CN115525012A

CN115525012A - Vehicle control method, vehicle control device, vehicle and storage medium

Info

Publication number: CN115525012A
Application number: CN202211216590.2A
Authority: CN
Inventors: 陈城; 周宏伟; 侯亚飞; 何文
Original assignee: Chongqing Changan Automobile Co Ltd
Current assignee: Chongqing Changan Automobile Co Ltd
Priority date: 2022-09-30
Filing date: 2022-09-30
Publication date: 2022-12-27

Abstract

The application relates to the technical field of automatic driving, in particular to a vehicle control method, a vehicle control device, a vehicle and a storage medium, wherein the method comprises the following steps: acquiring external environment information; planning according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm to generate first planning boundary, second planning boundary and safety boundary information; generating first control information according to the first planning boundary and generating second control information according to the second planning boundary; controlling the vehicle according to the first control information in a case where the first control information matches the second control information; under the condition that the first control information is not matched with the second control information, determining a target boundary according to the first planning boundary, the second planning boundary and the safety boundary information; and generating a control instruction according to the target boundary to control the vehicle. Therefore, the problems of safety and the like caused by vehicle system faults are solved, and the continuity and experience of intelligent driving of a user are improved.

Description

Vehicle control method, vehicle control device, vehicle and storage medium

Technical Field

The present application relates to the field of automatic driving technologies, and in particular, to a vehicle control method and apparatus, a vehicle, and a storage medium.

Background

The vehicle intelligent technology has great potential in the aspects of reducing traffic accidents, relieving traffic jam, improving road and vehicle utilization rate and the like, and becomes a competitive hot spot of numerous enterprises. The intelligent internet automobile is a new generation automobile which is provided with advanced vehicle-mounted sensors, controllers, actuators and the like, integrates modern communication and network technologies, realizes seamless connection of an in-automobile network, an out-automobile network and an inter-automobile network, has control functions of information sharing, complex environment sensing, intelligent decision making, automatic cooperation and the like, and can realize high-efficiency, safe, comfortable and energy-saving driving with an intelligent traveling system consisting of an intelligent road and auxiliary facilities. For automatic driving, most or almost all vehicles are controlled by a system, and how to avoid safety problems caused by system faults is very important.

In the related art, an automatic driving system provides a redundancy mechanism to prevent a Central Processing Unit (CPU) system from being blocked by a thread or provide a kinetic energy redundancy software architecture, which is suitable for different application scenarios.

However, the redundancy mechanism in the center of the related art does not consider the safety mechanism in the case of single point failure of an MCU (micro controller Unit), and the kinetic energy redundancy software architecture provided in the related art does not consider how to ensure the correctness of the calculation result of the chip a/B, and the current autopilot domain controller does not achieve full autopilot above level L4, and when the vehicle is autopilot at level L1-L3, the driver still has to keep alert and take back the vehicle control right at any time.

Disclosure of Invention

The application provides a vehicle control method, a vehicle control device, a vehicle and a storage medium, solves the problems of safety and the like caused by vehicle system faults, and improves the continuity and experience of intelligent driving of a user.

An embodiment of a first aspect of the present application provides a vehicle control method, including the following steps: acquiring external environment information; planning according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm respectively to generate first planning boundary, second planning boundary and safety boundary information; generating first control information according to the first planning boundary and generating second control information according to the second planning boundary; controlling the vehicle according to the first control information in a case where the first control information matches the second control information; or determining a target boundary according to the first planned boundary, the second planned boundary and the safety boundary information under the condition that the first control information is not matched with the second control information; and generating a control command according to the target boundary so as to control the vehicle.

According to the technical means, the problems of safety and the like caused by vehicle system faults are solved, and the continuity and experience of intelligent driving of users are improved.

Further, the external environment information includes sensor acquisition information and high-precision map information, and the external environment information is planned according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm respectively to generate a first planned boundary, a second planned boundary and safety boundary information, including: fusing the high-precision map information and the sensor acquisition information to generate target information; generating the first planning boundary and the second planning boundary according to the target information through the first preset algorithm and the second preset algorithm respectively; and generating the safety boundary information according to the sensor acquisition information or the target information through the third preset algorithm.

According to the technical means, the safety range is determined according to the generated safety boundary information, the safety of a driver is guaranteed, and the calculation force requirement is reduced.

