Efficient transmission method and device for vehicle communication data, medium and product

Abstract

The embodiment of the invention relates to the technical field of communication, and discloses an efficient transmission method and device for vehicle communication data, a medium and a product. The method comprises the steps that communication data of all vehicles running on a target road are acquired, and the communication data comprise position data and speed data; under the condition that the position data and the speed data between the at least two vehicles meet a preset differential coding condition, performing differential coding on the communication data of the at least two vehicles to obtain differential coding data; determining a compression ratio according to a driving state of a vehicle in a target road, and compressing the differential coding data by using the compression ratio to obtain data to be transmitted; and transmitting the to-be-transmitted data to a receiving end, and analyzing and restoring the to-be-transmitted data by the receiving end to obtain position data and speed data of each vehicle. By adopting the scheme, the transmission efficiency of the vehicle communication data can be improved while the data can be accurately analyzed.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device, medium and product for efficiently transmitting vehicle communication data. Background Art

[0002] In recent years, with the rapid development of Internet technology, the field of autonomous driving has developed rapidly. In a typical urban traffic environment, hundreds of vehicles may pass through the same road section at the same time. These vehicles continuously generate and send location information and speed information. Due to the close distance between vehicles, a lot of information may be very similar. For example, in traffic congestion, the speeds of many vehicles are almost the same. Therefore, the traditional data processing method of processing and storing all this information separately will cause data redundancy and waste of resources, and in some cases, there will be communication congestion and the communication data of some vehicles cannot be effectively obtained. Therefore, how to efficiently transmit vehicle communication data is a technical problem for those skilled in the art. Summary of the invention

[0003] One purpose of the present application is to provide an efficient transmission method, device, medium and product for vehicle communication data, at least to solve the problem of data redundancy in vehicle communication and congestion of communication channels. The present application obtains the position data and speed data of each vehicle traveling on the target road; when the position data and speed data between at least two vehicles meet the preset differential coding conditions, the communication data of the at least two vehicles are differentially encoded to obtain differentially encoded data; the compression rate is determined according to the driving state of the vehicle on the target road, and the differentially encoded data is compressed using the compression rate to obtain the data to be transmitted; the data to be transmitted is transmitted to the receiving end, and the position data and speed data of each vehicle are obtained by parsing and restoring the data by the receiving end. By adopting this scheme, the size of vehicle communication data can be reduced by differential coding, and reasonable compression can be performed according to the compression rate determined by the driving state of the vehicle on the road, so as to improve the transmission efficiency of vehicle communication data while ensuring that the data can be accurately parsed.

[0004] To achieve the above objectives, some embodiments of the present application provide the following aspects:

[0005] In a first aspect, some embodiments of the present application further provide a method for efficiently transmitting vehicle communication data, including:

[0006] Acquiring communication data of each vehicle traveling on the target road, wherein the communication data includes position data and speed data;

[0007] When the position data and speed data between at least two vehicles meet a preset differential encoding condition, differentially encoding the communication data of the at least two vehicles to obtain differentially encoded data;

[0008] Determining a compression rate according to the driving state of the vehicle on the target road, and compressing the differentially encoded data using the compression rate to obtain data to be transmitted;

[0009] The data to be transmitted is transmitted to a receiving end, and the receiving end parses and restores the data to obtain the position data and speed data of each vehicle.

[0010] In a second aspect, some embodiments of the present application further provide an electronic device, comprising: one or more processors; and a memory storing computer program instructions, wherein the computer program instructions, when executed, cause the processor to perform the steps of the method described above.

[0011] In a third aspect, some embodiments of the present application further provide a computer-readable medium having computer program instructions stored thereon, wherein the computer program instructions can be executed by a processor to implement the method as described above.

[0012] In a fourth aspect, some embodiments of the present application further provide a computer program product, comprising a computer program / instruction, which implements the steps of the method described above when executed by a processor.

