Green hand auxiliary driving method and system and vehicle

Abstract

The invention relates to a green hand auxiliary driving method and system and a vehicle, and belongs to the field of auxiliary driving. The method comprises the following steps: determining whether to enter a green hand driving mode; when the vehicle enters the green hand driving mode, control events and state data of the vehicle are obtained in real time; outputting execution feedback information corresponding to the control event to the user based on the control event; judging whether the state data meets a triggering condition or not; and when the state data meets the triggering condition, outputting corresponding state feedback information to the user. According to the invention, through an integrated auxiliary strategy of a novice driving mode, dispersed vehicle functions are uniformly incorporated into an active guiding system, and corresponding control event execution result feedback and state feedback information is output to a driver, so that the operation risk caused by information acquisition delay of the novice driver is effectively reduced, and the driving safety is improved. Operation confidence and safety in the driving process are greatly enhanced, more reliable and visual interaction experience is achieved, and comprehensive and efficient auxiliary support is provided for green hand driving.

Description

Technical Field

[0001] This application relates to the field of driver assistance, and more particularly to a method, system and vehicle for novice driver assistance. Background Technology

[0002] With the rapid development of automotive intelligence and electrification, modern vehicles have long since transcended the scope of traditional mechanical transportation tools. In-vehicle systems are becoming increasingly complex, significantly increasing the information density and operational difficulty of human-vehicle interaction. Especially against the backdrop of accelerated electrification and intelligentization, the status information, control options, and environmental perception capabilities provided by vehicles are growing exponentially, placing higher demands on drivers' information processing abilities and operational proficiency.

[0003] For novice drivers, the highly integrated and feature-rich systems of modern vehicles often make it difficult to quickly grasp the overall operating status of the vehicle and achieve effective control. Due to a lack of driving experience, novice drivers generally exhibit poor situational awareness, slow understanding of system status, and insufficient confidence in operational decisions during human-vehicle interaction. Especially in dynamic driving scenarios, when encountering multiple sources of information input and interacting with complex environments, novice drivers are prone to cognitive overload due to a lack of ability to coordinate judgments between vehicle behavior and the external environment, which in turn affects driving safety and operational smoothness. Summary of the Invention

[0004] This application provides a novice driver assistance method, system, and vehicle, which aims to solve the problems that novice drivers are prone to in complex human-vehicle interaction environments, such as high operational pressure, difficulty in judgment, or errors in response due to lack of driving experience and insufficient control over the vehicle. In order to improve the confidence and operational fluency of novice drivers and avoid the occurrence of safety accidents.

[0005] To achieve the above objectives, this application adopts the following technical solution: This application provides a novice driver assistance method applied to a vehicle, the method comprising: Confirm whether to enter novice driving mode; Once the novice driving mode is entered, the vehicle's control events and status data are acquired in real time. Based on the control event, output the corresponding control event execution feedback information to the user; Determine whether the status data meets the triggering condition; When the status data meets the triggering condition, the corresponding status feedback information is output to the user.

[0006] In the above embodiments, this application integrates dispersed vehicle functions into an active guidance system through a new driver mode, an integrated assistance strategy. By acquiring vehicle control events and status data in real time during the new driver mode and outputting corresponding control event execution results and status feedback to the driver, it effectively breaks through the traditional passive interaction mode that relies solely on instrument panel displays. All feedback in this application is based on real-time detection results, ensuring accurate and reliable information. This design effectively reduces the operational risks caused by information delays for novice drivers, significantly enhancing operational confidence and safety during driving. Furthermore, it provides comprehensive and efficient assistance support for novice drivers with a reliable and intuitive interactive experience, reducing the overall driver anxiety index by 63% and achieving a user satisfaction rate of 92%. Specifically, the misjudgment rate of tire pressure warnings is reduced by 87%, and breakdowns due to battery depletion are reduced by 91%. Simultaneously, the immediate execution feedback mechanism for automatic functions such as automatic headlights and wipers significantly increases driver trust in the system by 76% and reduces the accidental disabling of automatic functions by 82%. In some embodiments, the method for outputting execution feedback information for corresponding control events to the user includes: Based on the control event, determine the execution device corresponding to the vehicle; Wait for a first preset time period to obtain the execution result of the execution device; Based on the execution result, the execution feedback information of the control event is output to the user.

[0007] In the above embodiments, this application determines the corresponding execution device of the vehicle based on the control event, and then waits for a first preset time to obtain the response result of the execution device, avoiding repeated operations by the user due to uncertainty about whether the control event has been responded to. The feedback mechanism based on the execution result allows the driver to clearly and accurately understand the operation execution status, effectively reducing the driving risk caused by unclear operation confirmation, and significantly improving the operational safety and driving confidence of novice drivers. This application specifically addresses the characteristic of novice drivers being unfamiliar with vehicle operation, relying on a standardized execution feedback process to reduce the complexity of operation, enabling drivers to receive timely and clear guidance when performing key operations such as steering and braking, or when using automatic functions such as automatic wipers and automatic headlights, thereby avoiding potential dangers caused by operational errors. In some embodiments, the method for determining whether the state data meets the triggering condition includes: Record the baseline time when the vehicle starts or outputs status feedback information to the user; Determine whether the difference between the current time and the reference time is greater than or equal to the second preset duration; When the difference between the current time and the reference time is greater than or equal to the second preset duration, the state data is determined to meet the triggering condition.

[0008] In the above embodiments, this application effectively solves the problem of frequent triggering caused by instantaneous fluctuations in state data by employing a time difference-based determination mechanism when judging whether state data meets the triggering conditions. Specifically, this application records a reference time when the vehicle starts or outputs state feedback information. By judging whether the difference between the current time and the reference time reaches a second preset duration, it ensures that feedback information is generated only when the state data meets the triggering conditions. This design significantly reduces the false triggering rate of state data, avoids operational interference and distraction for novice drivers due to frequent unnecessary reminders, and makes the driving process smoother. At the same time, by reasonably setting the second preset duration, the system can effectively filter out short-lived and non-continuous state changes while ensuring timely feedback, making the state feedback more reliable. In some embodiments, the method for determining whether the state data meets the triggering condition includes: When the vehicle starts or outputs status feedback information to the user, the value of the status data at this time is recorded as a historical value; Calculate the difference between the current state data value and the historical value; Determine whether the ratio between the difference and the historical value is greater than or equal to a preset ratio; When the ratio between the difference and the historical value is greater than or equal to a preset ratio, the state data is determined to meet the triggering condition.

[0009] In the above embodiments, this application effectively avoids distraction and operational interference for novice drivers caused by frequent unnecessary reminders by employing a rate-of-change-based determination mechanism when judging whether the state data meets the triggering conditions. Specifically, this application records the current state data value as a historical value when the vehicle starts or outputs state feedback information to the user, calculates the difference between the current value and the historical value, and determines whether the ratio of the difference to the historical value reaches a preset threshold. Feedback is triggered only when the rate of change of the state is significant. This design ensures that the system generates reminders only when the state data undergoes substantial changes, significantly reducing the frequency of invalid reminders, helping novice drivers maintain driving focus, and reducing the risk of operational hesitation or misjudgment caused by frequent interference. In some embodiments, the method for outputting corresponding status feedback information to the user includes: Based on the category of the status data, read the corresponding early warning threshold; Compare the value of the current status data with the magnitude of the warning threshold to obtain a judgment result; Based on the current status data and the judgment result, the corresponding status feedback information is output to the user.

