Vehicle management method based on Beidou, iridium and 4G multimode communication

Abstract

The invention relates to a vehicle management method based on Beidou, iridium and 4G multimode communication, belongs to the field of vehicle management, and solves the problems of limited coverage, unstable signals, high data transmission delay and low command and dispatch efficiency caused by dependence on a single communication technology in an existing method. Comprising the following steps: acquiring communication quality data of each vehicle in preset unit time; based on the communication quality data of each vehicle, utilizing a trained multi-mode communication path selection model to carry out communication path dynamic evaluation, obtaining an optimal communication mode as a main communication path, and selecting a mode with relatively low communication cost from the remaining communication modes as an auxiliary communication path; and receiving the state multi-source data of each vehicle based on the main communication and auxiliary communication paths of each vehicle and the main communication and auxiliary communication report frequency, and sending a scheduling instruction to each vehicle based on the state multi-source data of each vehicle and a preset electronic fence to realize real-time monitoring and scheduling of each vehicle. And real-time monitoring, data transmission and commanding and dispatching of vehicles are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle management, and particularly relates to a vehicle management method based on Beidou, Iridium and 4G multi-mode communication. BACKGROUND

[0002] The existing vehicle management method usually relies on a single communication technology, such as GPS (Global Positioning System) or 4G network, which has the problems of limited coverage, unstable signal, high data transmission delay, etc. Especially in remote areas or complex terrain, the limitations of single communication technology are particularly obvious. In addition, the existing vehicle management method also has the problems of low efficiency and slow response in data processing and command scheduling. The specific technical defects are as follows:

[0003] Limited coverage: the coverage of single communication technology is limited, which cannot realize global seamless coverage;

[0004] Unstable signal: in complex terrain or bad weather conditions, the signal is easily disturbed, leading to communication interruption;

[0005] High data transmission delay: the data transmission path of single communication technology is longer, resulting in high transmission delay, which affects the real-time performance;

[0006] Low command scheduling efficiency: the existing vehicle management system lacks intelligentization and automation in command scheduling, resulting in low efficiency.

[0007] Lack of appropriate command scheduling logic: it is difficult to ensure the accuracy of data reachability. Lack of platform intelligent setting communication mode: now single communication mode is dominant, and it does not have intelligent configuration of multiple communication modes. SUMMARY

[0008] In view of the above analysis, the embodiments of the present application aim to provide a vehicle management method based on Beidou, Iridium and 4G multi-mode communication, to solve the technical problems of limited coverage, unstable signal, high data transmission delay and low command scheduling efficiency of the existing vehicle management method due to the reliance on single communication technology.

[0009] The main purpose of the present application is realized by the following technical solutions:

[0010] The present application provides a vehicle management method based on Beidou, Iridium and 4G multi-mode communication, comprising the following steps:

[0011] Obtain the communication quality data of each vehicle in a preset unit time;

[0012] Based on the communication quality data of each vehicle, a trained multi-mode communication path selection model is used to perform dynamic evaluation of the communication path, and the optimal communication mode is obtained as the main communication path, and a communication mode with lower communication cost is selected as the auxiliary communication path from the remaining communication modes;

[0013] Based on the main communication path and the auxiliary communication path of each vehicle, and the main communication and auxiliary communication reporting frequency, the state multi-source data of each vehicle is received, and based on the state multi-source data of each vehicle, the historical trajectory and the preset electronic fence, a dispatch instruction is sent to each vehicle to realize real-time monitoring and dispatching of each vehicle;

[0014] Among them, the communication mode includes Beidou satellite, Iridium satellite and 4G network.

[0015] Further, the communication quality data of each vehicle in a preset unit time is obtained, including:

[0016] The reference signal receiving power, the reference signal receiving quality, the signal to interference noise ratio, the 4G average transmission delay, the 4G successful transmission ratio, the 4G end-to-end transmission time, the 4G communication cost and the switching times of 4G as the main communication and auxiliary communication of the 4G network;

[0017] The signal to noise ratio, the number of visible satellites, the positioning accuracy factor, the Beidou average transmission delay, the Beidou successful transmission ratio, the Beidou end-to-end transmission time, the Beidou communication cost and the switching times of Beidou as the main communication and auxiliary communication of the Beidou satellite;

[0018] The signal to noise ratio, the link error rate, the Iridium average transmission delay, the Iridium successful transmission ratio, the Iridium end-to-end transmission time, the Iridium communication cost and the switching times of Iridium as the main communication and auxiliary communication of the Iridium satellite.

[0019] Further, the trained multi-mode communication path selection model is obtained through the following training process:

[0020] A communication path selection training sample set composed of a plurality of communication quality data and corresponding vehicle task state data is constructed, and the sample label is a one-hot encoding vector of all corresponding communication modes, and the optimal communication mode is 1 and the other communication modes are 0;

[0021] A multi-mode communication path selection model including an input layer, an LSTM network layer, a fully connected classification layer and an output layer in sequence is constructed;

[0022] The multi-mode communication path selection model is trained using the communication path selection training sample set;

[0023] The weighted cross-entropy loss value between the communication mode probability vector output by the model and the sample label is calculated;

[0024] According to the weighted cross-entropy loss value, the gradient is calculated by back propagation; the model weight and parameter are updated using Adam optimization algorithm;

[0025] Iterative forward propagation, loss calculation, back propagation and gradient update until the weighted cross-entropy loss function is minimized, then stop training, save all iteration of the objective function of the maximum model parameters as the trained multi-mode communication path selection model.

