Vehicle remote control method and system

Abstract

The invention provides a vehicle remote control method and system, and relates to the field of vehicle networking, and the method comprises the steps: responding to a control instruction from a terminal, and executing a control operation indicated by the control instruction on a target vehicle; instruction features are analyzed from the control instruction, and current vehicle condition information of the target vehicle is obtained; according to the current vehicle condition information and the instruction features, carrying out analog simulation on the vehicle condition of the target vehicle to obtain simulated vehicle condition information; performing information matching on the current vehicle condition information and the simulated vehicle condition information according to the instruction features and preset matching model configuration; and within a preset time range, intercepting vehicle condition information, which is not matched with the simulated vehicle condition information, in the current vehicle condition information to obtain target vehicle condition information, and sending the target vehicle condition information to the terminal, the target vehicle condition information being a set of various vehicle condition information, which is matched with the simulated vehicle condition information, in the current vehicle condition information. Through the method disclosed by the invention, the misoperation risk caused by information hopping is reduced.

Description

Technical Field

[0001] The present disclosure relates to the field of automobile networking, and in particular to a vehicle remote control method and system. Background Art

[0002] With the rapid development of intelligent connected vehicle technology, vehicle remote control functions have gradually become an important part of modern automobiles. Users can remotely operate vehicles through smart terminal devices, such as unlocking, starting vehicles, adjusting air conditioning, etc., which provides great convenience for users. However, in actual applications, users often face the problem of repeated state changes of operation buttons during remote control, which is mainly due to the synchronization delay between vehicle remote control instructions and real-time vehicle condition information. This unstable state not only affects the user's operating experience, but may also cause users to misjudge the vehicle status, thereby causing unnecessary safety hazards.

[0003] Although the related technologies attempt to improve the vehicle's response speed to remote control commands, these solutions often only focus on the vehicle condition feedback after the command is executed, and fail to effectively solve the problem of the state jump of the operation button of the smart terminal device during the reporting of the real vehicle condition information. In addition, the related technologies are relatively inadequate in handling abnormal situations, and are unable to timely and effectively feedback the real vehicle status to the user, resulting in the lack of necessary information support for the user when operating. Summary of the invention

[0004] The embodiments of the present disclosure provide a vehicle remote control method and system, aiming to solve the problems existing in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present disclosure is implemented as follows:

[0006] In a first aspect, an embodiment of the present disclosure provides a vehicle remote control method, the method comprising:

[0007] In response to a control instruction from the terminal, executing a control operation indicated by the control instruction on the target vehicle;

[0008] Parsing command features from the control command and acquiring current vehicle condition information of the target vehicle;

[0009] According to the current vehicle condition information and the instruction characteristics, the vehicle condition of the target vehicle is simulated to obtain simulated vehicle condition information;

[0010] According to the instruction feature and the preset matching model configuration, the current vehicle condition information is matched with the simulated vehicle condition information;

[0011] Within a preset time range, intercept the vehicle condition information in the current vehicle condition information that does not match the simulated vehicle condition information, obtain target vehicle condition information, and send the target vehicle condition information to the terminal. The target vehicle condition information is a collection of various vehicle condition information in the current vehicle condition information that matches the simulated vehicle condition information.

[0012] Optionally, the method further comprises:

[0013] According to the preset abnormality determination rules, the acquired current vehicle condition information of the target vehicle is checked;

[0014] When the current vehicle condition information is detected to be abnormal, the matching between the current vehicle condition information and the simulated vehicle condition information is stopped;

[0015] The current vehicle condition information is sent to the terminal.

[0016] Optionally, according to the instruction feature and a preset matching model configuration, matching the current vehicle condition information with the simulated vehicle condition information includes:

[0017] According to the instruction feature and the preset matching model configuration, each item of vehicle condition information in the current vehicle condition information is compared with each item of corresponding vehicle condition information in the simulated vehicle condition information, and the difference between each item of vehicle condition information is calculated;

[0018] Comparing the difference with a preset threshold;

[0019] For any vehicle condition information in the current vehicle condition information, if the difference is not greater than the preset threshold, it is determined that the vehicle condition information matches the simulated vehicle condition information; if the difference is greater than the preset threshold, it is determined that the vehicle condition information does not match the simulated vehicle condition information.

