Anti-collision early warning method and device, electronic equipment and readable storage medium

Abstract

The invention provides an anti-collision early warning method and device, electronic equipment and a readable storage medium, and the method comprises the steps: receiving first state information sent by a target vehicle, the first state information comprising a vehicle identifier, first position information, first speed information and first direction information of the target vehicle; determining second state information of the intelligent wearable device, wherein the second state information comprises second position information, second speed information and second direction information of the intelligent wearable device; determining a collision probability level according to the first state information and the second state information; according to the collision probability level, multi-dimensional early warning reminding corresponding to the collision probability level is generated, and the multi-dimensional early warning reminding comprises display information reminding of the first dimension, sound information reminding of the second dimension and touch information reminding of the third dimension. According to the technical scheme provided by one or more embodiments, the intelligent wearable device can be used for reminding pedestrians to avoid the vehicle collision risk in time.

Description

Technical Field

[0001] The present disclosure relates to the technical field of wearable intelligent devices, and in particular to an anti-collision warning method, device, electronic device and readable storage medium. Background Art

[0002] With the acceleration of urbanization and the surge in the number of motor vehicles, the complexity of urban traffic is also increasing. The complex traffic conditions not only increase the degree of road congestion, but also increase the incidence of traffic accidents, posing a severe challenge to road traffic safety. In addition, with the emergence of new business forms, such as the rapid development of express delivery and food delivery, the number of traffic accidents involving electric bicycles is also rising, further increasing the complexity of traffic safety management.

[0003] Vehicle blind spots refer to areas that cannot be directly observed by the driver in the normal driving position due to the limitations of the vehicle structure. These blind spots are particularly dangerous when the vehicle is starting, changing lanes, overtaking, etc., because pedestrians and cyclists may be in the driver's blind spot, increasing the risk of traffic accidents.

[0004] Pedestrians and cyclists often face more blind spots. The sudden appearance of vehicles in the blind spots can catch pedestrians and cyclists off guard, which can easily lead to threats to property and health. Therefore, the safety of pedestrians and cyclists on the road needs more attention and protection. Summary of the invention

[0005] In view of this, one or more embodiments of the present disclosure provide a collision avoidance warning method, device, electronic device and readable storage medium, which can use smart wearable equipment to promptly remind pedestrians to avoid vehicle collision risks.

[0006] On the one hand, the present disclosure provides an anti-collision warning method, which is applied to a smart wearable device, and the method includes: receiving first state information sent by a target vehicle, the first state information including a vehicle identification, first position information, first speed information and first direction information of the target vehicle; determining second state information of the smart wearable device, the second state information including second position information, second speed information and second direction information of the smart wearable device; determining a collision probability level according to the first state information and the second state information; and generating a multi-dimensional warning reminder corresponding to the collision probability level according to the collision probability level, the multi-dimensional warning reminder including a display information reminder of a first dimension, a sound information reminder of a second dimension and a tactile information reminder of a third dimension.

[0007] On the other hand, the present disclosure also provides an anti-collision warning device, which is applied to a smart wearable device, and the device includes: a receiving unit, used to receive first status information sent by a target vehicle, the first status information including a vehicle identification, first position information, first speed information and first direction information of the target vehicle; an acquisition unit, used to determine second status information of the smart wearable device, the second status information including second position information, second speed information and second direction information of the smart wearable device; an information processing unit, used to determine a collision probability level according to the first status information and the second status information; and a warning unit, used to generate a multi-dimensional warning reminder corresponding to the collision probability level according to the collision probability level, the multi-dimensional warning reminder including a display information reminder of a first dimension, a sound information reminder of a second dimension and a tactile information reminder of a third dimension.

[0008] On the other hand, the present disclosure further provides an electronic device, which includes a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the above-mentioned anti-collision warning method is implemented.

[0009] On the other hand, the present disclosure further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned anti-collision warning method is implemented.

