Auxiliary driving method and device, controller and vehicle

Abstract

The embodiment of the invention provides an auxiliary driving method and device, a controller and a vehicle. The method comprises the steps that a controller can obtain sensor data collected and uploaded by a plurality of sensors; the controller may generate first obstacle information based on the sensor data. The controller can analyze the first obstacle information to generate initial decision information. The controller can further optimize the initial decision information according to the first obstacle information and the data of all the sensors, and final decision information of auxiliary driving of the vehicle is generated. The controller can further optimize the initial decision information according to the first obstacle information and the data of all the sensors, and final decision information of auxiliary driving of the vehicle is generated. The method is used for achieving the effect of improving the safety of the vehicle.

Description

Technical Field

[0001] The present application relates to the field of assisted driving, and specifically to an assisted driving method, device, controller and vehicle. Background Art

[0002] As the use of cars increases, the frequency of traffic accidents is also increasing. In order to reduce the risk of collision, vehicles can be equipped with autonomous emergency braking systems (AEB) and autonomous emergency steering (AES). However, the current joint use of AEB and AES in vehicles needs to be further improved to improve the safety of the vehicle. Summary of the invention

[0003] The embodiments of the present application provide a driving assistance method, device, controller and vehicle to achieve the effect of improving the safety of the vehicle.

[0004] In a first aspect, an embodiment of the present application provides an assisted driving method, which is applied to a vehicle, wherein a controller of the vehicle includes a system chip of a safety level B and a microcontroller of a safety level D, including:

[0005] According to the sensor data collected by each of the multiple sensors in the vehicle, first obstacle information and initial decision information are generated in the system chip; wherein the initial decision information represents the initial decision of the assisted driving of the vehicle, and the first obstacle information is obstacle identification information of safety level B;

[0006] Based on the initial decision information, the first obstacle information and each of the sensor data, the microcontroller generates and executes final decision information for assisted driving of the vehicle with a safety level D.

[0007] In a second aspect, an embodiment of the present application provides an auxiliary driving device, which is applied to a vehicle, wherein a controller of the vehicle includes a system chip of a safety level B and a microcontroller of a safety level D, including:

[0008] a first processing module, configured to generate first obstacle information and initial decision information in the system chip according to sensor data collected by each of the plurality of sensors in the vehicle; wherein the initial decision information represents an initial decision of the assisted driving of the vehicle, and the first obstacle information is obstacle identification information of safety level B;

[0009] The second processing module is used to generate and execute final decision information of the assisted driving of the vehicle with a safety level D in the microcontroller based on the initial decision information, the first obstacle information and each of the sensor data.

[0010] In a third aspect, an embodiment of the present application provides a controller, including: a system chip and a microprocessor;

[0011] The system chip and the microprocessor respectively include a storage unit and a processing unit;

[0012] The storage unit stores computer-executable instructions;

[0013] The processing unit executes the computer-executable instructions stored in the storage unit, so that the processing unit executes the above first aspect and / or various possible implementations of the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a vehicle, comprising a plurality of sensors and the first aspect and / or various possible controllers of the first aspect.

[0015] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processing unit, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0016] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processing unit, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0017] The assisted driving method, device, controller, and vehicle provided in the embodiments of the present application generate first obstacle information of safety level B by using a system chip of safety level B, analyze the first obstacle information, and generate initial decision information of safety level B; generate second obstacle information of safety level D by using a microcontroller of safety level D, and optimize the initial decision information based on the first obstacle information and the second obstacle information to obtain final decision information of safety level D; and implement the means of executing the final decision information, so as to achieve the effect of improving the safety of the vehicle to safety level D on the basis of using a system chip of safety level B and a microcontroller of safety level D. In addition, the use of the system chip of safety level B and the microcontroller of safety level D avoids the need to increase hardware costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 A schematic diagram of a functional architecture provided for this application;

[0020] Figure 2 A schematic diagram of a driving assistance method provided in this application Figure 1 ;

[0021] Figure 3 A schematic diagram of a system architecture provided for this application Figure 1 ;

[0022] Figure 4 A schematic diagram of a system architecture provided for this application Figure 2 ;

[0023] Figure 5 A schematic diagram of a driving assistance method provided in this application Figure 2 ;

[0024] Figure 6 A schematic diagram of a driving assistance method provided in this application Figure 3 ;

[0025] Figure 7 A schematic diagram of the structure of a driving assistance device provided in this application;

[0026] Figure 8 A schematic diagram of the structure of a controller provided in this application. DETAILED DESCRIPTION

[0027] The following will describe the implementation methods of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, not for limiting the scope of protection of the present application.

[0028] As the number of cars in my country continues to increase, various types of traffic accidents and the resulting casualties and property losses are also on the rise. In order to reduce the risk of forward collisions, the Autonomous Emergency Braking (AEB) system has been gradually commercialized and applied to vehicles. However, when AEB faces sudden scenarios such as pedestrians crossing the road in front, emergency braking of the vehicle in front, or vehicles driving out of the intersection in the blind spot, it is still possible for a collision to occur in the event of emergency braking because the vehicle cannot detect the danger in advance. In order to further improve vehicle safety, the Autonomous Emergency steering (AES) function has also been applied to vehicles. The AES can work in conjunction with AEB to better solve the problem of forward collisions.

[0029] A commonly used functional architecture for the joint action of AES and AEB can be as follows: Figure 1 As shown, the hardware in the controller may include a system on chip (SOC) with a safety level of B and a microcontroller unit (MCU) with a safety level of D. Optionally, the above safety level is the Automotive Safety Integrity Level (ASIL). The ASIL is a standard defined by the ISO 26262 standard for evaluating the safety of electronic and electrical systems. Figure 1 As shown, the SOC is directly connected to the front camera module and the surrounding module, and can calculate the forward and lateral obstacle information through visual processing. At the same time, the SOC can also fuse the obstacle information obtained by visual processing with the information input by the external radar module to obtain obstacle information with a safety level of B, and then generate decision information based on the obstacle information. The decision information can be output to the decision planning module of the MCU. The decision planning module of the MCU can complete the corresponding vehicle assisted driving control based on the decision information. Since the safety level of the SOC is B, the safety level of the decision information generated by the SOC is also B. That is, the safety level of the decision executed by the MCU at this time is B. The decision information can be used to instruct the vehicle to perform emergency braking or emergency steering.

[0030] In order to further improve the safety of the vehicle and make the vehicle safety level D, the assisted driving method provided in this application can be based on the following Figure 1The SOC with a safety level of B and the MUC with a safety level of D shown in the figure improve the safety level of the final generated decision information by adding a safety mechanism in the MCU, so that the safety level of the decision information can meet the requirements of D. The implementation of this application fully exploits the computing power, interface and replaceable system functions of each vehicle-mounted ECU, and realizes a low-cost security strategy without adding new ECUs.

