Vehicle control method, device, equipment and readable storage medium

Abstract

The embodiments of the present application provide a vehicle control method, device, equipment and readable storage medium. The method includes: obtaining description data of a moving vehicle, the description data is used to describe the driving state of the moving vehicle; based on the description data of the moving vehicle, determining the state level corresponding to each driving mode of the moving vehicle, the state level corresponding to any driving mode is used to indicate the degree of matching between any driving mode and the driving state of the moving vehicle; based on the state level corresponding to each driving mode, determining the target driving mode of the moving vehicle in multiple driving modes, and controlling the moving vehicle to drive according to the target driving mode. The method is applied to the automatic driving scenario of an unmanned vehicle, and the target driving mode is determined according to the description data of the unmanned vehicle and the state level of each driving mode to achieve automatic driving. The method improves the adaptability of the target driving mode to the driving state of the vehicle and the flexibility of the automatic driving process of the moving vehicle.

Description

Technical Field

[0001] The present application relates to the field of unmanned driving control technology, and in particular to a vehicle control method, device, equipment and readable storage medium. Background Art

[0002] Unmanned vehicles use on-board sensor systems to sense the road environment, plan driving routes, and control vehicles to reach predetermined destinations. During the driving process of unmanned vehicles, in addition to the fully automatic driving system, there are also multiple control systems that issue driving instructions to unmanned vehicles, instructing unmanned vehicles to drive in different driving modes, and each control system corresponds to a different driving mode.

[0003] In the related art, fixed priorities are set for different control systems. In the scenario where multiple control systems issue driving instructions at the same time, the unmanned vehicle determines the target control system strictly according to the priority order, and controls the driving of the unmanned vehicle based on the target control system.

[0004] In the related art, the determination of the target control system is limited to a fixed priority, and the basis for determining the target driving mode for controlling the vehicle's driving is too single and has low flexibility, which easily leads to a situation where the driving mode indicated by the target control system does not match the driving state, resulting in poor adaptability of the vehicle control method to the actual driving state of the unmanned vehicle. Summary of the invention

[0005] The embodiments of the present application provide a vehicle control method, apparatus, device and readable storage medium, which improve the flexibility and diversity of vehicle control and the adaptability of the vehicle control method to driving conditions by determining a target driving mode based on vehicle description data.

[0006] In one aspect, a vehicle control method is provided, the method comprising:

[0007] Acquire description data of a moving vehicle, where the description data of the moving vehicle is used to describe the driving state of the moving vehicle;

[0008] Determining, based on the description data of the driving vehicle, the state levels corresponding to the plurality of driving modes of the driving vehicle, respectively, wherein the state level corresponding to any driving mode is used to indicate the degree of matching between any driving mode and the driving state of the driving vehicle;

[0009] Based on the state levels corresponding to the driving modes, a target driving mode of the driving vehicle is determined among the plurality of driving modes, and the driving vehicle is controlled to drive according to the target driving mode.

[0010] In one possible implementation, based on the description data of the moving vehicle, the status levels corresponding to the multiple driving modes of the moving vehicle are determined, including: determining the quality index corresponding to each driving mode based on the description data; determining the status level corresponding to each driving mode based on the quality index of each driving mode and the classification standard of the status level of each driving mode.

[0011] In a possible implementation, based on the state levels corresponding to the driving modes, a target driving mode of the driving vehicle is determined in a plurality of driving modes, including:

[0012] The state levels corresponding to the driving modes are compared with a plurality of reference conditions; in response to the state levels corresponding to the driving modes matching any of the reference conditions, a target driving mode of the moving vehicle is determined based on the switching method of the driving modes indicated by any of the reference conditions, and different reference conditions indicate the switching methods of the driving modes at different state levels.

[0013] In a possible implementation, based on the state levels corresponding to the driving modes, before determining the target driving mode of the driving vehicle in the multiple driving modes, the method further includes: obtaining driving instructions issued in the multiple driving modes;

[0014] Controlling the moving vehicle to drive according to the target driving mode includes: determining the driving instructions issued under the target driving mode among the received multiple driving instructions, and controlling the moving vehicle to drive according to the driving instructions under the target driving mode.

[0015] In a possible implementation, the multiple driving modes include a fully automatic driving mode, a degraded automatic driving mode, and a remote control driving mode. The fully automatic driving mode instructs the driving vehicle to autonomously plan a driving route and a driving speed. The degraded automatic driving mode instructs the driving vehicle to autonomously select a parking method according to the driving environment. The remote control driving mode instructs the driving vehicle to drive based on interactive instructions. The description data includes perception data and basic data.

[0016] Based on the description data of the moving vehicle, the state levels corresponding to the multiple driving modes of the moving vehicle are determined, including: based on the perception data, determining the state level corresponding to the fully automatic driving mode; based on the basic data, determining the state level corresponding to the remote control driving mode; based on the perception data and the map information included in the basic data, determining the state level corresponding to the degraded automatic driving mode.

[0017] In one possible implementation, a target driving mode of a moving vehicle is determined among multiple driving modes based on the status levels corresponding to each driving mode, including: in response to the current driving mode of the moving vehicle being the remote control driving mode or the degraded automatic driving mode, and the status level corresponding to the fully automatic driving mode indicates that the moving vehicle switches the driving mode to the fully automatic driving mode, then determining that the target driving mode of the moving vehicle is the fully automatic driving mode.

