Vehicle control device and method and storage medium

Abstract

The embodiment of the invention provides a vehicle control device and method and a storage medium, and the device comprises a brake mechanism which is configured to brake a vehicle; the vehicle lock mechanism is configured to unlock or lock a vehicle; the processing mechanism is in communication connection with the brake mechanism and the vehicle lock mechanism, and the processing mechanism is configured to respond to a locking control instruction sent by the vehicle management platform, determine the brake force level and control the brake mechanism to brake the vehicle based on the brake force level; determining whether the vehicle is in a braking state; and in response to determining that the vehicle is in the braking state, controlling the vehicle lock mechanism to lock the vehicle.

Description

Technical Field

[0001] This specification relates to the technical field of vehicle control, and particularly to a control device, method, and storage medium for braking and locking a vehicle. Background Art

[0002] Shared two-wheel vehicles and shared cars, as means of green travel, are widely used in today's society. To prevent users from using vehicles beyond the specified time, users from using vehicles outside the operating area, and vehicle loss, relevant strategies are adopted to perform a locking operation on shared vehicles. However, the locking operation performed on the vehicle is usually rather sudden, prone to problems related to riding safety or driving safety.

[0003] Therefore, it is necessary to provide a vehicle control device, method, and storage medium that can safely and effectively perform a locking operation on shared vehicles. Summary of the Invention

[0004] One or more embodiments of this specification provide a vehicle control device, which includes: a braking mechanism configured to brake the vehicle; a locking mechanism configured to unlock or lock the vehicle; a processing mechanism communicatively connected to the braking mechanism and the locking mechanism, and the processing mechanism is configured to: in response to a locking control instruction issued by a vehicle management platform, determine a braking force level and control the braking mechanism to brake the vehicle based on the braking force level; determine whether the vehicle is in a stopped state; and in response to determining that the vehicle is in a stopped state, control the locking mechanism to lock the vehicle.

[0005] In some embodiments, the device further includes a plurality of motion detection mechanisms, and determining whether the vehicle is in a stopped state includes: obtaining multiple sets of first data collected by the plurality of motion detection mechanisms; and based on the multiple sets of first data, determining whether the vehicle is in a stopped state.

[0006] In some embodiments, the plurality of motion detection mechanisms at least includes multiple ones of a locator, an accelerometer, a gyroscope, a speedometer, a camera, and a lidar.

[0007] In some embodiments, based on the multiple sets of first data, determining whether the vehicle is in a stopped state includes: for each motion detection mechanism, obtaining an initial determination result of whether the vehicle is stopped based on the first data collected by the motion detection mechanism; determining the confidence level of the motion detection mechanism based on the motion information and / or environmental information of the vehicle; and based on the initial determination result and the confidence level corresponding to each motion detection mechanism, determining whether the vehicle is in a stopped state.

[0008] In some embodiments, the plurality of motion detection mechanisms at least include a first motion detection mechanism with a first priority and a second motion detection mechanism with a second priority, where the first priority is higher than the second priority. Determining whether the vehicle is in a braking state based on the multiple sets of first data includes: obtaining an initial result of whether the vehicle is in a braking state based on the first data corresponding to the first motion detection mechanism; determining that the vehicle is in a non-braking state in response to the initial result indicating that the vehicle is in a non-braking state; and verifying the initial result based on the first data corresponding to the second motion detection mechanism in response to the initial result indicating that the vehicle is in a braking state.

[0009] In some embodiments, the device further includes a plurality of motion detection mechanisms. Determining the braking force level and controlling the braking mechanism to brake the vehicle based on the braking force level includes: obtaining at least one set of second data collected by at least one of the plurality of motion detection mechanisms before the braking mechanism brakes; determining the braking force level based on the at least one set of second data; and controlling the braking mechanism to brake the vehicle based on the braking force level.

[0010] In some embodiments, controlling the braking mechanism to brake the vehicle includes: determining whether the environment in which the vehicle is located satisfies the braking condition based on the environmental information of the vehicle; and controlling the braking mechanism to brake the vehicle based on the braking force level in response to determining that the environment in which the vehicle is located satisfies the braking condition.

[0011] In some embodiments, the processing mechanism is further configured to: send a locking prompt to the user through a terminal or a prompting mechanism installed on the vehicle before controlling the vehicle locking mechanism to lock the vehicle.

[0012] One or more embodiments of this specification provide a vehicle control method, which is executed by a processing mechanism and includes: determining a braking force level and controlling a braking mechanism to brake a vehicle based on the braking force level in response to a locking control instruction issued by a vehicle management platform; determining whether the vehicle is in a braking state; and controlling a vehicle locking mechanism to lock the vehicle in response to determining that the vehicle is in a braking state.

[0013] One or more embodiments of this specification provide a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a vehicle control method as described in any one of the above embodiments.