[0010] The technical solution provided by one or more embodiments of the present disclosure can utilize a smart wearable device to receive vehicle status information. After combining the status information of the smart wearable device itself, the smart wearable device can determine the collision probability level and form corresponding warning information. On the one hand, by utilizing the information processing capabilities of the smart wearable device, an accurate collision probability level can be provided in a timely manner. On the other hand, by utilizing the rich extended functions of the smart wearable device, various forms of warning information can be provided to increase the effectiveness and flexibility of the warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The features and advantages of the embodiments of the present disclosure will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present disclosure in any way. In the accompanying drawings:

[0012] Figure 1 A schematic diagram showing the steps of an anti-collision warning method in one embodiment of the present disclosure is shown;

[0013] Figure 2 A schematic diagram of an arrow display screen of a smart bracelet in one embodiment of the present disclosure is shown;

[0014] Figure 3 A schematic diagram of a process flow of an anti-collision warning method in one embodiment of the present disclosure is shown;

[0015] Figure 4 A schematic diagram of determining the distance between a user and a car in one embodiment of the present disclosure is shown;

[0016] Figure 5 A schematic diagram of functional units of an anti-collision warning device in one embodiment of the present disclosure is shown;

[0017] Figure 6 A schematic structural diagram of an electronic device in one embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0019] See also Figure 1 An anti-collision warning method provided in an embodiment of the present disclosure can be applied to smart wearable devices and may include the following steps.

[0020] S1: receiving first status information sent by a target vehicle, where the first status information includes a vehicle identification, first position information, first speed information and first direction information of the target vehicle.

[0021] In this embodiment, the smart wearable device may be an electronic device with data processing capabilities, such as a watch, glasses, bracelet, earphone, etc. The smart wearable device usually has connectivity, can be connected to the Internet, can be connected to other devices such as smart phones and smart cars through Bluetooth, Wi-Fi, etc., and can receive data sent by other devices.

[0022] In this embodiment, the vehicle can actively send the first state information to the outside, and can send it to the outside in the form of broadcast, Bluetooth, or wireless network (wifi). The smart wearable device can receive these state information. Among them, the first state information may include a vehicle identification to distinguish different vehicles. The vehicle identification can also reflect information such as the vehicle model. The first state information may include first position information. The first position information may be the current position of the vehicle, or it may be the historical position data of the vehicle, which can be obtained by the vehicle through the vehicle-mounted global positioning system. The first state information may include first speed information. The first speed information may be the current speed of the vehicle, or it may be the historical speed data of the vehicle. The first state information may include first direction information. The first direction information may be the current driving direction of the vehicle, or it may be the historical driving direction of the vehicle.

[0023] In this embodiment, by receiving the first status information sent by the vehicle, the smart wearable device can accurately perceive the surrounding vehicle information, thereby providing some early warning information.

[0024] It should be noted that some practical application scenarios of the present method may be: the wearable smart device and the target vehicle determine the communication protocol in advance, so that the smart wearable device can obtain the first state information sent by the target vehicle on the road.

[0025] In a practical application example, a smart wearable device can use Bluetooth communication to obtain the first status information of a vehicle. The transmission distance of Bluetooth is usually about 10 meters, but in some cases, after enhancing the radio frequency power, it can reach 100 meters or even farther. In this application example, a Bluetooth device with enhanced radio frequency power can be selected to establish Bluetooth communication, thereby ensuring the effect of warning the sudden appearance of a vehicle within a short distance. This short distance is generally within a range of 100 meters or 50 meters, which can allow pedestrians or cyclists to notice that there are vehicles that are about to suddenly travel around.

[0026] In some embodiments, the target vehicle is a vehicle equipped with a Bluetooth child, and the default state of the Bluetooth child is an on state. The Bluetooth mother body in the smart wearable device can detect the Bluetooth child body in a preset spatial area. If the Bluetooth child body is detected, a Bluetooth communication connection is established between the Bluetooth mother body and the Bluetooth child body. Based on the Bluetooth communication connection, the smart wearable device can receive the first state information sent by the target vehicle.

[0027] Specifically, considering that Bluetooth applications can realize not only the usual one-to-one applications, but also one-to-many applications. For example, instead of using the fixed-point matching function of Bluetooth, the surrounding information broadcasting function of Bluetooth is used. In this way, as long as the Bluetooth parent device can scan the matching Bluetooth child device, information exchange and transmission can be carried out.

