KR20230090398A - Autonomous driving computing platform based on redundant architecture - Google Patents

Abstract

The present disclosure provides an autonomous driving control system based on a redundant structure. This system includes a plurality of sensors configured to sense information about the surrounding environment of the autonomous vehicle, holds the main control right of the autonomous vehicle, and controls the autonomous vehicle by processing signals received from the plurality of sensors. A first processor configured to generate a first set of control signals used in the vehicle and a second processor configured to sense the surrounding environment of the vehicle by processing signals received from at least some of the plurality of sensors, wherein the first processor When an operation error is detected, the first processor transfers the main control right to the second processor, and the second processor is reconfigured to generate the first set of control signals.

Description

Autonomous driving computing platform based on redundant structure {AUTONOMOUS DRIVING COMPUTING PLATFORM BASED ON REDUNDANT ARCHITECTURE}

The present disclosure relates to a self-driving computing platform based on a redundant structure, and more particularly, by providing a redundant structure including a plurality of redundant processors or systems for self-driving control, various defects or operation errors related to self-driving control. It is about an autonomous driving computing platform that can effectively respond to autonomous driving control and provide safety and reliability.

An autonomous driving system may use a plurality of heterogeneous sensors, a plurality of power supplies, or a plurality of computing components to ensure reliable driving and safety. For example, when a plurality of computing components (or processors) process the same sensing data to generate self-driving control signals, a processor with an operating error is detected by comparing the self-driving control signals, and an appropriate response is made. By executing the procedure, more reliable autonomous driving can be implemented. In addition, various software and hardware reinforcements are being made to operate autonomous vehicles effectively and stably.

In addition, in order to increase the reliability of the safety of the autonomous driving system, a plurality of processors and backup processors that simultaneously perform redundant functions may be provided. However, while such an autonomous driving system having a multiplexing structure has advantages of high performance and high safety, there is a disadvantage of high power consumption because a plurality of processors perform the same control function. In particular, since the autonomous driving system performs image analysis using a high-performance processor such as a GPU to recognize the surrounding environment and generate an autonomous driving control signal based thereon, a large amount of computation is required, which leads to high power consumption.

In general, autonomous driving systems are applied to electric vehicles, and power consumption according to the amount of computation required for autonomous driving control directly affects the fuel efficiency of electric vehicles. In a situation where the capacity of batteries used in electric vehicles is limited to a certain level, a method for improving safety and reliability at the same time as increasing power efficiency has not yet been provided.

The present disclosure provides a method for configuring and operating an autonomous driving system using a dual structure-based autonomous driving computing platform in order to solve the problems of the conventional autonomous driving system described above.

According to an embodiment of the present disclosure, an autonomous driving control system based on a redundant structure includes a plurality of sensors configured to detect information about the surrounding environment of an autonomous vehicle, and holds a main control right of the autonomous vehicle, A first processor configured to process signals received from a plurality of sensors to generate a first set of control signals used to control an autonomous vehicle; and a second processor configured to detect, and when an operation error by the first processor is detected, the first processor transfers the main control right to the second processor so that the second processor generates a first set of control signals. is reconstructed

According to an embodiment, the autonomous driving control system further includes a memory for storing a plurality of pattern information related to an operation error on the autonomous driving control system, and an operation pattern of a first processor or a peripheral device associated with the first processor is stored in the memory. If it is the same as or similar to at least one of the plurality of pattern information stored in , it is determined that an operation error of the first processor has occurred.

According to an embodiment, the plurality of pattern information includes at least one of an EMI or EMC operation error pattern, a temperature error pattern, a processor error pattern, a power error pattern, a memory CRC error pattern, and a memory bit error pattern.

According to an embodiment, the second processor to which the main control right is transferred in the autonomous driving control system is reconfigured to generate at least a part of the first set of control signals according to the detected surrounding environment.

According to an embodiment, the second processor to which the main control right is transferred in the autonomous driving control system applies different sensor-specific weights to signals received from a plurality of sensors when the sensed surrounding environment requires a different level of autonomous driving control. restructured to

According to an embodiment, the second processor to which the main control right is transferred in the autonomous driving control system, when the sensed surrounding environment requires a different level of autonomous driving control, responds to signals received from a plurality of sensors as objects having different processing capacities. It is restructured to apply the recognition model.