[0013] Compared with the related art, the scheme provided in the embodiment of the present application obtains the communication data of each vehicle traveling on the target road, wherein the communication data includes position data and speed data; when the position data and speed data between at least two vehicles meet the preset differential coding conditions, the communication data of the at least two vehicles are differentially encoded to obtain differentially encoded data; the compression rate is determined according to the driving state of the vehicle on the target road, and the differentially encoded data is compressed using the compression rate to obtain the data to be transmitted; the data to be transmitted is transmitted to the receiving end, and the position data and speed data of each vehicle are obtained by parsing and restoring the data at the receiving end. By adopting this scheme, the size of vehicle communication data can be reduced by differential coding, and reasonable compression can be performed according to the compression rate determined by the driving state of the vehicle on the road, so as to improve the transmission efficiency of vehicle communication data while ensuring that the data can be accurately parsed. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0015] Figure 1 An exemplary flow chart of a method for efficiently transmitting vehicle communication data according to some embodiments of the present application;

[0016] Figure 2 An exemplary flow chart of a method for efficiently transmitting vehicle communication data according to some embodiments of the present application;

[0017] Figure 3 An exemplary flow chart of a method for efficiently transmitting vehicle communication data according to some embodiments of the present application;

[0018] Figure 4 An exemplary structural diagram of the electronic device is disclosed. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] First embodiment

[0021] The first embodiment of the present application relates to an efficient transmission method for vehicle communication data. Figure 1 As shown, the method may include the following steps:

[0022] Step S101, acquiring communication data of each vehicle traveling on a target road, wherein the communication data includes position data and speed data;

[0023] The communication data may include the location data and speed data of the vehicle, and may also include other data, such as driving direction data.

[0024] The communication data can be acquired by sending the communication data through the communication module after the vehicle collects the position data and speed data, and the control system receives and analyzes the data to obtain the position data and speed data of each vehicle.

[0025] Step S102, when the position data and speed data between at least two vehicles meet a preset differential encoding condition, differential encoding is performed on the communication data of the at least two vehicles to obtain differential encoding data;

[0026] The preset differential coding condition may be that the positions are close enough or the speeds are approximately the same. Since the position data and speed data of each vehicle can be obtained, the distance between any two vehicles can be determined based on the position data of each vehicle. If the distance between some vehicles is close enough, it can be determined that the positions of these vehicles meet the preset differential coding condition. Furthermore, it can be determined whether the speeds of these vehicles are approximately the same. If the speed difference of these vehicles is also small enough, it can be determined that the speeds of these vehicles meet the preset differential coding condition.

[0027] After the preset differential coding conditions are met, the communication data of these vehicles can be differentially coded. For example, the position of a vehicle can be used as a reference, and the position of each vehicle can be calculated based on the reference position. For example, the horizontal coordinate is -5m and the vertical coordinate is +8m, which means that the vehicle is 5 meters to the left and 8 meters in front of the reference position. The speed data can also be calculated in a similar way. For example, if the speed of the reference vehicle is 50 kilometers per hour and the speed of a certain vehicle is +3, it means that the speed of this vehicle is 53 kilometers per hour.

[0028] Using the similarity of position and speed data to pre-process data in vehicle communications is an effective method. By identifying and compressing similar or nearly identical data sets, the storage and transmission requirements of data can be significantly reduced. This method is particularly suitable for convoy driving or traffic congestion, where the relative position and speed of vehicles vary little.

[0029] Step S103, determining a compression rate according to the driving state of the vehicle on the target road, and compressing the differentially encoded data using the compression rate to obtain data to be transmitted;

[0030] The driving status of the vehicle on the target road may include a traffic congestion status and a traffic smoothness status, and may also include a peak traffic period and a non-peak traffic period.

[0031] In this solution, different compression rates can be determined according to different driving conditions, so that the differentially encoded data can be compressed using the compression rates to obtain data to be transmitted.

[0032] The compression algorithm of this solution can flexibly respond to different traffic environments. For example, the accuracy of location data can be adjusted in the case of traffic congestion (peak hours) and smooth traffic (off-peak hours), so that the data compression rate can be optimized according to actual needs and efficiency can be improved.

[0033] Step S104, transmitting the data to be transmitted to a receiving end, and parsing and restoring the data by the receiving end to obtain the position data and speed data of each vehicle.

[0034] In this solution, after the transmission data is obtained, it can be transmitted to the receiving end, such as a vehicle management system, which will restore it through the reverse decompression method to accurately reconstruct the original position and original speed of each vehicle, even if the data has been compressed during the transmission process. This is critical to ensure the integrity and accuracy of the data, especially in safety-sensitive vehicle communication systems.