[0028] Bluetooth technology can improve anti-interference ability and transmission efficiency through adaptive frequency hopping and small data packet design, which makes it possible to maintain good communication quality even in complex environments, and is more suitable for the complex traffic scenarios considered in this disclosure.

[0029] In some embodiments, the first state information actively sent by the vehicle to the outside may include the vehicle's motion state, that is, whether the vehicle is moving or stopped. For vehicles in a stopped state, no collision warning may be performed, and the warning level of the warning reminder information may be reduced. The vehicle's motion state may not require map data or specific vehicle applications, and may be determined through some vehicle sensor information. For example, engine heat may indicate that the vehicle is in a moving state. For example, tire rotation may also indicate that the vehicle is in a moving state.

[0030] S2: Determine second state information of the smart wearable device, where the second state information includes second position information, second speed information, and second direction information of the smart wearable device.

[0031] In this embodiment, the smart wearable device can use pre-integrated sensors, such as accelerometers, gyroscopes, etc., to determine the movement speed information and movement direction information to obtain the second speed information and the second direction information. The second speed information can be the current moving speed of the smart wearable device, or it can be the historical speed data of the smart wearable device. The second direction information can be the current moving direction of the smart wearable device, or it can be the historical moving direction of the smart wearable device. The smart wearable device can integrate the global positioning system function to determine its own positioning information and obtain the second position information. The second position information can be the current position of the smart wearable device, or it can be the historical positioning data of the smart wearable device.

[0032] S3: Determine a collision probability level according to the first state information and the second state information.

[0033] In this embodiment, the smart wearable device can comprehensively analyze the first state information and the second state information to determine the collision probability level. The smart wearable device can be connected to the network or the cloud to enhance computing power and determine the collision probability level. The smart wearable device can determine the collision probability level according to preset rules or pre-trained machine learning models. The smart wearable device can determine a customized and optimized collision probability level based on the user characteristics of the user and the vehicle characteristics of the target vehicle.

[0034] In some embodiments, the vehicle motion trajectory of the target vehicle can be determined based on the first position information, the first speed information, and the first direction information. The device motion trajectory of the smart wearable device can be determined based on the second position information, the second speed information, and the second direction information. Based on the vehicle motion trajectory and the device motion trajectory, a collision probability level can be determined. For example, if there is a possibility that two motion trajectories cross quickly, a high-level collision probability level can be determined; if the time node when the two motion trajectories complete the intersection is far away or there is no intersection, a low-level collision probability level can be determined.

[0035] In a practical application example, based on the first direction information, the historical movement direction of the target vehicle within a first predetermined period (e.g., 1 second) can be determined. When the historical movement direction of the vehicle does not trigger a reverse driving condition (that is, the movement direction is opposite within the first predetermined period), the historical movement direction of the vehicle can be determined as the predicted movement direction of the vehicle. Based on the predicted movement direction of the vehicle, the first position information, and the first speed information, the vehicle movement trajectory can be determined.

[0036] In a practical application example, the historical movement direction of the smart wearable device within the second predetermined period (e.g., 1 second) can be determined based on the second direction information. When the historical movement direction of the device does not trigger the reverse movement condition (that is, the movement direction is opposite within the first predetermined period), the historical movement direction of the device can be determined as the predicted movement direction of the device. Based on the predicted movement direction of the device, the second position information, and the second speed information, the movement trajectory of the device can be determined.

[0037] In some embodiments, the spatial straight-line distance between the target vehicle and the smart wearable device can be determined based on the first position information and the second position information. The collision probability level can be determined based on the comparison result of the spatial straight-line distance and a preset safety distance (e.g., 5 meters, 10 meters, etc.).

[0038] In some embodiments, a reference probability level may be determined based on the first position information, the first speed information, the first direction information, the second position information, the second speed information, and the second direction information. A collision avoidance coefficient of the target vehicle may be determined based on the vehicle identification. A collision probability level may be determined based on the reference probability level and the collision avoidance coefficient.

