Vehicle collision warning method and device, vehicle terminal and storage medium

Abstract

The application relates to a vehicle collision warning method and device, a vehicle terminal and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring external environment information of a target vehicle; performing collision warning analysis on the external environment information based on a collision warning model to obtain an initial warning result of the target vehicle; determining a vehicle state difference between the target vehicle and a reference vehicle; and determining a target warning result of the target vehicle according to the initial warning result and the vehicle state difference. The application can not only fully consider the influence of external environment information on the target warning result of the target vehicle, but also consider the influence of the vehicle state difference between the target vehicle and the reference vehicle on the target warning result of the target vehicle, so that the target warning result can be more in line with the actual situation of the target vehicle.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to a vehicle collision warning method, device, vehicle terminal, and storage medium. Background Technology

[0002] With the increasing popularity of automobiles, the number of cars produced and put into construction each year is increasing, which also leads to a higher probability of traffic accidents. To reduce the probability of traffic accidents, vehicle collision warning systems can be installed on cars to avoid them.

[0003] In existing technologies, collision warning systems detect the distance between the vehicle ahead and the target vehicle, and then determine whether the distance meets the braking distance of the target vehicle. Based on the judgment result, a collision warning is issued to the target vehicle. However, the accuracy of collision warnings for target vehicles in existing technologies is low, and they cannot effectively avoid traffic accidents. Summary of the Invention

[0004] Therefore, it is necessary to provide a vehicle collision warning method, device, vehicle terminal, and storage medium that can improve the accuracy of vehicle collision warning in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a vehicle collision warning method. The method includes:

[0006] Obtain information about the external environment of the target vehicle;

[0007] Based on the collision warning model, the external environment information is analyzed for collision warning to obtain the initial warning result of the target vehicle; wherein, the collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0008] Determine the differences in vehicle state between the target vehicle and the reference vehicle;

[0009] Based on the initial warning result and the difference in vehicle status, the target warning result for the target vehicle is determined.

[0010] In one embodiment, determining the vehicle state difference between the target vehicle and the reference vehicle includes:

[0011] Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record;

[0012] Based on the recording time of each historical braking record, the target braking record is determined from each historical braking record;

[0013] Based on the target braking record, the target vehicle status is determined;

[0014] Based on the target vehicle state and the reference vehicle state of the reference vehicle, the difference in vehicle state between the target vehicle and the reference vehicle is determined.

[0015] In one embodiment, determining the target vehicle state based on the target braking record includes:

[0016] Determine the braking distance and starting speed corresponding to the target braking record;

[0017] Based on the braking distance and the starting speed corresponding to the target braking record, the state of the target vehicle is predicted to obtain the target vehicle state.

[0018] In one embodiment, determining the target braking record from the historical braking records based on the recording time of each historical braking record includes:

[0019] Determine the time difference between the recording time of each historical braking record and the current time;

[0020] Historical braking records whose time difference is less than the difference threshold are used as target braking records.

[0021] In one embodiment, determining the target warning result for the target vehicle based on the initial warning result and the vehicle state difference includes:

[0022] Based on the differences in vehicle status, the initial warning result is corrected to obtain the target warning result for the target vehicle.

[0023] In one embodiment, the reference environment information includes at least one basic environment information; the training process of the collision warning model includes the following:

[0024] Obtain at least one basic environmental information corresponding to the reference vehicle;

[0025] Determine the warning impact weight corresponding to each basic environmental information, and label each basic environmental information based on the warning impact weight;

[0026] The initial early warning model is trained based on the basic environmental information labeled with the aforementioned early warning impact weights to obtain the collision early warning model.

[0027] Secondly, this application also provides a vehicle collision warning device. The device includes:

[0028] The acquisition module is used to acquire external environmental information of the target vehicle;

[0029] The early warning module is used to perform collision early warning analysis on the external environment information based on the collision early warning model to obtain the initial early warning result of the target vehicle; wherein, the collision early warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0030] The first determining module is used to determine the vehicle state difference between the target vehicle and the reference vehicle;

[0031] The second determining module is used to determine the target warning result of the target vehicle based on the initial warning result and the difference in vehicle status.

[0032] Thirdly, this application also provides a vehicle-mounted terminal. The vehicle-mounted terminal includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0033] Obtain information about the external environment of the target vehicle;

[0034] Based on the collision warning model, the external environment information is analyzed for collision warning to obtain the initial warning result of the target vehicle; wherein, the collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0035] Determine the differences in vehicle state between the target vehicle and the reference vehicle;

[0036] Based on the initial warning result and the difference in vehicle status, the target warning result for the target vehicle is determined.

[0037] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0038] Obtain information about the external environment of the target vehicle;

[0039] Based on the collision warning model, the external environment information is analyzed for collision warning to obtain the initial warning result of the target vehicle; wherein, the collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0040] Determine the differences in vehicle state between the target vehicle and the reference vehicle;

[0041] Based on the initial warning result and the difference in vehicle status, the target warning result for the target vehicle is determined.

