Vehicle control method and device based on vehicle cloud cooperation, and computer program product

Abstract

The invention discloses a vehicle cloud cooperation-based vehicle control method and device, and a computer program product. The method comprises the following steps: sending a connection request to vehicle-mounted terminal equipment of a target vehicle, so as to establish communication connection with the vehicle-mounted terminal equipment based on the connection request; acquiring a historical driving record of the target vehicle based on the communication connection; performing route analysis on a plurality of historical driving routes in the historical driving record to obtain common driving road sections of the target vehicle; and generating a vehicle-specific map packet of the target vehicle based on the common driving road section, and issuing the vehicle-specific map packet to the vehicle-mounted terminal equipment based on the connection request, so that the vehicle-mounted terminal equipment controls the target vehicle to drive based on the vehicle-specific map packet or call a cloud map. According to the method and the device, the technical problem that the response speed is low due to the fact that the map utilization rate of the national full-quantity map package for the vehicle with the relatively fixed driving route is low and the storage space is occupied in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of automotive electronics and information technology, and in particular, to a vehicle control method, device, and computer program product based on vehicle-cloud collaboration. Background Art

[0002] When commercial vehicles apply control strategies such as predictive cruise, predictive gear shifting, and predictive energy management, they need to know the road information ahead in advance, usually 2 kilometers, 3 kilometers, 8 kilometers or even longer; the road information mainly includes information such as the slope, curvature, and speed limit ahead.

[0003] Currently, the common practice in the industry is to pre-store a national full-scale map package in the vehicle-related controllers. The vehicle-related controllers include ECU controllers, T-Box networking terminals, electronic horizons, etc. The national full-scale map includes road data such as highways and national roads in each province and city. In the actual application process, the vehicle calls the pre-stored offline map package to obtain relevant road information. The map package is usually updated once every quarter, every six months or even once a year.

[0004] The disadvantages of the above method are that the national full-scale map package is relatively large, which requires a high storage capacity of the vehicle controller; at the same time, there are many map files, which also require a high query and calculation ability of the vehicle controller; the map package release cycle is long and the real-time performance is poor; the driving routes of commercial vehicles are relatively fixed, usually only running within a certain province or city, or often running on a fixed few routes, and a large amount of map data is not used, resulting in a low map utilization rate.

[0005] In view of the problem that the map utilization rate of the national full-scale map package is relatively low and it occupies storage space for vehicles with relatively fixed driving routes in the above-related technologies, resulting in a slow response speed, no effective solution has been proposed yet. Summary of the Invention

[0006] Embodiments of the present invention provide a vehicle control method, device, and computer program product based on vehicle-cloud collaboration to at least solve the technical problem that the map utilization rate of the national full-scale map package is relatively low and it occupies storage space for vehicles with relatively fixed driving routes in the related technologies, resulting in a slow response speed.

[0007] According to one aspect of an embodiment of the present invention, a vehicle control method based on vehicle-cloud collaboration is provided, including: sending a connection request to an in-vehicle terminal device of a target vehicle to establish a communication connection with the in-vehicle terminal device based on the connection request; obtaining a historical driving record of the target vehicle based on the communication connection, where the historical driving record is a driving record collected by the in-vehicle terminal device during a historical time period; performing route analysis on multiple historical driving routes in the historical driving record to obtain a frequently used driving section of the target vehicle, where the frequently used driving section is a section where the driving frequency of the target vehicle during the historical time period is higher than a predetermined frequency threshold; generating a vehicle-specific map package of the target vehicle based on the frequently used driving section, and sending the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call a cloud map.

[0008] Optionally, performing route analysis on multiple historical driving routes in the historical driving record to obtain a frequently used driving section of the target vehicle includes: obtaining a first coordinate hash value of a first waypoint in each historical driving route, where the first waypoint is a waypoint in the historical driving route, and the first coordinate hash value is a first hash value corresponding to the first coordinate of the first waypoint; obtaining a second coordinate hash value of a second waypoint in each predetermined section, where the second waypoint is a waypoint in the predetermined section, and the second coordinate hash value is a second hash value corresponding to the second coordinate of the second waypoint, where the predetermined section is a section involved in the historical driving route; sequentially matching the first coordinate hash values in all the historical driving routes with the second coordinate hash values in each predetermined section to obtain a matching frequency of each predetermined section, where the matching frequency is the number of times the second coordinate hash value is the same as the first coordinate hash value; calculating based on the matching frequency of each predetermined section and the total number of the predetermined sections to obtain the driving frequency of the target vehicle driving on each predetermined section during the historical time period; determining the predetermined section with the driving frequency higher than the predetermined frequency threshold as the frequently used driving section.

[0009] Optionally, matching the first coordinate hash values in all the historical driving routes with the second coordinate hash values in each of the predetermined road segments in sequence to obtain the matching frequencies of the predetermined road segments, including: determining the first ranking sequence numbers of each first sub-hash value in the first coordinate hash value, and determining the second ranking sequence numbers of each second sub-hash value in the second coordinate hash value, where the first sub-hash value is the first numerical value at each ranking sequence number in the first coordinate hash value, and the second sub-hash value is the second previous hash value numerical value at each ranking sequence number in the second coordinate hash value; determining the hash value formed by arranging in ascending order of the first ranking sequence number all the first sub-hash values with the first ranking sequence number not less than the first predetermined ranking sequence number as the first previous hash value, and determining the hash value formed by arranging in ascending order of the second ranking sequence number all the second sub-hash values with the second ranking sequence number not less than the first predetermined ranking sequence number as the second previous hash value; matching all the first previous hash values with the second previous hash values in each of the predetermined road segments in sequence, and determining the predetermined road segment that matches successfully with the first previous hash value as the target predetermined road segment; matching the first coordinate hash value corresponding to the first previous hash value with the second coordinate hash value corresponding to each of the target predetermined road segments in sequence, and in the case of each successful match, increasing the matching frequency of the predetermined road segment by 1 to obtain the matching frequencies of the predetermined road segments, where the initial value of the matching frequency of each of the predetermined road segments is 0, and the successful match means that the first previous hash value is the same as the second previous hash value.

[0010] Optionally, before determining the predetermined road segment with the driving frequency higher than the predetermined frequency threshold as the frequently used driving road segment, the vehicle control method based on vehicle-cloud collaboration further includes: sorting the driving frequencies of the predetermined road segments in descending order to obtain a sorting result; determining the driving frequency at the second predetermined ranking sequence number in the sorting result as the predetermined frequency threshold, where the second predetermined ranking sequence number is a ranking sequence number the same as or different from the first predetermined ranking sequence number; or, determining the frequency threshold set by the target object as the predetermined frequency threshold.

[0011] Optionally, a vehicle-specific map package for the target vehicle is generated based on the common driving sections, including: generating a vehicle-specific map for the target vehicle based on the common driving sections; determining the general index file corresponding to the common driving sections as a specific index file, and determining the general data file corresponding to the common driving sections as a specific data file, wherein the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all the roads in the cloud map, the general index information is used to search for the roads, and the general road information is used to record the positions and road conditions of the roads; integrating the vehicle-specific map, the specific index file, and the specific data file to obtain the vehicle-specific map package.

[0012] According to another aspect of the embodiments of the present invention, there is also provided a vehicle control method based on vehicle-cloud collaboration, including: responding to a connection request sent by the cloud to establish a communication connection with the cloud based on the connection request; receiving, based on the communication connection, the vehicle-specific map package sent by the cloud, wherein the vehicle-specific map package is a map package generated by the cloud according to the common driving sections in the historical driving record of the target vehicle, and the common driving sections are the sections where the driving frequency of the target vehicle is higher than a predetermined frequency threshold within a historical time period; obtaining the current position hash value of the target vehicle, wherein the current position hash value is a hash value calculated according to the current position coordinates of the target vehicle; when the current position hash value is found in the vehicle-specific map package, obtaining the first driving road information corresponding to the current position hash value in the vehicle-specific map package, and when the current position hash value is not found in the vehicle-specific map package, obtaining the second driving road information corresponding to the current position hash value in the cloud map; controlling the target vehicle to drive based on the first driving road information or the second driving road information.

[0013] Optionally, receive a vehicle-specific map package sent from the cloud, including: in response to a data acquisition instruction sent from the cloud, acquire the historical driving record of the target vehicle within a historical time period based on the data acquisition instruction; upload the historical driving record to the cloud to trigger the cloud to perform route analysis based on multiple historical driving routes in the historical driving record to obtain the frequently traveled sections of the target vehicle; receive the vehicle-specific map package generated by the cloud based on the frequently traveled sections, where the vehicle-specific map package includes: generating a vehicle-specific map of the target vehicle based on the frequently traveled sections, a dedicated index file corresponding to the frequently traveled sections, and a dedicated data file, the dedicated index file is used to record dedicated index information of the frequently traveled sections, the dedicated data file is used to record dedicated road information of the frequently traveled sections, the dedicated index information is used to find the frequently traveled sections, and the dedicated road information is used to record the location and road conditions of the frequently traveled sections.

[0014] Optionally, when the current location hash value is queried in the vehicle-specific map package, acquire first driving road information corresponding to the current location hash value in the vehicle-specific map package; when the current location hash value is not queried in the vehicle-specific map package, acquire second driving road information corresponding to the current location hash value in the cloud map, including: perform indexing in the dedicated index file of the vehicle-specific map package according to the current location hash value to obtain an indexing result; when the indexing result indicates that the current location hash value exists in the dedicated index file, determine the dedicated road information matching the current location hash value in the dedicated data file as the first driving road information; when the indexing result indicates that the current location hash value does not exist in the dedicated index file, determine the general road information corresponding to the current location hash value in the cloud map as the second driving road information.