[0026] Further, the objective function is as follows:

[0027]

[0028] Wherein, SuccessRate is the success transmission ratio in a preset unit of time; Latency is the average end-to-end transmission time of vehicle to vehicle management platform in a preset unit of time; CostWeight is the communication cost in a preset unit of time; SwitchFreq is the number of main communication and auxiliary communication switching in a preset unit of time.

[0029] Further, the weighted cross-entropy loss function is as follows:

[0030]

[0031] Wherein, Loss is the weighted cross-entropy loss value, C is the total number of communication mode categories, ω i is the weight of the ith communication mode; y i is the real label; p i is the communication mode probability vector predicted by the model.

[0032] Further, the input layer is used for normalizing the input state multi-source data to form an input vector;

[0033] The LSTM network layer is used to extract the features of the input vector and perform ReLU activation to obtain a feature vector;

[0034] The fully connected classification layer is used to generate scores of three communication modes from the feature vector;

[0035] The output layer uses Softmax function to convert the scores of three communication modes into a communication mode probability vector.

[0036] Further, the vehicle task state data includes normal mode, emergency mode and energy saving mode;

[0037] If the main communication fails continuously for n times, the auxiliary communication is triggered for retransmission;

[0038] If it is in emergency mode, the main communication and auxiliary communication are forced to be used in parallel transmission.

[0039] Further, the auxiliary communication reporting frequency is dynamically set based on the main communication reporting frequency, as follows:

[0040]

[0041] wherein f s is the auxiliary communication reporting frequency, f p is the main communication reporting frequency, and m is a preset multiple; and ω1 and ω2 are the cost weights of the main communication and the auxiliary communication, respectively.

[0042] The main communication reporting frequency is a dynamically preset value.

[0043] Further, the multi-source vehicle state data includes vehicle identification, position, speed, direction, UTC time, elevation, alarm signal, online / offline state, and communication mode.

[0044] The position of the vehicle includes longitude and latitude, and the alarm signal includes electronic fence crossing alarm, vehicle state abnormality alarm, and SOS alarm information.

[0045] Further, the dispatching instructions are sent to each vehicle through the main / auxiliary communication mode, wherein the dispatching instructions include electronic fence crossing, SOS emergency alarm, vehicle state abnormality processing dispatching instruction, and manually issued dispatching instruction.

[0046] The dispatching instructions are prevented from being tampered with using digital signatures, and the vehicle terminal executes the dispatching instructions after signature verification.

[0047] Compared with the prior art, the present application can achieve at least one of the following beneficial effects:

[0048] 1. The present application realizes real-time monitoring, data transmission and command and dispatching of vehicles through the cooperation of the three modes of "4G + Beidou + Iridium", the high-precision positioning and global coverage capability of the integrated Beidou and Iridium satellite systems, and the high-speed data transmission of the 4G network.

[0049] 2. The communication modes of the main communication path and the auxiliary communication path in the present application also better guarantee the communication success rate of data, based on the communication quality data of the vehicle, using a multi-mode communication path selection model to select the optimal communication mode as the main communication path and automatically switching the main / auxiliary path, realizing global seamless communication coverage in urban, mountainous and oceanic application scenarios, and completely eliminating problems such as single-signal blind area and weak-signal interruption, thereby realizing seamless coverage and never dropping the line.

[0050] 3、The application introduces the LSTM dynamic decision model as a multi-mode communication path selection model, real-time evaluates multi-dimensional communication quality data and task state, and completes main / auxiliary path selection within 5ms; the main path is reported at a high frequency every 10s, and the auxiliary path is reported at a low frequency every 100s, which not only guarantees real-time performance, but also saves more than 70% of communication costs, so that millisecond-level intelligent scheduling and response speed are improved by more than 10 times;

[0051] 4、The scheduling instruction of the application adopts AES-128-CBC encryption+ECDSA-P256 digital signature, bidirectional certificate verification, and main / auxiliary dual-channel redundant reporting; any single-point link that is broken cannot successfully tamper with or forge the instruction, ensuring the absolute safety and reliability of vehicle remote control and emergency scheduling; end-to-end safety loop and zero-tampering scheduling instruction are realized, and the efficiency and accuracy of vehicle scheduling are improved;

[0052] 5、The method has wide application prospects in the fields of logistics transportation, public transportation, emergency rescue and the like, and can significantly improve the reliability of vehicle management and the efficiency of command and scheduling.

[0053] In the application, the above technical solutions can be combined with each other to realize more preferred combination solutions. Other features and advantages of the application will be described in the subsequent specification, and some advantages will become apparent from the specification or be understood by implementing the application. The purposes and other advantages of the application can be realized and obtained from the contents specifically indicated in the specification and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0054] The accompanying drawings are included to provide a further understanding of the application and are incorporated herein and constitute a part of the application. The drawings illustrate embodiments of the application and, together with the description, serve to explain the principles of the application. In the drawings:

[0055] Figure 1 A vehicle management method based on Beidou, Iridium and 4G multi-mode communication in the embodiment of the application is shown in the flowchart;

[0056] Figure 2 A vehicle data reporting diagram using a main communication mode and an auxiliary communication mode in the embodiment of the application is shown;

[0057] Figure 3 A vehicle management platform receiving vehicle data and sending scheduling instructions in the embodiment of the application is shown in the schematic diagram;

[0058] Figure 4 A monitoring interface of the vehicle management platform in the embodiment of the application is shown in the schematic diagram;

[0059] Figure 5 A vehicle trajectory backtracking diagram in the embodiment of the application is shown. DETAILED DESCRIPTION

[0060] Preferred embodiments of the present application will be described in detail below with reference to the drawings, wherein the drawings constitute a part of this application, and are used to explain the principles of the application together with the embodiments of the application, but are not used to limit the scope of the application.