[0014] According to the above solution, by comprehensively utilizing multiple motion detection mechanisms on the vehicle, more reliable recognition results can be provided. In addition, performing a braking operation before locking the vehicle is beneficial to improving the safety when the vehicle is locked. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] This specification will be further described in the form of exemplary embodiments, which will be described in detail through the drawings. These embodiments are not restrictive. In these embodiments, the same numbers represent the same structures, where:

[0016] Figure 1A is a schematic diagram of the application scenario of the vehicle control device shown in some embodiments of this specification;

[0017] Figure 1B is an exemplary schematic diagram of the vehicle control device shown in some embodiments of this specification;

[0018] Figure 1C is an exemplary schematic diagram of the processing mechanism shown in some embodiments of this specification;

[0019] Figure 2 is an exemplary flowchart of the vehicle control method shown in some embodiments of this specification;

[0020] Figure 3 is an exemplary flowchart of determining whether the vehicle is in a stopped state based on multiple sets of first data shown in some embodiments of this specification. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structures or operations.

[0022] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the said words can be replaced by other expressions.

[0023] As shown in this specification and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0024] Flowcharts are used in this specification to illustrate the operations performed by the systems according to the embodiments of this specification. It should be understood that the previous or subsequent operations do not necessarily need to be executed precisely in sequence. On the contrary, the steps can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or more steps can be removed from these processes.

[0025] Figure 1A It is a schematic diagram of the application scenario of the vehicle control device shown in some embodiments of this specification. As Figure 1A shown, the application scenario 100 of the vehicle control device can include a vehicle 110, a vehicle management platform 120, and a network 130.

[0026] The vehicle 110 can include various types, for example, two-wheeled vehicles, automobiles, etc.

[0027] In some embodiments, a vehicle control device 111 is installed on the vehicle 110, which is used to obtain relevant information of the vehicle 110 (for example, coordinate position) and control the vehicle 110 (for example, perform braking and / or locking on the vehicle 110). Exemplarily, the vehicle control device 111 includes Figure 1B one or more components shown in, for example, a braking mechanism, a vehicle lock mechanism, a motion detection mechanism, a processing mechanism, a network communication mechanism, and a bus.

[0028] The braking mechanism is configured to brake the vehicle 110. Exemplarily, the braking mechanism includes components such as brake pads and brake discs. The vehicle lock mechanism is configured to unlock or lock the vehicle 110. Exemplarily, the vehicle lock mechanism includes components such as a lock body and a lock core. The motion detection mechanism is configured to detect the motion state of the vehicle 110. In some embodiments, multiple motion detection mechanisms are also installed on the vehicle 110. In some embodiments, the multiple motion detection mechanisms at least include multiple of a locator, an accelerometer, a gyroscope, a speedometer, a camera, and a lidar. Among them, the locator can be used to obtain the coordinate position of the vehicle 110; the accelerometer can be used to obtain the magnitude of the acceleration of the vehicle 110; the gyroscope can be used to obtain the magnitude of the angular velocity of the vehicle 110; the speedometer can be used to obtain the speed of the vehicle 110; the camera can be used to obtain the image data around the vehicle 110; the lidar can be used to obtain the laser point cloud around the vehicle 110.

[0029] The processing mechanism can be used to process data and / or information obtained from other components on the vehicle 110 and the vehicle management platform 120. In some embodiments, the processing mechanism can be communicatively connected to other components on the vehicle 110 (such as the braking mechanism, the vehicle lock mechanism, the motion detection mechanism) via a bus and control these components. For example, in response to a vehicle lock control instruction issued by the vehicle management platform 120, the processing mechanism can determine the braking force level and control the braking mechanism to brake the vehicle 110 based on the braking force level. For another example, the processing mechanism can acquire the data collected by the motion detection mechanism and determine whether the vehicle 110 is in a stopped state based on this data. For yet another example, in response to determining that the vehicle 110 is in a stopped state, the processing mechanism can control the vehicle lock mechanism to lock the vehicle 110.

[0030] In some embodiments, the processing mechanism includes Figure 1C the processor, the memory, and the processing bus shown in. In some embodiments, the processor can be communicatively connected to the memory via the processing bus to access the information and / or data stored thereon. The memory can store data, instructions, and / or any other information. In some embodiments, the memory can store the data obtained from the processor. In some embodiments, the memory can store the data and / or instructions that the processor uses to execute or implement the exemplary methods described in this specification. In some embodiments, the memory can include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), etc. or any combination thereof. In some embodiments, the memory can be a part of the processor.

[0031] The network communication mechanism can be connected to the network 130 to enable the connection of the vehicle control device 111 with external components such as the vehicle management platform 120 and the user terminal. The bus can enable the connection and / or communication between multiple components in the vehicle control device 111 (such as the processing mechanism, the braking mechanism, the vehicle lock mechanism, or the motion detection mechanism). For example, the processing mechanism can acquire motion detection data from the motion detection mechanism via the bus.

[0032] In some embodiments, the vehicle control device 111 can further include a prompting mechanism (not shown in the figure). The prompting mechanism is configured to issue a braking prompt or a vehicle lock prompt to the user before braking or locking the vehicle 110. Exemplarily, the braking mechanism includes components such as a speaker and an indicator light.

