WO2020140943A1

WO2020140943A1 - Method for configuring driving parameters and server

Info

Publication number: WO2020140943A1
Application number: PCT/CN2020/070102
Authority: WO
Inventors: 胡玉双
Original assignee: 中国移动通信有限公司研究院; 中国移动通信集团有限公司
Priority date: 2019-01-02
Filing date: 2020-01-02
Publication date: 2020-07-09
Also published as: CN111464933B; CN111464933A

Abstract

The present disclosure relates to the technical field of the Internet of Vehicles, and provided thereby are a method for configuring driving parameters and a server. According to driving data information provided by an application service end of a vehicle, first network data provided by an operation administration and maintenance (OAM) server and/or second network data provided by a network function (NF) server, acquiring network prediction parameter information of the vehicle for automatic driving; and sending the network prediction parameter information to the application service end of the vehicle.

Description

Driving parameter configuration method and server

Cross-reference of related applications

This application claims the priority of Chinese Patent Application No. 201910000978.0 filed in China on January 2, 2019, the entire contents of which are hereby incorporated by reference.

Technical field

The present disclosure relates to the field of Internet of Vehicle technology, and in particular, to a driving parameter configuration method and server.

Background technique

Autonomous vehicles now use video cameras, radar sensors, and laser rangefinders to understand the surrounding traffic conditions while driving, and navigate the road ahead through a detailed map (maps collected by manned cars) . That is to say, the current self-driving car can only drive on the existing planned route in a state where the wireless network is in good condition, and does not perceive the degree of road congestion ahead.

For example, on a road, the peak commute time is very congested. At this time, if there are too many autopilot users, it will affect the network status, and in severe cases, it will freeze, and even affect the safety of autopilot users. But stagger the peak period and the network is lightly loaded, and the user experience will be very good. Currently, self-driving vehicles cannot automatically switch between driving roads or manual driving based on network congestion. If the advancing vehicle is automatically adjusted according to the network performance of the upcoming NG-Radio Access Network (RAN), it will be very beneficial to autonomous driving.

Summary of the invention

The purpose of the technical solution of the present disclosure is to provide a driving parameter configuration method and a server, which are used to solve the problem that the automatic driving vehicle in the related art cannot be automatically adjusted according to network performance.

To solve the above technical problems, the embodiments of the present disclosure provide a driving parameter configuration method, which is applied to the network analysis server in the vehicle pair X. The method includes:

According to the driving data information provided by the application server of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function, obtain network prediction parameter information of the vehicle for automatic driving;

Send the network prediction parameter information to the application server of the vehicle.

An embodiment of the present disclosure also provides a driving parameter configuration method, which is applied to the application server in the vehicle-to-X. The method includes:

Obtain network prediction parameter information for automatic driving sent by the network analysis server.

An embodiment of the present disclosure also provides a server, wherein the server is a network analysis server used in the vehicle pair X, including a processor and a transceiver,

The processor is used to obtain the vehicle for automatic driving according to the driving data information provided by the application server of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function Network prediction parameter information;

The transceiver is used to send the network prediction parameter information to the application server of the vehicle.

An embodiment of the present disclosure also provides a server, which is applied to the application server in the vehicle-to-X, and includes a processor and a transceiver,

The transceiver is used to obtain network prediction parameter information for automatic driving sent by the network analysis server.

An embodiment of the present disclosure also provides a server, including a memory, a processor, and a computer program stored on the memory and executable on the processor; wherein, when the processor executes the program, it is implemented as described above The mentioned driving parameter configuration method.

An embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored, where the program implements the steps in the driving parameter configuration method described above when executed by a processor.

At least one of the above technical solutions of the present disclosure has the following beneficial effects: by driving data information provided by the application service end of the vehicle, the first network data provided by the OAM server and/or the second network provided by the network function NF server Data to obtain network prediction parameter information of the vehicle for automatic driving; and send the network prediction parameter information to the application server of the vehicle, so that the application server of the vehicle can automatically adjust according to the network prediction parameter information.