[0061] The technical product is a vehicle management method based on Beidou, Iridium and 4G multi-mode communication, which realizes real-time monitoring, data transmission and command scheduling of vehicles by using high-precision positioning and global coverage capability of Beidou and Iridium satellites, combining high-speed data transmission of 4G network.

[0062] In one specific embodiment of the present application, a vehicle management method based on Beidou, Iridium and 4G multi-mode communication is disclosed, as shown in Figure 1 The method comprises the following steps:

[0063] Step S1, obtaining communication quality data of each vehicle in a preset unit time;

[0064] Step S2, based on the communication quality data of each vehicle, using the trained multi-mode communication path selection model, performing communication path dynamic evaluation, obtaining the optimal communication mode as the main communication path, and selecting the communication mode with lower communication cost from the remaining communication modes as the auxiliary communication path;

[0065] Step S3, based on the main communication path and the auxiliary communication path of each vehicle, and the main communication and auxiliary communication reporting frequency, receiving state multi-source data of each vehicle respectively, sending scheduling instructions to each vehicle based on the state multi-source data of each vehicle, historical trajectory and preset electronic fence, and realizing real-time monitoring and scheduling of each vehicle;

[0066] The communication mode includes Beidou satellite, Iridium satellite and 4G network.

[0067] As shown in Figure 3 In the vehicle management platform, the electronic fence of each vehicle is configured, modified and deleted by using the vehicle configuration module, including the range and validity period of the electronic fence.

[0068] Step S1, specifically.

[0069] The communication quality data of each vehicle in a preset unit time is obtained, including:

[0070] The reference signal receiving power, the reference signal receiving quality, the signal interference noise ratio, the 4G average transmission delay, the 4G successful transmission proportion, the 4G end-to-end transmission time, the 4G communication cost and the switching times of 4G as the main communication and auxiliary communication of the 4G network;

[0071] Signal-to-noise ratio, number of visible satellites, positioning accuracy factor, average transmission delay, successful transmission ratio, end-to-end transmission time, communication cost and switching times of Beidou as the main and auxiliary communication.

[0072] Signal-to-noise ratio, link error rate, average transmission delay, successful transmission ratio, end-to-end transmission time, communication cost and switching times of Iridium as the main and auxiliary communication.

[0073] The vehicle terminal is responsible for collecting real-time communication quality data of the vehicle, and the communication quality data is input into the trained multi-mode communication path selection model in step S2 to obtain the optimal communication mode.

[0074] The function of step S1 is to collect the communication quality data of each vehicle within a predetermined time, so as to evaluate and optimize the main and auxiliary communication path selection of each vehicle in real time.

[0075] Step S2 includes steps S21-S22.

[0076] Step S21 obtains a trained multi-mode communication path selection model.

[0077] The trained multi-mode communication path selection model is obtained through the following training process:

[0078] A communication path selection training sample set composed of multiple communication quality data and corresponding vehicle task state data is constructed, and the sample label is a one-hot encoding vector of all corresponding communication modes, with the optimal communication mode being 1 and other communication modes being 0.

[0079] A multi-mode communication path selection model is constructed, which includes an input layer, an LSTM network layer, a fully connected classification layer and an output layer in turn.

[0080] The communication path selection training sample set is used to train the multi-mode communication path selection model.

[0081] The weighted cross-entropy loss value between the communication mode probability vector output by the model and the sample label is calculated.

[0082] According to the weighted cross-entropy loss value, the gradient is calculated by back propagation, and the model weight and parameter are updated using the Adam optimization algorithm.

[0083] Iterative forward propagation, loss calculation, back propagation and gradient update are performed until the weighted cross-entropy loss function is minimized, then the training is stopped, and the model parameters with the maximum objective function in all iterations are saved as the trained multi-mode communication path selection model.

[0084] The vehicle terminal is responsible for real-time collection and caching of the communication quality data of the vehicle, and then according to the reporting period of the primary / secondary path, the data package is returned to the vehicle management platform through the 4G network, Beidou satellite or Iridium satellite, and the vehicle management platform is then uniformly warehoused;

[0085] The communication quality data within a certain historical period, the communication success / failure flag, and the vehicle task state data constitute a communication path selection training sample set, which is used for offline training of the multi-mode communication path selection model by the cloud server.

[0086] The sample label is the optimal communication mode corresponding to the sample data. The communication path selection training sample set contains samples of city, highway, mountainous area and other application scenarios.

[0087] The proportion of the amount of samples of each category is exemplarily as follows: 4G network sample proportion is 60%; Beidou satellite sample proportion is 30%; Iridium satellite sample proportion is 10%.

[0088] The cloud server is offline trained for data incremental training.

[0089] The trained multi-mode communication path selection model is regularly updated and distributed to the vehicle-mounted edge device.

[0090] Exemplarily, the time interval of updating the model and distributing it to the vehicle-mounted edge device can be determined according to the needs of the actual application scenario and the changes in model performance. The periodic interval can be:

[0091] (1) Weekly: If the communication environment and vehicle task state change little, the model parameters of the multi-mode communication path selection model can be updated once a week to reflect any gradual changes.

[0092] (2) Monthly: In a relatively stable communication environment and slow model performance decline scenario, the model parameters of the multi-mode communication path selection model can be updated monthly.