[0033] The network 130 can facilitate the information and / or data exchange between the components in the vehicle 110 (such as the vehicle control device 111) and the vehicle management platform 120. In some embodiments, the components in the vehicle 110 and the vehicle management platform 120 can be connected and / or communicate via the network 130.

[0034] In some embodiments, network 130 can be any one or more of wireless networks. For example, network 130 can include the Internet, local area network (LAN), wide area network (WAN), wireless local area network (WLAN), metropolitan area network (MAN), public switched telephone network (PSTN), Bluetooth network, ZigBee network, near field communication (NFC), etc. or any combination thereof. The network connection between various parts can be in one of the above ways or in multiple ways. In some embodiments, network 130 can be of various topological structures such as point-to-point, shared, centralized, etc. or a combination of multiple topological structures. In some embodiments, network 130 can include one or more network access points. For example, network 130 can include wired and / or wireless network access points, such as base stations and / or Internet access points, through which components in vehicle 110 and vehicle management platform 120 can be connected to network 130 to exchange data and / or information.

[0035] Vehicle management platform 120 can be used to monitor vehicle 110. For example, vehicle management platform 120 can monitor whether the user uses vehicle 110 beyond the time limit, whether the user uses vehicle 110 beyond the operating area, etc. In some embodiments, in response to the user using vehicle 110 beyond the time limit and / or the user using vehicle 110 beyond the operating area, vehicle management platform 120 can generate a lock control instruction and send it to vehicle 110 through network 130.

[0036] It should be noted that the application scenario 100 of the vehicle control device is provided only for illustrative purposes and is not intended to limit the scope of this specification. For those of ordinary skill in the art, various modifications or changes can be made according to the description of this specification. For example, the application scenario 100 of the vehicle control device can be implemented on other devices to achieve similar or different functions. However, the changes and modifications will not depart from the scope of this specification.

[0037] For example, the application scenario 100 of the vehicle control device further includes a terminal, which can communicate and / or connect with components in vehicle 110 and / or vehicle management platform 120. For example, before the processing mechanism controls the vehicle lock mechanism to lock vehicle 110, it can send a lock prompt to the user through the terminal. Also, for example, the user can control components in vehicle 110 (such as the vehicle lock mechanism, brake mechanism, etc.) through the terminal. In some embodiments, the terminal can include a mobile device, an in-vehicle display, etc. or any combination of one or more other devices with input and / or output functions.

[0038] Figure 2It is an exemplary flowchart of a vehicle control method shown in some embodiments of this specification. In some embodiments, process 200 may be executed by a processing mechanism in vehicle control device 111. For example, process 200 may be stored in a memory in the processing mechanism in the form of a program or instruction. When the processing mechanism executes the instruction, process 200 may be implemented. The operation schematic diagram of process 200 presented below is illustrative. In some embodiments, the process may be completed by using one or more additional operations not described and / or one or more operations not discussed. Additionally, Figure 2 the order of the operations of process 200 shown and described below is not restrictive.

[0039] Step 210, in response to a lock control instruction issued by the vehicle management platform, determine a braking force level and control a braking mechanism to brake the vehicle based on the braking force level.

[0040] For more information about the vehicle and the braking mechanism, reference may be made to Figure 1A and Figure 1B its related descriptions.

[0041] In some embodiments, when the vehicle usage situation meets the lock condition (for example, the user uses the vehicle for an overtime, the user uses the vehicle beyond the operation area, etc.), the vehicle management platform may generate a lock control instruction and send it to the processing mechanism in the vehicle control device through the network.

[0042] The braking force level refers to the braking intensity of the vehicle. The higher the braking force level, the faster the vehicle is braked to a stop. For example, the braking force level may include three levels: high, medium, and low. The high force level may be to directly brake the vehicle. The medium force level may be to slowly brake the vehicle. The low force level may be to perform multiple spot brakes on the vehicle.

[0043] In some embodiments, the braking force level may be a preset braking force level.

[0044] In some embodiments, in response to a lock control instruction issued by the vehicle management platform, the processing mechanism may generate a braking instruction based on the braking force level and send the braking instruction to the braking mechanism through a bus to control the braking mechanism to brake the vehicle.

[0045] In some embodiments, the processing mechanism may obtain at least one set of second data collected by at least one motion detection mechanism among a plurality of motion detection mechanisms before the braking mechanism brakes; determine the braking force level based on the at least one set of second data; and control the braking mechanism to brake the vehicle based on the braking force level. For more information about the motion detection mechanism, reference may be made to Figure 1B its related descriptions. At least one motion detection mechanism may include any one or more motion detection mechanisms among the plurality of motion detection mechanisms.

[0046] The second data refers to the data related to the movement of the vehicle before braking. For example, the second data may include the coordinate position, acceleration magnitude, speed magnitude, etc. of the vehicle within a second preset time period before the vehicle brakes. Among them, the magnitude of the second preset time period may be a default value, a preset value, etc. In some embodiments, the processing mechanism may access at least one motion detection mechanism through a bus to obtain at least one set of second data.