[0018] In a possible implementation, the method further includes:

[0019] The description data and the driving mode switching result are sent to the server, which analyzes the received information and updates the classification standard of the state level of each driving mode based on the analysis result.

[0020] In another aspect, a vehicle control device is provided, the device comprising:

[0021] An acquisition module, used for acquiring description data of a moving vehicle, where the description data of the moving vehicle is used for describing the driving state of the moving vehicle;

[0022] A determination module, used to determine the state levels corresponding to the multiple driving modes of the driving vehicle based on the description data of the driving vehicle, wherein the state level corresponding to any driving mode is used to indicate the matching degree between any driving mode and the driving state of the driving vehicle;

[0023] The control module is used to determine a target driving mode of a driving vehicle among multiple driving modes based on the state levels corresponding to each driving mode, and control the driving vehicle to drive according to the target driving mode.

[0024] In a possible implementation, the acquisition module is used to determine the quality index corresponding to each driving mode based on the description data; and determine the state level corresponding to each driving mode based on the quality index of each driving mode and the classification standard of the state level of each driving mode.

[0025] In one possible implementation, the control module is used to compare the state levels corresponding to each driving mode with multiple reference conditions; in response to the state level corresponding to each driving mode matching any reference condition, the target driving mode of the moving vehicle is determined based on the switching method of the driving mode indicated by any reference condition, and different reference conditions indicate the switching method of each driving mode at different state levels.

[0026] In a possible implementation, the acquisition module is also used to acquire driving instructions issued under multiple driving modes; the control module is used to determine the driving instructions issued under the target driving mode among the multiple driving instructions received, and control the moving vehicle to drive according to the driving instructions under the target driving mode.

[0027] In a possible implementation, the multiple driving modes include a fully automatic driving mode, a degraded automatic driving mode, and a remote control driving mode. The fully automatic driving mode instructs the driving vehicle to autonomously plan a driving route and a driving speed. The degraded automatic driving mode instructs the driving vehicle to autonomously select a parking method according to the driving environment. The remote control driving mode instructs the driving vehicle to drive based on interactive instructions. The description data includes perception data and basic data.

[0028] A determination module is used to determine the state level corresponding to the fully automatic driving mode based on the perception data; determine the state level corresponding to the remote control driving mode based on the basic data; and determine the state level corresponding to the degraded automatic driving mode based on the perception data and the map information included in the basic data.

[0029] In one possible implementation, the control module is used to determine that the target driving mode of the moving vehicle is the fully automatic driving mode in response to the current driving mode of the moving vehicle being the remote control driving mode or the downgraded automatic driving mode, and the state level corresponding to the fully automatic driving mode instructs the moving vehicle to switch the driving mode to the fully automatic driving mode.

[0030] In a possible implementation, the device further includes:

[0031] The sending module sends the description data and the driving mode switching result to the server, and the server analyzes the received information and updates the classification standard of the state level of each driving mode based on the analysis result.

[0032] On the other hand, an electronic device is provided, which includes a processor and a memory, wherein at least one program code or instruction is stored in the memory, and the at least one program code or instruction is loaded and executed by the processor so that the electronic device implements any of the above-mentioned vehicle control methods.

[0033] On the other hand, a computer-readable storage medium is provided, in which at least one program code or instruction is stored. The program code is loaded and executed by a processor so that a computer implements any of the above-mentioned vehicle control methods.

[0034] On the other hand, a computer program or a computer program product is provided, wherein at least one computer instruction is stored in the computer program or the computer program product, and the at least one computer instruction is loaded and executed by a processor so that a computer implements any of the above-mentioned vehicle control methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of an implementation environment provided for an embodiment of the present application;

[0036] Figure 2 A schematic diagram of an implementation environment provided for an embodiment of the present application;

[0037] Figure 3 A flow chart of a vehicle control method provided in an embodiment of the present application;

[0038] Figure 4 A schematic diagram of the structure of a vehicle control device provided in an embodiment of the present application;

[0039] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0040] Figure 6 A schematic diagram of the structure of another electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical methods in this application, some embodiments of this application will be described below in conjunction with the accompanying drawings. It should be understood that, unless otherwise defined, all technical terms used in the embodiments of this application have the same meaning as those generally understood by those skilled in the art, and are only used to explain the embodiments of this application, and are not intended to limit this application.

[0042] See also Figure 1 , the implementation environment of the embodiment of the present application includes at least one terminal 11 and a server 12. The terminal 11 and the server 12 can be connected in communication to realize the interactive transmission of information. The embodiment of the present application does not limit the connection method between the terminal 11 and the server 12. In the embodiment of the present application, the terminal 11 determines the state levels corresponding to the driving modes of the driving vehicle according to the acquired description data of the driving vehicle, determines the target driving mode of the driving vehicle according to the state level, and controls the driving vehicle to drive according to the target driving model. The terminal 11 can upload the acquired description data and the result of the driving mode switching to the server 12. Information transmission between the terminal 11 and the server 12 can be based on wired or wireless means.

[0043] The terminal 11 may be any electronic product that can interact with a user through one or more methods such as a keyboard, a touch pad, a touch screen, and voice interaction, such as a mobile phone, a PPC (Pocket Personal Computer), a tablet computer, a car computer, etc.