[0015] Optionally, determining the general road information corresponding to the current location hash value in the cloud map as the second driving road information includes: acquiring a general index file and a general data file corresponding to the cloud map, where the general index file is used to record general index information of all roads in the cloud map, the general data file is used to record general road information of all roads in the cloud map, the general index information is used to find the roads, and the general road information is used to record the location and road conditions of the roads; when the current location hash value exists in the general index file, determine the general road information matching the current location hash value in the general data file as the second driving road information.

[0016] According to another aspect of the embodiments of the present invention, there is also provided a vehicle control device based on vehicle-cloud collaboration, including: a sending unit, configured to send a connection request to an in-vehicle terminal device of a target vehicle to establish a communication connection with the in-vehicle terminal device based on the connection request; a first obtaining unit, configured to obtain a historical driving record of the target vehicle based on the communication connection, where the historical driving record is a driving record collected by the in-vehicle terminal device during a historical time period; a second obtaining unit, configured to perform route analysis on multiple historical driving routes in the historical driving record to obtain a frequently traveled section of the target vehicle, where the frequently traveled section is a section of the target vehicle with a driving frequency higher than a predetermined frequency threshold during the historical time period; a generating unit, configured to generate a vehicle-specific map package of the target vehicle based on the frequently traveled section, and send the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call a cloud map.

[0017] Optionally, the second obtaining unit includes: a first obtaining module, configured to obtain a first coordinate hash value of a first passing point in each of the historical driving routes, where the first passing point is a passing point in the historical driving route, and the first coordinate hash value is a first hash value corresponding to the first coordinate of the first passing point; a second obtaining module, configured to obtain a second coordinate hash value of a second passing point in each predetermined section, where the second passing point is a passing point in the predetermined section, and the second coordinate hash value is a second hash value corresponding to the second coordinate of the second passing point, where the predetermined section is a section involved in the historical driving route; a third obtaining module, configured to sequentially match the first coordinate hash values in all the historical driving routes with the second coordinate hash values in each of the predetermined sections to obtain a matching frequency of each of the predetermined sections, where the matching frequency is the number of times the second coordinate hash value is the same as the first coordinate hash value; a fourth obtaining module, configured to calculate based on the matching frequency of each of the predetermined sections and the total number of the predetermined sections to obtain a driving frequency of the target vehicle on each of the predetermined sections during the historical time period; a first determining module, configured to determine that the predetermined section with the driving frequency higher than the predetermined frequency threshold is the frequently traveled section.

[0018] Optionally, the third acquisition module includes: a first determination sub-module, configured to determine a first ranking sequence number of each first sub-hash value in the first coordinate hash value, and determine a second ranking sequence number of each second sub-hash value in the second coordinate hash value, where the first sub-hash value is a first numerical value at each ranking sequence number in the first coordinate hash value, and the second sub-hash value is a second pre-hash value numerical value at each ranking sequence number in the second coordinate hash value; a second determination sub-module, configured to determine a hash value formed by arranging in ascending order all the first sub-hash values whose first ranking sequence numbers are not less than a first predetermined ranking sequence number as a first pre-hash value, and determine a hash value formed by arranging in ascending order all the second sub-hash values whose second ranking sequence numbers are not less than the first predetermined ranking sequence number as a second pre-hash value; a third determination sub-module, configured to sequentially match all the first pre-hash values with the second pre-hash values in each of the predetermined road segments, and determine the predetermined road segment that matches successfully with the first pre-hash value as a target predetermined road segment; a first acquisition sub-module, configured to sequentially match the first coordinate hash value corresponding to the first pre-hash value with the second coordinate hash value corresponding to each of the target predetermined road segments, and in the case of each successful match, increase the matching frequency of the predetermined road segment by 1 to obtain the matching frequencies of each of the predetermined road segments, where the initial value of the matching frequency of each of the predetermined road segments is 0, and the successful match means that the first pre-hash value is the same as the second pre-hash value.

[0019] Optionally, the vehicle control device based on vehicle-cloud collaboration further includes: a fifth acquisition module, configured to perform a descending order sorting on the driving frequencies of each of the predetermined road segments to obtain a sorting result before determining the predetermined road segment with a driving frequency higher than the predetermined frequency threshold as the frequently traveled road segment; a second determination module, configured to determine the driving frequency at a second predetermined ranking sequence number in the sorting result as the predetermined frequency threshold, where the second predetermined ranking sequence number is a ranking sequence number that is the same as or different from the first predetermined ranking sequence number; or, a third determination module, configured to determine the frequency threshold set by a target object as the predetermined frequency threshold.

[0020] Optionally, the generating unit includes: a generating module, configured to generate a vehicle-specific map for the target vehicle based on the common driving sections; a fourth determining module, configured to determine the general index file corresponding to the common driving sections as a dedicated index file, and determine the general data file corresponding to the common driving sections as a dedicated data file, where the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all the roads in the cloud map, the general index information is used to search for the roads, and the general road information is used to record the positions and road conditions of the roads; a sixth obtaining module, configured to integrate the vehicle-specific map, the dedicated index file, and the dedicated data file to obtain the vehicle-specific map package.

[0021] According to another aspect of the embodiments of the present invention, there is also provided a vehicle control device based on vehicle-cloud collaboration, including: a response unit, configured to respond to a connection request sent by the cloud to establish a communication connection with the cloud based on the connection request; a receiving unit, configured to receive the vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to the common driving sections in the historical driving record of the target vehicle, and the common driving sections are the sections where the driving frequency of the target vehicle in the historical time period is higher than a predetermined frequency threshold; a third obtaining unit, configured to obtain the current position hash value of the target vehicle, where the current position hash value is a hash value calculated according to the current position coordinates of the target vehicle; a fourth obtaining unit, configured to obtain the first driving road information corresponding to the current position hash value in the vehicle-specific map package when the current position hash value is found in the vehicle-specific map package, and obtain the second driving road information corresponding to the current position hash value in the cloud map when the current position hash value is not found in the vehicle-specific map package; a control unit, configured to control the target vehicle to drive based on the first driving road information or the second driving road information.

[0022] Optionally, the receiving unit includes: a response module, configured to respond to a data acquisition instruction sent by the cloud, and acquire the historical driving record of the target vehicle within a historical time period based on the data acquisition instruction; a trigger module, configured to upload the historical driving record to the cloud, so as to trigger the cloud to perform route analysis based on multiple historical driving routes in the historical driving record, and obtain the frequently traveled road segments of the target vehicle; a receiving module, configured to receive the vehicle-specific map package generated by the cloud based on the frequently traveled road segments, where the vehicle-specific map package includes: a vehicle-specific map of the target vehicle generated based on the frequently traveled road segments, a dedicated index file corresponding to the frequently traveled road segments, and a dedicated data file, the dedicated index file is used to record dedicated index information of the frequently traveled road segments, the dedicated data file is used to record dedicated road information of the frequently traveled road segments, the dedicated index information is used to find the frequently traveled road segments, and the dedicated road information is used to record the position and road conditions of the frequently traveled road segments.

[0023] Optionally, the fourth acquisition unit includes: a seventh acquisition module, configured to perform indexing in the dedicated index file of the vehicle-specific map package according to the current position hash value, and obtain an index result; a fifth determination module, configured to, when the index result indicates that the current position hash value exists in the dedicated index file, determine the dedicated road information matching the current position hash value in the dedicated data file as the first driving road information; a sixth determination module, configured to, when the index result indicates that the current position hash value does not exist in the dedicated index file, determine the general road information corresponding to the current position hash value in the cloud map as the second driving road information.

[0024] Optionally, the sixth determination module includes: a second acquisition sub-module, configured to acquire a general index file and a general data file corresponding to the cloud map, where the general index file is used to record general index information of all roads in the cloud map, the general data file is used to record general road information of all roads in the cloud map, the general index information is used to find the roads, and the general road information is used to record the position and road conditions of the roads; a fourth determination sub-module, configured to, when the current position hash value exists in the general index file, determine the general road information matching the current position hash value in the general data file as the second driving road information.

[0025] According to another aspect of the embodiments of the present invention, there is also provided a vehicle control system based on vehicle-cloud collaboration, and the vehicle control system based on vehicle-cloud collaboration uses any one of the above-mentioned vehicle control methods based on vehicle-cloud collaboration.

[0026] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, which includes a stored program, wherein the program executes any one of the above-mentioned vehicle control methods based on vehicle-cloud collaboration.

[0027] According to another aspect of the embodiments of the present invention, there is also provided a processor, which is used to run a program, wherein when the program runs, it executes any one of the above-mentioned vehicle control methods based on vehicle-cloud collaboration.

[0028] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, which includes computer instructions, and when the computer instructions are executed by a processor, they execute any one of the above-mentioned vehicle control methods based on vehicle-cloud collaboration.