[0047] In some embodiments, the processing mechanism may determine whether the vehicle is in a fast movement state or a slow movement state based on the second data. When the vehicle is in a fast movement state, the braking force level may be to perform multiple spot brakes or slow braking on the vehicle. When the vehicle is in a slow movement state, the braking force level may be to directly brake the vehicle. Only by way of example, the processing mechanism may determine whether the vehicle is in a fast movement state or a slow movement state based on the second data and a second preset rule. An exemplary second preset rule may include: when the speed in the second data is greater than a second speed threshold (for example, 15 km / h), the vehicle is in a fast movement state; when the speed in the second data is less than the second speed threshold, the vehicle is in a slow movement state.

[0048] In some embodiments, in order to improve the accuracy of detecting the movement state of the vehicle, the processing mechanism may determine whether the vehicle is in a fast movement state or a slow movement state by analyzing multiple sets of second data collected by multiple motion detection mechanisms. The analysis process of multiple sets of second data is similar to the analysis process of multiple sets of first data in step 220, which will not be elaborated here.

[0049] It should be understood that when the vehicle is moving at a relatively high speed, if the vehicle is directly braked, it is easy to cause the vehicle to roll over and result in dangerous accidents. Determining the braking force level based on the second data of the vehicle and controlling the braking mechanism to brake according to the braking force level is beneficial to improving the safety during the braking process.

[0050] In some embodiments, after determining the braking force level, the processing mechanism may determine whether the environment of the vehicle meets the braking conditions based on the environmental information of the vehicle; in response to determining that the environment of the vehicle meets the braking conditions, control the braking mechanism to brake the vehicle based on the braking force level.

[0051] The environmental information refers to the information related to the environment around the vehicle. For example, the environmental information may include the road conditions around the vehicle (for example, whether there is a traffic jam), the building information around the vehicle (for example, whether there are high-rise buildings), the distance between the vehicle and the vehicle behind, the distance between the vehicle and the intersection, etc.

[0052] In some embodiments, the processing mechanism may obtain the environmental information of the vehicle through a camera and / or lidar. For example, the processing mechanism may perform image analysis on the image data collected by the camera and / or the point cloud data collected by the lidar to determine the distance between the vehicle and the vehicle behind. In some embodiments, the processing mechanism may determine the environmental information around the real-time position of the vehicle by querying an environmental information database (such as a map database) based on the real-time position of the vehicle collected by the locator. Alternatively, the processing mechanism may send the real-time position to the vehicle management platform, and the vehicle management platform queries the environmental information and then sends it to the processing mechanism.

[0053] The braking condition refers to the condition that should be met when braking the vehicle. For example, the braking condition may include that the distance between the vehicle and the intersection is greater than a first preset distance. Another example is that the distance between the vehicle and the vehicle behind is greater than a second preset distance. Among them, the first preset distance and the second preset distance may be preset values in advance, default values, etc.

[0054] In some embodiments, in response to determining that the environment of the vehicle meets the braking condition, the processing mechanism may generate a braking instruction based on the braking force level and send it to the braking mechanism to control the braking mechanism to brake the vehicle based on the braking force level. In response to determining that the environment of the vehicle does not meet the braking condition, the processing mechanism may continue to monitor the environmental information of the vehicle until it determines that the environment where the vehicle is located meets the braking condition and then brakes the vehicle based on the braking force level.

[0055] In some other embodiments, in response to the locking control instruction issued by the vehicle management platform, the processing mechanism may first monitor the environmental information of the vehicle. When it detects that the environment where the vehicle is located meets the braking condition, the processing mechanism may determine the braking force level (such as based on the current speed of the vehicle), and then control the braking mechanism to brake the vehicle based on the braking force level.

[0056] In some embodiments of this specification, determining whether the vehicle can be braked based on the environmental information of the vehicle can prevent the vehicle from being braked at positions such as intersections and viaduct entrances, affecting road traffic. At the same time, the distance from the vehicle behind is also considered before braking the vehicle to prevent a rear-end collision with the vehicle behind when braking.

[0057] Step 220, determine whether the vehicle is in a braked state.

[0058] The braked state refers to the state where the vehicle is stationary or nearly stationary after braking.

[0059] In some embodiments, the processing mechanism may obtain the speed of the vehicle through the vehicle's speedometer. In response to the vehicle's speed being 0, the vehicle is in a stopped state; in response to the vehicle's speed not being 0, the vehicle is not in a stopped state. Alternatively, in response to the vehicle's speed being less than a first speed threshold (e.g., 0.1 m / s), it may be determined that the vehicle is in a stopped state; in response to the vehicle's speed being not less than the first speed threshold, it may be determined that the vehicle is not in a stopped state. It should be understood that the processing mechanism may also determine whether the vehicle's speed is 0 or less than the first speed threshold based on data collected by other motion detection mechanisms. For example, the processing mechanism may analyze multiple frames of images collected by the image unit over a period of time to determine whether the vehicle's speed is 0 or less than the first speed threshold.