[0042] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0043] Obtain information about the external environment of the target vehicle;

[0044] Based on the collision warning model, the external environment information is analyzed for collision warning to obtain the initial warning result of the target vehicle; wherein, the collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0045] Determine the differences in vehicle state between the target vehicle and the reference vehicle;

[0046] Based on the initial warning result and the difference in vehicle status, the target warning result for the target vehicle is determined.

[0047] The aforementioned vehicle collision warning method, device, vehicle terminal, and storage medium determine the initial warning result for the target vehicle based on a collision warning model and the external environmental information of the target vehicle, acquire the vehicle state difference between the target vehicle and the reference vehicle, and then determine the target warning result for the target vehicle based on the initial warning result and the vehicle state difference. Since this application first uses a collision warning model to analyze the external environmental information to obtain the initial warning result, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference, this application's method for providing collision warning to the target vehicle, compared to the prior art method that only uses the distance between the vehicle in front and the target vehicle, not only fully considers the influence of external environmental information on the target vehicle's target warning result, but also considers the influence of the vehicle state difference between the target vehicle and the reference vehicle on the target vehicle's target warning result. This makes the target warning result more consistent with the actual situation of the target vehicle, improves the accuracy of the target warning result, and enables the target vehicle to effectively avoid traffic accidents. Attached Figure Description

[0048] Figure 1 An application environment diagram of a vehicle collision warning method provided in this application embodiment;

[0049] Figure 2 A flowchart of a vehicle collision warning method provided in this application embodiment;

[0050] Figure 3A schematic diagram of the process for determining vehicle state differences provided in an embodiment of this application;

[0051] Figure 4 A flowchart illustrating the training process of the collision warning model provided in this application embodiment;

[0052] Figure 5 A flowchart of another vehicle collision warning method provided in this application embodiment;

[0053] Figure 6 This is a structural block diagram of a first type of vehicle collision warning device provided in an embodiment of this application;

[0054] Figure 7 This is a structural block diagram of a second type of vehicle collision warning device provided in an embodiment of this application;

[0055] Figure 8 A structural block diagram of a third type of vehicle collision warning device provided in this application embodiment;

[0056] Figure 9 This is a structural block diagram of the fourth vehicle collision warning device provided in the embodiments of this application;

[0057] Figure 10 This is an internal structure diagram of the vehicle-mounted terminal in one embodiment. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0059] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application. In the description of this application, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0060] Based on the above, the vehicle collision warning method provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, in one embodiment, a vehicle-mounted terminal is provided, which can be a server, and its internal structure diagram can be as follows. Figure 1 As shown, the vehicle-mounted terminal includes a processor, memory, and network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data acquired by the vehicle collision warning method. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a vehicle collision warning method.

[0061] This application discloses a vehicle collision warning method, device, vehicle terminal, and storage medium, which may include the following: determining the initial warning result of the target vehicle based on the collision warning model and the external environment information of the target vehicle, obtaining the vehicle state difference between the target vehicle and the reference vehicle, and then determining the target warning result of the target vehicle based on the initial warning result and the vehicle state difference.

[0062] In one embodiment, such as Figure 2 As shown, Figure 2 This is a flowchart illustrating a vehicle collision warning method provided in an embodiment of this application. Figure 1 The vehicle collision warning method executed by the in-vehicle terminal may include the following steps:

[0063] Step 201: Obtain the external environment information of the target vehicle.

[0064] It should be noted that external environmental information refers to environmental information in the driving environment that can affect the vehicle's physical and braking states. Specifically, external environmental information may include, but is not limited to: weather information (including: sunny, rainy, snowy, foggy, hazy, sandstorm, etc.); road information (including: asphalt road, cement concrete road, gravel road, natural dirt road, etc.); and light intensity level information (including: light intensity between 100 lx and 200 lx, light intensity between 200 lx and 300 lx, light intensity between 300 lx and 400 lx, etc.).

[0065] In one embodiment of this application, when it is necessary to obtain the external environment information of the target vehicle, the operation of obtaining the external environment information of the target vehicle can be performed by activating at least one environmental information sensor installed on the target vehicle, depending on the different types of environmental information sensors. The environmental information sensors may include, but are not limited to, temperature sensors, humidity sensors, vision sensors, photosensors, etc.

[0066] In another embodiment of this application, when it is necessary to obtain the external environment information of the target vehicle, the external environment information of the area where the target vehicle is located can be queried on the Internet based on the vehicle location of the target vehicle, thereby realizing the operation of obtaining the external environment information of the target vehicle through the Internet.

[0067] Step 202: Based on the collision warning model, perform collision warning analysis on the external environment information to obtain the initial warning result for the target vehicle.