Further, the fusing the high-precision map information and the external environment information to generate target information includes: respectively identifying and processing the sensor acquisition information and the high-precision map information to obtain first scene perception information and second scene perception information; and fusing the first scene perception information and the second scene perception information to generate the target information.

According to the technical means, the calculated planning boundary is more accurate according to the target information generated by fusion.

Further, the generating the first planning boundary and the second planning boundary according to the target information by the first preset algorithm and the second preset algorithm respectively includes: planning a transverse and longitudinal control target of the vehicle according to the target information; calculating a planned driving route of the vehicle according to the transverse and longitudinal control targets; and generating the first planned route according to the driving state of the vehicle and the planned driving route through the first preset algorithm, and generating the second planned route according to the driving state of the vehicle and the planned driving route through the second preset algorithm.

According to the technical means, the problem of misjudgment of the monitoring system is solved according to the two generated planning routes.

Further, the determining a target boundary according to the first planned boundary, the second planned boundary, and the safety boundary information includes: judging whether the first planning boundary and the second planning boundary are located in the safety boundary information; taking the first planned boundary as the target boundary if the first planned boundary is within the safety boundary information and the second planned boundary is not within the safety boundary information; or if the second planned boundary is within the safety boundary information and the first planned boundary is not within the safety boundary information, taking the second planned boundary as the target boundary; or generating the target boundary according to the safety boundary information under the condition that the first planning boundary and the second planning boundary are not located in the safety boundary information.

According to the technical means, the multi-channel voting mechanism selects the matched target boundary through multi-party result comparison, and the reliability of the system output result is improved.

Further, the vehicle control method further includes: acquiring fault information of the vehicle; and adjusting the automatic driving mode of the vehicle according to the fault information.

According to the technical means, the automatic driving mode of the vehicle is adjusted through the fault information, and the intelligence of vehicle driving is improved.

Further, the adjusting the automatic driving mode of the vehicle according to the fault information comprises: determining fault attributes according to the fault information, wherein the fault attributes comprise critical faults and noncritical faults; and under the condition that the fault attribute is a non-critical fault, adjusting the automatic driving mode of the vehicle after running for preset time.

According to the technical means, the running preset time of the self-driving system is set, a redundancy mechanism cannot be switched immediately when a vehicle breaks down, and the consistency of automatic driving is improved.

Further, the first preset algorithm and the second preset algorithm include heterogeneous algorithms, and the third preset algorithm includes a neural network algorithm.

According to the technical means, the heterogeneous algorithm can simultaneously support a single independent computer in a simd mode and a mimd mode or a group of independent computers interconnected by a high-speed network to complete a calculation task, and the neural network algorithm can learn the operation habits of drivers under different road conditions and continuously calculate to form a safety envelope.

An embodiment of a second aspect of the present application provides a vehicle control apparatus, including: the acquisition module is used for acquiring external environment information; the planning module is used for planning according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm respectively to generate a first planning boundary, a second planning boundary and safety boundary information; a generating module, configured to generate first control information according to the first planning boundary and generate second control information according to the second planning boundary; a first control module configured to control the vehicle according to the first control information when the first control information matches the second control information; a determining module, configured to determine a target boundary according to the first planned boundary, the second planned boundary, and the safety boundary information when the first control information and the second control information are not matched; and the second control module is used for generating a control instruction according to the target boundary so as to control the vehicle.

An embodiment of a third aspect of the present application provides a vehicle, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the vehicle control method as described in the above embodiments.

Further, the processors include a first processor, a second processor, a third processor and a fourth processor, the first processor is configured to obtain external environment information and perform planning according to the external environment information by using a first preset algorithm to generate a first planning boundary, the second processor is configured to obtain the external environment information and perform planning according to the external environment information by using a second preset algorithm to generate a second planning boundary, the third processor is configured to generate first control information according to the first planning boundary, and the fourth processor is configured to generate second control information according to the second planning boundary; the third processor or the fourth processor is further configured to control the vehicle according to the first control information if the first control information matches the second control information; or, under the condition that the first control information is not matched with the second control information, determining a target boundary according to the first planning boundary, the second planning boundary and the safety boundary information, and generating a control instruction according to the target boundary to control the vehicle.

A fourth aspect of the present application provides a computer-readable storage medium having stored thereon a computer program for execution by a processor for implementing the vehicle control method as in the above embodiments.

