A control strategy adaptive method, device, equipment and medium of a vehicle

Abstract

The application discloses a kind of vehicle control strategy adaptive method, device, equipment and medium.Control strategy adaptive method includes: obtaining weather forecast information, the position information of vehicle, the sensing data information of sensing device and the judgment information of driver to weather condition;Determine climate environment information according to weather forecast information, position information, sensing data information and judgment information;Determine the decision weight information of sensing device according to climate environment information;Determine the sensing error rate information of sensing device according to sensing data information;Determine the sensing result information of sensing device according to decision weight information, sensing error rate information and sensing data information;Determine the control strategy of vehicle according to sensing error rate information and sensing result information, wherein, when sensing result information is clear, control strategy is automatic driving or auxiliary driving.The application can solve the problem of conservative control strategy of existing vehicle.

Description

Technical Field

[0001] This invention relates to the field of vehicle autonomous driving control technology, and in particular to a vehicle control strategy adaptive method, device, equipment and medium. Background Technology

[0002] Autonomous driving and driver assistance technologies have been implemented in three types of vehicles: locomotives, urban rail transit, and automobiles, covering three major scenarios: trunk line transportation, urban commuting, and civilian travel. However, the implementation of this technology largely relies on radar and multi-sensor fusion technology. Product manufacturers need to couple and calibrate the radar and multiple sensors before the product leaves the factory, and achieve vehicle "intelligence" through scenario data training.

[0003] However, severe weather can weaken vehicle system performance at multiple levels, including perception, decision-making, and control, leading to safety hazards. At the perception level, rain, snow, frost, and dense fog directly interfere with sensor operation; cameras are prone to image blurring due to rain and snow covering the lens and light refraction and scattering, making it difficult to accurately identify lane lines, traffic signs, and obstacles; millimeter-wave radar signals are attenuated by rain and snow, and lidar point cloud data suffers from significant noise due to dense fog and hail, both of which can cause missed or false detections of obstacles. Simultaneously, icy roads and standing water alter the friction between the vehicle and the ground, affecting the data accuracy of wheel speed sensors and inertial measurement units, causing deviations in the system's self-positioning and attitude judgments. At the decision-making and control level, complex road conditions in severe weather can exceed the system's preset scenario library. For example, the hydroplaning effect on flooded roads and vehicle slippage on snow-covered roads make it difficult for autonomous driving algorithms to adjust braking and steering strategies in real time; sudden fog and a sharp drop in visibility can lead to delayed system decisions, preventing timely deceleration and avoidance maneuvers. In addition, extreme weather can damage vehicle-road cooperative equipment, such as roadside radar and communication base station malfunctions, which can lead to the interruption of information exchange between vehicles and cloud and roadside facilities, further reducing the reliability of autonomous driving and significantly increasing the probability of traffic accidents.

[0004] To address these issues, some smart car manufacturers are using technologies such as hydrophobic coatings and heated cameras to reduce environmental impact. They are also employing multi-sensor fusion (LiDAR + millimeter-wave radar + vision, camera + radar, etc.) data cross-validation, combined with algorithms to determine rain and snow intensity, and adjusting perception weights and control strategies (such as reducing speed and increasing following distance).

[0005] However, current intelligent vehicles lack autonomous environmental recognition capabilities, and their perception weights and control strategies are pre-programmed at the factory. In adverse weather conditions, vehicles cannot proactively adjust their autonomous driving strategies based on the environment. Furthermore, such adjustments are limited by the programmer's understanding of the environment and the vehicle's actual condition, as well as the manufacturer's principles of avoiding liability, often resulting in conservative strategies. For example, if a single sensing device in the intelligent vehicle is severely affected, it may directly disengage from autonomous or assisted driving. This leads to vehicles disengaging from autonomous or assisted driving when they could potentially complete the journey, leaving drivers and operators to passively bear the uncontrollable consequences caused by severe weather. Summary of the Invention

[0006] This invention provides a method, apparatus, device, and medium for adaptive vehicle control strategies to address the problem of conservative control strategies in existing vehicles.

