geographical location corresponding to the dynamic traffic information, where the path includes at least one of a road and a lane; calculating an autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matched with each path, where the autonomous driving feasibility value is used to determine an autonomous driving judgment result, and the autonomous driving judgment result includes enabling autonomous driving or not enabling autonomous driving. In this scenario, the dynamic traffic information may include, for example, real - time weather information, road friction coefficient, autonomous driving permission information, etc.

[0085] Among them, calculating the autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matched with each path may specifically include: determining an autonomous driving feasibility weight corresponding to each dynamic traffic information of the target path according to the dynamic traffic information matched with the target path; performing a weighted calculation according to the autonomous driving feasibility weights corresponding to each dynamic traffic information of the target path and the autonomous driving feasibility weights corresponding to each dynamic traffic information to obtain the autonomous driving feasibility value corresponding to the target path.

[0086] Among them, if the dynamic traffic information includes autonomous driving permission information, and the autonomous driving permission information may specifically include being able to drive autonomously or not being able to drive autonomously, then calculating the autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matched with each path may specifically include: if the autonomous driving permission information is not being able to drive autonomously, then determining the autonomous driving feasibility value such that the autonomous driving judgment result is not enabling autonomous driving.

[0087] For ease of understanding, an example is given below.

[0088] For example, in a data processing platform, dynamic traffic information such as dynamic speed limits, real - time weather, road friction coefficient, and autonomous driving activation can be fused and calculated to obtain information such as the autonomous driving feasibility value of "whether the current road can enable the ODD area" and the "driving speed during autonomous driving".

[0089] Among them, the full name of ODD is Operational Design Domain. The ODD of an autonomous vehicle refers to the operating conditions set for the function of the autonomous driving system, which may include, but are not limited to, environmental, geographical, and time - period restrictions, traffic flow, and road characteristics.

[0090] In the scenario of calculating the autonomous driving feasibility value, in actual application, autonomous driving cannot be enabled when the autonomous driving feasibility value is less than a set threshold. Optionally, the set threshold can be set according to experience. For example, it can be 0.5, etc.

[0091] Among them, the calculation of the set threshold can refer to the following method.

[0092] Equation 1: Threshold = ∑(the weight of the i-th dynamic traffic information * the weight of the i-th dynamic traffic information).

[0093] In Equation 1, i can be taken from 1 to n, where n is the number of types of dynamic traffic information.

[0094] In Equation 1, the weights of the dynamic traffic information corresponding to each dynamic traffic information can be set and adjusted as needed, and the sum of the weights of the dynamic traffic information corresponding to each dynamic traffic information can be 100%. The higher the weight, the greater the impact of the corresponding dynamic traffic information on autonomous driving. For example, the impact weight of real-time weather can be set to 30%, the impact weight of road friction coefficient can be set to 40%, and the total weight of other various dynamic traffic information can be 30%.

[0095] In Equation 1, for the same type of dynamic traffic information, different dynamic traffic situations can correspond to different weights of dynamic traffic information. In actual application, a look-up table of different dynamic traffic situations and weights of dynamic traffic information can be set in advance. When it is necessary to determine the weight of a certain dynamic traffic situation, it can be determined by looking up the table. In the embodiments of this specification, a weight of 1 can represent no impact on autonomous driving, a weight of 0 can represent inability to drive autonomously, and a value between 0 and 1 can represent the degree of impact on autonomous driving. The lower the weight, the greater the impact on autonomous driving. Taking the weight of weather information as an example, clear weather can be considered to have no impact on autonomous driving, and its weight can be 1. The weight of strong wind weather can be 0.9, and the weight of heavy snow weather can be 0.8, etc.

[0096] Optionally, when actually applied, in Equation 1, when the weight of any dynamic traffic information is 0, the threshold of Equation 1 can be 0. Thus, it can be ensured that when the dynamic traffic situation corresponding to one or more dynamic traffic information is very poor, it is no longer necessary to consider the situations of other dynamic traffic information, and it can be directly determined that autonomous driving is not possible, so as to save computing resources.