[0068] The collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0069] The initial warning result indicates whether the target vehicle will collide with the vehicle in front, and the predicted speed of the target vehicle when it does collide with the vehicle in front.

[0070] It should be noted that when performing collision warning analysis on external environmental information, the following can be included: inputting external environmental information into the collision warning model and obtaining the output result of the collision warning model, which is the initial warning result for the target vehicle.

[0071] To further explain, in order to ensure the accuracy of the initial prediction results and subsequent target prediction results, it is necessary to ensure that the similarity between the reference vehicle and the target vehicle is greater than the similarity threshold. Therefore, determining the reference vehicle corresponding to the target vehicle may specifically include the following: determining the production year, vehicle type, and mileage of each candidate vehicle; and determining the production year, vehicle type, and mileage of the target vehicle; then, determining the vehicle similarity between each candidate vehicle and the target vehicle through the three levels of production year, vehicle type, and mileage, and using the candidate vehicle with a similarity greater than the similarity threshold as the reference vehicle corresponding to the target vehicle.

[0072] In one embodiment of this application, when it is necessary to determine the vehicle similarity between each candidate vehicle and the target vehicle, for each candidate vehicle, it is determined whether the vehicle type of the candidate vehicle is the same as that of the target vehicle. If they are different, it is determined that the candidate vehicle is not the reference vehicle corresponding to the target vehicle. If they are the same, a first similarity is calculated between the production year of the candidate vehicle and the production year of the target vehicle, and a second similarity is calculated between the mileage of the candidate vehicle and the mileage of the target vehicle. The first similarity and the second similarity are averaged to obtain the target similarity.

[0073] Step 203: Determine the differences in vehicle status between the target vehicle and the reference vehicle.

[0074] It should be noted that when it is necessary to determine the difference in vehicle state between the target vehicle and the reference vehicle, the following may be included: determining at least one historical braking record of the target vehicle; predicting the state of the target vehicle based on the historical braking record to obtain the target vehicle state; and then determining the difference in vehicle state between the target vehicle and the reference vehicle state based on the target vehicle state and the reference vehicle state of the reference vehicle.

[0075] The value corresponding to the reference vehicle state can be used to characterize the braking effect of the reference vehicle during emergency braking. Furthermore, the braking effect of the reference vehicle can be represented by the braking distance required for emergency braking. If the value corresponding to the reference vehicle's emergency braking is higher, it indicates a better braking effect, meaning a shorter braking distance is required. Conversely, if the value corresponding to the reference vehicle's emergency braking is lower, it indicates a worse braking effect, meaning a longer braking distance is required.

[0076] To further explain, when it is necessary to determine the difference between the vehicle states of the target vehicle and the reference vehicle based on the target vehicle state and the reference vehicle state of the reference vehicle, the difference between the target vehicle state and the reference vehicle state can be calculated, and the result obtained is the difference between the vehicle states of the target vehicle and the reference vehicle.

[0077] In one embodiment of this application, if the vehicle state difference is positive, it indicates that the braking effect of the target vehicle during emergency braking is better than that of the reference vehicle during emergency braking; if the vehicle state difference is negative, it indicates that the braking effect of the target vehicle during emergency braking is worse than that of the reference vehicle during emergency braking.

[0078] Step 204: Determine the target warning result for the target vehicle based on the initial warning result and the difference in vehicle status.

[0079] The target warning result is used to indicate whether the target vehicle will collide with the vehicle in front after vehicle state difference correction, and the predicted speed of the target vehicle when it collides with the vehicle in front.

[0080] It should be noted that since the difference in vehicle state can be used to represent the difference in braking effect between the target vehicle and the reference vehicle when they perform emergency braking, the initial warning result can be corrected based on the difference in vehicle state to obtain the target warning result for the target vehicle.

[0081] Specifically, based on the differences in vehicle status, the difference between the braking effect of the target vehicle when it performs emergency braking and the braking effect of the reference vehicle when it performs emergency braking is determined. Then, the initial warning result is corrected based on this difference to obtain the target warning result for the target vehicle.

[0082] In one embodiment of this application, if the vehicle state difference is positive but the absolute value of the vehicle state difference is small, it indicates that the braking effect of the target vehicle when it performs emergency braking is better than that of the reference vehicle when it performs emergency braking, but the difference is small. Therefore, when the initial warning result indicates that the target vehicle has collided with the vehicle in front, it is determined that the target warning result can also indicate that the target vehicle has collided with the vehicle in front, but when the target vehicle collides with the vehicle in front, the predicted driving speed of the target vehicle is lower (appropriately reduced according to the absolute value of the vehicle state difference).