[0007] In a first aspect, embodiments of the present invention provide a vehicle control strategy adaptive method, comprising: It obtains weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions; Climate and environmental information is determined based on the weather forecast information, the location information, the sensing data information, and the judgment information. The decision weight information of the sensing device is determined based on the climate and environmental information. The sensing error rate information of the sensing device is determined based on the sensing data information; The sensing result information of the sensing device is determined based on the decision weight information, the sensing error rate information, and the sensing data information. The vehicle control strategy is determined based on the perception error rate information and the perception result information, wherein when the perception result information is clear, the control strategy is automatic driving or assisted driving.

[0008] Optionally, obtain weather forecast information, including: After the vehicle is started, it connects to the network to obtain the weather forecast information.

[0009] Optionally, determining the sensing error rate information of the sensing device based on the sensing data information includes: Based on the sensing data obtained by the sensing device from sensing the preset reference marker under the climate environment information, and the reference sensing data obtained by the sensing device from sensing the preset reference marker under normal climate environment, the sensing error rate information of the sensing device is determined.

[0010] Optionally, determining the sensing result information of the sensing device based on the decision weight information, the sensing error rate information, and the sensing data information includes: The sensing data information is calibrated based on the sensing error rate information; The sensing result information of the sensing device is determined based on the decision weight information and the calibrated sensing data information.

[0011] Optionally, determining a vehicle control strategy based on the perception error rate information and the perception result information includes: The decision weight information is adjusted based on the perception error rate information and the perception result information; The vehicle's control strategy is adjusted based on the adjusted decision weight information and the perception result information.

[0012] Optionally, after determining the climate and environmental information, the adaptive control strategy method further includes: The protection method for the sensing device is determined based on the climate and environmental information.

[0013] Optionally, the protection method of the sensing device is determined based on the climate environment information, including: When the climate environment information indicates an abnormal climate environment and the temperature information of the climate environment is less than or equal to zero, the protection method includes heating the sensing device; When the climate environment information indicates an abnormal climate environment, and the climate environment includes rain, the protection method includes activating the windshield wipers; When the climate environment information indicates an abnormal climate environment, and the climate environment affects the camera and ultrasonic radar, the protection method includes blowing air to remove dust from the camera lens.

[0014] In a second aspect, embodiments of the present invention provide a vehicle control strategy adaptive device for executing the control strategy adaptive method as described in the first aspect, the control strategy adaptive device comprising: The information acquisition unit is used to acquire weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions. A climate and environmental information determination unit is used to determine climate and environmental information based on the weather forecast information, the location information, the sensing data information, and the judgment information. A decision weight information determination unit is used to determine the decision weight information of the sensing device based on the climate environment information. A perception error rate information determination unit is used to determine the perception error rate information of the perception device based on the perception data information. A perception result information determination unit is used to determine the perception result information of the perception device based on the decision weight information, the perception error rate information, and the perception data information. The control strategy determination unit is used to determine the vehicle's control strategy based on the perception error rate information and the perception result information.

[0015] Thirdly, embodiments of the present invention provide a vehicle control strategy adaptive device, the control strategy adaptive device comprising: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the control strategy adaptive method as described in the first aspect.

[0016] Fourthly, embodiments of the present invention provide a storage medium storing a computer program thereon, which, when executed by a processor, implements the control strategy adaptive method as described in the first aspect.