[0093] (3) Quarterly: For some slower changing environments, or when the model has become quite mature and the performance is stable, it can be updated once a quarter.

[0094] (4) Instant update in special cases: When the communication environment changes significantly (such as the implementation of new communication policies, large-scale network upgrades, etc.), the model parameters may need to be updated immediately to adapt to the new environment.

[0095] The vehicle management platform monitors the performance indicators of the multi-mode communication path selection model, such as accuracy, communication cost, switching frequency, etc., and decides when to update the model according to the performance of these indicators. In addition, the model parameters are fully tested and simulated before being updated to ensure that the incremental trained multi-mode communication path selection model performs as expected in the actual environment.

[0096] The input layer is used to normalize the input state multi-source data to form an input vector;

[0097] The LSTM network layer is used to extract features from the input vector and perform ReLU activation to obtain a feature vector;

[0098] The fully connected classification layer is used to generate scores for the three communication methods from the feature vector;

[0099] The output layer uses the Softmax function to convert the scores of the three communication methods into a probability vector of the communication method.

[0100] The input state data from multiple sources is normalized, for example, by Min-Max scaling, to form an input vector X = [x1, x2, ..., x...]. n In this invention, the communication quality data is 23-dimensional data, and the vehicle task status data is 24-dimensional data in total, with n being 24.

[0101] The output layer of the multi-mode communication path selection model outputs a probability vector S = [S 4G ,S BDS ,S Iridium ], where S 4G S BDS S Iridium The scores are the probabilities of 4G network, Beidou satellite and Iridium satellite respectively; S∈[0,1]; the one with the highest score is the optimal communication method.

[0102] Calculate the probability vector S of the communication method in real time; select the communication method with the highest score as the optimal communication path and use it as the main communication path.

[0103] Primary = argmax i∈4G,BDS,Iridium s i

[0104] Among them, 4G, BDS, and Iridium refer to 4G network, BeiDou satellite, and Iridium satellite, respectively.

[0105] The objective function is as follows:

[0106]

[0107] Among them, SuccessRate is the percentage of successful transmissions within a preset unit of time; Latency is the average end-to-end transmission time from the vehicle to the vehicle management platform within a preset unit of time; CostWeight is the communication cost within a preset unit of time; and SwitchFreq is the number of times the primary and secondary communication are switched within a preset unit of time.

[0108] Exemplarily, a = 0.6, b = 0.3, g = 0.1, d = 0.05; in specific applications, changes are made according to specific needs.

[0109] The weighted cross-entropy loss function is as follows:

[0110]

[0111] Wherein, Loss is the weighted cross-entropy loss value, C is the total number of communication mode categories, w i is the weight of the i-th communication mode; y i is the real label; p i is the communication mode probability vector predicted by the model.

[0112] Wherein, Loss is the weighted cross-entropy loss value, which is a scalar, the smaller the value, the more accurate the multi-mode communication path selection model prediction; C is the total number of communication mode categories, in this application, 4G network, Beidou satellite and Iridium satellite three categories; w i is the i-th weight coefficient, used to balance the category imbalance or cost difference; exemplarily, 4G network w1 = 1; Beidou satellite w2 = 3; Iridium satellite w3 = 10;

[0113] y i is the real label; exemplarily, One-hot encoding is used, the 4G network label is [1, 0, 0], the Beidou satellite label is [0, 1, 0], and the Iridium satellite label is [0, 0, 1].

[0114] p i is the communication mode probability predicted by the model, which is the output of Softmax; exemplarily, the output probability is [0.8, 0.15, 0.05], and the optimal communication mode is 4G network.

[0115] Step S22, using the trained multi-mode communication path selection model to obtain the optimal communication path as the main communication path, and selecting the communication mode with lower communication cost from the remaining communication modes as the auxiliary communication path.

[0116] Exemplary description: assume that a logistics transport vehicle traveling in a remote mountain area needs to keep real-time communication with the vehicle management platform. The vehicle is equipped with a multi-mode communication terminal supporting 4G network, Beidou satellite and Iridium satellite.

[0117] (1) Obtain communication quality data

[0118] The vehicle terminal collects the following communication quality data within a preset time interval (for example, every 10 seconds):

[0119] 4G network: reference signal received power (RSRP = -90 dBm), reference signal received quality (RSRQ = -10 dB), signal-to-interference-and-noise ratio (SINR = 10 dB), average transmission delay (50 ms), successful transmission ratio (95%), end-to-end transmission time (60 ms), communication cost (￥0.02 / MB).

[0120] Beidou satellite: signal-to-noise ratio (SNR = 20 dB), number of visible satellites (8), positioning accuracy factor (PDOP = 2), average transmission delay (200 ms), successful transmission ratio (85%), end-to-end transmission time (250 ms), communication cost is higher than 4G network and lower than iridium satellite.

[0121] Iridium satellite: signal-to-noise ratio (SNR = 15 dB), bit error rate (BER = 1e-4), average transmission delay (500 ms), successful transmission ratio (90%), end-to-end transmission time (550 ms), communication cost is relatively high.

[0122] (2) Evaluate the optimal communication path

[0123] The vehicle terminal inputs the communication quality data and vehicle task state data (normal mode, emergency mode or energy saving mode) into the trained multi-mode communication path selection model. The multi-mode communication path selection model calculates the score probability of each communication mode in real time according to the input data to obtain the optimal communication mode.

[0124] The vehicle task state is configured by the vehicle configuration module of the vehicle management platform.