Therefore, the external environment information is obtained, planning is carried out according to the external environment information based on a first preset algorithm, a second preset algorithm and a third preset algorithm, first planning boundary information, second planning boundary information and safety boundary information are generated, first control information is generated according to the first planning boundary and second control information is generated according to the second planning boundary, the vehicle is controlled according to the first control information under the condition that the first control information is matched with the second control information, a target boundary is determined according to the first planning boundary, the second planning boundary and the safety boundary information under the condition that the first control information is not matched with the second control information, and a control command is generated according to the target boundary to control the vehicle. Therefore, the problems of safety and the like caused by vehicle system faults are solved, the L4-L5-level full-automatic driving requirements are met, the taking-over task when the self-driving system is in fault is completed by the self-driving system, the participation of a driver is not needed, the continuity and the experience of intelligent driving of a user are improved, and the time and the labor cost in development and later maintenance and upgrading are reduced.

Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 is a flow chart of a vehicle control method provided according to an embodiment of the application;

FIG. 2 is a block schematic diagram of vehicle control system logic according to one embodiment of the present application;

FIG. 3 is a schematic diagram of an ADS (Advanced Driving System) architecture according to an embodiment of the present application;

FIG. 4 is a flow chart of a vehicle control method according to one embodiment of the present application;

FIG. 5 is a block schematic diagram of a vehicle control apparatus according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a vehicle according to an embodiment of the present application.

Description of the reference numerals: 10-vehicle control device, 100-acquisition module, 200-planning module, 300-generation module, 400-first control module, 500-determination module, 600-second control module, 601-memory, 602-processor, 603-communication interface.

Detailed Description

Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are illustrative and intended to explain the present application and should not be construed as limiting the present application.

A vehicle control method, a device, a vehicle, and a storage medium of the embodiments of the present application are described below with reference to the drawings. In order to solve the safety problem caused by the vehicle system failure in the background art, the application provides a vehicle control method, in which external environment information is acquired, planning is performed according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm to generate a first planning boundary, a second planning boundary and safety boundary information, first control information is generated according to the first planning boundary and second control information is generated according to the second planning boundary, a vehicle is controlled according to the first control information under the condition that the first control information is matched with the second control information, a target boundary is determined according to the first planning boundary, the second planning boundary and the safety boundary information under the condition that the first control information is not matched with the second control information, and a control instruction is generated according to the target boundary to control the vehicle. Therefore, the problems of safety and the like caused by vehicle system faults are solved, and the continuity and experience of intelligent driving of a user are improved.

Specifically, fig. 1 is a flowchart of a vehicle control method provided in an embodiment of the present application.

As shown in fig. 1, the vehicle control method includes the steps of:

in step S101, outside environment information is acquired.

It can be understood that, in the embodiments of the present application, the sensor includes a laser radar and a camera to acquire external environment information, including acquiring vehicle information, pedestrian information, or obstacle information around the vehicle, and the like, around the vehicle, or acquiring information such as traffic lights, buildings, or lane lines, around the vehicle through a high-precision map.

In step S102, planning is performed according to the external environment information through a first preset algorithm, a second preset algorithm, and a third preset algorithm, respectively, to generate first planning boundary, second planning boundary, and safety boundary information.

Optionally, in some embodiments, the first preset algorithm and the second preset algorithm comprise heterogeneous algorithms, and the third preset algorithm comprises a neural network algorithm.

Optionally, in some embodiments, the external environment information includes sensor acquisition information and high-precision map information, and is respectively planned according to the external environment information through a first preset algorithm, a second preset algorithm, and a third preset algorithm, so as to generate a first planned boundary, a second planned boundary, and safety boundary information, including: fusing the high-precision map information and the sensor acquisition information to generate target information; generating a first planning boundary and a second planning boundary according to the target information through a first preset algorithm and a second preset algorithm respectively; and generating safety boundary information according to the information acquired by the sensor or the target information through a third preset algorithm.

In some embodiments, the generating of the target information by fusing the high-precision map information and the external environment information includes: respectively identifying and processing the sensor acquisition information and the high-precision map information to obtain first scene perception information and second scene perception information; and fusing the first scene perception information and the second scene perception information to generate target information.

The technical personnel in the field should understand that the acquired high-precision map information and the sensor acquisition information are fused to generate target information, the target information is generated into a first planning boundary and a second planning boundary through a first preset algorithm and a second preset algorithm, the neural network algorithm continuously learns based on the neural network algorithm according to the information and/or the target information acquired by the sensor, and external sensing information is used to generate safety boundary information.