[0031] In order to achieve the above requirements, this application analyzes the relevant failure scenarios that need to meet functional safety ASIL D, and finds that the main optimized scenario of ASIL D is the scenario of unexpected triggering of AES during the normal operation of the vehicle. Unexpected triggering of AES usually occurs when the steering angle is large and the steering rate is fast, and due to the unexpected nature of the triggering, the driver is usually unable to take over the vehicle in time. From the analysis of unexpected triggering of AES, it can be seen that the implementation of AES requires accurate identification of lateral dangerous targets to ensure that the AES function is triggered when there are no dangerous targets on the side. At the same time, in order to ensure that the implementation of the AES function can meet the safety requirements of ASIL D, adding a safety mechanism in the MCU can further optimize the identification of lateral dangerous targets, improve the recognition accuracy, and the accuracy of AES triggering judgment.

[0032] This application adds a safety mechanism to the MCU to achieve a solution that implements the safety requirements of ASIL D when using an ASIL B chip system and an ASIL D microcontroller, thereby improving the safety of the vehicle, solving the problem of insufficient computing power of the microcontroller unit, and realizing a low-cost safety strategy without adding new ECUs.

[0033] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0034] Figure 2 Schematic diagram of the process of the assisted driving method provided in this application Figure 1 ,like Figure 2 As shown, with the controller in the vehicle as the execution subject, the method includes:

[0035] S101. Generate first obstacle information and initial decision information in a system chip according to sensor data collected by each of a plurality of sensors in a vehicle, wherein the initial decision information represents an initial decision of the assisted driving of the vehicle, and the first obstacle information is obstacle identification information of safety level B.

[0036] In this embodiment, the system chip in the controller can obtain sensor data collected and uploaded by multiple sensors. Optionally, the sensor can be set on the vehicle. The sensor set on the vehicle can upload the sensor data to the system chip in the controller in real time. Optionally, the sensor can also be set on the roadside. The system chip in the controller can obtain the sensor data uploaded by the sensor set on the roadside when the distance to the roadside sensor is less than or equal to the sensor threshold.

[0037] The system chip in the controller can generate first obstacle information based on the sensor data. The first obstacle information is used to indicate obstacles around the vehicle. Specifically, the first obstacle information can be used to describe in detail key features such as the position, speed and type of obstacles around the vehicle. Since the safety level of the system chip is B, the first obstacle information is obstacle identification information with a safety level of B. Optionally, the first obstacle information may include information about all obstacles around the vehicle. Optionally, the system chip in the controller may identify the sensor data through a preset recognition algorithm. Optionally, the recognition algorithm may be a machine learning algorithm. For example, the machine learning algorithm may be a region-based convolutional neural network (R-CNN), a single shot multi-box detector obstacle recognition (SSD), YOLO, etc. Optionally, the system chip in the controller may pre-process the sensor data and input the sensor data into the recognition algorithm to obtain the first obstacle information on the road. Optionally, the system chip in the controller may also input each sensor data into a recognition algorithm corresponding to the sensor to obtain the obstacle corresponding to the sensor. The system chip in the controller may intersect the obstacles corresponding to each sensor to obtain the final first obstacle information.

[0038] The system chip in the controller can analyze the first obstacle information and generate initial decision information. The initial decision information preliminarily plans the vehicle's assisted driving action path and strategy.

[0039] Optionally, this step may be performed on a system chip.

[0040] In one example, a specific process in which a system chip in a controller generates first obstacle information and initial decision information according to sensor data may include:

[0041] Step 1: Identify each sensor data to obtain the third obstacle information corresponding to each sensor data.

[0042] In this step, the system chip in the controller may be preset with a recognition model corresponding to each sensor. The system chip in the controller may use the recognition model corresponding to the sensor to recognize the sensor data uploaded by the sensor, and obtain the third obstacle information corresponding to the sensor data. The third obstacle information is the information of obstacles around the vehicle obtained after recognizing the sensor data. For example, when a visual sensor and a radar sensor are included, the third obstacle information recognized by the visual sensor and the third obstacle information recognized by the radar sensor may be included. The third obstacle information recognized by the visual sensor and the third obstacle information recognized by the radar sensor may contain different obstacles, or there may be different recognition results of position, speed and type for one obstacle.

[0043] Step 2: Match the third obstacle information corresponding to each sensor data to obtain the first obstacle information.

[0044] In this step, the system chip in the controller can integrate and refine the third obstacle information corresponding to each sensor data by matching, so as to obtain more accurate and comprehensive first obstacle information. Optionally, the matching requirement of the obstacle can be determined according to the safety requirement of ASIL B. Optionally, the way to integrate and refine the third obstacle information corresponding to each sensor data can be to calculate the intersection or union of the third obstacle information corresponding to each sensor data to obtain the final first obstacle information. Optionally, in one implementation, when the fourth obstacle information corresponding to the visual sensor data does not contain obstacle A, and the fourth obstacle information corresponding to the radar sensor data contains obstacle A, the system chip in the controller may not record the obstacle A in the first obstacle information. In another implementation, when the fourth obstacle information corresponding to the visual sensor data does not contain obstacle A, and the fourth obstacle information corresponding to the radar sensor data contains obstacle A, the system chip in the controller may record the obstacle A in the first obstacle information.

[0045] Step 3: Generate initial decision information based on the first obstacle information.

[0046] In this step, a decision algorithm may be provided in the system chip in the controller. The system chip in the controller may input the first obstacle information into the decision algorithm, and the decision may obtain the initial decision information. Optionally, the requirements of the decision algorithm may be determined according to the safety requirements of ASIL B. Optionally, the initial decision information may be used to indicate whether there is an obstacle in the front of the vehicle, and whether the vehicle needs to avoid collision with the obstacle by emergency braking. If emergency braking is required, the system chip in the controller may also calculate the deceleration of the vehicle. And, the decision information may also be used to indicate whether there is an obstacle on the side of the vehicle. If there is no obstacle on the side of the vehicle, the system chip in the controller may also plan the angle of emergency steering of the vehicle, so that the vehicle may avoid collision with the obstacle in the front of the vehicle by emergency steering. Optionally, the judgment of the emergency steering may be performed when it is impossible to avoid collision with the obstacle in the front by deceleration.

[0047] S102, based on the initial decision information, the first obstacle information and the data from each sensor, the microcontroller generates and executes the final decision information for the assisted driving of the vehicle with a safety level D.

[0048] In this embodiment, the microcontroller in the controller further optimizes the initial decision information according to the first obstacle information and each sensor data to generate the final decision information of the assisted driving of the vehicle. Optionally, the first obstacle information can be optimized according to the sensor information according to a more sophisticated obstacle recognition rule, so as to use the optimized first obstacle information to optimize the initial decision information and obtain the final decision information. The final decision information can be determined according to the safety requirements of ASIL D. Optionally, the execution of this step can be performed on the microcontroller in the controller. The microcontroller in the controller can be preset with an identification algorithm determined according to the safety requirements of ASIL D. The microcontroller in the controller can optimize and identify the first obstacle information through the identification algorithm to obtain more accurate obstacle information. The microcontroller in the controller can detect and optimize the initial decision information according to the more accurate obstacle information to obtain the final decision information.