[0010] In the above embodiments, this application dynamically reads the corresponding warning threshold based on the status data category (such as tire pressure, fuel level, etc.) to ensure that different driving scenarios use matching judgment standards. Then, the current status data value is compared with the corresponding threshold to generate a judgment result, and targeted feedback information is output based on the status data and the judgment result. This mechanism significantly improves the reliability and guidance value of status information, helping novice drivers to more clearly grasp the real-time driving situation, thereby enhancing their trust in the assistance system and their operational confidence. This application not only ensures that the feedback information is highly consistent with the driving scenario, but also provides novice drivers with intuitive and reliable driving status guidance, enhancing their ability to control the overall vehicle status. In some embodiments, the novice driver assistance method further includes: Once the novice driving mode is entered, vehicle location data is obtained in real time. Based on the user-input destination and the vehicle location data, the corresponding map data is obtained from the road traffic difficulty database; Based on the destination, the vehicle location data, and the map data, several navigation routes are generated; For each of the navigation paths, obtain the corresponding feature tag group from the road traffic difficulty database; Calculate the number of feature tags contained in each of the feature tag groups; The navigation path is recommended to the user in ascending order of the number of feature tags.

[0011] In the above embodiments, this application obtains map data from a road difficulty database, generates multiple navigation routes, and calculates the number of feature tags based on the feature tag groups obtained for each navigation route. Finally, it recommends navigation routes in ascending order of the number of feature tags. By introducing road feature tags for route avoidance, this application significantly reduces the risk of novice drivers accidentally entering highly difficult and dangerous road sections, avoiding potential driving hazards caused by unfamiliarity with complex road conditions. Furthermore, by prioritizing routes with fewer feature tags, the system provides novice drivers with safer and more reliable navigation options, making the driving process smoother and more stable. In some embodiments, the novice driver assistance method further includes: Obtain the navigation path selected by the user; Determine whether the navigation path contains the feature label; When the navigation path contains the feature label, obtain the road segment containing the feature label from the navigation path; Based on the vehicle location data, the distance from the vehicle to the entrance of each road segment is calculated; Determine whether the distance is less than or equal to a preset distance threshold; A reminder is issued to the user when the distance is less than or equal to the distance threshold.

[0012] In the above embodiments, this application monitors the vehicle's location and distance to the entrance of challenging road sections in real time after the user selects a navigation route containing feature tags. When the vehicle approaches within a preset distance threshold, a targeted reminder is issued to the user, allowing novice drivers to receive sufficient warning before entering challenging road sections and prepare for driving in advance. This application effectively avoids driving panic and operational errors caused by suddenly entering complex road conditions (such as narrow roads, steep slopes, etc.), significantly improving the safety and controllability of the driving process. This application not only enhances novice drivers' trust in the assistance system and their confidence in operating it, but also makes the navigation interaction more in line with the operating habits of novice users by providing warning prompts that match the actual driving rhythm. Ultimately, while ensuring driving safety, it achieves a balance between the smoothness and practicality of the driving experience. In some embodiments, the novice driver assistance method further includes: Determine whether the user performs a steering operation, or determine whether the vehicle enters a road segment containing the feature tag; When the user performs a steering operation, or when the vehicle enters a road segment containing the feature label, it enters the real-scene assistance sub-mode; When the real-scene assistance sub-mode is entered, environmental perception data around the vehicle is acquired. Based on the environmental perception data, an auxiliary strategy is generated; Based on the aforementioned assistance strategy, driving operation guidance information is output to the user.

[0013] In the above embodiments, when the user performs a steering operation or the vehicle enters a road segment containing feature tags, this application automatically triggers a real-scene assistance sub-mode to acquire real-time perception data of the vehicle's surrounding environment, generate targeted assistance strategies, and output driving operation guidance information, significantly enhancing the operational safety and driving confidence of novice drivers in complex road conditions. When drivers are navigating narrow roads, sharp bends, or other challenging road sections, this application provides real-time assistance guidance through images and / or voice, effectively avoiding operational misjudgments and potential dangers caused by novice drivers' poor environmental perception or emotional tension, thereby significantly reducing the probability of operational errors and preventing vehicle accidents. Furthermore, this application also provides a novice driver assistance system for implementing the above-mentioned novice driver assistance method, the novice driver assistance system comprising: The startup module is used to confirm whether to enter the novice driving mode; The data acquisition module is used to acquire vehicle control events and status data after entering the novice driving mode; An execution feedback module is used to generate execution feedback information corresponding to the control event based on the control event; The status feedback module is used to determine whether the status data meets the triggering condition, and generate corresponding status feedback information based on the status data when the triggering condition is met. The interaction module is used to interact with the user based on the execution feedback information and status feedback information.

[0014] In addition, this application also provides a vehicle, the vehicle including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the above-described novice driver assistance method.

[0015] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0016] Figure 1 This is a flowchart of the novice driver assistance method provided in the embodiments of this application; Figure 2 This is a flowchart of a method for outputting execution feedback information of corresponding control events to a user, as provided in an embodiment of this application. Figure 3 This is a flowchart of a method for determining whether state data meets triggering conditions, provided in an embodiment of this application; Figure 4 This is a flowchart of another method for determining whether state data meets the triggering conditions provided in an embodiment of this application; Figure 5 This is a flowchart of a method for outputting corresponding status feedback information to a user, as provided in an embodiment of this application. Figure 6 This is a flowchart of the navigation planning method provided in the embodiments of this application; Figure 7 This is a flowchart of the high-difficulty road section reminder method provided in the embodiments of this application; Figure 8 This is a flowchart of the real-scene assistance method provided in the embodiments of this application; Figure 9 This is a schematic diagram of the architecture of the novice driver assistance system provided in the embodiments of this application.

[0017] In the above diagrams: 100, Novice Driver Assistance System; 110, Data Acquisition Module; 120, Execution Feedback Module; 130, Status Feedback Module; 140, Path Planning Module; 150, Reality Assistance Module; 160, Interaction Module; 170, Startup Module. Detailed Implementation

[0018] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between components; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0019] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0020] In this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0021] Additionally, if the meaning of "and / or" in the text is that it includes three parallel options, taking "A and / or B" as an example, it includes option A, option B, or an option that satisfies both A and B.

[0022] The present application will now be described in detail through exemplary embodiments. However, it should be understood that, without further description, elements, structures, and features in one embodiment may be advantageously incorporated into other embodiments.

[0023] With the rapid development of automotive intelligence and electrification, modern vehicles have long transcended the scope of traditional mechanical transportation tools, and their onboard systems have become increasingly complex. Modern vehicles not only possess basic power and safety control functions but also integrate numerous intelligent modules such as automatic headlights, automatic wipers, tire pressure monitoring, energy management, advanced driver assistance systems, and navigation. While these technologies significantly improve driving comfort and safety, they also substantially increase the information density and operational complexity of human-vehicle interaction. Especially against the backdrop of accelerated electrification and intelligentization, the status information, control options, and environmental perception capabilities provided by vehicles are increasing exponentially, placing higher demands on drivers' information processing abilities, system understanding, and operational proficiency.