Specifically, the embodiment of the application takes information acquired by a high-precision map and sensor acquisition information as input, accurately senses the surrounding environment of an automatic driving vehicle through a series of calculation and processing to obtain first scene sensing information, fuses the sensors, the vehicle, pedestrians and obstacle targets identified by an internal algorithm to obtain second scene sensing information, and fuses the first scene sensing information and the second scene sensing information to generate target information.

Further, in some embodiments, generating the first planning boundary and the second planning boundary according to the target information by the first preset algorithm and the second preset algorithm, respectively, includes: planning a transverse and longitudinal control target of the vehicle according to the target information; calculating a planned driving route of the vehicle according to the transverse and longitudinal control targets; and generating a first planned route according to the driving state of the vehicle and the planned driving route through a first preset algorithm, and generating a second planned route according to the driving state of the vehicle and the planned driving route through a second preset algorithm.

The transverse and longitudinal control targets comprise a speed target and an acceleration target, the driving state of the vehicle comprises an automatic driving mode and a non-automatic driving mode, and the planned driving route of the user is obtained through the self-driving system.

It should be understood by those skilled in the art that the transverse and longitudinal control targets of the vehicle are planned based on the target information, the planning decision information is output according to the driving state of the vehicle and the planned driving route to generate a first planned route, and the planning decision information is output according to the driving state of the vehicle and the planned driving route through a second preset algorithm to generate a second planned route.

In step S103, first control information is generated according to the first planned boundary and second control information is generated according to the second planned boundary.

It can be understood that, when generating the first control information, the embodiment of the application may process the first planned boundary based on a preset heterogeneous algorithm to obtain the first control information, where the first control information may be a control instruction for the vehicle, such as controlling acceleration or deceleration of the vehicle, and is not limited in this respect.

It should be noted that the preset heterogeneous algorithm is only exemplary and is not a limitation to the present application, and those skilled in the art may also adopt other algorithms when generating the first control information according to the first planning boundary; in the embodiment of the present application, the manner of generating the second control information according to the second planned boundary is consistent with the above-mentioned strategy of generating the first control information according to the first planned boundary, and details are not repeated here to avoid redundancy.

In step S104, the vehicle is controlled based on the first control information when the first control information matches the second control information.

It can be understood that, if the generated first control information is consistent with the second control information, it indicates that the chip of the vehicle self-driving system is not failed, and at this time, the vehicle may maintain the current driving system state.

In step S105, in the case that the first control information does not match the second control information, a target boundary is determined according to the first planned boundary, the second planned boundary, and the safety boundary information.

Wherein, in some embodiments, determining the target boundary based on the first planned boundary, the second planned boundary, and the safety boundary information comprises: judging whether the first planning boundary and the second planning boundary are positioned in the safety boundary information or not; taking the first planned boundary as a target boundary under the condition that the first planned boundary is located in the safety boundary information and the second planned boundary is not located in the safety boundary information; or taking the second planned boundary as the target boundary under the condition that the second planned boundary is located in the safety boundary information and the first planned boundary is not located in the safety boundary information; or generating the target boundary according to the safety boundary information under the condition that the first planning boundary and the second planning boundary are not located in the safety boundary information.

In step S106, a control instruction is generated to control the vehicle according to the target boundary.

Specifically, the embodiment of the application outputs the generated target boundary to control monitoring, the control monitoring generates a control instruction, and degradation processing is performed on an automatic vehicle driving system or parking processing or emergency braking is performed on a vehicle.

Therefore, according to the implementation of the method, external environment information is obtained, planning is carried out according to the external environment information based on a first preset algorithm, a second preset algorithm and a third preset algorithm, first planning boundary information, second planning boundary information and safety boundary information are generated, first control information is generated according to the first planning boundary and second control information is generated according to the second planning boundary, the vehicle is controlled according to the first control information under the condition that the first control information is matched with the second control information, a target boundary is determined according to the first planning boundary, the second planning boundary and the safety boundary information under the condition that the first control information is not matched with the second control information, and a control command is generated according to the target boundary to control the vehicle. Therefore, the problems of safety and the like caused by vehicle system faults are solved, the problem of misjudgment caused by algorithm defects of the monitoring system is solved, and the continuity and the experience of intelligent driving of a user are improved.