[0049] In one example, the process of the microcontroller in the controller obtaining the final decision information may include:

[0050] Step 1: Generate second obstacle information based on the data from each sensor. The second obstacle information is obstacle identification information of safety level D.

[0051] In this step, the microcontroller in the controller can generate second obstacle information that is more accurate than the first obstacle information based on the data collected in real time by each sensor. The second obstacle information is generated in a different manner from the first obstacle information, and the second obstacle information has a higher safety requirement. The safety level of the second obstacle information can be D.

[0052] Step 2: Optimize the initial decision information based on the first obstacle information and the second obstacle information to obtain the final decision information.

[0053] In this step, the microcontroller in the controller can comprehensively consider the advantages and complementarity of the first obstacle information and the second obstacle information, and optimize and adjust the initial decision information through intelligent algorithms, in order to obtain more accurate and reliable final decision information. The microcontroller in the controller can convert the final decision information into a series of precise control instructions to guide the vehicle to perform corresponding actions such as emergency braking, emergency steering or warning.

[0054] In the assisted driving method provided in the embodiment of the present application, the controller can obtain sensor data collected and uploaded by multiple sensors. The controller can generate first obstacle information based on the sensor data. The controller can analyze the first obstacle information to generate initial decision information. The controller can further optimize the initial decision information based on the first obstacle information and each sensor data to generate final decision information for assisted driving of the vehicle. The controller can further optimize the initial decision information based on the first obstacle information and each sensor data to generate final decision information for assisted driving of the vehicle. By optimizing the initial decision information according to the sensor information and the first obstacle information after acquiring the first obstacle information and the initial decision information, the effect of improving vehicle safety is achieved.

[0055] Based on the above embodiments, Figure 3 and Figure 4 The following are structural diagrams of two system architectures. Figure 3 An external system-level architecture designed for a safety architecture that meets ASIL D level, such as Figure 4 Internal hardware and software architecture levels designed for an ASIL D safety architecture.

[0056] like Figure 3As shown, the safety architecture may include a first group of sensors and a second group of sensors. Among them, the first group of sensors may include a front-view camera module, a surrounding camera module, a high-precision map, and a laser radar, and the second group of sensors may include a front-view radar and a corner radar. Among them, the number of laser radars and corner radars may be 4. The safety architecture may also include an automatic driving control unit, a gateway, an emergency braking control module, an emergency steering control module, and a human-computer interaction control module. Among them, the first group of sensors and the second group of sensors constitute the perception system of the vehicle. The two groups of sensors are set based on the principle of minimizing risks, and the two groups of sensors are independent. Among them, the first group of sensors is connected to the automatic driving control module 7 through a surrounding deserializer, a front-view deserializer, and Ethernet. The second group of sensors is connected to the automatic driving control module through two CAN buses, and is directly connected to the gateway through Ethernet. The automatic driving control module 7 is connected to the gateway through two CAN buses. The gateway 8 is connected to the emergency braking control module, the emergency steering control module, and the human-computer interaction control module through three CAN buses.

[0057] like Figure 4 As shown, the safety architecture may include an automatic driving control module. The automatic driving control module may include a system chip and a microcontroller. Among them, the system chip deploys three modules: visual processing, perception fusion, and decision planning. The microcontroller includes four software modules: lateral dangerous target determination, AEB / AES arbitration, AEB control, and AES control. Among them, the visual processing module inside the system chip can be connected to the perception fusion module through internal chip communication, and the perception fusion module is connected to the decision planning module through internal chip communication. The visual processing and decision planning modules can also be connected to the lateral dangerous target determination module and the AEB / AES arbitration module inside the microcontroller through inter-chip communication. The AEB control and AES control modules can be connected to the gateway through the CAN bus. The AEB / AES arbitration module inside the microcontroller is connected to the AEB control and AES control.

[0058] Among them, the front camera module, front radar, corner radar, surround camera module, and lidar all meet the safety requirements of ASIL B. The gateway, emergency brake control module, and emergency steering control module meet the safety requirements of ASIL D. The three modules of visual processing, perception fusion, and decision planning in the system chip meet the safety requirements of ASIL B. The four modules of lateral dangerous target determination, AEB / AES arbitration, AEB control, and AES control in the microcontroller meet the safety requirements of ASIL D.

[0059] Among them, under the safety requirements of ASIL B, the decision-making planning in the system chip can plan the need for emergency steering, and the MCU can also arbitrate with AEB. If the emergency braking trigger can avoid the collision at this time, the MCU can directly output the braking request instruction for emergency braking. If the arbitration shows that the emergency braking trigger cannot avoid the collision, it is necessary to output the emergency steering control instruction for collision avoidance. However, in order to meet the safety requirements of ASIL D and avoid unexpected steering, the MCU can also perform safety analysis through the lateral dangerous target judgment module to avoid unexpected steering, oversteering, understeering and other problems.

[0060] Figure 5 Schematic diagram of the process of the assisted driving method provided in this application Figure 2 ,like Figure 5 As shown, in this embodiment Figures 1 to 4 Based on the illustrated embodiment, the process of generating the final decision information is described in detail. The specific process of the method includes:

[0061] S201: Identify each sensor data to obtain third obstacle information corresponding to each sensor data.

[0062] In this embodiment, the microcontroller in the controller may store a recognition model corresponding to each sensor. The microcontroller in the controller may use the recognition model to recognize the sensor data of each sensor to obtain the third obstacle information corresponding to each sensor data.

[0063] S202: Fusing and screening the third obstacle information to obtain second obstacle information.

[0064] In this embodiment, the microcontroller in the controller fuses and filters the third obstacle information corresponding to each sensor data, removes redundant or erroneous obstacle information, and obtains more accurate second obstacle information. Optionally, the microcontroller in the controller can obtain the second obstacle information by first filtering, then fusing, and then filtering. Optionally, the microcontroller in the controller can also obtain the second obstacle information by first fusing and then filtering.

[0065] In one example, the specific process of the microcontroller in the controller obtaining the second obstacle information by first screening, then fusing, and then screening may include:

[0066] Step 1: Filter the third obstacle information according to the probability threshold corresponding to each sensor data to obtain the fourth obstacle information.

