Intelligent travel method and device based on artificial intelligence, equipment and storage medium

Abstract

The invention discloses an intelligent travel method, device and equipment based on artificial intelligence and a storage medium, and relates to the technical field of vehicle control, and the intelligent travel method based on artificial intelligence comprises the steps: obtaining a first reference instruction and a vehicle operation historical record; obtaining a second reference instruction according to the vehicle operation historical record and the first reference instruction; sending the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction; and based on the correction instruction and the second reference instruction, a target instruction is obtained, so that vehicle control is completed according to the target instruction. The vehicle environment is adjusted in advance by monitoring the in-vehicle environment temperature, the seat temperature, the steering wheel temperature and the like of the vehicle and combining the vehicle using habit of a vehicle owner and the capacity of the vehicle, and the more comfortable vehicle using environment is provided for the vehicle owner.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to smart travel methods, devices, equipment and storage media based on artificial intelligence. Background Art

[0002] As intelligence, electrification and networking become the development trend of the automotive industry, car owners have increasing requirements for vehicle travel and experience. They expect that the vehicle can automatically adjust to the best state before using it to provide a comfortable travel environment. This demand has promoted the research and development of vehicle intelligent control systems, in order to achieve automatic optimization of the vehicle environment through technical means.

[0003] Most vehicles on the market currently only support separate air conditioning control, which often cannot quickly create a comfortable in-car environment in bad weather. In addition, these systems usually lack the ability to monitor and pre-process the status of vehicle components in real time, resulting in damage to vehicle components under extreme conditions or after long-term use, affecting vehicle performance and service life.

[0004] There are two main problems with existing control methods: first, the ability to adjust the in-vehicle environment is limited, which cannot meet the personalized comfort needs of car owners; second, the lack of real-time monitoring and preventive maintenance of vehicle component status leads to a high failure rate. These problems limit the optimization of vehicle performance and the improvement of owner experience. Therefore, how to intelligently adjust the vehicle travel environment according to the owner's habits has become an urgent problem to be solved. Summary of the invention

[0005] The purpose of this application is to provide a smart travel method, device, equipment and storage medium based on artificial intelligence, aiming to solve the technical problem of how to intelligently adjust the vehicle travel environment according to the owner's habits. To achieve the above purpose, this application proposes a smart travel method based on artificial intelligence, the method comprising:

[0006] Obtaining a first reference instruction and a vehicle operation history record;

[0007] Obtaining a second reference instruction according to the vehicle operation history record and the first reference instruction;

[0008] Sending the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction;

[0009] Based on the correction command and the second reference command, a target command is obtained so that vehicle control is completed according to the target command.

[0010] In one embodiment, before obtaining the first reference instruction and the vehicle operation history record, the method further includes:

[0011] Get sensor data and preset combination instructions;

[0012] Based on the sensor data, obtaining an initial instruction;

[0013] Based on the initial instruction and the preset combined instruction, a first reference instruction is obtained.

[0014] In one embodiment, obtaining a second reference instruction according to the vehicle operation history record and the first reference instruction includes:

[0015] Performing data cleaning on the vehicle operation history records to obtain reference vehicle operation history records;

[0016] Based on a preset algorithm and the reference vehicle operation history record, obtaining an extended instruction;

[0017] A second reference instruction is obtained based on the extended instruction and the first reference instruction.

[0018] In one embodiment, after obtaining the second reference instruction according to the vehicle operation history record and the first reference instruction, the method further includes:

[0019] Obtain vehicle driving data and preset vehicle driving safety data;

[0020] If the vehicle driving data is less than or equal to the preset vehicle driving safety data, obtaining the remaining safe driving data of the vehicle based on the vehicle driving data and the preset vehicle driving safety data;

[0021] If the vehicle driving data is greater than or equal to the preset vehicle driving safety data, an alarm message is sent.

[0022] In one embodiment, if the vehicle driving data is greater than or equal to the preset vehicle driving safety data, an alarm message is sent, including:

[0023] Obtain recording device information and request signals;

[0024] Obtaining identification information of the terminal device according to the request signal;

[0025] If the identification information of the terminal device matches the recording device information, an alarm signal is sent.

[0026] In one embodiment, if the vehicle driving data is greater than or equal to the preset vehicle driving safety data, after sending the alarm information, the method further includes:

[0027] Get the current vehicle location, cloud-annotated location, and map data;

[0028] Based on the current vehicle position, the cloud-annotated position and map data, reference road information is obtained.