BRIEF DESCRIPTION

1 is a block diagram of a wireless communication system to which an embodiment of the present disclosure can be applied;

2 is a schematic flowchart of a driving parameter configuration method applied to a network analysis server in a vehicle pair X according to an embodiment of the present disclosure;

FIG. 3 is a schematic flowchart of a driving parameter configuration method applied to an application server in a vehicle pair X according to an embodiment of the present disclosure;

4 shows a schematic structural diagram of a server according to an embodiment of the present disclosure;

5 is a schematic structural diagram of a server according to another embodiment of the present disclosure;

6 shows a schematic structural diagram of a server according to yet another embodiment of the present disclosure;

7 is a schematic structural diagram of a server according to another embodiment of the present disclosure;

Figure 8 shows the TS23.503 5G NWDA network architecture diagram;

FIG. 9 shows a schematic flow chart of AF going to NWDA to request network performance information.

detailed description

In order to make the technical problems, technical solutions and advantages to be solved by the present disclosure more clear, the following will describe in detail with reference to the accompanying drawings and specific embodiments.

The terms "first", "second", etc. in the specification and claims of the present disclosure are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way are interchangeable under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, processes, methods, systems, products or devices that contain a series of steps or units need not be limited to those clearly listed Those steps or units may instead include other steps or units that are not explicitly listed or inherent to these processes, methods, products, or equipment. In the description and claims, "and/or" means at least one of the connected objects.

The technology described in this article is not limited to Long Time Evolution (LTE)/LTE Evolution (LTE-Advanced, LTE-A) systems, and can also be used in various wireless communication systems, such as Code Division Multiple Access (Code Division Division) Multiple Access (CDMA), Time Division Multiple Access (Time Division Multiple Access, TDMA), Frequency Division Multiple Access (Frequency Division Multiple Access, FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), single carrier frequency Multiple access (Single-carrier Frequency-Division Multiple Access, SC-FDMA) and other systems. The terms "system" and "network" are often used interchangeably. The CDMA system can implement radio technologies such as CDMA2000, Universal Terrestrial Radio Access (UTRA) and so on. UTRA includes Wideband CDMA (Wideband Code Multiple Access (WCDMA) and other CDMA variants. TDMA systems can implement radio technologies such as Global System for Mobile (GSM). OFDMA system can realize such as Ultra Mobile Broadband (Ultra Mobile Broadband, UMB), Evolved UTRA (Evolution-UTRA, E-UTRA), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Flash-OFDM Etc. radio technology. UTRA and E-UTRA are part of the Universal Mobile Telecommunications System (UMTS). LTE and more advanced LTE (such as LTE-A) are new UMTS versions that use E-UTRA. UTRA, E-UTRA, UMTS, LTE, LTE-A, and GSM are described in documents from an organization named "3rd Generation Partnership Project (3GPP)". CDMA2000 and UMB are described in documents from an organization named "3rd Generation Partnership Project 2" (3GPP2). The technology described herein can be used for the systems and radio technologies mentioned above as well as other systems and radio technologies. However, the following description describes the NR system for example purposes, and NR terminology is used in most of the description below, although these techniques can also be applied to applications other than NR system applications.

The following description provides examples without limiting the scope, applicability, or configuration set forth in the claims. Changes may be made in the function and arrangement of the discussed elements without departing from the spirit and scope of the present disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.

Please refer to FIG. 1, which shows a block diagram of a wireless communication system to which an embodiment of the present disclosure can be applied. The wireless communication system includes user equipment 11 and network equipment 12. The user equipment 11 may also be called a terminal or a user terminal (User Equipment, UE), and the user equipment 11 may be a network analysis server in the car-to-X, an application server in the car-to-X, a mobile phone, and a tablet (Tablet Personal) Computer), laptop (Laptop), personal digital assistant (Personal Digital Assistant, PDA), mobile Internet device (Mobile Internet Device (MID), wearable device (Wearable Device) or vehicle-mounted equipment and other terminal side devices, It should be noted that the specific type of the user equipment 11 is not limited in the embodiments of the present disclosure. The network device 12 may be a base station and/or a core network element, wherein the base station may be a base station of 5G and later versions (for example: gNB, 5G, NR, etc.), or a base station in other communication systems (for example: eNB, WLAN Access point, or other access points, etc.), where the base station may be called Node B, evolved Node B, access point, base transceiver station (Base Transceiver Station, BTS), radio base station, radio transceiver, basic Service set (Basic Service Set, BSS), extended service set (Extended Service Set, ESS), Node B, evolved Node B (eNB), home Node B, home evolved Node B, WLAN access point, WiFi node or In some other suitable terminology in the field, as long as the same technical effect is achieved, the base station is not limited to a specific technical vocabulary. It should be noted that in the embodiments of the present disclosure, only the base station in the NR system is used as an example, but The specific type of base station is not limited.