Further, in some embodiments, the vehicle control method further comprises: acquiring fault information of a vehicle; and adjusting the automatic driving mode of the vehicle according to the fault information.

It should be appreciated that if the vehicle is unable to maintain a high level of autopilot conditions, the autopilot system obtains fault information for the vehicle and adjusts the autopilot mode of the vehicle based on the fault information for the vehicle.

Wherein, in some embodiments, adjusting the autonomous driving mode of the vehicle based on the fault information comprises: determining fault attributes according to the fault information, wherein the fault attributes comprise critical faults and non-critical faults; and under the condition that the fault attribute is a non-critical fault, adjusting the automatic driving mode of the vehicle after running for a preset time.

Determining a fault attribute according to the fault information, if the fault attribute is a non-critical fault, continuously operating the self-driving system within a preset time, adjusting an automatic driving mode of the vehicle after the self-driving system operates for the preset time, and switching to redundancy control; if the fault attribute is a critical fault, the function of the self-driving system is degraded to enter a safe state, and if the self-driving system is degraded and cannot enter the safe state, the vehicle is safely stopped or emergently braked.

In order to further understand the vehicle control method according to the embodiment of the present application, the following description is made in detail with reference to fig. 2 to 4, where fig. 2 is a block schematic diagram of a logic of a vehicle control system according to an embodiment of the present application, fig. 3 is an architecture schematic diagram of an ADS according to an embodiment of the present application, and fig. 3 is a flowchart of the vehicle control method according to an embodiment of the present application.

In this embodiment, as shown in fig. 2 and 3, the vehicle control system includes two chips (chip 1 and chip 2). Wherein, the chip 1 is a main chip, generally, the same system modules in the chip 1 and the chip 2 monitor heartbeat mutually, if any system module in the chip fails, the other same system module reports a fault state to the security policy module for processing; if any system module in the chip 1 fails, the chip 2 switches to the chip 2 for control after monitoring the heartbeat to find a fault; if any system module in the chip 2 fails, the function of the self-driving system is degraded, but the normal safe operation is not influenced. The decision-making verification module obtains a safety range through input sensor information, obtains the safety range based on the sensor information and outputs the safety range to a safety strategy; the control arbitration module arbitrates the control result of the double chips and judges whether the output instruction is correct or not. The safety strategy is responsible for processing faults of the double chips and the double-chip internal system module and judging whether the results of the double-chip planning decision 1 and the planning decision 2 conform to a safety range calculated by the decision check module according to external sensing information, and if the results of the planning decision 1 and the planning decision 2 are consistent, the result of the planning decision 1 is output and can be used as a safety strategy; if the results of the planning decision 1 and the planning decision 2 are not consistent, the planning decision 1 is within a safety range, and the result of the planning decision 1 is output to be used as a 'safety strategy'; the planning decision 2 is in a safety range, and the result of the planning decision 2 is output to be a 'safety strategy'; if the results of the planning decision 1 and the planning decision 2 are not consistent and are not in the safety range, the results of the planning decision 1/2 are not output to be used as the safety strategy.

Specifically, as shown in fig. 4, after the automatic driving domain controller is activated, the dual chips respectively output the sensing fusion 11 and the sensing fusion 21 based on the heterogeneous algorithm by using external sensing information, and respectively output corresponding target information to the respective planning decision 12 and the planning decision 22 based on the heterogeneous algorithm by using sensing information, and the planning decision respectively outputs the planning decision information to the control 13 and the control 23 and the decision check 16 based on the heterogeneous algorithm by using target information.

Then, the decision check 16 is responsible for collecting fault information of the internal system modules of the chip 1 and the chip 2 and sending the fault information to the security policy 15/25 for processing, meanwhile, the decision check 16 outputs a security range decision check 16 based on a neural network algorithm to transmit planning decision information of the security range and the chip 1 and the chip 2 to the security policy 15/25, and the controller 13 and the controller 23 respectively output control information to the control arbiter 14/24 based on a heterogeneous algorithm by using the planning decision information.

Then, the security policy 15/25 respectively judges whether the first planning boundary and the second planning boundary of the planning decision information of the chip 1 and the chip 2 fall within the security boundary information, if the chip 1 meets the requirements or the chip 1 and the chip 2 have the same results, the security policy has no action; if the chip 2 is satisfied, the safety strategy selects the planning decision information of the chip 2 as a safety boundary; if the received planning decision 1/2 results are not available or the arbitration results are inconsistent, a safety boundary is output to the control arbitration based on the safety range.

