Intelligent propaganda and education method, system and device for online car-hailing driver and storage medium

Abstract

The invention relates to an intelligent propaganda and education method, system and device for online car-hailing drivers and a storage medium. The method comprises the following steps: acquiring driving behavior data, service evaluation data and training feedback data of an online car-hailing driver in real time; generating personalized description data corresponding to the online car-hailing driver according to the collected data, wherein the personalized description data comprises driving skill description data, service level description data and training demand description data; determining customized propaganda and education contents of the online car-hailing driver according to the personalized description data; the customized propaganda and education content is pushed to the online car-hailing driver through multiple ways, and the learning condition of the customized propaganda and education content by the online car-hailing driver is recorded in real time. According to the invention, timely, efficient and personalized educational training can be carried out on the online car-hailing driver, and the driving skill, service level and safety awareness of the online car-hailing driver are improved.

Description

Technical Field

[0001] The present application relates to the field of traffic management and educational technology, and in particular to an intelligent education method, system, computer device and storage medium for online car-hailing drivers. Background Art

[0002] With the rapid development of the online car-hailing industry, the number of online car-hailing drivers has increased dramatically, but their overall quality and service level are uneven, which leads to problems such as frequent traffic accidents and uneven service quality. Education is an important way to improve the quality and service level of drivers. The existing education methods are usually carried out through offline training and simple online courses. However, this method lacks personalization and real-timeness, and it is difficult to meet the training needs of a large-scale driver team.

[0003] Specifically, there are currently some driver training systems based on mobile applications and online platforms. These systems usually train drivers through online courses, video tutorials and assessment tests, with the aim of improving drivers' driving skills and service levels. However, the education content provided to drivers by these driver training systems has some deficiencies in terms of personalization and real-time. That is, the existing driver training systems usually adopt unified training content and standards, and will not customize personalized education content for different drivers according to their specific circumstances. However, the driving skills, service levels and training needs of different drivers are usually different, so unified training content cannot meet the needs of all drivers, which will lead to unsatisfactory overall training results for online car-hailing drivers. In addition, these driver training systems usually train and assess relevant drivers only after they encounter traffic problems or receive complaints from passengers. This method lacks real-time monitoring and immediate feedback, and the errors and irregular operations made by drivers during driving cannot be corrected and improved in a timely manner. Summary of the invention

[0004] In response to the above-mentioned deficiencies or shortcomings, the present application provides an intelligent education method, system, computer device and storage medium for online car-hailing drivers. The embodiments of the present application can provide timely, efficient and personalized education and training for online car-hailing drivers to improve their driving skills, service level and safety awareness.

[0005] According to a first aspect, the present application provides an intelligent education method for online car-hailing drivers. In some embodiments, the method includes:

[0006] Collect online car-hailing drivers’ driving behavior data, service evaluation data, and training feedback data in real time;

[0007] Generate personalized description data corresponding to online car-hailing drivers based on the collected data, including driving skills description data, service level description data and training needs description data;

[0008] Determine customized education content for online ride-hailing drivers based on personalized description data;

[0009] Customized educational content is pushed to online ride-hailing drivers through various channels, and the online ride-hailing drivers’ learning status of the customized educational content is recorded in real time.

[0010] In some embodiments, the real-time collection of driving behavior data, service evaluation data, and training feedback data of online ride-hailing drivers includes:

[0011] The driving behavior data generated by the vehicle during driving is collected in real time by sensors installed in the vehicle corresponding to the online car-hailing driver, and the driving behavior data includes one or more of average vehicle speed information, number of emergency brakes, number of emergency accelerations, and turning angles;

[0012] Obtaining passengers' service evaluation data on online ride-hailing drivers through online ride-hailing platforms, where the service evaluation data includes one or more of rating information, comment information, and complaint records;

[0013] The training feedback data generated by online ride-hailing drivers during the training process is obtained through the education and promotion execution platform. The training feedback data includes one or more of the course completion status, test scores and learning feedback information.