[0020] Optionally, according to the instruction feature and the preset matching model configuration, each item of vehicle condition information in the current vehicle condition information is compared with each item of corresponding vehicle condition information in the simulated vehicle condition information, and the difference between each item of vehicle condition information is calculated, including:

[0021] According to the instruction characteristics, all vehicle condition information items that need to be compared are determined;

[0022] Extracting corresponding vehicle condition information items from the current vehicle condition information and the simulated vehicle condition information respectively;

[0023] According to the difference calculation method configured by the matching model, the difference of each vehicle condition information item between the current vehicle condition information item and the simulated vehicle condition information item is calculated, wherein the expression of the difference calculation method is:

[0024]

[0025] Wherein, D is the difference, X1 is the value of the current vehicle condition information, and X2 is the value of the simulated vehicle condition information.

[0026] Optionally, simulating the vehicle condition of the target vehicle according to the current vehicle condition information and the instruction feature to obtain simulated vehicle condition information includes:

[0027] Inputting the current vehicle condition information and the instruction features into a simulation model, wherein the simulation model is pre-trained using historical vehicle condition information and historical instruction features as training samples;

[0028] Acquire simulated vehicle condition information corresponding to the current control instruction output by the simulation model;

[0029] Also includes:

[0030] The instruction features are used as historical instruction features, and the current vehicle condition information is used as historical vehicle condition information, and is input into the simulation model to perform iterative training on the simulation model.

[0031] Optionally, the method further comprises:

[0032] In response to an update instruction from the target vehicle, the current vehicle condition information of the target vehicle is updated, and the update instruction is triggered when the target vehicle monitors a change in the current vehicle condition information.

[0033] In a second aspect, an embodiment of the present disclosure provides a vehicle remote control system, which is applied to a vehicle remote control method, the system comprising: a terminal, a target vehicle, a command module, a simulation module and a matching module, wherein the command module, the simulation module and the matching module are deployed in the cloud;

[0034] An instruction module, used for parsing instruction features from the control instruction from the terminal, and forwarding the control instruction to the simulation module and the matching module;

[0035] A simulation module, used to simulate the vehicle condition of the target vehicle according to the current vehicle condition information and the command characteristics to obtain simulated vehicle condition information;

[0036] A matching module is used to match the current vehicle condition information with the simulated vehicle condition information according to the instruction characteristics and a preset matching model configuration; within a preset time range, intercept the vehicle condition information in the current vehicle condition information that does not match the simulated vehicle condition information.

[0037] Optionally, the system further includes an abnormal module, and the abnormal module is deployed in the cloud;

[0038] The abnormal module is used to check the current vehicle condition information of the target vehicle according to the preset abnormality judgment rules; if the current vehicle condition information is found to be abnormal, stop matching the current vehicle condition information with the simulated vehicle condition information; and send the current vehicle condition information to the terminal.

[0039] Optionally, the target vehicle is deployed with a vehicle condition reporting module and a command execution module;

[0040] The vehicle condition reporting module is used to monitor the current vehicle condition information of the target vehicle; when the current vehicle condition information is detected to have changed, an update instruction is triggered, and the update instruction is used to instruct the cloud to update the current vehicle condition information of the target vehicle;

[0041] The instruction execution module is used to respond to the control instruction from the terminal, call the controller to execute the control operation indicated by the control instruction on the target vehicle, and send the execution result to the vehicle condition reporting module.

[0042] Optionally, the instruction module forwards the control instruction to the simulation module and the matching module based on a subscription-publishing mechanism.

[0043] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0044] The present disclosure significantly improves the remote control performance of intelligent connected vehicles by responding to control commands from terminals and performing corresponding control operations. First, by parsing the command features in the control commands and obtaining the current vehicle condition information of the target vehicle, the user's intentions are accurately understood and the vehicle status is reflected in real time. Secondly, the vehicle condition of the target vehicle is simulated using simulation technology to generate simulated vehicle condition information, so that the vehicle's response can be foreseen before actual operation. In particular, the present disclosure matches the current vehicle condition information with the simulated vehicle condition information through a preset matching model configuration, and intercepts the vehicle condition information that does not match the simulated vehicle condition information within a preset time range.

