Vehicle monitoring method, device, terminal equipment and storage medium

Abstract

This application is applicable to the field of computer technology and provides a vehicle monitoring method, apparatus, terminal device, and storage medium, including: determining a vehicle queue based on first vehicle data transmitted by at least three vehicles, the first vehicle data being able to indicate whether the corresponding vehicle is an intelligent vehicle, the vehicle queue including, in order, a first vehicle, a second vehicle, and a third vehicle, the second vehicle being a non-intelligent vehicle, and the first vehicle and the third vehicle being both intelligent vehicles; determining warning data based on second vehicle data transmitted by each intelligent vehicle in the vehicle queue, the second vehicle data at least including the speed and distance of the corresponding intelligent vehicle, the distance being the distance between the corresponding intelligent vehicle and the second vehicle; transmitting the warning data to the second vehicle, which is used to issue an accident warning based on the warning data. This application can improve the driving safety of non-intelligent vehicles without increasing costs.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and in particular relates to a vehicle monitoring method, apparatus, terminal device, and computer-readable storage medium. Background Art

[0002] In recent years, with the rapid evolution of mobile internet technology, intelligent vehicle technology has also developed rapidly. An intelligent vehicle is a comprehensive system that integrates environmental perception, decision-making, and assisted driving. It utilizes computing, modern sensing, artificial intelligence, and automatic control technologies. This system automatically analyzes driving data collected by intelligent hardware such as sensors and cameras, and then analyzes potential accidents based on this data.

[0003] The current intelligent vehicle market is still in its infancy, and most vehicles in production and application are non-intelligent vehicles. Therefore, currently, intelligent hardware and software are usually deployed on non-intelligent vehicles to achieve upgrades and renovations.

[0004] Currently, the cost of intelligent upgrades for vehicles is relatively high. For example, in large-scale applications such as transport fleets, it costs a lot to achieve intelligent upgrades for all vehicles. Summary of the Invention

[0005] The embodiments of the present application provide a vehicle monitoring method, apparatus, terminal device, and storage medium, which can improve the driving safety of non-intelligent vehicles without increasing costs.

[0006] In a first aspect, an embodiment of the present application provides a vehicle monitoring method, applied to a data platform, comprising:

[0007] Determining a vehicle queue based on first vehicle data sent by at least three vehicles, wherein the first vehicle data can indicate whether a corresponding vehicle is an intelligent vehicle, the vehicle queue sequentially comprising a first vehicle, a second vehicle, and a third vehicle, wherein the second vehicle is a non-intelligent vehicle, and the first vehicle and the third vehicle are both intelligent vehicles;

[0008] Determining warning data based on second vehicle data sent by each of the smart vehicles in the vehicle queue, wherein the second vehicle data includes at least a speed and a distance between the corresponding smart vehicle, where the distance is the distance between the corresponding smart vehicle and the second vehicle;

[0009] The warning data is sent to the second vehicle, and the second vehicle is used to perform accident warning according to the warning data.

[0010] In a second aspect, an embodiment of the present application provides a vehicle monitoring method, which is applied to an intelligent vehicle in a vehicle queue, wherein the intelligent vehicle is a first vehicle or a third vehicle, and the vehicle queue further includes a second vehicle located between the first vehicle and the third vehicle, wherein the second vehicle is a non-intelligent vehicle, and the method includes:

[0011] Determining second vehicle data of the smart vehicle, where the second vehicle data includes a vehicle distance and a speed of the smart vehicle, where the vehicle distance is a distance between the smart vehicle and the second vehicle;

[0012] The second vehicle data is sent to a data platform, and the data platform is used to determine the warning data of the second vehicle based on the second vehicle data.

[0013] In a third aspect, an embodiment of the present application provides a vehicle monitoring device, which is applied to a data platform and includes:

[0014] a vehicle queue determination module, configured to determine a vehicle queue based on first vehicle data transmitted by at least three vehicles, wherein the first vehicle data can indicate whether the corresponding vehicle is an intelligent vehicle, the vehicle queue comprising, in order, a first vehicle, a second vehicle, and a third vehicle, wherein the second vehicle is a non-intelligent vehicle, and the first vehicle and the third vehicle are both intelligent vehicles;

[0015] a warning data acquisition module, configured to determine warning data based on second vehicle data sent by each of the smart vehicles in the vehicle queue, wherein the second vehicle data includes at least a speed and a vehicle distance of the corresponding smart vehicle, wherein the vehicle distance is the distance between the corresponding smart vehicle and the second vehicle;

[0016] The sending module is used to send the warning data to the second vehicle, and the second vehicle is used to perform accident warning according to the warning data.

[0017] In a fourth aspect, an embodiment of the present application provides a terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the vehicle monitoring method described in the first aspect or the steps of the vehicle monitoring method described in the second aspect are implemented.

[0018] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the vehicle monitoring method described in the first aspect or the steps of the vehicle monitoring method described in the second aspect.

[0019] In the sixth aspect, an embodiment of the present application provides a computer program product, which, when running on a terminal device, enables the terminal device to execute the steps of the vehicle monitoring method described in any one of the first aspect or the steps of the vehicle monitoring method described in the second aspect.

[0020] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0021] In an embodiment of the present application, since a vehicle queue including non-intelligent vehicles is determined based on the first vehicle data reported by each of at least three vehicles, and the vehicles in the front and rear of the non-intelligent vehicle in the vehicle queue are all intelligent vehicles, and the intelligent vehicles can calculate driving-related data such as the distance between themselves and the vehicles in the front and rear based on intelligent algorithms, the warning data determined based on the second vehicle data including the speed and distance of the intelligent vehicles sent by each intelligent vehicle in the vehicle queue can reflect the driving-related data of the second vehicle, so that the second vehicle can perform accident warning based on the received warning data, and thus the non-intelligent vehicle can realize accident warning without deploying intelligent hardware and algorithms, that is, the function of intelligent warning is realized without the need for intelligent upgrading of the non-intelligent vehicle, thereby improving the driving safety of the non-intelligent vehicle on the basis of reducing the modification cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art.

[0023] Figure 1 This is a flow chart of a vehicle monitoring method applied to a data platform provided by an embodiment of the present application;

[0024] Figure 2 This is a schematic diagram of a vehicle queue provided in an embodiment of the present application;

[0025] Figure 3 The present invention provides a method for monitoring intelligent vehicles in a vehicle queue.

[0026] Figure 4 Schematic diagram of the structure of a vehicle monitoring device applied to a data platform provided in an embodiment of the present application;

[0027] Figure 5 1 is a schematic structural diagram of a vehicle monitoring device for an intelligent vehicle in a vehicle queue provided by an embodiment of the present application;

[0028] Figure 6 It is a structural diagram of the terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0030] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0031] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0032] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0033] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in yet other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized.

[0034] Example 1:

[0035] Figure 1 A flow chart of a vehicle monitoring method applied to a data platform provided by an embodiment of the present invention is shown, and is described in detail as follows:

[0036] Step S101: determining a vehicle queue based on first vehicle data sent by at least three vehicles.