[0067] In this step, the microcontroller in the controller may be provided with a probability threshold corresponding to each sensor data. The microcontroller in the controller may first filter the third obstacle information corresponding to each sensor data according to the probability threshold corresponding to each sensor, thereby obtaining the fourth obstacle information. Optionally, the probability thresholds corresponding to different sensors may be the same. For example, the probability thresholds of the visual sensor and the radar sensor may both be 80%. Optionally, different sensors may correspond to different probability thresholds. For example, the probability threshold corresponding to the visual sensor may be 75%, and the probability threshold corresponding to the radar sensor may both be 85%. The microcontroller in the controller may filter the third obstacle information corresponding to each sensor data according to the probability value of each obstacle and the probability threshold corresponding to the sensor. If the probability value of the obstacle in the third obstacle information is less than the probability threshold, the microcontroller in the controller may delete the obstacle whose probability value is less than the probability threshold, and retain the obstacle whose probability value is greater than or equal to the probability value, thereby obtaining the fourth obstacle information corresponding to the sensor data.

[0068] Step 2: Fusing and matching the fourth obstacle information corresponding to each sensor data to obtain fifth obstacle information.

[0069] In this step, the microcontroller in the controller can fuse and match the fourth obstacle information corresponding to each sensor data. This process is intended to integrate the data of different sensors to improve the accuracy and reliability of obstacle detection, and then obtain the fifth obstacle information. Optionally, the microcontroller in the controller can determine the obstacles with the same position in the fourth obstacle information corresponding to each sensor information by matching, and retain the obstacles with the same position to obtain the fifth obstacle information. Optionally, the microcontroller in the controller can also obtain the obstacle information of each obstacle detected by each sensor data by fusion calculation, and then form the fifth obstacle information.

[0070] Among them, an implementation method of obtaining the fifth obstacle information by fusion matching may include the following steps:

[0071] Step 21: Match the fourth obstacle information corresponding to each sensor data to obtain the sixth obstacle information corresponding to each sensor data.

[0072] In this step, the microcontroller in the controller matches the fourth obstacle information corresponding to each sensor data to determine whether the obstacle in the fourth obstacle information corresponding to each sensor data is the same obstacle. If the obstacle in the fourth obstacle information corresponding to each sensor data is the same obstacle, the microcontroller in the controller completes the matching of the obstacle and stores the obstacle in the sixth obstacle information. Optionally, in one implementation, when the fourth obstacle information corresponding to the visual sensor data does not contain obstacle A, and the fourth obstacle information corresponding to the radar sensor data contains obstacle A, the microcontroller in the controller may not record the obstacle A in the sixth obstacle information. In another implementation, when the fourth obstacle information corresponding to the visual sensor data does not contain obstacle A, and the fourth obstacle information corresponding to the radar sensor data contains obstacle A, the microcontroller in the controller may record the obstacle A in the sixth obstacle information and use 0 to complete the information corresponding to the visual sensor data.

[0073] Step 22: weighted fusion is performed on the sixth obstacle information corresponding to each sensor data according to the probability weight corresponding to each sensor data to obtain the fifth obstacle information.

[0074] In this step, the microcontroller in the controller can obtain the probability weight corresponding to each sensor data. The microcontroller in the controller can perform weighted fusion on the probability value of each obstacle in the sixth obstacle information to obtain the final probability value of each obstacle. The microcontroller in the controller can compose the fifth obstacle information according to the final probability value of each obstacle. Optionally, in one implementation, the probability weight of the sensor data can be set according to an empirical value. In another implementation, the probability weight of the sensor data can be determined according to the detection accuracy of the sensor data.

[0075] Optionally, the microcontroller in the controller may also determine the probability weight corresponding to each sensor data according to the third obstacle information and the sixth obstacle information corresponding to each sensor data. Specifically, the microcontroller in the controller may determine the first number of obstacles that exist in both the third obstacle information and the sixth obstacle information corresponding to each sensor data. The microcontroller in the controller may determine the first parameter according to the ratio of the first number to the second number of obstacles in the third obstacle information corresponding to the sensor data. The microcontroller in the controller may process the first parameter corresponding to each sensor data to obtain the probability weight of each sensor data. Optionally, the sum of the probability weights corresponding to each sensor data may be 1.

[0076] Step 3: Filter the fifth obstacle information according to a preset fusion threshold to obtain the second obstacle information.

[0077] In this step, a preset fusion threshold may be stored in the microcontroller in the controller. The microcontroller in the controller may further screen the fifth obstacle information according to the preset fusion threshold. Specifically, the microcontroller in the controller may use the fusion threshold to compare the probability value of each obstacle in the fifth obstacle information. If the probability value of the obstacle in the fifth obstacle information is greater than or equal to the fusion threshold, the microcontroller in the controller may retain the obstacle in the second obstacle information. If the probability value of the obstacle in the fifth obstacle information is less than the fusion threshold, the microcontroller in the controller may delete the obstacle.

[0078] In another example, the specific process of the microcontroller in the controller obtaining the second obstacle information by first fusing and then screening may include:

[0079] Step 1: Match the third obstacle information with the probability threshold corresponding to each sensor data to obtain the seventh obstacle information corresponding to each sensor data.

[0080] In this step, the microcontroller in the controller matches the third obstacle information corresponding to each sensor data to determine whether the obstacle in the third obstacle information corresponding to each sensor data is the same obstacle. If the obstacle in the third obstacle information corresponding to each sensor data is the same obstacle, the microcontroller in the controller completes the matching of the obstacle and stores the obstacle in the seventh obstacle information. Optionally, in one implementation, when the third obstacle information corresponding to the visual sensor data does not contain obstacle A, and the third obstacle information corresponding to the radar sensor data contains obstacle A, the microcontroller in the controller may not record the obstacle A in the seventh obstacle information. In another implementation, when the third obstacle information corresponding to the visual sensor data does not contain obstacle A, and the third obstacle information corresponding to the radar sensor data contains obstacle A, the microcontroller in the controller may record the obstacle A in the seventh obstacle information and use 0 to complete the information corresponding to the visual sensor data.

[0081] Step 2: According to the probability weight corresponding to each sensor data, weighted fusion is performed on the seventh obstacle information corresponding to each sensor data to obtain the eighth obstacle information.

[0082] In this step, the microcontroller in the controller can obtain the probability weight corresponding to each sensor data. The microcontroller in the controller can perform weighted fusion on the probability value of each obstacle in the seventh obstacle information to obtain the final probability value of each obstacle. The microcontroller in the controller can compose the eighth obstacle information according to the final probability value of each obstacle. Optionally, in one implementation, the probability weight of the sensor data can be set according to an empirical value. In another implementation, the probability weight of the sensor data can be determined according to the detection accuracy of the sensor data.

[0083] Step 3: Filter the eighth obstacle information according to a preset fusion threshold to obtain second obstacle information.

[0084] In this step, a preset screening threshold may be stored in the microcontroller in the controller. The microcontroller in the controller may further screen the eighth obstacle information according to the preset screening threshold. Specifically, the microcontroller in the controller may use the screening threshold to compare the probability value of each obstacle in the eighth obstacle information. If the probability value of the obstacle in the eighth obstacle information is greater than or equal to the screening threshold, the microcontroller in the controller may retain the obstacle in the second obstacle information. If the probability value of the obstacle in the eighth obstacle information is less than the screening threshold, the microcontroller in the controller may delete the obstacle.