According to an embodiment, while a first processor generates a first set of control signals by processing signals received from at least some of a plurality of sensors in an autonomous driving system, a second processor is configured to process signals received from at least some of the plurality of sensors. The signals are independently processed to generate a second set of control signals that are of a smaller range than the set of control signals.

According to one embodiment, the plurality of sensors in the autonomous driving control system includes at least one of a LiDAR sensor, a laser sensor, an infrared sensor, and a camera.

According to another embodiment of the present disclosure, an autonomous driving control method based on a redundant structure, executed by at least one processor, includes sensing information about the surrounding environment of an autonomous vehicle by a plurality of sensors, generating a first set of control signals used for controlling the autonomous vehicle by processing signals received from a plurality of sensors by a first processor having a main control right for the autonomous vehicle; detecting the surrounding environment of the vehicle by processing signals received from at least some of the plurality of sensors, and when an operation error by the first processor is detected, the first processor transfers the main control right to the second processor Moving forward, reconfiguring the second processor to generate the first set of control signals.

According to another embodiment of the present disclosure, a computer program stored in a computer readable recording medium is provided to execute an autonomous driving control method in a computer.

According to various embodiments of the present disclosure, when a main processor error is detected based on a fault list, the redundant structure-based autonomous driving control system between a plurality of redundant processors in order to minimize the risk of the error. Reliability regarding the safety of autonomous driving can be secured by minimizing the time required for switching control rights.

According to various embodiments of the present disclosure, in operating a redundant structure-based autonomous driving control system, a backup processor on standby to respond to a failure of a main processor by determining a specific sensor set necessary for autonomous driving control according to surrounding conditions. It is possible to effectively reduce the power consumed in

Effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, wherein like reference numbers indicate like elements, but are not limited thereto.
1 is a diagram illustrating an example in which an autonomous driving system based on a dual structure according to an embodiment of the present disclosure controls road driving of an autonomous vehicle.
2 is a block diagram showing the configuration of an autonomous driving control system according to an embodiment of the present disclosure.
3 is a block diagram showing the configuration of an error detection unit according to an embodiment of the present disclosure.
4 is a block diagram illustrating configurations of a first processor and a second processor according to an embodiment of the present disclosure.
5 is a flowchart illustrating an autonomous driving control method based on a redundant structure according to an embodiment of the present disclosure.
6 is a flowchart illustrating an autonomous driving control method based on a redundant structure according to another embodiment of the present disclosure.

Hereinafter, specific details for the implementation of the present disclosure will be described in detail with reference to the accompanying drawings. However, in the following description, if there is a risk of unnecessarily obscuring the gist of the present disclosure, detailed descriptions of well-known functions or configurations will be omitted.

In the accompanying drawings, identical or corresponding elements are given the same reference numerals. In addition, in the description of the following embodiments, overlapping descriptions of the same or corresponding components may be omitted. However, omission of a description of a component does not intend that such a component is not included in an embodiment.

Advantages and features of the disclosed embodiments, and methods of achieving them, will become apparent with reference to the following embodiments in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms, only the present embodiments make the present disclosure complete, and those of ordinary skill in the art to which the present disclosure belongs It is provided only to fully inform the person of the scope of the invention.

Terms used in this disclosure will be briefly described, and the disclosed embodiments will be described in detail.

The terminology used in the present disclosure has been selected from general terms that are currently widely used as much as possible while considering functions in the present disclosure, but they may vary depending on the intention or precedent of a person skilled in the related field, the emergence of new technologies, and the like. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, terms used in the present disclosure should be defined based on the meaning of the term and the general content of the present disclosure, not simply the name of the term.

Expressions in the singular number in this disclosure include plural expressions unless the context clearly dictates that they are singular. Also, plural expressions include singular expressions unless the context clearly specifies that they are plural.

In the entirety of the present disclosure, when a certain part is said to 'include' a certain component, it means that it may further include other components, not excluding other components unless otherwise stated.