[0125] Assuming that the score probability output by the model is:

[0126] 4G network: 0.7 (high score, but high cost);

[0127] Beidou satellite: 0.2 (medium score, low cost);

[0128] Iridium satellite: 0.1 (lowest score, but highest cost).

[0129] (3) Determine the primary and secondary communication paths

[0130] According to the score probability output by the multi-mode communication path selection model, the communication mode with the highest score, i.e. 4G network (score 0.7), is selected as the optimal communication mode, which is the primary communication path.

[0131] From the remaining communication modes, the communication mode with lower communication cost, i.e. Beidou satellite (score 0.2, cost lower than iridium), is selected as the secondary communication path. The reporting frequency of the secondary communication path can be set to 10 times that of the primary communication path, i.e. once every 100 seconds.

[0132] The vehicle terminal intelligently selects an optimal communication mode as a main communication path and a lower-cost communication mode as an auxiliary communication path to ensure stable and reliable communication in various environments while effectively controlling communication costs.

[0133] The step S2 is to use the trained multi-mode communication path selection model to dynamically evaluate and select the optimal main communication path and the lower-cost auxiliary communication path according to the real-time acquired vehicle communication quality data and task state, so as to realize efficient and reliable vehicle communication management.

[0134] The step S3 is specifically.

[0135] The vehicle task state data includes a normal mode, an emergency mode, and an energy-saving mode.

[0136] If the main communication fails continuously for n times, the auxiliary communication is triggered for retransmission.

[0137] If it is the emergency mode, the main communication and the auxiliary communication are forced to be transmitted in parallel.

[0138] For example, n is 3, and when the main communication path fails continuously for 3 times, the auxiliary communication path is triggered for retransmission immediately.

[0139] The auxiliary communication reporting frequency is dynamically set based on the main communication reporting frequency, as follows:

[0140]

[0141] Wherein, f s is the auxiliary communication reporting frequency, f p is the main communication reporting frequency, and m is a preset multiple; ω1 and ω2 are the cost weights of the main communication and the auxiliary communication, respectively.

[0142] The main communication reporting frequency is a dynamically preset value.

[0143] The main communication reporting frequency f p and the preset multiple m are dynamically set by the vehicle configuration module of the vehicle management platform based on task requirements; for example, f p is set to 10 seconds by default.

[0144] For example, m is preset to 10 times, which can be changed according to specific requirements in specific applications.

[0145] The initial default communication modes are 4G network, Beidou satellite, and Iridium satellite in sequence. When one communication mode is the main communication path, the other communication mode is the auxiliary communication path. The communication time of the auxiliary communication path is ten times (which can be flexibly set according to specific requirements) of the communication time of the main communication path, which ensures the reception rate of bidirectional data between the vehicle end and the vehicle management platform end.

[0146] The method is mainly used in the fields of logistics transportation, public transportation, emergency rescue, etc., to provide users with efficient, reliable and safe vehicle management means, and to improve the efficiency and accuracy of vehicle scheduling.

[0147] The communication interval time of the auxiliary communication path is ten times that of the main communication path. For example, if the communication interval time of the main communication path is 10 seconds, the communication interval time of the auxiliary communication path is 100 seconds. This design can reduce the dependence on the auxiliary communication method while ensuring the continuity of data transmission, thereby saving costs and resources.

[0148] As shown in Figure 2

[0149] Main communication path: preferred communication link (default 4G network), responsible for main data transmission task, high communication frequency (such as reporting data every 10 seconds);

[0150] Auxiliary communication path: backup communication link (default Beidou satellite), responsible for redundant backup task, low communication frequency (such as reporting once every 100 seconds).

[0151] In the subsequent process, the auxiliary communication reporting frequency is continuously and dynamically set based on the main communication reporting frequency; at the same time, the main communication reporting frequency can also be set immediately according to the specific situation.

[0152] First, continuity is guaranteed: when the main communication path is interrupted, the auxiliary communication path is still periodically transmitting data, avoiding complete data loss;

[0153] Example: when the main communication path fails, there is at least one data transmission by the auxiliary communication path within 100 seconds.

[0154] At the same time, cost optimization: satellite communication (especially Iridium) is expensive, and reducing the frequency can save up to 90% of the cost.

[0155] Work scenario example, as shown in Table 1.

[0156] Table 1: Work scenario example

[0157]

[0158] This design allows flexible switching in different communication environments to ensure the continuity and reliability of communication as much as possible in any situation. For example, in remote areas, 4G network signals may not be available, at which time Beidou satellite or Iridium satellite can be used as the main communication path; while in urban areas, 4G network signals as the main communication path can provide faster data transmission speed, and Beidou satellite or Iridium satellite as backup to deal with unstable 4G network signals. ​

[0159] The vehicle state multi-source data includes vehicle identification, position, speed, direction, UTC time, elevation, alarm signal, online / offline state and communication mode.

[0160] The position of the vehicle includes vehicle longitude and latitude; the alarm signal includes electronic fence crossing alarm, vehicle state abnormal alarm SOS alarm information.

[0161] The elevation of the vehicle is the altitude of the vehicle.

[0162] The dispatching instructions are sent to each vehicle through the primary / secondary communication mode; wherein the dispatching instructions include electronic fence crossing, SOS emergency alarm, vehicle state abnormal processing dispatching instructions, and manually issued dispatching instructions.

[0163] The digital signature is used to prevent the dispatching instructions from being tampered with; the vehicle terminal verifies the signature and executes the dispatching instructions after passing the verification.