[0083] In one embodiment of this application, if the vehicle state difference is positive but the absolute value of the vehicle state difference is large, it indicates that the braking effect of the target vehicle when it performs emergency braking is better than that of the reference vehicle when it performs emergency braking, and the difference is large. Therefore, when the initial warning result indicates that the target vehicle is colliding with the vehicle in front, it is determined that the target warning result can also indicate that the target vehicle is colliding with the vehicle in front, but when the target vehicle is colliding with the vehicle in front, the predicted driving speed of the target vehicle is lower (appropriately reduced according to the absolute value of the vehicle state difference); or, it is determined that the target warning result can indicate that the target vehicle will not collide with the vehicle in front.

[0084] In one embodiment of this application, if the vehicle state difference is negative, but the absolute value of the vehicle state difference is small, it indicates that the braking effect of the target vehicle during emergency braking is worse than that of the reference vehicle during emergency braking, but the difference is small. Therefore, when the initial warning result indicates that the target vehicle has collided with the vehicle in front, it is determined that the target warning result also indicates that the target vehicle has collided with the vehicle in front, but the predicted speed of the target vehicle is higher when the target vehicle collides with the vehicle in front (appropriately increased according to the absolute value of the vehicle state difference). Furthermore, when the initial warning result indicates that the target vehicle has not collided with the vehicle in front, it is determined that the target warning result can also indicate that the target vehicle has not collided with the vehicle in front, or it can be determined that the target warning result can indicate that the target vehicle has collided with the vehicle in front, but the predicted speed of the target vehicle is lower when the target vehicle collides with the vehicle in front.

[0085] In one embodiment of this application, if the vehicle state difference is negative but the absolute value of the vehicle state difference is large, it indicates that the braking effect of the target vehicle during emergency braking is worse than that of the reference vehicle during emergency braking, but the difference is significant. Therefore, when the initial warning result indicates that the target vehicle has collided with the vehicle in front, it is determined that the target warning result also indicates that the target vehicle has collided with the vehicle in front, but the predicted speed of the target vehicle is higher when the target vehicle collides with the vehicle in front (appropriately increased according to the absolute value of the vehicle state difference). Furthermore, when the initial warning result indicates that the target vehicle has not collided with the vehicle in front, it is determined that the target warning result can also indicate that the target vehicle has not collided with the vehicle in front, or it can be determined that the target warning result can indicate that the target vehicle has collided with the vehicle in front, but the predicted speed of the target vehicle is higher when the target vehicle collides with the vehicle in front.

[0086] It should be noted that, based on the target warning model, the initial warning result can be corrected according to the differences in vehicle status to obtain the target warning result for the target vehicle.

[0087] The aforementioned vehicle collision warning method determines the initial warning result for the target vehicle based on a collision warning model and the external environmental information of the target vehicle, obtains the vehicle state difference between the target vehicle and the reference vehicle, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference. Since this application first uses a collision warning model to analyze the external environmental information to obtain the initial warning result, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference, this method, compared to the prior art method that only uses the distance between the vehicle in front and the target vehicle for collision warning, not only fully considers the influence of external environmental information on the target vehicle's target warning result, but also considers the influence of the vehicle state difference between the target vehicle and the reference vehicle on the target vehicle's target warning result. This makes the target warning result more consistent with the actual situation of the target vehicle, improves the accuracy of the target warning result, and enables the target vehicle to effectively avoid traffic accidents.

[0088] In one embodiment, existing collision warning systems detect the distance between a vehicle ahead and a target vehicle, determine whether the distance meets the target vehicle's braking distance, and issue a collision warning to the target vehicle based on the determination result. However, the accuracy of collision warnings for target vehicles in existing technologies is low, failing to effectively avoid traffic accidents. To solve the above problems, a solution can be implemented as follows: Figure 3 As shown, based on the reference vehicle's reference vehicle state, the differences in vehicle state between the target vehicle and the reference vehicle are determined, which may specifically include the following:

[0089] Step 301: Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record.

[0090] The recording time of the historical braking record is used to indicate the time when the target vehicle generated the historical braking record.

[0091] In one embodiment of this application, if each historical braking record and its recording time are stored in the local storage device of the target vehicle, then when it is necessary to obtain each historical braking record and its recording time, the historical braking record and its recording time can be obtained from the local storage device, thereby realizing the operation of determining at least one historical braking record of the target vehicle and the recording time of each historical braking record.

[0092] In one embodiment of this application, if each historical braking record and its recording time are stored in a cloud server corresponding to the target vehicle, then when it is necessary to obtain each historical braking record and its recording time, an information retrieval request can be sent to the cloud server. The information retrieval request includes the vehicle identifier of the target vehicle. Based on the vehicle identifier, each historical braking record and its recording time are retrieved from the information stored in the cloud server, thereby realizing the operation of determining at least one historical braking record of the target vehicle and the recording time of each historical braking record.

[0093] Step 302: Determine the target braking record from each historical braking record based on the recording time of each historical braking record.