The term 'unit' or 'module' used in the specification means a software or hardware component, and the 'unit' or 'module' performs certain roles. However, 'unit' or 'module' is not meant to be limited to software or hardware. A 'unit' or 'module' may be configured to reside in an addressable storage medium and may be configured to reproduce one or more processors. Thus, as an example, 'unit' or 'module' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, properties , procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, or variables. Functions provided within components and 'units' or 'modules' may be combined into a smaller number of components and 'units' or 'modules', or may be combined into additional components and 'units' or 'modules'. can be further separated.

According to one embodiment of the present disclosure, a 'unit' or 'module' may be implemented with a processor and a memory. The term “processor” should be interpreted broadly to include general-purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, and the like. In some circumstances, “processor” may refer to an application specific integrated circuit (ASIC), programmable logic device (PLD), field programmable gate array (FPGA), or the like. The term "processor" refers to a combination of processing devices, such as, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in conjunction with a DSP core, or any other such configuration. may also refer to

In the present disclosure, 'system' may refer to a configuration including one or more servers, computing devices, software modules or components that execute a recommendation function and/or a function of predicting business growth probability, or a combination thereof. and, for example, it may refer to one or more computing devices, server devices, or distributed computing devices providing cloud services, but is not limited thereto. Hereinafter, when describing embodiments of a redundant structure-based autonomous driving system, the system includes one or more of a software architecture, an operating system, a library, a driver, or hardware modules such as processors and memories that implement redundancy-based autonomous driving. It may mean that components are combined.

1 is a diagram illustrating an example in which an autonomous driving system based on a dual structure according to an embodiment of the present disclosure controls road driving of an autonomous vehicle.

The autonomous vehicle 110 shown in FIG. 1 may include an autonomous driving module 120 generating an autonomous driving control signal. The self-driving module 120 includes a main block (hereinafter referred to as 'first processor') configured to process signals received from a plurality of sensors to generate a set of control signals used for controlling the self-driving vehicle 110. ) 112 and a shadow block (hereinafter referred to as 'second processor') 124 configured to sense the surrounding environment of the vehicle 110 by processing signals received from at least some of the plurality of sensors. can do. In addition, the self-driving vehicle 110 may include a plurality of sensors such as a camera 130, lidar 140, and radar 150, but the configuration is not limited thereto.

The self-driving module 120 may process signals (or sensing data) received from the plurality of sensors 130 , 140 , and 150 to perform ambient environment or object recognition. The road driving example 100 shows an example in which the autonomous driving module 120 recognizes an object and a surrounding environment including another vehicle 160 based on signals received from a plurality of sensors.

In one embodiment, the main block (first processor) 122 of the autonomous driving module 120 holds the main control right for the autonomous vehicle 110 . The main block 122 holding the main control right executes all functions of autonomous driving based on signals received from all sensors 130, 140, and 150 mounted in the vehicle 110, or controls the operation of sensors 130, 140, and 150. Only some functions of autonomous driving may be executed according to the surrounding environment recognized based on the signal For example, the main block 122 performs high-performance object recognition based on signals received from all sensors 130, 140, and 150. Precise and accurate autonomous driving control can be executed by recognizing the surrounding environment using the model.

In one embodiment, the shadow block (second processor) 124 of the autonomous driving module 120 may sense the surrounding environment of the vehicle without holding the main control right. When the autonomous driving module 120 requests a different level of autonomous driving control according to the surrounding environment, the shadow block (second processor) 124 may apply an object recognition model of different processing capacity or a weight for each sensor. there is. For example, the shadow block 124 applies a high weight to the camera 130 for low-level autonomous driving control when the surrounding environment is relatively simple and the risk of an accident is low, while the other sensors 140 and 150 ), a low weight can be applied. In another example, the shadow block 124 may apply a high weight to all sensors 130, 140, and 150 for a high level of autonomous driving control when the surrounding environment is relatively complex and the risk of an accident is high. Additionally or alternatively, the shadow block (second processor) 124 may execute a minimum function overlapping with the main block (first processor) 122 even in the absence of a main control right. For example, the shadow block 124 may execute low-level autonomous driving control based on signals received from some of the sensors 140 and 150 in a state in which there is no main control right.