[0037] Among them, the above-mentioned first vehicle data can indicate whether the corresponding vehicle is an intelligent vehicle. Optionally, the data in the first vehicle data that can indicate whether the corresponding vehicle is an intelligent vehicle can be the vehicle's license plate number or vehicle type (i.e., the vehicle's intelligent type, including intelligent vehicles and non-intelligent vehicles) and other data that can reflect the vehicle's intelligent type. For example, the first vehicle data may include the license plate number of the vehicle that sends the first vehicle data (i.e., the vehicle's unique identifier), and the data platform stores vehicle information such as the model, vehicle type, license plate number, and owner of each vehicle. The data platform can retrieve the vehicle information corresponding to the license plate number based on the license plate number in the first vehicle data, thereby being able to determine whether the vehicle that sends the first vehicle data is an intelligent vehicle based on the retrieved vehicle information. Alternatively, in order to reduce the vehicle information retrieval steps and improve data processing efficiency, the vehicle type can also be directly added to the first vehicle data to directly indicate whether the vehicle that sends the first vehicle data is an intelligent vehicle.

[0038] The above-mentioned vehicle queue includes a first vehicle, a second vehicle and a third vehicle in sequence, the above-mentioned second vehicle is a non-intelligent vehicle, and the above-mentioned first vehicle and the above-mentioned third vehicle are both the above-mentioned intelligent vehicles, that is, the intelligent vehicles and non-intelligent vehicles in the vehicle queue are arranged in a cross-arrangement relationship, and the non-intelligent vehicle is located between the two intelligent vehicles.

[0039] The aforementioned intelligent vehicles refer to vehicles that incorporate integrated systems that include one or more functions, including environmental perception, planning and decision-making, and multi-level assisted driving. Intelligent vehicles are upgraded from ordinary vehicles with intelligent features, such as the addition of advanced sensors (such as radar, front and rear cameras), controllers, and actuators. Furthermore, they may be equipped with artificial intelligence algorithms such as image retrieval and corresponding neural network models, giving the vehicles intelligent environmental perception capabilities and the ability to automatically analyze safe and hazardous driving conditions. Non-intelligent vehicles, on the other hand, are vehicles that have not undergone intelligent upgrades and lack such capabilities as environmental perception and automatic analysis of safe and hazardous driving conditions.

[0040] Specifically, since three vehicles are required to form a vehicle queue, after receiving the first vehicle data sent by at least three vehicles (that is, there are at least three vehicles sending the first vehicle data to the data platform), the vehicle queue is determined based on the first vehicle data sent by at least three vehicles.

[0041] In an embodiment of the present application, since the first vehicle data sent by the vehicle can indicate whether the corresponding vehicle is an intelligent vehicle, it is possible to determine whether the corresponding vehicle is an intelligent vehicle based on the first vehicle data, thereby determining the vehicle queue based on intelligent vehicles and non-intelligent vehicles.

[0042] Step S102: determining warning data based on the second vehicle data sent by each of the smart vehicles in the vehicle queue.

[0043] The second vehicle data includes at least the speed and distance of the corresponding smart vehicle, where the distance is the distance between the corresponding smart vehicle and the second vehicle. It should be understood that the corresponding smart vehicle referred to herein is the smart vehicle that transmits the second vehicle data. For example, the second vehicle information transmitted by the first vehicle in a vehicle queue includes the speed of the first vehicle and the distance between the first vehicle and the second vehicle.

[0044] Specifically, since non-intelligent vehicles have not undergone intelligent transformation, they cannot perceive the surrounding environment of the vehicle and realize functions such as automatic warning, while intelligent vehicles can perceive the surrounding environment and automatically calculate data related to vehicle driving, and the driving of intelligent vehicles in the vehicle queue will affect the driving of non-intelligent vehicles. Therefore, in an embodiment of the present application, the warning data of the second vehicle is determined based on the second vehicle data sent by each intelligent vehicle in the vehicle queue (i.e., the first vehicle and the third vehicle), so that the second vehicle can perform accident warning based on the warning data.

[0045] Optionally, the warning data may be data from the unprocessed second vehicle data (such as the speed and distance of each intelligent vehicle), so that the second vehicle can judge whether the second vehicle will have an accident, an accident that may occur, etc. based on the relevant driving data, so as to provide an accident warning. In this case, the warning data at least includes the vehicle distance (i.e., the distance between the first vehicle and the second vehicle and the distance between the third vehicle and the second vehicle). The warning data may also be an analysis result obtained by the data platform after directly analyzing the data of each second vehicle. The analysis result indicates whether the second vehicle will have an accident, an accident that may occur, etc., so that the second vehicle can directly provide an accident warning based on the analysis result in the warning data, without the need for the second vehicle, which is a non-intelligent vehicle, to perform analysis and judgment, thereby improving the accident warning efficiency of the second vehicle.

[0046] Optionally, the second vehicle data may also include turn signals of the vehicle in front and / or behind detected by the smart vehicle (such as the vehicle in front turning on the left turn signal), the steering data of the smart vehicle (for example, data on turning right in 10 seconds, preparing to overtake, etc.), fault conditions (such as brake failure, etc.) or other vehicle driving-related data, so that the second vehicle can know the movements of the smart vehicles in front and behind it in advance, and can make corresponding processing in time to reduce the occurrence of accidents. Correspondingly, the warning data determined based on the second vehicle data may also include the steering data, fault conditions and other vehicle driving-related data of the smart vehicle.

[0047] In an embodiment of the present application, since the intelligent vehicles in the vehicle queue are respectively located in front of and behind the non-intelligent vehicles, they have an impact on the driving of the non-intelligent vehicles, and the second vehicle data sent by the intelligent vehicles contains data such as the speed and distance of the intelligent vehicles that affect the driving of the non-intelligent vehicles. Therefore, the warning data determined based on the second vehicle data can reflect the driving accident status of the non-intelligent vehicles, so that the non-intelligent vehicles can perform accident warnings based on the warning data, reducing the risks of non-intelligent vehicles and increasing safety without the need to upgrade the non-intelligent vehicles to intelligent ones.

[0048] Step S103: sending the warning data to the second vehicle, and the second vehicle is used to issue an accident warning based on the warning data.

[0049] Specifically, after receiving the warning data, the data platform sends it in real time to the second vehicle in the vehicle queue. The second vehicle can then issue an accident warning based on the warning data sent by the data platform. Alternatively, if the warning data received by the second vehicle is the result of analysis and judgment by the data platform, directly indicating whether an accident will occur or is likely to occur, the second vehicle can directly issue an alarm for the expected or likely accident and alert the user of the second vehicle via voice. If the warning data received by the second vehicle is unprocessed data (including at least vehicle distance), the second vehicle can combine its own speed and the second vehicle data to determine whether the second vehicle will collide with the smart vehicle ahead or behind, and issue an accident warning based on the judgment result.

[0050] In the embodiment of the present application, since the intelligent vehicle can perceive the surrounding environment based on the intelligent device and calculate the data related to its driving, such as the distance between itself and the vehicles in front and behind, through the intelligent algorithm, and the intelligent vehicle in the vehicle queue containing at least 3 vehicles is located in front and behind the non-intelligent vehicle respectively, therefore, the warning data determined based on the second vehicle data including the speed and distance of the intelligent vehicle sent by the intelligent vehicles located in front and behind the non-intelligent vehicle can reflect the data related to the driving of the second vehicle, so that the second vehicle can perform accident warning based on the received warning data, and then the non-intelligent vehicle can realize accident warning without deploying intelligent hardware and algorithms, that is, the function of intelligent warning is realized without the need for intelligent upgrading of the non-intelligent vehicle, thereby providing driving safety of the non-intelligent vehicle on the basis of reducing the modification cost.