[0035] The technical solution provided by this embodiment is to obtain the communication data of each vehicle traveling on the target road, wherein the communication data includes position data and speed data; when the position data and speed data between at least two vehicles meet the preset differential coding conditions, the communication data of the at least two vehicles are differentially encoded to obtain differentially encoded data; a compression rate is determined according to the driving state of the vehicle on the target road, and the differentially encoded data is compressed using the compression rate to obtain data to be transmitted; the data to be transmitted is transmitted to the receiving end, and the position data and speed data of each vehicle are obtained by parsing and restoring the data at the receiving end. By adopting this solution, the size of vehicle communication data can be reduced by differential coding, and reasonable compression can be performed according to the compression rate determined by the driving state of the vehicle on the road, so as to improve the transmission efficiency of vehicle communication data while ensuring that the data can be accurately parsed.

[0036] Second embodiment

[0037] The second embodiment of the present application relates to an efficient transmission method for vehicle communication data. This embodiment optimizes the above embodiment as follows: when the position data and speed data between at least two vehicles meet the preset differential coding conditions, the communication data of the at least two vehicles are differentially encoded to obtain differentially encoded data, including: calculating the Euclidean distance between any two vehicles according to the position data of each vehicle in the target road; calculating the speed difference between any two vehicles according to the speed data of each vehicle in the target road; when the Euclidean distance and / or speed difference between the two vehicles meet the preset differential coding conditions, the two vehicles are determined as vehicles to be encoded; all vehicles to be encoded are determined, and all vehicles to be encoded are differentially encoded to obtain differentially encoded data.

[0038] like Figure 2 As shown, the method may include the following steps:

[0039] Step S201, acquiring communication data of each vehicle traveling on a target road, wherein the communication data includes position data and speed data;

[0040] Step S202, calculating the Euclidean distance between any two vehicles based on the position data of each vehicle on the target road;

[0041] For example, the position data and speed data of each vehicle on the target road are as follows:

[0042] Data example:

[0043] Vehicle 1: position (40.7128, -74.0060), speed 50km / h;

[0044] Vehicle 2: position (40.7129, -74.0061), speed 52km / h;

[0045] Vehicle 3: position (40.7130, -74.0062), speed 51km / h;

[0046] Vehicle 4: position (40.7500, -73.9900), speed 55km / h;

[0047] First, we calculate the location similarity and use the Euclidean distance formula to measure the similarity between two location points, thereby identifying redundant information in the data set. The formula is as follows:

[0048]

[0049] Where x1, y1 and x2, y2 are the latitude and longitude coordinates of the two vehicles respectively. This formula determines the proximity of the locations by calculating the straight-line distance between the two points.

[0050] Step S203, calculating the speed difference between any two vehicles according to the speed data of each vehicle on the target road;

[0051] Speed ​​similarity calculation:

[0052] Speed ​​similarity is evaluated by calculating the absolute value of the difference between the speeds of the two vehicles, using the following formula:

[0053] Δv=|v2-v1|;

[0054] This formula reflects a direct comparison of the speeds of the two vehicles and is used to determine whether their operating states are close.

[0055] Step S204, when the Euclidean distance and / or speed difference between the two vehicles meets the preset differential encoding condition, the two vehicles are determined as vehicles to be encoded;

[0056] Set a similarity threshold to decide when two data sets are considered similar and can be merged or compressed. For example:

[0057] Position threshold: 0.0002 degrees;

[0058] Speed ​​threshold: 5km / h;

[0059] These thresholds are set based on the actual needs and accuracy requirements of the system and are used to determine when the data from two vehicles is similar enough to be processed further.

[0060] Use the above formula and threshold to perform similarity analysis on the vehicles in the fleet. Calculate the position and speed differences between each pair of vehicles and determine whether they can be considered similar based on the set threshold. The calculation process includes: For each pair of vehicles, calculate the Euclidean distance of the position and the speed difference.

[0061] Example calculation of vehicle 1 and vehicle 2:

[0062]

[0063] Δv 1,2 =|52-50|=2km / h;

[0064] If d 1,2 Less than 0.0002 degrees and Δv 1,2 If the speed is less than 5 km / h, the data of vehicle 1 and vehicle 2 are considered similar and suitable for data merging or compression.

[0065] Step S205, determining all vehicles to be coded, and performing differential coding on all vehicles to be coded to obtain differential coding data;

[0066] After determining that the vehicle data is highly similar, only the differences between the data are recorded through differential encoding, significantly reducing the amount of data transmission and storage requirements. This method uses the similarity of existing data to optimize the storage and transmission of information and reduces the overall data load by only transmitting the changed parts.