[0039] Specifically, based on the vehicle identification, the vehicle characteristics can be determined, such as the vehicle's weight, volume, brake sensitivity, whether it has an onboard collision avoidance system, etc. In this way, based on the characteristic parameters of the vehicle, the collision avoidance coefficient can be determined to correct the baseline probability level and obtain the collision probability level. The collision probability level can be more customized and more in line with the specific characteristics of the user, ensuring that the generated warning information is more accurate and effective.

[0040] In some embodiments, when determining the collision probability level, the user characteristic information (such as age, gender, height, physical signs, current heart rate value, etc.) authorized by the user collected or stored by the smart wearable device can be used to correct the generation result of the collision probability level, so that the final collision probability level is more customized and more in line with the specific characteristics of the user, thereby making the generated warning information more accurate and effective.

[0041] S4: Generate a multi-dimensional warning reminder corresponding to the collision probability level according to the collision probability level, wherein the multi-dimensional warning reminder includes a display information reminder of a first dimension, a sound information reminder of a second dimension, and a tactile information reminder of a third dimension.

[0042] In this embodiment, the multi-dimensional warning information ensures the reliability of the warning information and meets various practical application scenarios. For example, sometimes the user sees the display information reminder, and sometimes does not see it. The user can still be reminded in time through the sound information reminder and the tactile information reminder. For another example, sometimes the user is in a noisy environment and does not hear the sound information reminder. The tactile information reminder combined with the real information reminder can still effectively remind the user. Multi-dimensional warning reminders enable smart wearable devices to provide users with comprehensive warning reminders to ensure that users are informed of warning information in a timely manner.

[0043] In this embodiment, the smart wearable device can be equipped with a small OLED or LCD screen. When there is a warning message, the screen will light up and display the warning information content, which can be a display information reminder in the form of text, pattern, symbol, etc. The display information reminder can distinguish the warning information corresponding to different collision probability levels through different icons, colors or display frequencies.

[0044] In this embodiment, the smart wearable device may be built with a micro speaker, and when there is an early warning message, the micro speaker may emit a sound, which may be a simple beep, a specific ringtone, a voice prompt, etc. Users can set different volume levels according to their needs and environment to ensure that they can hear the voice information reminder when needed.

[0045] In this embodiment, the smart wearable device may be equipped with a vibration motor, and when there is an early warning message, the vibration motor may vibrate to provide a tactile information reminder. The intensity and pattern of the vibration may be adjusted according to the user's preferences to suit different usage scenarios and personal needs.

[0046] In a practical application example, the smart wearable device can be a smart bracelet. Figure 2 When applying the anti-collision warning method disclosed in the present invention, the smart bracelet can develop an arrow display function, a vibration function, an information receiving module and an information processing module.

[0047] Specifically, when the bracelet wearer is walking or riding on the road, a car may suddenly appear on the left or right. Using the arrow display function, the arrow on the left can indicate that a car is coming from the left, and the arrow on the right can indicate that a car is coming from the right. Different arrow display frequencies can represent different levels of danger. When the arrow is displayed at a low frequency, it can represent that a car is coming slowly, indicating that the user is in a low level of danger in the current scenario. When the arrow is displayed at a high frequency, it can represent that a car is coming quickly, indicating that the user is in a high level of danger in the current scenario.

[0048] Corresponding to the two modes of arrow display, the vibration function can achieve fast vibration and slow vibration. Slow vibration corresponds to low frequency of arrow display, and the user's risk level is low. Fast vibration corresponds to high frequency of arrow display, and the user's risk level is high. By setting the two modes of arrow display and vibration, users can get warning information through the vibration of the bracelet when they do not see the warning information represented by the arrow display.

[0049] The information receiving module and information processing module of the wristband correspond to the communication function and information processing function of the wristband respectively. The wristband can process the information sent from the vehicle, so as to determine which direction the vehicle is coming from and how fast it is. Furthermore, the wristband can determine the frequency of the arrow display and the speed of vibration.