The base station may communicate with the user equipment 11 under the control of the base station controller. In various examples, the base station controller may be part of the core network or some base stations. Some base stations can communicate control information or user data with the core network through the backhaul. In some examples, some of these base stations may communicate with each other directly or indirectly through a backhaul link, which may be a wired or wireless communication link. The wireless communication system can support operation on multiple carriers (waveform signals of different frequencies). Multi-carrier transmitters can transmit modulated signals on these multiple carriers simultaneously. For example, each communication link may be a multi-carrier signal modulated according to various radio technologies. Each modulated signal can be sent on a different carrier and can carry control information (eg, reference signals, control channels, etc.), overhead information, data, etc.

The base station can wirelessly communicate with the user equipment 11 via one or more access point antennas. Each base station can provide communication coverage for its respective coverage area. The coverage area of an access point may be divided into sectors that only constitute a part of the coverage area. The wireless communication system may include different types of base stations (eg, macro base stations, micro base stations, or pico base stations). The base station may also utilize different radio technologies, such as cellular or WLAN radio access technologies. The base station may be associated with the same or different access network or operator deployment. The coverage areas of different base stations (including the coverage areas of the same or different types of base stations, the coverage areas using the same or different radio technologies, or the coverage areas belonging to the same or different access networks) may overlap.

The communication link in the wireless communication system may include an uplink for carrying uplink (Uplink, UL) transmission (for example, from the user equipment 11 to the network device 12), or a downlink for carrying downlink (Downlink, DL) ) Transmission (e.g., from the network device 12 to the user equipment 11) downlink. UL transmission may also be referred to as reverse link transmission, and DL transmission may also be referred to as forward link transmission. Downlink transmission can be performed using licensed frequency bands, unlicensed frequency bands, or both. Similarly, uplink transmissions can be performed using licensed frequency bands, unlicensed frequency bands, or both.

The following explains the abbreviations that may be involved:

NF: Network Function (module).

NWDA: network analysis logic function module of network, which analyzes the specific network information status of contracted users to other network elements according to the slice granularity.

NEF: network capability opening function.

UDM: user data management User data management, similar to the HSS function in 4G, is the UE's contract database.

UDR: unified data repository unified data storage library, 5G system allows UDM, PCF and NEF to store data in UDR, including UDM and PCF subscription data and strategy data, for NEF open data structure and application data (including for (Packet Flow Description (PFD) for application detection, application request information for multiple UEs).

OAM: operation, administration and maintenance. According to the actual needs of the operator's network operation, the network management is usually divided into three categories: operation, management, and maintenance, referred to as OAM. The operation mainly completes the daily network and business analysis, prediction, planning and configuration work; the maintenance is mainly the daily operation activities of the network and its business testing and fault management.

AF: application function. It can be a third-party application or an operator's own business. If it is a third-party application, AF needs to interact with NWDA or UDM through NEF.

Referring to FIG. 8, the following describes the network architecture in which the driving parameter configuration method of the embodiment of the present disclosure is located with reference to FIG. 8.

The application of NWDA here can be to provide specific network data analysis by slice to other network function modules. NWDA can analyze the specific network information status divided by slices with contract information to other network elements. Other network elements can also directly collect all required network status analysis information from NWDA.

Here, NWDAF is a service interface, and AF can subscribe to it or notify it of AF network performance information.

NWDA obtains information from NF, OAM or AF, then analyzes offline, and regularly updates network prediction parameter information. NWDA can save results locally or in UDR.

It can be understood that NWDA may be the network analysis server mentioned below, and AF may be the application server mentioned below.

The following information supports network performance prediction:

Table 1: AFs and service data for predicting network performance information

Table 2: Network data of NFs and predicted network performance information in 5G system

Table 3: OAM and network data for predicting network performance information in 5G systems

Referring to FIG. 2 below, an embodiment of the present disclosure provides a driving parameter configuration method, which is applied to a network analysis server in a vehicle pair X. The method includes:

Step S21, according to the driving data information provided by the application server of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function, obtaining the network prediction parameters of the vehicle for automatic driving information;

Here, the network analysis server analyzes/predicts the network performance of the upcoming NG-RAN can consider the following factors, such as the speed and direction of the vehicle or the upcoming location, information related to the network performance (load information based on time and space information ), based on the driving data information provided by the application server of the vehicle, the first network data provided by the OAM server and/or the second network data provided by the network function NF server, the network prediction for the vehicle for automatic driving can be obtained Parameter information.