[0097] For example, the autonomous driving permission information can have a veto power. That is, if the autonomous driving permission information of the current road is not for autonomous driving, the threshold is directly 0; if the autonomous driving permission information of the current road is for autonomous driving, the threshold is calculated normally according to Equation 1.

[0098] In an alternative embodiment, the driving reference information obtained based on dynamic traffic information can be used in a parking lot scenario. That is, the real-time information in the parking lot can be integrated into the static parking lot data to simultaneously meet the requirements of traditional parking lot navigation and autonomous driving scenarios such as AVP (Automated Valet Parking).

[0099] Specifically, the dynamic traffic information may include real-time parking lot information, and the real-time parking lot information may include parking space availability information, for example, the number of available parking spaces and the location of available parking spaces. Matching the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result may specifically include: matching the real-time parking lot information with the parking lot in the map data according to the geographical location corresponding to the real-time parking lot information; determining parking reference information corresponding to the parking lot according to the real-time parking lot information matched with the parking lot, where the parking reference information is used for at least one of parking lot navigation or automatic parking. Among them, parking lot navigation may refer to planning a route for a vehicle to enter the parking lot; automatic parking may refer to planning a route for a vehicle to be placed in a parking space.

[0100] According to the solution of the embodiments of the present specification, various real-time information can be online integrated into the static map network, and the types of integrated information are relatively numerous and cover comprehensively, including real-time traffic events and traffic flow information, road friction coefficient, road weather, dynamic speed limit, traffic signal service, parking lot, autonomous driving start service, etc. Information, which can meet the usage requirements of multiple scenarios (manual driving navigation, autonomous driving navigation, parking lot navigation, etc.).

[0101] In the solution of the embodiments of the present specification, a large range of data (for example, national data) is matched and processed at one time in the cloud, and the data required by the vehicle terminal is sent to the vehicle terminal, without performing data matching and fusion processing at the vehicle terminal, which can solve the problem of the computing power bottleneck of the vehicle terminal. And because the cloud can obtain a wide range of data and process data quickly, the vehicle terminal can quickly obtain more dynamic information, solve the problem of low data freshness of the vehicle terminal, and can improve the navigation effect and meet the data requirements of scenarios such as autonomous driving.

[0102] In addition, when the cloud sends data to the vehicle terminal, the differential data packet is sent, so the network consumption is small and the data transmission speed is fast.

[0103] Based on the same idea, the embodiments of the present specification also provide a device corresponding to the above method.

[0104] Figure 5 For the embodiments of the present specification, corresponding to Figure 2Structural schematic diagram of a driving reference information providing device. As Figure 5 shown, this device is applied to a cloud data processing platform and specifically may include:

[0105] An information acquisition module 502, configured to acquire dynamic traffic information; the dynamic traffic information refers to traffic-related information that changes with at least one of time or space;

[0106] A matching and fusion module 504, configured to match the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information, and obtain a second matching and fusion result;

[0107] A difference module 506, configured to obtain driving reference information according to the difference result between the first matching and fusion result and the second matching and fusion result; wherein, the first matching and fusion result is the result of matching the previous dynamic traffic information with the previous full-scale map data;

[0108] An information sending module 508, configured to send the driving reference information to a vehicle terminal.

[0109] Based on Figure 5 the device, some specific implementation schemes of this method are also provided in the embodiments of this specification, which will be described below.

[0110] Optionally, the difference module 506 may specifically be configured to: perform a difference calculation on the first matching and fusion result and the second matching and fusion result to obtain a difference data packet; store the difference data packet and the second matching and fusion result; mark the version of the difference data packet and the version of the second matching and fusion result; the version of the difference data packet is consistent with the version of the first matching and fusion result; the version of the second matching and fusion result is the next version of the first matching and fusion result.