[0044] Server 12 can be a single server or a server cluster composed of multiple servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), as well as big data and artificial intelligence platforms.

[0045] Those skilled in the art should understand that the above-mentioned terminal 11 and server 12 are only examples, and other existing or future terminals or servers that may appear, if they can be used in the present application, should also be included in the protection scope of the present application and are included here by reference.

[0046] In one possible implementation, see Figure 2 , the terminal 11 is composed based on multiple different control systems. Multiple driving modes correspond to corresponding control systems. In an exemplary embodiment, the terminal 11 includes a fully automatic driving system, a degraded automatic driving system, a remote control driving system and an arbitration control system. The terminal 11 also includes a monitoring device for obtaining descriptive data of the unmanned vehicle during driving. The arbitration control system determines the system for controlling the vehicle based on the descriptive data obtained by the monitoring device. The server 12 can receive and store the descriptive data obtained by the terminal 11, as well as the target driving mode determined by the terminal 11. In a possible implementation, the server 12 can perform data analysis based on the received data and update the classification criteria for the state levels of each driving mode in the unmanned vehicle.

[0047] See also Figure 3 , an embodiment of the present application provides a vehicle control method, which includes but is not limited to the following steps 301-303.

[0048] Step 301: Acquire description data of a moving vehicle, where the description data of the moving vehicle is used to describe the driving state of the moving vehicle.

[0049] The moving vehicle may be an unmanned vehicle, and the description data of the moving vehicle is used to describe the driving state of the moving vehicle at the current moment, including but not limited to the perception data and basic data of the moving vehicle. The perception data refers to the data obtained by the moving vehicle during the driving process, including but not limited to the driving data of the moving vehicle itself, the environmental data of the moving vehicle, the evaluation data of the current driving route of the moving vehicle, the quality data of the current signal used for communication by the terminal on the moving vehicle, etc.; the basic data refers to the data related to the attributes of the moving vehicle itself, or the basic data refers to the map and other information used by the moving vehicle during the driving process. The basic data is generally not affected by the driving state of the moving vehicle, such as map information, information marked on various signs in the map, and the attribute information of the moving vehicle, such as height, etc.

[0050] In a possible implementation, the method of obtaining the descriptive data of a moving vehicle includes: obtaining the perception data through a monitoring device, and obtaining the basic data from a local terminal or a server. The monitoring device for obtaining the perception data can be installed on the moving vehicle, and transmit the collected perception data to the terminal by wired or wireless means; the monitoring device can also be installed in the terminal, and the perception data is directly obtained by the terminal. The monitoring device can include a variety of devices for monitoring the driving status of a moving vehicle, such as radar, camera, and sensor.

[0051] In a possible implementation, the monitoring device can be installed in the front, rear, left, and right directions of the moving vehicle, or in multiple directions such as the roof, bottom, or left front, left rear, etc. The embodiment of the present application does not limit the number and installation position of the monitoring device.

[0052] Step 302: Based on the description data of the moving vehicle, determine the state levels corresponding to the multiple driving modes of the moving vehicle, and the state level corresponding to any driving mode is used to indicate the degree of matching between any driving mode and the driving state of the moving vehicle.

[0053] As an unmanned vehicle, the driving vehicle can be driven in multiple driving modes to cope with different driving environments. For example, in addition to the fully automatic driving mode, there are multiple different driving modes to ensure the safe driving of the driving vehicle in a complex driving environment. The driving vehicle drives according to the corresponding driving instructions issued by the control system corresponding to the different driving modes.

[0054] The multiple driving modes of the moving vehicle correspond to different state levels under different driving conditions of the moving vehicle, and the state level corresponding to any driving mode can reflect the degree of matching between the current driving condition of the moving vehicle and any driving mode. Optionally, the state level corresponding to any driving mode can also be used to indicate the switching mode between any driving mode and other driving modes under the current driving condition. The description data includes multiple types and quantities of data, and the current driving condition of the moving vehicle can be objectively described based on the description data.

[0055] In one possible implementation, the process of determining the state levels corresponding to multiple driving modes of a moving vehicle based on the descriptive data of the moving vehicle includes: determining the quality index of each driving mode based on the descriptive data; and determining the state level corresponding to each driving mode based on the quality index of each driving mode and the classification criteria of the state level of each driving mode.

[0056] In one possible implementation, a method for determining the quality indicators of each driving mode based on the description data includes but is not limited to: based on the description data, determining the quality data corresponding to the description data according to the quality standards corresponding to different description data; and determining the quality indicators corresponding to each driving mode based on the quality data.

[0057] In one possible implementation, the quality indicator can be expressed in the form of an evaluation score; the quality standard is a score standard set for various descriptive data and used to evaluate the descriptive data; the quality data is the score corresponding to the descriptive data; the division standard of the state level of each driving mode is a segmented division of the evaluation score, and different evaluation score segments correspond to different state levels.

[0058] Exemplarily, based on the descriptive data, according to the score standards corresponding to different descriptive data, the score corresponding to the descriptive data is determined, and the evaluation score corresponding to each driving mode is determined based on the score; based on the evaluation score corresponding to each driving mode and the classification standard of the state level of each driving mode, the state level corresponding to each driving mode is determined.