If the safety strategy 15/25 cannot maintain the high-level automatic driving condition, a degradation instruction is preferentially sent to the state machine for degradation processing, and when the safety strategy 15/25 cannot process system faults and the system degradation cannot enter a safety state, the vehicle is controlled to be safely stopped, and blind processing (emergency braking in emergency) and the like are performed.

And finally, the control arbitration 14/24 compares the control results of the chip 1 and the chip 2, if the results are inconsistent, the safety policy is reported, and if the safety boundary is received to be valid, the control is performed by connecting to the safety boundary.

It should be noted that, in order to avoid unexpected exit of the self-driving system due to common cause failure, the chip 1 and the chip 2 should be physically isolated, and different power supplies should be provided to ensure complete independence between them.

According to the vehicle control method provided by the embodiment of the application, the external environment information is obtained, planning is carried out according to the external environment information based on a first preset algorithm, a second preset algorithm and a third preset algorithm, a first planning boundary, a second planning boundary and safety boundary information are generated, first control information is generated according to the first planning boundary and second control information is generated according to the second planning boundary, the vehicle is controlled according to the first control information under the condition that the first control information is matched with the second control information, a target boundary is determined according to the first planning boundary, the second planning boundary and the safety boundary information under the condition that the first control information is not matched with the second control information, and a control instruction is generated according to the target boundary to control the vehicle. Therefore, the problems of safety and the like caused by vehicle system faults are solved, the taking-over task when the self-driving system faults meet the L4-L5-level full-automatic driving requirement is completed by the self-driving system, the participation of a driver is not needed, the continuity and experience of intelligent driving of a user are improved, and the time and labor cost in development and later maintenance upgrading are reduced.

Next, a vehicle control apparatus proposed according to an embodiment of the present application is described with reference to the drawings.

Fig. 5 is a block diagram schematically illustrating a vehicle control device according to an embodiment of the present application.

As shown in fig. 5, the vehicle control device 10 includes: an acquisition module 100, a planning module 200, a generation module 300, a first control module 400, a determination module 500, and a second control module 600.

The acquiring module 100 is configured to acquire external environment information; the planning module 200 is configured to plan according to external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm, respectively, and generate first planning boundary, second planning boundary and safety boundary information; a generating module 300, configured to generate first control information according to the first planning boundary and generate second control information according to the second planning boundary; a first control module 400 for controlling the vehicle according to the first control information in case that the first control information matches the second control information; a determining module 500, configured to determine a target boundary according to the first planned boundary, the second planned boundary, and the safety boundary information when the first control information is not matched with the second control information; and a second control module 600 for generating a control command to control the vehicle according to the target boundary.

Further, the external environment information includes sensor acquisition information and high-precision map information, and the planning module 200 is specifically configured to: fusing the high-precision map information and the sensor acquisition information to generate target information; generating a first planning boundary and a second planning boundary according to the target information through a first preset algorithm and a second preset algorithm respectively; and generating safety boundary information according to the information acquired by the sensor or the target information through a third preset algorithm.

Further, the planning module 200 is further configured to: respectively identifying and processing the sensor acquisition information and the high-precision map information to obtain first scene perception information and second scene perception information; and fusing the first scene perception information and the second scene perception information to generate target information.

Further, the planning module 200 is further configured to: planning a transverse and longitudinal control target of the vehicle according to the target information; calculating a planned driving route of the vehicle according to the transverse and longitudinal control targets; and generating a first planned route according to the driving state of the vehicle and the planned driving route through a first preset algorithm, and generating a second planned route according to the driving state of the vehicle and the planned driving route through a second preset algorithm.

Further, the determining module 500 is configured to determine whether the first planned boundary and the second planned boundary are located in the safety boundary information; taking the first planned boundary as a target boundary under the condition that the first planned boundary is positioned in the safety boundary information and the second planned boundary is not positioned in the safety boundary information; or taking the second planned boundary as the target boundary under the condition that the second planned boundary is positioned in the safety boundary information and the first planned boundary is not positioned in the safety boundary information; or generating the target boundary according to the safety boundary information under the condition that the first planning boundary and the second planning boundary are not positioned in the safety boundary information.