[0067] The processing formula and calculation method are as follows:

[0068] Select benchmark data:

[0069] Select a reference vehicle in the fleet, usually the one with the most central location or the one whose data is received first. The data of this vehicle will be used as the reference point for differential encoding.

[0070] Assume the position and speed of vehicle 1 as a reference.

[0071] Calculate the difference data:

[0072] The position and speed of each vehicle are compared with the reference vehicle and differential values ​​are calculated. These differential values ​​represent the amount of change relative to the reference vehicle, not the absolute value.

[0073] The difference formula can be expressed as:

[0074] Δx = x_vehicle - x_baseline;

[0075] Δy=y_vehicle-y_base;

[0076] Δv=v_vehicle-v_base;

[0077] Where y_vehicle and v_vehicle are the position and velocity of the vehicle, and x_reference, y_reference, and v_reference are the position and velocity of the reference vehicle.

[0078] Calculate the difference data between vehicle 2 and reference vehicle 1:

[0079] Base vehicle 1: position (40.7128, -74.0060), speed 50 km / h;

[0080] Vehicle 2: position (40.7129, -74.0061), speed 52km / h;

[0081] Difference calculation:

[0082] Δx 1,2 =40.7129-40.7128=0.0001;

[0083] Δy 1,2 =-74.0061+74.0060=-0.0001;

[0084] Δv 1,2 =52-50=2km / h;

[0085] This means that the position and speed of vehicle 2 are 0.0001 degrees east and 0.0001 degrees south, respectively, and the speed increases by 2 km / h compared to reference vehicle 1.

[0086] Difference data between vehicle 3 and reference vehicle 1:

[0087] Vehicle 3: position (40.7130, -74.0062), speed 51km / h;

[0088] Difference calculation:

[0089] Δx 1,3 =40.7130-40.7128=0.0002;

[0090] Δy 1,3 =-74.0062+74.0060=-0.0002;

[0091] Δv 1,3 =51-50=1km / h;

[0092] This means that the position of vehicle 3 is shifted by 0.0002 degrees east and 0.0002 degrees south compared to reference vehicle 1, and the speed is increased by 1 km / h.

[0093] Vehicle 4 handling:

[0094] Vehicle 4 is not suitable for differential encoding with the benchmark vehicle because its position (40.7500, -73.9900) and speed (55km / h) are quite different from those of the benchmark vehicle. Therefore, the data of vehicle 4 will be processed separately or with different compression strategies.

[0095] Step S206, determining a compression rate according to the driving state of the vehicle on the target road, and compressing the differentially encoded data using the compression rate to obtain data to be transmitted;

[0096] Step S207, transmitting the data to be transmitted to a receiving end, and parsing and restoring the data by the receiving end to obtain the position data and speed data of each vehicle.

[0097] Accordingly, the core goal of reverse decompression is to use the received baseline data and differential data to accurately reconstruct the original position and speed information of each vehicle. This process ensures that the information compressed during data transmission can be fully and accurately restored, ensuring the integrity and accuracy of the data.

[0098] Receive baseline and differential data:

[0099] Assume that each receiving station or vehicle can receive a copy of the benchmark vehicle's data and the differential data of other vehicles relative to the benchmark vehicle.

[0100] The formula to reconstruct the original data is:

[0101] Position reconstruction formula:

[0102] x_original=x_baseline+Δx;

[0103] y_original=y_baseline+Δy;

[0104] v_original=v_base+Δv;

[0105] These formulas use the reference position (x_reference, y_reference) and the difference (Δx, Δy) to calculate the original position of each vehicle. The speed is calculated in a similar way. Specific embodiment:

[0107] Assume that the benchmark vehicle data is: position (40.7128, -74.0060), speed 50km / h.

[0108] Assume that the received differential data is as follows:

[0109] Vehicle 2’s position differential data:

[0110] Input: Δx = 0.0001;

[0111] Input: Δy = -0.0001;

[0112] Speed ​​differential data:

[0113] Input: Δv = 2km / h;

[0114] According to the reconstruction formula, the original data of vehicle 2 can be calculated as follows:

[0115] x_original = 40.7128 + 0.0001 = 40.7129;

[0116] y_original = -74.0060-0.0001 = -74.0061;

[0117] v_original=50+2=52km / h.