[0059] The quality standards used in determining the quality indicators corresponding to different driving modes are different. The quality standards include the description data used in the evaluation process of the corresponding driving mode, the basis for determining the evaluation score corresponding to each description data, etc. The quality standards can be in a table form, recording the corresponding relationship between different values ​​of each description data and the evaluation score; or they can be set as a functional relationship between the quality indicator and the description data, and the quality indicator of the driving mode is calculated based on the numerical value of the corresponding description data.

[0060] For example, based on the characteristics of different types of description data, different weight coefficients can also be set for different types of description data. In the embodiment of the present application, the score standard is not limited. The score standard can be set accordingly according to the characteristics of different driving modes and the characteristics of each description data. A single scoring mode can be used, or multiple scoring methods can be used in combination. In addition, the division standard of the state level of each driving mode can be the corresponding relationship between the evaluation score and the state level, which is not limited in the present application.

[0061] In a possible implementation, the multiple driving modes of the moving vehicle include three driving modes: a fully automatic driving mode, a degraded automatic driving mode, and a remote control driving mode. The description data includes perception data and basic data.

[0062] Among them, the fully automatic driving mode instructs the vehicle to autonomously plan the driving route and driving speed. When the vehicle drives according to the instructions in the fully automatic driving mode, no human intervention is required. The degraded automatic driving mode instructs the vehicle to autonomously select the parking method according to the driving environment. For example, the vehicle performs emergency braking under the degraded automatic driving model, or pulls over or slows down to stop according to the driving environment of the vehicle. The remote control driving mode instructs the vehicle to drive based on interactive instructions. For example, when the vehicle drives in the remote control driving mode, the safety officer operates the vehicle to drive, and the driving instructions triggered by the safety officer are remotely transmitted to the vehicle through the information channel.

[0063] In a possible implementation, the process of determining the state level corresponding to each driving mode of the moving vehicle based on the description data includes, but is not limited to: determining the state level corresponding to the fully automatic driving mode based on the perception data; determining the state level corresponding to the remote control driving mode based on the basic data; determining the state level corresponding to the degraded automatic driving mode based on the perception data and the map information included in the basic data. In the process of determining the state level corresponding to the corresponding driving mode according to each data in the description data, the method for determining the driving mode based on the quality standard of the driving mode and the state level classification standard can be applied.

[0064] Exemplarily, based on the perception data, the state level corresponding to the fully autonomous driving mode is determined. The perception data includes, but is not limited to, the environmental data of the scene in which the driving vehicle is located, the driving data of the driving vehicle itself, etc. Through the value of the perception data, based on the score standard given in the above content, the quality index corresponding to the fully autonomous driving mode is obtained. The embodiment of the present application does not limit the data type included in the perception data, and the data type included in the perception data collected by the monitoring device can be determined based on experience.

[0065] In a possible implementation, before determining the quality index, it is first determined whether the perception data is normal, for example, whether the time interval for acquiring data exceeds the set time threshold, whether new perception data is obtained within a certain period of time, etc. If the perception data is normal, the evaluation score of the fully autonomous driving mode is determined based on the perception data, and the perception data can be based on the driving speed, surrounding environment information, etc. determined by the monitoring device. Then, according to the classification standard of the quality index and the state level of the fully autonomous driving mode, the state level corresponding to the fully autonomous driving mode is determined.

[0066] Exemplarily, the fully autonomous driving mode corresponds to the following five status levels: A0-A4.

[0067] A0: In an unsafe state, downgrade intervention is required, and remote control mode takeover is requested in real time;

[0068] A1: Give risk warnings and be ready to be taken over by remote control mode at any time;

[0069] A2: It is in a safe state and does not need to request remote control mode takeover in a degraded state;

[0070] A3: Good condition, but not suitable for switching from remote control to fully autonomous driving mode, not suitable for system switching;

[0071] A4: In good condition, switching seamlessly from any driving mode to fully autonomous driving mode.

[0072] Among the above status levels, A0-A2 indicate switching from fully automatic driving mode to other driving modes under the current driving state of the moving vehicle; A3 indicates that it is not suitable to switch from other driving modes to fully automatic driving mode under the current driving state of the moving vehicle; A4 indicates switching from other driving modes to fully automatic driving mode under the current driving state of the moving vehicle.

[0073] In one possible implementation, the value ranges of the quality indicators corresponding to the above five state levels are determined in the state level classification standard. Then, according to the value of the quality indicator of the fully automatic driving mode of the driving vehicle in the current driving state, the state level of the fully automatic driving mode in the current driving state is matched in the classification standard.

[0074] Exemplarily, the state level corresponding to the remote control driving mode is determined based on the planned route and signal delay degree in the basic data. The remote control driving mode requires the transmission network to transmit driving instructions to the moving vehicle, so the signal delay degree during information transmission is an important factor affecting the operation of the remote control driving mode. In this exemplary embodiment, the planned route and the signal delay degree can be scored respectively based on the corresponding evaluation criteria, and then the comprehensive score is obtained. Based on the comprehensive score and the classification criteria of the state level of the remote control driving mode, the state level of the remote control driving mode is determined.

[0075] Exemplarily, the remote control mode corresponds to the following three status levels: T0-T2.

[0076] T0: video or control delay is too high; T1: sections with poor signals are marked in advance; T2: video and control delay is low.