[0029] In one embodiment, the method further comprises: obtaining a target instruction based on the correction instruction and the second reference instruction so that after the vehicle control is completed according to the target instruction, the method further comprises:

[0030] Get the preset time;

[0031] Based on the preset time, obtain the vehicle operation history record within the preset time;

[0032] Obtaining a correction instruction based on a preset algorithm, the vehicle operation history record and the vehicle operation history record within the preset time;

[0033] The correction instruction is updated to the second reference instruction.

[0034] In addition, to achieve the above objectives, the present application also proposes a smart travel device based on artificial intelligence, the device comprising:

[0035] An acquisition module, used for acquiring a first reference instruction and a vehicle operation history record;

[0036] An obtaining module, configured to obtain a second reference instruction according to the vehicle operation history record and the first reference instruction;

[0037] A sending module, used for sending the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction;

[0038] The control module is used to obtain a target instruction based on the correction instruction and the second reference instruction, so as to complete vehicle control according to the target instruction.

[0039] In addition, to achieve the above-mentioned objectives, the present application also proposes an artificial intelligence-based smart travel device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the artificial intelligence-based smart travel method as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the smart travel method based on artificial intelligence as described above are implemented.

[0041] In addition, to achieve the above-mentioned objectives, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the smart travel method based on artificial intelligence as described above.

[0042] One or more technical solutions proposed in this application have at least the following technical effects:

[0043] This application first obtains the first reference instruction and the vehicle operation history record, and can comprehensively consider the historical operation data of the vehicle and the current instruction requirements; then, using this information, a second reference instruction is obtained to more accurately guide the operation of the vehicle; then, the second reference instruction is sent to the preset device, and the device feeds back a correction instruction based on this instruction to further optimize the vehicle control strategy; finally, the correction instruction and the second reference instruction are combined to generate a target instruction to achieve precise vehicle control, thereby improving the efficiency and comfort of vehicle operation. This application ensures the intelligence and adaptability of vehicle control, so that the vehicle can intelligently adjust the operating state according to real-time data and historical experience to achieve the best performance and safety standards. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] In order to more clearly illustrate the embodiments of the present application 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, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0046] Figure 1 A flowchart of the first embodiment of the smart travel method based on artificial intelligence provided by this application;

[0047] Figure 2 A flow chart of the second embodiment of the smart travel method based on artificial intelligence provided by this application;

[0048] Figure 3 This is a schematic diagram of the module structure of the smart travel device based on artificial intelligence according to an embodiment of the present application;

[0049] Figure 4 This is a schematic diagram of the device structure of the hardware operating environment involved in the artificial intelligence-based smart travel method in the embodiment of the present application.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] As intelligence, electrification and networking become the development trend of the automotive industry, car owners have increasing travel requirements and experience needs for vehicles. They expect that the vehicle can automatically adjust to the best state before using the car to provide a comfortable travel environment. This demand has promoted the research and development of vehicle intelligent control systems, in order to achieve automatic optimization of the vehicle environment through technical means. At present, most vehicles on the market only support separate air-conditioning control, which often cannot quickly create a comfortable in-car environment in bad weather. In addition, these systems usually lack the ability to monitor and pre-process the status of vehicle components in real time, resulting in damage to vehicle components under extreme conditions or after long-term use, affecting vehicle performance and service life. There are two main problems with existing vehicle control methods: first, the ability to adjust the in-car environment is limited, which cannot meet the personalized needs of car owners for comfort; second, the lack of real-time monitoring and preventive maintenance of the status of vehicle components leads to a high failure rate. These problems limit the optimization of vehicle performance and the improvement of owner experience.

[0054] The main solution of the embodiment of the present application is: the embodiment first obtains the first reference instruction and the vehicle operation history record, which can comprehensively consider the historical operation data of the vehicle and the current instruction requirements; then, using this information, a second reference instruction is obtained to more accurately guide the operation of the vehicle; then, the second reference instruction is sent to the preset device, and the device feeds back the correction instruction according to this instruction to further optimize the vehicle control strategy; finally, the target instruction is generated by combining the correction instruction and the second reference instruction to achieve precise vehicle control, thereby improving the efficiency and comfort of vehicle operation. This embodiment ensures the intelligence and adaptability of vehicle control, so that the vehicle can intelligently adjust the operating state according to real-time data and historical experience to achieve the best performance and safety standards.