[0045] It effectively filters out irrelevant or erroneous vehicle condition information, ensuring that the target vehicle condition information received by the end user is accurate and reliable, thereby reducing the jump phenomenon of the operation button and improving the user's operating experience and confidence. The present disclosure not only improves the response speed and accuracy of vehicle remote control, but also optimizes the user experience through the information interception mechanism and reduces the risk of misoperation caused by information jump. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 is a schematic diagram of the steps of a vehicle remote control method provided by an embodiment of the present disclosure;

[0048] Figure 2 is a flow chart of a complete vehicle remote control method provided by an embodiment of the present disclosure;

[0049] Figure 3 It is a structural block diagram of a vehicle remote control system provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0051] The present disclosure aims to solve the problems existing in the related art, such as slow response speed of vehicle remote control commands, inaccurate information feedback, and repeated jumps in the status of operation buttons. To this end, the present disclosure proposes an improved vehicle remote control method and system, which effectively improves the performance of vehicle remote control and user operation experience by introducing command feature analysis, simulation and information matching mechanisms. The present disclosure can not only accurately analyze the user's control commands and obtain the vehicle's current vehicle condition information in real time, but also predict the vehicle's response through simulation technology, ensuring that the vehicle condition information received by the terminal user is accurate, thereby reducing instability during operation. Next, the specific implementation methods of the present disclosure and its advantages and effects in practical applications will be described in detail.

[0052] Figure 1 FIG. 1 is a schematic diagram of the steps of a vehicle remote control method provided by an embodiment of the present disclosure, such as Figure 1 As shown, the method includes:

[0053] Step S101, in response to a control instruction from a terminal, executing a control operation indicated by the control instruction on a target vehicle;

[0054] Step S102, parsing command features from the control command and acquiring current vehicle condition information of the target vehicle;

[0055] Step S103, simulating the vehicle condition of the target vehicle according to the current vehicle condition information and the instruction feature to obtain simulated vehicle condition information;

[0056] Step S104, matching the current vehicle condition information with the simulated vehicle condition information according to the instruction feature and the preset matching model configuration;

[0057] Step S105, within a preset time range, intercept the vehicle condition information in the current vehicle condition information that does not match the simulated vehicle condition information, obtain target vehicle condition information, and send the target vehicle condition information to the terminal, wherein the target vehicle condition information is a collection of various vehicle condition information in the current vehicle condition information that matches the simulated vehicle condition information.

[0058] Involving step S101, in the embodiment of the present disclosure, the terminal can be a variety of types of intelligent mobile terminal devices, such as smart phones, tablet computers or other smart devices, etc. Users can conveniently remotely control and monitor the target vehicle by downloading a dedicated application, and perform operations such as unlocking and starting the vehicle. The intelligent network cloud first receives and responds to the control instructions issued by the user through the terminal device. The intelligent network cloud is an integrated cloud computing platform, which is mainly used to support the remote control, data processing and information interaction of intelligent networked vehicles. The present disclosure considers using the intelligent network cloud as a transfer station for control instructions in order to utilize its powerful data processing capabilities, computing capabilities and centralized management advantages to improve the remote control performance of intelligent networked vehicles. For the sake of convenience in the following text, the present disclosure will refer to the intelligent network cloud as the cloud. Once the control instruction is received, the cloud will immediately parse the control instruction, obtain the instruction characteristics of the control instruction, and call the corresponding control module to execute the operation specified in the instruction.

[0059] Involving step S102, in the disclosed embodiment, the instruction feature refers to the specific information and attributes contained in the remote control instruction issued by the user through the smart terminal device. The instruction feature can help the cloud understand the user's intention and perform corresponding processing. The instruction feature may include the instruction type, instruction parameters, instruction timeliness, and instruction context. For example, the control instruction is "turn on the air conditioner, set the temperature to 22 degrees", the instruction type is "turn on the air conditioner"; the instruction parameter is "set the temperature to 22 degrees"; the instruction timeliness is high priority. After parsing the instruction feature, the cloud obtains the current vehicle condition information of the target vehicle through the communication interface with the target vehicle. The current vehicle condition information includes but is not limited to the vehicle status, sensor data, environmental information, etc. By obtaining the current vehicle condition information, the user's control instructions are combined with the actual status of the vehicle to ensure the effectiveness and safety of the instructions.

[0060] Involving step S103, after obtaining the current vehicle condition information and instruction features, a pre-configured simulation model is used to simulate the vehicle condition. The simulation model can be an algorithm or program that can generate a predicted target vehicle condition based on the input instruction features and the current vehicle condition information. The simulation model is based on machine learning, physical simulation or other calculation methods, and is intended to accurately reflect the expected state of the vehicle after executing the instruction. According to the user's instruction, the vehicle condition that needs to be changed is determined. For example, if the instruction is "turn on the air conditioner and set the temperature to 22 degrees", the change in the temperature inside the car after the air conditioner is turned on is simulated. Using the current vehicle condition information as a basis, the actual state of the vehicle is considered. For example, if the temperature inside the car is already close to 22 degrees, the simulation result will characterize that the temperature change after the air conditioner is turned on is small. Optionally, the influence of the external environment, such as external temperature, humidity, etc., can also be considered. Factors in the external environment may affect the rate of change of the temperature inside the car. After simulation, simulated vehicle condition information is generated, including the expected state of the vehicle after executing the user's instruction. For example, the simulated vehicle condition information characterizes that after the air conditioner is turned on, the temperature inside the car is expected to drop to 22 degrees within a period of time.