[0050] It is worth noting that the target vehicle of the present disclosure can be one or more vehicles, and the corresponding multi-dimensional warning reminder can be for one or more vehicles. According to different actual application scenarios, if it is difficult for the smart wearable device to provide multi-dimensional warning reminders for multiple vehicles at the same time, the target vehicle closest to the smart wearable device can be determined as the warning vehicle, and only the multi-dimensional warning reminder corresponding to the warning vehicle can be provided on the smart wearable device.

[0051] An anti-collision warning method provided in one embodiment of the present disclosure can be applied to a smart bracelet.

[0052] First of all, the smart bracelet can receive the vehicle status information sent by the vehicle. Specifically, the vehicle can determine whether it is in driving or stationary state. As long as the speed of the vehicle is greater than 0, the vehicle can be determined to be in driving state for the next 3s. It is not until it stops and then delays for another 3s that the vehicle can be determined to be stationary. When the vehicle is in driving state, the speed range can be further determined. For example, if the speed of the vehicle is greater than 0 and less than or equal to 2m / s, it is a low-speed range. If the speed of the vehicle is greater than 2m / s, it is a high-speed range. The vehicle also needs to locate its own position information. The vehicle status information sent by the vehicle to the bracelet may include vehicle speed, positioning coordinates and vehicle number (each vehicle can be numbered separately to prevent vehicle confusion).

[0053] Secondly, the smart bracelet can determine the direction of the user's movement, and can determine the direction of movement of the smart bracelet based on the direction of the user's movement two seconds before and after the movement. The smart bracelet can simultaneously receive vehicle status information of surrounding vehicles in real time. After receiving the vehicle status information, the smart bracelet can determine the distance between the vehicle and the person based on the vehicle positioning information in the vehicle status information. Once the distance is less than 5m and the current vehicle speed is high, a high-risk level warning can be triggered. The smart bracelet will display a high-frequency red arrow and vibrate violently. In other cases, it indicates a low-risk level warning. The smart bracelet can display a very low-frequency green arrow and vibrate slightly.

[0054] In some practical application scenarios, the arrow display colors of the smart bracelet end can be divided into green and red, green represents no danger, and red represents danger. The arrow display frequency of the smart bracelet end can be divided into low display frequency and high display frequency, low display frequency represents no danger, and high display frequency represents danger. The frequency value of the high display frequency and the frequency value of the low display frequency can present a multiple relationship with distinguishing degree. For example, the low display frequency of the arrow on the smart bracelet end can be 20Hz, and the high display frequency can be 1KHz. The vibration frequency of the smart bracelet end can be divided into low vibration frequency and high vibration frequency, low vibration frequency represents no danger, and high vibration frequency represents danger. The frequency value of the high vibration frequency and the frequency value of the low vibration frequency can present a multiple relationship with distinguishing degree. For example, a slight vibration of the smart bracelet end can be a vibration of 3s, and a severe vibration can be a vibration of 3 times in 1s.

[0055] See also Figure 3 , an anti-collision warning method provided in one embodiment of the present disclosure may include the following process.

[0056] After the vehicle determines the direction of the vehicle, it sends the vehicle information to the smart wearable device. After the smart wearable device determines the direction of the user, it can combine the vehicle information for fusion analysis to determine the current distance between the user and the vehicle. As long as the current distance reaches the preset distance limit requirement, the corresponding function warning can be performed on the smart wearable device. In this way, pedestrians or cyclists can detect potential collision hazards in time.

[0057] The direction of a pedestrian or cyclist can be determined by the direction of the individual's movement 1 second before and after. Once the movement starts, it can be assumed that the same direction is maintained for 3 seconds, unless reverse travel is triggered (that is, the movement direction is opposite 1 second before and after). The same is true for the direction of the car.

[0058] See also Figure 4The distance between the user and the car can be determined not by the intersection distance on the path, but by the straight-line distance in space. As long as the straight-line distance in space reaches the warning requirement, a warning message will be generated. The distance limit requirement for low-risk can be 10 meters, and the distance limit requirement for high-risk can be 5 meters.