[0060] In some embodiments, to improve the accuracy of the stopped state detection, the processing mechanism may obtain multiple sets of first data collected by multiple motion detection mechanisms; and based on the multiple sets of first data, determine whether the vehicle is in a stopped state. The first data refers to data related to the motion of the vehicle after braking. For example, the first data may include the coordinate position of the vehicle, the magnitude of the acceleration, the magnitude of the speed, the surrounding image data, the surrounding point cloud data, etc. within a first preset time period after the vehicle brakes.

[0061] In some embodiments, the processing mechanism may determine whether the vehicle is in a stopped state based on multiple sets of first data through a first preset rule. The first preset rule may include various types. For example, whether the distance between the coordinate positions of the vehicle within the first preset time period is less than a third preset distance (e.g., 1 m), and whether the magnitude of the vehicle's speed within the first preset time period is less than the first speed threshold (e.g., 0.1 m / s). In response to this, it is determined that the vehicle is in a stopped state. Another example is whether the magnitude of the vehicle's speed within the first preset time period is less than the first speed threshold, and whether the magnitude of the acceleration and / or the magnitude of the angular velocity of the vehicle within the first preset time period is less than the acceleration threshold and / or the angular velocity threshold. In response to this, it is determined that the vehicle is in a stopped state.

[0062] In some embodiments, the processing mechanism may determine the initial determination result and confidence level corresponding to each motion detection mechanism, and determine whether the vehicle is in a stopped state based on the initial determination result and the confidence level. For more content about the foregoing embodiments, reference may be made to Figure 3 and its related descriptions.

[0063] Step 230, in response to determining that the vehicle is in a stopped state, control the vehicle lock mechanism to lock the vehicle.

[0064] For more content about the vehicle lock mechanism, reference may be made to Figure 1B and its related descriptions.

[0065] In some embodiments, in response to determining that the vehicle is in a stopped state, the processing mechanism may generate a locking instruction and send it to the vehicle locking mechanism via a bus to control the vehicle locking mechanism to lock the vehicle.

[0066] In some embodiments of this specification, before locking the vehicle, a braking operation is first performed on the vehicle, and after determining that the vehicle has stopped, the locking operation is performed. This can not only make the vehicle locking safer and more effective, but also avoid damage to the vehicle lock caused by locking a vehicle that is still in a moving state. On the other hand, the method in this specification can also improve the user experience and avoid injuring the user due to sudden locking during riding.

[0067] In some embodiments, before controlling the vehicle locking mechanism to lock the vehicle, the processing mechanism may send a locking prompt to the user through a prompting mechanism installed on the vehicle. There can be various ways of the locking prompt. For example, voice prompt, light prompt, etc. Correspondingly, the prompting mechanism may include a speaker, an indicator light, etc. In some other embodiments, the processing mechanism may send a locking prompt to the user through the user's terminal (such as a mobile phone).

[0068] In some embodiments, before controlling the braking mechanism to brake the vehicle, the processing mechanism may also send a braking prompt to the user through the prompting mechanism installed on the vehicle and / or the terminal. The way of the braking prompt is similar to the locking prompt.

[0069] In some embodiments of this specification, before locking or braking the vehicle, sending relevant prompts to the user to let the user know that the vehicle is about to be locked or braked can improve the safety of vehicle locking or braking and improve the user experience at the same time.

[0070] Figure 3 It is an exemplary flowchart for determining whether a vehicle is in a stopped state based on multiple sets of first data shown in some embodiments of this specification. In some embodiments, process 300 may be used to implement step 220.

[0071] In some embodiments, for each motion detection mechanism, the processing mechanism respectively executes step 311 and step 312 on it to determine the initial determination result and confidence level corresponding to the motion detection mechanism.

[0072] Step 311, based on the first data collected by the motion detection mechanism, obtain an initial determination result of whether the vehicle has stopped.

[0073] For more content about the first data, reference can be made to Figure 2 and its related descriptions.

[0074] The initial determination result refers to the determination result of whether the vehicle has stopped braking initially determined based on the data collected by a certain motion detection mechanism. For example, the initial determination result may include that the vehicle is in a braking state and the vehicle is in a non-braking state.

[0075] In some embodiments, the processing mechanism may determine whether the first data is less than its corresponding preset threshold based on the first data. In response to yes, the initial determination result is that the vehicle is in a braking state; in response to no, the initial determination result is that the vehicle is in a non-braking state. Only as an example, when the motion detection mechanism is a speedometer, the first data may include the speed magnitude of the vehicle within a first preset time period. If the speed of the vehicle within the first preset time period is less than the first speed threshold, the initial determination result is that the vehicle is in a braking state. Another example is that when the motion detection mechanism is a camera, the first data may include multiple frame image data collected by the vehicle within a first preset time period. The processing mechanism may analyze the differences between the multiple frame image data to determine whether the differences are less than the image difference threshold. If the analysis result is that the differences are less than the image difference threshold, the initial determination result is that the vehicle is in a braking state.

[0076] Step 312: Determine the confidence level of the motion detection mechanism based on the motion information and / or environmental information of the vehicle.

[0077] For more content about environmental information, reference can be made to Figure 2 and its related descriptions.