Further, the vehicle control device 10 further includes: and the adjusting module is used for acquiring the fault information of the vehicle and adjusting the automatic driving mode of the vehicle according to the fault information.

Further, the adjusting module is specifically configured to: determining fault attributes according to the fault information, wherein the fault attributes comprise a critical fault and a non-critical fault; and under the condition that the fault attribute is a non-critical fault, adjusting the automatic driving mode of the vehicle after running for a preset time.

Further, the first preset algorithm and the second preset algorithm comprise heterogeneous algorithms, and the third preset algorithm comprises a neural network algorithm.

It should be noted that the foregoing explanation of the embodiment of the vehicle control method is also applicable to the vehicle control device of the embodiment, and is not repeated herein.

According to the vehicle control device provided by the embodiment of the application, the external environment information is obtained, planning is carried out according to the external environment information based on the first preset algorithm, the second preset algorithm and the third preset algorithm, the first planning boundary, the second planning boundary and the safety boundary information are generated, the first control information is generated according to the first planning boundary, the second control information is generated according to the second planning boundary, the vehicle is controlled according to the first control information under the condition that the first control information is matched with the second control information, the target boundary is determined according to the first planning boundary, the second planning boundary and the safety boundary information under the condition that the first control information is not matched with the second control information, and the control command is generated according to the target boundary so as to control the vehicle. Therefore, the problems of safety and the like caused by vehicle system faults are solved, the taking-over task when the self-driving system faults meet the L4-L5-level full-automatic driving requirement is completed by the self-driving system, the participation of a driver is not needed, the continuity and experience of intelligent driving of a user are improved, and the time and labor cost in development and later maintenance upgrading are reduced.

Fig. 6 is a schematic structural diagram of a vehicle according to an embodiment of the present application. The vehicle may include:

a memory 601, a processor 602, and a computer program stored on the memory 601 and executable on the processor 602.

The processor 602, when executing the program, implements the vehicle control method provided in the above-described embodiments.

Further, the vehicle further includes:

a communication interface 603 for communication between the memory 601 and the processor 602.

The memory 601 is used for storing computer programs that can be run on the processor 602.

The Memory 601 may include a high-speed RAM (Random Access Memory) Memory, and may also include a non-volatile Memory, such as at least one disk Memory.

If the memory 601, the processor 602 and the communication interface 603 are implemented independently, the communication interface 603, the memory 601 and the processor 602 may be connected to each other through a bus and perform communication with each other. The bus may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 6, but that does not indicate only one bus or one type of bus.

Optionally, in a specific implementation, if the memory 601, the processor 602, and the communication interface 603 are integrated into a chip, the memory 601, the processor 602, and the communication interface 603 may complete mutual communication through an internal interface.

The processor 602 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.

Optionally, the processor 602 includes a first processor, a second processor, a third processor and a fourth processor, the first processor is configured to obtain external environment information and perform planning according to the external environment information by using a first preset algorithm to generate a first planning boundary, the second processor is configured to obtain the external environment information and perform planning according to the external environment information by using a second preset algorithm to generate a second planning boundary, the third processor is configured to generate first control information according to the first planning boundary, and the fourth processor is configured to generate second control information according to the second planning boundary; the third processor or the fourth processor is further used for controlling the vehicle according to the first control information under the condition that the first control information is matched with the second control information; or under the condition that the first control information is not matched with the second control information, determining a target boundary according to the first planning boundary, the second planning boundary and the safety boundary information, and generating a control instruction according to the target boundary to control the vehicle.

Embodiments of the present application also provide a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the vehicle control method as above.

In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless explicitly defined otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.

It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a programmable gate array, a field programmable gate array, or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are exemplary and should not be construed as limiting the present application and that changes, modifications, substitutions and alterations in the above embodiments may be made by those of ordinary skill in the art within the scope of the present application.

Claims

1. A vehicle control method characterized by comprising:

acquiring external environment information;

planning according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm respectively to generate first planning boundary, second planning boundary and safety boundary information;

generating first control information according to the first planning boundary and generating second control information according to the second planning boundary;

controlling the vehicle according to the first control information in a case where the first control information matches the second control information; or

Determining a target boundary according to the first planned boundary, the second planned boundary and the safety boundary information under the condition that the first control information is not matched with the second control information;

and generating a control instruction according to the target boundary to control the vehicle.