[0059] In particular, if multiple vehicles appear at the same time, the nearest vehicle can be identified to find the warning vehicle with the closest linear distance in space. On this basis, it can be determined whether the distance between the person and the warning vehicle triggers the low-risk distance limit requirement or the high-risk distance limit requirement.

[0060] The technical solution provided by one or more embodiments of the present disclosure can utilize a smart wearable device to receive vehicle status information. After combining the status information of the smart wearable device itself, the smart wearable device can determine the collision probability level and form corresponding warning information. On the one hand, by utilizing the information processing capabilities of the smart wearable device, an accurate collision probability level can be provided in a timely manner. On the other hand, by utilizing the rich extended functions of the smart wearable device, various forms of warning information can be provided to increase the effectiveness and flexibility of the warning.

[0061] See also Figure 5 The present disclosure also provides an anti-collision warning device, which can be applied to a smart wearable device, and the device includes:

[0062] The receiving unit 100 is used to receive first state information sent by a target vehicle, wherein the first state information includes a vehicle identification, first position information, first speed information and first direction information of the target vehicle;

[0063] An acquisition unit 200 is used to determine second state information of the smart wearable device, where the second state information includes second position information, second speed information, and second direction information of the smart wearable device;

[0064] An information processing unit 300, configured to determine a collision probability level according to the first state information and the second state information;

[0065] The warning unit 400 is used to generate a multi-dimensional warning reminder corresponding to the collision probability level according to the collision probability level, and the multi-dimensional warning reminder includes a display information reminder in the first dimension, a sound information reminder in the second dimension, and a tactile information reminder in the third dimension.

[0066] In one embodiment, the information processing unit 300 is specifically used to determine the vehicle motion trajectory of the target vehicle based on the first position information, the first speed information and the first direction information; determine the device motion trajectory of the smart wearable device based on the second position information, the second speed information and the second direction information; and determine the collision probability level based on the vehicle motion trajectory and the device motion trajectory.

[0067] In one embodiment, the information processing unit 300 includes a first processing sub-unit 301, which is used to determine the vehicle historical movement direction of the target vehicle within a first predetermined period based on the first direction information; when the vehicle historical movement direction does not trigger a reverse driving condition, determine the vehicle historical movement direction as the vehicle predicted movement direction; based on the vehicle predicted movement direction, the first position information and the first speed information, determine the vehicle movement trajectory.

[0068] In one embodiment, the information processing unit 300 includes a second processing sub-unit 302, which is used to determine the historical movement direction of the device of the smart wearable device within a second predetermined period based on the second direction information; when the historical movement direction of the device does not trigger a reverse movement condition, the historical movement direction of the device is determined as the predicted movement direction of the device; based on the predicted movement direction of the device, the second position information and the second speed information, the movement trajectory of the device is determined.

[0069] In one embodiment, the information processing unit 300 is specifically used to determine the spatial straight-line distance between the target vehicle and the smart wearable device based on the first position information and the second position information; and determine the collision probability level based on the comparison result between the spatial straight-line distance and the preset safety distance.

[0070] In one embodiment, the information processing unit 300 is specifically used to determine a baseline probability level based on the first position information, the first speed information, the first direction information, the second position information, the second speed information and the second direction information; determine the anti-collision coefficient of the target vehicle based on the vehicle identification; and determine the collision probability level based on the baseline probability level and the anti-collision coefficient.

[0071] In one embodiment, the target vehicle is a vehicle equipped with a Bluetooth sub-body, and the default state of the Bluetooth sub-body is the on state. The receiving unit 100 is specifically used to detect the Bluetooth sub-body in a preset spatial area based on the Bluetooth mother body in the smart wearable device; if the Bluetooth sub-body is detected, a Bluetooth communication connection is established between the Bluetooth mother body and the Bluetooth sub-body; based on the Bluetooth communication connection, the first state information sent by the target vehicle is received.

[0072] Each unit described in the above embodiments may be implemented by a computer chip or a product having a certain function. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0073] For the convenience of description, the above devices are described in terms of functions and are described separately in various units. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0074] See also Figure 6 The present disclosure also provides an electronic device, which includes a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the above-mentioned anti-collision warning method is implemented.