[0014] In some embodiments, the personalized description data corresponding to the online car-hailing driver is generated based on the collected data, including:

[0015] Clean the collected driving behavior data, service evaluation data, and training feedback data of online ride-hailing drivers;

[0016] Extracting first feature data that can reflect the driver's driving skills from the cleaned driving behavior data, and generating driving skill description data according to the first feature data;

[0017] Extracting second characteristic data that can reflect the driver's service level from the cleaned service evaluation data, and generating service level description data according to the second characteristic data;

[0018] The third characteristic data that can reflect the training needs are extracted from the cleaned training feedback data, and the training needs description data are generated according to the third characteristic data.

[0019] In some embodiments, after cleaning the collected driving behavior data, service evaluation data, and training feedback data of the online ride-hailing driver, the method further includes:

[0020] Conduct statistical analysis based on driving behavior data, service evaluation data, and training feedback data after cleaning;

[0021] Based on the statistical analysis results, a first feature that can reflect the driver's driving skills, a second feature that can reflect the driver's service level, and a third feature that can reflect the training needs are determined.

[0022] In some embodiments, the customized education content for online car-hailing drivers is determined based on the personalized description data, including:

[0023] According to the preset personalized content recommendation strategy, the education content that is most relevant to the driving skill description data, the service level description data and the training demand description data is selected from the pre-built education content library as the customized education content.

[0024] In some embodiments, customized education content is pushed to online ride-hailing drivers through a variety of channels, including:

[0025] Push customized education content to online ride-hailing drivers through the driver-side application of online ride-hailing platforms, and provide online learning and interactive functions;

[0026] Providing online learning and downloading services of customized education content to online ride-hailing drivers through the education execution platform;

[0027] Customized educational content is pushed to online ride-hailing drivers through the on-board devices installed in their vehicles, and interactive teaching is carried out.

[0028] In some embodiments, after recording in real time the learning status of the online car-hailing driver on the customized education content, the method further includes:

[0029] After the online car-hailing drivers complete the learning tasks corresponding to the customized education content, they will be assessed;

[0030] Evaluate the training effectiveness of online ride-hailing drivers based on the assessment results;

[0031] Update the personalized description data corresponding to the online car-hailing driver based on the evaluation results;

[0032] Determine new customized education content based on the updated personalized description data of online ride-hailing drivers;

[0033] New customized education content is pushed to online ride-hailing drivers through these multiple channels.

[0034] According to a second aspect, the present application provides an intelligent education system for online car-hailing drivers. In some embodiments, the system includes:

[0035] Data collection module, used to collect online car-hailing drivers’ driving behavior data, service evaluation data, and training feedback data in real time;

[0036] A description data generation module is used to generate personalized description data corresponding to online car-hailing drivers based on the collected data. The personalized description data includes driving skill description data, service level description data and training demand description data;

[0037] The education content customization module is used to determine the customized education content for online car-hailing drivers based on personalized description data;

[0038] The education execution module is used to push customized education content to online taxi drivers through various channels, and record the learning status of the customized education content by the online taxi drivers in real time.

[0039] According to a third aspect, the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the intelligent education method for online car-hailing drivers provided in any of the above embodiments are implemented.

[0040] According to a fourth aspect, the present application provides 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 intelligent education method for online car-hailing drivers provided in any of the above embodiments are implemented.

[0041] In the above-mentioned embodiment of the present application, the education system will collect the driving behavior data, service evaluation data and training feedback data of the online car-hailing driver in real time, and generate the personalized description data corresponding to the online car-hailing driver based on the collected data, and then customize the education content for the online car-hailing driver based on the personalized description data, obtain the customized education content, and finally push the customized education content to the online car-hailing driver in combination with multiple channels, and record the learning of the customized education content by the online car-hailing driver in real time. This method can provide customized education content for each online car-hailing driver according to his driving skills, service level and training needs, and can also monitor the driving behavior of the online car-hailing driver in real time during the work of the online car-hailing driver and provide immediate feedback on the errors and irregular operations that occur during the driving process of the driver, so that the errors and irregular operations that occur during the driving process of the driver can be corrected and improved in time, and the service quality and driving safety of the driver can be improved. Through the above-mentioned operation, timely, efficient and personalized education and training can be carried out for the online car-hailing driver, improving his driving skills, service level and safety awareness, and ultimately improving the overall comprehensive quality of the online car-hailing driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of the system architecture of an intelligent education system for executing an intelligent education method for online car-hailing drivers provided by the present application according to one or more embodiments;