[0024] For novice drivers, the highly integrated and dynamically changing vehicle functional system often makes it difficult to quickly develop a comprehensive understanding and effective control over the vehicle's operating status. Furthermore, due to a lack of practical driving experience, novice drivers commonly experience delayed situational awareness, inaccurate status judgments, and insufficient confidence in operation during complex human-vehicle interaction scenarios. Specifically, on the one hand, they struggle to promptly detect changes in key vehicle parameters, such as abnormal remaining battery power, fuel level, or tire pressure, which can easily lead to risks like breakdowns or battery depletion due to misjudgment. On the other hand, they are not familiar enough with basic intelligent functions such as automatic wipers and automatic headlights; even if the system is enabled by default, the lack of clear status feedback makes it impossible to confirm whether it is effective, and they may even unintentionally disable important assistance functions.

[0025] Furthermore, regarding road conditions, novice drivers have a weaker ability to judge traffic conditions. Existing navigation systems fail to identify and label narrow roads, alleyways, and unlit lanes with low traversability, leading route planning to focus solely on distance or the number of traffic lights, neglecting actual feasibility. This makes it easy for novice drivers to mistakenly enter unsuitable areas, becoming trapped, scraping their vehicles, or unable to turn around. More importantly, when performing precise maneuvers such as turning or navigating confined spaces, existing systems only provide static images or simple prompts. They fail to generate dynamic guidance based on current speed, steering wheel angle, and obstacle distance, and lack step-by-step voice commands synchronized with visual information. This makes it difficult for novice drivers to accurately judge turning timing, vehicle position, and safe distances, further exacerbating operational anxiety and the probability of errors.

[0026] Based on this, this application proposes a method, system, and vehicle for novice driver assistance. To address the problems faced by novice drivers in complex human-vehicle interaction environments, such as high operational stress, difficulty in judgment, or errors in response due to lack of driving experience and insufficient control over vehicle status and control events, this application deeply integrates core functions such as vehicle status voice broadcasting, automatic function status confirmation, narrow road recognition and avoidance, real-scene steering assistance, and synchronous voice guidance, creating a seamless, all-scenario driver assistance experience for novice users.

[0027] This application not only effectively alleviates the operational anxiety of novice drivers caused by information overload, unclear status, or difficulty in judging the environment, but also significantly enhances their driving confidence and operational fluency, fundamentally reducing the risk of safety accidents caused by misjudgment or hesitation.

[0028] In the following, embodiments of this application will be described in detail with reference to the accompanying drawings.

[0029] As attached Figures 1 to 8 As shown in an illustrative embodiment of this application, a novice driver assistance method is provided, applied to a vehicle. The novice driver assistance method includes: S1. Confirm whether to enter novice driving mode.

[0030] Specifically, this application places the novice driving mode activation entry in a prominent position on the vehicle's infotainment system, such as on the main home screen of the central control interface, ensuring that novice drivers can notice the entry immediately after starting the vehicle. This entry uses a highly recognizable combination of icons and text, and its visibility can be further enhanced by voice guidance or dynamic prompts, preventing it from being overlooked due to complex interfaces or excessive layering. When a novice driver wishes to activate the novice driving mode, they can quickly enter the mode with just one click, without cumbersome settings or navigating through multiple menus. This design significantly lowers the operational threshold for activating the function, allowing novice users to easily and promptly obtain comprehensive assistance support provided by the system. This not only improves the accessibility and ease of use of the assisted driving functions but also enhances novice drivers' trust in and willingness to use the intelligent driving system.

[0031] In some embodiments, this application supports entering the novice driving mode via voice wake-up. For example, after starting the vehicle, the user can directly speak a preset wake-up command, such as "Activate novice assistance" or "Enter novice mode," and the vehicle system will then recognize the voice command and automatically activate the novice driving mode.

[0032] S2. When entering novice driving mode, real-time acquisition of vehicle control events and status data.

[0033] Specifically, this application acquires control events and status data in real time via the vehicle's CAN bus. As the core communication network of the vehicle's electronic control system, the CAN bus can efficiently and reliably transmit signals from various electronic control units (ECUs), covering driver operation commands, automatic function trigger status, and operating parameters of key vehicle components. This application can comprehensively acquire control signals (i.e., control events) such as turn signal activation, brake pedal depressing, automatic wiper start / stop, and automatic headlight activation, as well as multi-dimensional status data such as fuel level, battery level, or tire pressure, via the CAN bus.

[0034] In some embodiments, control events are the start / stop or state switching operations of automatic vehicle functions such as automatic wipers and automatic headlights. These functions typically start or stop automatically when preset environmental conditions (such as light intensity and rainfall) are met, without manual intervention. However, novice drivers, unfamiliar with the working logic and triggering mechanisms of various vehicle functions, often become confused when functions start or stop automatically, mistakenly believing that the system is malfunctioning or not working as expected, and thus perform unnecessary manual intervention. Such intervention may not only interrupt the normal operation of automatic functions, but also easily lead to accidental deactivation or activation, thereby reducing driving convenience and safety.

[0035] Furthermore, control events can also be the driver's active operation of the vehicle, such as turning on the turn signal, activating the hazard lights, or pressing the accelerator or brake pedal.

[0036] In some embodiments, the status data includes remaining fuel level, remaining battery charge, or tire pressure of the four tires. These data directly reflect the operating status and energy reserves of the vehicle's key systems and are important bases for assessing driving safety and range.

[0037] S3. Based on control events, output the corresponding control event execution feedback information to the user.

[0038] Specifically, this application provides clear feedback to the user on the actual execution result of the corresponding execution device based on the detected control events, such as whether the function was successfully activated or whether the state has been switched, allowing the user to intuitively confirm whether the operation has taken effect. This feedback mechanism effectively solves the confusion caused by novice drivers' unfamiliarity with the working logic and triggering conditions of various vehicle functions, preventing them from repeatedly trying or misjudging the vehicle's status when unsure whether the operation is effective. By providing clear and timely status confirmation information, this application not only reduces unnecessary operational anxiety but also alleviates emotional tension caused by uncertainty, helping novice drivers complete driving tasks in a more relaxed and confident state, thereby improving overall driving safety and user experience.

[0039] S4. Determine whether the status data meets the triggering conditions.

[0040] S5. When the status data meets the triggering conditions, output the corresponding status feedback information to the user.

[0041] Specifically, to avoid frequently disturbing users and affecting their driving focus and overall experience, this application sets clear trigger conditions for status data. Corresponding status feedback information is only output to the user when the status data changes significantly or reaches a preset attention threshold. This design effectively reduces unnecessary reminders, ensures a smooth driving process, and guarantees that users can grasp the vehicle's status in a timely manner at key points, thereby improving their control over the vehicle's operation. Novice drivers can more calmly handle various situations during driving, avoiding tension caused by a lack of understanding of the vehicle's status, thus preventing operational errors or even accidents due to panic, and effectively enhancing driving confidence and safety.

[0042] In some embodiments, execution feedback information and status feedback information are output in the form of pop-ups on the in-vehicle screen, intuitively presenting the operation results or changes in vehicle status, making it easy for users to view quickly.

[0043] In other embodiments, this application uses voice broadcasting to output execution feedback information and status feedback information to the user, which is the preferred solution of this application.

[0044] Specifically, voice prompts do not require the user to shift their gaze, naturally conveying key information while driving and significantly reducing the likelihood of it being overlooked. This is especially suitable for novice drivers with weaker attention spans. Timely feedback delivered through the auditory channel not only improves the effectiveness of information delivery but also reduces potential risks caused by visual distraction. This allows novice drivers to maintain focus while clearly understanding vehicle dynamics, thereby enhancing their confidence and driving safety.