[0061] Involving step S104, information matching is performed using a preset matching model configuration. The matching model can be an algorithm or a set of rules that is intended to compare the current vehicle condition information with the simulated vehicle condition information to determine the similarity and consistency between them. The matching model can be configured according to different vehicle condition characteristics (such as temperature, humidity, vehicle status, etc.) to ensure the accuracy and reliability of the matching. During the matching process, relevant features such as the temperature inside the vehicle, the air conditioning status, the vehicle lock status, etc. are extracted from the current vehicle condition information and the simulated vehicle condition information. The difference between the current vehicle condition information and the simulated vehicle condition information can also be directly calculated to characterize the similarity between the two. For example, if the simulated vehicle condition information shows that the temperature inside the vehicle is 22 degrees, and the current vehicle condition information shows that it is 21 degrees, if the temperature difference of 1 degree is within the preset threshold, the two values ​​will be judged to be close. It is also possible to judge whether the current vehicle condition information is consistent with the simulated vehicle condition information based on other matching criteria indicated by the matching model configuration. If consistent, it is considered that the state of the vehicle meets the user's instructions; if inconsistent, further processing is required.

[0062] Involving step S105, an interception operation is performed according to a preset time range. The core of the interception mechanism is to ensure that only the vehicle condition information that matches the simulated vehicle condition information is allowed to pass, and the unmatched information will be filtered out. If the status displayed by the current vehicle condition information is inconsistent with the simulated vehicle condition information, the vehicle condition information will be marked as unmatched. After interception and screening, the various vehicle condition information that matches the simulated vehicle condition information in the current vehicle condition information is extracted and integrated into a target vehicle condition information set, which represents the expected state of the vehicle after executing the user's instructions. Finally, the target vehicle condition information is sent to the terminal device. The target vehicle condition information includes various vehicle condition data consistent with the simulated vehicle condition information, which is used to update the user's display on the terminal device to ensure that the user can obtain the latest status of the vehicle in real time.

[0063] The present disclosure significantly improves the remote control performance of intelligent networked vehicles by responding to control instructions from the terminal and performing corresponding control operations. First, by parsing the command features in the control command and obtaining the current vehicle condition information of the target vehicle, the user's intention is accurately understood and the vehicle status is reflected in real time. Secondly, the vehicle condition of the target vehicle is simulated by simulation technology to generate simulated vehicle condition information, so that the response of the vehicle can be foreseen before actual operation. In particular, the present disclosure matches the current vehicle condition information with the simulated vehicle condition information through a preset matching model configuration, and intercepts the vehicle condition information that does not match the simulated vehicle condition information within a preset time range, effectively filtering out irrelevant or erroneous vehicle condition information, ensuring that the target vehicle condition information received by the terminal user is accurate and reliable, thereby reducing the jumping phenomenon of the operation button and improving the user's operating experience and confidence. The present disclosure not only improves the response speed and accuracy of vehicle remote control, but also optimizes the user experience through the information interception mechanism, and reduces the risk of misoperation caused by information jumping.

[0064] Exemplarily, the method also includes: checking the acquired current vehicle condition information of the target vehicle according to preset abnormality judgment rules; if it is detected that the current vehicle condition information is abnormal, stopping the information matching between the current vehicle condition information and the simulated vehicle condition information; and sending the current vehicle condition information to the terminal.

[0065] The preset abnormality judgment rules can define which vehicle condition information is considered abnormal based on the normal working parameters and historical data of the vehicle. For example, the temperature inside the vehicle exceeds the normal range, the sensor data is inconsistent, and the vehicle status does not meet expectations. All of these may be included in the scope of abnormal judgment. After obtaining the current vehicle condition information of the target vehicle, the current vehicle condition information is checked according to the preset abnormality judgment rules, specifically, including data verification, logical judgment, and threshold comparison. If an abnormality is found in the current vehicle condition information during the inspection, the matching process of the current vehicle condition information and the simulated vehicle condition information will be stopped immediately. Because when an abnormality occurs, the simulation results will no longer be reliable. If the simulated vehicle condition information continues to be used as a screening reference, the abnormal current vehicle condition information will be intercepted and screened, and incorrect or unreliable information will be propagated to the end user.