[0043] Figure 2A flowchart of an intelligent education method for online car-hailing drivers provided by the present application according to one or more embodiments;

[0044] Figure 3 A structural block diagram of an intelligent education system for online car-hailing drivers provided by the present application according to one or more embodiments;

[0045] Figure 4 This is a diagram of the internal structure of a computer device provided by the present application according to one or more embodiments. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below in conjunction with the accompanying drawings. It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0047] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are only examples of systems and methods consistent with some aspects of the present application as detailed in the attached claims.

[0048] In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances. In addition, in the description of the present application, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0049] In view of the shortcomings or defects of the prior art, the present application provides an intelligent education method for online car-hailing drivers. In some embodiments, the method can be applied to an intelligent education system (referred to as the system, which can be implemented by an independent server or a server cluster). The system architecture of the system is as follows: Figure 1As shown, the system will provide customized education content for each online car-hailing driver in the online car-hailing platform through this method, and can also monitor the driving behavior of the online car-hailing driver in real time during the work of the online car-hailing driver and provide instant feedback on the driver's errors and irregular operations during the driving process, so that the driver's errors and irregular operations during the driving process can be corrected and improved in time. This operation can provide timely, efficient and personalized education and training for online car-hailing drivers, improve their driving skills, service level and safety awareness, and ultimately improve the overall comprehensive quality of online car-hailing drivers.

[0050] In some embodiments, the method includes Figure 2 The steps shown are as follows, and the method is explained by taking the method applied to the intelligent education system as an example.

[0051] S110: Real-time collection of online car-hailing drivers’ driving behavior data, service evaluation data, and training feedback data.

[0052] The system can collect driving behavior data, service evaluation data and training feedback data of each online car-hailing driver in real time through a variety of sensors and data interfaces. Among them, driving behavior data is the data generated by the vehicle corresponding to the online car-hailing driver during the operation period that can reflect the driver's driving behavior. Service evaluation data is the evaluation information of the service level of the online car-hailing driver when the passenger performs a travel task after the online car-hailing driver completes a travel task, such as rating information, comment information, passenger complaint records, etc. Training feedback data is the learning feedback data of the online car-hailing driver on the propaganda content previously pushed by the system.

[0053] In some embodiments, the operation of collecting the driving behavior data, service evaluation data, and training feedback data of the online car-hailing driver in real time may include:

[0054] (1) The sensors installed in the vehicle corresponding to the online car-hailing driver collect the driving behavior data generated by the vehicle in real time during driving.

[0055] The vehicle corresponding to the online car-hailing driver is equipped with a variety of sensors. The vehicle will generate driving behavior data based on the data collected by various sensors and upload it to the online car-hailing platform. Among them, the driving behavior data may include one or more of the average speed information, number of emergency brakes, number of emergency accelerations, and turning angles generated by the relevant vehicle in the past preset time. The preset time can be set according to actual conditions. Furthermore, the system can pull the driving behavior data related to the online car-hailing driver from the platform through the data interface provided in advance by the online car-hailing platform for subsequent processing.

[0056] (2) Obtain passengers’ service evaluation data on online ride-hailing drivers through the online ride-hailing platform.

[0057] The system can pull service evaluation data related to the online ride-hailing drivers from the platform through the data interface pre-provided by the online ride-hailing platform. The service evaluation data may include one or more of the rating information (indicating the passenger's service rating of the driver), comment information and complaint records.

[0058] (3) Obtain training feedback data generated by online ride-hailing drivers during the training process through the education and implementation platform.