[0085] S203: Determine at least one initial driving area according to the initial decision information.

[0086] In this embodiment, the microcontroller in the controller can obtain the initial decision information that has been generated. The microcontroller in the controller can extract at least one initial driving area from the initial decision information. The initial driving area can be an area that can be driven as indicated by the initial decision information. For example, when emergency braking can avoid a collision, the initial driving area can include a forward driving area. For another example, when there are multiple emergency steering angles that can avoid a collision, the initial driving area can include multiple lateral areas.

[0087] S204: Generate an activation mark of the initial driving area according to the first obstacle information and the second obstacle.

[0088] In this embodiment, the microcontroller in the controller can generate a corresponding activation mark for each initial driving area according to the first obstacle information and the second obstacle information. The activation mark is used to indicate whether the initial driving area needs to be activated. Optionally, the microcontroller in the controller can determine whether the initial driving area contains an obstacle according to the first obstacle information and the second obstacle information, and determine whether the initial driving area needs to be activated.

[0089] In one example, the process of generating the activation mark may include the following steps:

[0090] Step 1: If the initial driving area does not include the first obstacle information and the second obstacle information, the activation mark of the initial driving area is activatable.

[0091] In this step, the microcontroller in the controller can check whether the initial driving area contains the first obstacle information and / or the second obstacle information. That is, whether the obstacles indicated in the first obstacle information and the second obstacle information appear in the initial driving area. If the initial driving area does not contain the obstacles indicated in the first obstacle information and the second obstacle information, the microcontroller in the controller will set the activation flag of the initial driving area to activatable. When the drivable area is activatable, it means that the drivable area is a safe area.

[0092] Step 2: If the initial driving area includes the first obstacle information and / or the second obstacle information, the activation mark of the initial driving area is inactivatable.

[0093] In this step, if the initial driving area contains obstacles indicated in the first obstacle information and / or the second obstacle information, the microcontroller in the controller will accordingly set the activation flag of the initial driving area to inactivation. When the drivable area is inactivation, it means that a collision may occur when driving in the drivable area. That is, the initial driving area determined according to the first obstacle information is inaccurate.

[0094] In another example, the process of generating the activation mark may include:

[0095] If the initial driving area does not include the first obstacle information and the second obstacle information, the activation mark of the initial driving area is activatable. If the initial driving area includes the first obstacle information and the second obstacle information, the activation mark of the initial driving area is inactivatable. If the initial driving area includes the first obstacle information but does not include the second obstacle information, the activation mark of the initial driving area is high-risk. If the initial driving area does not include the first obstacle information but includes the second obstacle information, the activation mark of the initial driving area is high-risk.

[0096] S205: Generate final decision information according to the activation mark of the initial driving area.

[0097] In this embodiment, the microcontroller in the controller can determine the decision that the microcontroller in the controller ultimately needs to execute based on the activation identifiers of each initial driving area, and then generate final decision information. Optionally, the activation identifier may include activating the initial driving area or not activating it. If the activation identifier indicates that the initial driving area is activated, the microcontroller in the controller can generate final decision information based on the activated initial driving area. If the activation identifier indicates that the initial driving area is activated, the microcontroller in the controller can generate final decision information based on the activated initial driving area. If the activation identifier indicates that the initial driving area is not activated, the microcontroller in the controller can delete the inactivated drivable area from the decision information.

[0098] In one example, the process of generating final decision information by the microcontroller in the controller may include:

[0099] Step 1: If the activation mark of the lateral initial driving area corresponding to the initial decision information is activatable, determine that the final decision information instructs the vehicle to control the vehicle to make an emergency turn according to the lateral initial driving area with the activation mark as activatable.

[0100] In this step, after receiving the initial decision information, the microcontroller in the controller may first check the activation mark of the lateral initial driving area corresponding to the initial decision information. If the activation mark of the lateral initial driving area is activatable, the microcontroller in the controller may determine that the final decision information is to perform an emergency turn according to the activatable lateral initial driving area. Optionally, when there are multiple lateral initial driving areas with activation marks that are activatable, the microcontroller in the controller may determine the steering angle for the final emergency turn according to the steering angles corresponding to each initial driving area. Optionally, the microcontroller in the controller may choose to turn to the smallest steering angle.

[0101] Step 2: If the activation marks of the lateral initial driving areas corresponding to the initial decision information are all inactivatable, determine whether the activation mark of the forward initial driving area corresponding to the initial decision information is activatable.

[0102] In this step, if the activation marks of all lateral initial driving areas corresponding to the initial decision information are inactivatable, the microcontroller in the controller further determines the activation mark of the forward initial driving area.

[0103] Step 3: If the activation mark of the forward initial driving area corresponding to the initial decision information is activatable, determine that the final decision information instructs the vehicle to control the vehicle emergency braking according to the forward initial driving area with the activation mark as activatable.

[0104] In this step, when the activation mark of the forward initial driving area is activatable, the microcontroller in the controller immediately determines the final decision information. The final decision information instructs the vehicle to perform emergency braking measures according to the forward initial driving area.

[0105] Step 4: If the activation marks of the lateral initial driving areas corresponding to the initial decision information are all inactivatable, a first warning message is generated. The first warning message is used to remind the user that the collision cannot be avoided by turning.

[0106] In this step, if the activation marks of the lateral initial driving areas corresponding to the initial decision information are all inactivatable, it means that the steering cannot avoid the collision. At this time, the microcontroller in the controller will immediately generate a first warning message to prompt the user. The first warning message is used to prompt the user that the lateral collision cannot be avoided.

[0107] Step 5: If the activation marks of the forward initial driving area corresponding to the initial decision information are all inactivatable, a second warning message is generated. The second warning message is used to remind the user that the collision cannot be avoided by braking.

[0108] In this step, if the lateral areas are not feasible, the microcontroller in the controller then checks the activation mark of the forward initial driving area. If the activation marks of the forward initial driving area are all displayed as inactivatable, it means that emergency braking cannot avoid the collision. At this time, the microcontroller in the controller will generate a second warning message to issue a corresponding warning to the user. The second warning message is used to remind the user that the forward collision cannot be avoided.

[0109] In the assisted driving method provided by the embodiment of the present application, the microcontroller in the controller may store the recognition model corresponding to each sensor. The microcontroller in the controller may use the recognition model to identify the sensor data of each sensor to obtain the third obstacle information corresponding to each sensor data. The microcontroller in the controller will fuse and filter the third obstacle information corresponding to each sensor data, and eliminate the redundant or erroneous obstacle information therein, so as to obtain more accurate second obstacle information. The microcontroller in the controller may extract at least one initial driving area from the initial decision information. The microcontroller in the controller may generate a corresponding activation mark for each initial driving area according to the first obstacle information and the second obstacle information. The microcontroller in the controller may determine the decision that the microcontroller in the controller needs to execute in the end according to the activation marks of each initial driving area, and then generate the final decision information. The sensor data is identified, fused and filtered by the recognition model stored in the microcontroller in the controller to obtain accurate second obstacle information, and the activation mark is generated for the initial driving area in combination with the first obstacle information, and then the means of generating and executing the final decision information according to the activation mark is achieved to improve the safety of the vehicle.