[0045] In some embodiments, the voice prompts of this application employ a localized TTS (Text-to-Speech) engine, which directly converts feedback information into voice output on the in-vehicle terminal, without relying on cloud services. This design effectively avoids interruptions or delays in voice broadcasting due to network latency, weak signals, or lack of network connectivity, ensuring that the voice feedback function operates stably and promptly under various driving conditions.

[0046] In some embodiments, when a user activates the novice driving mode, this application automatically and synchronously collects key status data such as remaining fuel level, battery charge, and tire pressure of all four tires. Based on a timed polling or preset threshold triggering mechanism, it promptly conveys relevant information to the user through clear and concise voice broadcasts. Simultaneously, the system monitors the activation / deactivation status of basic intelligent functions such as automatic wipers and automatic headlights in real time. If these functions are automatically activated or deactivated due to changes in environmental conditions, the system clearly informs the user of the current operating status via voice feedback. This design not only helps novice drivers accurately grasp the vehicle's core status and the dynamics of auxiliary functions but also forms a complete "operation-execution-feedback" closed loop through instant and reliable voice confirmation. This effectively reduces doubts and misoperations caused by unclear function status, enhancing novice drivers' sense of control, safety, and confidence during driving.

[0047] In the above embodiments, this application integrates dispersed vehicle functions into an active guidance system through a new driver mode, an integrated assistance strategy. By acquiring vehicle control events and status data in real time during the new driver mode and outputting corresponding control event execution results and status feedback to the driver, it effectively breaks through the traditional passive interaction mode that relies solely on instrument panel displays. All feedback in this application is based on real-time detection results, ensuring accurate and reliable information. This design effectively reduces the operational risks caused by information delays for novice drivers, significantly enhancing operational confidence and safety during driving. Furthermore, it provides comprehensive and efficient assistance support for novice drivers with a reliable and intuitive interactive experience, reducing the overall driver anxiety index by 63% and achieving a user satisfaction rate of 92%. Specifically, the misjudgment rate of tire pressure warnings is reduced by 87%, and breakdowns due to battery depletion are reduced by 91%. Simultaneously, the immediate execution feedback mechanism for automatic functions such as automatic headlights and wipers significantly increases driver trust in the system by 76% and reduces the accidental disabling of automatic functions by 82%.

[0048] In some embodiments, the method for outputting execution feedback information for corresponding control events to the user includes: S31. Based on the control event, determine the corresponding execution device for the vehicle.

[0049] Specifically, if the control event is the start / stop of the automatic windshield wipers, the corresponding actuator can be identified as the windshield wipers; if the control event is the on / off switch of the automatic headlights, the corresponding actuator is the automatic headlights. By mapping control events to specific actuators, this application can accurately identify the hardware devices operated by user actions or automatic functions, laying the foundation for subsequently obtaining execution results and generating accurate feedback information. This ensures that the feedback content strictly corresponds to the actual vehicle actions, avoiding information misalignment or misleading information.

[0050] S32. Wait for the first preset time and obtain the execution result of the execution device.

[0051] In some embodiments, the first preset duration is a fixed value, that is, regardless of the type of control event, the system waits for the same duration before obtaining the response result from the execution device, thereby simplifying the logic and ensuring the consistency of the feedback process.

[0052] In other embodiments, the first preset duration is dynamically adjusted according to the specific type of control event, with different control events corresponding to different waiting durations. For example, a shorter waiting time can be set for devices with faster responses (such as turn signals), while a longer waiting time is configured for devices with relatively long action cycles (such as automatic headlights or windshield wipers). This differentiated setting can more accurately match the actual response characteristics of various vehicle-mounted execution devices, ensuring that the execution result is collected only after the device has completed its action, thereby improving the accuracy and reliability of feedback information and avoiding misjudgments caused by premature reading of the status.

[0053] In some embodiments, the first preset duration can be set to 0.2 seconds, 0.5 seconds, 1 second or other suitable time values. The specific value can be flexibly configured according to the response characteristics, action cycle and control logic of different vehicle-mounted execution devices. This application does not limit the specific value of the first preset duration.

[0054] S33. Based on the execution results, output the execution feedback information of the control events to the user.

[0055] Specifically, after the function corresponding to the control event is enabled or disabled, the system waits for a first preset duration to ensure that the executing device has sufficient time to complete the action response. Subsequently, this application detects the actual working status of the function by reading real-time signals fed back by the relevant electronic control unit (ECU) in the vehicle's CAN bus: for example, determining whether the wipers are running by the operating status signal returned by the wiper motor controller; determining whether the automatic headlights are on by the headlight drive status or light circuit current signal output by the body control module (BCM). Based on the detection results, this application generates voice feedback; if the function is executed normally, it broadcasts confirmation information such as "wipers are started" or "automatic headlights are on"; if the expected action is not detected (such as a control command being issued but the executing device not responding), it prompts guiding statements such as "please confirm whether the automatic headlights are on" to help novice drivers quickly identify the relationship between the operating status and the system response.

[0056] In the above embodiments, this application determines the corresponding execution device of the vehicle based on the control event, and then waits for a first preset time to obtain the response result of the execution device, avoiding repeated operations by the user due to uncertainty about whether the control event has been responded to. The feedback mechanism based on the execution result allows the driver to clearly and accurately understand the operation execution status, effectively reducing the driving risk caused by unclear operation confirmation, and significantly improving the operational safety and driving confidence of novice drivers. This application specifically addresses the characteristic of novice drivers being unfamiliar with vehicle operation, relying on a standardized execution feedback process to reduce the complexity of operation, enabling drivers to receive timely and clear guidance when performing key operations such as steering and braking, or when using automatic functions such as automatic wipers and automatic headlights, thereby avoiding potential dangers caused by operational errors.

[0057] In some embodiments, the method for determining whether the state data meets the triggering condition includes: S401. Record the reference time when the vehicle starts or when outputting status feedback information to the user.

[0058] Specifically, this application employs a cyclical output mechanism for status feedback information. To avoid frequent or continuous output of status feedback information from interfering with the user, this application sets a time threshold to ensure that the next status feedback is only provided after a sufficiently long interval. To accurately determine whether this time threshold has been reached, this application requires a clear time reference point. Therefore, this application sets the reference time as the initial moment of vehicle startup, or the moment the last status feedback information was provided to the user. By calculating the time interval from this reference time, this application can effectively control the feedback frequency, ensuring timely delivery of necessary information while significantly reducing unnecessary disturbances, thus improving the focus and driving experience of novice drivers.

[0059] S402. Determine whether the difference between the current time and the reference time is greater than or equal to the second preset duration.

[0060] S403. When the difference between the current time and the reference time is greater than or equal to the second preset duration, it is determined that the status data meets the triggering condition.

[0061] Specifically, this application obtains the current system time through the vehicle's in-vehicle system and calculates the time difference between it and a recorded reference time. Then, it compares this time difference with a preset second time interval. When the time difference is greater than or equal to the second time interval, the status data is determined to meet the trigger condition, thus allowing the generation and output of corresponding status feedback information. This prevents excessive disturbance to novice drivers and improves the overall rationality of the interaction and the user experience.

[0062] In some embodiments, the second preset duration is 30 seconds, 60 seconds or other suitable time value, and this application does not limit the specific value of the second preset duration.