Here, the driving data information may include the driving speed of the vehicle.

The first network data may include load information of the wireless access network and/or mobile network coverage information.

The second network data may include location information, quality of service QoS flow bit rate, QoS flow identification (QoS Flow ID, QFI) QFI, QoS flow packet delay rate and/or QoS flow packet error rate.

Here, the network prediction parameter information may include at least one of the following:

Predict network service quality Qos, predict vehicle travel speed, predict vehicle travel direction, network load information within a preset time period and network load information within a preset area.

Step S22: Send the network prediction parameter information to the application server of the vehicle.

Here, the network analysis server acquires the network prediction parameter information of the vehicle for automatic driving and sends it to the application server of the vehicle, so that the application server of the vehicle can decide whether to be in the upcoming NG-RAN according to the predicted network prediction parameter information Maintain the automatic driving mode and take specific decision-making behaviors, such as switching the car from the automatic driving state to manual driving, or changing the driving path according to the multi-path network performance information, so that the application server of the vehicle performs automatic based on the network prediction parameter information Adjustment.

In an embodiment of the present disclosure, the method may further include: obtaining a driving parameter analysis request sent by the application server; wherein, in the step of sending the network prediction parameter information to the application server of the vehicle, responding to the The driving parameter analysis request sends the network prediction parameter information to the application server of the vehicle.

Here, the driving parameter configuration method applied to the network analysis server in the vehicle pair X according to the embodiment of the present disclosure may be that the network prediction parameter information is sent to the application server of the vehicle according to the driving parameter analysis request sent by the application server .

In an embodiment of the present disclosure, step S22, in the step of sending the network prediction parameter information to the application server of the vehicle, the network prediction parameter information may be sent through a service interface or a capability opening function NEF module To the application server of the vehicle.

Here, the application server (AF shown in FIGS. 8 and 9 or V2Xserver) can directly request or reserve network prediction parameter information from the network analysis server (NWDA shown in FIGS. 8 and 9) through the service interface. The network analysis server can also exchange information through NEF and NWDAF to provide analysis information related to predicted network performance to the application server.

In the embodiment of the present disclosure, after acquiring the network prediction parameter information of the vehicle for automatic driving, the method may further include: storing the network prediction parameter information locally, or storing the network prediction parameter information to a unified Data repository UDR.

Here, the network analysis server may store the network prediction parameter information locally or to the unified data storage UDR. For example, when the amount of UE information is too large, the network prediction parameter information may be selected to be stored in the unified data storage UDR.

The driving parameter configuration method of the embodiment of the present disclosure will be described below with reference to FIG. 9.

1. NWDA can collect information from NF (shown in Table 2) and then perform data analysis. These data analysis results (network prediction parameter information) are opened to AF through NEF.

2. Simultaneously with the first step, NWDA collects NG-RAN and other network information (shown in Table 3) from OAM and then performs data analysis, and the results of these data analysis are opened to AF through NEF.

3. It can happen at the same time as the first and second steps. NWDA collects application information (shown in Table 1) from AF and then performs data analysis. AF provides the data to NWDA through NEF.

After collecting network information from NFs, AF and OAM, NWDA can derive a set of network performance parameters offline, which consists of the following parts:

a) The value of 5GS QoS parameter combination, such as 5QI (packet delay budget, packet error rate, average window, maximum data burst capacity), guaranteed traffic bit rate, maximum flow bit rate, maximum packet loss rate, etc.;

b) Application identifier;

c) Effective space conditions;

d) Time effective conditions;

e) NWDAF event ID.

4. In order to create a request, AF can trigger a service request (for example, Nnwdaf_AnalyticsInfo_Request service request) through NEF to NWDA. For the request data, please refer to the definition in Table 1.

5. The NWDA trigger reaction service (for example, Nnwdaf_AnalyticsInfo_Request reaction service) operates to the AF through NEF, and then NWDA gives the AF the network prediction parameter information needed by the AF.