[0094] It should be noted that when it is necessary to determine the target braking record from each historical braking record, the following may be included: determining the time difference between the recording time of each historical braking record and the current time; and taking the historical braking records whose time difference is less than the difference threshold as the target braking record.

[0095] The difference threshold can be set and adjusted based on the staff's historical experience and actual vehicle warning needs. The range of the difference threshold is not limited here.

[0096] Step 303: Determine the target vehicle status based on the target braking record.

[0097] It should be noted that when it is necessary to determine the state of a target vehicle, the specific steps may include the following: determining the braking distance and starting speed corresponding to the target braking record; and predicting the state of the target vehicle based on the braking distance and starting speed corresponding to the target braking record.

[0098] In one embodiment of this application, the state of a target vehicle can be predicted based on braking distance and starting speed according to a pre-set vehicle state lookup table; wherein, the vehicle state lookup table records the target vehicle state corresponding to different braking distances and starting speeds; therefore, the target vehicle state corresponding to the braking distance and starting speed can be determined from the vehicle state lookup table.

[0099] In another embodiment of this application, the state prediction of the target vehicle can be realized based on the braking distance and starting speed corresponding to the target braking record according to the pre-trained analysis model. Specifically, the braking distance and starting speed corresponding to the target braking record are input into the pre-trained analysis model to obtain the output result of the analysis model, which is the target vehicle state of the target vehicle.

[0100] The training process of the analysis model includes: obtaining the sample braking distance and sample starting speed; labeling the sample braking distance and sample starting speed with sample state information based on human experience; and inputting the sample braking distance and sample starting speed labeled with sample state information into the analysis model to realize the training operation of the analysis model.

[0101] Step 304: Determine the vehicle state difference between the target vehicle and the reference vehicle based on the target vehicle state and the reference vehicle state of the reference vehicle.

[0102] In one embodiment of this application, determining the vehicle state difference between the target vehicle and the reference vehicle may specifically include the following: performing a difference calculation between the target vehicle state and the reference vehicle state, and the result obtained is the vehicle state difference between the target vehicle and the reference vehicle.

[0103] Specifically, if the vehicle state difference is positive, it means that the braking effect of the target vehicle during emergency braking is better than that of the reference vehicle during emergency braking; if the vehicle state difference is negative, it means that the braking effect of the target vehicle during emergency braking is worse than that of the reference vehicle during emergency braking.

[0104] The aforementioned vehicle collision warning method determines the target vehicle's state and, based on the target vehicle's state and the reference vehicle's state, identifies the difference in vehicle states between the target vehicle and the reference vehicle. Therefore, this application considers the difference in vehicle states between the target vehicle and the reference vehicle when issuing a collision warning, making the warning result more consistent with the actual situation of the target vehicle, improving the accuracy of the warning result, and enabling the target vehicle to effectively avoid traffic accidents.

[0105] In one embodiment, such as Figure 4 As shown, if the reference environmental information includes at least one basic environmental information, the training process of the collision warning model may specifically include the following:

[0106] Step 401: Obtain at least one basic environmental information corresponding to the reference vehicle.

[0107] The basic environmental information can include weather information for the reference vehicle (including: sunny, rainy, snowy, foggy, hazy, sandstorm, etc.), road information (including: asphalt road, cement concrete road, gravel road, natural dirt road, etc.), and light intensity level information (including: light intensity between 100 lx and 200 lx, light intensity between 200 lx and 300 lx, light intensity between 300 lx and 400 lx, etc.).

[0108] In one embodiment of this application, when it is necessary to obtain at least one basic environmental information corresponding to a reference vehicle, the operation of obtaining at least one basic environmental information corresponding to the reference vehicle can be performed by activating at least one environmental information sensor installed on the reference vehicle, depending on the different types of environmental information sensors. The environmental information sensors may include, but are not limited to, temperature sensors, humidity sensors, vision sensors, photosensors, etc.

[0109] Step 402: Determine the warning impact weight corresponding to each basic environmental information, and label each basic environmental information based on the warning impact weight.

[0110] Among them, the warning impact weight is used to represent the degree of impact of each basic environmental information on the accuracy of vehicle collision warnings for reference vehicles.

[0111] In one embodiment of the application, when it is necessary to determine the warning impact weight corresponding to each basic environmental information, the impact weight of each basic environmental information can be evaluated based on the historical experience of the staff, and then the warning impact weight corresponding to each basic environmental information can be determined.

[0112] Step 403: Train the initial early warning model based on the basic environmental information labeled with the early warning impact weights to obtain the collision early warning model.

[0113] In one embodiment of this application, when it is necessary to train an initial warning model based on basic environmental information labeled with warning impact weights, it is possible to determine whether a reference vehicle collides with a vehicle in front under each basic environmental information, and the collision speed when the reference vehicle collides with a vehicle in front under each basic environmental information. Then, based on the basic environmental information labeled with warning impact weights, whether the reference vehicle collides with a vehicle in front under each basic environmental information, and the collision speed when the reference vehicle collides with a vehicle in front under each basic environmental information, the initial warning model is trained to obtain a collision warning model.