[0051] In some embodiments, the above step S101 includes:

[0052] A1. For each of the at least three vehicles, receive first vehicle data sent by the vehicle during driving.

[0053] A2. For each received first vehicle data, determine whether the vehicle corresponding to the first vehicle data is the non-intelligent vehicle or the intelligent vehicle.

[0054] A3. Determine the non-intelligent vehicle and the intelligent vehicle that satisfy a target position relationship based on the determined intelligent vehicle and the determined non-intelligent vehicle, where the target position relationship is that the non-intelligent vehicle is located between the two intelligent vehicles.

[0055] A4. Determine the corresponding vehicle queue based on the non-intelligent vehicles and the intelligent vehicles that satisfy the target position relationship.

[0056] Specifically, to improve the safety of non-intelligent vehicles while driving, the system receives in real time first vehicle data transmitted by each of at least three vehicles while driving. Based on each received first vehicle data, the system determines whether the vehicle corresponding to the first vehicle is a non-intelligent vehicle or an intelligent vehicle based on the information carried in the first vehicle data, thereby determining each intelligent vehicle and each non-intelligent vehicle in the transmission of the first vehicle data. Optionally, the first vehicle data can be data acquired in real time by the corresponding vehicle, thereby improving the real-time nature of the first vehicle data and, therefore, the real-time nature of subsequent accident warnings.

[0057] After determining the intelligent and non-intelligent vehicles, a non-intelligent vehicle and an intelligent vehicle that satisfy a target position relationship are determined based on the determined intelligent and non-intelligent vehicles. The target position relationship is that the non-intelligent vehicle is located between two intelligent vehicles. After determining the non-intelligent vehicle and the intelligent vehicle that satisfy the target position relationship, a vehicle queue corresponding to the non-intelligent vehicle is determined based on the non-intelligent vehicle and the intelligent vehicle that satisfy the target position relationship.

[0058] For example, assuming that the first vehicle data sent by vehicles A, B, C, D, and E are received respectively, it is determined that the intelligent vehicles include vehicle A, vehicle C, and vehicle D, and the non-intelligent vehicles include vehicle B and vehicle E according to each first vehicle data. Among them, it is judged that the intelligent vehicle A is in front of the non-intelligent vehicle B, and the intelligent vehicle C is behind the non-intelligent vehicle B, that is, the non-intelligent vehicle B is located between the two intelligent vehicles (vehicle A and vehicle C), indicating that the position relationship between the intelligent vehicle A, the non-intelligent vehicle B, and the intelligent vehicle C meets the target position relationship, and the non-intelligent vehicle B and two intelligent vehicles (vehicle A and vehicle C) that meet the target position relationship are obtained. Then, the vehicle queue corresponding to the non-intelligent vehicle B is determined according to the intelligent vehicle A, the non-intelligent vehicle B, and the intelligent vehicle C.

[0059] In the embodiment of the present application, since the received first vehicle data is data sent in real time by the vehicle during driving, the vehicles in the determined vehicle queue are all vehicles in driving state, so that when accident warnings are subsequently issued to non-intelligent vehicles, accident warnings are issued to non-intelligent vehicles in driving process, thereby improving the safety of non-intelligent vehicles in driving process. Moreover, the non-intelligent vehicle in the vehicle queue is located between two intelligent vehicles, and data from different directions of the non-intelligent vehicle can be obtained for accident warning, thereby improving the comprehensiveness and accuracy of the accident warning.

[0060] In some embodiments, when the vehicle is a non-intelligent vehicle, the first vehicle data includes the license plate number of the non-intelligent vehicle; when the vehicle is an intelligent vehicle, the first vehicle data includes the license plate number of the intelligent vehicle and the license plate number of the vehicle in front of the intelligent vehicle and / or the license plate number of the vehicle behind the intelligent vehicle. Correspondingly, the above step A3 includes:

[0061] A31. Determine whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the intelligent vehicles, and determine whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle behind another of the intelligent vehicles.

[0062] A32. If the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the intelligent vehicles, and is the same as the license plate number of the vehicle behind another of the intelligent vehicles, then it is determined that the non-intelligent vehicle is between the two intelligent vehicles, and the non-intelligent vehicle and the two intelligent vehicles satisfying the target position relationship are obtained.

[0063] Specifically, in order to improve the accuracy of the vehicle queue, in some embodiments, when a vehicle sends first vehicle data to the data platform, it is required to add its own license plate number to the first vehicle data, and the intelligent vehicle is required to add the license plate number of the vehicle in front of the intelligent vehicle and / or the license plate number of the vehicle behind the intelligent vehicle to the first vehicle data. When determining the non-intelligent vehicle and the intelligent vehicle that meet the target position relationship based on the determined intelligent vehicle and non-intelligent vehicle, based on the license plate number of the non-intelligent vehicle, the license plate number that is the same as the license plate number of the non-intelligent vehicle is found from the license plate numbers of the vehicles in front of and behind each intelligent vehicle, that is, it is determined whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of an intelligent vehicle (the front license plate number), and it is determined whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle behind another intelligent vehicle (the rear license plate number).

[0064] For example, suppose the license plate number of a non-intelligent vehicle is A, and the license plate numbers of the vehicles in front of the three intelligent vehicles (B, C, D) are B1, C1 and D1 respectively, and the license plate numbers of the vehicles behind them are B2, C2 and D2 respectively. When finding the license plate number that is the same as the license plate number of the non-intelligent vehicle from the license plates of the vehicles in front and behind of the three intelligent vehicles, first determine whether the license plate numbers B1, C1 and D1 of the vehicles in front are the same as license plate number A, and obtain the license plate number C1 of the vehicle in front of the intelligent vehicle C is the same as the license plate number of the non-intelligent vehicle A. Then determine whether the license plate numbers B2 and D2 of the vehicles behind are the same as license plate number A, and obtain the license plate number D2 of the vehicle behind the intelligent vehicle D is the same as the license plate number of the non-intelligent vehicle A.

[0065] Optionally, the license plate number of the vehicle in front and / or the license plate number of the vehicle behind the smart vehicle in the first vehicle data received from the smart vehicle may be obtained by the smart vehicle using an intelligent algorithm such as image recognition or image detection based on collected video data. It is understood that if there is no vehicle in front of or behind the smart vehicle, the license plate number of the vehicle in front or behind will not be included in the first vehicle data of the smart vehicle.

[0066] In an embodiment of the present application, since the first vehicle data sent by the intelligent vehicle includes the license plate number of the vehicle in front and / or the license plate number of the vehicle behind it, and the first vehicle data sent by the non-intelligent vehicle includes its own license plate number, it is possible to accurately determine whether the non-intelligent vehicle is located between two intelligent vehicles based on the license plate numbers of each vehicle in front and each vehicle behind, thereby obtaining a vehicle queue that meets the target position relationship.