It can be understood that the NWDA here may be the network analysis server described above, and the AF may be the application server described above.

Referring to FIG. 3, an embodiment of the present disclosure also provides a driving parameter configuration method, which is applied to the application server in the vehicle pair X. The method includes:

Step S31: Acquire network prediction parameter information for automatic driving sent by the network analysis server.

It can be understood that the network prediction parameter information in the driving parameter configuration method applied to the application server in the vehicle pair X described above can be sent by the network analysis server. Therefore, the embodiment of the present disclosure is applied to the vehicle pair X The driving parameter configuration method on the application server side and the driving parameter configuration method applied to the network analysis server in the vehicle-to-X described above are corresponding to each other, and have corresponding beneficial effects. In order to avoid repetition, they will not be repeated here.

Optionally, the method may further include:

According to the network prediction parameter information, determine the current driving route, driving parameters and/or driving mode, wherein the driving mode includes manual driving and automatic driving.

Optionally, the network prediction parameter information includes at least one of the following:

Optionally, before acquiring the network prediction parameter information for automatic driving sent by the network analysis server, the method may further include:

Send a driving parameter analysis request to the network analysis server.

Optionally, in the step of sending a driving parameter analysis request to the network analysis server, a driving parameter analysis request may be sent to the network analysis server through a service interface or a capability opening function NEF module;

In the step of obtaining the network prediction parameter information for automatic driving sent by the network analysis server, the network prediction parameter information for automatic driving sent by the network analysis server may be obtained through a service interface or a capability opening function NEF module.

Referring to FIG. 4, an embodiment of the present disclosure further provides a server 40, wherein the server 40 is a network analysis server applied in the vehicle-to-X, including a processor 41 and a transceiver 42,

The processor 41 is used to acquire the vehicle for automatic use according to the driving data information provided by the application service end of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function Driving network prediction parameter information;

The transceiver 42 is used to send the network prediction parameter information to the application server of the vehicle.

The server 40 of the embodiment of the present disclosure can implement various processes in the above method embodiment applied to the network analysis server in the vehicle pair X, and has corresponding beneficial effects. In order to avoid repetition, it will not be repeated here.

Here, the network prediction parameter information includes at least one of the following:

Here, the driving data information includes the driving speed of the vehicle.

Here, the first network data includes load information of the wireless access network and/or mobile network coverage information.

Here, the second network data includes location information, quality of service QoS flow bit rate, QFI, QoS flow packet delay rate and/or QoS flow packet error rate.

Here, the processor 41 is also used to obtain a driving parameter analysis request sent by the application server;

Wherein, the transceiver 42 is specifically configured to send the network prediction parameter information to the application server of the vehicle in response to the driving parameter analysis request.

Here, the transceiver 42 is also specifically used to send the network prediction parameter information to the application server of the vehicle through a service interface or a capability opening function NEF module.

Here, the processor 41 is also used to store the network prediction parameter information locally, or store the network prediction parameter information to the unified data storage UDR.

Referring to FIG. 5, an embodiment of the present disclosure also provides a server 50, which is applied to an application server in the vehicle-to-X, and includes a processor 51 and a transceiver 52,

The transceiver 52 is used to obtain network prediction parameter information for automatic driving sent by the network analysis server.

The server 50 of the embodiment of the present disclosure can implement various processes in the above method embodiment applied to the application server in the vehicle pair X, and has corresponding beneficial effects. In order to avoid repetition, details are not repeated here.

Optionally, the processor is configured to determine the current driving route, driving parameters and/or driving mode according to the network prediction parameter information, where the driving mode includes manual driving and automatic driving.

Optionally, the transceiver 52 is further configured to send a driving parameter analysis request to the network analysis server.

Optionally, the transceiver 52 is specifically configured to send a driving parameter analysis request to the network analysis server through a service interface or a capability opening function NEF module;

The transceiver 52 is also specifically used to obtain network prediction parameter information for automatic driving sent by the network analysis server through a service interface or a capability opening function NEF module.

As shown in FIG. 6, an embodiment of the present disclosure further provides a server, which may be a network analysis server in the vehicle pair X. As shown in FIG. 6, the server includes: a processor 600 and a transceiver 610.