In one embodiment, the shadow block (second processor) 124 sends a first set of control signals to the main block (first processor) 122 to respond to defects in the main block (first processor) 122. During creation, a minimum autonomous driving function overlapping with the main block (first processor) 122 may be executed. At this time, the shadow block (second processor) 124 performs the least overlapping self-driving function, than the set of control signals generated by the main block (first processor) 122 to execute all autonomous driving functions. A small range of control signal sets can be generated.

In one embodiment, an error pattern of the main block (first processor) 122 is detected based on a fault list, and when it is determined that a defect has occurred according to the detection result, the self-driving vehicle 110 The main control right may be transferred from the main block (first processor) 122 to the shadow block (second processor) 124 . The shadow block (second processor) 124 to which control has been transferred generates a control signal for performing all autonomous driving functions performed by the main block (first processor) 122 or, depending on the recognized surrounding environment, generates some control signals. It can generate control signals to perform functions.

In one embodiment, the error pattern information of the defect list includes, but is not limited to, electromagnetic interference (EMI), electromagnetic compatibility (EMC), temperature, processor, power, memory CRC, memory bit error pattern, and the like. The first processor or the second processor may detect an internal defect by monitoring an operation of the first processor or a peripheral device associated with the first processor based on the defect list.

According to the above-described embodiments, in the autonomous driving control system including a plurality of processors having a dual structure, the processor (eg, the first processor) having the main control right recognizes the surrounding environment and autonomous driving based thereon. While executing control, another processor (eg, a second processor) may only exercise awareness of the surrounding environment. In this configuration, when a defect occurs in the first processor having the main control right, since the second processor is in a state in which the recognition of the surrounding environment is executed, when the main control right is transferred from the first processor to the second processor, the second processor The processor may immediately execute autonomous driving control according to the main control right based on the result of recognizing the surrounding environment. Accordingly, while the main control right is transferred from the first processor to the second processor, a vacuum period of normal autonomous driving control may be minimized and system stability may be ensured. In addition, the second processor can minimize power consumption of the entire system by reducing standby power consumption while there is no main control right by executing only recognition of the surrounding environment while the main control right is not held.

2 is a block diagram showing the configuration of an autonomous driving control system according to an embodiment of the present disclosure.

As shown, the autonomous driving control system 200. It may include a sensor unit 210, a control instruction unit 220, an error detection unit 230, an emergency response unit 240, and a weighting unit 250. The control instruction unit 220, the error detection unit 230, the emergency response unit 240, and the weighting unit 250 may correspond to the autonomous driving module 120 shown in FIG. 1, for example.

In one embodiment, the sensor unit 210 may include a plurality of sensors, that is, a camera 130, a lidar 140, and a radar 150, but is not limited thereto. The sensor unit 210 may be connected to the BUS 260 to transmit sensing data to the control directing unit 220 . The BUS 260 may be connected to the sensor bus interfaces 222A and 222B of the control instructing unit 220 to transmit sensing data. The control instructing unit 220 may generate an autonomous driving control signal using the sensing data received from the sensor unit 210 .

In one embodiment, the control directing unit 220 may include a first processor 221A and a second processor 221B. Here, the first processor 221A may correspond to the main block, and the second processor 221B may correspond to the shadow block. The first processor 221A may include a sensor bus interface 222A and a main calculation unit 223A, and the main calculation unit 223A may include a driving control unit 224A and an ambient sensing unit 225A. The second processor 221B may include a sensor bus interface 222B and a sub operation unit 223A, and the sub operation unit 223A may include a driving control unit 224A and an ambient sensing unit 225B.

In one embodiment, the error detecting unit 230 may include a memory 232 and an error pattern detecting unit 234 . The error detecting unit 230 may detect an operating error of each processor by monitoring the operating state of the processors 221A and 221B. In detecting an error in the error detecting unit 230, the error may be detected by comparing the current operating state of the processors 221A and 221B with an error pattern. The error pattern detecting unit 234 may compare error patterns included in the defect list stored in the memory 232 with current operating states of the processors 221A and 221B.

In one embodiment, the emergency response unit 240 may include an alarm unit 242 and an emergency route generator 244. When the error detection unit 230 detects an error, the emergency response unit 240 may execute an emergency response procedure as a response thereto. When the error detection unit 230 detects an error, the alarm unit 242 may generate and transmit a warning message. After sending the warning message, the autonomous driving control system 200 may perform any one of semi-autonomous driving, manual driving, and emergency driving.