[0067] In some embodiments, when the vehicle is the smart vehicle, the first vehicle data also includes the location information of the smart vehicle. Before step A31, the following steps may be performed:

[0068] Determine two adjacent smart vehicles based on the position information of the smart vehicles to obtain the target vehicle set.

[0069] or,

[0070] If the above-mentioned first vehicle data of the above-mentioned non-intelligent vehicle also includes the location information of the above-mentioned non-intelligent vehicle, the target area is determined according to the above-mentioned location information of the above-mentioned non-intelligent vehicle, and the above-mentioned intelligent vehicle located in the above-mentioned target area is determined according to the above-mentioned location information of the above-mentioned intelligent vehicle to obtain the target vehicle set.

[0071] Correspondingly, the above step A31 includes:

[0072] Determine whether the license plate number of the above-mentioned non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the above-mentioned intelligent vehicles in the above-mentioned target vehicle set, and determine whether the license plate number of the above-mentioned non-intelligent vehicle is the same as the license plate number of the vehicle behind another of the above-mentioned intelligent vehicles in the above-mentioned target vehicle set.

[0073] Specifically, in order to further improve the efficiency of determining vehicle queues, when judging whether the license plate number of a non-intelligent vehicle is the same as the license plate number of the vehicle in front of or behind the intelligent vehicle, the two adjacent intelligent vehicles can be first determined based on the position information of the intelligent vehicle in the first vehicle data to obtain a target vehicle set (only including these two adjacent intelligent vehicles), and then judge whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of an intelligent vehicle in the target vehicle set, and whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle behind another intelligent vehicle in the target vehicle set.

[0074] Alternatively, if some non-intelligent vehicles have positioning functions and their first vehicle data contains the location information of the non-intelligent vehicle, for the non-intelligent vehicles whose first vehicle data contains location information, a target area can be first determined based on the location information of the non-intelligent vehicle (for example, a circular area with a radius of 500 meters centered on the location of the non-intelligent vehicle), and then the intelligent vehicles located in the target area are determined based on the location information of each intelligent vehicle, and regarded as a target vehicle set (including all intelligent vehicles in the target area). It is then determined whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of an intelligent vehicle in the target vehicle set, and whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle behind another intelligent vehicle in the target vehicle set.

[0075] In an embodiment of the present application, it is only determined whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of or behind the intelligent vehicle in the determined target vehicle set. There is no need to compare it with the license plate numbers of the vehicles in front of or behind all intelligent vehicles, thereby improving the efficiency of determining the vehicle queue and further improving the efficiency of accident warning for non-intelligent vehicles.

[0076] In some embodiments, step A4 includes:

[0077] For the non-intelligent vehicle and the corresponding two intelligent vehicles that satisfy the target position relationship, the vehicle distance between the non-intelligent vehicle and the two intelligent vehicles is obtained.

[0078] Optionally, when obtaining the distance between the non-intelligent vehicle and the two corresponding intelligent vehicles, the intelligent vehicle can be instructed to obtain the distance between the intelligent vehicle and the vehicle in front and behind using distance sensors or image detection methods when sending the first vehicle data, and the obtained distance can be added to the first vehicle data. The data platform can then obtain the distance between the non-intelligent vehicle and the intelligent vehicle in the first vehicle data. Alternatively, when it is necessary to obtain the distance between the non-intelligent vehicle and the intelligent vehicle, a command can be sent to the corresponding intelligent vehicle, causing the corresponding intelligent vehicle to obtain the distance between itself and the non-intelligent vehicle and send the obtained distance to the data platform.

[0079] If the distance between the non-intelligent vehicle and the two intelligent vehicles is less than or equal to a preset threshold, the non-intelligent vehicle is used as the second vehicle, and the first vehicle and the third vehicle are determined based on the two intelligent vehicles to obtain the vehicle queue.

[0080] Specifically, since the range of perception that intelligent vehicles can have is limited, relevant data cannot be detected well for vehicles outside a certain distance. Therefore, in order to improve the accuracy of accident warnings for non-intelligent vehicles, in an embodiment of the present application, when determining a vehicle queue based on a non-intelligent vehicle that meets the target position relationship and the two intelligent vehicles corresponding to the non-intelligent vehicle, the distance between the non-intelligent vehicle and the two intelligent vehicles is obtained. If the distance between the non-intelligent vehicle and each of the two intelligent vehicles is less than or equal to a preset threshold (such as 100 meters), it is considered that the non-intelligent vehicle and the two intelligent vehicles can be used as a vehicle queue. At this time, the non-intelligent vehicle is regarded as the second vehicle, the intelligent vehicle located in front of the non-intelligent vehicle among the two intelligent vehicles is regarded as the first vehicle, and the intelligent vehicle located behind the non-intelligent vehicle is regarded as the third vehicle, and the vehicle queue corresponding to the non-intelligent vehicle is obtained.

[0081] Optionally, when the distance between the non-intelligent vehicle and one of the two intelligent vehicles is less than or equal to a preset threshold, and the distance between the non-intelligent vehicle and the other intelligent vehicle is greater than the preset threshold, because only the distance between one of the intelligent vehicles and the non-intelligent vehicle does not meet the preset threshold, at this time, a second judgment can be made on the distance between the intelligent vehicle and the non-intelligent vehicle after waiting for a preset time (such as 3 seconds). If the distance between the intelligent vehicle and the non-intelligent vehicle is still greater than the preset threshold in the second judgment, the vehicle queue is disbanded. If the result of the second judgment indicates that the distance between the non-intelligent vehicle and each of the two intelligent vehicles is less than or equal to the preset threshold, the three vehicles can be determined as a vehicle queue.

[0082] In an embodiment of the present application, after obtaining a non-intelligent vehicle and two intelligent vehicles that meet the target position relationship, they are combined into a vehicle queue when the distance between the non-intelligent vehicle and the intelligent vehicles in front and behind it is less than or equal to the preset threshold. Therefore, the intelligent vehicles in the vehicle queue can better detect the data related to the non-intelligent vehicle, thereby improving the accuracy of the obtained second vehicle data, and further improving the accuracy of the accident warning of the non-intelligent vehicle.

[0083] In some embodiments, the above step S102 includes:

[0084] The front pre-collision time of the second vehicle is calculated according to the speed of the second vehicle, the speed of the first vehicle, and the vehicle distance corresponding to the first vehicle.

[0085] The rear pre-collision duration of the second vehicle is calculated according to the speed of the second vehicle, the speed of the third vehicle, and the vehicle distance corresponding to the third vehicle.

[0086] The warning data is determined according to the front pre-collision time and the rear pre-collision time.