[0164] Beidou-3 global satellite navigation adopts a hybrid constellation of MEO / GEO / IGSO:

[0165] (1) MEO (Medium Earth Orbit), provides global basic positioning;

[0166] (2) GEO (Geostationary Earth Orbit), enhances local area signal, supports short message communication;

[0167] (3) IGSO (Inclined Geosynchronous Orbit) optimizes the positioning capability in high latitude (such as the North Pole) and complex terrain (such as mountainous areas).

[0168] The hybrid constellation design of Beidou satellite realizes high-precision positioning, navigation and timing services with global coverage + regional enhancement.

[0169] The Iridium system is composed of a global communication constellation of 66 low earth orbit (LEO) satellites, which are distributed in 6 orbital planes, each with 11 satellites. The orbit of these satellites is about 780 kilometers high, with an inclination of 86.4 degrees, covering almost every corner of the earth.

[0170] Multi-band antenna receiving technology is adopted to support Beidou RNSS (Satellite Radio Navigation Service) / RDSS (Satellite Radio Determination Service) and Iridium signals. The original state multi-source data is captured, tracked, demodulated and decoded (in accordance with the communication protocol of the corresponding satellite system, such as Beidou BDS-B1I / B2I / B3I, Iridium specific frame structure).

[0171] Extract the payload data.

[0172] The decoded information includes: vehicle identification, location (latitude and longitude), speed, direction, UTC time, elevation, alarm signal, vehicle online / offline status and communication method, and signal-to-noise ratio.

[0173] UTC is the abbreviation of "Coordinated Universal Time", which is the "standard time" used globally, and is the most authoritative and accurate time standard internationally.

[0174] Everywhere in the world has its own local time (such as Beijing time UTC+8), and cross-time zone and cross-country communication is easy to be confused.

[0175] Satellites (Beidou satellites, GPS, Iridium satellites, etc.) and communication systems use UTC as the time reference to ensure global device time consistency and avoid errors.

[0176] Exemplarily,

[0177] If the Beidou satellite sends a piece of data, the timestamp shows "2025-07-2305:30:00UTC":

[0178] Beijing time is 2025-07-2313:30:00 (UTC+8).

[0179] London time is 2025-07-2306:30:00 (UTC+1, summer time).

[0180] UTC is the "world standard time", and satellites and communication systems use UTC time to ensure time synchronization and avoid cross-time zone confusion.

[0181] In the satellite signal communication module of the vehicle management platform, the Beidou communication module uses a Beidou III satellite card; the satellite signal communication module consists of Beidou III satellite signal reception and Iridium satellite reception.

[0182] By adopting a multi-band antenna design supporting multiple frequency bands, multi-band reception is achieved. The Beidou III satellite system realizes global coverage through the combination of MEO (Medium Earth Orbit), GEO (Medium Earth Orbit) and IGSO (Inclined Geosynchronous Orbit) satellites, and provides enhanced services in the Asia-Pacific region.

[0183] Iridium satellite system achieves global coverage through 66 LEO (Low Earth Orbit) satellites, ensuring that users in any location around the world can receive signals from at least one Iridium satellite.

[0184] 4G communication module of the vehicle management platform: high-speed data transmission through 4G network, improving the speed and reliability of data transmission.

[0185] Receive byte stream data through TCP (Transmission Control Protocol) method, convert to decimal or UTF-8 text according to protocol.

[0186] Real-time data transmission ensures real-time and stability of data transmission, reduces data transmission delay.

[0187] The sensors installed on the vehicle terminal cache the vehicle state multi-source data obtained to the vehicle terminal, and then transmit them to the data processing module of the vehicle management platform through the main communication path, which is parsed and signed by the data processing module.

[0188] The command and dispatch instructions are set by the command and dispatch module of the vehicle management platform, signed digitally, and then sent out. After receiving by the vehicle terminal, the dispatch instruction content is parsed and the corresponding operation is performed.

[0189] Exemplarily, the vehicle state multi-source data is obtained by the sensors installed on the vehicle terminal:

[0190] (1) Positioning and navigation sensors, including Beidou / Iridium dual-mode positioning module, obtaining vehicle latitude, longitude, and elevation (altitude of the vehicle's location), UTC time; Inertial Measurement Unit (IMU), short-time positioning compensation through accelerometer + gyroscope in satellite signal blind area (tunnel / underground);

[0191] (2) Vehicle monitoring sensors

[0192] Vehicle speed sensor: obtaining real-time vehicle speed;

[0193] Direction sensor, such as electronic compass, obtaining vehicle heading angle;

[0194] Altitude sensor, such as barometric altimeter, obtaining altitude.

[0195] (3) Safety and alarm sensors

[0196] SOS emergency button, manually triggered by the driver, sending alarm signal through 4G / short message;

[0197] Vehicle door status sensor, magnetic switch (door open / close state detection), combined with electronic fence crossing alarm.

[0198] The vehicle terminal digitally signs the original state multi-source data, and uploads the original state multi-source data to the vehicle management platform through the main / auxiliary communication path based on the reporting frequency of the main / auxiliary communication path through the communication module (including the satellite signal communication module and the 4G communication module);

[0199] The data processing module of the vehicle management platform digitally signs and decodes the received original state multi-source data, and outputs the processed state multi-source data, thereby improving the efficiency and accuracy of data processing.

[0200] The command and dispatch module of the vehicle management platform receives the state multi-source data of each vehicle terminal based on the main communication path and the auxiliary communication path of each vehicle and the reporting frequency of the main communication and the auxiliary communication, sends a dispatch instruction to each vehicle based on the state multi-source data, the historical trajectory of each vehicle, and a preset electronic fence, and realizes real-time monitoring and dispatching of each vehicle.