[0118] In a preferred embodiment, determining the reference position and reference speed of all vehicles to be encoded includes:

[0119] The vehicle closest to the center point of the vehicle to be coded among all the vehicles to be coded is taken as the reference vehicle;

[0120] The position data of the reference vehicle is determined as a reference position, and the speed data of the reference vehicle is determined as a reference speed.

[0121] In a preferred embodiment, determining the reference position and reference speed of all vehicles to be encoded includes:

[0122] The vehicle to be encoded that receives the communication data first among all the vehicles to be encoded is used as the reference vehicle;

[0123] The position data of the reference vehicle is determined as a reference position, and the speed data of the reference vehicle is determined as a reference speed.

[0124] Among them, whether determining the benchmark vehicle by position or by using the vehicle with faster communication speed as the benchmark vehicle, vehicles within a certain range and with similar speed to the benchmark vehicle can be differentially encoded, thereby reducing the volume of communication data of these vehicles, removing redundant data, and improving the efficiency of data transmission and data analysis.

[0125] By using this differential encoding method, we can significantly reduce the amount of data that needs to be transmitted, because only the difference from the baseline data is transmitted instead of the complete data set. This method is particularly suitable for environments where the vehicle position and speed do not change much, such as slow-moving traffic jams or convoy driving. Through differential encoding, the efficiency of data transmission and storage can be effectively improved.

[0126] Third embodiment

[0127] The third embodiment of the present application relates to an efficient transmission method for vehicle communication data. This embodiment optimizes the above embodiment as follows: when the position data and speed data between at least two vehicles meet the preset differential coding conditions, the communication data of the at least two vehicles are differentially encoded to obtain differentially encoded data, including: calculating the Euclidean distance between any two vehicles according to the position data of each vehicle in the target road; calculating the speed difference between any two vehicles according to the speed data of each vehicle in the target road; when the Euclidean distance and / or speed difference between the two vehicles meet the preset differential coding conditions, the two vehicles are determined as vehicles to be encoded; all vehicles to be encoded are determined, and all vehicles to be encoded are differentially encoded to obtain differentially encoded data.

[0128] like Figure 3 As shown, the method may include the following steps:

[0129] Step S301, acquiring communication data of each vehicle traveling on a target road, wherein the communication data includes position data and speed data;

[0130] Step S302, when the position data and speed data between at least two vehicles meet a preset differential encoding condition, differential encoding is performed on the communication data of the at least two vehicles to obtain differential encoding data;

[0131] Step S303, obtaining a vehicle speed index, a vehicle flow index, and an accident frequency index of vehicles on the target road;

[0132] This solution dynamically adjusts the compression strategy according to the current traffic environment to optimize data transmission efficiency and reduce unnecessary network burden.

[0133] First, you need to determine the context by analyzing real-time or historical traffic data to determine whether it is peak or off-peak. Use formulas to define the context, such as analyzing vehicle speed, traffic volume, and accident frequency to define traffic status.

[0134] Step S304, determining context data according to the vehicle speed index, the vehicle flow index and the accident frequency index;

[0135] Define the context function:

[0136] formula:

[0137] Context f = w1*vehicle speed index + w2*traffic flow index + w3*accident frequency index;

[0138] Vehicle speed index calculation:

[0139] formula:

[0140] Vehicle speed index = MAX (0, 1-(vehicle speed / set maximum speed));

[0141] Traffic flow index calculation:

[0142] formula:

[0143] Traffic flow index = traffic flow / set maximum traffic flow;

[0144] Accident frequency index calculation:

[0145] formula:

[0146] Accident frequency index = accident frequency / set maximum accident frequency.

[0147] Step S305, determining a compression ratio according to the context data;

[0148] This solution can adjust the compression rate by determining the context data, so as to achieve compression with different compression rates under different traffic conditions.

[0149] In a preferred embodiment, determining the compression ratio according to the context data includes:

[0150] Determining, according to the context data, whether the target road is currently in a peak hour or a non-peak hour;

[0151] If it is during the peak period, the compression rate is determined to be the first compression rate;

[0152] If it is in a non-peak period, the compression rate is determined to be the second compression rate.