[0017] The technical solution of this invention, by setting up a system capable of determining climate environment information based on acquired weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions, enables autonomous identification of the climate environment. Furthermore, by setting up a system capable of determining the vehicle's control strategy based on the sensing error rate and sensing results of the sensing devices, and by allowing the vehicle to operate in either autonomous or assisted driving mode as long as the sensing results are clear, this improves the vehicle's autonomous decision-making ability. Instead of automatically disengaging from autonomous or assisted driving simply because a particular sensing device is severely affected, this solution addresses the problem of conservative control strategies in existing vehicles and helps reduce traffic problems and legal disputes caused by inappropriate control strategies due to extreme weather conditions.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1A flowchart of a vehicle control strategy adaptive method provided in an embodiment of the present invention; Figure 2 A flowchart for determining climate and environmental information is provided as an embodiment of the present invention; Figure 3 A flowchart of another vehicle control strategy adaptive method provided in an embodiment of the present invention; Figure 4 A flowchart of another vehicle control strategy adaptive method provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a vehicle control strategy adaptive device provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of a vehicle control strategy adaptive device provided in an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. The terms "upper," "lower," "left," "right," etc., indicate orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings and are only used to describe the relative positional relationships between components or constituent parts, and do not specifically limit the specific installation orientation of each component or constituent part.

[0023] Figure 1This is a flowchart illustrating a vehicle control strategy adaptive method according to an embodiment of the present invention. The defect repair method in this embodiment is applicable to situations requiring adaptive adjustment of the vehicle's control strategy. This control strategy adaptive method can be executed by a vehicle control strategy adaptive device, which can be implemented in software and / or hardware and specifically configured within the vehicle's control strategy adaptive equipment. (Refer to...) Figure 1 The adaptive vehicle control strategy method in this embodiment of the invention includes: S110: Obtain weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions.

[0024] As one feasible implementation method, obtaining weather forecast information includes: connecting the vehicle to the internet after starting the vehicle to obtain weather forecast information.

[0025] For example, the vehicle will be powered on after starting, so that the vehicle can connect to the network to query the weather forecast, obtain real-time weather forecast information, and transmit the obtained weather forecast information to the control strategy adaptive device.

[0026] The vehicle's location information can be whether the vehicle is indoors or outdoors. The adaptive control strategy device can determine this by the signal strength of the onboard GPS device, because the GPS signal strength is different when the vehicle is indoors compared to when it is outdoors. The GPS signal strength is weaker when the vehicle is indoors and stronger when it is outdoors.

[0027] When the vehicle starts, it will be powered on, and the sensing devices installed on the vehicle will also be powered on and turned on. The sensing devices can then perceive the surrounding environment, obtain sensing data information corresponding to the surrounding environment, and transmit the obtained sensing data information to the control strategy adaptive device.

[0028] The information a driver uses to assess weather conditions can be their judgment of whether the outdoor weather is abnormal.

[0029] S120. Determine climate and environmental information based on weather forecast information, location information, sensor data information, and judgment information.

[0030] Figure 2 A flowchart for determining climate and environmental information is provided as an embodiment of the present invention, with reference to... Figure 2In this embodiment of the invention, when the weather forecast indicates abnormal weather and the vehicle is in an outdoor environment, the sensing data obtained by the sensing device during normal calibration is abnormal; or when the weather forecast indicates abnormal weather and the vehicle is in an outdoor environment, the sensing data obtained by the sensing device during normal calibration is normal, but the driver confirms that the weather is abnormal; or when the weather forecast indicates abnormal weather, the vehicle is in an indoor environment, and the driver confirms that the weather is abnormal, the control strategy adaptive device will determine that the climate environment is abnormal. When the weather forecast indicates normal weather, or when the weather forecast indicates abnormal weather, but the driver confirms that the weather is normal, the control strategy adaptive device will determine that the climate environment is normal and can activate autonomous driving.