[0029] In the embodiments of the present invention, a connection request is sent to the in-vehicle terminal device of the target vehicle to establish a communication connection with the in-vehicle terminal device based on the connection request; the historical driving record of the target vehicle is obtained based on the communication connection, where the historical driving record is the driving record collected by the in-vehicle terminal device during a historical time period; route analysis is performed on multiple historical driving routes in the historical driving record to obtain the frequently used driving sections of the target vehicle, where the frequently used driving sections are the sections where the driving frequency of the target vehicle during the historical time period is higher than a predetermined frequency threshold; a vehicle-specific map package of the target vehicle is generated based on the frequently used driving sections, and the vehicle-specific map package is sent to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call the cloud map. Through the above technical solutions, the purpose of analyzing the historical driving routes of the vehicle by the cloud to obtain the frequently used driving sections of the vehicle is achieved, and it is realized that the vehicle-specific map package generated by the cloud based on the frequently used driving sections of the vehicle and related files is stored in the vehicle so that the vehicle can drive according to its specific map package on a daily basis, and it also provides the technical effect that the vehicle can call the cloud map to drive when needed, saving the storage space for storing the map of the vehicle, improving the response speed and the utilization rate of the map stored in the vehicle, and thus solving the technical problems in the related art that for vehicles with relatively fixed driving routes, the utilization rate of the national full-scale map package is relatively low, and it occupies storage space, resulting in a slower response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0031] Figure 1 It is a hardware structure block diagram of a mobile terminal of a vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention;

[0032] Figure 2 is a flowchart of a vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention;

[0033] Figure 3 is a schematic diagram of a cloud map-related file according to an embodiment of the present invention;

[0034] Figure 4 is a flowchart of an alternative vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention;

[0035] Figure 5 is a schematic diagram of analyzing common driving sections according to an embodiment of the present invention;

[0036] Figure 6 is a schematic diagram of analyzing the process of the vehicle driving frequency on a certain section according to an embodiment of the present invention;

[0037] Figure 7 is a schematic diagram of analyzing the process of the vehicle driving frequency on another section according to an embodiment of the present invention;

[0038] Figure 8 is a schematic diagram of analyzing the process of the vehicle driving frequency on yet another section according to an embodiment of the present invention;

[0039] Figure 9 is a schematic diagram of the statistical result of the vehicle driving frequency on each section according to an embodiment of the present invention;

[0040] Figure 10 is a schematic diagram of a vehicle-specific map-related file according to an embodiment of the present invention;

[0041] Figure 11 is a flowchart of another alternative vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention;

[0042] Figure 12 is a flowchart of the vehicle obtaining road information and running according to an embodiment of the present invention;

[0043] Figure 13 is a schematic diagram of a vehicle control device based on vehicle-cloud collaboration according to an embodiment of the present invention;

[0044] Figure 14 is a schematic diagram of an alternative vehicle control device based on vehicle-cloud collaboration according to an embodiment of the present invention.

[0045] Among them, the above-mentioned drawings include the following reference numerals:

[0046] 102, processor; 104, memory; 106, transmission device; 108, input / output device. Detailed implementation manners

[0047] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0048] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0049] For the convenience of description, some nouns or terms that may be involved in the embodiments of the present invention are explained below:

[0050] 1) Predictive cruise: It is an assisted driving function that allows the driver to set a constant speed when driving on a highway or during other long-distance driving, which helps to improve the fuel economy of the vehicle.

[0051] 2) Slope: It is a measure that describes the degree of terrain inclination and is usually used to measure the inclination angle of the ground or road surface. There are usually several ways of expression: percentage slope, degree slope, ratio slope, etc. Different slope expression methods are applied in different situations.

[0052] 3) T-Box: The full name is Telematics Box, which is an intelligent vehicle networking terminal device. It is usually installed inside the vehicle and serves as a bridge connecting the vehicle to the external network. Its main function is to collect various data of the vehicle, such as location information, driving status, engine parameters, etc., and transmit these data to a remote server or cloud platform through wireless communication network technology.

[0053] 4) ECU: Engine Control Unit, an abbreviation for engine control unit, is an electronic device used to control the operation of an automotive engine. The ECU receives data from various sensors and adjusts engine parameters according to preset programs and algorithms to ensure efficient and stable operation of the engine under various working conditions. Its main functions include fuel management, ignition control, emission control, fault diagnosis, and adaptive learning, etc.

[0054] As introduced in the background art, for vehicles with relatively fixed driving routes, the map usage rate of the national full-scale map package is low, and it occupies storage space, resulting in a slow response speed. To address the above defects, in the embodiments of the present invention, a vehicle control method, device, and computer program product based on vehicle-cloud collaboration are provided.

[0055] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0056] The method embodiments provided in the embodiments of the present invention can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal of a vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in Figure 1 processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above mobile terminal. For example, the mobile terminal may further include more or fewer components than Figure 1 shown in

[0057] The memory 104 can be used to store computer programs, such as software programs and modules of application software, such as the computer program corresponding to the vehicle control method based on vehicle-cloud collaboration in the embodiments of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above-mentioned method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories may be connected to the mobile terminal through a network. Examples of the above-mentioned network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by a communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network adapter (abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (abbreviated as RF) module, which is used to communicate with the Internet wirelessly.

[0058] According to an embodiment of the present invention, a method embodiment of a vehicle control method based on vehicle-cloud collaboration is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0059] Figure 2 is a flowchart of a vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention, as Figure 2 shown, the method includes the following steps:

[0060] Step S202, sending a connection request to the in-vehicle terminal device of the target vehicle to establish a communication connection with the in-vehicle terminal device based on the connection request.

[0061] Optionally, the above-mentioned in-vehicle terminal device may include but is not limited to vehicle networking intelligent terminal devices such as T-Box (Telematics Box).

[0062] In this embodiment, a communication connection between the cloud and the in-vehicle terminal device can be established first, so that subsequent communication and data interaction can be carried out between the cloud and the in-vehicle terminal device.

[0063] The following combinesFigure 3 Describe in detail the information stored in the cloud in the above embodiments of the present invention. Figure 3 It is a schematic diagram of a cloud map-related file according to an embodiment of the present invention; as Figure 3 shown, the cloud can store the full national map and store it separately according to the general index file and the general data file.

[0064] Specifically, the cloud general data file includes road IDs (here the road is equivalent to the road segment in the embodiment of the present invention), each ID corresponding to a road, and each road including road information such as longitude, latitude, hash value (8 bits), distance value, slope value, etc. Among them, according to the longitude and latitude, the corresponding hash value can be calculated using the hash algorithm; the cloud general index file includes road IDs, the first two hash values, and the first three hash values. Among them, the first two hash values are the first 2 bits of the 8-bit hash values corresponding to all coordinate points on the road, and the first three hash values are the first 3 bits of the 8-bit hash values corresponding to all coordinate points on the road. One road ID may correspond to one first two hash values, such as Route1 contains ww, or may correspond to multiple first two hash values, such as Route3 contains wn, wp; the first two hash values in the same road ID correspond to one or more first three hash values.

[0065] Step S204, obtain the historical driving record of the target vehicle based on the communication connection, where the historical driving record is the driving record collected by the on-vehicle terminal device during the historical time period.

[0066] In this embodiment, the cloud can obtain information such as the historical driving record of the vehicle through the on-vehicle terminal device.

[0067] Next, in combination with Figure 4 Further describe in detail the above embodiments of the present invention. Figure 4 It is a flowchart of an optional vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention.

[0068] As Figure 4 shown, the position information, historical driving record, etc. of the vehicle must first be uploaded to the cloud through on-vehicle terminal devices such as on-vehicle terminal devices, so as to facilitate the subsequent analysis of the frequently traveled routes of the vehicle by the cloud.

[0069] Step S206, perform route analysis on multiple historical driving routes in the historical driving record to obtain the frequently traveled road segments of the target vehicle, where the frequently traveled road segments are the road segments where the driving frequency of the target vehicle during the historical time period is higher than the predetermined frequency threshold.

[0070] As Figure 4As shown in the figure, the cloud can analyze, based on the obtained historical driving records of the vehicle, which sections are the sections that the vehicle often drives on within a historical time period, and use the analyzed sections as the common driving sections of the vehicle.

[0071] It should be noted that here, by analyzing the historical driving records of the vehicle within a certain historical time period, it is determined which sections the vehicle often drives to, so as to obtain which map areas containing which sections have a higher usage rate for the vehicle, so as to generate a dedicated map package belonging to the vehicle in a targeted manner.

[0072] The historical time period here can be the past month, a quarter, a year, etc., and can be selected in combination with the actual situation on the basis of being able to objectively reflect the driving preferences of the vehicle.

[0073] According to the above embodiments of the present invention, in the above step S206, route analysis is performed on multiple historical driving routes in the historical driving records to obtain the common driving sections of the target vehicle, including: obtaining the first coordinate hash value of the first passing point in each historical driving route, where the first passing point is the passing point in the historical driving route, and the first coordinate hash value is the first hash value corresponding to the first coordinate of the first passing point; obtaining the second coordinate hash value of the second passing point in each predetermined section, where the second passing point is the passing point in the predetermined section, and the second coordinate hash value is the second hash value corresponding to the second coordinate of the second passing point, where the predetermined section is the section involved in the historical driving route; sequentially matching the first coordinate hash values in all historical driving routes with the second coordinate hash values in each predetermined section to obtain the matching frequency of each predetermined section, where the matching frequency is the number of times the second coordinate hash value is the same as the first coordinate hash value; calculating according to the matching frequency of each predetermined section and the total number of predetermined sections to obtain the driving frequency of the target vehicle on each predetermined section within the historical time period; determining the predetermined sections with a driving frequency higher than the predetermined frequency threshold as the common driving sections.

[0074] The following combines Figure 5 , Figure 6 , Figure 7 , Figure 8 , Figure 9 , Figure 10 and Figure 5 to elaborate in detail on the route analysis process of the cloud in the above embodiments of the present invention. Figure 6 is a schematic diagram of analyzing common driving sections according to an embodiment of the present invention; Figure 7 is a schematic diagram of analyzing the driving frequency of the vehicle on a certain section according to an embodiment of the present invention; Figure 8 is a schematic diagram of analyzing the driving frequency of the vehicle on another section according to an embodiment of the present invention;Figure 9 It is a schematic diagram of the statistical result of the driving frequency of a vehicle in each section according to an embodiment of the present invention; Figure 10 It is a schematic diagram of a vehicle-specific map-related file according to an embodiment of the present invention.