[0114] The aforementioned vehicle collision warning method trains the initial warning model using basic environmental information labeled with warning impact weights, ensuring that subsequent collision warning analysis of external environmental information can be successfully performed based on the collision warning model, thus guaranteeing the smooth progress of subsequent processes.

[0115] In one embodiment, such as Figure 5 As shown, when it is necessary to determine the target warning result for a target vehicle, the following may be included:

[0116] Step 501: Obtain the external environment information of the target vehicle.

[0117] Step 502: Based on the collision warning model, perform collision warning analysis on the external environment information to obtain the initial warning result for the target vehicle.

[0118] Step 503: Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record.

[0119] Step 504: Determine the time difference between the recording time of each historical braking record and the current time.

[0120] Step 505: Select historical braking records whose time difference is less than the difference threshold as target braking records.

[0121] Step 506: Determine the braking distance and starting speed corresponding to the target braking record.

[0122] Step 507: Based on the braking distance and starting speed corresponding to the target braking record, predict the state of the target vehicle to obtain the target vehicle state.

[0123] Step 508: Determine the vehicle state difference between the target vehicle and the reference vehicle based on the target vehicle state and the reference vehicle state of the reference vehicle.

[0124] Step 509: Based on the differences in vehicle status, correct the initial warning result to obtain the target warning result for the target vehicle.

[0125] The aforementioned vehicle collision warning method determines the initial warning result for the target vehicle based on a collision warning model and the external environmental information of the target vehicle, obtains the vehicle state difference between the target vehicle and the reference vehicle, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference. Since this application first uses a collision warning model to analyze the external environmental information to obtain the initial warning result, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference, this method, compared to the prior art method that only uses the distance between the vehicle in front and the target vehicle for collision warning, not only fully considers the influence of external environmental information on the target vehicle's target warning result, but also considers the influence of the vehicle state difference between the target vehicle and the reference vehicle on the target vehicle's target warning result. This makes the target warning result more consistent with the actual situation of the target vehicle, improves the accuracy of the target warning result, and enables the target vehicle to effectively avoid traffic accidents.

[0126] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0127] Based on the same inventive concept, this application also provides a vehicle collision warning device for implementing the vehicle collision warning method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more vehicle collision warning device embodiments provided below can be found in the limitations of the vehicle collision warning method described above, and will not be repeated here.

[0128] In one embodiment, such as Figure 6 As shown, a vehicle collision warning device is provided, including: an acquisition module 10, a warning module 20, a first determination module 30, and a second determination module 40, wherein:

[0129] The acquisition module 10 is used to acquire external environmental information of the target vehicle.

[0130] The early warning module 20 is used to perform collision early warning analysis on external environmental information based on the collision early warning model to obtain the initial early warning result of the target vehicle. The collision early warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0131] The training process of the collision warning model includes the following: acquiring at least one basic environmental information corresponding to the reference vehicle; determining the warning impact weights corresponding to each basic environmental information and labeling each basic environmental information based on the warning impact weights; training the initial warning model based on each basic environmental information labeled with warning impact weights to obtain the collision warning model.

[0132] The first determining module 30 is used to determine the difference in vehicle state between the target vehicle and the reference vehicle based on the reference vehicle state of the reference vehicle.

[0133] The second determining module 40 is used to determine the target warning result of the target vehicle based on the initial warning result and the difference in vehicle status.

[0134] The aforementioned vehicle collision warning device determines the initial warning result for the target vehicle based on a collision warning model and the external environmental information of the target vehicle, obtains the vehicle state difference between the target vehicle and the reference vehicle, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference. Since this application first uses a collision warning model to analyze the external environmental information to obtain the initial warning result, and then determines the target warning result for the target vehicle based on the initial warning result and the vehicle state difference, this application's method for providing collision warnings to the target vehicle, compared to the prior art method that only uses the distance between the vehicle in front and the target vehicle, not only fully considers the influence of external environmental information on the target vehicle's target warning result, but also considers the influence of the vehicle state difference between the target vehicle and the reference vehicle on the target vehicle's target warning result. This makes the target warning result more consistent with the actual situation of the target vehicle, improves the accuracy of the target warning result, and enables the target vehicle to effectively avoid traffic accidents.

[0135] In one embodiment, such as Figure 7 As shown, a vehicle collision warning device is provided. The first determining module 30 of the vehicle collision warning device includes: a first determining unit 31, a second determining unit 32, a third determining unit 33, and a fourth determining unit 34, wherein:

[0136] The first determining unit 31 is used to determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record.

[0137] The second determining unit 32 is used to determine the target braking record from each historical braking record based on the recording time of each historical braking record.