In the embodiment of the present disclosure, the server may further include: a memory 620 connected to the processor 600 through a bus interface. The transceiver 610 is connected to the processor 600 through a bus interface. The memory 620 may store programs and data used by the processor when performing operations. The processor 600 can call and execute the programs and data stored in the memory 620;

The processor 600 is used to acquire the vehicle for automatic use according to the driving data information provided by the application service end of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function Driving network prediction parameter information;

The transceiver 610 is used to send the network prediction parameter information to the application server of the vehicle.

Here, as an optional manner, the network prediction parameter information includes at least one of the following:

Here, as an optional manner, the driving data information includes the driving speed of the vehicle.

Here, as an optional manner, the first network data includes load information of the wireless access network and/or mobile network coverage information.

Here, as an optional manner, the second network data includes location information, quality of service QoS flow bit rate, QFI, QoS flow packet delay rate, and/or QoS flow packet error rate.

Here, as an optional manner, the processor 600 is also used to obtain a driving parameter analysis request sent by the application server;

Wherein, the transceiver 610 is specifically configured to send the network prediction parameter information to the application server of the vehicle in response to the driving parameter analysis request.

Here, as an optional method, the transceiver 610 is also specifically used to send the network prediction parameter information to the application server of the vehicle through a service interface or a capability opening function NEF module.

Here, as an optional manner, the processor 600 is further configured to store the network prediction parameter information locally, or store the network prediction parameter information to the unified data storage UDR.

Wherein, in FIG. 6, the bus architecture may include any number of interconnected buses and bridges, specifically one or more processors represented by the processor 600 and various circuits of the memory represented by the memory 620 are linked together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, etc., which are well known in the art, and therefore, they will not be described further herein. The bus interface provides an interface. The transceiver 610 may be a plurality of elements, that is, including a transmitter and a transceiver, and provides a unit for communicating with various other devices on a transmission medium. The processor 600 is responsible for managing the bus architecture and general processing, and the memory 620 may store data used by the processor 600 when performing operations.

The server embodiment of the present disclosure corresponds to the above embodiment of the driving parameter configuration method applied to the network analysis server in the vehicle pair X. All the implementation means in the above method embodiment are applicable to the embodiment of the server, and Can achieve the same technical effect.

Those skilled in the art can understand that all or part of the steps of the above embodiments can be completed by hardware, or can be completed by instructing related hardware through a computer program, and the computer program includes instructions to perform part or all of the steps of the above method. ; And the computer program may be stored in a readable storage medium, the storage medium may be any form of storage medium.

As shown in FIG. 7, this embodiment provides another server, including:

A processor 71; and a memory 73 connected to the processor 71 through a bus interface 72, the memory 73 is used to store programs and data used by the processor 71 when performing operations, and the processor 71 calls and executes The programs and data stored in the memory 73. The transceiver 74 is connected to the bus interface 72.

The transceiver 74 is used to obtain network prediction parameter information for automatic driving sent by the network analysis server.

Here, the processor 71 is configured to determine the current driving route, driving parameters and/or driving mode according to the network prediction parameter information, where the driving mode includes manual driving and automatic driving.

Here, the transceiver 74 is also used to send a driving parameter analysis request to the network analysis server.

Here, the transceiver 74 is specifically used to send a driving parameter analysis request to the network analysis server through a service interface or a capability opening function NEF module;

The transceiver 74 is also specifically used to obtain network prediction parameter information for automatic driving sent by a network analysis server through a service interface or a capability opening function NEF module.

It should be noted that, in FIG. 7, the bus architecture may include any number of interconnected buses and bridges. Specifically, one or more processors represented by the processor 71 and various circuits of the memory represented by the memory 73 are linked together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, etc., which are well known in the art, and therefore, they will not be described further herein. The bus interface provides an interface. The transceiver 74 may be a plurality of elements, including a transmitter and a transceiver, and provides a unit for communicating with various other devices on a transmission medium. For different user devices, the user interface 75 may also be an interface that can be externally connected to the required device. The connected devices include, but are not limited to, a keypad, a display, a speaker, a microphone, and a joystick. The processor 71 is responsible for managing the bus architecture and general processing, and the memory 73 may store data used by the processor 71 when performing operations.

The server embodiment of the present disclosure corresponds to the above-mentioned embodiment of the driving parameter configuration method applied to the application server in the vehicle pair X. All the implementation means in the above-mentioned method embodiment are applicable to the embodiment of the server, and can also To achieve the same technical effect.

An embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the steps in the driving parameter configuration method described above.

An embodiment of the present disclosure also provides a computer-readable storage medium, including instructions, which when executed on a computer, causes the computer to execute the method as described above. Specifically, a computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, the processes of the above-mentioned paging method embodiments are implemented, and the same technical effect can be achieved. To avoid repetition, details are not described here. Wherein, the computer-readable storage medium, such as read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

Those of ordinary skill in the art may realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application of the technical solution and design constraints. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present disclosure.

Those skilled in the art can clearly understand that for the convenience and conciseness of the description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and details are not described herein again.

In the embodiments provided by the present disclosure, it should be understood that the disclosed device and method may be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the unit is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical, or other forms.

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

In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.

If the function 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 disclosure essentially or part of the contribution to the related technology 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, including several The instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present disclosure. The foregoing storage media include various media that can store program codes, such as a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

In addition, it should be pointed out that, in the device and method of the present disclosure, obviously, each component or each step can be decomposed and/or recombined. These decompositions and/or recombinations should be regarded as equivalent solutions of the present disclosure. Also, the steps for performing the above-mentioned series of processing can naturally be executed in chronological order in the order described, but they do not necessarily need to be executed in chronological order, and some steps can be executed in parallel or independently of each other. For those of ordinary skill in the art, all or any steps or components of the methods and devices of the present disclosure can be understood, and can be implemented in hardware, firmware in any computing device (including a processor, a storage medium, etc.) or a network of computing devices , Software, or a combination thereof, which can be realized by those of ordinary skill in the art using their basic programming skills after reading the description of the present disclosure.

Therefore, the purpose of the present disclosure can also be achieved by running a program or a group of programs on any computing device. The computing device may be a well-known general-purpose device. Therefore, the object of the present disclosure can also be achieved only by providing a program product containing program code for implementing the method or device. That is, such a program product also constitutes the present disclosure, and a storage medium storing such a program product also constitutes the present disclosure. Obviously, the storage medium may be any well-known storage medium or any storage medium developed in the future. It should also be noted that, in the device and method of the present disclosure, obviously, each component or each step can be decomposed and/or recombined. These decompositions and/or recombinations should be regarded as equivalent solutions of the present disclosure. Moreover, the steps for performing the above-mentioned series of processing can naturally be performed in chronological order in the order described, but they do not necessarily need to be performed in chronological order. Certain steps can be performed in parallel or independently of each other.

The above is only an optional embodiment of the present disclosure. It should be noted that those of ordinary skill in the art can make several improvements and retouching without departing from the principles of the present disclosure. These improvements and retouching The scope of protection of this disclosure should also be considered.

Claims

A driving parameter configuration method is applied to the network analysis server in the vehicle pair X. The method includes:

According to the driving data information provided by the application server of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function, obtain network prediction parameter information of the vehicle for automatic driving;

Send the network prediction parameter information to the application server of the vehicle.
The driving parameter configuration method according to claim 1, wherein the network prediction parameter information includes at least one of the following:

Predict network service quality Qos, predict vehicle travel speed, predict vehicle travel direction, network load information within a preset time period and network load information within a preset area.
The driving parameter configuration method according to claim 1, wherein the driving data information includes a driving speed of the vehicle.
The driving parameter configuration method according to claim 1, wherein the first network data includes load information and/or mobile network coverage information of a wireless access network.
The driving parameter configuration method according to claim 1, wherein the second network data includes location information, quality of service QoS flow bit rate, QoS flow identification QFI, QoS flow packet delay rate and/or QoS flow packet error rate.
The driving parameter configuration method according to claim 1, further comprising:

Obtain a driving parameter analysis request sent by the application server;

Wherein, in the step of sending the network prediction parameter information to the application server of the vehicle, in response to the driving parameter analysis request, the network prediction parameter information is sent to the application server of the vehicle.
The driving parameter configuration method according to claim 1, wherein in the step of sending the network prediction parameter information to an application server of a vehicle, the network prediction parameter is transmitted through a service interface or a capability opening function NEF module The information is sent to the application server of the vehicle.
The driving parameter configuration method according to claim 1, wherein, after acquiring the network prediction parameter information of the vehicle for automatic driving, the method further comprises:

Store the network prediction parameter information locally, or store the network prediction parameter information to the unified data storage UDR.
A driving parameter configuration method is applied to the application server in the vehicle-to-X. The method includes:

Obtain network prediction parameter information for automatic driving sent by the network analysis server.
The driving parameter configuration method according to claim 9, further comprising:

According to the network prediction parameter information, determine the current driving route, driving parameters and/or driving mode, wherein the driving mode includes manual driving and automatic driving.
The driving parameter configuration method according to claim 9, wherein the network prediction parameter information includes at least one of the following:

Predict network service quality Qos, predict vehicle travel speed, predict vehicle travel direction, network load information within a preset time period and network load information within a preset area.
The driving parameter configuration method according to claim 9, wherein before acquiring the network prediction parameter information for automatic driving sent by the network analysis server, the method further comprises:

Send a driving parameter analysis request to the network analysis server.
The driving parameter configuration method according to claim 12, wherein in the step of sending a driving parameter analysis request to the network analysis server, the driving is sent to the network analysis server through a service interface or a capability opening function NEF module Parameter analysis request;

In the step of obtaining the network prediction parameter information for automatic driving sent by the network analysis server, the network prediction parameter information for automatic driving sent by the network analysis server is obtained through a service interface or a capability opening function NEF module.
A server, wherein the server is a network analysis server used in the vehicle pair X, including a processor and a transceiver, wherein:

The processor is used to obtain the vehicle for automatic driving according to the driving data information provided by the application server of the vehicle, the first network data provided by the OAM server of the operation and maintenance management and/or the second network data provided by the NF server of the network function Network prediction parameter information;

The transceiver is used to send the network prediction parameter information to the application server of the vehicle.
The server according to claim 14, wherein the network prediction parameter information includes at least one of the following:

Predict network service quality Qos, predict vehicle travel speed, predict vehicle travel direction, network load information within a preset time period and network load information within a preset area.
The server according to claim 14, wherein the driving data information includes a driving speed of the vehicle.
The server according to claim 14, wherein the first network data includes load information of the wireless access network and/or mobile network coverage information.
The server according to claim 14, wherein the second network data includes location information, quality of service QoS stream bit rate, QFI, QoS stream packet delay rate and/or QoS stream packet error rate.
The server according to claim 14, wherein

The processor is also used to obtain a driving parameter analysis request sent by the application server;

Wherein, the transceiver is specifically used to send the network prediction parameter information to the application server of the vehicle in response to the driving parameter analysis request.
The server according to claim 14, wherein the transceiver is further specifically used to send the network prediction parameter information to a vehicle application server through a service interface or a capability opening function NEF module.
The server according to claim 14, wherein the processor is further configured to store the network prediction parameter information locally, or store the network prediction parameter information to a unified data storage UDR.
A server, which is applied to the application server in the vehicle-to-X, includes a processor and a transceiver, wherein:

The transceiver is used to obtain network prediction parameter information for automatic driving sent by the network analysis server.
The server according to claim 22, wherein

The processor is configured to determine a current driving route, driving parameters and/or driving mode according to the network prediction parameter information, where the driving mode includes manual driving and automatic driving.
The server according to claim 22, wherein the network prediction parameter information includes at least one of the following:

Predict network service quality Qos, predict vehicle travel speed, predict vehicle travel direction, network load information within a preset time period and network load information within a preset area.
The server according to claim 22, wherein the transceiver is further configured to send a driving parameter analysis request to the network analysis server.
The server according to claim 25, wherein the transceiver is specifically configured to send a driving parameter analysis request to the network analysis server through a service interface or a capability opening function NEF module;

The transceiver is also specifically used to obtain network prediction parameter information for automatic driving sent by a network analysis server through a service interface or a capability opening function NEF module.
A server, including a memory, a processor, and a computer program stored on the memory and executable on the processor; wherein, when the processor executes the program, any one of claims 1-8 is implemented The driving parameter configuration method.
A server, including a memory, a processor, and a computer program stored on the memory and executable on the processor; wherein, when the processor executes the program, any one of claims 9-13 is implemented The driving parameter configuration method.
A computer-readable storage medium on which a computer program is stored, wherein when the program is executed by a processor, the steps in the driving parameter configuration method according to any one of claims 1 to 8 are implemented, or the rights are implemented as The steps in the driving parameter configuration method described in any one of 9-13 are required.