[0077] Among the above status levels, at the T0 level, the information delay is too high, indicating that the remote control driving mode is not suitable for the current driving state; at the T1 level, the section with poor signal transmission in the current driving route is identified, which is used to instruct the vehicle to switch the driving mode before entering the section with poor signal transmission; T2 indicates that the current signal state is good and the remote control driving mode can be applied in the current state.

[0078] Exemplarily, based on map input information and perception data, the state level corresponding to the degraded automatic driving mode is determined. The map input information and perception data may include the type of intersection, the degree of traffic congestion, whether there are obstacles, etc. Based on the analysis of the real-time perception data of the vehicle's environment and the map input information, it is determined whether the degraded automatic driving mode is applicable in the current driving state. The degraded automatic driving mode is used to control the emergency stop or pull-over of the moving vehicle. Therefore, in the process of determining the level state of the degraded automatic driving mode, the current driving scene of the moving vehicle is analyzed and evaluated.

[0079] Exemplarily, the degraded autonomous driving mode has four status levels as shown below: X0-X3.

[0080] X0: Not suitable for starting the downgrade system; X1: Suitable for deceleration and parking; X2: Suitable for pull-over parking; X3: Suitable for downgrade strategy without stopping.

[0081] Step 303: Based on the state levels corresponding to the driving modes, a target driving mode of the driving vehicle is determined among the multiple driving modes, and the driving vehicle is controlled to drive according to the target driving mode.

[0082] In this step, based on the state levels corresponding to each driving mode, the process of determining the target driving mode of the driving vehicle in multiple driving modes includes: comparing the state level corresponding to each driving mode with multiple reference conditions, and in response to the state level corresponding to each driving mode matching any reference condition, determining the target driving mode of the driving vehicle based on the switching method of the driving mode indicated by any reference condition, wherein different reference conditions indicate the switching method of each driving mode at different state levels.

[0083] In a possible implementation, referring to the exemplary embodiment in step 302, the multiple driving modes include a fully automatic driving mode, a degraded automatic driving mode, and a remote control driving mode, and the following reference conditions 1-6 are exemplarily given:

[0084] Reference condition 1: The fully autonomous driving mode is in the A1 or A2 state level, and the remote control issues a control command: switch from the fully autonomous driving mode to the remote control driving mode.

[0085] Reference condition 2: Fully autonomous driving mode is in state level A4: Switching from remote control driving mode to fully autonomous driving mode.

[0086] Reference condition 3: The remote control mode is in the T1 or T2 state level, and a command is issued in the remote control mode: automatically switch from degraded driving to remote control driving mode.

[0087] Reference condition 4: Degraded autonomous driving mode is in the X1 or X2 state level, and the remote control mode is in the T0 state level: Switch from the remote control mode to the automatic degraded driving mode.

[0088] Reference condition 5: Fully autonomous driving mode is in state level A4: Automatically switches from degraded autonomous driving mode to fully autonomous driving mode.

[0089] Reference condition 6: The fully autonomous driving mode is in state level A0 and the degraded system is in state X1, X2 or X3: Automatically switch from the fully autonomous driving mode to the degraded autonomous driving mode.

[0090] In a possible implementation, before determining the target driving mode in this step, multiple driving instructions issued in each driving mode are also obtained. Exemplarily, when a pedestrian suddenly appears in front of the moving vehicle, multiple driving modes generate corresponding braking or deceleration driving instructions based on the description data at the current moment. After determining the target driving mode of the moving vehicle based on the state level corresponding to each driving mode, controlling the moving vehicle to drive according to the target driving mode includes: determining the driving instructions issued under the target driving mode among the multiple driving instructions received, and controlling the moving vehicle to drive according to the driving instructions in the target driving mode. Based on this possible implementation, the problem of instruction selection when multiple driving systems issue driving instructions at the same time can be solved, and the final selection is the driving instruction that matches the target driving mode, which can effectively improve the safety of the moving vehicle during driving.

[0091] In a possible implementation, after obtaining the driving instructions corresponding to each driving mode, the correctness of each driving instruction is judged, and then the target driving mode of the moving vehicle is determined based on the judgment result and the state level corresponding to each driving mode. For example, in a scenario where braking is required, driving modes A and B both generate braking instructions, and driving mode C mistakenly generates an acceleration instruction. After identifying the wrong instruction, driving mode C is directly abandoned, and the target driving mode is determined only based on the state levels of the remaining driving modes A and B.

[0092] Exemplarily, the status levels corresponding to the current driving modes are determined based on the descriptive data, and it is determined that the fully autonomous driving mode should be switched to the remote control driving mode, and a braking operation should be performed; however, during the execution process, the remote control driving mode issues an erroneous command, then the erroneous command is identified, and the mode is switched to the degraded autonomous driving mode in an emergency, and an emergency braking operation is performed.

[0093] In one possible implementation, in response to the current driving mode of the moving vehicle being the remote control driving mode or the degraded automatic driving mode, and the state level corresponding to the fully automatic driving mode indicates that the moving vehicle switches from any driving mode to the fully automatic driving mode, the target driving mode of the moving vehicle is determined to be the fully automatic driving mode; the moving vehicle directly switches from the remote control mode or the degraded automatic driving mode to the fully automatic driving mode.

[0094] In a possible implementation, the terminal further performs the following operations: sending description data and driving mode switching results to the server, the server analyzing the received information, and updating the scoring standards corresponding to each driving mode based on the analysis results.