[0059] The education execution platform can be a module in the system for providing customized education content to online car-hailing drivers and interacting with online car-hailing drivers. It will record the feedback data of online car-hailing drivers on the education content pushed by the system in the past specific period of time (for example, the past week). The system can pull the training feedback data related to online car-hailing drivers from the platform through the data interface pre-provided by the education execution platform. The training feedback data may include one or more of the course completion status, test scores and learning feedback information (such as feedback from drivers on the education content).

[0060] S120: Generate personalized description data corresponding to the online car-hailing driver based on the collected data, where the personalized description data includes driving skill description data, service level description data and training needs description data.

[0061] In some embodiments, the operation of generating personalized description data corresponding to the online car-hailing driver based on the collected data includes:

[0062] (1) Performing data cleaning on the driving behavior data, service evaluation data, and training feedback data collected from online ride-hailing drivers; the data cleaning operations on the collected data include a series of processing such as removing missing values, outliers, and noise data. Performing data cleaning operations on the data can ensure data quality and indirectly improve the accuracy and completeness of the personalized description data subsequently generated for the online ride-hailing drivers.

[0063] In this embodiment, the personalized description data of each online car-hailing driver is specifically composed of multiple description data, and different description data represent the behavioral characteristics of the online car-hailing driver in different aspects. For example, the personalized description data of the online car-hailing driver includes driving skill description data (describing the driver's behavioral characteristics in driving skills), service level description data (characterizing the driver's behavioral characteristics in online car-hailing services) and training needs description data (characterizing the driver's needs for training and education).

[0064] (2) extracting first feature data that can reflect the driver's driving skills from the cleaned driving behavior data, and generating driving skill description data based on the first feature data; wherein the system extracts the feature data of the first feature from the cleaned driving behavior data based on the predetermined first feature that can reflect the driver's driving skills as the first feature data. If there are multiple first features, the system will organize the first feature data according to a predetermined description data format (for example, splicing certain features, converting the format of certain feature data into a standard format, etc.), and the organized data is the above-mentioned driving skill description data (which can reflect the driver's ability level in terms of safe driving, energy-saving driving, etc.).

[0065] (3) extracting second characteristic data that can reflect the driver's service level from the cleaned service evaluation data, and generating service level description data based on the second characteristic data; wherein the system extracts characteristic data of the second characteristic from the cleaned service evaluation data based on the predetermined second characteristic that can reflect the driver's service level as the second characteristic data. If there are multiple second characteristics, the system will organize the second characteristic data according to the predetermined description data format, and the organized data is the above-mentioned service level description data (which can reflect the driver's service quality, and specifically can include the index values ​​of multiple indicators such as passenger satisfaction and service attitude).

[0066] (4) extracting third characteristic data that can reflect the training needs from the cleaned training feedback data, and generating training needs description data based on the third characteristic data; wherein the system extracts the characteristic data of the third characteristic from the cleaned training feedback data based on the predetermined third characteristic that can reflect the training needs of the driver, as the third characteristic data. There are multiple third characteristics, and the system will organize the third characteristic data according to the predetermined description data format, and the organized data is the above-mentioned training needs description data (which may include identification information for characterizing the skills and knowledge points that the driver needs to focus on improving).

[0067] In some embodiments, after data cleaning of the collected driving behavior data, service evaluation data and training feedback data of the online ride-hailing driver, the method further includes: performing statistical analysis based on the cleaned driving behavior data, service evaluation data and training feedback data; determining a first feature that can reflect the driver's driving skills, a second feature that can reflect the driver's service level, and a third feature that can reflect training needs based on the statistical analysis results.

[0068] In this embodiment, the system can perform statistical analysis on the cleaned data to identify key features related to driver driving behavior, service quality, and training needs, thereby providing support for the subsequent customized generation of personalized description data and educational content.

[0069] S130: Determine customized education content for online car-hailing drivers based on the personalized description data.

[0070] In some embodiments, the operation of determining customized education content for online ride-hailing drivers based on personalized description data may include: selecting education content that is most relevant to driving skill description data, service level description data, and training needs description data from a pre-built education content library as customized education content based on a preset personalized content recommendation strategy.