[0066] After stopping information matching, the current vehicle condition information is sent directly to the terminal device, allowing users to understand the real status of the vehicle in a timely manner, especially when an abnormality occurs, users can quickly obtain information and take corresponding measures.

[0067] The present invention timely detects potential problems and takes measures to avoid delivering wrong information to users by checking and processing abnormalities in the current vehicle condition information of the target vehicle, thereby ensuring the accuracy and reliability of the information and further improving the security and user experience of the remote control system of the intelligent networked vehicle.

[0068] Exemplarily, according to the instruction characteristics and the preset matching model configuration, the current vehicle condition information is matched with the simulated vehicle condition information, including: according to the instruction characteristics and the preset matching model configuration, each item of vehicle condition information in the current vehicle condition information is compared with the corresponding item of vehicle condition information in the simulated vehicle condition information one by one, and the difference between each item of vehicle condition information is calculated; the difference is compared with a preset threshold; for any item of vehicle condition information in the current vehicle condition information, if the difference is not greater than the preset threshold, it is determined that the vehicle condition information matches the simulated vehicle condition information; if the difference is greater than the preset threshold, it is determined that the vehicle condition information does not match the simulated vehicle condition information.

[0069] The main purpose of information matching is to ensure the consistency between the current vehicle condition information and the simulated vehicle condition information, so as to determine whether the actual state of the vehicle meets the user's control instructions. During the matching process, each item of data in the current vehicle condition information (such as temperature, humidity, vehicle status, etc.) is compared with the corresponding item in the simulated vehicle condition information, and each vehicle condition feature will be analyzed separately to ensure a meticulous matching process. For example, if the current vehicle condition information shows that the temperature inside the car is 21 degrees, and the simulated vehicle condition information shows 22 degrees, the two values ​​will be compared. For each comparison item, the difference between them is calculated. The difference can be calculated by absolute difference or relative difference. The calculated difference will be compared with the preset threshold, which is used to determine the degree of match between the current vehicle condition information and the simulated vehicle condition information. For example, if the preset threshold is 2 degrees, in the above example, the difference of 1 degree is less than the threshold of 2 degrees, indicating that the two values ​​are matched. According to the comparison results, each vehicle condition information will be judged. If the difference between any vehicle condition information in the current vehicle condition information is not greater than the preset threshold, the vehicle condition information is judged to match the simulated vehicle condition information, that is, the vehicle condition information can be considered reliable and meets the user's control instructions. On the contrary, if the difference is greater than the preset threshold, the vehicle condition information is judged to be inconsistent with the simulated vehicle condition information, indicating that the vehicle status is inconsistent with expectations.

[0070] The present disclosure effectively identifies inconsistent vehicle condition information through precise item-by-item comparison and difference calculation, thereby improving the user's operating experience and reducing the risk of misoperation.

[0071] Exemplarily, according to the instruction feature and the preset matching model configuration, each item of vehicle condition information in the current vehicle condition information is compared with each item of corresponding vehicle condition information in the simulated vehicle condition information, and the difference between each item of vehicle condition information is calculated, including:

[0072] According to the instruction characteristics, all vehicle condition information items that need to be compared are determined;

[0073] Extracting corresponding vehicle condition information items from the current vehicle condition information and the simulated vehicle condition information respectively;

[0074] According to the difference calculation method configured by the matching model, the difference of each vehicle condition information item between the current vehicle condition information item and the simulated vehicle condition information item is calculated, wherein the expression of the difference calculation method is:

[0075]

[0076] Wherein, D is the difference, X1 is the value of the current vehicle condition information, and X2 is the value of the simulated vehicle condition information.

[0077] According to the instruction features, the vehicle condition information items that need to be compared are first identified. Suppose the user issues the instruction "Turn on the air conditioner and set the temperature to 22 degrees." According to the instruction, the vehicle condition information items that need to be compared include: the current temperature inside the vehicle, the air conditioning status (on or off), and the vehicle lock status. The data corresponding to the above-determined vehicle condition information items are extracted from the current vehicle condition information and the simulated vehicle condition information. According to the difference calculation method configured according to the preset matching model, the difference between the current vehicle condition information item and the simulated vehicle condition information item is calculated. In the embodiment of the present disclosure, the similarity is calculated by relative difference.

[0078] For each vehicle condition information extracted, the difference is calculated. Assuming that the current vehicle interior temperature and the simulated vehicle interior temperature are X1=21 and X2=22 respectively, the difference is:

[0079]

[0080] It should be noted that the temperature inside the car is a typical numerical vehicle condition information, but most vehicle condition information is non-numerical information. For example, the air-conditioning status has only two indications, on and off, and needs to be converted into numerical values ​​for comparison. The "on" state can be pre-assigned a first numerical value, and the "off" state can be pre-assigned a second numerical value, and then substituted into the above formula for calculation.