[0153] During peak hours, since the position changes between vehicles are small, the data accuracy is reduced and the compression rate is increased; the compression rate can be changed by adjusting the data accuracy formula:

[0154] Compression ratio = 1 / data accuracy;

[0155] When the data precision is adjusted to 0.001 degree, the compression rate is improved.

[0156] During off-peak hours, due to frequent location changes, high data accuracy is maintained to ensure accurate delivery of information.

[0157] Maintain data accuracy to 0.0001 degrees to ensure detailed data records.

[0158] During traffic jams:

[0159] Automatically adjust location data accuracy when average speed decreases and traffic volume increases:

[0160] If the average vehicle speed is ≤30km / h and the traffic volume is high, the data accuracy is 0.001 degrees;

[0161] When traffic is light:

[0162] When the average speed is higher than the normal traffic flow, maintain high data accuracy:

[0163] If the average vehicle speed is >60km / h and the traffic flow is normal, the data accuracy is 0.0001 degrees.

[0164] Step S306, compressing the differentially encoded data using the compression rate to obtain data to be transmitted;

[0165] Step S307, transmitting the data to be transmitted to a receiving end, and parsing and restoring the data by the receiving end to obtain the position data and speed data of each vehicle.

[0166] This embodiment can flexibly cope with different traffic environments. For example, in the case of traffic congestion (peak hours) and smooth traffic (off-peak hours), the accuracy of the location data can be adjusted, so that the data compression rate can be optimized according to actual needs to improve efficiency.

[0167] The technical solution provided in the embodiment of the present application dynamically adjusts the data compression strategy in vehicle-to-vehicle (V2V) communication through real-time and historical traffic data analysis. This method not only improves the efficiency of data transmission, but also ensures the reliability and accuracy of communication under different traffic conditions. First, the solution can improve the efficiency of data transmission. By dynamically adjusting the compression rate, the technology can significantly reduce the amount of data transmission during peak traffic. For example, by reducing data accuracy and increasing the compression rate, the burden on the network is reduced and the overall transmission efficiency is improved. This means that in an environment with network congestion, the system can process and transmit key data more efficiently. Secondly, the solution can optimize the use of network resources. The dynamic compression strategy allows the system to intelligently allocate network bandwidth and storage resources according to real-time traffic conditions. When traffic is smooth, the system will maintain high data accuracy to ensure that the transmitted information is detailed and accurate, which is conducive to rapid and accurate response in emergency situations. In traffic congestion, the network overload is avoided by reducing the amount of data, thereby optimizing the use of resources. Thirdly, the solution can enhance the reliability and security of data transmission. In a complex traffic environment, it is crucial to ensure the integrity and timeliness of data. This technology adjusts the data processing method to adapt to different traffic conditions, reduces the risk of data loss due to network problems, and enhances the stability and reliability of the system. Finally, this solution can improve the adaptability and flexibility of the system. This technical solution enables the system to flexibly respond to changing traffic conditions and automatically adjust data processing strategies. This high degree of adaptability is achieved by continuously monitoring traffic parameters and updating compression settings in real time, allowing the system to maintain optimal performance in various environments.

[0168] In addition, some embodiments of the present application also provide an electronic device. The electronic device may be a digital computer in various forms, such as a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, etc. The electronic device may also be a mobile device in various forms, such as a personal digital assistant, a cellular phone, a smart phone, a wearable device, and other similar computing devices.

[0169] The electronic device includes: one or more processors; and a memory storing computer program instructions, wherein when the computer program instructions are executed, the processor executes the steps of the method provided in any one or more of the above embodiments. Figure 4 An exemplary structural diagram of the electronic device is disclosed. Figure 4 As shown, the electronic device includes: one or more processors 401, memory 402, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Among them, the components shown in this article, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0170] The electronic device may further include: an input device 403 and an output device 404. The processor 401, the memory 402, the input device 403 and the output device 404 may be connected via a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0171] The input device 403 can receive input digital or character information, and generate key signal input related to the user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick and other input devices. The output device 404 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display and a plasma display. In some embodiments, the display device may be a touch screen.

[0172] To provide interaction with a user, the electronic device may be a computer. The computer has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0173] In the embodiments of the present application, a computer program / instruction is stored on a computer-readable medium, and when the computer program / instruction is executed by a processor, the steps of the method provided by any one or more of the above embodiments are implemented. The computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions.