In one embodiment, in the semi-autonomous driving mode, the control instructing unit 220 may generate an autonomous driving control signal using all or part of the sensing data received from the sensor unit 210 . In the manual driving mode, the control instructing unit 220 may transfer all control rights of the vehicle to the driver or provide driving assistance services such as lane keeping assistance so that the driver may directly operate the vehicle. Meanwhile, in the emergency driving mode, the control instructing unit 220 may generate a control signal to move the vehicle to a safe place along the emergency path generated by the emergency path generating unit 244 .

In one embodiment, the weighting unit 250 may include a memory 252 and a sensor weight determining unit 254 . The sensor weight determination unit 254 may apply different weights for each sensor when the surrounding environment sensed by the surrounding sensing units 225A and 225B requires different levels of autonomous driving control. In addition, when the surrounding environment sensed by the surrounding sensors 225A and 225B requires different levels of autonomous driving control, the driving controllers 224A and 224B may apply object recognition models with different processing capacities.

3 is a block diagram showing the configuration of an error detection unit according to an embodiment of the present disclosure.

As shown, the error detecting unit 230 may include a memory 232 and an error pattern detecting unit 234 . A defect list 300 including defects or error patterns related to the processor or its peripheral device may be stored in the memory 232 of the detector 230 . Based on the error pattern of the defect list 300, the error pattern detecting unit 234 may detect an error of the processors 221A and 221B. The error pattern items of the defect list 300 include, for example, an Electro-Magnetic Interference (EMI) operation error pattern 310, an Electro-Magnetic Compatibility (EMC) operation error pattern 320, a temperature error pattern 330, A processor error pattern 340, a power error pattern 350, a memory Cyclic Redundancy Check (CRC) error pattern 360, and the like may be included, but are not limited thereto.

Among the error pattern items of the defect list 300, EMI (Electro-Magnetic Interference) may mean electromagnetic interference, and electromagnetic interference refers to electromagnetic waves radiated or conducted from various electronic parts installed in an autonomous vehicle that function as other devices. can mean hindering In addition, EMC (Electro-Magnetic Compatibility) may mean electromagnetic compatibility or compatibility, and may mean the ability of a device to secure performance by applying to both the electromagnetic wave giving side and the receiving side. The temperature error pattern 330 may be a temperature error of a part of a system circuit, and may mean a level of temperature that affects the circuit. The processor error pattern 340 may mean an error pattern that can be checked by BIST (built-in self-test) or the like. The power error pattern 350 may mean supplying power in excess of or less than the range in which the system can normally operate. Memory CRC error patterns (360) can be divided into hardware problems and software problems, and can be caused by direct damage to data due to storage methods or work methods, storage errors, viruses, etc. It can be caused by crash damage.

4 is a block diagram illustrating configurations of a first processor and a second processor according to an embodiment of the present disclosure.

FIG. 4 shows the configuration of the first processor 221A and the second processor 221B in the control instructing unit 220 in detail. The first processor 221A may include a main arithmetic unit 223A and a memory 440, and the main arithmetic unit 223A may include a driving control unit 224A and a peripheral monitoring unit 225A. The second processor 221B may include a sub arithmetic unit 223B and a memory 470, and the sub arithmetic unit 223B may include a driving control unit 224B and a surrounding monitoring unit 225B. In FIG. 4 , the memories 440 and 470 are shown as being configured outside the main operation unit 223A and the sub operation unit 223B, but may be configured inside the main operation unit 223A and the sub operation unit 223B.

In one embodiment, the driving control unit 224A of the main operation unit 223A may be configured with the sensor set determining unit 410, and the surrounding monitoring unit 225A may be configured with the object recognition model application unit 430. . The driving control unit 224B of the sub operation unit 223B may be configured with the sensor set determining unit 450, and the surrounding monitoring unit 225B may be configured with the object recognition model applying unit 460.

In one embodiment, the driving control unit 224A of the main operation unit 223A, when a different level of autonomous driving control is required according to the surrounding situation detected by the surrounding sensing unit 225A, through the sensor set determination unit 410 Determine the different sensor sets. The surrounding detection unit 225A of the driving control unit 224A detects the surrounding situation, and when a different level of autonomous driving control is required according to the surrounding situation, the object recognition model applying unit 430 applies a different object recognition model. . Information about different sensor sets and different object recognition models may be stored in the memory 440 .