[0075] The present disclosure also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned anti-collision warning method is implemented.

[0076] The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0077] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory, that is, implementing the method in the above method embodiment.

[0078] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0079] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0080] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0081] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0082] Although the embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A collision prevention warning method, characterized in that: The method is applied to a smart wearable device, and the method comprises: Receiving first state information sent by a target vehicle, the first state information including a vehicle identification, first position information, first speed information and first direction information of the target vehicle; Determine second state information of the smart wearable device, where the second state information includes second position information, second speed information, and second direction information of the smart wearable device; determining a collision probability level according to the first state information and the second state information; According to the collision probability level, a multi-dimensional warning reminder corresponding to the collision probability level is generated, and the multi-dimensional warning reminder includes a display information reminder of a first dimension, a sound information reminder of a second dimension, and a tactile information reminder of a third dimension.

2. The method according to claim 1, characterized in that The determining the collision probability level according to the first state information and the second state information includes: determining a vehicle motion trajectory of the target vehicle according to the first position information, the first speed information, and the first direction information; Determine a device motion trajectory of the smart wearable device according to the second position information, the second speed information, and the second direction information; The collision probability level is determined based on the vehicle motion trajectory and the device motion trajectory.

3. The method according to claim 2, characterized in that The determining the vehicle motion trajectory of the target vehicle according to the first position information, the first speed information and the first direction information includes: Determining a historical vehicle movement direction of the target vehicle within a first predetermined period according to the first direction information; When the historical movement direction of the vehicle does not trigger a reverse driving condition, determining the historical movement direction of the vehicle as the predicted movement direction of the vehicle; The vehicle motion trajectory is determined based on the vehicle predicted motion direction, the first position information and the first speed information.

4. The method according to claim 2, characterized in that: The determining, according to the second position information, the second speed information, and the second direction information, a device motion trajectory of the smart wearable device includes: Determining a historical movement direction of the smart wearable device within a second predetermined period according to the second direction information; When the historical movement direction of the device does not trigger a reverse movement condition, determining the historical movement direction of the device as the predicted movement direction of the device; The movement trajectory of the device is determined based on the predicted movement direction of the device, the second position information, and the second speed information.

5. The method according to claim 1, characterized in that The determining the collision probability level according to the first state information and the second state information includes: Determine the spatial straight-line distance between the target vehicle and the smart wearable device according to the first position information and the second position information; The collision probability level is determined according to a comparison result between the spatial straight-line distance and a preset safety distance.

6. The method according to claim 1, characterized in that The determining the collision probability level according to the first state information and the second state information includes: determining a reference probability level according to the first position information, the first speed information, the first direction information, the second position information, the second speed information, and the second direction information; Determining the anti-collision coefficient of the target vehicle according to the vehicle identification; The collision probability level is determined based on the reference probability level and the collision prevention coefficient.

7. The method according to claim 1, characterized in that The target vehicle is a vehicle installed with a Bluetooth sub-body, the default state of the Bluetooth sub-body is an on state, and the receiving of the first state information sent by the target vehicle includes: Based on the Bluetooth parent in the smart wearable device, detecting the Bluetooth child in a preset spatial area; If the Bluetooth child is detected, a Bluetooth communication connection is established between the Bluetooth parent and the Bluetooth child; Based on the Bluetooth communication connection, the first status information sent by the target vehicle is received.

8. An anti-collision warning device, characterized in that: The device is applied to a smart wearable device, and comprises: A receiving unit, configured to receive first status information sent by a target vehicle, wherein the first status information includes a vehicle identification, first position information, first speed information, and first direction information of the target vehicle; an acquiring unit, configured to determine second state information of the smart wearable device, wherein the second state information includes second position information, second speed information, and second direction information of the smart wearable device; an information processing unit, configured to determine a collision probability level according to the first state information and the second state information; The warning unit is used to generate a multi-dimensional warning reminder corresponding to the collision probability level according to the collision probability level, and the multi-dimensional warning reminder includes a display information reminder of the first dimension, a sound information reminder of the second dimension, and a tactile information reminder of the third dimension.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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