[0031] It should be noted that the climate environment information in this embodiment of the invention includes not only the judgment of whether the climate environment is abnormal, but also the specific climate environment type. It is understood that different climate environment types will result in different degrees of impact on various sensing devices or different sensing data. Therefore, the climate environment type can be determined based on the specific degree of impact on various sensing devices or the sensing data they receive. Specifically, the correspondence between climate environment types and the degree of impact on various sensing devices or the sensing data they receive can be referred to in Table 1 below: Table 1 It should be noted that the " / " in Table 1 indicates that the sensing data obtained by the sensing device is unrelated to the corresponding climate environment type and is not used as a basis for determining the corresponding climate environment type. A severe impact on the camera refers to the difference between the sensing data obtained by the camera under normal climate conditions and the sensing data obtained by the camera under abnormal climate conditions for the same preset reference marker being within a first preset range. A slight impact on the millimeter-wave radar refers to the difference between the sensing data obtained by the millimeter-wave radar under normal climate conditions and the sensing data obtained by the millimeter-wave radar under abnormal climate conditions for the same preset reference marker being within a second preset range. An abnormal rain sensor refers to the difference between the sensing data obtained by the millimeter-wave radar under rain conditions and the sensing data obtained by the rain sensor under abnormal climate conditions (rainy climate conditions) for the same preset reference marker exceeding a first preset threshold. A moderate impact on the lidar refers to the difference between the sensing data obtained by the lidar under normal climate conditions and the sensing data obtained by the lidar under abnormal climate conditions for the same preset reference marker being within a third preset range. The impact on lidar is defined as follows: a severe impact means the difference between the sensing data obtained by lidar under normal weather conditions and the sensing data obtained by lidar under abnormal weather conditions for the same preset reference marker is within the fourth preset range. A slight impact on ultrasonic radar is defined as the difference between the sensing data obtained by ultrasonic radar under normal weather conditions and the sensing data obtained by ultrasonic radar under abnormal weather conditions for the same preset reference marker is within the fifth preset range. A moderate impact on ultrasonic radar is defined as the difference between the sensing data obtained by ultrasonic radar under normal weather conditions and the sensing data obtained by ultrasonic radar under abnormal weather conditions for the same preset reference marker is within the sixth preset range. A severe impact on ultrasonic radar is defined as the difference between the sensing data obtained by ultrasonic radar under normal weather conditions and the sensing data obtained by ultrasonic radar under abnormal weather conditions for the same preset reference marker is within the seventh preset range.

[0032] It should be noted that the embodiments of the present invention do not limit the specific values ​​of the first preset range, the second preset range, the third preset range, the fourth preset range, the fifth preset range, the sixth preset range, the seventh preset range, and the first preset threshold, and those skilled in the art can set them themselves.

[0033] It should also be noted that the normal climate environment in the embodiments of the present invention refers to a climate environment without rain, snow, ice, frost, fog and haze, while the abnormal climate environment in the embodiments of the present invention refers to a climate environment with any or more of the following conditions: rain, snow, ice, frost, fog and haze.

[0034] S130. Determine the decision weight information of the sensing equipment based on climate and environmental information.

[0035] It is understandable that different climatic environments have varying degrees of impact on different sensing devices. To improve the accuracy of the sensing results determined based on the sensing data from each sensing device, this embodiment of the invention can first determine the decision weight information for each sensing device based on the climatic environment information. The greater the impact of the climatic environment on the sensing device, the smaller the weight of the sensing data from that device in determining the sensing result. It should be noted that the correspondence between climatic environment information and decision weight information is determined in advance through experiments. The corresponding relationship table can be pre-stored in a storage device. When the adaptive control strategy device needs to obtain the corresponding decision weight information after determining the climatic environment information, it can retrieve the relationship table from the storage device, and then determine the decision weight information of the sensing device based on the determined climatic environment information and the relationship table.

[0036] S140. Determine the sensing error rate information of the sensing device based on the sensing data information.

[0037] As a feasible implementation method, the sensing error rate information of the sensing device is determined based on the sensing data information, including: determining the sensing error rate information of the sensing device based on the sensing data information obtained by the sensing device in sensing a preset reference marker under climatic environmental information, and the reference sensing data information obtained by the sensing device in sensing a preset reference marker under normal climatic conditions.