[0071] The education content library may include education content in various aspects such as driving skills, safety knowledge, and service specifications. The system can select the most relevant education content as customized education content based on various description data. For example, the most relevant education content can be selected from education content related to driving skills based on driving skill description data, the most relevant education content can be selected from education content related to service specifications based on service level description data, and the most relevant education content can be selected from all education content based on training needs description data, and the selected education content can be used as customized education content for online car-hailing drivers.

[0072] The above-mentioned education content library is pre-constructed, which can cover various aspects of education content such as driving skills, safety knowledge, service specifications, etc., and can include content in various forms of education such as video courses, text teaching materials, interactive training, etc.

[0073] S140: Push the customized education content to the online car-hailing drivers through various channels, and record the learning status of the online car-hailing drivers on the customized education content in real time.

[0074] The system can push customized education content to online ride-hailing drivers through a variety of channels. For example, the system can push customized education content to online ride-hailing drivers through the driver-side application of the online ride-hailing platform, and provide online learning and interactive functions; the system also provides online learning and download services for customized education content to online ride-hailing drivers through the education execution platform; the system can also push customized education content to online ride-hailing drivers through on-board devices installed in the drivers' vehicles, and conduct interactive teaching.

[0075] In order to further improve the effect of education, the system can also use virtual reality (VR) technology to provide immersive driving training and service scenario simulation to online car-hailing drivers. Specifically, VR equipment can be provided for online car-hailing drivers, so that drivers can use VR equipment to conduct driving training and service scenario simulation in a pre-established virtual reality environment. Real driving and service scenarios can be reproduced through virtual scenes, which is conducive to improving the emergency response capabilities and service levels of online car-hailing drivers. In addition, real-time interactive teaching can be achieved through VR equipment, which helps to correct the driver in time when he makes an erroneous operation.

[0076] Furthermore, a dedicated driver learning community can be established to provide a platform for communication and sharing, encouraging online ride-hailing drivers to share their driving and service experiences on the platform so that drivers can learn from each other and thus improve the effectiveness of education.

[0077] In some embodiments, after recording the online taxi driver's learning status of the customized education content in real time, the method also includes: assessing the online taxi driver after the online taxi driver completes the learning task corresponding to the customized education content; evaluating the training effect of the online taxi driver based on the assessment results; updating the personalized description data corresponding to the online taxi driver based on the evaluation results; determining new customized education content based on the updated personalized description data of the online taxi driver; and pushing the new customized education content to the online taxi driver through these multiple channels.

[0078] In this embodiment, after the system provides customized education content to online car-hailing drivers, it will evaluate the training effect of the drivers and adjust the education strategy according to the evaluation results. Among them, the learning effect of the driver can be evaluated through testing and assessment, and the knowledge mastery and skill improvement can be recorded. After obtaining the evaluation results, the personalized description data generated for the driver before is updated based on the evaluation results, and the corresponding education content is selected from the education content library based on the new personalized description data and pushed to the driver for learning. This embodiment can continuously optimize the education content and push strategy of each online car-hailing driver according to the evaluation results, and continuously improve the effectiveness and pertinence of the education.

[0079] It should be noted that, with respect to the various steps included in the intelligent education method for online car-hailing drivers provided in any of the above embodiments, unless otherwise specified in this document, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least part of these steps may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0080] Based on the same inventive concept, the present application also provides an intelligent education system for online car-hailing drivers. Figure 3 As shown in the figure, the intelligent education system for online car-hailing drivers includes the following modules:

[0081] The data collection module 110 is used to collect the driving behavior data, service evaluation data and training feedback data of the online car-hailing drivers in real time;

[0082] A description data generation module 120 is used to generate personalized description data corresponding to the online car-hailing driver based on the collected data, and the personalized description data includes driving skill description data, service level description data and training demand description data;

[0083] The education content customization module 130 is used to determine the customized education content for online car-hailing drivers based on the personalized description data;

[0084] The education execution module 140 is used to push customized education content to online car-hailing drivers through various channels, and record the learning status of the online car-hailing drivers on the customized education content in real time.