[0078] Motion information refers to information related to the motion of the vehicle. For example, motion information may include the magnitude of the vehicle's acceleration, speed magnitude, etc. In some embodiments, the processing mechanism may obtain the motion information of the vehicle by accessing a specific motion detection mechanism (such as an accelerometer, gyroscope, etc.).

[0079] The confidence level reflects the reliability of the first data collected by the motion detection mechanism and the reliability of the initial determination result determined based on the first data. In some embodiments, the confidence level may be represented by a real number. The larger the value, the higher the reliability of the first data collected by the motion detection mechanism and the higher the reliability of the initial determination result determined based on the first data. In some embodiments, the confidence levels of multiple motion detection mechanisms are all within the range of 0-1. In some embodiments, the sum of the confidence levels of multiple motion detection mechanisms is 1.

[0080] In some embodiments, the processing mechanism may determine the confidence level of the motion detection mechanism based on the motion information and / or environmental information of the vehicle through a third preset rule. The third preset rule may include multiple types. For example, when the vehicle is traveling at night, the clarity and reliability of the image data obtained by the camera are relatively low. Therefore, the third preset rule may include that in response to the brightness of the vehicle's surrounding environment being less than the brightness threshold, the confidence level corresponding to the camera is set to be relatively small. Another example is that when the vehicle is traveling at a relatively high speed, it is difficult for the locator to obtain the real-time position of the vehicle, and the clarity of the image data obtained by the camera is also relatively low. Therefore, the third preset rule may include that in response to the vehicle's speed being greater than the third speed threshold (for example, 20 kilometers per hour), the confidence level corresponding to the locator and / or the camera is set to be relatively small. Still another example is that when there are high-rise buildings in the vehicle's surrounding environment, it is easy to block the positioning signal of the locator, resulting in a relatively low reliability of the real-time position of the vehicle determined by the locator. Therefore, the third preset rule may include that in response to the presence of high-rise buildings around the vehicle, the confidence level corresponding to the locator is set to be relatively small.

[0081] After the processing mechanism determines the initial determination result and the confidence level corresponding to each motion detection mechanism, the processing mechanism may execute step 320 to determine whether the vehicle is in a braking state.

[0082] Step 320: Based on the initial determination result and the confidence level corresponding to each motion detection mechanism, determine whether the vehicle is in a braking state.

[0083] In some embodiments, the processing mechanism may assign values to the initial determination results corresponding to the motion detection mechanisms. For example, the processing mechanism may assign a value of -1 to the initial determination result that the vehicle is in a braking state; the processing mechanism may assign a value of 1 to the initial determination result that the vehicle is in a non-braking state. The processing mechanism may obtain a summation value through weighted summation based on the assigned values of the initial determination results and the confidence levels corresponding to each motion detection mechanism. In response to the summation value being positive, it is determined that the vehicle is in a non-braking state; in response to the summation value being negative, it is determined that the vehicle is in a braking state. Only as an example, the initial determination results and the confidence levels corresponding to multiple motion detection mechanisms are respectively: the vehicle is in a braking state (assigned a value of -1), with a confidence level of 0.4; the vehicle is in a braking state (assigned a value of -1), with a confidence level of 0.5; the vehicle is in a non-braking state (assigned a value of 1), with a confidence level of 0.1. Then the summation value calculated by the processing mechanism is -1×0.4 + -1×0.5 + 1×0.1 = -0.8. In response to the summation value -0.8 being negative, it is determined that the vehicle is in a braking state.

[0084] In some embodiments, the processing mechanism may process the initial determination result and the confidence level corresponding to each motion detection mechanism through a braking determination model to determine whether the vehicle is in a braking state.

[0085] The braking determination model can be a machine learning model for determining whether a vehicle is in a braking state. For example, the braking determination model can be a Deep Neural Network (DNN) model. In some embodiments, the input of the braking determination model can include the initial determination result and confidence level corresponding to each motion detection mechanism; the output can include a determination result indicating whether the vehicle is in a braking state.

[0086] In some embodiments, the braking determination model can be trained with multiple labeled training samples. The training samples can include the sample initial determination results and sample confidence levels corresponding to the sample motion detection mechanisms of the sample vehicle. The label can include the sample determination result indicating whether the sample vehicle corresponding to this set of training samples is in a braking state. In some embodiments, the training samples and labels can be obtained based on historical data. For example, multiple training samples can be input into an initial braking determination model, and the value of the loss function can be determined based on the label and the output of the initial braking determination model. The parameters of the initial braking determination model can be iteratively updated based on the loss function. When the iterative preset condition is met, the model training is completed, and a trained braking determination model is obtained. Among them, the iterative preset condition can be that the loss function converges, the number of iterations reaches a threshold, etc.

[0087] In some embodiments of this specification, by synthesizing the initial determination result and confidence level corresponding to each motion detection mechanism to determine whether the vehicle is in a braking state, the influence of multiple factors can be considered simultaneously, and the determination of whether the vehicle is in a braking state is more accurate.