[0075] As Figure 5 shown, the cloud can first convert the GPS longitude and latitude coordinates of the passing points in each historical driving route (equivalent to the driving routes 1 to 5 in Figure 5 ) uploaded by the in-vehicle terminal device into 8-bit hash values, and then match them one by one with the 8-bit hash values in each predetermined section (equivalent to Route1 to Route5 in Figure 5 ) in the cloud map database to obtain the matching frequency of each predetermined section, that is, the number of times these historical driving routes have traveled on each predetermined section during the historical time period.

[0076] It should be noted that, in order to reduce the amount of data to be matched and improve the matching speed, the sections involved in the historical driving routes can be used as the predetermined sections for matching; for example, assuming that there are G sections (i.e., Route1 to Route100) recorded in the cloud map, but the vehicle only involves n sections, namely Route1... Routen, in the selected historical driving routes, then these n sections can be used as the predetermined sections. When analyzing the common routes of the vehicle, it is only necessary to match the hash values corresponding to the passing point coordinates in the historical driving routes with the hash values corresponding to the passing point coordinates in each predetermined section (in the embodiment of the present invention, the matching process is described by taking the 5 sections shown in Figure 5 , that is, Route1... Route5, as an example).

[0077] In a specific embodiment of the present invention, the first coordinate hash values in all historical driving routes are sequentially matched with the second coordinate hash values in each predetermined section to obtain the matching frequencies of the respective predetermined sections, including: determining the first ranking serial numbers of each first sub-hash value in the first coordinate hash value, and determining the second ranking serial numbers of each second sub-hash value in the second coordinate hash value, where the first sub-hash value is the first numerical value at each ranking serial number in the first coordinate hash value, and the second sub-hash value is the second pre-hash value numerical value at each ranking serial number in the second coordinate hash value; determining the hash value composed of all first sub-hash values with the first ranking serial number not less than the first predetermined ranking serial number in ascending order of the first ranking serial number as the first pre-hash value, and determining the hash value composed of all second sub-hash values with the second ranking serial number not less than the first predetermined ranking serial number in ascending order of the second ranking serial number as the second pre-hash value; sequentially matching all first pre-hash values with the second pre-hash values in each predetermined section, and determining the predetermined section that successfully matches the first pre-hash value as the target predetermined section; sequentially matching the first coordinate hash value corresponding to the first pre-hash value with the second coordinate hash value corresponding to each target predetermined section, and in the case of each successful match, increasing the matching frequency of the predetermined section by 1 to obtain the matching frequencies of the respective predetermined sections, where the initial value of the matching frequency of each predetermined section is 0, and a successful match means that the first pre-hash value is the same as the second pre-hash value.

[0078] Specifically, during the matching process, the first two or three hash values of the hash value corresponding to the historical driving route (i.e., the first leading hash value) can be sequentially matched with the first two or three hash values of the hash value corresponding to each predetermined section (i.e., the second leading hash value), that is, preliminary screening can be performed based on the general index file to first lock the section it may correspond to. For example, assuming that the first leading hash value is wq, corresponding to Route2 and Route5, then the complete 8-bit hash values (i.e., the second coordinate hash values) corresponding to Route2 and Route5 in the general data can be screened out, and then the complete 8-bit hash value (i.e., the first coordinate hash value) corresponding to the first leading hash value is matched with the second coordinate hash values of the screened sections (i.e., the target predetermined sections, which can be Route2 and Route5 here). In each case of successful matching, the matching frequency of the corresponding predetermined section is increased by 1 to obtain the matching frequencies of each predetermined section; that is, the driving frequencies of each predetermined section can be calculated by cumulative counting; for example, whenever the hash value corresponding to the passing point coordinate of a historical driving route is the same as the hash value corresponding to the passing point coordinate of a certain predetermined section, that is, when the matching is successful, the count of the driving frequency of this predetermined section can be incremented by 1, and if the matching is not successful, its count remains unchanged; such a matching method that first screens through the leading hash value and then performs precise matching using the complete hash value greatly reduces the workload of matching and improves the matching efficiency.

[0079] As Figure 6 shown, taking driving route 1 as an example, passing through Route1 and Route4, the coordinate hashes in driving route 1 will ultimately match the hashes in the general data files of Route1 and Route4, and the matching and counting are performed coordinate by coordinate. Taking driving route 1 matching Route1 as an example, assuming all are matched, the matching counts are all increased by 1. Assuming that Route1 contains 1000 coordinate points, the mean value of the corresponding 1000 matching counts is finally calculated; as Figure 7 shown, there is also a section of data in driving route 2 that will match Route1, and the matching count continues to accumulate; as Figure 8 shown, there is also a section of data in driving route 3 that will match Route1, and the matching count continues to accumulate. Such iterative calculations are performed until driving route 1, driving route 2, driving route 3, driving route 4, and driving route 5 have all completed the relevant matching calculations with Route1, Route2, Route3, Route4, and Route5; calculate the mean value of the matching counts of each road (i.e., the vehicle driving frequency), sort them from high to low, and count TOP 1 - TOP N to obtain the Figure 9 vehicle driving frequency statistics table shown.

[0080] In an alternative embodiment of the present invention, before determining that a predetermined road section with a driving frequency higher than a predetermined frequency threshold is a frequently traveled road section, the vehicle control method based on vehicle-cloud collaboration further includes: sorting the driving frequencies of each predetermined road section in descending order to obtain a sorting result; determining that the driving frequency at the second predetermined ranking number in the sorting result is the predetermined frequency threshold, where the second predetermined ranking number is the same or different from the first predetermined ranking number; or determining the frequency threshold set by the target object as the predetermined frequency threshold.

[0081] Specifically, as Figure 4 shown, the frequently traveled road sections of the vehicle (equivalent to Figure 4 the frequently traveled routes of the vehicle in Figure 4 ) can be screened out according to the driving frequencies of each predetermined road section (equivalent to Figure 9 ). When performing the screening here, that is, when determining the value of M in TOP M, the following methods may be included but are not limited to: 1) Sort the driving frequencies in descending order (such as Figure 9 ), and then select according to the driving frequency. For example, select the fixed TOP 3 routes, corresponding to Figure 9 the first 3 rows, and the value of M is 3; also select according to the specific hardware resources. If the hardware can only store and query 100 roads, only the TOP 100 routes can be selected, corresponding to Figure 9 the first 100 rows, and the value of M is 100; 2) It is also possible to select according to the value of the driving frequency. If the routes with a vehicle driving frequency exceeding 2 times are considered fixed routes, then it corresponds to the first row of the above table, and the value of M is 1.

[0082] Step S208: Generate a vehicle-specific map package for the target vehicle based on the frequently traveled road sections, and send the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call the cloud map.

[0083] In this embodiment, a vehicle-specific map package for the vehicle can be generated based on the frequently traveled road sections of the vehicle analyzed in the above steps and sent to the in-vehicle terminal device of the vehicle, so that the in-vehicle terminal device can control the target vehicle to drive based on the vehicle-specific map package; of course, if the current driving position of the vehicle is not included in the vehicle-specific map package, the cloud also provides a solution for the vehicle to remotely call the cloud map for driving, so that the vehicle can drive normally; this can save a large amount of storage space for vehicles with relatively fixed driving routes, without the need to store or update the full national map for a long time, and only need to store its own exclusive map package, which also improves the driving flexibility of the vehicle. When needed, it can call the cloud map to drive and is not limited to the area included in the vehicle-specific map package.

[0084] In a specific embodiment of the present invention, a vehicle-specific map package for a target vehicle is generated based on frequently traveled road segments, including: generating a vehicle-specific map for the target vehicle based on frequently traveled road segments; determining the general index file corresponding to the frequently traveled road segments as a dedicated index file, and determining the general data file corresponding to the frequently traveled road segments as a dedicated data file, wherein the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all roads in the cloud map, the general index information is used to search for roads, and the general road information is used to record the location and road conditions of roads; integrating the vehicle-specific map, the dedicated index file, and the dedicated data file to obtain a vehicle-specific map package.

[0085] As Figure 10 shown, the cloud can filter out the corresponding data from the cloud general index file and general data file according to the road ID of the frequently traveled road segments, generate the corresponding dedicated index file and dedicated data file, and generate a data format that can be stored and queried by the vehicle controller, such as an SQLite database file, and then integrate it with the vehicle-specific map generated based on the frequently traveled road segments to obtain the vehicle-specific map package of the vehicle.

[0086] As can be seen from the above, through the technical solution provided by the above embodiment of the present invention, a connection request can be sent to the in-vehicle terminal device of the target vehicle to establish a communication connection based on the connection request; obtain the historical driving record of the target vehicle based on the communication connection, wherein the historical driving record is the driving record collected by the in-vehicle terminal device during the historical time period; perform route analysis on multiple historical driving routes in the historical driving record to obtain the frequently traveled road segments of the target vehicle, wherein the frequently traveled road segments are the road segments where the driving frequency of the target vehicle during the historical time period is higher than a predetermined frequency threshold; generate a vehicle-specific map package for the target vehicle based on the frequently traveled road segments, and send the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call the cloud map, achieving the purpose of analyzing the historical driving routes of the vehicle by the cloud to obtain the frequently traveled road segments of the vehicle, realizing storing the vehicle-specific map package generated by the cloud based on the frequently traveled road segments of the vehicle and related files in the vehicle so that the vehicle can drive according to its dedicated map package during daily driving, and also providing the vehicle with the technical effect of being able to call the cloud map for driving when needed, saving the storage space for storing maps in the vehicle, improving the response speed, and the utilization rate of the maps stored in the vehicle.