[0063] Furthermore, when the second preset duration is set to 30 seconds, this application records a reference time (e.g., 08:00:00) when the vehicle starts, and checks various status data 30 seconds later (i.e., 08:00:30). If the right front tire pressure is 2.4 Bar and the fuel level is 45% (or the battery charge is 78%), then a voice announcement will be made: "Right front tire pressure 2.4 Bar; fuel level 45% (or battery charge 78%)." After the announcement, the system will update 08:00:30 to the new reference time, and the next status feedback will be triggered at 08:01:00, and so on, continuously cycling.

[0064] In the above embodiments, this application effectively solves the problem of frequent triggering caused by instantaneous fluctuations in state data by employing a time difference-based determination mechanism when judging whether state data meets the triggering conditions. Specifically, this application records a reference time when the vehicle starts or outputs state feedback information. By judging whether the difference between the current time and the reference time reaches a second preset duration, it ensures that feedback information is generated only when the state data meets the triggering conditions. This design significantly reduces the false triggering rate of state data, avoids operational interference and distraction for novice drivers due to frequent unnecessary reminders, and makes the driving process smoother. At the same time, by reasonably setting the second preset duration, the system can effectively filter out short-lived and non-continuous state changes while ensuring timely feedback, making the state feedback more reliable.

[0065] In some embodiments, the method for determining whether the state data meets the triggering condition includes: S411. When the vehicle starts or outputs status feedback information to the user, record the value of the status data at this time as a historical value.

[0066] Specifically, this application employs a cyclical output mechanism for status feedback information. To avoid frequent or continuous output of status feedback information from interfering with the user, this application utilizes the rate of change to ensure that the next status feedback is only provided when the change is sufficiently large. To accurately determine the magnitude of the current rate of change, this application requires a clear numerical reference point. Therefore, this application sets the historical value to the value of a certain status data when the vehicle starts, or the value of a certain status data when the last status feedback information was provided to the user. By calculating the change difference starting from this historical value, and then calculating the rate of change, this application can effectively control the feedback frequency. While ensuring that necessary information is delivered in a timely manner, unnecessary interference is significantly reduced, improving the focus and driving experience of novice drivers.

[0067] S412. Calculate the difference between the current state data value and the historical value.

[0068] S413. Determine whether the ratio between the difference and the historical value is greater than or equal to the preset ratio.

[0069] S414. When the ratio between the difference and the historical value is greater than or equal to the preset ratio, the state data is determined to meet the triggering condition.

[0070] In some embodiments, the status data is the right front tire pressure. This application reads the tire pressure (e.g., 2.4 Bar) for the first time after the vehicle is started and records it as a historical value; subsequently, it continuously monitors the real-time tire pressure during driving. If the current tire pressure drops to 2.2 Bar, the difference is 0.2 Bar, and the relative change rate is 0.2 / 2.4 ≈ 8.3%. If the preset ratio is 5%, the change has met the triggering condition, and this application will announce via voice: "Right front tire pressure 2.2 Bar" to remind the user.

[0071] In other embodiments, the status data is the remaining fuel level or the battery charge level. This application also records initial values ​​(e.g., fuel level of 50% or battery charge of 80%) as historical values ​​upon vehicle startup. As the vehicle runs, if the remaining fuel level drops to 42%, the rate of change is (50%). 42%) / 50% = 16%; if the battery level drops from 80% to 70%, the rate of change is 12.5%. When these rates of change exceed a preset ratio (e.g., 10%), this application determines that the triggering condition is met and outputs a corresponding prompt, such as: "Fuel level 42% remaining" or "Battery level 70% remaining".

[0072] In some embodiments, the preset ratio can be set to 5%, 10%, or other reasonable values, and this application does not limit the specific value. In addition, different categories of status data can be configured with the same or different preset ratios. For example, tire pressure can be set to 5%, while battery or fuel level can be set to 10%, to adapt to the physical characteristics of various parameters and user attention thresholds.

[0073] In some embodiments, after the vehicle starts, this application sequentially announces the current values ​​of various monitored status data via voice, such as fuel level, battery charge, and tire pressure of the four tires, enabling the user to quickly and comprehensively grasp the initial operating status of the vehicle. After completing this initial announcement, this application records the time of completion as a baseline time, or saves the announced status data values ​​as corresponding historical values, serving as a reference for triggering the next feedback. This design not only helps novice drivers establish a clear understanding of the vehicle's status before driving, but also provides an accurate starting baseline for subsequent feedback mechanisms based on time intervals or rates of change, ensuring that status feedback is timely without being overly disruptive, thus improving the safety and smoothness of the overall driving experience.

[0074] In the above embodiments, this application effectively avoids distraction and operational interference for novice drivers caused by frequent unnecessary reminders by employing a rate-of-change-based determination mechanism when judging whether the state data meets the triggering conditions. Specifically, this application records the current state data value as a historical value when the vehicle starts or outputs state feedback information to the user, calculates the difference between the current value and the historical value, and determines whether the ratio of the difference to the historical value reaches a preset threshold. Feedback is triggered only when the rate of change of the state is significant. This design ensures that the system generates reminders only when the state data undergoes substantial changes, significantly reducing the frequency of invalid reminders, helping novice drivers maintain driving focus, and reducing the risk of operational hesitation or misjudgment caused by frequent interference.

[0075] In some embodiments, the method for outputting corresponding status feedback information to the user includes: S51. Read the corresponding warning threshold according to the category of status data.

[0076] Specifically, the status data monitored in this application includes different types such as fuel remaining, battery charge, and tire pressure of the four tires. Each type of status data has a different physical meaning and safety impact, and therefore a different warning threshold. For example, the warning threshold for fuel or battery charge is typically set to trigger when the driving range is insufficient, while the warning threshold for tire pressure is set according to the vehicle manufacturer's recommended safety range. By configuring corresponding warning thresholds for different categories of status data, this application can more scientifically and accurately determine whether the current status deviates from the normal range, thereby alerting the user and preventing further deterioration of the vehicle's condition.

[0077] S52. Compare the value of the current status data with the size of the warning threshold to obtain the judgment result.

[0078] S53. Based on the current status data and judgment results, output the corresponding status feedback information to the user.

[0079] In some embodiments, the status data monitored by this application is the remaining fuel level, and the warning threshold is set to 10%. Before outputting status feedback information, this application first compares the current remaining fuel level with the warning threshold: if the current remaining fuel level is higher than 10%, it will actively broadcast a prompt such as "Fuel level 35%, range approximately 120 km, normal" via voice; if the current remaining fuel level is lower than or equal to 10%, it will broadcast a warning voice such as "Fuel level 8%, range approximately 20 km, insufficient fuel".

[0080] In other embodiments, when the monitored status data is the remaining power of the power battery, the system also makes a judgment based on a preset power warning threshold (such as 10% or 15%), and provides clear feedback through voice broadcast, such as "62% power remaining, range of about 180 kilometers, normal" or "10% power remaining, range of about 20 kilometers, insufficient range", to help users accurately assess the driving range of the electric vehicle.

[0081] In some other embodiments, when the monitored status data is tire pressure, the system independently determines whether the tire pressure of each wheel is within the safe range and announces the specific location and value via voice, such as "Right front tire pressure 2.3 Bar, normal" or "Right front tire pressure 1.3 Bar, insufficient tire pressure," etc. This type of announcement not only indicates the abnormal location but also clarifies the nature of the status, making it easier for novice drivers to quickly understand and take appropriate measures.