[0038] It should be noted that the baseline sensing data obtained by the sensing device from sensing preset reference markers under normal climatic conditions is pre-acquired and can be stored in a storage device. When it is necessary to determine the sensing error rate of the sensing device, the adaptive control strategy device can retrieve the aforementioned baseline sensing data from the storage device. Then, based on the sensing data obtained by the sensing device from sensing preset reference markers under climatic conditions, which is acquired in real time by the sensing device, and the aforementioned baseline sensing data, the sensing error rate of the sensing device can be determined. It should also be noted that the sensing data obtained by the sensing device from sensing preset reference markers under climatic conditions can also be first stored in the storage device by the sensing device and then retrieved by the adaptive control strategy device.

[0039] For example, the millimeter-wave radar has a detection range of 3m for a preset reference marker under normal weather conditions, but a detection range of 5m under weather conditions (e.g., the weather conditions indicated by the weather conditions are rainy). The error distance of 2m between the two can be divided by the detection distance of 3m under normal weather conditions to obtain the sensing error rate information of the sensing device, which is 66.66%.

[0040] S150. Determine the sensing result information of the sensing device based on the decision weight information, the sensing error rate information, and the sensing data information.

[0041] As a feasible implementation method, the perception result information of the sensing device is determined based on decision weight information, perception error rate information, and perception data information, including: calibrating the perception data information based on the perception error rate information; and determining the perception result information of the sensing device based on the decision weight information and the calibrated perception data information.

[0042] It should be noted that the aforementioned perception result information may include, but is not limited to, the position, speed, shape, and category characteristics of the marker. Once the control strategy adaptive device has determined the perception result information, it can store the perception result information in a storage device so that it can be retrieved when needed.

[0043] Compared to existing methods that directly use the sensing data from sensing devices as the basis for sensing results, this embodiment of the invention, in order to improve the accuracy of sensing results, first calibrates the sensing data from each sensing device based on the sensing error rate information of each sensing device under the current climate environment. Specifically, the calibrated sensing data can be obtained by dividing the sensing data by the sensing error rate.

[0044] For example, the adaptive control strategy device can adjust the perception data coupling based on the decision weight information of the sensing device and the calibrated perception data information to obtain the perception result. For instance, an onboard vehicle with 10 radars (6 of which are millimeter-wave radars, 2 are ultrasonic radars, and 2 are lidars) and 2 cameras can perform feature coupling of the position, speed, shape, and category features of a reference marker when perceiving it, in order to perform target fusion, deduplication, and tracking, and output the final perception result.

[0045] S160. Determine the vehicle control strategy based on the perception error rate information and perception result information, wherein when the perception result information is clear, the control strategy is automatic driving or assisted driving.

[0046] It should be noted that once the control strategy adaptive device has determined the sensing result information, it can store the sensing result information in a storage device so that it can be retrieved when needed.

[0047] The adaptive control strategy device in this embodiment of the invention not only refers to the perception error rate information of the sensing devices, but also takes into account whether the perception result information is clear. When some sensing devices have a perception error rate, but the perception result information is clear, autonomous driving or assisted driving will still be adopted.

[0048] Once the vehicle's control strategy is determined, the vehicle's controller can execute the strategy, while simultaneously recording the execution information of the control strategy and the vehicle's driving information, storing them in a storage device for later retrieval when needed. This invention enables autonomous climate environment identification by setting up a system that can determine climate environment information based on acquired weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions. Furthermore, it allows for the determination of vehicle control strategies based on the sensing error rate and sensing results of the sensing devices. As long as the sensing results are clear, the vehicle's control strategy can be either autonomous driving or assisted driving, which improves the vehicle's autonomous decision-making ability. Instead of automatically disengaging from autonomous driving or assisted driving simply because a particular sensing device is severely affected, this invention solves the problem of conservative control strategies in existing vehicles and helps reduce traffic problems and legal disputes caused by inappropriate control strategies due to extreme weather conditions.

[0049] Figure 3 This is a flowchart of another adaptive vehicle control strategy method provided in an embodiment of the present invention. Figure 3 The illustrated embodiment provides a detailed explanation of how to determine the vehicle's control strategy based on perception error rate information and perception result information. (Refer to...) Figure 2 The adaptive vehicle control strategy method in this embodiment of the invention includes: S210: Obtain weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions.