[0087] Therefore, through the technical solution provided by the above embodiment of the present invention, the technical problems in the related art that for vehicles with relatively fixed driving routes, the map utilization rate of the national full-scale map package is low, and it occupies storage space, resulting in a slow response speed, are solved.

[0088] According to an embodiment of the present invention, there is also provided a method embodiment of a vehicle control method based on vehicle-cloud collaboration. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0089] Figure 11 is a flowchart of another optional vehicle control method based on vehicle-cloud collaboration according to an embodiment of the present invention, as Figure 11 shown, the method includes the following steps:

[0090] Step S1102, respond to the connection request sent by the cloud to establish a communication connection with the cloud based on the connection request.

[0091] Step S1104, receive the vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to the frequently traveled sections in the historical driving records of the target vehicle, and the frequently traveled sections are the sections where the driving frequency of the target vehicle in the historical time period is higher than a predetermined frequency threshold.

[0092] In this embodiment, the in-vehicle terminal device can receive the vehicle-specific map package sent by the cloud, and the vehicle controller can also download the special index file and special data file of the vehicle-specific map package through the in-vehicle terminal device and perform offline storage.

[0093] According to the above example of the present invention, in the above step S1104, receiving the vehicle-specific map package sent by the cloud based on the communication connection includes: responding to the data acquisition instruction sent by the cloud to acquire the historical driving records of the target vehicle in the historical time period based on the data acquisition instruction; uploading the historical driving records to the cloud to trigger the cloud to perform route analysis based on multiple historical driving routes in the historical driving records to obtain the frequently traveled sections of the target vehicle; receiving the vehicle-specific map package generated by the cloud based on the frequently traveled sections, where the vehicle-specific map package includes: generating the vehicle-specific map of the target vehicle based on the frequently traveled sections, the special index file corresponding to the frequently traveled sections, and the special data file, the special index file is used to record the special index information of the frequently traveled sections, the special data file is used to record the special road information of the frequently traveled sections, the special index information is used to find the frequently traveled sections, and the special road information is used to record the location and road conditions of the frequently traveled sections.

[0094] Specifically, the in-vehicle terminal device can first respond to the data acquisition instruction sent by the cloud, then obtain the historical driving records of the vehicle within the historical time period according to the instruction and upload them to the cloud. After the cloud performs route analysis, it then receives the vehicle-specific map package generated by the cloud.

[0095] Step S1106: Obtain the current position hash value of the target vehicle, where the current position hash value is a hash value calculated based on the current position coordinates of the target vehicle.

[0096] The following combines Figure 12 to elaborate in detail on the actual operation process of the vehicle in the above embodiments of the present invention. Figure 12 is a flowchart of a vehicle obtaining road information and running according to an embodiment of the present invention; as Figure 12 shown, during the running of the vehicle, the real-time position coordinates of the vehicle can be obtained, and the hash value corresponding to its coordinates can be calculated to facilitate subsequent querying of the corresponding road information based on the hash value.

[0097] Step S1108: When the current position hash value is found in the vehicle-specific map package, obtain the first driving road information corresponding to the current position hash value in the vehicle-specific map package; when the current position hash value is not found in the vehicle-specific map package, obtain the second driving road information corresponding to the current position hash value in the cloud map.

[0098] In this embodiment, when the vehicle actually performs predictive control, it can first query in the files in the vehicle-specific map package based on the current position hash value of the vehicle. If it can be found, query the corresponding road information (i.e., the first driving road information) in the vehicle-specific map package. If it cannot be found, send an online request to the cloud to query in the cloud general map file based on the current position hash value of the vehicle to obtain the corresponding road information (i.e., the second driving road information).

[0099] According to the above embodiments of the present invention, in the above step S1108, when the current position hash value is found in the vehicle-specific map package, obtain the first driving road information corresponding to the current position hash value in the vehicle-specific map package; when the current position hash value is not found in the vehicle-specific map package, obtain the second driving road information corresponding to the current position hash value in the cloud map, including: indexing according to the current position hash value in the dedicated index file of the vehicle-specific map package to obtain an index result; when the index result indicates that the current position hash value exists in the dedicated index file, determine the dedicated road information matching the current position hash value in the dedicated data file as the first driving road information; when the index result indicates that the current position hash value does not exist in the dedicated index file, determine the general road information corresponding to the current position hash value in the cloud map as the second driving road information.

[0100] As Figure 12 shown, the 8-bit hash value corresponding to the GPS position coordinates can be calculated first, and the first 3-bit hash value can be taken (the specific number of bits to be selected can be determined according to the actual situation, and no specific limit is set here); query in the proprietary index file through the first 3-bit hash value to confirm the corresponding road ID, so as to narrow the query range and reduce the matching workload; if it can be queried in the proprietary index file, then query in the corresponding proprietary data file to obtain the road information in front of the road; if it cannot be queried in the vehicle-specific map package, then query in the cloud map.

[0101] In a specific embodiment of the present invention, determining the general road information corresponding to the current position hash value in the cloud map as the second driving road information includes: obtaining the general index file and the general data file corresponding to the cloud map, where the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all roads in the cloud map, the general index information is used to find roads, and the general road information is used to record the position and road conditions of roads; when the current position hash value exists in the general index file, determining the general road information matching the current position hash value in the general data file as the second driving road information.

[0102] Specifically, after sending an online request to the cloud, it is also necessary to obtain its general index file and general data file first. First, query in the general index file according to the first 3-bit hash value of the hash value corresponding to the current position coordinates of the vehicle for preliminary screening, and then query in the selected general data file according to the hash value corresponding to the current position coordinates of the vehicle to obtain the corresponding road information.

[0103] Step S1110, controlling the target vehicle to drive based on the first driving road information or the second driving road information.

[0104] As Figure 12As shown, corresponding predictive cruise strategies can be executed according to the road information recorded in the first driving road information or the second driving road information, and the vehicle can be controlled to drive according to such strategies. For example, when the road information includes longitude: 119.231523, latitude: 36.717306, hash value: wwsbchjt, distance: 0 m, slope: +3% (uphill), the corresponding predictive cruise strategy may be that when the vehicle is about to enter an uphill section, the predictive cruise strategy may be to appropriately increase the engine torque to ensure that the vehicle has sufficient power to climb the slope, while avoiding sudden acceleration on the slope, which may cause an increase in fuel consumption. If the slope is relatively steep or long, it may be to reduce the vehicle speed in advance to reduce the kinetic energy loss at the top of the slope, thereby saving fuel. When the road information includes longitude: 119.230437, latitude: 36.717860, hash value: wwsbchkc, distance: 115 m, curvature: high (sharp bend), the predictive cruise strategy may be to automatically decelerate to ensure the vehicle passes through the bend safely. When the road information includes longitude: 119.229800, latitude: 36.718155, hash value: wwsbchk5, distance: 200 m, speed limit: 60 km / h, the predictive cruise strategy may be to automatically adjust the vehicle speed when encountering a speed limit section so that it does not exceed the speed indicated by the speed limit sign to ensure the safety of vehicle driving. If the current vehicle speed is higher than the speed limit, the system will implement deceleration measures in advance, using engine braking or gently stepping on the brake, which not only ensures safety but also avoids the discomfort caused by sudden deceleration.

[0105] As can be seen from the above, through the technical solution provided by the above embodiments of the present invention, a connection request sent by the cloud can be responded to, so as to establish a communication connection with the cloud based on the connection request; a vehicle-specific map package sent by the cloud is received based on the communication connection, wherein the vehicle-specific map package is a map package generated by the cloud according to the frequently traveled road sections in the historical driving records of the target vehicle, and the frequently traveled road sections are the road sections where the driving frequency of the target vehicle in the historical time period is higher than a predetermined frequency threshold; the current position hash value of the target vehicle is obtained, wherein the current position hash value is a hash value calculated according to the current position coordinates of the target vehicle; when the current position hash value is found in the vehicle-specific map package, the first driving road information corresponding to the current position hash value in the vehicle-specific map package is obtained, and when the current position hash value is not found in the vehicle-specific map package, the second driving road information corresponding to the current position hash value in the cloud map is obtained; the target vehicle is controlled to drive based on the first driving road information or the second driving road information, achieving the purpose of analyzing the historical driving route of the vehicle by the cloud to obtain the frequently traveled road sections of the vehicle, realizing storing the vehicle-specific map package generated by the cloud based on the frequently traveled road sections of the vehicle and related files in the vehicle so that the vehicle can drive according to its specific map package for daily driving, and also providing the vehicle with the technical effect of being able to call the cloud map for driving when needed, saving the storage space for storing the map in the vehicle, improving the response speed and the utilization rate of the map stored in the vehicle.

[0106] Therefore, through the technical solution provided by the above embodiments of the present invention, the technical problems in the related art that for vehicles with relatively fixed driving routes, the map utilization rate of the national full-scale map package is relatively low and it occupies storage space, resulting in a slow response speed, are solved.

[0107] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0108] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such an understanding, the technical solution of the present application, in essence, or the part that makes contributions to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application.

[0109] According to an embodiment of the present invention, there is also provided a vehicle-cloud collaboration-based vehicle control device for implementing the above vehicle-cloud collaboration-based vehicle control method. Figure 13 It is a schematic diagram of a vehicle-cloud collaboration-based vehicle control device according to an embodiment of the present invention, as Figure 13 shown. The device includes: a sending unit 131, a first obtaining unit 133, a second obtaining unit 135, and a generating unit 137. The vehicle-cloud collaboration-based vehicle control device will be described in detail below.