[0088] In some embodiments, the processing mechanism can determine the confidence level of each motion detection mechanism based on the motion information and / or environmental information of the vehicle; determine at least one target motion detection mechanism from multiple motion detection mechanisms based on the confidence level of each motion detection mechanism; and determine whether the vehicle is in a braking state based on at least one set of first data collected by the at least one target motion detection mechanism.

[0089] In some embodiments, the processing mechanism can determine the confidence level of each motion detection mechanism by performing step 312 based on the motion information and / or environmental information of the vehicle.

[0090] The target motion detection mechanism refers to the motion detection mechanism selected for determining whether the vehicle is in a braking state. In some embodiments, the processing mechanism can sort the confidence levels in descending order, select the confidence levels greater than the confidence level threshold, and determine the motion detection mechanisms corresponding to the selected confidence levels as the target motion detection mechanisms. The processing mechanism can access the target motion detection mechanisms through a bus to obtain the first data corresponding to the target motion detection mechanisms.

[0091] The process of determining whether the vehicle is in a braking state based on at least one set of first data collected by at least one target motion detection mechanism is similar to the process of determining whether the vehicle is in a braking state based on multiple sets of first data in step 220, and will not be elaborated here.

[0092] In some embodiments of the present specification, first, a motion detection mechanism with a relatively high confidence level is selected as the target motion detection mechanism, and then based on the first data of the target motion detection mechanism, it is determined whether the vehicle is in a braking state, which can reduce the amount of data for calculation while ensuring the accuracy of the judgment result, and is conducive to shortening the calculation time.

[0093] In some embodiments, the multiple motion detection mechanisms at least include a first motion detection mechanism with a first priority and a second motion detection mechanism with a second priority, and the first priority is higher than the second priority.

[0094] The priority reflects the importance of the motion detection mechanism. The first priority is higher than the second priority, indicating that the importance of the first motion detection mechanism with the first priority is greater than that of the second motion detection mechanism with the second priority. In some embodiments, the types of motion detection mechanisms corresponding to the first motion detection mechanism and the second motion detection mechanism can be default types, preset types, etc. For example, for multiple motion detection mechanisms, it is possible to more simply and accurately determine whether the vehicle is in a braking state based on the first data obtained by the locator and the speedometer, while the accuracy of determining whether the vehicle is in a braking state based on the first data obtained by the camera and the mechanical radar is lower, and the required amount of calculation is also larger. Therefore, the locator and the speedometer can be the first motion detection mechanism; the camera and the mechanical radar can be the second motion detection mechanism.

[0095] The processing mechanism can obtain an initial result of whether the vehicle is in a braking state based on the first data corresponding to the first motion detection mechanism; in response to the initial result indicating that the vehicle is not in a braking state, it is determined that the vehicle is not in a braking state; in response to the initial result indicating that the vehicle is in a braking state, the initial result is verified based on the first data corresponding to the second motion detection mechanism.

[0096] In some embodiments, the process of obtaining the initial result of whether the vehicle is in a braking state based on the first data corresponding to the first motion detection mechanism is similar to the process of determining whether the vehicle is in a braking state based on multiple sets of first data in step 220, and will not be elaborated here.

[0097] In some embodiments, in response to the initial result indicating that the vehicle is in a stopped state, the processing mechanism may determine whether the vehicle is in a stopped state based on the first data corresponding to the second motion detection mechanism. If the response is affirmative, it is determined that the vehicle is in a stopped state. The process of determining whether the vehicle is in a stopped state based on the first data corresponding to the second motion detection mechanism is similar to the process of determining whether the vehicle is in a stopped state based on multiple sets of first data in step 220, and will not be elaborated here again.

[0098] In some embodiments of this specification, the multiple motion detection mechanisms are sorted by priority, and only the first data collected by the first motion detection mechanism with the highest priority is used for judgment, which is beneficial to reducing the amount of calculation and shortening the calculation time. When the initial result indicates that the vehicle is in a stopped state, the first data collected by the second motion detection mechanism with the second priority is further used for verification, which can further improve the accuracy of the judgment, prevent locking when the vehicle is not in a stopped state, and is beneficial to improving the safety during the locking process.

[0099] In some embodiments, step 312 may be omitted, and the processing mechanism may directly determine whether the vehicle is in a stopped state based on the initial determination results corresponding to the multiple motion detection mechanisms. For example, the processing mechanism may count the number of initial determination results corresponding to the multiple motion detection mechanisms where the initial determination result is that the vehicle is in a stopped state and the number of initial determination results where the vehicle is not in a stopped state, and determine whether the vehicle is in a stopped state based on the initial determination result with the largest number.

[0100] It should be noted that the above descriptions of processes 200 and 300 are only for illustration and explanation, and do not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to processes 200 and 300 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0101] One or more embodiments of this specification provide a computer-readable storage medium, and the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a vehicle control method as described in any one of the above embodiments.

[0102] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are proposed in this specification, so such modifications, improvements, and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0103] Meanwhile, this specification uses specific terms to describe the embodiments of this specification. Terms such as "an embodiment", "one embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0104] Moreover, unless clearly stated in the claims, the order of the processing elements and sequences, the use of numerical and alphabetical characters, or the use of other names in this specification are not used to limit the order of the processes and methods in this specification. Although various examples are discussed in the above disclosure for some currently useful embodiments of the invention, it should be understood that such details are for illustrative purposes only. The appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on existing servers or mobile devices.