[0081] Through the above steps, the current vehicle condition information and the simulated vehicle condition information can be effectively compared item by item, the difference can be calculated and a matching judgment can be made, thereby ensuring the accuracy and reliability of the intelligent connected vehicle during remote control.

[0082] Exemplarily, simulating the vehicle condition of the target vehicle according to the current vehicle condition information and the instruction feature to obtain simulated vehicle condition information includes: inputting the current vehicle condition information and the instruction feature into a simulation model, wherein the simulation model is pre-trained using historical vehicle condition information and historical instruction features as training samples; and obtaining simulated vehicle condition information corresponding to the current control instruction output by the simulation model;

[0083] Also includes:

[0084] The instruction features are used as historical instruction features, and the current vehicle condition information is used as historical vehicle condition information, and is input into the simulation model to perform iterative training on the simulation model.

[0085] The simulation aims to predict the state of the target vehicle under a specific instruction by analyzing the current vehicle condition information and instruction characteristics. The simulation model is a pre-trained algorithm model, optionally built using machine learning or deep learning technology, and its training samples include historical vehicle condition information and historical instruction characteristics. By using historical data for pre-training, the simulation model can learn the response mode of the vehicle under different instructions, so that when receiving new instructions, it can generate corresponding simulated vehicle condition information.

[0086] The current vehicle condition information and instruction features are input into the simulation model, and the simulation model outputs the simulated vehicle condition information corresponding to the current control instruction based on its internal learning and training. For example, if the current vehicle condition information shows that the temperature inside the car is 21 degrees, and the user instruction is "set the temperature to 22 degrees", the simulation model can output "the simulated temperature inside the car is 22 degrees, and the air conditioning state is on".

[0087] In order to continuously improve the accuracy of the simulation model, the current command features and current vehicle condition information are input into the simulation model as new historical data. By continuously updating the model's training data, it can better adapt to new situations and changes. The simulation model will adjust and optimize based on the new data to improve future prediction capabilities. For example, if in a certain operation, the user's command is to "turn on the air conditioner", and the actual vehicle condition shows that the air conditioner fails to turn on normally, the simulation model records this situation and takes this feedback into account in future training to better simulate similar scenarios.

[0088] The present invention utilizes the current vehicle condition information and command features to generate accurate simulated vehicle condition information through simulation model. At the same time, the iterative training process ensures the continuous optimization and adaptability of the model, thereby improving the performance and user experience of remote control of intelligent connected vehicles.

[0089] Exemplarily, the method further includes: updating current vehicle condition information of the target vehicle in response to an update instruction from the target vehicle, wherein the update instruction is triggered when the target vehicle detects a change in the current vehicle condition information.

[0090] When the vehicle's internal system or sensor detects changes in vehicle condition information, it automatically generates and sends update instructions so that the cloud can obtain the latest status of the target vehicle in a timely manner. The monitoring system of the target vehicle tracks and records various vehicle condition information (such as fuel volume, speed, temperature, fault status, etc.) in real time. Once the current vehicle condition information is found to have changed, an update instruction will be generated through the vehicle condition reporting module. For example, if the vehicle's fuel volume drops from 50 liters to 45 liters, or the vehicle speed increases from 0 to 10 kilometers per hour, these changes will trigger the generation of an update instruction. Once the update instruction is triggered, the update instruction will be sent to the cloud platform of the target vehicle for subsequent processing and recording. After receiving the update instruction, the cloud updates the current vehicle condition information according to the information in the instruction.

[0091] The present invention timely updates the current vehicle condition information so that the intelligent connected vehicle can maintain the accuracy and real-time nature of the information during operation, thereby improving the reliability of remote control.

[0092] Figure 2 is a flow chart of a complete vehicle remote control method provided by an embodiment of the present disclosure, such as Figure 2 As shown, in the disclosed embodiment, the user first sends a control instruction through the terminal. After the cloud receives the control instruction, the instruction is first parsed and cached. The parsed instruction features will be forwarded to different processing modules. In the left branch, the target vehicle condition is simulated based on the parsed instruction features, simulation model and the actual vehicle condition information of the current vehicle, a simulated vehicle condition information is generated, and this information is returned to the mobile terminal so that the user can understand the expected state of the vehicle. In the right branch, the actual vehicle condition of the current vehicle is intercepted based on the instruction features and interception model configuration, and the vehicle condition information that does not match the simulated vehicle condition is screened out. At the same time, the abnormal monitoring mechanism is turned on to monitor in real time whether there is an abnormal situation of the remote control operation. Once an abnormality is detected, the interception process of the vehicle condition will be immediately interrupted, and the real vehicle condition information will be fed back to the mobile terminal to ensure that the user can obtain the actual state of the vehicle in a timely manner. It can not only provide accurate simulated vehicle condition information, but also effectively intercept mismatched vehicle conditions, thereby improving the user's operating experience and safety.