[0110] The sending unit 131 is configured to send a connection request to an in-vehicle terminal device of a target vehicle, so as to establish a communication connection with the in-vehicle terminal device based on the connection request.

[0111] The first obtaining unit 133 is configured to obtain a historical driving record of the target vehicle based on the communication connection, where the historical driving record is a driving record collected by the in-vehicle terminal device during a historical time period.

[0112] The second obtaining unit 135 is configured to perform route analysis on multiple historical driving routes in the historical driving record to obtain a frequently traveled section of the target vehicle, where the frequently traveled section is a section where the driving frequency of the target vehicle during the historical time period is higher than a predetermined frequency threshold.

[0113] The generating unit 137 is configured to generate a vehicle-specific map package for the target vehicle based on the frequently traveled section, and send the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to travel based on the vehicle-specific map package or call a cloud map.

[0114] It should be noted here that the above sending unit 131, first obtaining unit 133, second obtaining unit 135, and generating unit 137 correspond to steps S202 to S208 in the above embodiments. The instances and application scenarios implemented by the four units and the corresponding steps are the same, but are not limited to the content disclosed in the above embodiments.

[0115] As can be seen from the above, in the solution described in the above embodiments of the present invention, a connection request can be sent to the in-vehicle terminal device of the target vehicle by the sending unit to establish a communication connection with the in-vehicle terminal device based on the connection request; then, the first acquisition unit can be used to acquire the historical driving record of the target vehicle based on the communication connection, where the historical driving record is the driving record collected by the in-vehicle terminal device within the historical time period; then, the second acquisition unit can be used to perform route analysis on multiple historical driving routes in the historical driving record to obtain the frequently used driving sections of the target vehicle, where the frequently used driving sections are the sections where the driving frequency of the target vehicle within the historical time period is higher than a predetermined frequency threshold; finally, the generation unit can be used to generate a vehicle-specific map package for the target vehicle based on the frequently used driving sections, and send the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device can control the target vehicle to drive based on the vehicle-specific map package or call the cloud map, achieving the purpose of analyzing the historical driving route of the vehicle by the cloud to obtain the frequently used driving sections of the vehicle, realizing storing the vehicle-specific map package generated by the cloud based on the frequently used driving sections of the vehicle and related files in the vehicle so that the vehicle can drive daily according to its specific map package, and also providing the vehicle with the technical effect of being able to call the cloud map to drive when needed, saving the storage space for storing the map in the vehicle, improving the response speed and the utilization rate of the map stored in the vehicle.

[0116] Therefore, through the technical solution provided by the above embodiments of the present invention, the technical problem in the related art that for vehicles with relatively fixed driving routes, the map utilization rate of the national full-scale map package is low and it occupies storage space, resulting in a slow response speed, is solved.

[0117] In an alternative embodiment of the present invention, the second acquisition unit includes: a first acquisition module, configured to acquire the first coordinate hash value of the first waypoint in each historical driving route, where the first waypoint is the waypoint in the historical driving route, and the first coordinate hash value is the first hash value corresponding to the first coordinate of the first waypoint; a second acquisition module, configured to acquire the second coordinate hash value of the second waypoint in each predetermined section, where the second waypoint is the waypoint in the predetermined section, and the second coordinate hash value is the second hash value corresponding to the second coordinate of the second waypoint, where the predetermined section is the section involved in the historical driving route; a third acquisition module, configured to sequentially match the first coordinate hash values in all historical driving routes with the second coordinate hash values in each predetermined section to obtain the matching frequency of each predetermined section, where the matching frequency is the number of times the second coordinate hash value is the same as the first coordinate hash value; a fourth acquisition module, configured to calculate according to the matching frequency of each predetermined section and the total number of predetermined sections to obtain the driving frequency of the target vehicle on each predetermined section within the historical time period; a first determination module, configured to determine that the predetermined section with a driving frequency higher than the predetermined frequency threshold is the frequently used driving section.

[0118] In an alternative embodiment of the present invention, the third acquisition module includes: a first determination sub-module, configured to determine the first ranking serial number of each first sub-hash value in the first coordinate hash value, and determine the second ranking serial number of each second sub-hash value in the second coordinate hash value, where the first sub-hash value is the first numerical value at each ranking serial number in the first coordinate hash value, and the second sub-hash value is the second pre-hash value numerical value at each ranking serial number in the second coordinate hash value; a second determination sub-module, configured to determine the hash value formed by arranging in ascending order of the first ranking serial number all the first sub-hash values whose first ranking serial number is not less than the first predetermined ranking serial number as the first pre-hash value, and determine the hash value formed by arranging in ascending order of the second ranking serial number all the second sub-hash values whose second ranking serial number is not less than the first predetermined ranking serial number as the second pre-hash value; a first acquisition sub-module, configured to sequentially match all the first pre-hash values with the second pre-hash values in each predetermined road section, and the third determination sub-module sequentially matches all the first pre-hash values with the second pre-hash values in each predetermined road section to determine the predetermined road section that successfully matches the first pre-hash value as the target predetermined road section; a first acquisition sub-module, configured to sequentially match the first coordinate hash value corresponding to the first pre-hash value with the second coordinate hash value corresponding to each target predetermined road section, and in the case of each successful match, increase the matching frequency of the predetermined road section by 1 to obtain the matching frequencies of each predetermined road section, where the initial value of the matching frequency of each predetermined road section is 0, and a successful match means that the first pre-hash value is the same as the second pre-hash value.

[0119] In an alternative embodiment of the present invention, the vehicle control device based on vehicle-cloud collaboration further includes: a fifth acquisition module, configured to sort the driving frequencies of each predetermined road section in descending order to obtain a sorting result before determining that the predetermined road section with a driving frequency higher than the predetermined frequency threshold is a frequently traveled road section; a second determination module, configured to determine the driving frequency at the second predetermined ranking serial number in the sorting result as the predetermined frequency threshold, where the second predetermined ranking serial number is the same or different from the first predetermined ranking serial number; or, a third determination module, configured to determine the frequency threshold set by the target object as the predetermined frequency threshold.

[0120] In an alternative embodiment of the present invention, the generation unit includes: a generation module for generating a vehicle-specific map of the target vehicle based on common driving sections; a fourth determination module for determining the general index file corresponding to the common driving section as a dedicated index file and determining the general data file corresponding to the common driving section as a dedicated data file, where the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all roads in the cloud map, the general index information is used to search for roads, and the general road information is used to record the location and road conditions of the roads; a sixth acquisition module for integrating the vehicle-specific map, the dedicated index file, and the dedicated data file to obtain a vehicle-specific map package.

[0121] According to an embodiment of the present invention, there is also provided a vehicle control device based on vehicle-cloud collaboration for implementing the above-mentioned vehicle control method based on vehicle-cloud collaboration. Figure 14 It is a schematic diagram of an alternative vehicle control device based on vehicle-cloud collaboration according to an embodiment of the present invention, as Figure 14 shown. The device includes: a response unit 141, a receiving unit 143, a third acquisition unit 145, a fourth acquisition unit 147, and a control unit 149. The vehicle control device based on vehicle-cloud collaboration will be described in detail below.

[0122] The response unit 141 is used to respond to a connection request sent by the cloud to establish a communication connection with the cloud based on the connection request.

[0123] The receiving unit 143 is used to receive the vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to the common driving sections in the historical driving records of the target vehicle, and the common driving sections are the sections where the driving frequency of the target vehicle is higher than a predetermined frequency threshold within a historical time period.

[0124] The third acquisition unit 145 is used to acquire the current position hash value of the target vehicle, where the current position hash value is a hash value calculated based on the current position coordinates of the target vehicle.

[0125] The fourth acquisition unit 147 is used to acquire the first driving road information corresponding to the current position hash value in the vehicle-specific map package when the current position hash value is found in the vehicle-specific map package, and acquire the second driving road information corresponding to the current position hash value in the cloud map when the current position hash value is not found in the vehicle-specific map package.

[0126] The control unit 149 is used to control the target vehicle to drive based on the first driving road information or the second driving road information.

[0127] It should be noted here that the above-mentioned response unit 141, receiving unit 143, third acquisition unit 145, fourth acquisition unit 147 and control unit 149 correspond to steps S1102 to S1110 in the above embodiment. The instances and application scenarios realized by the five units and the corresponding steps are the same, but are not limited to the content disclosed in the above embodiment.

[0128] As can be seen from the above, in the solution described in the above embodiment of the present invention, the response unit can respond to the connection request sent by the cloud to establish a communication connection with the cloud based on the connection request; then the receiving unit is used to receive the vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to the frequently traveled road segments in the historical driving record of the target vehicle, and the frequently traveled road segments are the road segments where the driving frequency of the target vehicle in the historical time period is higher than a predetermined frequency threshold; then the third acquisition unit is used to acquire the current position hash value of the target vehicle, where the current position hash value is a hash value calculated according to the current position coordinates of the target vehicle; then, when the fourth acquisition unit queries the current position hash value in the vehicle-specific map package, the first driving road information corresponding to the current position hash value in the vehicle-specific map package is acquired, and when the current position hash value is not queried in the vehicle-specific map package, the second driving road information corresponding to the current position hash value in the cloud map is acquired; finally, the control unit is used to control the target vehicle to drive based on the first driving road information or the second driving road information, achieving the purpose of analyzing the historical driving route of the vehicle by the cloud to obtain the frequently traveled road segments of the vehicle, realizing the storage of the vehicle-specific map package generated by the cloud based on the frequently traveled road segments of the vehicle and related files to the vehicle so that the vehicle can drive according to its dedicated map package for daily driving, and also providing the vehicle with the technical effect of being able to call the cloud map for driving when needed, saving the storage space for storing the map in the vehicle, improving the response speed and the utilization rate of the map stored in the vehicle.