[0138] The third determining unit 33 is used to determine the target vehicle status based on the target braking record.

[0139] The fourth determining unit 34 is used to determine the vehicle state difference between the target vehicle and the reference vehicle.

[0140] The fourth determining unit is specifically used to correct the initial warning result based on the differences in vehicle status, so as to obtain the target warning result for the target vehicle.

[0141] In one embodiment, such as Figure 8 As shown, a vehicle collision warning device is provided. The third determining unit 33 in the vehicle collision warning device includes: a first determining subunit 331 and a prediction subunit 332, wherein:

[0142] The first determining subunit 331 is used to determine the braking distance and starting speed corresponding to the target braking record.

[0143] The prediction subunit 332 is used to predict the state of the target vehicle based on the braking distance and starting speed corresponding to the target braking record, so as to obtain the target vehicle state.

[0144] In one embodiment, such as Figure 9 As shown, a vehicle collision warning device is provided. The second determining unit 32 in the vehicle collision warning device includes: a second determining subunit 321 and a third determining subunit 322, wherein:

[0145] The second determining subunit 321 is used to determine the time difference between the recording time of each historical braking record and the current time.

[0146] The third determining subunit 322 is used to select historical braking records whose time difference is less than the difference threshold as target braking records.

[0147] Each module in the aforementioned vehicle collision warning device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the vehicle terminal in hardware form or independent of it, or stored in the memory of the vehicle terminal in software form, so that the processor can call and execute the corresponding operations of each module.

[0148] In one embodiment, a vehicle-mounted terminal is provided. This vehicle-mounted terminal can be a terminal, and its internal structure diagram can be as follows: Figure 10As shown, the vehicle-mounted terminal includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a vehicle collision warning method. The display unit of the vehicle-mounted terminal forms a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the vehicle terminal can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the vehicle terminal, or external keyboards, touchpads, or mice, etc.

[0149] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the vehicle terminal to which the present application is applied. A specific vehicle terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0150] In one embodiment, an in-vehicle terminal is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0151] Obtain information about the external environment of the target vehicle;

[0152] Based on the collision warning model, collision warning analysis is performed on external environmental information to obtain the initial warning result for the target vehicle. The collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0153] Determine the differences in vehicle condition between the target vehicle and the reference vehicle;

[0154] Based on the initial warning results and the differences in vehicle status, the target warning result for the target vehicle is determined.

[0155] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0156] Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record;

[0157] Based on the recording time of each historical braking record, the target braking record is determined from each historical braking record;

[0158] The target vehicle status is determined based on the target braking record;

[0159] Based on the target vehicle's state and the reference vehicle's state, determine the differences in vehicle states between the target vehicle and the reference vehicle.

[0160] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0161] Determine the braking distance and starting speed corresponding to the target braking record;

[0162] Based on the braking distance and starting speed corresponding to the target braking record, the state of the target vehicle is predicted to obtain the target vehicle state.

[0163] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0164] Determine the time difference between the recording time of each historical braking record and the current time;

[0165] Historical braking records whose time difference is less than the difference threshold are used as target braking records.

[0166] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0167] Based on the differences in vehicle status, the initial warning result is corrected to obtain the target warning result for the target vehicle.

[0168] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0169] Obtain at least one basic environmental information corresponding to the reference vehicle;

[0170] Determine the warning impact weight corresponding to each basic environmental information, and label each basic environmental information based on the warning impact weight;

[0171] The initial early warning model is trained based on the basic environmental information labeled with the impact weight of the early warning, and a collision early warning model is obtained.

[0172] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0173] Obtain information about the external environment of the target vehicle;

[0174] Based on the collision warning model, collision warning analysis is performed on external environmental information to obtain the initial warning result for the target vehicle. The collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0175] Determine the differences in vehicle condition between the target vehicle and the reference vehicle;

[0176] Based on the initial warning results and the differences in vehicle status, the target warning result for the target vehicle is determined.

[0177] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0178] Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record;

[0179] Based on the recording time of each historical braking record, the target braking record is determined from each historical braking record;

[0180] The target vehicle status is determined based on the target braking record;

[0181] Based on the target vehicle's state and the reference vehicle's state, determine the differences in vehicle states between the target vehicle and the reference vehicle.

[0182] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0183] Determine the braking distance and starting speed corresponding to the target braking record;

[0184] Based on the braking distance and starting speed corresponding to the target braking record, the state of the target vehicle is predicted to obtain the target vehicle state.

[0185] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0186] Determine the time difference between the recording time of each historical braking record and the current time;

[0187] Historical braking records whose time difference is less than the difference threshold are used as target braking records.

[0188] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0189] Based on the differences in vehicle status, the initial warning result is corrected to obtain the target warning result for the target vehicle.