In one embodiment, the driving control unit 224B of the sub-computing unit 223B may set a sensor set when a different level of autonomous driving control is requested from the first processor 221A according to the surrounding situation detected by the surrounding sensing unit 225B. The decision unit 450 determines different sensor sets. The surrounding detection unit 225B of the driving control unit 224B detects the surrounding situation, and when a different level of autonomous driving control is requested from the first processor 221A according to the surrounding situation, the object recognition model application unit 460 Apply different object recognition models. Information about different sensor sets and different object recognition models may be stored in the memory 470 .

In one embodiment, the driving control unit 224B of the sub operation unit 223B independently processes signals received from some of the plurality of sensors while the main operation unit 223A generates the first control signal set, A second control signal set having a smaller range than the first control signal set generated by the calculation unit 223A may be generated. The sub operation unit 223B may not hold the main control right of the autonomous vehicle 110 until the error detection unit 230 detects an error in the first processor 221A. The second control signal set generated by the sub-computing unit 223B may be an autonomous driving control signal for responding to an error of the first processor 221A.

5 is a flowchart illustrating an operating method of an autonomous driving system based on a redundant structure according to an embodiment of the present disclosure.

The operation method 500 of the autonomous driving system shown in FIG. 5 may start with a step 510 of receiving sensor data. In one embodiment, the sensing data received in step 510 may be sensing data received from the camera 130, lidar 140, and radar 150, but is not limited thereto.

An operation 520 of sensing surrounding environment information may be executed. In an embodiment, the surrounding environment information may be information sensed by the surrounding sensing units 225A and 225B of the main operation unit 223A and the sub operation unit 223B using a plurality of sensing data.

Step 530 of generating a first set of control signals in the first processor may be executed. In one embodiment, the first control signal set may be generated by applying object recognition models of different processing capacities and data of different sensor sets when different levels of autonomous driving control are required according to surrounding environments.

Operation 540 of recognizing ambient environment information by processing signals received from some of the sensors by the second processor may be executed. In an embodiment, the surrounding environment information may be information sensed by the surrounding sensing unit 225B of the sub operation unit 223B using a plurality of sensing data.

Step 550 of determining whether the first processor is operating abnormally may be executed. In one embodiment, the determination of whether the first processor operates abnormally may be performed by the error detecting unit 230 and may be based on the defect list 300 stored in the memory 232 .

In step 550, in response to determining that the first processor is operating abnormally, the main control right may be transferred to the second processor. In one embodiment, the second processor 221B may receive the main control right from the processor 221A and generate an autonomous driving control signal by applying data of different sensor sets and/or object recognition models of different processing capacities. there is.

The method 500 of operating an autonomous driving system may further include generating a first set of control signals in a second processor (570). In one embodiment, the first control signal set may be a control signal set having a greater range than the second control signal set generated by the second processor 221B before the first processor 221A detects an error.

6 is a flowchart illustrating an operating method of an autonomous driving system based on a redundant structure according to another embodiment of the present disclosure.

As shown, the method 600 of operating an autonomous driving system may begin with receiving sensor data (610). In one embodiment, the sensing data received in step 610 may be the camera 130, lidar 140, or radar 150, but is not limited thereto.

An operation 620 of sensing surrounding environment information may be executed. In an embodiment, the surrounding environment information may be information sensed by the surrounding sensing units 225A and 225B of the main operation unit 223A and the sub operation unit 223B using a plurality of sensing data.

Also, step 630 of generating a first set of control signals in the first processor may be executed. In one embodiment, the first set of control signals may be generated by applying data of different sensor sets and/or object recognition models of different processing capacities when different levels of autonomous driving control are required according to the surrounding environment. .

Operation 640 of recognizing ambient environment information by processing signals received from some of the sensors by the second processor may be executed. In an embodiment, the surrounding environment information may be information sensed by the surrounding sensing unit 225B of the sub operation unit 223B using a plurality of sensing data.