[0087] Specifically, to further improve the efficiency of accident warning, when determining the warning data of the second vehicle based on the second vehicle data, the data platform directly performs accident analysis on the second vehicle based on the second vehicle data and determines the warning data based on the analysis results. The collision accident data is analyzed based on the speed of the second vehicle and the speed and distance of each intelligent vehicle. That is, the front pre-collision time of the second vehicle is calculated based on the speed of the second vehicle, the speed of the first vehicle, and the corresponding distance of the first vehicle (i.e., the distance between the first and second vehicles). The front pre-collision time can indicate the time required for the second vehicle to collide with the first vehicle at the current speed. At the same time, the rear pre-collision time of the second vehicle is calculated based on the speed of the second vehicle, the speed of the third vehicle, and the corresponding distance of the third vehicle. The rear pre-collision time can indicate the time required for the second vehicle to be collided with the third vehicle at the current speed. After calculating the front and rear pre-collision times of the second vehicle, the front and rear pre-collision times are compared with a first collision time threshold (e.g., 20 seconds). If the front and / or rear pre-collision times are less than the first collision time threshold, a warning message, such as an impending collision with the vehicle ahead and / or vehicle behind, may be generated. A corresponding response suggestion (e.g., increasing the vehicle speed to between 80 and 90 kilometers per hour) may also be provided in response to the warning message. Warning data is determined based on one or more of the following data: the front and rear pre-collision times, the speed of the first vehicle, the corresponding distance between the first vehicle and the warning message, the response suggestion, and the warning data. The warning data includes at least the warning message, so that the second vehicle can clearly understand the potential accident. Optionally, if the front and / or rear pre-collision times are greater than or equal to the first collision time threshold, the front and / or rear pre-collision times may be used as the warning message.

[0088] Optionally, since there may be other vehicles in front of the first vehicle during the actual driving process of the vehicle queue, this will have a certain impact on the driving of the vehicle queue. Therefore, in some embodiments, when there is a vehicle in front of the first vehicle, the second vehicle data sent by the first vehicle also includes the length of the first vehicle (i.e., the length of the vehicle body) and the distance between the first vehicle and the vehicle in front of it (the distance in front). When determining the warning data based on the second vehicle data, the pre-collision time of the second vehicle outside the team can be calculated based on the speed of the first vehicle, the distance corresponding to the first vehicle, the speed of the second vehicle, and the distance in front. The pre-collision time of the vehicle outside the team can indicate the time required for the second vehicle to collide with the vehicle in front of the first vehicle. When the pre-collision time of the vehicle outside the team is less than the second collision time threshold (such as 30s), a corresponding warning message is generated based on the pre-collision time of the vehicle outside the team. Among them, the pre-collision time of the vehicle outside the team is:

[0089]

[0090] FD1 is the distance between the first vehicle and the second vehicle, FFD is the distance between the first vehicle and the vehicle in front of it, CL1 is the length of the first vehicle, C1 is the speed of the first vehicle, and C2 is the speed of the second vehicle.

[0091] In some embodiments, the second vehicle data sent by the first vehicle and / or the third vehicle in the vehicle queue also includes the side distance of the second vehicle (including the left side distance and right side distance of the front and rear of the vehicle, respectively) and the turn signal (such as a left turn signal). When determining the warning data based on the second vehicle data, the length of the second vehicle is also obtained, and the lane departure accident of the second vehicle (such as the vehicle body crossing the line, driving out of the current lane) is analyzed based on the length, side distance, turn signal and speed of the second vehicle. If the turn signal indicates that the second vehicle is not turning (that is, the second vehicle does not give a turn signal), the deviation time of the second vehicle deviating from the lane is calculated based on the speed and side distance of the second vehicle, and when the deviation time is greater than the deviation time threshold (such as 3s), a corresponding warning message is generated (such as the vehicle will deviate from the lane from the left after the deviation time). When the body posture of the second vehicle is biased to the right, the deviation time is as follows:

[0092]

[0093] When the second vehicle's body posture deviates to the left, the deviation duration is as follows:

[0094]

[0095] Among them, such as Figure 2 In the vehicle queue shown, RF is the right side distance of the front of the second vehicle, LF is the left side distance of the front of the second vehicle, RB is the right side distance of the rear of the second vehicle, LB is the left side distance of the rear of the second vehicle, CL2 is the length of the second vehicle, and C2 is the speed of the second vehicle.

[0096] The second vehicle's body posture can be the posture of the second vehicle identified by the first and / or third vehicles using a posture recognition model or algorithm, and the identified second vehicle's body posture is incorporated into the second vehicle data. The second vehicle data, including distance, side distance, and turn signal data, is calculated by the corresponding intelligent vehicle using image recognition, distance detection, or other models or intelligent algorithms. This is conventional technology and will not be further elaborated upon here.

[0097] In an embodiment of the present application, when the warning data is determined based on the second vehicle data, the accident analysis of the second vehicle is performed directly based on the second vehicle data, and the warning data is determined based on the analysis results, so that the subsequent second vehicle can be warned directly based on the warning data, and there is no need to make a judgment based on the second vehicle data belonging to the non-intelligent vehicle, thereby reducing the equipment requirements for the non-intelligent vehicle and improving the accident warning efficiency of the non-intelligent vehicle.

[0098] In some embodiments, the above method further comprises:

[0099] During the driving process of the second vehicle, if the distance between the second vehicle and the first vehicle is greater than the preset threshold, and / or if the distance between the second vehicle and the third vehicle is greater than the preset threshold, the vehicle queue corresponding to the second vehicle is disbanded.

[0100] Specifically, while the second vehicle in a vehicle queue is traveling, the distances between the second vehicle and the first and second vehicles are detected at a preset detection interval (e.g., every 5 seconds). If both the distances between the second vehicle and the first vehicle and the distances between the second vehicle and the third vehicle are greater than a preset threshold (e.g., 120 meters, which may be different from the threshold preset when determining a vehicle queue), the vehicle queue corresponding to the second vehicle is disbanded, and a new vehicle queue is determined for the second vehicle (a non-intelligent vehicle) that includes the non-intelligent vehicle. If only the distance between the second vehicle and the first vehicle is greater than the preset threshold, or only the distance between the second vehicle and the third vehicle is greater than the preset threshold, the vehicle queue corresponding to the second vehicle is also disbanded, and a new vehicle queue is determined for the second vehicle. Optionally, when only the distance between the second vehicle and the first vehicle or the distance between the second vehicle and the third vehicle is greater than the preset threshold, because only the distance between one smart vehicle and the second vehicle does not meet the preset threshold, at this time, a second judgment can be made on the distance between the smart vehicle and the second vehicle after waiting for a preset period of time. If the distance between the smart vehicle and the second vehicle is still greater than the preset threshold, the vehicle queue is disbanded. If the result of the second judgment indicates that the distance between the smart vehicle and the second vehicle is less than or equal to the preset threshold, there is no need to disband the vehicle queue.

[0101] In an embodiment of the present application, the distance between a non-intelligent vehicle and an intelligent vehicle in a vehicle queue during driving is detected to ensure that the two intelligent vehicles can better collect the second vehicle data during driving, improve the accuracy of the second vehicle data, and thus improve the accuracy of accident warnings and the safety of non-intelligent vehicles.

[0102] In some embodiments, the number of vehicles in a specific application scenario where there is a transport fleet is usually large, and the positional relationship of the vehicles in the fleet is usually unchanged. Therefore, while satisfying the target positional relationship of the vehicles in the vehicle queue (the non-intelligent vehicle is located between two intelligent vehicles), the vehicle queue may also include more than 3 vehicles. It is understandable that the number of vehicles included in the vehicle queue is 2n+1 (n is greater than or equal to 1), where n is the number of non-intelligent vehicles in the vehicle queue, and the position of the non-intelligent vehicle in the vehicle queue is 2n (for example, the vehicle queue contains 2 non-intelligent vehicles, that is, the vehicle queue includes a total of 5 vehicles, of which the second and fourth vehicles are non-intelligent vehicles). In the embodiment of the present application, a vehicle queue containing three vehicles is used for illustration.