[0190] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0191] Obtain at least one basic environmental information corresponding to the reference vehicle;

[0192] Determine the warning impact weight corresponding to each basic environmental information, and label each basic environmental information based on the warning impact weight;

[0193] The initial early warning model is trained based on the basic environmental information labeled with the impact weight of the early warning, and a collision early warning model is obtained.

[0194] In one embodiment, a vehicle is provided, including a computer program that, when executed by a processor, performs the following steps:

[0195] Obtain information about the external environment of the target vehicle;

[0196] Based on the collision warning model, collision warning analysis is performed on external environmental information to obtain the initial warning result for the target vehicle. The collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the similarity between the reference vehicle and the target vehicle is greater than the similarity threshold.

[0197] Determine the differences in vehicle condition between the target vehicle and the reference vehicle;

[0198] Based on the initial warning results and the differences in vehicle status, the target warning result for the target vehicle is determined.

[0199] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0200] Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record;

[0201] Based on the recording time of each historical braking record, the target braking record is determined from each historical braking record;

[0202] The target vehicle status is determined based on the target braking record;

[0203] Based on the target vehicle's state and the reference vehicle's state, determine the differences in vehicle states between the target vehicle and the reference vehicle.

[0204] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0205] Determine the braking distance and starting speed corresponding to the target braking record;

[0206] Based on the braking distance and starting speed corresponding to the target braking record, the state of the target vehicle is predicted to obtain the target vehicle state.

[0207] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0208] Determine the time difference between the recording time of each historical braking record and the current time;

[0209] Historical braking records whose time difference is less than the difference threshold are used as target braking records.

[0210] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0211] Based on the differences in vehicle status, the initial warning result is corrected to obtain the target warning result for the target vehicle.

[0212] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0213] Obtain at least one basic environmental information corresponding to the reference vehicle;

[0214] Determine the warning impact weight corresponding to each basic environmental information, and label each basic environmental information based on the warning impact weight;

[0215] The initial early warning model is trained based on the basic environmental information labeled with the impact weight of the early warning, and a collision early warning model is obtained.

[0216] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0217] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0218] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0219] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A vehicle collision warning method, characterized in that, The method includes: Obtain information about the external environment of the target vehicle; Based on the collision warning model, the external environment information is analyzed for collision warning to obtain the initial warning result of the target vehicle; wherein, the collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold. Determine the differences in vehicle state between the target vehicle and the reference vehicle; Based on the initial warning result and the difference in vehicle status, the target warning result for the target vehicle is determined.

2. The method according to claim 1, characterized in that, Determining the vehicle state difference between the target vehicle and the reference vehicle includes: Determine at least one historical braking record of the target vehicle, and the recording time of each historical braking record; Based on the recording time of each historical braking record, the target braking record is determined from each historical braking record; Based on the target braking record, the target vehicle status is determined; Based on the target vehicle state and the reference vehicle state of the reference vehicle, the difference in vehicle state between the target vehicle and the reference vehicle is determined.

3. The method according to claim 2, characterized in that, Determining the target vehicle state based on the target braking record includes: Determine the braking distance and starting speed corresponding to the target braking record; Based on the braking distance and the starting speed corresponding to the target braking record, the state of the target vehicle is predicted to obtain the target vehicle state.

4. The method according to claim 2, characterized in that, The step of determining the target braking record from each historical braking record based on the recording time of each historical braking record includes: Determine the time difference between the recording time of each historical braking record and the current time; Historical braking records with a time difference less than the difference threshold are selected as target braking records.

5. The method according to claim 1, characterized in that, The step of determining the target warning result for the target vehicle based on the initial warning result and the difference in vehicle status includes: Based on the differences in vehicle status, the initial warning result is corrected to obtain the target warning result for the target vehicle.

6. The method according to claim 1, characterized in that, The reference environment information includes at least one basic environment information; the training process of the collision warning model includes the following: Obtain at least one basic environmental information corresponding to the reference vehicle; Determine the warning impact weight corresponding to each basic environmental information, and label each basic environmental information based on the warning impact weight; Based on the basic environmental information labeled with the warning impact weights, the initial warning model is trained to obtain the collision warning model.

7. A vehicle collision warning device, characterized in that, The device includes: The acquisition module is used to acquire external environmental information of the target vehicle; The early warning module is used to perform collision warning analysis on the external environment information based on the collision warning model to obtain the initial warning result of the target vehicle; wherein the collision warning model is trained based on the reference environment information corresponding to the reference vehicle, and the vehicle similarity between the reference vehicle and the target vehicle is greater than the similarity threshold. The first determining module is used to determine the vehicle state difference between the target vehicle and the reference vehicle; The second determining module is used to determine the target warning result of the target vehicle based on the initial warning result and the difference in vehicle status.

8. A vehicle-mounted terminal, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A vehicle comprising a computer program, characterized in that, The vehicle includes the vehicle-mounted terminal as described in claim 8.

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