[0174] The memory 402 can be used as a non-transient computer-readable storage medium, which can be used to store non-transient software programs, non-transient computer executable programs and modules. The processor 401 executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory 402, so as to implement the program instructions / modules corresponding to the method provided by any one or more of the above embodiments in the embodiments of the present application.

[0175] The memory 402 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage devices. In some embodiments, the memory 402 may optionally include a memory remotely arranged relative to the processor 401, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0176] It should be noted that the computer-readable medium described in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0177] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, modules of programs or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0178] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0179] In the above-described embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. For example, it can be implemented by using an application specific integrated circuit (ASIC), a general-purpose computer or any other similar hardware device. In certain embodiments, the software program of the present application can be executed by a processor to implement the above steps or functions. Similarly, the software program of the present application (including relevant data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive or a floppy disk and similar devices. In addition, some steps or functions of the present application can be implemented by hardware, for example, as a circuit that cooperates with a processor to perform each step or function.

[0180] The computer program product provided in the embodiment of the present application includes one or more computer programs / instructions, and when the computer program / instructions are executed by the processor, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from a computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0181] The flow chart or block diagram in the accompanying drawings shows the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated system for hardware that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0182] The scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claim may also be implemented by one unit or device through software or hardware. The words "first", "second", etc. are only used to distinguish the description, and do not indicate any particular order, nor can they be understood as indicating or implying relative importance.

[0183] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily mention changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-restrictive.

Claims

1. A method for efficiently transmitting vehicle communication data, characterized in that: The method comprises: Acquiring communication data of each vehicle traveling on the target road, wherein the communication data includes position data and speed data; When the position data and speed data between at least two vehicles meet a preset differential encoding condition, differentially encoding the communication data of the at least two vehicles to obtain differentially encoded data; Determine a compression rate according to the driving state of the vehicle on the target road, and compress the differentially encoded data using the compression rate to obtain data to be transmitted; The data to be transmitted is transmitted to a receiving end, and the receiving end parses and restores the position data and speed data of each vehicle to obtain the position data and speed data.

2. The method according to claim 1, characterized in that: When the position data and speed data between at least two vehicles meet a preset differential coding condition, differential coding is performed on the communication data of the at least two vehicles to obtain differential coding data, including: Calculate the Euclidean distance between any two vehicles based on the position data of each vehicle on the target road; Calculate the speed difference between any two vehicles based on the speed data of each vehicle on the target road; When the Euclidean distance and / or speed difference between the two vehicles meets a preset differential encoding condition, the two vehicles are determined as vehicles to be encoded; All vehicles to be coded are determined, and differential coding is performed on all vehicles to be coded to obtain differential coding data.

3. The method according to claim 2, characterized in that Perform differential encoding on all vehicles to be encoded to obtain differential encoding data, including: Determine the reference position and reference speed of all vehicles to be encoded; All vehicles to be encoded are differentially encoded in position according to the reference position, and differentially encoded in speed according to the reference speed, to obtain differentially encoded data.

4. The method according to claim 3, characterized in that: Determine the reference position and reference speed of all vehicles to be encoded, including: The vehicle closest to the center point of the vehicle to be coded among all the vehicles to be coded is taken as the reference vehicle; The position data of the reference vehicle is determined as a reference position, and the speed data of the reference vehicle is determined as a reference speed.

5. The method according to claim 3, characterized in that: Determine the reference position and reference speed of all vehicles to be encoded, including: The vehicle to be encoded that receives the communication data first among all the vehicles to be encoded is used as the reference vehicle; The position data of the reference vehicle is determined as a reference position, and the speed data of the reference vehicle is determined as a reference speed.

6. The method according to claim 1, characterized in that The compression ratio is determined according to the driving state of the vehicle on the target road, including: Obtaining the vehicle speed index, traffic flow index and accident frequency index of vehicles on the target road; determining context data according to the vehicle speed index, the vehicle flow index, and the accident frequency index; A compression ratio is determined based on the context data.

7. The method according to claim 6, characterized in that Determining a compression ratio according to the context data includes: Determining, according to the context data, whether the target road is currently in a peak hour or a non-peak hour; If it is during the peak period, the compression rate is determined to be the first compression rate; If it is in a non-peak period, the compression rate is determined to be the second compression rate.

8. An electronic device, characterized in that: The electronic device comprises: one or more processors; and A memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method as claimed in any one of claims 1 to 7.

9. A computer readable medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images