Step 650 of determining whether the first processor is operating abnormally may be executed. In one embodiment, the determination of the abnormal operation of the first processor may be performed by the error detecting unit 230 and may be based on the defect list 300 stored in the memory 232 .

In response to determining that the first processor is operating abnormally in step 650, step 660 of transferring the main control right to the second processor may be executed. In one embodiment, the second processor 221B may receive the main control right and generate a driving control signal by applying data of different sensor sets and/or object recognition models of different processing capacities.

Step 670 of generating a first set of control signals in the second processor may be executed. In one embodiment, the first control signal set may be a control signal set having a larger range than the second control signal set generated by the second processor 221B before the first processor 221A detects an error.

In response to determining that the first processor 221A is normally operating in step 650, step 652 of requesting a different level of autonomous driving may be executed.

In response to determining that different levels of autonomous driving are required in step 652, step 654 of applying different weights for each sensor to signals received from a plurality of sensors may be executed. In one embodiment, a high weight may be applied to all sensors in a situation in which a highway enters a city or in a situation in which there are many vehicles 160 around the self-driving vehicle 110 . For example, the shadow block 124 applies a high weight to the camera 130 for low-level autonomous driving control when the surrounding environment is relatively simple and the risk of an accident is low, while the other sensors 140 and 150 ), a low weight can be applied. In another example, the shadow block 124 may apply a high weight to all sensors 130, 140, and 150 for a high level of autonomous driving control when the surrounding environment is relatively complex and the risk of an accident is high.

Step 656 of applying, by the second processor, object recognition models of different processing capacities may be executed. Step 658 may also be executed in which the second processor generates a second set of control signals. In one embodiment, the second processor 221B may generate a control signal set even in the absence of a control right. The second control signal set generated by the second processor 221B may have a smaller range than the first control signal set generated by the first processor 221A.

According to the above-described embodiments, in the autonomous driving control system including a plurality of processors having a dual structure, the processor (eg, the first processor) having the main control right recognizes the surrounding environment and autonomous driving based thereon. While executing control, another processor (eg, a second processor) may only exercise awareness of the surrounding environment. In this configuration, when a defect occurs in the first processor having the main control right, since the second processor is in a state in which the recognition of the surrounding environment is executed, when the main control right is transferred from the first processor to the second processor, the second processor The processor may directly execute autonomous driving control according to the main control right based on the result of recognizing the surrounding environment. Accordingly, while the main control right is transferred from the first processor to the second processor, a vacuum period of normal autonomous driving control may be minimized and system stability may be ensured. In addition, the second processor can minimize power consumption of the entire system by reducing standby power consumption while there is no main control right by executing only recognition of the surrounding environment while the main control right is not held.

The above method may be provided as a computer program stored in a computer readable recording medium to be executed on a computer. The medium may continuously store programs executable by a computer or temporarily store them for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or combined hardware, but is not limited to a medium directly connected to a certain computer system, and may be distributed on a network. Examples of the medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROM and DVD, magneto-optical media such as floptical disks, and ROM, RAM, flash memory, etc. configured to store program instructions. In addition, examples of other media include recording media or storage media managed by an app store that distributes applications, a site that supplies or distributes various other software, and a server.

The methods, acts or techniques of this disclosure may be implemented by various means. For example, these techniques may be implemented in hardware, firmware, software, or combinations thereof. Those skilled in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchange of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design requirements imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementations should not be interpreted as causing a departure from the scope of the present disclosure.

In a hardware implementation, the processing units used to perform the techniques may include one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs) ), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, and other electronic units designed to perform the functions described in this disclosure. , a computer, or a combination thereof.

Accordingly, the various illustrative logical blocks, modules, and circuits described in connection with this disclosure may be incorporated into a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or may be implemented or performed in any combination of those designed to perform the functions described in A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other configuration.

In firmware and/or software implementation, the techniques include random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), PROM ( on a computer readable medium, such as programmable read-only memory (EPROM), erasable programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, compact disc (CD), magnetic or optical data storage device, or the like. It can also be implemented as stored instructions. Instructions may be executable by one or more processors and may cause the processor(s) to perform certain aspects of the functionality described in this disclosure.