[0201] The reporting frequency of the main communication path is set by the dispatch instruction, and a default communication rule is set.

[0202] Default rule example:

[0203] From the perspective of ensuring communication, the default rule is that the 4G network mobile signal is the main one, and the Beidou satellite signal is the auxiliary one. If the 4G network mobile signal is very poor, the Beidou signal is the main one, and the Iridium satellite signal is the auxiliary one.

[0204] Rule setting example:

[0205] Since the cost of Iridium satellite is relatively high, and the driving path of the vehicle is smooth and safe, even if the data is lost occasionally for a few minutes, it does not affect safety. Therefore, the rule is set to 4G network as the main one and Beidou satellite as the auxiliary one, and even if the 4G network signal is occasionally poor, Iridium satellite positioning and data transmission and reception are not allowed.

[0206] The 4G network communication is set as the main communication path, the Beidou and Iridium satellites are set as the auxiliary communication path, and the communication interval is ten times the default main communication time interval; the 4G network mobile signal is poor, and the Beidou satellite or Iridium satellite communication is used.

[0207] Through the user interface module of the vehicle management platform, the user is provided with convenient operation and data display functions through Web, iOS, and Android mobile terminal applications; the user operation interface supports the user to view the positions of all vehicles, query the historical trajectories of the vehicles, supports multiple mobile terminal devices such as smartphones, tablet computers, and notebook computers to access and display data of user basic information, vehicle basic information, and vehicle online statistical information.

[0208] For example, Figure 4As shown, the monitoring interface of the vehicle management platform displays the online and offline information, location information, speed information of the vehicle, and the communication mode of the position reporting of the vehicle terminal of the vehicle.

[0209] The vehicle configuration module of the vehicle management platform adds, modifies, and deletes terminal vehicle information, configures the electronic fence range and the validity period, and reports the frequency of the main communication path.

[0210] As shown in the figure, the vehicle state multi-source data is stored in the InfluxDB database according to the time sequence; the time sequence-based state multi-source data is used for real-time playback of the vehicle track. Figure 5

[0211] InfluxDB is an open-source time series database used for storing and querying time series data, which realizes fast querying and playback of vehicle track data. The specific fields stored in InfluxDB include vehicle identification, timestamp, longitude and latitude, speed, direction heading angle, elevation, positioning method, and communication mode.

[0212] The command and dispatch module of the vehicle management platform supports real-time viewing of the vehicle identification, vehicle terminal identification, alarm type, alarm time, and longitude and latitude of the alarm position of each alarm information.

[0213] When the vehicle encounters danger, the driver presses the SOS button (manual triggering by the driver), and sends the alarm information to the vehicle management platform;

[0214] When the vehicle crosses the electronic fence boundary (such as the vehicle entering the restricted area), an automatic cross-border alarm is sent to the vehicle management platform;

[0215] When the vehicle state is abnormal, such as overspeeding or long-time stagnation, an automatic vehicle state abnormality alarm is sent to the vehicle management platform;

[0216] The vehicle electronic fence is set, modified, and deleted through the vehicle management platform.

[0217] The vehicle management platform uses AES-128-CBC encryption + ECDSA-P256 digital signature to prevent the dispatch command from being tampered with; the vehicle terminal verifies the signature and executes the dispatch command.

[0218] The function of step S3 is to use the main and auxiliary communication paths and the reporting frequency of the vehicle, combined with the vehicle state multi-source data and the electronic fence, to realize real-time monitoring, data reception, and intelligent dispatch command sending of the vehicle, so as to improve the reliability and efficiency of vehicle management.

[0219] In summary, the vehicle management method based on Beidou, Iridium, and 4G multi-mode communication has the following beneficial effects:

[0220] ​1、The present application realizes real-time monitoring, data transmission and command scheduling of vehicles through the cooperation of the three modes of 4G+Beidou+Iridium, the high-precision positioning and global coverage capability of the integrated Beidou and Iridium satellite systems, and the high-speed data transmission of the 4G network.

[0221] 2、The communication mode of the main communication path and the auxiliary communication path in the present application also better guarantees the data communication success rate, based on vehicle communication quality data, using a multi-mode communication path selection model, the optimal communication mode is selected as the main communication path, and the main / auxiliary path is automatically switched, realizing global seamless communication coverage in urban, mountainous and oceanic application scenarios, completely eliminating single signal blind area, weak signal interruption and other problems, realizing seamless coverage of the whole world, and communication never dropping;

[0222] 3、The present application introduces an LSTM dynamic decision model as a multi-mode communication path selection model, which can real-time evaluate multi-dimensional communication quality data and task state, and complete main / auxiliary path selection within 5ms; the main path is reported at a high frequency of 10s, and the auxiliary path is reported at a low frequency of 100s, which not only guarantees real-time performance, but also saves more than 70% of communication cost, so as to realize millisecond-level intelligent scheduling and more than 10 times speed improvement;

[0223] 4、The scheduling instruction of the present application adopts AES-128-CBC encryption+ECDSA-P256 digital signature, bidirectional certificate verification, and main / auxiliary dual-channel redundant reporting; any single point link that is broken cannot successfully tamper with or forge the instruction, ensuring the absolute safety and reliability of vehicle remote control and emergency scheduling, realizing end-to-end safety closed loop, zero tampering of scheduling instruction, and improving the efficiency and accuracy of vehicle scheduling;

[0224] 5、The method has wide application prospects in the fields of logistics transportation, public transportation, emergency rescue and the like, and can significantly improve the reliability of vehicle management and the efficiency of command scheduling.