[0095] The embodiment of the present application provides a vehicle control method, which determines the state levels corresponding to multiple driving modes of the moving vehicle based on the description data of the moving vehicle, determines the target driving mode based on the state level of each driving mode, and then controls the moving vehicle to travel in the target driving mode. The vehicle control method provided in the embodiment of the present application can be applied to the scenario of controlling an unmanned vehicle to perform automatic driving. According to the description data of the unmanned vehicle and the state level of each driving mode, the target driving mode is further determined to control the unmanned vehicle to perform automatic driving. The vehicle control method of the embodiment of the present application enriches the diversity of vehicle methods, improves the adaptability of the target driving mode to the driving state of the vehicle, and thereby improves the flexibility of controlling the vehicle to perform automatic driving.

[0096] The present application embodiment provides a vehicle control device, see Figure 4 , the device comprises:

[0097] An acquisition module 401 is used to acquire description data of a moving vehicle, where the description data of the moving vehicle is used to describe the driving state of the moving vehicle;

[0098] A determination module 402, configured to determine, based on the description data of the driving vehicle, the state levels corresponding to the multiple driving modes of the driving vehicle, respectively, wherein the state level corresponding to any driving mode is used to indicate the degree of matching between any driving mode and the driving state of the driving vehicle;

[0099] The control module 403 is used to determine a target driving mode of the driving vehicle among multiple driving modes based on the state levels corresponding to each driving mode, and control the driving vehicle to drive according to the target driving mode.

[0100] In a possible implementation, the acquisition module 401 is used to determine the quality index corresponding to each driving mode based on the description data; and determine the state level corresponding to each driving mode based on the quality index of each driving mode and the classification standard of the state level of each driving mode.

[0101] In one possible implementation, the control module 403 is used to compare the state levels corresponding to each driving mode with multiple reference conditions; in response to the state level corresponding to each driving mode matching any reference condition, based on the switching method of the driving mode indicated by any reference condition, determine the target driving mode of the driving vehicle, and different reference conditions indicate the switching method of each driving mode at different state levels.

[0102] In a possible implementation, the acquisition module 401 is also used to acquire driving instructions issued under multiple driving modes; the control module 403 is used to determine the driving instructions issued under the target driving mode among the multiple driving instructions received, and control the moving vehicle to drive according to the driving instructions under the target driving mode.

[0103] In a possible implementation, the multiple driving modes include a fully automatic driving mode, a degraded automatic driving mode, and a remote control driving mode. The fully automatic driving mode instructs the driving vehicle to autonomously plan a driving route and a driving speed. The degraded automatic driving mode instructs the driving vehicle to autonomously select a parking method according to the driving environment. The remote control driving mode instructs the driving vehicle to drive based on interactive instructions. The description data includes perception data and basic data.

[0104] The determination module 402 is used to determine the state level corresponding to the fully automatic driving mode based on the perception data; determine the state level corresponding to the remote control driving mode based on the basic data; and determine the state level corresponding to the degraded automatic driving mode based on the perception data and the map information included in the basic data.

[0105] In one possible implementation, the control module 403 is used to determine that the target driving mode of the moving vehicle is the fully automatic driving mode in response to the current driving mode of the moving vehicle being the remote control driving mode or the degraded automatic driving mode, and the state level corresponding to the fully automatic driving mode indicates that the moving vehicle switches from any driving mode to the fully automatic driving mode.

[0106] In a possible implementation, the device further includes:

[0107] The sending module sends the description data and the driving mode switching result to the server, and the server analyzes the received information and updates the classification standard of the state level of each driving mode based on the analysis result.

[0108] An embodiment of the present application provides a computer-readable storage medium, in which at least one program code or instruction is stored. The program code or instruction is loaded and executed by a processor to enable a computer to implement any vehicle control method such as in the method embodiment.

[0109] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0110] In an exemplary embodiment, a computer program or a computer program product is also provided. The computer program or the computer program product stores at least one computer instruction, and the at least one computer instruction is loaded and executed by a processor to enable a computer to implement any of the above-mentioned vehicle control methods.

[0111] Figure 5 It is a structural diagram of an electronic device provided in an embodiment of the present application. The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors 501 and one or more memories 502, wherein the one or more memories 502 store at least one program instruction, and the at least one program instruction is loaded and executed by the one or more processors 501 to implement the vehicle control method provided by the above-mentioned various method embodiments. Exemplarily, the processor 501 is a central processing unit (CPU). Of course, the electronic device may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The electronic device may also include other components for implementing device functions, which will not be repeated here.

[0112] In an exemplary embodiment, see Figure 6 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, and the computer device includes a processor 601 and a memory 602. The processor 601 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 601 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array).

[0113] The processor 601 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 601 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 601 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0114] The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 602 is used to store at least one instruction, which is used to be executed by the processor 601 to implement the vehicle control method provided by the method embodiment of the present application.

[0115] In some embodiments, the terminal may also optionally include: a peripheral device interface 603 and at least one peripheral device. The processor 601, the memory 602 and the peripheral device interface 603 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 603 via a bus, a signal line or a circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 604, a display screen 605, a camera assembly 606, an audio circuit 607, a positioning assembly 608 and a power supply 609. The peripheral device interface 603 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 601 and the memory 602.