[0129] Therefore, through the technical solution provided by the above embodiment of the present invention, the technical problems in the related art that for vehicles with relatively fixed driving routes, the map utilization rate of the national full-scale map package is low and it occupies storage space, resulting in a slow response speed, are solved.

[0130] In an alternative embodiment of the present invention, the receiving unit includes: a response module, configured to respond to a data acquisition instruction sent by the cloud to acquire the historical driving record of the target vehicle within a historical time period based on the data acquisition instruction; a trigger module, configured to upload the historical driving record to the cloud to trigger the cloud to perform route analysis based on multiple historical driving routes in the historical driving record to obtain the frequently traveled sections of the target vehicle; a receiving module, configured to receive the vehicle-specific map package generated by the cloud based on the frequently traveled sections, where the vehicle-specific map package includes: a vehicle-specific map of the target vehicle generated based on the frequently traveled sections, a dedicated index file corresponding to the frequently traveled sections, and a dedicated data file, the dedicated index file is used to record the dedicated index information of the frequently traveled sections, the dedicated data file is used to record the dedicated road information of the frequently traveled sections, the dedicated index information is used to find the frequently traveled sections, and the dedicated road information is used to record the location and road conditions of the frequently traveled sections.

[0131] In an alternative embodiment of the present invention, the fourth acquisition unit includes: a seventh acquisition module, configured to perform indexing in the dedicated index file of the vehicle-specific map package according to the current position hash value to obtain an indexing result; a fifth determination module, configured to determine, when the indexing result indicates that the current position hash value exists in the dedicated index file, that the dedicated road information matching the current position hash value in the dedicated data file is the first driving road information; a sixth determination module, configured to determine, when the indexing result indicates that the current position hash value does not exist in the dedicated index file, that the general road information corresponding to the current position hash value in the cloud map is the second driving road information.

[0132] In an alternative embodiment of the present invention, the sixth determination module includes: a second acquisition sub-module, configured to acquire the general index file and the general data file corresponding to the cloud map, where the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all roads in the cloud map, the general index information is used to find roads, and the general road information is used to record the location and road conditions of the roads; a fourth determination sub-module, configured to determine, when the current position hash value exists in the general index file, that the general road information matching the current position hash value in the general data file is the second driving road information.

[0133] On the other hand, according to an embodiment of the present invention, there is also provided a vehicle control system based on vehicle-cloud collaboration, and the vehicle control system based on vehicle-cloud collaboration uses any one of the above vehicle control methods based on vehicle-cloud collaboration.

[0134] On the other hand, according to an embodiment of the present invention, there is also provided a computer-readable storage medium, and the computer-readable storage medium includes a stored program, where the program executes any one of the above vehicle control methods based on vehicle-cloud collaboration.

[0135] Optionally, in this embodiment, the above computer-readable storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the communication devices in the communication device group.

[0136] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: sending a connection request to the in-vehicle terminal device of the target vehicle to establish a communication connection with the in-vehicle terminal device based on the connection request; obtaining the historical driving record of the target vehicle based on the communication connection, where the historical driving record is the driving record collected by the in-vehicle terminal device during the historical time period; performing route analysis on multiple historical driving routes in the historical driving record to obtain the frequently traveled sections of the target vehicle, where the frequently traveled sections are the sections where the driving frequency of the target vehicle during the historical time period is higher than a predetermined frequency threshold; generating a vehicle-specific map package for the target vehicle based on the frequently traveled sections, and sending the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call the cloud map.

[0137] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: obtaining the first coordinate hash value of the first waypoint in each historical driving route, where the first waypoint is the waypoint in the historical driving route, and the first coordinate hash value is the first hash value corresponding to the first coordinate of the first waypoint; obtaining the second coordinate hash value of the second waypoint in each predetermined section, where the second waypoint is the waypoint in the predetermined section, and the second coordinate hash value is the second hash value corresponding to the second coordinate of the second waypoint, where the predetermined section is the section involved in the historical driving route; sequentially matching the first coordinate hash values in all historical driving routes with the second coordinate hash values in each predetermined section to obtain the matching frequency of each predetermined section, where the matching frequency is the number of times the second coordinate hash value is the same as the first coordinate hash value; calculating based on the matching frequency of each predetermined section and the total number of predetermined sections to obtain the driving frequency of the target vehicle on each predetermined section during the historical time period; determining that the predetermined section with a driving frequency higher than the predetermined frequency threshold is the frequently traveled section.

[0138] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining a first ranking sequence number of each first sub-hash value in the first coordinate hash value, and determining a second ranking sequence number of each second sub-hash value in the second coordinate hash value, where the first sub-hash value is the first numerical value at each ranking sequence number in the first coordinate hash value, and the second sub-hash value is the second previous hash value numerical value at each ranking sequence number in the second coordinate hash value; determining the hash value formed by arranging in ascending order of the first ranking sequence number all the first sub-hash values whose first ranking sequence number is not less than a first predetermined ranking sequence number as the first previous hash value, and determining the hash value formed by arranging in ascending order of the second ranking sequence number all the second sub-hash values whose second ranking sequence number is not less than the first predetermined ranking sequence number as the second previous hash value; sequentially matching all the first previous hash values with the second previous hash values in each predetermined road section, and determining the predetermined road section that matches successfully with the first previous hash value as the target predetermined road section; sequentially matching the first coordinate hash value corresponding to the first previous hash value with the second coordinate hash values corresponding to each target predetermined road section, and in the case of each successful match, increasing the matching frequency of the predetermined road section by 1 to obtain the matching frequencies of each predetermined road section, where the initial values of the matching frequencies of each predetermined road section are all 0, and a successful match means that the first previous hash value is the same as the second previous hash value.

[0139] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: sorting the driving frequencies of each predetermined road section in descending order to obtain a sorting result; determining the driving frequency at a second predetermined ranking sequence number in the sorting result as the predetermined frequency threshold, where the second predetermined ranking sequence number is a ranking sequence number the same as or different from the first predetermined ranking sequence number; or, determining the frequency threshold set by the target object as the predetermined frequency threshold.

[0140] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: generating a vehicle-specific map for the target vehicle based on the common driving road sections; determining the common index file corresponding to the common driving road sections as the specific index file, and determining the common data file corresponding to the common driving road sections as the specific data file, where the common index file is used to record the common index information of all roads in the cloud map, the common data file is used to record the common road information of all roads in the cloud map, the common index information is used to search for roads, and the common road information is used to record the location and road conditions of the roads; integrating the vehicle-specific map, the specific index file, and the specific data file to obtain a vehicle-specific map package.

[0141] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: respond to a connection request sent by the cloud to establish a communication connection with the cloud based on the connection request; receive a vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to the frequently traveled sections in the historical driving record of the target vehicle, and the frequently traveled sections are sections where the driving frequency of the target vehicle in the historical time period is higher than a predetermined frequency threshold; obtain the current position hash value of the target vehicle, where the current position hash value is a hash value calculated based on the current position coordinates of the target vehicle; when the current position hash value is found in the vehicle-specific map package, obtain the first driving road information corresponding to the current position hash value in the vehicle-specific map package, and when the current position hash value is not found in the vehicle-specific map package, obtain the second driving road information corresponding to the current position hash value in the cloud map; control the target vehicle to drive based on the first driving road information or the second driving road information.

[0142] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: respond to a data acquisition instruction sent by the cloud to obtain the historical driving record of the target vehicle in the historical time period based on the data acquisition instruction; upload the historical driving record to the cloud to trigger the cloud to perform route analysis based on multiple historical driving routes in the historical driving record to obtain the frequently traveled sections of the target vehicle; receive a vehicle-specific map package generated by the cloud based on the frequently traveled sections, where the vehicle-specific map package includes: generating a vehicle-specific map of the target vehicle based on the frequently traveled sections, a dedicated index file corresponding to the frequently traveled sections, and a dedicated data file, the dedicated index file is used to record the dedicated index information of the frequently traveled sections, the dedicated data file is used to record the dedicated road information of the frequently traveled sections, the dedicated index information is used to find the frequently traveled sections, and the dedicated road information is used to record the location and road conditions of the frequently traveled sections.

[0143] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: perform indexing in the dedicated index file of the vehicle-specific map package according to the current position hash value to obtain an index result; when the index result indicates that the current position hash value exists in the dedicated index file, determine that the dedicated road information matching the current position hash value in the dedicated data file is the first driving road information; when the index result indicates that the current position hash value does not exist in the dedicated index file, determine that the general road information corresponding to the current position hash value in the cloud map is the second driving road information.

[0144] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: obtaining a general index file and a general data file corresponding to a cloud map, where the general index file is used to record general index information of all roads in the cloud map, the general data file is used to record general road information of all roads in the cloud map, the general index information is used to find roads, and the general road information is used to record the location and road conditions of roads; in the case where the current location hash value exists in the general index file, determining the general road information matching the current location hash value in the general data file as the second driving road information.

[0145] According to another aspect of the embodiments of the present invention, there is also provided a processor, where the processor is used to run a program, and when the program runs, it executes the vehicle control method based on vehicle-cloud collaboration in any one of the above.

[0146] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, including computer instructions, and when the computer instructions are executed by a processor, they execute the vehicle control method based on vehicle-cloud collaboration in any one of the above.