[0103] It can be understood that when the number of vehicles contained in the vehicle queue (2n+1, n is a non-intelligent vehicle) is greater than 3, that is, the number of non-intelligent vehicles in the vehicle queue is greater than 1, when obtaining the second vehicle data to determine the warning data of the non-intelligent vehicle, the warning data of the non-intelligent vehicle is determined based on the intelligent vehicles located in front and behind the non-intelligent vehicle. For example, assume that a vehicle queue contains five vehicles in sequence: A, B, C, D, and E, where vehicle B and vehicle D are non-intelligent vehicles. When determining the warning data of vehicle B and vehicle D, vehicle A, vehicle C, and vehicle E determine the warning data of vehicle B based on the second vehicle data related to vehicle B collected by vehicle A and vehicle C (at this time, vehicle A can be regarded as the first vehicle, vehicle B can be regarded as the second vehicle, and vehicle C can be regarded as the third vehicle), and determine the warning data of vehicle D based on the second vehicle data related to vehicle D collected by vehicle C and vehicle D (at this time, vehicle C can be regarded as the first vehicle, vehicle D can be regarded as the second vehicle, and vehicle E can be regarded as the third vehicle). The data platform receives two different second vehicle data sent by vehicle C (i.e., the second vehicle data related to vehicle B and the second vehicle data related to vehicle D).

[0104] Figure 3 A flow chart of a vehicle monitoring method for an intelligent vehicle in a vehicle queue provided by an embodiment of the present application is shown. The intelligent vehicle is a first vehicle or a third vehicle. The vehicle queue also includes a second vehicle located between the first vehicle and the third vehicle. The second vehicle is a non-intelligent vehicle. The method is described in detail as follows:

[0105] Step S301: Determine second vehicle data of the smart vehicle, where the second vehicle data includes a vehicle distance and a speed of the smart vehicle. The vehicle distance is the distance between the smart vehicle and the second vehicle.

[0106] Specifically, the smart vehicle obtains its own speed and the real-time distance between it and a second vehicle in real time while driving, obtains the distance between the smart vehicle and the second vehicle, and obtains the second vehicle data of the smart vehicle based on the speed and distance. For example, if the second vehicle data of a first vehicle needs to be determined, the speed of the first vehicle and the distance between the first vehicle and the second vehicle need to be obtained to obtain the distance. Optionally, when obtaining the second vehicle data of the smart vehicle, the second vehicle data can be obtained every preset time interval (e.g., 3 seconds).

[0107] Optionally, the above-mentioned second vehicle data also includes the length of the first vehicle, turning data (such as turning right in 10 seconds, preparing to overtake, etc.), fault conditions and other driving-related data of the second vehicle, as well as the second vehicle's turn signal, side distance and other second vehicle-related data, to increase data diversity for better accident warning.

[0108] In some embodiments, since the smart vehicle is equipped with a camera for sensing the surrounding environment and can capture vehicles in front of and behind the smart vehicle, in embodiments of the present application, when acquiring the second vehicle data, the video data of the second vehicle captured by the camera on the smart vehicle is acquired, and the distance between the smart vehicle and the second vehicle is calculated based on the video data to obtain the required vehicle distance. When it is necessary to add the side distance and turn signal of the second vehicle to the second vehicle data, the distance from the front or rear of the second vehicle to the lane lines on both sides is calculated based on the second vehicle in the video data to obtain the side distance of the second vehicle (including the left side distance and right side distance of the front or rear of the vehicle). At the same time, image recognition or target detection is performed based on the video data to detect whether the second vehicle has a turn signal in the video frame, as well as the turning direction indicated by the turn signal, to obtain the turn signal of the second vehicle. It is understandable that when the smart vehicle is the first vehicle, the side distance acquired is the left side distance and right side distance of the front of the second vehicle, and when the smart vehicle is the second vehicle, the side distance acquired is the left side distance and right side distance of the rear of the second vehicle.

[0109] In an embodiment of the present application, the intelligent vehicle obtains its own speed, distance and other data in real time to obtain real-time second vehicle data, so that the warning data subsequently determined based on the second vehicle data has better real-time performance.

[0110] Step S302: Send the second vehicle data to a data platform, and the data platform is used to determine the warning data of the second vehicle based on the second vehicle data.

[0111] In an embodiment of the present application, since the second vehicle data is data related to the driving of the second vehicle, when the real-time second vehicle data is obtained, the second vehicle data is sent to the data platform in real time. The data platform can determine the warning data of the second vehicle based on the second vehicle data obtained in real time, so as to provide accident warning for the second vehicle, which is a non-intelligent vehicle, thereby improving the efficiency of accident warning and improving the safety of the second vehicle.

[0112] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0113] Example 2:

[0114] Corresponding to the vehicle monitoring method applied to the data platform described in the above embodiment, Figure 4 A structural block diagram of a vehicle monitoring device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0115] Reference Figure 4 The device includes: a vehicle queue determination module 41, a warning data acquisition module 42, and a sending module 43.

[0116] a vehicle queue determining module 41 configured to determine a vehicle queue based on first vehicle data transmitted by at least three vehicles, wherein the first vehicle data can indicate whether the corresponding vehicle is an intelligent vehicle, the vehicle queue comprising, in order, a first vehicle, a second vehicle, and a third vehicle, wherein the second vehicle is a non-intelligent vehicle, and the first vehicle and the third vehicle are both intelligent vehicles;

[0117] a warning data acquisition module 42 for determining warning data based on second vehicle data transmitted by each of the smart vehicles in the vehicle queue, wherein the second vehicle data includes at least a speed and a vehicle distance of the corresponding smart vehicle, wherein the vehicle distance is the distance between the corresponding smart vehicle and the second vehicle;

[0118] The sending module 43 is used to send the above-mentioned warning data to the above-mentioned second vehicle, and the above-mentioned second vehicle is used to issue an accident warning based on the above-mentioned warning data.

[0119] In the embodiment of the present application, since the intelligent vehicle can perceive the surrounding environment based on the intelligent device and calculate the data related to its driving, such as the distance between itself and the vehicles in front and behind, through the intelligent algorithm, and the intelligent vehicle in the vehicle queue containing at least 3 vehicles is located in front and behind the non-intelligent vehicle respectively, therefore, the warning data determined based on the second vehicle data including the speed and distance of the intelligent vehicle sent by the intelligent vehicles located in front and behind the non-intelligent vehicle can reflect the data related to the driving of the second vehicle, so that the second vehicle can perform accident warning based on the received warning data, and then the non-intelligent vehicle can realize accident warning without deploying intelligent hardware and algorithms, that is, the function of intelligent warning is realized without the need for intelligent upgrading of the non-intelligent vehicle, thereby providing driving safety of the non-intelligent vehicle on the basis of reducing the modification cost.

[0120] In some embodiments, the vehicle queue determination module 41 includes:

[0121] The first vehicle data receiving unit is configured to receive, from each of the at least three vehicles, first vehicle data sent by the vehicle during its driving process.