[0085] In some embodiments, the data acquisition module 110 includes:

[0086] The first collection submodule is used to collect driving behavior data generated by the vehicle during driving in real time through sensors installed in the vehicle corresponding to the online car-hailing driver, and the driving behavior data includes one or more of average vehicle speed information, number of emergency brakes, number of emergency accelerations and turning angles;

[0087] The second collection submodule is used to obtain the service evaluation data of the passengers on the online car-hailing drivers through the online car-hailing platform, and the service evaluation data includes one or more of the rating information, comment information and complaint records;

[0088] The third collection sub-module is used to obtain the training feedback data generated by the online car-hailing drivers during the training process through the education and publicity execution platform. The training feedback data includes one or more of the course completion status, test scores and learning feedback information.

[0089] In some embodiments, the description data generation module 120 includes:

[0090] The data cleaning submodule is used to clean the collected driving behavior data, service evaluation data and training feedback data of online ride-hailing drivers;

[0091] A first generating submodule is used to extract first characteristic data that can reflect the driver's driving skills from the cleaned driving behavior data, and generate driving skill description data according to the first characteristic data;

[0092] The second generating submodule is used to extract the second characteristic data reflecting the driver's service level from the cleaned service evaluation data, and generate the service level description data according to the second characteristic data;

[0093] The third generating submodule is used to extract third characteristic data that can reflect the training needs from the cleaned training feedback data, and generate training needs description data according to the third characteristic data.

[0094] In some embodiments, the description data generation module 120 further includes:

[0095] The statistical analysis submodule is used to perform statistical analysis based on the driving behavior data, service evaluation data and training feedback data after cleaning;

[0096] The key feature identification submodule is used to determine, based on the statistical analysis results, a first feature that can reflect the driver's driving skills, a second feature that can reflect the driver's service level, and a third feature that can reflect training needs.

[0097] In some embodiments, the education content customization module 130 is specifically used to select the education content most relevant to the driving skill description data, the service level description data and the training demand description data from the pre-built education content library as the customized education content according to a preset personalized content recommendation strategy.

[0098] In some embodiments, the education execution module 140 includes:

[0099] The first execution submodule is used to push customized education content to online car-hailing drivers through the driver-side application of the online car-hailing platform, and provide online learning and interactive functions;

[0100] The second execution submodule is used to provide online learning and downloading services of customized education content to online car-hailing drivers through the education execution platform;

[0101] The third execution submodule is used to push customized educational content to the online car-hailing driver through the on-board device installed in the online car-hailing driver's vehicle and conduct interactive teaching.

[0102] In some embodiments, the system further includes an effect evaluation module (not shown in the figure). The effect evaluation module is used to:

[0103] After the online car-hailing drivers complete the learning tasks corresponding to the customized education content, they will be assessed;

[0104] Evaluate the training effectiveness of online ride-hailing drivers based on the assessment results;

[0105] Update the personalized description data corresponding to the online car-hailing driver based on the evaluation results;

[0106] Determine new customized education content based on the updated personalized description data of online ride-hailing drivers;

[0107] New customized education content is pushed to online ride-hailing drivers through these multiple channels.

[0108] For the specific limitations of the intelligent education system for online car-hailing drivers, please refer to the limitations of the intelligent education method for online car-hailing drivers mentioned above, which will not be repeated here. Each module in the above-mentioned intelligent education system for online car-hailing drivers can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0109] In some embodiments, the present application provides a computer device, whose internal structure diagram can be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as propaganda content, and the specific stored data can also be found in the definitions in the above method embodiments. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an intelligent propaganda method for online car-hailing drivers is implemented.

[0110] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0111] This embodiment also provides a computer device. In some embodiments, the computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the intelligent education method for online car-hailing drivers provided in any of the above embodiments can be implemented.

[0112] The present application also provides a computer-readable storage medium. In some embodiments, a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps of the intelligent education method for online car-hailing drivers provided in any of the above embodiments are implemented.