[0050] S220. Determine climate and environmental information based on weather forecast information, location information, sensor data information, and judgment information.

[0051] S230. Determine the decision weight information of the sensing equipment based on climate and environmental information.

[0052] S240. Determine the sensing error rate information of the sensing device based on the sensing data information.

[0053] S250. Determine the sensing result information of the sensing device based on the decision weight information, the sensing error rate information, and the sensing data information.

[0054] S260. Adjust the decision weight information based on the perception error rate information and perception result information.

[0055] S270. Adjust the vehicle's control strategy based on the adjusted decision weight information and perception result information. When the perception result information is clear, the control strategy is either autonomous driving or assisted driving.

[0056] For example, when the perception error rate of all sensing devices is less than 20% and the final perception result information is clear, the decision weight information is not adjusted, and the vehicle's control strategy is to activate the normal autonomous driving function.

[0057] When the perception error rate of some sensing devices exceeds 20%, but the perception result information is clear, the sensing devices with a perception error rate exceeding 20% ​​(millimeter-wave radar, ultrasonic radar, lidar, cameras, etc.) are identified. Then, the weights of each sensing device are adjusted according to the perception result information to obtain the adjusted decision weight information. For example, in foggy weather, camera imaging is difficult and lidar error exceeds 20%, but the perception error rate of millimeter-wave radar and ultrasonic radar is less than 20%. When the perception result information obtained after data calibration and coupling algorithm adjustment is clear, the adaptive control strategy device will ignore the camera's visual signal, use the lidar signal only as reference information, and use the millimeter-wave radar and ultrasonic radar perception signals as the main decision information. At the same time, based on the maximum range that millimeter-wave radar and ultrasonic radar can perceive and the vehicle's braking distance, the vehicle speed-limited autonomous driving is performed.

[0058] When the perception error rate of some sensing devices exceeds 20%, and the perception result information is clear but incomplete, the location of the sensing devices with a perception error rate exceeding 20% ​​(such as in front of, on both sides of, and behind the vehicle) is identified. Then, the weight of each sensing device is adjusted according to the perception result information. For example, if hail damages the millimeter-wave radar in the middle of the left side of the vehicle, but the left side is covered by radars in front and behind, the perception result information corresponding to the environment on the left side of the vehicle is still clear. In this case, the vehicle is downgraded to driver assistance mode, indicating that the single-sided sensing device of the vehicle is damaged, and the driver takes over the control of the vehicle.

[0059] When the perception error rate of some sensing devices exceeds 20% and the perception result information is unclear, the location of the sensing devices with an error rate exceeding 20% ​​(such as in front of the vehicle, on both sides, and behind the vehicle) is identified. Then, the weight of each sensing device is adjusted according to the perception result information. For example, if hail damages a single-sided sensing device on the vehicle and there is no alternative sensing data on that side, the vehicle will indicate that the single-sided sensing device is damaged. In this case, only the available sensing information is provided for driving assistance, and the driver takes full control of the vehicle.

[0060] When the error rate of most (e.g., over 80%) of the sensing devices is higher than 20%, and the sensing results are unclear, the vehicle is prohibited from activating the autonomous driving system and a recommendation not to drive is given.

[0061] Figure 4 A flowchart illustrating another vehicle control strategy adaptive method provided in this embodiment of the invention. Figure 4 The illustrated embodiments enrich the flow of the adaptive control strategy method in the embodiments of the present invention. (Refer to...) Figure 4 The vehicle control strategy adaptive method in this embodiment of the invention includes: S310: Obtain weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions.

[0062] S320. Determine climate and environmental information based on weather forecast information, location information, sensor data information, and judgment information.

[0063] S330. Determine the protection method for sensing equipment based on climate and environmental information.