[0055] It should be noted that the execution subject of the embodiment of the present application can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device that can realize the above functions. The following takes the electronic control unit as an example to illustrate this embodiment and the following embodiments.

[0056] Based on this, the embodiment of the present application provides a smart travel method based on artificial intelligence, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the artificial intelligence-based smart travel method of this application.

[0057] In this embodiment, the artificial intelligence-based smart travel method includes steps S10 to S40:

[0058] Step S10, obtaining a first reference instruction and a vehicle operation history record;

[0059] It should be noted that the first reference instruction may refer to an instruction formed based on the owner's vehicle usage habits, preset vehicle settings or immediate vehicle usage needs. These instructions may include the owner's specific operation requests for the vehicle, such as set target temperature, seat adjustment preferences, driving mode selection, etc., or the vehicle's startup parameters automatically generated according to a preset program. The vehicle operation history record may be a data record accumulated by the vehicle in the past operation, including but not limited to mileage, fuel consumption, maintenance records, fault records, driving behavior patterns, etc. These historical records provide the system with background information on vehicle usage and performance, which helps the system analyze the vehicle's usage patterns and potential problem points.

[0060] It can be understood that this step is to obtain the operating instructions set by the car owner, as well as the vehicle's past operating data records, including mileage, fuel consumption, maintenance and fault history, etc., so as to integrate these real-time and historical information to provide comprehensive data support for the vehicle's intelligent control.

[0061] As an example, before obtaining the first reference instruction and the vehicle operation history record, it also includes: obtaining sensor data and a preset combination instruction; obtaining an initial instruction based on the sensor data; and obtaining a first reference instruction based on the initial instruction and the preset combination instruction.

[0062] Among them, the sensor data can be real-time data collected by various sensors on the vehicle, including but not limited to temperature sensors, pressure sensors, speed sensors, etc. These data reflect the current physical state and environmental conditions of the vehicle, such as the temperature inside the vehicle, the engine temperature, the tire pressure, the vehicle speed, etc. The initial instruction is an instruction directly derived from the sensor data, which represents the system's immediate response to the current vehicle state. For example, if the temperature sensor shows that the temperature inside the vehicle is too high, the initial instruction may be to lower the air conditioning temperature. The preset combination instruction can be an instruction set composed of conditions and rules preset by the owner. These instructions may include default settings when the vehicle is started, safety checklists, energy-saving mode settings, etc. The preset combination instruction reflects the normal operation mode of the vehicle and the owner's personal preferences. For example, the temperature sensor data of the steering wheel, the sensor data of the main driver's seat, and the air conditioning adjustment mode are integrated to obtain the initial data of the steering wheel and main driver's seat temperature corresponding to 10 minutes after adjusting the air conditioning cold wind level 4. When the owner's preset combination is obtained as a steering wheel temperature of 23 degrees and a main driver's seat temperature of 25 degrees, the first reference instruction set by the owner's preset combination can be achieved by adjusting the air conditioning cold wind level 4 internal circulation for 11 minutes.

[0063] Specifically, real-time data from various vehicle sensors, such as temperature, pressure, and speed, are first collected, and then initial instructions for the current vehicle state are generated based on these sensor data. Next, these initial instructions are combined with pre-set combined instructions to obtain the first reference instructions, which is the basis for the subsequent intelligent control process. It combines the real-time physical state and the preset operation logic, providing a starting point for the intelligent control of the vehicle.

[0064] Step S20, obtaining a second reference instruction according to the vehicle operation history record and the first reference instruction;

[0065] It should be noted that the second reference instruction refers to a further refined and optimized instruction generated after comprehensive analysis of the vehicle's operating history data and the first reference instruction generated based on current sensor data and preset combined instructions. This instruction takes into account the vehicle's past operating mode, performance trends and maintenance records, as well as the current vehicle status and the owner's immediate needs, and is used to more accurately guide the operation and control of the vehicle to achieve more efficient, safe and personalized vehicle operation.

[0066] It can be understood that by analyzing the vehicle's operating history and the first reference instructions generated based on sensor data and preset combination instructions, and combining this information to generate a second reference instruction, this instruction can more accurately reflect the vehicle's actual operating needs and the owner's driving habits, and provide more refined guidance for the vehicle's intelligent control.