[0111] Accordingly, the information sending module 508 may specifically be configured to: receive a data acquisition request sent by a vehicle terminal; the data acquisition request carries a cached data version of a third matching and fusion result currently cached by the vehicle terminal; determine whether the cached data version is consistent with the version of the differential data packet or the version of the second matching and fusion result, to obtain a version determination result; if the version determination result indicates that the cached data version is consistent with the version of the differential data packet, then send the differential data packet to the vehicle terminal as driving reference information; if the version determination result indicates that the cached data version is consistent with the version of the second matching and fusion result, then send an empty data packet to the vehicle terminal as driving reference information; if the version determination result indicates that the cached data version is inconsistent with the version of the differential data packet and inconsistent with the version of the second matching and fusion result, then send the second matching and fusion result to the vehicle terminal as driving reference information.

[0112] Optionally, the driving reference information may be the estimated travel time corresponding to each path; the matching and fusion module 504 may specifically be configured to: match the dynamic traffic information to each path in the map data according to the geographical location corresponding to the dynamic traffic information; the path includes at least one of a road and a lane; calculate the estimated travel time corresponding to each path according to the dynamic traffic information matched to each path; the estimated travel time corresponding to each path is used to determine a driving route planning result.

[0113] Optionally, the driving reference information may be an autonomous driving feasibility value; the matching and fusion module 504 may specifically be configured to: match the dynamic traffic information to each path in the map data according to the geographical location corresponding to the dynamic traffic information; the path includes at least one of a road and a lane; calculate the autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matched to each path; the autonomous driving feasibility value is used to determine an autonomous driving judgment result, and the autonomous driving judgment result includes enabling autonomous driving or not enabling autonomous driving.

[0114] Optionally, the dynamic traffic information may include real-time parking lot information, and the real-time parking lot information may include parking space availability information; the matching and fusion module 504 may specifically be configured to: match the real-time parking lot information to a parking lot in the map data according to the geographical location corresponding to the real-time parking lot information; determine parking reference information corresponding to the parking lot according to the real-time parking lot information matched to the parking lot; the parking reference information is used for at least one of parking lot navigation or automatic parking.

[0115] It can be understood that the above-mentioned modules refer to computer programs or program segments for performing one or more specific functions. In addition, the distinction of the above-mentioned modules does not mean that the actual program code must also be separated.

[0116] Based on the same idea, the embodiments of this specification also provide a system corresponding to the above method.

[0117] Figure 6 The structural schematic diagram of a driving reference information providing system provided by an embodiment of this specification is shown.

[0118] As Figure 6 shown, the driving reference information providing system may include a big data platform 602, a cloud data processing platform 604, and a vehicle terminal 606.

[0119] Among them, the big data platform 602 is used to determine dynamic traffic information. Although Figure 6 the dynamic traffic information such as traffic light services, real-time traffic information, real-time weather conditions, dynamic speed limits, traffic restriction information, road friction coefficients, parking lot information, and automatic driving activation are shown, it can be understood that the actual traffic information in actual applications may also include other types of information, not limited to the examples listed here.

[0120] The cloud data processing platform 604 is used to obtain dynamic traffic information from the big data platform 602, where the dynamic traffic information refers to traffic-related information that changes with at least one of time or space; it is used to match the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result, and obtain driving reference information according to the differential result between the first matching and fusion result and the second matching and fusion result, where the first matching and fusion result is the result of the previous dynamic traffic information matching the previous full-scale map data; and it is used to send the driving reference information to the vehicle terminal 606.

[0121] In actual applications, the cloud data processing platform 604 may include an information matching module and an information fusion module. Among them, the information matching module is used to match the data obtained from the big data platform to the map data local to the cloud data platform, and the information fusion module is used to perform information extraction and fusion on the basis of information matching to obtain a data matching and fusion result, and further obtain driving reference information to be sent to the vehicle terminal to assist automatic driving.

[0122] The vehicle terminal 606 is used to obtain driving reference information from the cloud data processing platform 604. In actual applications, the vehicle terminal may include one or more vehicles.