[0064] As a feasible implementation method, the protection method for the sensing device is determined based on the climate environment information, including: when the climate environment information is abnormal and the temperature information of the climate environment is less than or equal to zero, the protection method includes heating the sensing device; when the climate environment information is abnormal and the climate environment includes rain, the protection method includes activating the windshield wipers; when the climate environment information is abnormal and the climate environment affects the camera and ultrasonic radar, the protection method includes blowing air to remove dust from the camera lens.

[0065] It should be noted that, in the embodiments of the present invention, abnormal climate environment refers to at least one of the following: rain, snow, ice, frost, fog, and haze.

[0066] By implementing different protective measures for sensing devices under different climatic conditions, this invention can reduce the impact of abnormal weather conditions on sensing devices, thereby improving the accuracy of the sensing data and increasing the probability of clear sensing results. This further reduces traffic problems and legal disputes caused by improper control strategies due to extreme weather conditions.

[0067] S340. Determine the decision weight information of the sensing equipment based on climate and environmental information.

[0068] S350. Determine the sensing error rate information of the sensing device based on the sensing data information.

[0069] S360. Determine the sensing result information of the sensing device based on the decision weight information and the sensing data information.

[0070] S370. Determine the vehicle control strategy based on the perception error rate information and perception result information.

[0071] Based on the same inventive concept, embodiments of the present invention also provide a vehicle control strategy adaptive device. Figure 5 This is a schematic diagram of a vehicle control strategy adaptive device provided in an embodiment of the present invention, with reference to... Figure 5 The vehicle control strategy adaptive device in this embodiment of the invention includes: Information acquisition unit 410 is used to acquire weather forecast information, vehicle location information, sensing data information from sensing devices, and driver's judgment information on weather conditions; climate environment information determination unit 420 is used to determine climate environment information based on weather forecast information, location information, sensing data information, and judgment information; decision weight information determination unit 430 is used to determine decision weight information for sensing devices based on climate environment information; perception error rate information determination unit 440 is used to determine perception error rate information for sensing devices based on sensing data information; perception result information determination unit 450 is used to determine perception result information for sensing devices based on decision weight information, perception error rate information, and sensing data information; control strategy determination unit 460 is used to determine vehicle control strategy based on perception error rate information and perception result information.

[0072] The control strategy adaptive device provided in the embodiments of the present invention can execute the control strategy adaptive method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0073] Figure 6 A schematic diagram of a control strategy adaptive device 500, which can be used to implement embodiments of the present invention, is shown. The control strategy adaptive device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The control strategy adaptive device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0074] like Figure 6As shown, the control strategy adaptive device 500 includes at least one processor 510 and a memory, such as a read-only memory (ROM) 520 and a random access memory (RAM) 530, communicatively connected to the at least one processor 510. The memory stores computer programs executable by the at least one processor. The processor 510 can perform various appropriate actions and processes based on the computer program stored in the ROM 520 or loaded from storage unit 580 into the RAM 530. The RAM 530 may also store various programs and data required for the operation of the control strategy adaptive device 500. The processor 510, ROM 520, and RAM 530 are interconnected via a bus 540. An input / output (I / O) interface 550 is also connected to the bus 540.

[0075] Multiple components in the control policy adaptive device 500 are connected to the I / O interface 550, including: an input unit 560, such as a keyboard, mouse, etc.; an output unit 570, such as various types of displays, speakers, etc.; a storage unit 580, such as a disk, optical disk, etc.; and a communication unit 590, such as a network card, modem, wireless transceiver, etc. The communication unit 590 allows the control policy adaptive device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0076] Processor 510 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 510 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 510 performs the various methods and processes described above, such as adaptive control strategies.

[0077] In some embodiments, the control policy adaptation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 580. In some embodiments, part or all of the computer program may be loaded and / or installed onto the control policy adaptation device 500 via read-only memory (ROM) 520 and / or communication unit 590. When the computer program is loaded into random access memory (RAM) 530 and executed by processor 510, one or more steps of the control policy adaptation method described above may be performed. Alternatively, in other embodiments, processor 510 may be configured to perform the control policy adaptation method by any other suitable means (e.g., by means of firmware).