[0093] Figure 3 is a structural block diagram of a vehicle remote control system provided by an embodiment of the present disclosure, such as Figure 3 As shown, the system is applied to a vehicle remote control method as described above, and includes: a terminal 201, a target vehicle 202, an instruction module 203, a simulation module 204 and a matching module 205, and the instruction module 203, the simulation module 204 and the matching module 205 are deployed in the cloud;

[0094] The instruction module 203 is used to parse the instruction feature from the control instruction from the terminal 201, and forward the control instruction to the simulation module 204 and the matching module 205;

[0095] The simulation module 204 is used to simulate the vehicle condition of the target vehicle according to the current vehicle condition information and the command characteristics to obtain simulated vehicle condition information;

[0096] The matching module 205 is used to match the current vehicle condition information with the simulated vehicle condition information according to the instruction characteristics and the preset matching model configuration; within a preset time range, intercept the vehicle condition information in the current vehicle condition information that does not match the simulated vehicle condition information.

[0097] Exemplarily, the system further includes an exception module 206, which is deployed in the cloud;

[0098] The abnormality module 206 is used to check the acquired current vehicle condition information of the target vehicle according to the preset abnormality judgment rules; if the current vehicle condition information is found to be abnormal, stop the information matching between the current vehicle condition information and the simulated vehicle condition information; and send the current vehicle condition information to the terminal.

[0099] Exemplarily, the target vehicle is deployed with a vehicle condition reporting module 207 and a command execution module 208;

[0100] The vehicle condition reporting module 207 is used to monitor the current vehicle condition information of the target vehicle 202; when the current vehicle condition information is detected to have changed, an update instruction is triggered, and the update instruction is used to instruct the cloud to update the current vehicle condition information of the target vehicle;

[0101] The instruction execution module is used to respond to the control instruction from the terminal 201, call the controller to execute the control operation indicated by the control instruction on the target vehicle 202, and send the execution result to the vehicle condition reporting module 207.

[0102] Exemplarily, the instruction module forwards the control instruction to the simulation module and the matching module based on a subscription-publishing mechanism.

[0103] The instruction module acts as a publisher and publishes the parsed control instructions to a specific message channel.

[0104] The message channel can be a topic, and modules that subscribe to the topic can receive messages from the instruction module. As subscribers, the simulation module and the matching module have subscribed to the message channel published by the instruction module in advance. When the instruction module publishes a control instruction, the simulation module and the matching module automatically receive the control instruction and perform corresponding processing according to the instruction characteristics.

[0105] The present disclosure considers using the subscription publishing mechanism as the forwarding rule, considering that the main advantage of the subscription publishing mechanism is the decoupling between modules. The instruction module does not need to know the specific implementation or status of the simulation module and the matching module, and only needs to publish the message to the channel, thereby improving the overall response speed and processing capability.

[0106] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods and systems. Therefore, the embodiments of the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present disclosure may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] The embodiments of the present disclosure are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing terminal device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded into a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0108] Although the preferred embodiments of the present disclosure have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present disclosure.

[0109] Finally, it should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "include..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements. A vehicle remote control method and system provided by the present disclosure are described in detail above. The principle and implementation method of the present disclosure are explained in this article using specific examples. The description of the above embodiments is only used to help understand the method and its core idea of ​​the present disclosure; at the same time, for those of ordinary skill in the art, according to the idea of ​​the present disclosure, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present disclosure.

Claims

1. A vehicle remote control method, characterized in that: The method comprises: In response to a control instruction from the terminal, executing a control operation indicated by the control instruction on the target vehicle; Parsing command features from the control command and acquiring current vehicle condition information of the target vehicle; According to the current vehicle condition information and the instruction characteristics, the vehicle condition of the target vehicle is simulated to obtain simulated vehicle condition information; According to the instruction feature and the preset matching model configuration, the current vehicle condition information is matched with the simulated vehicle condition information; Within a preset time range, intercept the vehicle condition information in the current vehicle condition information that does not match the simulated vehicle condition information, obtain target vehicle condition information, and send the target vehicle condition information to the terminal. The target vehicle condition information is a collection of various vehicle condition information in the current vehicle condition information that matches the simulated vehicle condition information.