[0225] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing related hardware, and the program can be stored in a computer readable storage medium, wherein the computer readable storage medium is a disk, an optical disk, a read-only memory or a random access memory, etc.

[0226] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any changes or replacements within the technical range disclosed by the present application can be easily thought by those skilled in the art, which should be covered within the protection scope of the present application.

Claims

1. A vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication, characterized in that, include: Obtain communication quality data for each vehicle within a preset unit of time; Based on the communication quality data of each vehicle, a trained multi-mode communication path selection model is used to dynamically evaluate the communication path, obtain the optimal communication method as the main communication path, and select the communication method with lower communication cost as the auxiliary communication path from the remaining communication methods. Based on the main and auxiliary communication paths of each vehicle, as well as the reporting frequencies of the main and auxiliary communications, the system receives multi-source status data of each vehicle. Based on the multi-source status data, historical trajectories, and preset electronic fences of each vehicle, the system sends dispatch instructions to each vehicle to achieve real-time monitoring and dispatch of each vehicle. The communication methods include BeiDou satellites, Iridium satellites, and 4G networks.

2. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 1, characterized in that, The acquisition of communication quality data for each vehicle within a preset unit of time includes: The reference signal received power, reference signal received quality, signal-to-noise ratio, average 4G transmission delay, 4G successful transmission rate, 4G end-to-end transmission time, 4G communication cost, and the number of times 4G is used as the primary or secondary communication method. The signal-to-noise ratio of BeiDou satellites, the number of visible satellites, the positioning accuracy factor, the average transmission delay of BeiDou, the percentage of successful transmissions of BeiDou, the end-to-end transmission time of BeiDou, the cost of BeiDou communication, and the number of times BeiDou is switched between primary and secondary communication. The signal-to-noise ratio, link error rate, average transmission delay, successful transmission rate, end-to-end transmission time, communication cost, and number of times Iridium satellites switch between primary and secondary communication modes.

3. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 2, characterized in that, The trained multi-mode communication path selection model is obtained through the following training process: Construct a training sample set for communication path selection consisting of multiple communication quality data and corresponding vehicle task status data. The sample label is a one-hot encoded vector of all corresponding communication methods, with the optimal communication method being 1 and other communication methods being 0. A multi-mode communication path selection model is constructed, consisting of an input layer, an LSTM network layer, a fully connected classification layer, and an output layer. The multi-mode communication path selection model is trained using the aforementioned communication path selection training sample set; Calculate the weighted cross-entropy loss value between the communication method probability vector output by the model and the sample label; The gradient is calculated using backpropagation based on the weighted cross-entropy loss value; the model weights and parameters are then updated using the Adam optimization algorithm. Training stops when the weighted cross-entropy loss function is minimized by iterating forward propagation, loss calculation, backpropagation, and gradient update. The model parameter with the largest objective function in all iterations is saved as the trained multi-mode communication path selection model.

4. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 3, characterized in that, The objective function is as follows: Among them, SuccessRate is the percentage of successful transmissions within a preset unit of time; Latency is the average end-to-end transmission time from the vehicle to the vehicle management platform within a preset unit of time; CostWeight is the communication cost within a preset unit of time; and SwitchFreq is the number of times the primary and secondary communication are switched within a preset unit of time.

5. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 3, characterized in that, The weighted cross-entropy loss function is as follows: Where Loss is the weighted cross-entropy loss value, C is the total number of communication method categories, and ω i Let y be the weight of the i-th type of communication method; i For real labels; p i This is the probability vector of the communication method predicted by the model.

6. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 3, characterized in that, The input layer is used to normalize the multi-source state data to form an input vector; The LSTM network layer is used to extract features from the input vector and perform ReLU activation to obtain a feature vector; The fully connected classification layer is used to generate scores for the three communication methods from the feature vector; The output layer uses the Softmax function to convert the scores of the three communication methods into a probability vector of the communication method.

7. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 3, characterized in that, The vehicle task status data includes normal mode, emergency mode, and energy-saving mode; If the main communication fails to transmit n times consecutively, the auxiliary communication is triggered to retransmit. In emergency mode, dual-path parallel transmission of primary and secondary communication will be forcibly enabled.

8. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 1, characterized in that, The secondary communication reporting frequency is dynamically set based on the primary communication reporting frequency, as follows: Among them, f s For auxiliary communication reporting frequency, f p The main communication reporting frequency is set to m, which is a preset multiple; ω1 and ω2 are the cost weights of the main communication and auxiliary communication, respectively. The main communication reporting frequency is a dynamically preset value.

9. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to claim 1, characterized in that, The multi-source data on vehicle status includes vehicle identification, location, speed, direction, UTC time, elevation, alarm signal, online / offline status, and communication method; The vehicle's location includes its longitude and latitude; the alarm signals include electronic fence boundary crossing alarm, vehicle status abnormality alarm, and SOS alarm information.

10. The vehicle management method based on BeiDou, Iridium, and 4G multi-mode communication according to any one of claims 1-9, characterized in that, Dispatch instructions are sent to each vehicle via primary / secondary communication; wherein, the dispatch instructions include electronic fence boundary crossing, SOS emergency alarm, vehicle status abnormality handling dispatch instructions, and manually issued dispatch instructions; Digital signatures are used to prevent dispatch instructions from being tampered with; dispatch instructions are executed after the vehicle terminal verifies the signature.

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