[0110] On the basis of the above embodiment, the microcontroller in the controller may also add the following judgment in the process of generating the final decision information to improve the validity of the final decision information and the safety of the vehicle to meet the safety requirements of ASIL D. The specific process may include:

[0111] S301. If the final decision information indicates that the vehicle performs emergency steering or emergency braking, determine whether a control module used to perform emergency braking or emergency steering has an abnormality.

[0112] In this embodiment, the microcontroller in the controller can access the control module for performing emergency braking or emergency steering when it is determined that the final decision information instructs the vehicle to perform emergency steering or emergency braking, so as to determine whether there is an abnormality in the control module for performing emergency braking or emergency steering. Optionally, the microcontroller in the controller can also access the control module for performing emergency steering when it is determined in S205 that emergency steering needs to be performed, so as to determine whether there is an abnormality in the control module for performing emergency steering. Optionally, the microcontroller in the controller can also access the control module for performing emergency braking when it is determined in S205 that emergency braking needs to be performed, so as to determine whether there is an abnormality in the control module for performing emergency braking. Optionally, the abnormality may include response delay, signal instability, functional failure, etc.

[0113] S302: If the control module for performing emergency braking or emergency steering has an abnormality, generate third prompt information. The third prompt information is used to prompt the user that the control module for performing emergency braking or emergency steering has an abnormality.

[0114] In this embodiment, the microcontroller in the controller can also generate a third prompt message when an abnormality occurs in the control module used to perform emergency braking or emergency steering, so as to inform the user that an abnormality currently occurs in the control module used to perform emergency braking or emergency steering, so as to ensure that the user can understand and take possible countermeasures in a timely manner to ensure driving safety.

[0115] Optionally, the microcontroller in the controller may generate a third prompt message when it is determined in S205 that emergency steering is required and the control module of the emergency steering is abnormal. Thereafter, the microcontroller in the controller may generate a third prompt message when it is determined in S205 that emergency braking is required and the control module of the emergency braking is abnormal.

[0116] Based on the above embodiments, Figure 6As shown in the figure, based on the above architecture hierarchy, after the vehicle is powered on, the AES is powered on synchronously. The perception system transmits the environmental perception information to the automatic driving control module through relevant channels. After processing and identification, the automatic driving control module sends the forward and lateral control commands to the gateway via the CAN bus. The gateway then forwards the forward control command to the emergency braking control module and the emergency steering control module through two CAN buses, and forwards the human-machine interface (HMI) control signal to the human-machine interaction control module through another CAN bus to realize the vehicle's driving assistance control. The specific process may include:

[0117] S401. The vehicle controller may control the vehicle to start.

[0118] S402: The visual processing module processes obstacles perceived by the visual module.

[0119] In this embodiment, the visual processing module obtains the video information in front of the vehicle collected by the front-view camera module and the video information on the side of the vehicle collected by the periscope camera module through the deserializer. The visual processing module recognizes and processes the video information to obtain the obstacle information contained in the video information. The obstacle information may specifically include obstacles such as vehicles, pedestrians, and stationary objects. The visual processing module can also calculate the relative position information between the vehicle and the obstacle, the motion properties of the obstacle, etc. Among them, the motion properties of the obstacle may include speed, lateral acceleration, longitudinal acceleration, heading angle, etc. The visual processing module can pass the obstacle information to the perception fusion module. The visual processing module is developed according to ASIL B level.

[0120] S403, the perception fusion module fuses the forward-looking radar target and the target after visual processing.

[0121] In this embodiment, the perception fusion module can match and fuse the first obstacle information transmitted by the visual processing module with the obstacles identified by the external sensors corner radar, laser radar, and forward radar. The perception fusion module can also reconstruct the coordinates of the obstacle according to the vehicle's own coordinate system to obtain the first obstacle information. The perception fusion module can pass the first obstacle information to the decision planning module. The perception fusion module is developed according to ASIL B level.

[0122] S404: The decision-making planning module determines whether the conditions for triggering AEB are met.

[0123] In this embodiment, the decision planning module determines whether there is an obstacle in the forward direction that may cause a collision risk with the vehicle based on the first obstacle information. If yes, the condition for triggering AEB is met.

[0124] S405, the decision planning module plans the AEB deceleration / AES steering angle.

[0125] In this embodiment, when the decision planning module determines that AEB needs to be triggered, the decision planning module can perform AEB deceleration planning. At the same time, the decision planning module can also perform AES function steering angle planning by determining the lateral drivable area. The decision planning module can ultimately calculate the AEB deceleration and AES steering angle, and form the initial decision information. The controller's system chip can output the initial decision information to the AEB / AES arbitration module. The decision planning module is developed according to ASIL B level.

[0126] S406: The lateral dangerous target judgment module determines whether there is an obstacle.

[0127] In this embodiment, the lateral dangerous target determination module can receive the first obstacle information identified by the visual module. The first obstacle information may include obstacles such as vehicles, personnel, and guardrails. At the same time, the lateral dangerous target determination module can also receive obstacles input from the corner radar. The lateral dangerous target module performs a target check for obstacles in the initial driving area designated for the operation of the AES function. If there is an obstacle in the initial driving area, the dangerous target flag can be recorded as yes. If there is no obstacle, the dangerous target flag can be recorded as no. The microcontroller in the controller can pass the lateral dangerous target flag to the AEB / AES arbitration module. The lateral dangerous target determination module is developed according to ASIL D level.

[0128] S407: Check whether the emergency brake control module is faulty.

[0129] In this embodiment, the AES / AEB arbitration module determines whether AES and AEB need to be activated based on the initial decision information input by the decision planning module. When it is determined that there is an obstacle ahead and the collision cannot be avoided by triggering AEB, and there is a dangerous target on the side, it is necessary to determine whether the emergency brake control module is faulty.

[0130] S408 , the AEB / AES arbitration module arbitrates and triggers the AEB function.

[0131] In this embodiment, when the AES / AEB arbitration module determines that there is no fault in the braking system, it outputs an AES control request to the AEB control module. The AES / AEB arbitration module is developed according to ASIL D level.

[0132] S409. The AEB control module outputs a control instruction.

[0133] In this embodiment, the AEB control outputs a deceleration control instruction to the braking system.

[0134] S410: The AEB / AES arbitration module inhibits triggering of the AEB function and issues a fault prompt indicating that AEB cannot be activated.

[0135] In this embodiment, if the AES / AEB arbitration module determines that the emergency brake control module is faulty, activation of the AEB function is suppressed, and a fault prompt indicating that the AEB function cannot be activated is sent to the HMI.