[0122] The vehicle classification unit is used to determine, for each received first vehicle data, whether the vehicle corresponding to the first vehicle data belongs to the non-intelligent vehicle or the intelligent vehicle.

[0123] The vehicle position relationship determination unit is used to determine the above-mentioned non-intelligent vehicle and the above-mentioned intelligent vehicle that meet the target position relationship based on the determined above-mentioned intelligent vehicle and the above-mentioned non-intelligent vehicle, and the above-mentioned target position relationship is that the above-mentioned non-intelligent vehicle is located between the two above-mentioned intelligent vehicles.

[0124] The vehicle queue determination unit is used to determine the corresponding vehicle queue based on the non-intelligent vehicles and the intelligent vehicles that meet the target position relationship.

[0125] In some embodiments, the vehicle queue determination module 41 further includes:

[0126] The first license plate number judgment unit is used to judge whether the license plate number of the above-mentioned non-intelligent vehicle is the same as the license plate number of the vehicle in front of the above-mentioned intelligent vehicle, and to judge whether the license plate number of the above-mentioned non-intelligent vehicle is the same as the license plate number of the vehicle behind another above-mentioned intelligent vehicle.

[0127] The vehicle determination unit is used to determine that the non-intelligent vehicle is between the two intelligent vehicles if the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the intelligent vehicles and the same as the license plate number of the vehicle behind another of the intelligent vehicles, thereby obtaining the non-intelligent vehicle and the two intelligent vehicles that satisfy the target position relationship.

[0128] In some embodiments, the vehicle queue determination module 41 further includes:

[0129] The first set acquisition unit is configured to determine two adjacent smart vehicles according to the position information of the smart vehicles to obtain the target vehicle set.

[0130] The second set acquisition unit is used to determine the target area according to the above-mentioned position information of the above-mentioned non-intelligent vehicle if the above-mentioned first vehicle data of the above-mentioned non-intelligent vehicle also includes the position information of the above-mentioned non-intelligent vehicle, and determine the above-mentioned intelligent vehicle located in the above-mentioned target area according to the above-mentioned position information of the above-mentioned intelligent vehicle to obtain the target vehicle set.

[0131] The second license plate number judgment unit is used to judge whether the license plate number of the above-mentioned non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the above-mentioned intelligent vehicles in the above-mentioned target vehicle set, and to judge whether the license plate number of the above-mentioned non-intelligent vehicle is the same as the license plate number of the vehicle behind another of the above-mentioned intelligent vehicles in the above-mentioned target vehicle set.

[0132] In some embodiments, the vehicle queue determination module 41 further includes:

[0133] The vehicle distance acquisition unit is used to obtain the vehicle distance between the non-intelligent vehicle and the corresponding two intelligent vehicles that meet the target position relationship.

[0134] The vehicle queue acquisition unit is configured to, if the distance between the non-intelligent vehicle and the two intelligent vehicles is less than or equal to a preset threshold, use the non-intelligent vehicle as the second vehicle, determine the first vehicle and the third vehicle based on the two intelligent vehicles, and obtain the vehicle queue.

[0135] In some embodiments, the warning data acquisition module 42 includes:

[0136] The front pre-collision time calculation unit is used to calculate the front pre-collision time of the second vehicle according to the speed of the second vehicle, the speed of the first vehicle and the vehicle distance corresponding to the first vehicle.

[0137] The rear pre-collision time calculation unit is used to calculate the rear pre-collision time of the second vehicle according to the speed of the second vehicle, the speed of the third vehicle and the vehicle distance corresponding to the third vehicle.

[0138] The warning data acquisition unit is used to determine the warning data according to the front pre-collision time and the rear pre-collision time.

[0139] In some embodiments, the vehicle monitoring device further includes:

[0140] The vehicle queue monitoring module is configured to disband the vehicle queue corresponding to the second vehicle if, during the driving process of the second vehicle, the distance between the second vehicle and the first vehicle is greater than the preset threshold, and / or if the distance between the second vehicle and the third vehicle is greater than the preset threshold.

[0141] Corresponding to the vehicle monitoring method for intelligent vehicles in a vehicle queue described in the above embodiment, Figure 5 A structural block diagram of a vehicle monitoring device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0142] Reference Figure 5 The device includes: a second vehicle data acquisition module 51 and a data sending module 52.

[0143] A second vehicle data acquisition module 51 is configured to determine second vehicle data of the smart vehicle, wherein the second vehicle data includes a vehicle distance and a speed of the smart vehicle, wherein the vehicle distance is the distance between the smart vehicle and the second vehicle;

[0144] The data sending module 52 is used to send the second vehicle data to a data platform, and the data platform is used to determine the warning data of the second vehicle based on the second vehicle data.

[0145] In an embodiment of the present application, since the second vehicle data is data related to the driving of the second vehicle, when the real-time second vehicle data is obtained, the second vehicle data is sent to the data platform in real time. The data platform can determine the warning data of the second vehicle based on the second vehicle data to perform accident warning for the second vehicle, which is a non-intelligent vehicle, thereby improving the efficiency of accident warning and improving the safety of the second vehicle.

[0146] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0147] Example 3:

[0148] Figure 6 This is a schematic diagram of the structure of a terminal device provided in one embodiment of the present application. Figure 6 As shown, the terminal device 6 of this embodiment includes: at least one processor 60 ( Figure 6Only one processor is shown in the figure), a memory 61, and a computer program 62 stored in the memory 61 and executable on the at least one processor 60, wherein the processor 60 implements the steps of any of the above-mentioned method embodiments when executing the computer program 62.

[0149] The terminal device 6 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that Figure 6 It is only an example of the terminal device 6 and does not constitute a limitation on the terminal device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0150] The processor 60 may be a central processing unit (CPU), or 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, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0151] In some embodiments, the memory 61 may be an internal storage unit of the terminal device 6, such as a hard disk or memory of the terminal device 6. In other embodiments, the memory 61 may also be an external storage device of the terminal device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 6. Furthermore, the memory 61 may also include both an internal storage unit of the terminal device 6 and an external storage device. The memory 61 is used to store an operating system, application programs, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store data that has been output or is about to be output.

[0152] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0153] An embodiment of the present application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps of any of the above-mentioned method embodiments when executing the computer program.

[0154] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented.