[0116] In some embodiments, the processor 601, the memory 602 and the peripheral device interface 603 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 601, the memory 602 and the peripheral device interface 603 can be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0117] The radio frequency circuit 604 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 604 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 604 converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 604 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and the like. The radio frequency circuit 604 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: a metropolitan area network, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 604 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0118] The display screen 605 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 605 is a touch display screen, the display screen 605 also has the ability to collect touch signals on the surface or above the surface of the display screen 605. The touch signal can be input to the processor 601 as a control signal for processing. At this time, the display screen 605 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 605 can be one, set on the front panel of the terminal; in other embodiments, the display screen 605 can be at least two, respectively set on different surfaces of the terminal or in a folding design; in other embodiments, the display screen 605 can be a flexible display screen, set on a curved surface or a folding surface of the terminal. Even, the display screen 605 can also be set to a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 605 can be made of materials such as LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), etc.

[0119] The camera assembly 606 is used to capture images or videos. Optionally, the camera assembly 606 includes a front camera and a rear camera. Typically, the front camera is arranged on the front panel of the terminal, and the rear camera is arranged on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize the panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 606 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0120] The audio circuit 607 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 601 for processing, or input them into the radio frequency circuit 604 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 601 or the radio frequency circuit 604 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 607 may also include a headphone jack.

[0121] The positioning component 608 is used to locate the current geographical location of the terminal to implement navigation or LBS (Location Based Service). The positioning component 608 can be a positioning component based on the US GPS (Global Positioning System), China's Beidou system, Russia's Grenas system or the European Union's Galileo system.

[0122] The power supply 609 is used to power various components in the terminal. The power supply 609 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 609 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0123] In some embodiments, the terminal further includes one or more sensors 610 , including but not limited to: an acceleration sensor 611 , a gyroscope sensor 612 , a pressure sensor 613 , a fingerprint sensor 614 , an optical sensor 615 , and a proximity sensor 616 .

[0124] The acceleration sensor 611 can detect the magnitude of acceleration on the three coordinate axes of the coordinate system established by the terminal. For example, the acceleration sensor 611 can be used to detect the components of gravity acceleration on the three coordinate axes. The processor 601 can control the display screen 605 to display the user interface in a horizontal view or a vertical view according to the gravity acceleration signal collected by the acceleration sensor 611. The acceleration sensor 611 can also be used for collecting game or user motion data.

[0125] The gyroscope sensor 612 can detect the body direction and rotation angle of the terminal, and the gyroscope sensor 612 can cooperate with the acceleration sensor 611 to collect the user's 3D actions on the terminal. The processor 601 can implement the following functions based on the data collected by the gyroscope sensor 612: motion sensing (such as changing the UI according to the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0126] The pressure sensor 613 can be set in the side frame of the terminal and / or the lower layer of the display screen 605. When the pressure sensor 613 is set in the side frame of the terminal, the user's holding signal of the terminal can be detected, and the processor 601 performs left and right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 613. When the pressure sensor 613 is set in the lower layer of the display screen 605, the processor 601 controls the operability controls on the UI interface according to the user's pressure operation on the display screen 605. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0127] The fingerprint sensor 614 is used to collect the user's fingerprint, and the processor 601 identifies the user's identity based on the fingerprint collected by the fingerprint sensor 614, or the fingerprint sensor 614 identifies the user's identity based on the collected fingerprint. When the user's identity is identified as a trusted identity, the processor 601 authorizes the user to perform relevant sensitive operations, which include unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings. The fingerprint sensor 614 can be set on the front, back, or side of the terminal. When a physical button or manufacturer logo is set on the terminal, the fingerprint sensor 614 can be integrated with the physical button or manufacturer logo.

[0128] The optical sensor 615 is used to collect the ambient light intensity. In one embodiment, the processor 601 can control the display brightness of the display screen 605 according to the ambient light intensity collected by the optical sensor 615. Specifically, when the ambient light intensity is high, the display brightness of the display screen 605 is increased; when the ambient light intensity is low, the display brightness of the display screen 605 is reduced. In another embodiment, the processor 601 can also dynamically adjust the shooting parameters of the camera component 606 according to the ambient light intensity collected by the optical sensor 615. The proximity sensor 616, also known as the distance sensor, is usually set on the front panel of the terminal.

[0129] The proximity sensor 616 is used to collect the distance between the user and the front of the terminal. In one embodiment, when the proximity sensor 616 detects that the distance between the user and the front of the terminal is gradually decreasing, the processor 601 controls the display screen 605 to switch from the screen-on state to the screen-off state; when the proximity sensor 616 detects that the distance between the user and the front of the terminal is gradually increasing, the processor 601 controls the display screen 605 to switch from the screen-off state to the screen-on state.

[0130] Those skilled in the art will understand that Figure 6 The structure shown in the figure does not constitute a limitation on the terminal, and may include more or less components than those shown in the figure, or combine certain components, or adopt a different component arrangement.

[0131] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions. For example, the description data of the moving vehicles involved in this application are all obtained with full authorization.

[0132] It should be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0133] The term "at least one" in this application means one or more, and the term "plurality" in this application means two or more.