Although the embodiments described above have been described as utilizing aspects of the presently-disclosed subject matter in one or more stand-alone computer systems, the disclosure is not limited thereto and may be implemented in conjunction with any computing environment, such as a network or distributed computing environment. . Further, aspects of the subject matter in this disclosure may be implemented in a plurality of processing chips or devices, and storage may be similarly affected across multiple devices. These devices may include PCs, network servers, and portable devices.

Although the present disclosure has been described in relation to some embodiments in this specification, it should be noted that various modifications and changes can be made without departing from the scope of the present disclosure that can be understood by those skilled in the art. something to do. Moreover, such modifications and variations are intended to fall within the scope of the claims appended hereto.

110: autonomous vehicle 120: autonomous driving module
122: Main Block 124: Shadow Block
130: Camera 140: LIDAR
150: Radar 160: Vehicle
200: autonomous driving control system 210: sensor unit
220: control instruction unit 221A: first processor
222A: sensor bus interface 223A: main operation unit
224A: driving control unit 225A: surrounding sensing unit
221B: second processor 222B: sensor bus interface
223B: sub calculation unit 224B: driving control unit
225B: peripheral detection unit 230: error detection unit
232: memory 234: error pattern detector
240: emergency response unit 242: alarm unit
244: emergency route generation unit 250: weighting unit
252: memory 254: sensor weight determination unit
300: Fault List (300) 410: Sensor set determining unit
430: object recognition model application unit 440: memory
450: sensor set determination unit 460: object recognition model application unit
470: memory

Claims (10)

In an autonomous driving control system based on a redundant structure,
A plurality of sensors configured to sense information about the surrounding environment of the self-driving vehicle;
a first processor configured to hold a main control right of the autonomous vehicle and to process signals received from the plurality of sensors to generate a first set of control signals used to control the autonomous vehicle; and
And a second processor configured to sense the surrounding environment of the vehicle by processing signals received from at least some of the plurality of sensors,
When an operation error by the first processor is detected, the first processor transfers the main control right to the second processor so that the second processor is reconfigured to generate the first set of control signals. control system.
According to claim 1,
Further comprising a memory for storing a plurality of pattern information related to an operation error on the autonomous driving control system,
When an operation pattern of the first processor or a peripheral device associated with the first processor is the same as or similar to at least one of a plurality of pattern information stored in the memory, it is determined that an operation error of the first processor has occurred. system.
According to claim 2,
The plurality of pattern information includes at least one of an EMI or EMC operation error pattern, a temperature error pattern, a processor error pattern, a power error pattern, a memory CRC error pattern, and a memory bit error pattern.
According to claim 1,
The second processor to which the main control right has been transferred,
The autonomous driving control system is reconfigured to generate at least a part of the first set of control signals according to the sensed surrounding environment.
According to claim 1,
The second processor to which the main control right has been transferred,
Wherein the autonomous driving control system is reconfigured to apply different sensor-specific weights to signals received from the plurality of sensors when the sensed surrounding environment requires a different level of autonomous driving control.
According to claim 1,
The second processor to which the main control right has been transferred,
The autonomous driving control system, which is reconfigured to apply object recognition models of different processing capacities to signals received from the plurality of sensors when the sensed surrounding environment requires a different level of autonomous driving control.
According to claim 1,
While the first processor processes signals received from at least some of the plurality of sensors to generate the first set of control signals, the second processor independently processes signals received from at least some of the plurality of sensors. to generate a second control signal set having a smaller range than the control signal set.
According to claim 1,
The plurality of sensors include at least one of a LiDAR sensor, a laser sensor, an infrared sensor, and a camera.
In the autonomous driving control method based on a redundant structure, executed by at least one processor,
Sensing information about the surrounding environment of the self-driving vehicle by a plurality of sensors;
generating a first set of control signals used to control the autonomous vehicle by processing signals received from the plurality of sensors, by a first processor having a main control right of the autonomous vehicle;
sensing, by a second processor, a surrounding environment of the vehicle by processing signals received from at least some of the plurality of sensors; and
When an operation error by the first processor is detected, transferring, by the first processor, the main control right to the second processor, and reconfiguring the second processor to generate the first control signal set. Including, autonomous driving control method.
A computer program stored in a computer readable recording medium to execute the method according to claim 9 on a computer.

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