[0136] S411, the AEB / AES arbitration module inhibits triggering of the AES function and issues a fault prompt indicating that AES cannot be activated.

[0137] In this embodiment, when the AES / AEB arbitration module determines that there is a fault in the steering control module, the AES function is inhibited from being activated, and a fault prompt indicating that the AES function cannot be activated is sent to the HMI.

[0138] S412: Check whether the emergency steering control module is faulty.

[0139] In this embodiment, the AES / AEB arbitration module determines whether AES and AEB need to be activated based on the information input by the decision planning module. When it is determined that there is an obstacle ahead, the collision cannot be avoided by triggering AEB, and there is no obstacle to the side, it is necessary to determine whether the steering control module is faulty. Among them, when it is determined that there is an obstacle ahead, the collision cannot be avoided by triggering AEB, and there is no obstacle to the side, the AES / AEB arbitration module can determine that an emergency steering operation needs to be performed.

[0140] S413 , the AEB / AES arbitration module arbitrates and triggers the AES function.

[0141] In this embodiment, the AES / AEB arbitration module determines that the steering control module has no faults, and then outputs an AES control request to the AES control module.

[0142] S414. The AES control module outputs a control instruction.

[0143] In this embodiment, the AES module outputs a steering control instruction to the steering system.

[0144] Figure 7 A schematic diagram of the structure of the auxiliary driving device provided in this application, such as Figure 7 As shown, the driving assistance device 500 provided in this embodiment is applied to a vehicle, and the controller of the vehicle includes a system chip of safety level B and a microcontroller of safety level D, including:

[0145] The first processing module 501 is used to generate first obstacle information and initial decision information in the system chip according to the sensor data collected by each sensor of the multiple sensors in the vehicle; wherein the initial decision information represents the initial decision of the assisted driving of the vehicle, and the first obstacle information is the obstacle identification information of the safety level B;

[0146] The second processing module 502 is used to generate and execute the final decision information of the assisted driving of the vehicle with safety level D in the microcontroller according to the initial decision information, the first obstacle information and the data of each sensor.

[0147] Optionally, the second processing module 501 is used to:

[0148] Generate second obstacle information based on the data from each sensor; the second obstacle information is obstacle identification information of safety level D;

[0149] Initial decision information is optimized according to the first obstacle information and the second obstacle information to obtain final decision information.

[0150] Optionally, the second processing module 501 is used to:

[0151] Identify each sensor data to obtain third obstacle information corresponding to each sensor data;

[0152] The third obstacle information is fused and screened to obtain the second obstacle information.

[0153] Optionally, the second processing module 501 is used to:

[0154] The third obstacle information is screened according to the probability threshold corresponding to each sensor data to obtain fourth obstacle information;

[0155] fusing and matching the fourth obstacle information corresponding to each sensor data to obtain fifth obstacle information;

[0156] The fifth obstacle information is screened according to a preset fusion threshold to obtain the second obstacle information.

[0157] Optionally, the second processing module 501 is used to:

[0158] Matching the fourth obstacle information corresponding to each sensor data to obtain the sixth obstacle information corresponding to each sensor data;

[0159] According to the probability weight corresponding to each sensor data, the sixth obstacle information corresponding to each sensor data is weightedly fused to obtain the fifth obstacle information.

[0160] Optionally, the second processing module 501 is used to:

[0161] Determining at least one initial driving area according to the initial decision information;

[0162] generating an activation mark of an initial driving area according to the first obstacle information and the second obstacle;

[0163] The final decision information is generated according to the activation mark of the initial driving area.

[0164] Optionally, the second processing module 501 is used to:

[0165] If the initial driving area does not include the first obstacle information and the second obstacle information, the activation mark of the initial driving area is activatable;

[0166] If the initial driving area includes the first obstacle information and / or the second obstacle information, the activation mark of the initial driving area is inactivatable.

[0167] Optionally, the second processing module 501 is used to:

[0168] If the activation mark of the lateral initial driving area corresponding to the initial decision information is activatable, determining the final decision information to instruct the vehicle to control the emergency steering of the vehicle according to the lateral initial driving area with the activation mark as activatable;

[0169] If the activation marks of the lateral initial driving areas corresponding to the initial decision information are all inactivatable, determining whether the activation mark of the forward initial driving area corresponding to the initial decision information is activatable;

[0170] If the activation mark of the forward initial driving area corresponding to the initial decision information is activatable, it is determined that the final decision information instructs the vehicle to control the vehicle emergency braking according to the forward initial driving area with the activation mark as activatable.

[0171] Optionally, the second processing module 501 is used to:

[0172] If the activation marks of the lateral initial driving areas corresponding to the initial decision information are all inactivatable, a first warning message is generated; the first warning message is used to prompt the user that the collision cannot be avoided by turning;

[0173] If the activation marks of the forward initial driving area corresponding to the initial decision information are all inactivatable, a second warning message is generated; the second warning message is used to prompt the user that braking cannot avoid a collision.

[0174] Optionally, the first processing module 501 is used to:

[0175] Identify each sensor data to obtain third obstacle information corresponding to each sensor data;

[0176] Matching the third obstacle information corresponding to each sensor data to obtain the first obstacle information;

[0177] Initial decision information is generated according to the first obstacle information.

[0178] Optionally, the second processing module 501 is used to:

[0179] If the final decision information indicates that the vehicle performs emergency steering or emergency braking, determining whether there is an abnormality in a control module for performing emergency braking or emergency steering;

[0180] If there is an abnormality in the control module used to perform emergency braking or emergency steering, a third prompt message is generated; the third prompt message is used to prompt the user that there is an abnormality in the control module used to perform emergency braking or emergency steering.

[0181] The auxiliary driving device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be described in detail here.

[0182] Figure 8 This is a schematic diagram of the structure of the controller provided in this application. Figure 8 As shown, the controller 600 provided in this embodiment includes: a system chip and a microprocessor. The system chip and the microprocessor may respectively include: at least one processing unit 601 and a storage unit 602. Optionally, the controller 600 also includes a communication component 603. The processing unit 601, the storage unit 602 and the communication component 603 are connected via a bus 604.

[0183] In a specific implementation process, at least one processing unit 601 executes the computer execution instructions stored in the storage unit 602, so that at least one processing unit 601 executes the above method.

[0184] The specific implementation process of the processing unit 601 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0185] In the above embodiments, it should be understood that the processing unit may be a central processing unit (CPU), or other general processing units, a digital signal processing unit (DSP), an application specific integrated circuit (ASIC), etc. The general processing unit may be a microprocessing unit or the processing unit may be any conventional processing unit, etc. The steps of the method disclosed in the invention may be directly embodied as being executed by a hardware processing unit, or may be executed by a combination of hardware and software modules in the processing unit.

[0186] The storage unit may include a high-speed storage unit (Random Access Memory, RAM), and may also include a non-volatile storage unit (Non-volatile Memory, NVM), such as at least one disk storage unit.