[0067] As an example, after obtaining the second reference instruction based on the vehicle operation history record and the first reference instruction, it also includes: obtaining vehicle driving data and preset vehicle driving safety data; if the vehicle driving data is less than or equal to the preset vehicle driving safety data, then obtaining the vehicle's remaining safe driving data based on the vehicle driving data and the preset vehicle driving safety data; if the vehicle driving data is greater than or equal to the preset vehicle driving safety data, then sending an alarm message.

[0068] Among them, the vehicle driving data may be data collected during the actual driving process of the vehicle, which may include real-time information such as the current vehicle speed, the distance traveled, the remaining fuel, and the tire wear. The preset vehicle driving safety data may be a safety threshold pre-set according to the vehicle manufacturer's recommendations, regulatory requirements, or the owner's personal settings, such as the maximum speed limit, the maximum driving distance, the fuel warning threshold, etc. The remaining safe driving data of the vehicle may be the distance or time that the vehicle can still safely drive calculated based on the vehicle's current driving data and the preset safety data. For example, if the vehicle's fuel level is lower than the preset threshold, the system will calculate the distance that the vehicle can still drive based on the current fuel level. The alarm information may be an alarm message sent when the vehicle's driving data reaches or exceeds the preset safety data to remind the driver or the vehicle management system to take necessary safety measures. The alarm information may be a visual, auditory, or tactile warning, such as a warning light on the dashboard, a sound alarm, or a seat vibration, etc., or it may be sent to the central control screen or a terminal device bound to the user, etc., in order to ensure vehicle safety and prevent accidents.

[0069] Specifically, the actual driving data of the vehicle and the preset safety threshold are first collected, and then the two data are compared: if the actual driving data (such as speed or mileage) is within the safety threshold, the system will calculate the distance or time that the vehicle can still drive safely; if the actual driving data exceeds the safety threshold, the system will automatically send an alarm message to remind the driver or make other safety responses to ensure the safety of the vehicle. This process is designed to monitor the vehicle status in real time and prevent potential safety risks.

[0070] As an example, if the vehicle driving data is greater than or equal to the preset vehicle driving safety data, an alarm message is sent, including: obtaining recording device information and a request signal; obtaining identification information of the terminal device according to the request signal; if the identification information of the terminal device matches the recording device information, an alarm signal is sent.

[0071] Among them, the recorded device information can be device-related information stored inside the system, which may include the device model, serial number, registration information, etc., which are used to uniquely identify and verify the device. The request signal can be a signal or request sent from a terminal device, which may be for obtaining services, data transmission, or performing an operation. This request signal may contain specific instructions or queries that need to be processed. The identification information can be the unique identification information of the terminal device, which can be a device ID, MAC address, or other form of unique identifier, which is used to identify and distinguish different terminal devices in a network or system.

[0072] Specifically, the request signal from the terminal device is first collected and the device information is recorded, and then the identification information of the terminal device, such as the device ID or MAC address, is extracted from the request signal. If these identification information matches the device information recorded by the system, indicating that the request comes from a known and trusted device, the system will send an alarm signal, which may be to confirm that the security check has passed, trigger an early warning mechanism, or execute other predetermined security response measures. This process ensures that only verified devices can trigger specific system responses, enhancing the security and responsiveness of the system.

[0073] As an example, if the vehicle driving data is greater than or equal to the preset vehicle driving safety data, after sending the alarm information, it also includes: obtaining the current vehicle position, the position marked in the cloud and the map data; based on the current vehicle position, the position marked in the cloud and the map data, obtaining reference road information.

[0074] Among them, the current vehicle position can be the actual geographical location of the vehicle at a certain moment, usually obtained through GPS or other positioning systems, which can provide the latitude and longitude coordinates of the vehicle. The cloud-annotated location can be preset location information related to the vehicle stored on the cloud server. These locations may include vehicle repair shops, gas stations, and other places that can solve the corresponding problems of alarm signals. Map data can be a detailed map containing information such as roads, traffic rules, and geographical features. This data can come from a digital map service provider and is used to assist navigation and route planning. Reference road information can be road information obtained through a comprehensive analysis of the current vehicle position, the cloud-annotated location, and map data, which is used to assist driving decisions. This may include the best driving route, traffic conditions, estimated arrival time, road construction information, etc., to help vehicles plan routes and make corresponding driving adjustments.