[0123] In actual applications, after obtaining the driving reference information, the vehicle terminal can also send the data to the driving navigation module to support traditional SD navigation. Under the condition of meeting the conditions for autonomous driving, the latest full-volume data obtained can also be sent to the autonomous driving module to support HD navigation. In addition, the latest full-volume data obtained can also be sent to the rendering module to meet the requirement of rendering the navigation map on the human-machine interaction interface.

[0124] The above describes specific embodiments of this specification. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0125] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other.

[0126] The devices, systems, and methods provided in the embodiments of this specification are corresponding. Therefore, the devices and systems also have beneficial technical effects similar to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the corresponding devices and systems will not be elaborated here.

[0127] For the convenience of description, when describing the above devices, they are divided into various units according to functions and described separately. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0128] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented 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.

[0129] The present invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may 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 executed by the processor of the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart flow or flows and / or block or blocks. Figure 1 in one flow or more flows and / or blocks Figure 1 or in one block or more blocks.

[0130] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in the flowchart flow or flows and / or block or blocks. Figure 1 in one flow or more flows and / or blocks Figure 1 or in one block or more blocks.

[0131] 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, and thus the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and / or block or blocks. Figure 1 in one flow or more flows and / or blocks Figure 1 or in one block or more blocks.

[0132] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, commodity or device that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device that includes the element.

[0133] This application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

[0134] The above are only embodiments of this application and are not intended to limit this application. For those skilled in the art, various changes and modifications can be made to this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of this application shall be included within the scope of the claims of this application.

Claims

1. A method for providing driving reference information, characterized in that, Applied to a cloud data processing platform, the method includes: Obtain dynamic traffic information; the dynamic traffic information refers to traffic-related information that changes with at least one of time or space; According to the geographical location corresponding to the dynamic traffic information, match the dynamic traffic information to the latest version of the full-scale map data to obtain a second matching and fusion result; Obtain driving reference information according to the difference result between the first matching and fusion result and the second matching and fusion result; wherein, the first matching and fusion result is the result of matching the previous dynamic traffic information with the previous full-scale map data; Send the driving reference information to the vehicle terminal.

2. The method according to claim 1, wherein The obtaining of driving reference information according to the difference result between the first matching and fusion result and the second matching and fusion result specifically includes: Perform a difference calculation on the first matching and fusion result and the second matching and fusion result to obtain a difference data packet; Store the difference data packet and the second matching and fusion result; Mark the version of the difference data packet and the version of the second matching and fusion result; the version of the difference data packet is consistent with the version of the first matching and fusion result; the version of the second matching and fusion result is the next version of the first matching and fusion result.

3. The method according to claim 2, wherein The sending of the driving reference information to the vehicle terminal specifically includes: Receive a data acquisition request sent by the vehicle terminal; the data acquisition request carries the cached data version of the third matching and fusion result currently cached by the vehicle terminal; Judge whether the cached data version is consistent with the version of the difference data packet or the version of the second matching and fusion result to obtain a version judgment result; If the version judgment result indicates that the cached data version is consistent with the version of the difference data packet, then send the difference data packet to the vehicle terminal as the driving reference information; If the version judgment result indicates that the cached data version is consistent with the version of the second matching and fusion result, then send an empty data packet to the vehicle terminal as the driving reference information; If the version judgment result indicates that the cached data version is inconsistent with the version of the difference data packet and inconsistent with the version of the second matching and fusion result, then send the second matching and fusion result to the vehicle terminal as the driving reference information.

4. The method according to claim 1, characterized in that The driving reference information is the estimated travel time corresponding to each path; the matching of the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result specifically includes: According to the geographical location corresponding to the dynamic traffic information, match the dynamic traffic information to each path in the map data; the path includes at least one of a road and a lane; Calculate the estimated travel time corresponding to each path according to the dynamic traffic information matched to each path; the estimated travel time corresponding to each path is used to determine the driving route planning result.