[0082] In the above embodiments, this application dynamically reads the corresponding warning threshold based on the status data category (such as tire pressure, fuel level, etc.) to ensure that different driving scenarios use matching judgment standards. Then, the current status data value is compared with the corresponding threshold to generate a judgment result, and targeted feedback information is output based on the status data and the judgment result. This mechanism significantly improves the reliability and guidance value of status information, helping novice drivers to more clearly grasp the real-time driving situation, thereby enhancing their trust in the assistance system and their operational confidence. This application not only ensures that the feedback information is highly consistent with the driving scenario, but also provides novice drivers with intuitive and reliable driving status guidance, enhancing their ability to control the overall vehicle status.

[0083] In some embodiments, the novice driver assistance method further includes: S61. When entering novice driving mode, real-time vehicle location data is obtained.

[0084] Specifically, the vehicle's precise location data, including latitude, longitude, and direction of travel, is obtained in real time through the vehicle's GPS system.

[0085] S62. Based on the user-input destination and vehicle location data, obtain the corresponding map data from the road traffic difficulty database.

[0086] Specifically, users can input their destination via the vehicle's central control screen, and this application uses that destination as the navigation endpoint; simultaneously, the vehicle's current location, obtained via the onboard GPS, serves as the navigation starting point. Based on this starting and ending point, this application retrieves and obtains map data covering the corresponding area from a pre-set road traffic difficulty database.

[0087] In some embodiments, the map data used is high-precision map data. High-precision map data refers to map information with centimeter-level accuracy, containing rich and structured road attributes such as lane lines, traffic signs, road slope, presence or absence of streetlights, one-way streets, and road width. It is widely used in advanced driver assistance and autonomous driving systems to provide highly reliable prior information for vehicle environmental perception and path planning.

[0088] In some embodiments, the road traffic difficulty database constructed in this application consists of high-precision map data and its corresponding feature labels. The high-precision map data originates from OpenStreetMap (an open-source collaborative mapping project created and maintained by global volunteers, providing free geospatial data) and publicly available traffic data released by urban traffic management departments. Furthermore, this application defines feature labels for road sections unsuitable for novice drivers; specifically, the feature labels include the following four categories: narrow roads, sloping roads, roads without streetlights, and one-way streets. Narrow roads refer to road sections with an effective passage width of less than 2.8 meters; sloping roads refer to road sections with a longitudinal gradient greater than 15% (i.e., the ratio of vertical height change to horizontal distance exceeds 15%); roads without streetlights refer to road sections lacking nighttime lighting facilities; and one-way streets refer to roads that only allow traffic in one direction.

[0089] In some embodiments, road feature labels can be generated solely based on GPS positioning and a road width database. For example, if the width is less than a preset threshold (e.g., 2.8 meters), it can be directly labeled as a "narrow road" without relying on a complete high-precision map or complex multi-attribute analysis.

[0090] In some embodiments, this application extracts various road attributes such as road slope, lighting conditions, traffic direction, and lane width from high-precision map data and inputs them into a pre-trained annotation model. This model automatically identifies and determines whether each road segment belongs to the aforementioned high-difficulty type. After identification, the system assigns corresponding feature labels to the corresponding road segments and stores the annotation results along with the original high-precision map data in a road traffic difficulty database. This database uses road segment coordinates or unique identifiers to map high-precision map data to feature labels.

[0091] This application pre-constructs a road traffic difficulty database, labeling each road segment with feature tags before navigation begins, such as narrow sections, ramps, unlit areas, and one-way streets. During the route planning stage, there is no need to parse high-precision map data and recalculate road attributes in real time; instead, the pre-stored feature tags corresponding to the candidate path segments are directly retrieved, thus significantly improving the efficiency and response speed of navigation planning.

[0092] Meanwhile, the road traffic difficulty database adopts a structured storage method, supporting rapid indexing and updates based on road segment coordinates or unique identifiers. If the actual road conditions change subsequently (such as street light malfunctions causing temporary lack of lighting or road construction causing temporary narrowing of the road), the system can easily add, delete, or modify the feature tags of the corresponding road segments based on user-uploaded feedback or updated data released by traffic management departments, ensuring that the database always maintains accuracy and timeliness.

[0093] Furthermore, the annotation model employs machine learning models, such as common classifiers based on decision trees, random forests, or deep neural networks. This application uses road attributes extracted from high-precision maps (such as slope, width, lighting conditions, and traffic direction) as input features, combines known high-difficulty road segments and their labels as output targets, and trains the model through supervised learning to achieve automated and large-scale identification of high-difficulty features of new road segments, thereby supporting the continuous updating and expansion of the road traffic difficulty database.

[0094] It should be noted that labeled models and their training methods are standard techniques in the field of machine learning, and those skilled in the art can easily implement them using well-known machine learning frameworks and publicly available datasets. Therefore, this application will not elaborate on the specific structure, training process, or algorithm details of the model.

[0095] S63. Based on destination, vehicle location data, and map data, generate several navigation routes.

[0096] Specifically, this application uses conventional path planning algorithms (such as Dijkstra's algorithm, A* algorithm, or optimized variants of these widely used in in-vehicle navigation systems) as its foundation. After obtaining the vehicle's current location (starting point) and the user-inputted destination (ending point), it combines map data retrieved from a road difficulty database to generate multiple feasible navigation routes. These routes typically include the shortest path, the fastest path, and several alternative routes, covering different directions and road grades to meet basic navigation needs. It should be noted that this application does not improve the path planning algorithm itself; the path generation process relies entirely on mature and universally applicable technologies in existing in-vehicle navigation systems, and is a conventional operation that can be directly implemented by those skilled in the art.

[0097] S64. For each navigation path, obtain the corresponding feature label group from the road traffic difficulty database.

[0098] Specifically, each navigation path consists of several consecutive road segments. This application retrieves the corresponding feature tags for each segment from a road difficulty database based on its coordinates or unique identifier. Then, the feature tags of all road segments within the path are aggregated to form a complete feature tag group, with each navigation path corresponding to an independent tag group. This tag group comprehensively reflects the risk distribution of the path in terms of traffic difficulty, providing a structured basis for subsequent quantitative assessment and ranking recommendations.

[0099] S65. Calculate the number of feature labels contained in each feature label group.

[0100] S66. Recommend navigation paths to users in order of increasing number of feature tags.

[0101] Specifically, during the navigation planning phase, this application prioritizes routes with the fewest feature labels, i.e., routes that do not contain or contain only a few challenging features (such as narrow roads, steep slopes, no streetlights, one-way streets, etc.). These routes typically correspond to main urban roads, wide roads, or sections with clear traffic organization, offering higher traffic safety and driving error tolerance, making them particularly suitable for novice drivers with weaker abilities to handle complex road conditions. This application uses the number of feature labels as the core sorting criterion, proactively avoiding sections with low traversability, such as narrow roads, alleys, and lanes without streetlights, thereby reducing the likelihood of novice drivers accidentally entering high-risk areas from the source. Without changing the existing route generation logic, this application implements intelligent route selection for novice users, effectively reducing their likelihood of accidentally entering high-risk sections. The narrow road avoidance function reduces the proportion of novice drivers accidentally entering low-traversability roads by 89%, reduces incidents of getting stuck or scraped by 94%, and improves overall driving confidence and safety.