[0075] Specifically, first obtain the real-time geographic location of the vehicle, that is, the current vehicle location, through GPS or other positioning technologies. At the same time, retrieve the preset location information related to the vehicle from the cloud server, such as the repair shop or gas station that the owner frequently visits. These cloud-annotated locations help personalized navigation services. In addition, access the latest map data, including road networks, traffic rules, real-time traffic conditions and other information. Combining these three - the precise current vehicle location, personalized cloud location annotations and detailed map data, the reference road information of the vehicle is calculated, which includes the recommended best driving route, estimated driving time and possible traffic conditions, etc., to provide real-time and accurate navigation services for the vehicle, and assist driving decisions to ensure driving safety and efficiency.

[0076] Step S30, sending the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction;

[0077] It should be noted that the preset device can be a device or system component that receives and processes instructions that is pre-set or specified in the vehicle system. These devices can be control units inside the vehicle, such as an engine control unit (ECU), a body control module (BCM) or other sensors and actuators, or they can be devices outside the vehicle, such as smartphone applications, telematics systems or cloud servers, which can receive instructions from the vehicle and respond. The revised instruction refers to the adjusted or optimized instruction returned by the preset device after processing the received second reference instruction. These revised instructions may include fine-tuning of the original instructions to ensure that the vehicle control is more accurate and adapts to actual operating conditions. For example, based on the preset combined instruction of getting on the car at 8 o'clock every day, the first reference instruction of the car controlling the vehicle components to reach a comfortable temperature (which can be set by the owner) at 8 o'clock is obtained. According to the vehicle operation history record, the car gets on the car at 7:50 every day, and the second reference instruction of the car controlling the vehicle components to reach a comfortable temperature at 7:50 is obtained. However, when the owner obtains the second reference instruction, he believes that the actual trip should be 7:55, so the revised instruction of the car controlling the vehicle components to reach a comfortable temperature at 7:55 is fed back.

[0078] It is understood that the second reference instruction generated based on the vehicle operation history and the first reference instruction is sent to a preset device, such as a vehicle control unit or an external monitoring system. These preset devices will feedback correction instructions based on the received second reference instructions, and these correction instructions may include adjustments or supplements to the original instructions to ensure that the vehicle control is more precise and adapted to actual operating conditions, thereby optimizing vehicle performance and safety. Correcting instructions based on instructions and its own real-time data feedback to optimize vehicle control and response helps to improve the intelligence level of the vehicle system and ensure that vehicle operation is safer, more efficient and personalized.

[0079] Step S40, obtaining a target instruction based on the correction instruction and the second reference instruction, so as to complete vehicle control according to the target instruction.

[0080] It should be noted that the target instruction can be the final control instruction formed by combining the correction instruction and the second reference instruction. This target instruction is the direct basis for the vehicle control system to perform specific operations. It integrates the correction instruction fed back from the preset device (which may include the response to environmental changes or the adjustment of the device status) and the previously generated second reference instruction (based on the vehicle operation history and the first reference instruction). The target instruction ensures that the vehicle's control action can accurately meet the current driving conditions, safety requirements and the personalized needs of the owner, and realizes the intelligent control of the vehicle, including but not limited to adjusting the vehicle's power output, braking system, steering system, in-vehicle environment control, etc., to complete a safe, efficient and comfortable driving experience. For example, in the above example, when the owner obtains the second reference instruction, it is believed that the actual trip should be on the car at 7:55, and then the correction instruction of the car controlling the vehicle components to reach a comfortable temperature at 7:55 is fed back. After combining with the second reference instruction, the vehicle operation history data is predicted through data intelligence analysis to obtain a more accurate time, that is, the target instruction of the car controlling the vehicle components to reach a comfortable temperature at 7:53 is obtained.

[0081] It is understandable that the correction instruction and the second reference instruction are comprehensively analyzed to generate a precise target instruction, which will guide the vehicle's control system to perform specific operations, such as adjusting the vehicle's power system, suspension system or interior environment, etc., to ensure that the vehicle's operation is consistent with the driver's intention and adapts to current road and environmental conditions, thereby achieving safe and efficient driving.