5. The method according to claim 4, wherein The calculating of the estimated travel time corresponding to each path according to the dynamic traffic information matched to each path specifically includes: Determine the expected passing speed of each path according to the dynamic traffic information matching each path and the static speed limit value corresponding to each path; Calculate the expected passing time of each path according to the expected passing speed of each path and the path length of each path.

6. The method according to claim 5, characterized in that, The determining the expected passing speed of each path according to the dynamic traffic information matching each path and the static speed limit value corresponding to each path specifically includes: Determine the passing speed limit value corresponding to each dynamic traffic information of the target path according to the dynamic traffic information matching the target path; Determine the expected passing speed of the target path according to the passing speed limit value corresponding to each dynamic traffic information of the target path.

7. The method according to claim 1, characterized in that The driving reference information is an autonomous driving feasibility value; the matching the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result specifically includes: Match the dynamic traffic information to each path in the map data according to the geographical location corresponding to the dynamic traffic information; the path includes at least one of a road and a lane; Calculate the autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matching each path; the autonomous driving feasibility value is used to determine an autonomous driving judgment result, and the autonomous driving judgment result includes turning on autonomous driving or not turning on autonomous driving.

8. The method according to claim 7, wherein The calculating the autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matching each path specifically includes: Determine the autonomous driving feasibility weight value corresponding to each dynamic traffic information of the target path according to the dynamic traffic information matching the target path; Perform weighted calculation according to the autonomous driving feasibility weight value corresponding to each dynamic traffic information of the target path and the autonomous driving feasibility weight corresponding to each dynamic traffic information to obtain the autonomous driving feasibility value corresponding to the target path.

9. The method according to claim 7, wherein The dynamic traffic information includes autonomous driving permission information; the autonomous driving permission information specifically includes being able to drive autonomously or not being able to drive autonomously; The calculating the autonomous driving feasibility value corresponding to each path according to the dynamic traffic information matching each path specifically includes: If the autonomous driving permission information is not being able to drive autonomously, then determine the autonomous driving feasibility value so that the autonomous driving judgment result is not turning on autonomous driving.

10. The method according to claim 1, wherein The dynamic traffic information includes real-time parking lot information, and the real-time parking lot information includes parking space availability information; The matching the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information to obtain a second matching and fusion result specifically includes: Match the real-time parking lot information to the parking lot in the map data according to the geographical location corresponding to the real-time parking lot information; Determine the parking reference information corresponding to the parking lot according to the real-time parking lot information matching the parking lot; the parking reference information is used for at least one of parking lot navigation and automatic parking.

11. A driving reference information providing device, which is applied to a cloud data processing platform and includes: An information acquisition module, which is used to acquire dynamic traffic information; The dynamic traffic information refers to traffic-related information that changes with at least one of time or space; A matching and fusion module, configured to match the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information, to obtain a second matching and fusion result; A differential module, configured to obtain driving reference information according to the differential result between the first matching and fusion result and the second matching and fusion result; wherein, the first matching and fusion result is the result of matching the previous dynamic traffic information with the previous full-scale map data; An information sending module, configured to send the driving reference information to a vehicle terminal.

12. A driving reference information providing system, characterized in that, It includes a big data platform, a cloud data processing platform, and a vehicle terminal; The big data platform is configured to determine dynamic traffic information; The cloud data processing platform is configured to obtain dynamic traffic information from the big data platform, and the dynamic traffic information refers to traffic-related information that changes with at least one of time or space; It is configured to match the dynamic traffic information to the latest version of the full-scale map data according to the geographical location corresponding to the dynamic traffic information, to obtain a second matching and fusion result, and to obtain driving reference information according to the differential result between the first matching and fusion result and the second matching and fusion result, wherein the first matching and fusion result is the result of matching the previous dynamic traffic information with the previous full-scale map data; and is configured to send the driving reference information to the vehicle terminal; The vehicle terminal is configured to obtain driving reference information from the cloud data processing platform.

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