[0155] An embodiment of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0156] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process of the above-mentioned method embodiment by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can at least include: any entity or device capable of carrying computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, mobile hard drive, magnetic disk, or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0157] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0158] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0159] In the embodiments provided in this application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0160] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0161] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A vehicle monitoring method, applied to a data platform, characterized in that: include: Determining a vehicle queue based on first vehicle data sent by at least three vehicles, wherein the first vehicle data can indicate whether a corresponding vehicle is an intelligent vehicle, the vehicle queue sequentially comprising a first vehicle, a second vehicle, and a third vehicle, wherein the second vehicle is a non-intelligent vehicle, and the first vehicle and the third vehicle are both intelligent vehicles; Determining warning data based on second vehicle data sent by each of the smart vehicles in the vehicle queue, wherein the second vehicle data includes at least a speed and a distance between the corresponding smart vehicle, where the distance is the distance between the corresponding smart vehicle and the second vehicle; sending the warning data to the second vehicle, the second vehicle being configured to perform an accident warning according to the warning data; The determining of the vehicle queue based on the first vehicle data sent by at least three vehicles includes: For each of the at least three vehicles, receiving first vehicle data sent by the vehicle during driving; For each received first vehicle data, determining whether the vehicle corresponding to the first vehicle data belongs to the non-intelligent vehicle or the intelligent vehicle; Determining, based on the determined intelligent vehicle and the determined non-intelligent vehicle, the non-intelligent vehicle and the intelligent vehicle that satisfy a target position relationship, wherein the target position relationship is that the non-intelligent vehicle is located between the two intelligent vehicles; Determining the vehicle queue according to the non-intelligent vehicle and the corresponding two intelligent vehicles that meet the target position relationship; When the vehicle is the non-intelligent vehicle, the first vehicle data includes the license plate number of the non-intelligent vehicle; when the vehicle is the intelligent vehicle, the first vehicle data includes the license plate number of the intelligent vehicle and the license plate number of the vehicle in front of the intelligent vehicle and / or the license plate number of the vehicle behind the intelligent vehicle. The determining of the non-intelligent vehicle and the intelligent vehicle that satisfy the target position relationship based on the determined intelligent vehicle and the non-intelligent vehicle includes: Determining whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle in front of the intelligent vehicle, and determining whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle behind another intelligent vehicle; If the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the intelligent vehicles, and is the same as the license plate number of the vehicle behind another of the intelligent vehicles, then it is determined that the non-intelligent vehicle is between the two intelligent vehicles, and the non-intelligent vehicle and the two intelligent vehicles that satisfy the target position relationship are obtained.

2. The vehicle monitoring method according to claim 1, wherein: When the vehicle is the smart vehicle, the first vehicle data further includes location information of the smart vehicle, and before determining whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle in front of the smart vehicle, and determining whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle behind another smart vehicle, further comprising: Determine two adjacent smart vehicles according to the position information of the smart vehicles to obtain a target vehicle set, or, If the first vehicle data of the non-intelligent vehicle also includes location information of the non-intelligent vehicle, determining a target area according to the location information of the non-intelligent vehicle, and determining the intelligent vehicle located in the target area according to the location information of the intelligent vehicle, to obtain the target vehicle set; The determining whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle in front of the intelligent vehicle, and determining whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle behind another intelligent vehicle, includes: Determine whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the intelligent vehicles in the target vehicle set, and determine whether the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle behind another of the intelligent vehicles in the target vehicle set.

3. The vehicle monitoring method according to claim 1, wherein: The determining the vehicle queue according to the non-intelligent vehicle and the corresponding two intelligent vehicles that satisfy the target position relationship includes: For the non-intelligent vehicle and the corresponding two intelligent vehicles that meet the target position relationship, obtaining a distance between the non-intelligent vehicle and the two intelligent vehicles; If the distance between the non-intelligent vehicle and the two intelligent vehicles is less than or equal to a preset threshold, the non-intelligent vehicle is used as the second vehicle, and the first vehicle and the third vehicle are determined based on the two intelligent vehicles to obtain the vehicle queue.

4. The vehicle monitoring method according to claim 3, wherein: The method further comprises: During the driving of the second vehicle, if the distance between the second vehicle and the first vehicle is greater than the preset threshold, and / or if the distance between the second vehicle and the third vehicle is greater than the preset threshold, the vehicle queue corresponding to the second vehicle is disbanded.

5. The vehicle monitoring method according to any one of claims 1 to 4, characterized in that: Determining early warning data according to second vehicle data sent by each of the intelligent vehicles in the vehicle queue includes: Calculating a front pre-collision time of the second vehicle according to the speed of the second vehicle, the speed of the first vehicle, and the vehicle distance corresponding to the first vehicle; Calculating the rear pre-collision time of the second vehicle according to the speed of the second vehicle, the speed of the third vehicle, and the vehicle distance corresponding to the third vehicle; The warning data is determined according to the front pre-collision time duration and the rear pre-collision time duration.

6. A vehicle monitoring method, characterized in that: Applied to an intelligent vehicle in a vehicle platoon according to claim 1, the intelligent vehicle is a first vehicle or a third vehicle, the vehicle platoon further includes a second vehicle located between the first vehicle and the third vehicle, the second vehicle being a non-intelligent vehicle, the method comprising: Determining second vehicle data of the smart vehicle, where the second vehicle data includes a vehicle distance and a speed of the smart vehicle, where the vehicle distance is a distance between the smart vehicle and the second vehicle; The second vehicle data is sent to a data platform, and the data platform is used to determine the warning data of the second vehicle based on the second vehicle data.

7. A vehicle monitoring device, applied to a data platform, characterized in that: include: a vehicle queue determination module, configured to determine a vehicle queue based on first vehicle data transmitted by at least three vehicles, wherein the first vehicle data can indicate whether the corresponding vehicle is an intelligent vehicle, the vehicle queue comprising, in order, a first vehicle, a second vehicle, and a third vehicle, wherein the second vehicle is a non-intelligent vehicle, and the first vehicle and the third vehicle are both intelligent vehicles; a warning data acquisition module, configured to determine warning data based on second vehicle data sent by each of the smart vehicles in the vehicle queue, wherein the second vehicle data includes at least a speed and a vehicle distance of the corresponding smart vehicle, wherein the vehicle distance is the distance between the corresponding smart vehicle and the second vehicle; A sending module, configured to send the warning data to the second vehicle, and the second vehicle is configured to perform an accident warning according to the warning data; The vehicle queue determination module includes: a first vehicle data receiving unit, configured to receive, for each of the at least three vehicles, first vehicle data sent by the vehicle during driving; a vehicle classification unit, configured to determine, for each received first vehicle data, whether the vehicle corresponding to the first vehicle data belongs to the non-intelligent vehicle or the intelligent vehicle; a vehicle position relationship determining unit, configured to determine, based on the determined intelligent vehicle and the determined non-intelligent vehicle, the non-intelligent vehicle and the intelligent vehicle that satisfy a target position relationship, wherein the target position relationship is that the non-intelligent vehicle is located between the two intelligent vehicles; a vehicle queue determining unit, configured to determine the vehicle queue based on the non-intelligent vehicle and the corresponding two intelligent vehicles that satisfy the target position relationship; When the vehicle is the non-intelligent vehicle, the first vehicle data includes the license plate number of the non-intelligent vehicle; when the vehicle is the intelligent vehicle, the first vehicle data includes the license plate number of the intelligent vehicle and the license plate number of the vehicle in front of the intelligent vehicle and / or the license plate number of the vehicle behind the intelligent vehicle. The vehicle queue determination module further includes: a first license plate number determination unit, configured to determine whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle in front of the intelligent vehicle, and to determine whether the license plate number of the non-intelligent vehicle is the same as the license plate number of a vehicle behind another intelligent vehicle; A vehicle determination unit is used to determine that the non-intelligent vehicle is between the two intelligent vehicles if the license plate number of the non-intelligent vehicle is the same as the license plate number of the vehicle in front of one of the intelligent vehicles and the same as the license plate number of the vehicle behind another of the intelligent vehicles, thereby obtaining the non-intelligent vehicle and the two intelligent vehicles that satisfy the target position relationship.

8. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 5 or the method according to claim 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 or the method according to claim 6 is implemented.

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