[0082] As an example, based on the correction instruction and the second reference instruction, a target instruction is obtained so that after the vehicle control is completed according to the target instruction, it also includes: obtaining a preset time; based on the preset time, obtaining the vehicle operation history record within the preset time; based on a preset algorithm, the vehicle operation history record and the vehicle operation history record within the preset time, obtaining a correction instruction; and updating the correction instruction to the second reference instruction.

[0083] The preset time may be a time period preset by the system, which may be of any length, such as one day, one week or one month, and is used to specify the time range for collecting and analyzing the vehicle's operating data. The vehicle operation history record within the preset time period may be a collection of all the vehicle's operating data within the above preset time period, including historical information such as mileage, speed, acceleration, fuel consumption, and maintenance records, which may be used to analyze the vehicle's usage patterns and performance trends. The preset algorithm may be a calculation or analysis method predefined by the system for processing and analyzing the data of the vehicle operation history record. These algorithms may include statistical analysis, pattern recognition, predictive models, etc., which are intended to extract useful information and insights from historical data. Corrective instructions may be instructions for adjusting or optimizing vehicle performance and operation generated after analyzing the vehicle operation history record within the preset time period based on the preset algorithm. These instructions may involve maintenance plans for the vehicle, suggestions for improving driving behavior, or adjustments to vehicle settings, with the goal of improving the efficiency, safety, and reliability of the vehicle. For example, after the above-mentioned target instruction is to control the vehicle components to reach a comfortable temperature at 7:53, after one week (preset time), a correction instruction is obtained with the actual boarding time being 8:30 based on the operating data within one week (the vehicle operation history record within the preset time), and the second reference instruction is updated. After the update, it can be sent to the user terminal to obtain the user's correction instruction, and finally the updated target instruction is obtained to cope with changes in vehicle usage time.

[0084] Specifically, first determine a preset time range, then collect vehicle operation history data within the time period, and then compare with the previously obtained operation history records, use a preset algorithm to analyze these historical data to identify potential performance problems or optimization opportunities, and generate corrective instructions based on these analysis results. Finally, integrate these corrective instructions into the second reference instructions to update and optimize the vehicle's control strategy in real time, thereby improving the efficiency and safety of vehicle operation.

[0085] This embodiment provides a smart travel method based on artificial intelligence. This embodiment first obtains the first reference instruction and the vehicle operation history record, which can comprehensively consider the historical operation data of the vehicle and the current instruction requirements; then, using this information, a second reference instruction is obtained to more accurately guide the operation of the vehicle; then, the second reference instruction is sent to a preset device, and the device feeds back a correction instruction based on this instruction to further optimize the vehicle control strategy; finally, the correction instruction and the second reference instruction are combined to generate a target instruction to achieve precise vehicle control, thereby improving the efficiency and comfort of vehicle operation. This embodiment ensures the intelligence and adaptability of vehicle control, so that the vehicle can intelligently adjust the operating state according to real-time data and historical experience to achieve the best performance and safety standards.

[0086] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 2 , Figure 2 This is a flow chart of the second embodiment of the smart travel method based on artificial intelligence of the present application. Step S20 of the smart travel method based on artificial intelligence includes steps S21 to S23:

[0087] Step S21, performing data cleaning on the vehicle operation history records to obtain reference vehicle operation history records;

[0088] It should be noted that the reference vehicle operation history record can be a vehicle operation history data set obtained after the data cleaning process for further analysis and decision-making. Data cleaning refers to the processing of the original vehicle operation history record to eliminate erroneous, duplicated, incomplete or inconsistent data to ensure the quality and accuracy of the data. By extracting clean and reliable information from a large amount of raw data, this information can be used for vehicle performance analysis, fault diagnosis, maintenance plan formulation, etc., providing accurate data support for intelligent control and health management of vehicles.

[0089] It is understandable that the collected vehicle operation history records are cleaned to remove erroneous redundant information, so as to obtain a clean, accurate and reliable reference vehicle operation history record. This cleaned data set will be used for subsequent analysis and decision-making, helping to more accurately understand and predict vehicle performance, failure trends and maintenance needs, and provide high-quality data support for intelligent control and health management of vehicles.