[0078] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0079] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0080] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, a portable computer disk, a hard disk, random access memory (RAM) 530, read-only memory (ROM) 520, erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0081] To provide user interaction, the systems and techniques described herein can be implemented on a control strategy adaptive device, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the control strategy adaptive device. Other types of devices can also be used to provide user interaction. For example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback). Input from the user can be received in any form (including sound input, voice input, or tactile input).

[0082] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0083] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0084] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0085] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An adaptive control strategy method for a vehicle, characterized in that, include: It obtains weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions; Climate and environmental information is determined based on the weather forecast information, the location information, the sensing data information, and the judgment information. The decision weight information of the sensing device is determined based on the climate and environmental information. The sensing error rate information of the sensing device is determined based on the sensing data information; The sensing result information of the sensing device is determined based on the decision weight information, the sensing error rate information, and the sensing data information. The vehicle control strategy is determined based on the perception error rate information and the perception result information, wherein when the perception result information is clear, the control strategy is automatic driving or assisted driving.

2. The adaptive control strategy method according to claim 1, characterized in that, Get weather forecast information, including: After the vehicle is started, it connects to the network to obtain the weather forecast information.

3. The adaptive control strategy method according to claim 1, characterized in that, Determining the sensing error rate information of the sensing device based on the sensing data information includes: Based on the sensing data obtained by the sensing device from sensing the preset reference marker under the climate environment information, and the reference sensing data obtained by the sensing device from sensing the preset reference marker under normal climate environment, the sensing error rate information of the sensing device is determined.

4. The adaptive control strategy method according to claim 1, characterized in that, The sensing result information of the sensing device is determined based on the decision weight information, the sensing error rate information, and the sensing data information, including: The sensing data information is calibrated based on the sensing error rate information; The sensing result information of the sensing device is determined based on the decision weight information and the calibrated sensing data information.

5. The adaptive control strategy method according to claim 1, characterized in that, Determining the vehicle control strategy based on the perception error rate information and the perception result information includes: The decision weight information is adjusted based on the perception error rate information and the perception result information; The vehicle's control strategy is adjusted based on the adjusted decision weight information and the perception result information.

6. The adaptive control strategy method according to claim 1, characterized in that, After determining the climate and environmental information, the adaptive control strategy method further includes: The protection method for the sensing device is determined based on the climate and environmental information.

7. The adaptive control strategy method according to claim 6, characterized in that, Determining the protection method of the sensing device based on the climate environment information includes: When the climate environment information indicates an abnormal climate environment and the temperature information of the climate environment is less than or equal to zero, the protection method includes heating the sensing device; When the climate environment information indicates an abnormal climate environment, and the climate environment includes rain, the protection method includes activating the windshield wipers; When the climate environment information indicates an abnormal climate environment, and the climate environment affects the camera and ultrasonic radar, the protection method includes blowing air to remove dust from the camera lens.

8. A vehicle control strategy adaptive device, used to execute the control strategy adaptive method as described in any one of claims 1-7, characterized in that, The adaptive control strategy device includes: The information acquisition unit is used to acquire weather forecast information, vehicle location information, sensing data from sensing devices, and the driver's judgment of weather conditions. A climate and environmental information determination unit is used to determine climate and environmental information based on the weather forecast information, the location information, the sensing data information, and the judgment information. A decision weight information determination unit is used to determine the decision weight information of the sensing device based on the climate environment information. A perception error rate information determination unit is used to determine the perception error rate information of the perception device based on the perception data information. A perception result information determination unit is used to determine the perception result information of the perception device based on the decision weight information, the perception error rate information, and the perception data information. The control strategy determination unit is used to determine the vehicle's control strategy based on the perception error rate information and the perception result information.

9. A vehicle control strategy adaptive device, characterized in that, The adaptive control strategy device includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the control strategy adaptive method as described in any one of claims 1-7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the adaptive control strategy method as described in any one of claims 1-7.

Images