[0147] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0148] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0149] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0150] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] In addition, in each embodiment of the present invention, each functional unit can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0152] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0153] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A vehicle control method based on vehicle-cloud collaboration, characterized in that, Including: Sending a connection request to the in-vehicle terminal device of the target vehicle to establish a communication connection with the in-vehicle terminal device based on the connection request; Obtaining the historical driving record of the target vehicle based on the communication connection, where the historical driving record is the driving record collected by the in-vehicle terminal device within a historical time period; Performing route analysis on multiple historical driving routes in the historical driving record to obtain the frequently traveled sections of the target vehicle, where the frequently traveled sections are the sections where the driving frequency of the target vehicle within the historical time period is higher than a predetermined frequency threshold; Generating a vehicle-specific map package for the target vehicle based on the frequently traveled sections, and sending the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call the cloud map; 2. The vehicle control method based on vehicle-cloud collaboration according to claim 1, wherein, Performing route analysis on multiple historical driving routes in the historical driving record to obtain the frequently traveled sections of the target vehicle, including: Obtaining the first coordinate hash value of the first waypoint in each historical driving route, where the first waypoint is the waypoint in the historical driving route, and the first coordinate hash value is the first hash value corresponding to the first coordinate of the first waypoint; Obtaining the second coordinate hash value of the second waypoint in each predetermined section, where the second waypoint is the waypoint in the predetermined section, and the second coordinate hash value is the second hash value corresponding to the second coordinate of the second waypoint, where the predetermined section is the section involved in the historical driving route; Sequentially matching the first coordinate hash values in all the historical driving routes with the second coordinate hash values in each predetermined section to obtain the matching frequency of each predetermined section, where the matching frequency is the number of times the second coordinate hash value is the same as the first coordinate hash value; Calculating based on the matching frequency of each predetermined section and the total number of predetermined sections to obtain the driving frequency of the target vehicle on each predetermined section within the historical time period; Determining the predetermined section with the driving frequency higher than the predetermined frequency threshold as the frequently traveled section; 3. The vehicle control method based on vehicle-cloud collaboration according to claim 2, wherein, Sequentially matching the first coordinate hash values in all the historical driving routes with the second coordinate hash values in each predetermined section to obtain the matching frequency of each predetermined section, including: Determining the first ranking order number of each first sub-hash value in the first coordinate hash value, and determining the second ranking order number of each second sub-hash value in the second coordinate hash value, where the first sub-hash value is the first value at each ranking order number in the first coordinate hash value, and the second sub-hash value is the second previous hash value at each ranking order number in the second coordinate hash value; Determine the first leading hash value by arranging in ascending order of the first ranking serial number all the first sub-hash values whose first ranking serial number is not less than the first predetermined ranking serial number, and determine the second leading hash value by arranging in ascending order of the second ranking serial number all the second sub-hash values whose second ranking serial number is not less than the first predetermined ranking serial number; Successively match all the first leading hash values with the second leading hash values in each of the predetermined road segments, and determine the predetermined road segment that successfully matches the first leading hash value as the target predetermined road segment; Successively match the first coordinate hash value corresponding to the first leading hash value with the second coordinate hash values corresponding to the respective target predetermined road segments. In the case of each successful match, increase the matching frequency of the target predetermined road segment by 1 to obtain the matching frequencies of the respective predetermined road segments, where the initial value of the matching frequency of each predetermined road segment is 0, and the successful match means that the first leading hash value is the same as the second leading hash value.

4. The vehicle control method based on vehicle-cloud collaboration according to claim 2, characterized in that Before determining the predetermined road segments with a driving frequency higher than the predetermined frequency threshold as the frequently traveled road segments, the method further includes: Sort the driving frequencies of the respective predetermined road segments in descending order to obtain a sorting result; Determine the driving frequency at the second predetermined ranking serial number in the sorting result as the predetermined frequency threshold, where the second predetermined ranking serial number is a ranking serial number the same as or different from the first predetermined ranking serial number; Or, Determine the frequency threshold set by the target object as the predetermined frequency threshold.

5. The vehicle control method based on vehicle-cloud collaboration according to claim 1, wherein Generate a vehicle-specific map package for the target vehicle based on the frequently traveled road segments, including: Generate a vehicle-specific map for the target vehicle based on the frequently traveled road segments; Determine the general index file corresponding to the frequently traveled road segments as a dedicated index file, and determine the general data file corresponding to the frequently traveled road segments as a dedicated data file, where the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all roads in the cloud map, the general index information is used to search for the roads, and the general road information is used to record the positions and road conditions of the roads; Integrate the vehicle-specific map, the dedicated index file, and the dedicated data file to obtain the vehicle-specific map package.

6. A vehicle control method based on vehicle-cloud collaboration, characterized in that, Including: Respond to a connection request sent by the cloud to establish a communication connection with the cloud based on the connection request; Receive the vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to the frequently traveled road segments in the historical driving record of the target vehicle, and the frequently traveled road segments are the road segments where the driving frequency of the target vehicle is higher than the predetermined frequency threshold within a historical time period; Obtain the current position hash value of the target vehicle, where the current position hash value is a hash value calculated according to the current position coordinates of the target vehicle; When the current location hash value is found in the vehicle-specific map package, obtain the first driving road information corresponding to the current location hash value in the vehicle-specific map package. When the current location hash value is not found in the vehicle-specific map package, obtain the second driving road information corresponding to the current location hash value in the cloud map; Control the target vehicle to drive based on the first driving road information or the second driving road information.

7. The vehicle control method based on vehicle-cloud collaboration according to claim 6, wherein Receive the vehicle-specific map package sent by the cloud based on the communication connection, including: Respond to the data acquisition instruction sent by the cloud to obtain the historical driving records of the target vehicle during the historical time period based on the data acquisition instruction; Upload the historical driving records to the cloud to trigger the cloud to perform route analysis based on multiple historical driving routes in the historical driving records to obtain the frequently used driving sections of the target vehicle; Receive the vehicle-specific map package generated by the cloud based on the frequently used driving sections, where the vehicle-specific map package includes: a vehicle-specific map of the target vehicle generated based on the frequently used driving sections, a dedicated index file corresponding to the frequently used driving sections, and a dedicated data file. The dedicated index file is used to record the dedicated index information of the frequently used driving sections, the dedicated data file is used to record the dedicated road information of the frequently used driving sections, the dedicated index information is used to find the frequently used driving sections, and the dedicated road information is used to record the location and road conditions of the frequently used driving sections.

8. The vehicle control method based on vehicle-cloud collaboration according to claim 6, wherein When the current location hash value is found in the vehicle-specific map package, obtain the first driving road information corresponding to the current location hash value in the vehicle-specific map package. When the current location hash value is not found in the vehicle-specific map package, obtain the second driving road information corresponding to the current location hash value in the cloud map, including: Index according to the current location hash value in the dedicated index file of the vehicle-specific map package to obtain an index result; When the index result indicates that the current location hash value exists in the dedicated index file, determine the dedicated road information matching the current location hash value in the dedicated data file as the first driving road information; When the index result indicates that the current location hash value does not exist in the dedicated index file, determine the general road information corresponding to the current location hash value in the cloud map as the second driving road information.

9. The vehicle control method based on vehicle-cloud collaboration according to claim 8, wherein, Determine the general road information corresponding to the current location hash value in the cloud map as the second driving road information, including: Obtain the general index file and general data file corresponding to the cloud map, where the general index file is used to record the general index information of all roads in the cloud map, the general data file is used to record the general road information of all roads in the cloud map, the general index information is used to find the roads, and the general road information is used to record the location and road conditions of the roads; When the current position hash value exists in the general index file, determine that the general road information in the general data file that matches the current position hash value is the second driving road information.

10. A vehicle control device based on vehicle-cloud collaboration, characterized in that, Including: A sending unit, configured to send a connection request to an in-vehicle terminal device of a target vehicle, so as to establish a communication connection with the in-vehicle terminal device based on the connection request; A first obtaining unit, configured to obtain a historical driving record of the target vehicle based on the communication connection, where the historical driving record is a driving record collected by the in-vehicle terminal device within a historical time period; A second obtaining unit, configured to perform route analysis on multiple historical driving routes in the historical driving record to obtain a frequently traveled section of the target vehicle, where the frequently traveled section is a section of the target vehicle with a driving frequency higher than a predetermined frequency threshold within the historical time period; A generating unit, configured to generate a vehicle-specific map package of the target vehicle based on the frequently traveled section, and send the vehicle-specific map package to the in-vehicle terminal device based on the connection request, so that the in-vehicle terminal device controls the target vehicle to drive based on the vehicle-specific map package or call a cloud map.

11. A vehicle control device based on vehicle-cloud collaboration, characterized in that, Including: A response unit, configured to respond to a connection request sent by the cloud, so as to establish a communication connection with the cloud based on the connection request; A receiving unit, configured to receive a vehicle-specific map package sent by the cloud based on the communication connection, where the vehicle-specific map package is a map package generated by the cloud according to a frequently traveled section in the historical driving record of the target vehicle, and the frequently traveled section is a section of the target vehicle with a driving frequency higher than a predetermined frequency threshold within the historical time period; A third obtaining unit, configured to obtain a current position hash value of the target vehicle, where the current position hash value is a hash value calculated according to the current position coordinates of the target vehicle; A fourth obtaining unit, configured to obtain first driving road information corresponding to the current position hash value in the vehicle-specific map package when the current position hash value is found in the vehicle-specific map package, and obtain second driving road information corresponding to the current position hash value in the cloud map when the current position hash value is not found in the vehicle-specific map package; A control unit, configured to control the target vehicle to drive based on the first driving road information or the second driving road information.

12. A computer program product, comprising computer instructions, characterized in that, When the computer instructions are executed by a processor, execute the vehicle control method based on vehicle-cloud collaboration according to any one of claims 1 to 9.

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