[0113] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0114] Those skilled in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink), DRAM (SLDRAM), memory bus (Rambus), direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0115] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An intelligent education method for online car-hailing drivers, characterized in that: The method comprises: Collect online car-hailing drivers’ driving behavior data, service evaluation data, and training feedback data in real time; Generate personalized description data corresponding to the online car-hailing driver based on the collected data, wherein the personalized description data includes driving skill description data, service level description data and training needs description data; Determining customized education content for the online car-hailing driver based on the personalized description data; The customized educational content is pushed to the online car-hailing driver through multiple channels, and the learning status of the online car-hailing driver on the customized educational content is recorded in real time.

2. The method according to claim 1, characterized in that Real-time collection of online car-hailing drivers’ driving behavior data, service evaluation data, and training feedback data, including: The driving behavior data generated by the vehicle during driving is collected in real time by using sensors installed in the vehicle corresponding to the online car-hailing driver, wherein the driving behavior data includes one or more of average vehicle speed information, number of emergency brakes, number of emergency accelerations, and turning angles; Obtaining, through the online car-hailing platform, service evaluation data of passengers on the online car-hailing driver, wherein the service evaluation data includes one or more of rating information, comment information, and complaint records; The training feedback data generated by the online car-hailing driver during the training process is obtained through the education and promotion execution platform, and the training feedback data includes one or more of the course completion status, test scores and learning feedback information.

3. The method according to claim 1, characterized in that Generate personalized description data corresponding to the online car-hailing driver based on the collected data, including: Cleaning the collected driving behavior data, service evaluation data, and training feedback data of the online car-hailing drivers; extracting first feature data that can reflect the driver's driving skills from the cleaned driving behavior data, and generating the driving skill description data according to the first feature data; Extracting second characteristic data that can reflect the driver's service level from the cleaned service evaluation data, and generating the service level description data according to the second characteristic data; The third characteristic data that can reflect the training needs are extracted from the cleaned training feedback data, and the training needs description data are generated according to the third characteristic data.

4. The method according to claim 3, characterized in that After cleaning the collected driving behavior data, service evaluation data, and training feedback data of the online car-hailing driver, the method further includes: Conduct statistical analysis based on driving behavior data, service evaluation data, and training feedback data after cleaning; Based on the statistical analysis results, a first feature that can reflect the driver's driving skills, a second feature that can reflect the driver's service level, and a third feature that can reflect the training needs are determined.

5. The method according to claim 3, characterized in that The customized propaganda content for the online car-hailing driver is determined according to the personalized description data, including: According to a preset personalized content recommendation strategy, the education content that is most relevant to the driving skill description data, the service level description data, and the training demand description data is selected from a pre-built education content library as the customized education content.

6. The method according to claim 1, characterized in that The customized propaganda content is pushed to the online car-hailing driver through various channels, including: Pushing the customized education content to the online ride-hailing driver through the driver-side application of the online ride-hailing platform, and providing online learning and interactive functions; Providing online learning and downloading services of the customized education content to the online ride-hailing drivers through the education execution platform; The customized educational content is pushed to the online car-hailing driver through the on-board device installed in the online car-hailing driver's vehicle, and interactive teaching is carried out.

7. The method according to claim 1, characterized in that After recording the learning status of the online car-hailing driver on the customized education content in real time, the method further includes: After the online car-hailing driver completes the learning task corresponding to the customized education content, assessing the online car-hailing driver; Evaluate the training effect of the online car-hailing drivers based on the assessment results; Update the personalized description data corresponding to the online car-hailing driver according to the evaluation results; Determining new customized education content based on the updated personalized description data of the online ride-hailing driver; The new customized education content is pushed to the online car-hailing driver through the multiple channels.

8. An intelligent education system for online car-hailing drivers, characterized in that: The system comprises: Data collection module, used to collect online car-hailing drivers’ driving behavior data, service evaluation data, and training feedback data in real time; A description data generation module, used to generate personalized description data corresponding to the online car-hailing driver based on the collected data, wherein the personalized description data includes driving skill description data, service level description data and training demand description data; A propaganda content customization module, used to determine the customized propaganda content for the online car-hailing driver according to the personalized description data; The education execution module is used to push the customized education content to the online car-hailing driver through various channels, and record the learning status of the online car-hailing driver on the customized education content in real time.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

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