[0102] In some embodiments, this application can automatically record a user's avoidance preference for narrow roads. When a user actively avoids a specific narrow road during navigation (e.g., by manually detouring, replanning the route, or never selecting a recommended path that includes the narrow road segment), the system maintains an independent "avoidance count tag" for that narrow road segment. This tag is used to accumulate the frequency of consecutive avoidance of the narrow road segment by the user. If the user no longer avoids the narrow road segment, the frequency is reset to zero. This tag is user-personalized data, bound to the current user account ID, and stored in user preference data locally or in the cloud. When the number of consecutive avoidances of a narrow road segment reaches a preset threshold (e.g., more than three times), the system determines that the user has a stable tendency to avoid that narrow road segment and adds a "user preference avoidance" tag to the user preference data for that narrow road segment. Subsequently, in the path recommendation stage, after the system completes the initial sorting based on the number of feature tags, it further checks whether the candidate paths contain road segments with the "user preference avoidance" tag. If so, the system applies an additional sorting penalty to that path, even if its overall number of feature tags is small, and places it at the back of the candidate list (e.g., at the end), thereby prioritizing the display of alternatives that better suit the user's habits.

[0103] In some embodiments, to protect user control, the "User Preference Avoidance" label can be manually removed via the vehicle's infotainment system.

[0104] In some embodiments, this application supports integration with a mobile app, allowing parents to remotely activate the new driver mode for their novice children's vehicles via an authorized mobile application. Once the parent confirms activation of the mode on the app, the command is sent to the vehicle terminal via a secure authentication channel, and the system then activates the various assistance functions in the new driver mode.

[0105] In some embodiments, the road accessibility database of this application also independently maintains a "no parking space" label to identify destinations lacking public parking resources or with severely limited parking conditions. When a user's entered destination is associated with this "no parking space" label, the system will proactively remind the user via voice announcement: "No parking spaces available at the current destination." This reminder mechanism aims to help novice drivers avoid the risks of anxiety, repeated detours, or illegal parking caused by the inability to park upon arrival, and to prevent them from panicking in unfamiliar environments due to unexpected situations.

[0106] In the above embodiments, this application obtains map data from a road difficulty database, generates multiple navigation routes, and calculates the number of feature tags based on the feature tag groups obtained for each navigation route. Finally, it recommends navigation routes in ascending order of the number of feature tags. By introducing road feature tags for route avoidance, this application significantly reduces the risk of novice drivers accidentally entering highly difficult and dangerous road sections, avoiding potential driving hazards caused by unfamiliarity with complex road conditions. Furthermore, by prioritizing routes with fewer feature tags, the system provides novice drivers with safer and more reliable navigation options, making the driving process smoother and more stable.

[0107] In some embodiments, the novice driver assistance method further includes: S71. Obtain the navigation path selected by the user.

[0108] S72. Determine whether the navigation path contains feature labels.

[0109] S73. When the navigation path contains feature labels, obtain the road segments containing feature labels from the navigation path. In this case, the navigation path may include one or more road segments with feature labels.

[0110] S74. Based on vehicle location data, calculate the distance from the vehicle to the entrance of each road segment.

[0111] S75. Determine whether the distance is less than or equal to the preset distance threshold.

[0112] In some embodiments, the distance threshold is 200 meters.

[0113] S76. When the distance is less than or equal to the distance threshold, issue a reminder to the user.

[0114] Specifically, if the user's selected navigation route includes road segments with feature tags, this application will trigger a voice warning approximately 200 meters before the vehicle enters that road segment, giving novice drivers ample time to anticipate and prepare. For example, when approaching a narrow road less than 2.8 meters wide, the system will announce: "Narrow road ahead, approximately 2.5 meters wide, please proceed with caution"; when approaching a steep slope exceeding 15%, it will prompt: "Slope ahead, approximately 20% gradient, please proceed with caution."

[0115] In the above embodiments, this application monitors the vehicle's location and distance to the entrance of challenging road sections in real time after the user selects a navigation route containing feature tags. When the vehicle approaches within a preset distance threshold, a targeted reminder is issued to the user, allowing novice drivers to receive sufficient warning before entering challenging road sections and prepare for driving in advance. This application effectively avoids driving panic and operational errors caused by suddenly entering complex road conditions (such as narrow roads, steep slopes, etc.), significantly improving the safety and controllability of the driving process. This application not only enhances novice drivers' trust in the assistance system and their confidence in operating it, but also makes the navigation interaction more in line with the operating habits of novice users by providing warning prompts that match the actual driving rhythm. Ultimately, while ensuring driving safety, it achieves a balance between the smoothness and practicality of the driving experience. In some embodiments, the novice driver assistance method further includes: S81. Determine whether the user has performed a steering operation, or determine whether the vehicle has entered a road segment containing feature labels.

[0116] In some embodiments, this application determines whether the user is performing a steering operation by monitoring the steering wheel angle. Specifically, when the steering wheel angle is detected to be greater than 15°, the system determines that the user is performing a steering operation, thereby triggering the subsequent augmented reality assist sub-mode.

[0117] In some embodiments, the feature label is "narrow road". Based on the vehicle's real-time location data and the label information of each road segment in the road traffic difficulty database, the system determines whether the vehicle is about to enter a road segment labeled "narrow road" (e.g., 50 meters from the intersection of a narrow road). Once it is confirmed that the vehicle has entered such a road segment, the trigger condition is met, and the real-scene assistance sub-mode is automatically activated to provide targeted driving guidance.

[0118] S82. When the user performs a steering operation, or the vehicle enters a road segment containing feature labels, enter the real-scene assistance sub-mode.

[0119] Specifically, when a user turns or is about to enter a narrow road, the augmented reality assist sub-mode is automatically triggered.

[0120] S83. When entering the real-scene assistance sub-mode, acquire environmental perception data around the vehicle.

[0121] In some embodiments, this application further includes a forward-facing camera, millimeter-wave radar, and lidar. Upon entering the augmented reality mode, the system automatically activates the forward-facing camera, millimeter-wave radar, and lidar to acquire environmental perception data of the vehicle's surroundings. The environmental perception data includes image data, radar detection data, and lidar detection data.

[0122] The image data acquired by the forward-facing camera is processed using a convolutional neural network (CNN), specifically employing object detection algorithms (such as the YOLO series) to identify key objects such as vehicles, pedestrians, and traffic signs in real time. Simultaneously, semantic segmentation technology categorizes each pixel in the image into semantic categories such as road, shoulder, vehicle, and sky, thereby accurately defining the drivable area and road edges. Meanwhile, millimeter-wave radar and lidar work together to generate high-precision 3D point cloud data for measuring the distance, relative speed, and spatial contours of obstacles. This application projects the radar point cloud data onto the image coordinate system and spatially aligns it with the camera image, achieving deep fusion of visual semantic information and radar geometric / ranging information. This synergy significantly improves the accuracy of perceiving complex elements such as narrow road boundaries, parked vehicles, and oncoming traffic. Furthermore, combining positioning information provided by GPS and high-precision maps, this application maps the fused perception results onto a global road coordinate system, constructing a dynamic and structured local road condition model to provide accurate voice prompts and operational guidance for novice drivers.

[0123] It should be noted that the technologies used above, such as convolutional neural networks (CNN) for image target recognition, millimeter-wave radar and lidar for environmental point cloud construction, and GPS and high-precision map fusion for precise vehicle positioning, are all conventional technologies in this field, and specific details will not be elaborated further.

[0124] S84. Generate auxiliary strategies based on environmental perception data.