2. The method according to claim 1, characterized in that The method further comprises: According to the preset abnormality determination rules, the acquired current vehicle condition information of the target vehicle is checked; When the current vehicle condition information is detected to be abnormal, the matching between the current vehicle condition information and the simulated vehicle condition information is stopped; The current vehicle condition information is sent to the terminal.

3. The method according to claim 1, characterized in that According to the instruction feature and the preset matching model configuration, the current vehicle condition information is matched with the simulated vehicle condition information, including: According to the instruction feature and the preset matching model configuration, each item of vehicle condition information in the current vehicle condition information is compared with each item of corresponding vehicle condition information in the simulated vehicle condition information, and the difference between each item of vehicle condition information is calculated; Comparing the difference with a preset threshold; For any vehicle condition information in the current vehicle condition information, if the difference is not greater than the preset threshold, it is determined that the vehicle condition information matches the simulated vehicle condition information; if the difference is greater than the preset threshold, it is determined that the vehicle condition information does not match the simulated vehicle condition information.

4. The method according to claim 3, characterized in that According to the instruction feature and the preset matching model configuration, each item of vehicle condition information in the current vehicle condition information is compared with each item of corresponding vehicle condition information in the simulated vehicle condition information, and the difference between each item of vehicle condition information is calculated, including: According to the instruction characteristics, all vehicle condition information items that need to be compared are determined; Extracting corresponding vehicle condition information items from the current vehicle condition information and the simulated vehicle condition information respectively; According to the difference calculation method configured by the matching model, the difference of each vehicle condition information item between the current vehicle condition information item and the simulated vehicle condition information item is calculated, wherein the expression of the difference calculation method is: Wherein, D is the difference, X1 is the value of the current vehicle condition information, and X2 is the value of the simulated vehicle condition information.

5. The method according to claim 1, characterized in that The simulating the vehicle condition of the target vehicle according to the current vehicle condition information and the instruction feature to obtain simulated vehicle condition information includes: Inputting the current vehicle condition information and the instruction features into a simulation model, wherein the simulation model is pre-trained using historical vehicle condition information and historical instruction features as training samples; Acquire simulated vehicle condition information corresponding to the current control instruction output by the simulation model; Also includes: The instruction features are used as historical instruction features, and the current vehicle condition information is used as historical vehicle condition information, and is input into the simulation model to perform iterative training on the simulation model.

6. The method according to claim 1, characterized in that The method further comprises: In response to an update instruction from the target vehicle, the current vehicle condition information of the target vehicle is updated, and the update instruction is triggered when the target vehicle monitors a change in the current vehicle condition information.

7. A vehicle remote control system, characterized in that: Applied to the method according to any one of claims 1 to 6, the system comprises: a terminal, a target vehicle, a command module, a simulation module and a matching module, wherein the command module, the simulation module and the matching module are deployed in the cloud; An instruction module, used for parsing instruction features from the control instruction from the terminal, and forwarding the control instruction to the simulation module and the matching module; A simulation module, used to simulate the vehicle condition of the target vehicle according to the current vehicle condition information and the command characteristics to obtain simulated vehicle condition information; A matching module is used to match the current vehicle condition information with the simulated vehicle condition information according to the instruction characteristics and a preset matching model configuration; within a preset time range, intercept the vehicle condition information in the current vehicle condition information that does not match the simulated vehicle condition information.

8. The system according to claim 7, characterized in that The system further includes an abnormal module, which is deployed in the cloud; The abnormal module is used to check the current vehicle condition information of the target vehicle according to the preset abnormality judgment rules; if the current vehicle condition information is found to be abnormal, stop matching the current vehicle condition information with the simulated vehicle condition information; and send the current vehicle condition information to the terminal.

9. The system according to claim 7, characterized in that The target vehicle is equipped with a vehicle condition reporting module and a command execution module; The vehicle condition reporting module is used to monitor the current vehicle condition information of the target vehicle; when the current vehicle condition information is detected to have changed, an update instruction is triggered, and the update instruction is used to instruct the cloud to update the current vehicle condition information of the target vehicle; The instruction execution module is used to respond to the control instruction from the terminal, call the controller to execute the control operation indicated by the control instruction on the target vehicle, and send the execution result to the vehicle condition reporting module.

10. The system according to claim 7, characterized in that The instruction module forwards the control instruction to the simulation module and the matching module based on a subscription publishing mechanism.

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