[0134] It should be understood that the terms used in the description of the various examples herein are only for describing specific examples and are not intended to be limiting. As used in the description of the various examples and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0135] It should also be understood that the term “comprise” (also known as “includes,” “including,” “comprises” and / or “comprising”) when used in this specification specifies the presence of stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0136] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0137] It should also be understood that the terms "if" and "if" may be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting." Similarly, the phrases "if it is determined that ..." or "if [a stated condition or event] is detected" may be interpreted to mean "upon determining that ..." or "in response to determining that ..." or "upon detecting [a stated condition or event]" or "in response to detecting [a stated condition or event]," depending on the context.

[0138] It should also be understood that the references to "one embodiment", "an embodiment", or "a possible implementation" throughout the specification mean that specific features, structures, or characteristics related to the embodiment or implementation are included in at least one embodiment of the present application. Therefore, the references to "in one embodiment" or "in an embodiment", or "a possible implementation" throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0139] The above description is only an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle control method, characterized in that: The method comprises: Acquiring description data of a moving vehicle, wherein the description data of the moving vehicle is used to describe a moving state of the moving vehicle; Based on the description data of the driving vehicle, determining the state levels corresponding to the multiple driving modes of the driving vehicle, respectively, wherein the state level corresponding to any driving mode is used to indicate the degree of matching between any driving mode and the driving state of the driving vehicle; Determining a target driving mode of the driving vehicle from among the plurality of driving modes based on the state levels corresponding to the respective driving modes, and controlling the driving vehicle to drive according to the target driving mode; Before determining the target driving mode of the driving vehicle among the plurality of driving modes based on the state levels respectively corresponding to the driving modes, the method further includes: Obtaining driving instructions issued under the multiple driving modes; The controlling the vehicle to travel according to the target driving mode includes: Determine the driving instructions issued under the target driving mode among the received multiple driving instructions, and control the moving vehicle to drive according to the driving instructions under the target driving mode.

2. The method according to claim 1, characterized in that: The determining, based on the description data of the driving vehicle, the state levels corresponding to the plurality of driving modes of the driving vehicle respectively comprises: Determining a quality indicator corresponding to each driving mode based on the description data; Based on the quality indicators of the driving modes and the classification criteria of the state levels of the driving modes, the state levels corresponding to the driving modes are determined.

3. The method according to claim 1 or 2, characterized in that: The determining of the target driving mode of the driving vehicle from among the plurality of driving modes based on the state levels respectively corresponding to the driving modes includes: comparing the state levels corresponding to the driving modes respectively with a plurality of reference conditions; In response to the state level corresponding to each driving mode matching any reference condition, the target driving mode of the moving vehicle is determined based on the switching manner of the driving mode indicated by any reference condition, and different reference conditions indicate the switching manner of each driving mode at different state levels.

4. The method according to claim 1, characterized in that: The multiple driving modes include a fully automatic driving mode, a degraded automatic driving mode, and a remote control driving mode, wherein the fully automatic driving mode indicates that the driving vehicle autonomously plans a driving route and a driving speed, the degraded automatic driving mode indicates that the driving vehicle autonomously selects a parking method according to the driving environment, and the remote control driving mode indicates that the driving vehicle drives based on interactive instructions, and the description data includes perception data and basic data; The determining, based on the description data of the driving vehicle, the state levels corresponding to the plurality of driving modes of the driving vehicle respectively comprises: Determining a state level corresponding to the fully autonomous driving mode based on the perception data; Based on the basic data, determining a state level corresponding to the remote control driving mode; Based on the perception data and the map information included in the basic data, a state level corresponding to the degraded autonomous driving mode is determined.

5. The method according to claim 4, characterized in that The determining of the target driving mode of the driving vehicle from among the plurality of driving modes based on the state levels respectively corresponding to the driving modes includes: In response to the current driving mode of the moving vehicle being the remote control driving mode or the degraded automatic driving mode, and the state level corresponding to the fully automatic driving mode indicates that the moving vehicle switches the driving mode to the fully automatic driving mode, it is determined that the target driving mode of the moving vehicle is the fully automatic driving mode.

6. The method according to claim 1, characterized in that The method further comprises: The description data and the driving mode switching result are sent to a server, and the server analyzes the received information and updates the classification standard of the state level of each driving mode based on the analysis result.

7. A vehicle control device, characterized in that: The device comprises: An acquisition module, used for acquiring description data of a moving vehicle, wherein the description data of the moving vehicle is used for describing a moving state of the moving vehicle; a determination module, configured to determine, based on the description data of the driving vehicle, state levels corresponding to a plurality of driving modes of the driving vehicle, respectively, wherein the state level corresponding to any driving mode is used to indicate a matching degree between any driving mode and the driving state of the driving vehicle; The control module is configured to determine a target driving mode of the driving vehicle from among the plurality of driving modes based on the state levels corresponding to the driving modes, and control the driving vehicle to drive according to the target driving mode; before determining the target driving mode of the driving vehicle from among the plurality of driving modes based on the state levels corresponding to the driving modes, the control module further includes: Obtaining driving instructions issued under the multiple driving modes; The controlling the vehicle to travel according to the target driving mode includes: Determine the driving instructions issued under the target driving mode among the received multiple driving instructions, and control the moving vehicle to drive according to the driving instructions under the target driving mode.

8. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one program code or instruction, and the at least one program code or instruction is loaded and executed by the processor so that the electronic device implements the vehicle control method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one program code or instruction, which is loaded and executed by a processor so that the computer implements the vehicle control method described in any one of claims 1-6.

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