[0187] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0188] The present application also provides a vehicle, comprising a plurality of sensors and Figure 7 The controller shown in the figure can be used to execute and implement the above method.

[0189] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processing unit.

[0190] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processing unit executes the computer-executable instructions, the above method is implemented.

[0191] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory cell (SRAM), an electrically erasable programmable read-only memory cell (EEPROM), an erasable programmable read-only memory cell (EPROM), a programmable read-only memory cell (PROM), a read-only memory cell (ROM), a magnetic storage cell, a flash memory cell, a magnetic disk or an optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0192] An exemplary readable storage medium is coupled to a processing unit so that the processing unit can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processing unit. The processing unit and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processing unit and the readable storage medium can also exist in the device as discrete components.

[0193] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0194] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0195] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0196] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory unit (Read-Only Memory, ROM), random access memory unit (Random Access Memory, RAM), disk or optical disk, and other media that can store program codes.

[0197] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0198] The above embodiments are only preferred embodiments for fully illustrating the present application, and the protection scope of the present application is not limited thereto. Any equivalent substitution or change made by a person skilled in the art based on the present application is within the protection scope of the present application.

Claims

1. A driving assistance method, characterized in that: Applied to a vehicle, wherein a controller of the vehicle includes a system chip of safety level B and a microcontroller of safety level D, the method comprising: According to the sensor data collected by each of the multiple sensors in the vehicle, first obstacle information and initial decision information are generated in the system chip; wherein the initial decision information represents the initial decision of the assisted driving of the vehicle, and the first obstacle information is obstacle identification information of safety level B; Based on the initial decision information, the first obstacle information and each of the sensor data, the microcontroller generates and executes final decision information for assisted driving of the vehicle with a safety level D.

2. The method according to claim 1, characterized in that According to the initial decision information, the first obstacle information and each of the sensor data, the microcontroller generates and executes final decision information of the assisted driving of the vehicle with a safety level D, including: Generate second obstacle information according to the data of each sensor; the second obstacle information is obstacle identification information of safety level D; The initial decision information is optimized according to the first obstacle information and the second obstacle information to obtain the final decision information.

3. The method according to claim 2, characterized in that Generate second obstacle information according to the data from each sensor, including: Identify each sensor data to obtain third obstacle information corresponding to each sensor data; The third obstacle information is fused and screened to obtain the second obstacle information.

4. The method according to claim 3, characterized in that The third obstacle information is fused and screened to obtain the second obstacle information, including: Filter the third obstacle information according to the probability threshold corresponding to each sensor data to obtain fourth obstacle information; fusing and matching the fourth obstacle information corresponding to each sensor data to obtain fifth obstacle information; The fifth obstacle information is screened according to a preset fusion threshold to obtain the second obstacle information.

5. The method according to claim 4, characterized in that The fourth obstacle information corresponding to each sensor data is fused and matched to obtain fifth obstacle information, including: Matching the fourth obstacle information corresponding to each sensor data to obtain sixth obstacle information corresponding to each sensor data; The sixth obstacle information corresponding to each sensor data is weightedly fused according to the probability weight corresponding to each sensor data to obtain the fifth obstacle information.

6. The method according to claim 2, characterized in that Optimizing the initial decision information according to the first obstacle information and the second obstacle information to obtain the final decision information includes: Determining at least one initial driving area according to the initial decision information; generating an activation mark of the initial driving area according to the first obstacle information and the second obstacle; The final decision information is generated according to the activation mark of the initial driving area.

7. The method according to claim 6, characterized in that Generating an activation mark of the initial driving area according to the first obstacle information and the second obstacle includes: If the initial driving area does not include the first obstacle information and the second obstacle information, the activation mark of the initial driving area is activatable; If the initial driving area includes the first obstacle information and / or the second obstacle information, the activation mark of the initial driving area is inactivatable.

8. The method according to claim 6, characterized in that Generating the final decision information according to the activation mark of the initial driving area includes: If the activation mark of the lateral initial driving area corresponding to the initial decision information is activatable, determining that the final decision information instructs the vehicle to control emergency steering of the vehicle according to the lateral initial driving area for which the activation mark is activatable; If the activation marks of the lateral initial driving area corresponding to the initial decision information are all inactivatable, determining whether the activation mark of the forward initial driving area corresponding to the initial decision information is activatable; If the activation mark of the forward initial driving area corresponding to the initial decision information is activatable, it is determined that the final decision information instructs the vehicle to control emergency braking of the vehicle according to the forward initial driving area with the activation mark as activatable.

9. The method according to claim 8, characterized in that The method further comprises: If the activation marks of the initial driving area on the side corresponding to the initial decision information are all inactivatable, a first warning message is generated; the first warning message is used to prompt the user that the collision cannot be avoided by turning; If the activation marks of the forward initial driving area corresponding to the initial decision information are all inactivatable, a second warning message is generated; the second warning message is used to remind the user that braking cannot avoid a collision.

10. The method according to claim 1, characterized in that Generating first obstacle information and initial decision information in the system chip according to sensor data collected by each of the multiple sensors in the vehicle includes: Identify each sensor data to obtain third obstacle information corresponding to each sensor data; Matching the third obstacle information corresponding to each sensor data to obtain the first obstacle information; The initial decision information is generated according to the first obstacle information.

11. The method according to any one of claims 1 to 10, characterized in that The method further comprises: If the final decision information indicates that the vehicle performs emergency steering or emergency braking, determining whether a control module for performing the emergency braking or the emergency steering has an abnormality; If there is an abnormality in the control module used to perform the emergency braking or the emergency steering, a third prompt message is generated; the third prompt message is used to prompt the user that there is an abnormality in the control module used to perform the emergency braking or the emergency steering.

12. A driving assistance device, characterized in that: Applied to a vehicle, the vehicle includes a system chip of safety level B and a microcontroller of safety level D, the device includes: a first processing module, configured to generate first obstacle information and initial decision information in the system chip according to sensor data collected by each of the plurality of sensors in the vehicle; wherein the initial decision information represents an initial decision of the assisted driving of the vehicle, and the first obstacle information is obstacle identification information of safety level B; The second processing module is used to generate and execute final decision information of the assisted driving of the vehicle with a safety level D in the microcontroller based on the initial decision information, the first obstacle information and each of the sensor data.

13. A controller, characterized in that: The controller includes: a system chip and a microprocessor; The system chip and the microprocessor respectively include a storage unit and a processing unit; The storage unit stores computer-executable instructions; the processing unit executes the computer-executable instructions stored in the storage unit, so that the processing unit executes the method according to any one of claims 1 to 11.

14. A vehicle, characterized in that: The vehicle comprises: a plurality of sensors and the controller as claimed in claim 13.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 11 when executed by a processing unit.

16. A computer program product, comprising a computer program, wherein when the computer program is executed by a processing unit, the method according to any one of claims 1 to 11 is implemented.

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