[0105] Similarly, it should be noted that, in order to simplify the presentation of the disclosure in this specification and thus help the understanding of one or more embodiments of the invention, in the previous description of the embodiments of this specification, sometimes multiple features are grouped into one embodiment, drawing, or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than those mentioned in the claims. In fact, the features of the embodiments are fewer than all the features of the individual embodiments disclosed above.

[0106] In some embodiments, numbers are used to describe the components and the quantity of attributes. It should be understood that such numbers used to describe the embodiments are modified by the modifiers "about", "approximate", or "substantially" in some examples. Unless otherwise stated, "about", "approximate", or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and these approximate values can change according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of this specification to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are made as precise as possible within the feasible range.

[0107] For each patent, patent application, patent application publication, and other materials cited in this specification, such as articles, books, specifications, publications, documents, etc., their entire contents are hereby incorporated by reference into this specification. This excludes the application history files that are inconsistent with or conflict with the content of this specification, as well as the files that limit the broadest scope of the claims of this specification (currently or subsequently appended to this specification). It should be noted that if there are any inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the supplementary materials of this specification and the content described in this specification, the descriptions, definitions, and / or uses of terms in this specification shall prevail.

[0108] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be regarded as consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A vehicle control device, characterized in that, The device includes: A braking mechanism configured to brake the vehicle; A vehicle lock mechanism configured to unlock or lock the vehicle; A processing mechanism communicatively connected to the braking mechanism and the vehicle lock mechanism, and the processing mechanism is configured to: In response to a lock control instruction issued by a vehicle management platform, determine a braking force level and control the braking mechanism to brake the vehicle based on the braking force level; Determine whether the vehicle is in a stopped state; and In response to determining that the vehicle is in a stopped state, control the vehicle lock mechanism to lock the vehicle.

2. The device according to claim 1, characterized in that, The device further includes a plurality of motion detection mechanisms. Determining whether the vehicle is in a stopped state includes: Obtaining multiple sets of first data collected by the plurality of motion detection mechanisms; and Based on the multiple sets of first data, determining whether the vehicle is in a stopped state.

3. The device according to claim 2, characterized in that, The plurality of motion detection mechanisms at least includes multiple of a locator, an accelerometer, a gyroscope, a speedometer, a camera, and a lidar.

4. The device according to claim 2, characterized in that Based on the multiple sets of first data, determining whether the vehicle is in a stopped state includes: For each motion detection mechanism, Based on the first data collected by the motion detection mechanism, obtaining an initial determination result of whether the vehicle is stopped; Based on the motion information and / or environmental information of the vehicle, determining the confidence level of the motion detection mechanism; Based on the initial determination result and the confidence level corresponding to each motion detection mechanism, determining whether the vehicle is in a stopped state.

5. The device according to claim 2, characterized in that, The plurality of motion detection mechanisms at least includes a first motion detection mechanism of a first priority and a second motion detection mechanism of a second priority, and the first priority is higher than the second priority. Based on the multiple sets of first data, determining whether the vehicle is in a stopped state includes: Based on the first data corresponding to the first motion detection mechanism, obtaining an initial result of whether the vehicle is in a stopped state; In response to the initial result being that the vehicle is in a non-stopped state, determining that the vehicle is in a non-stopped state; In response to the initial result being that the vehicle is in a stopped state, verifying the initial result based on the first data corresponding to the second motion detection mechanism.

6. The device according to claim 1, characterized in that, The device further includes a plurality of motion detection mechanisms. Determining the braking force level and controlling the braking mechanism to brake the vehicle based on the braking force level includes: Obtaining at least one set of second data collected by at least one motion detection mechanism among the plurality of motion detection mechanisms before the braking mechanism brakes; Based on the at least one set of second data, determining the braking force level; and Controlling the braking mechanism to brake the vehicle based on the braking force level.

7. The device according to claim 6, characterized in that, Controlling the braking mechanism to brake the vehicle includes: Based on the environmental information of the vehicle, determining whether the environment where the vehicle is located meets the braking conditions; In response to determining that the environment where the vehicle is located meets the braking conditions, controlling the braking mechanism to brake the vehicle based on the braking force level.

8. The device according to claim 1, characterized in that The processing mechanism is further configured to: Before controlling the vehicle lock mechanism to lock the vehicle, a locking prompt is sent to the user through a terminal or a prompting mechanism installed on the vehicle.

9. A vehicle control method, characterized in that, The method is executed by a processing mechanism and includes: In response to a locking control instruction issued by a vehicle management platform, determining a braking force level and controlling a braking mechanism to brake the vehicle based on the braking force level; Determining whether the vehicle is in a stopped state; and In response to determining that the vehicle is in a stopped state, controlling the vehicle lock mechanism to lock the vehicle.

10. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions, and when a computer reads the computer instructions in the storage medium, the computer executes a vehicle control method as described in claim 9.

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