[0090] Step S22, obtaining an extension instruction based on a preset algorithm and the reference vehicle operation history record;

[0091] It should be noted that extended instructions can be a series of instructions or suggestions generated by in-depth analysis of the operating history of the reference vehicle after cleaning using a preset algorithm. These instructions are based on trends, patterns and insights from historical data and are intended to provide more specific guidance for vehicle operation and maintenance. Extended instructions may include performance optimization suggestions, predictive maintenance instructions, and driving behavior adjustments.

[0092] It is understandable that the extended instructions are generated by using the preset algorithm to conduct an in-depth analysis of the reference vehicle operation history after data cleaning. These extended instructions are based on the trends, patterns and abnormalities identified in the historical data, and are intended to provide more specific operation guidance and maintenance suggestions, such as performance optimization, predictive maintenance, driving behavior adjustment, etc., to optimize the vehicle's operating efficiency, safety and reliability, and to guide the future operation and maintenance of the vehicle, and improve the level of intelligent vehicle management.

[0093] Step S23: obtaining a second reference instruction based on the extended instruction and the first reference instruction.

[0094] It is understandable that the extended instructions obtained from the analysis of the vehicle operation history are combined with the first reference instructions initially collected, taking into account the historical performance data, current status and preset operating parameters of the vehicle, to generate a second reference instruction. This second reference instruction is a more comprehensive and refined instruction that integrates the results of real-time data and historical analysis to more accurately guide the control and adjustment of the vehicle, ensuring that the vehicle operation meets both immediate needs and takes into account long-term performance and maintenance strategies, thereby optimizing vehicle control.

[0095] This embodiment first performs data cleaning on the vehicle operation history records to remove invalid or erroneous data points and obtain accurate and reliable reference vehicle operation history records. Then, using these cleaned data and preset algorithms, the historical records are analyzed to identify patterns and trends, thereby generating extended instructions, which may include performance optimization suggestions and predictive maintenance instructions. Finally, these extended instructions are combined with the initial first reference instructions, and the real-time needs and historical analysis results are comprehensively considered to derive the second reference instructions, which provide a more comprehensive and refined guidance for vehicle control. This embodiment ensures that vehicle operation meets both immediate needs and long-term performance and maintenance strategies, realizes optimization and intelligent management of vehicle control, and enables the vehicle control system to make more accurate and forward-looking decisions based on detailed historical data and real-time feedback.

[0096] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the smart travel method based on artificial intelligence of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0097] This application also provides a smart travel device based on artificial intelligence, please refer to Figure 3 , the artificial intelligence-based smart travel device includes:

[0098] An acquisition module 10 is used to acquire a first reference instruction and a vehicle operation history record;

[0099] An obtaining module 20 is used to obtain a second reference instruction according to the vehicle operation history record and the first reference instruction;

[0100] A sending module 30, configured to send the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction;

[0101] The control module 40 is used to obtain a target instruction based on the correction instruction and the second reference instruction, so as to complete vehicle control according to the target instruction.

[0102] The AI-based smart travel device provided in this application adopts the AI-based smart travel method in the above embodiment, which can solve the technical problem of how to intelligently adjust the vehicle travel environment according to the habits of the owner. Compared with the prior art, the beneficial effects of the AI-based smart travel device provided in this application are the same as the beneficial effects of the AI-based smart travel method provided in the above embodiment, and the other technical features in the AI-based smart travel device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0103] The present application provides an artificial intelligence-based smart travel device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the artificial intelligence-based smart travel method in the above-mentioned embodiment one.

[0104] Reference below Figure 4 , which shows a schematic diagram of the structure of an AI-based smart travel device suitable for implementing the embodiment of the present application. The AI-based smart travel device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The AI-based smart travel device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present application.

[0105] like Figure 4As shown, the smart travel device based on artificial intelligence may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the smart travel device based on artificial intelligence are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the AI-based smart travel device to communicate wirelessly or wired with other devices to exchange data. Although the AI-based smart travel device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0106] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0107] The AI-based smart travel device provided by this application adopts the AI-based smart travel method in the above embodiment, which can solve the technical problem of how to intelligently adjust the vehicle travel environment according to the habits of the owner. Compared with the prior art, the beneficial effects of the AI-based smart travel device provided by this application are the same as the beneficial effects of the AI-based smart travel method provided by the above embodiment, and the other technical features of the AI-based smart travel device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0108] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0109] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0110] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the artificial intelligence-based smart travel method in the above-mentioned embodiment.