2. The vehicle control method according to claim 1, wherein the external environment information includes sensor acquisition information and high-precision map information, and the generating of the first planned boundary, the second planned boundary and the safety boundary information by respectively planning according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm includes:

fusing the high-precision map information and the sensor acquisition information to generate target information;

generating the first planning boundary and the second planning boundary according to the target information through the first preset algorithm and the second preset algorithm respectively;

and generating the safety boundary information according to the sensor acquisition information or the target information through the third preset algorithm.

3. The vehicle control method according to claim 2, wherein the fusion processing of the high-precision map information and the external environment information to generate target information includes:

respectively identifying and processing the sensor acquisition information and the high-precision map information to obtain first scene perception information and second scene perception information;

and fusing the first scene perception information and the second scene perception information to generate the target information.

4. The vehicle control method according to claim 3, wherein the generating the first planned boundary and the second planned boundary according to the target information by the first preset algorithm and the second preset algorithm, respectively, includes:

planning a transverse and longitudinal control target of the vehicle according to the target information;

calculating a planned driving route of the vehicle according to the transverse and longitudinal control targets;

generating the first planned route according to the driving state of the vehicle and the planned driving route by the first preset algorithm, and

and generating the second planned route according to the driving state of the vehicle and the planned driving route through the second preset algorithm.

5. The vehicle control method of claim 1, wherein determining a target boundary based on the first planned boundary, the second planned boundary, and the safety boundary information comprises:

judging whether the first planning boundary and the second planning boundary are positioned in the safety boundary information or not;

taking the first planned boundary as the target boundary if the first planned boundary is within the safety boundary information and the second planned boundary is not within the safety boundary information; or

Taking the second planned boundary as the target boundary if the second planned boundary is within the safety boundary information and the first planned boundary is not within the safety boundary information; or

And under the condition that the first planning boundary and the second planning boundary are not positioned in the safety boundary information, generating the target boundary according to the safety boundary information.

6. The vehicle control method according to claim 1, characterized by further comprising:

acquiring fault information of the vehicle;

and adjusting the automatic driving mode of the vehicle according to the fault information.

7. The vehicle control method according to claim 6, wherein the adjusting the automatic driving mode of the vehicle according to the failure information includes:

determining fault attributes according to the fault information, wherein the fault attributes comprise critical faults and non-critical faults;

and under the condition that the fault attribute is a non-critical fault, adjusting the automatic driving mode of the vehicle after running for preset time.

8. The vehicle control method according to claim 1, characterized in that the first preset algorithm and the second preset algorithm include heterogeneous algorithms, and the third preset algorithm includes a neural network algorithm.

9. A vehicle control apparatus characterized by comprising:

the acquisition module is used for acquiring external environment information;

the planning module is used for planning according to the external environment information through a first preset algorithm, a second preset algorithm and a third preset algorithm respectively to generate a first planning boundary, a second planning boundary and safety boundary information;

a generating module, configured to generate first control information according to the first planning boundary and generate second control information according to the second planning boundary;

a first control module configured to control the vehicle according to the first control information when the first control information matches the second control information;

a determining module, configured to determine a target boundary according to the first planned boundary, the second planned boundary, and the safety boundary information when the first control information and the second control information are not matched;

and the second control module is used for generating a control instruction according to the target boundary so as to control the vehicle.

10. A vehicle, characterized by comprising a processor and a memory, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the vehicle control method according to any one of claims 1 to 8.

11. The vehicle of claim 10, wherein the processor comprises a first processor, a second processor, a third processor, and a fourth processor, the first processor is configured to obtain external environment information and generate a first planning boundary by planning according to the external environment information through a first preset algorithm, the second processor is configured to obtain external environment information and generate a second planning boundary by planning according to the external environment information through a second preset algorithm, the third processor is configured to generate first control information according to the first planning boundary, and the fourth processor is configured to generate second control information according to the second planning boundary;

the third processor or the fourth processor is further configured to control the vehicle according to the first control information if the first control information matches the second control information; or, under the condition that the first control information is not matched with the second control information, determining a target boundary according to the first planning boundary, the second planning boundary and the safety boundary information, and generating a control instruction according to the target boundary to control the vehicle.

12. A non-transitory computer-readable storage medium containing a computer program, wherein the computer program, when executed by a processor, causes the processor to execute the vehicle control method according to any one of claims 1 to 8.