[0111] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0112] The above-mentioned computer-readable storage medium may be included in the smart travel device based on artificial intelligence; or it may exist independently without being assembled into the smart travel device based on artificial intelligence.

[0113] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by an artificial intelligence-based smart travel device, the artificial intelligence-based smart travel device enables the following: to obtain a first reference instruction and a vehicle operation history record; to obtain a second reference instruction based on the vehicle operation history record and the first reference instruction; to send the second reference instruction to a preset device so that the preset device can feedback a correction instruction based on the second reference instruction; and to obtain a target instruction based on the correction instruction and the second reference instruction so as to complete vehicle control according to the target instruction.

[0114] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0115] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0116] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0117] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned intelligent travel method based on artificial intelligence, and can solve the technical problem of how to intelligently adjust the vehicle travel environment according to the habits of the owner. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the intelligent travel method based on artificial intelligence provided in the above-mentioned embodiment, and will not be repeated here.

[0118] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned artificial intelligence-based smart travel method.

[0119] The computer program product provided by this application can solve the technical problem of how to intelligently adjust the vehicle travel environment according to the habits of the owner. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the intelligent travel method based on artificial intelligence provided by the above embodiment, which will not be repeated here.

[0120] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A smart travel method based on artificial intelligence, characterized in that: The method comprises: Obtaining a first reference instruction and a vehicle operation history record; Obtaining a second reference instruction according to the vehicle operation history record and the first reference instruction; Sending the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction; Based on the correction command and the second reference command, a target command is obtained so that vehicle control is completed according to the target command.

2. The method according to claim 1, characterized in that Before obtaining the first reference instruction and the vehicle operation history record, the method further includes: Get sensor data and preset combination instructions; Based on the sensor data, obtaining an initial instruction; Based on the initial instruction and the preset combined instruction, a first reference instruction is obtained.

3. The method according to claim 1, characterized in that The obtaining of a second reference instruction according to the vehicle operation history record and the first reference instruction comprises: Performing data cleaning on the vehicle operation history records to obtain reference vehicle operation history records; Based on a preset algorithm and the reference vehicle operation history record, obtaining an extended instruction; A second reference instruction is obtained based on the extended instruction and the first reference instruction.

4. The method according to claim 1, characterized in that After obtaining the second reference instruction according to the vehicle operation history record and the first reference instruction, the method further includes: Obtain vehicle driving data and preset vehicle driving safety data; If the vehicle driving data is less than or equal to the preset vehicle driving safety data, obtaining the remaining safe driving data of the vehicle based on the vehicle driving data and the preset vehicle driving safety data; If the vehicle driving data is greater than or equal to the preset vehicle driving safety data, an alarm message is sent.

5. The method as claimed in claim 4, characterized in that If the vehicle driving data is greater than or equal to the preset vehicle driving safety data, sending an alarm message includes: Obtain recording device information and request signals; Obtaining identification information of the terminal device according to the request signal; If the identification information of the terminal device matches the recording device information, an alarm signal is sent.

6. The method as claimed in claim 4, characterized in that If the vehicle driving data is greater than or equal to the preset vehicle driving safety data, after sending the alarm information, the method further includes: Get the current vehicle location, cloud-annotated location, and map data; Based on the current vehicle position, the cloud-annotated position and map data, reference road information is obtained.

7. The method according to claim 1, characterized in that After obtaining a target instruction based on the correction instruction and the second reference instruction so as to complete vehicle control according to the target instruction, the method further comprises: Get the preset time; Based on the preset time, obtain the vehicle operation history record within the preset time; Obtaining a correction instruction based on a preset algorithm, the vehicle operation history record, and the vehicle operation history record within the preset time; The correction instruction is updated to the second reference instruction.

8. A smart travel device based on artificial intelligence, characterized in that: The device comprises: An acquisition module, used for acquiring a first reference instruction and a vehicle operation history record; An obtaining module, configured to obtain a second reference instruction according to the vehicle operation history record and the first reference instruction; A sending module, used for sending the second reference instruction to a preset device, so that the preset device feeds back a correction instruction according to the second reference instruction; The control module is used to obtain a target instruction based on the correction instruction and the second reference instruction, so as to complete vehicle control according to the target instruction.

9. A smart travel device based on artificial intelligence, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the artificial intelligence-based smart travel method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the artificial intelligence-based smart travel method as described in any one of claims 1 to 7 are implemented.

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