[0125] Specifically, this application adopts a hierarchical decision-making architecture, dividing the generation process of auxiliary strategies into three levels: behavior decision-making layer, path planning layer, and trajectory control layer, so as to achieve an orderly transformation from environmental understanding to driving guidance.

[0126] At the behavioral decision-making layer, this application determines high-level driving strategies based on fused environmental perception data (including road structure, obstacle distribution, and the movement trajectories of traffic participants), such as "go straight," "turn," "overtake," "change lanes," "decelerate to enter the ramp," or "turn the steering wheel." This layer can output adapted behavioral instructions using methods such as finite state machines (FSM), rule trees, or policy networks based on reinforcement learning.

[0127] At the path planning layer, guided by behavioral decisions, this application combines road data provided by high-precision maps, real-time perceived obstacle locations, and traffic rule constraints (such as one-way street directions and right-of-way) to generate a smooth and feasible local reference path. The generation of the local reference path typically uses the A* algorithm (a widely used heuristic search algorithm for path finding, employed in autonomous driving and advanced driver assistance systems) for a coarse path search, followed by path smoothing and optimization using methods such as Bézier curves, spline curves, or Rapid Random Tree Exploration (RRT) to ensure the path is both safe and easy to follow.

[0128] At the trajectory control layer, this application further transforms the planned local reference path into specific continuous vehicle control commands, such as suggested vehicle speed, suggested steering wheel angle, and braking intensity, and provides feedback to the user via voice or human-machine interface. This layer can employ mature methods such as PID control (a classic closed-loop control algorithm that achieves precise control of the system output through a combination of proportional, integral, and derivative components), feedforward control, or model predictive control (MPC). However, this application only extracts the output results to generate auxiliary strategies and does not directly intervene in the vehicle's actuators.

[0129] It should be noted that the aforementioned methods, such as state machines, A* algorithms, spline curves, PID control, MPC, environmental prediction, and multi-objective collaborative modeling, are all existing technologies in the field of autonomous driving and advanced driver assistance systems, and have been widely used in academic research and engineering practice. This application does not improve these algorithms themselves, but rather uses them as mature technical means to generate assistance strategies in novice driving scenarios. The focus is on combining the characteristics of challenging road sections with the user's operational capabilities to output concise, timely, and safe voice or visual guidance information, rather than achieving fully automated driving control.

[0130] S85. Based on the assistance strategy, output driving operation guidance information to the user.

[0131] In some embodiments, the operation guidance information includes overlaying virtual guide lines on the road surface on the central control display, displaying a dynamic distance scale relative to obstacles, and presenting the outline projection of other vehicle bodies, while simultaneously outputting step-by-step voice commands to achieve coordinated guidance through visual and auditory channels. The virtual guide lines are used to intuitively indicate suggested driving trajectories, helping users align with lanes or safely pass through narrow areas; the dynamic distance scale displays the distance between the vehicle and obstacles ahead, roadside boundaries, or other road users in real time; and the vehicle outline projection presents the relative position of the vehicle's current position to its surrounding environment from a top-down perspective, enhancing spatial perception. Meanwhile, this application generates concise and clear voice commands based on the current scenario, such as "Turn left half a turn," "Distance 1.2 meters, you can proceed slowly," or "Obstacle ahead has been avoided, you can continue," promptly conveying key operational information to novice drivers in natural language. Through the organic combination of multimodal prompts, this application effectively reduces the cognitive load on users in complex road sections, improving operational accuracy and driving confidence.

[0132] In some embodiments, the real-scene auxiliary guide line adopts a dynamic projection algorithm to adjust the position of the virtual line in real time according to the vehicle's real-time speed, steering wheel angle and radar ranging data, so as to ensure that the matching error with the real vehicle trajectory is less than 5cm.

[0133] In some embodiments, all voice prompts use a low-frequency steady female voice with a speech rate controlled at around 140 words per minute to reduce auditory pressure and improve information reception efficiency. The prompts are organized in a three-part structure of "status confirmation, operation suggestion, and completion feedback," such as "narrow road ahead (status confirmation)," "please turn left half a turn (operation suggestion)," and "aligned with the center of the lane (completion feedback)." This clear and closed-loop information delivery enhances the trust and operational certainty of novice drivers.

[0134] In some embodiments, augmented reality assist functions can be fully implemented through AR HUD (augmented reality head-up display), which projects key information such as virtual guide lines, distance scales, and vehicle outlines directly into the driver's field of vision, replacing the central control screen display.

[0135] In the above embodiments, when the user performs a steering operation or the vehicle enters a road segment containing feature tags, this application automatically triggers a real-scene assistance sub-mode, acquires real-time perception data of the vehicle's surrounding environment, generates targeted assistance strategies, and outputs driving operation guidance information, significantly enhancing the operational safety and driving confidence of novice drivers in complex road conditions. When drivers are navigating narrow roads, sharp bends, or other challenging road sections, this application provides real-time assistance guidance through images and / or voice, effectively avoiding operational misjudgments and potential dangers caused by novice drivers' poor environmental perception or emotional tension. This increases the novice driver steering success rate from 61% to 95%, reduces the average passage time by 42%, and effectively prevents vehicle accidents.

[0136] In addition, such as Figure 9 As shown, this application also provides a novice driver assistance system for implementing the above-described novice driver assistance method. The novice driver assistance system 100 includes a startup module 170, which is used to confirm whether to enter the novice driving mode. When the user triggers the novice driving mode start button, the system will automatically enter the novice driving mode and simultaneously load and start all modules of the novice driver assistance system 100.

[0137] In some embodiments, the novice driver assistance system 100 includes a data acquisition module 110, used to acquire vehicle control events, status data, and vehicle position data after entering the novice driving mode; and to further acquire environmental perception data around the vehicle after entering the real-scene assistance sub-mode. This module collects various control events such as vehicle speed, steering wheel angle, braking signal, automatic headlight status, and automatic wiper status, as well as vehicle status data such as fuel level or battery charge and tire pressure, by connecting to the vehicle's local CAN bus. Furthermore, the data acquisition module 110 includes sensors such as a positioning unit (e.g., GNSS / GPS), a forward-facing camera, millimeter-wave radar, and lidar, used to acquire high-precision location information and images, point clouds, and ranging data of the surrounding environment.

[0138] In some embodiments, the novice driver assistance system 100 includes an execution feedback module 120, which monitors the execution result of the corresponding execution device based on a control event and generates execution feedback information for the corresponding control event.

[0139] In some embodiments, the novice driver assistance system 100 includes a status feedback module 130, which is used to determine whether the status data meets the triggering conditions, and generate corresponding status feedback information based on the status data when the triggering conditions are met.

[0140] In some embodiments, the novice driver assistance system 100 includes a path planning module 140, which is used to obtain map data from a road difficulty database, generate navigation routes, and recommend routes in ascending order based on the number of feature tags corresponding to each navigation route; the path planning module 140 is also used to generate reminder information when the vehicle approaches a road segment containing feature tags.

[0141] In some embodiments, the novice driver assistance system 100 includes a real-scene assistance module 150, which is used to enter a real-scene assistance sub-mode when it detects that the user performs a steering operation or the vehicle enters a road segment containing feature labels, and generate an assistance strategy based on environmental perception data, and then generate driving operation guidance information according to the assistance strategy.

[0142] In some embodiments, the novice driver assistance system 100 includes an interaction module 160, used to interact with the user in a multimodal manner through a central control display screen and voice broadcast, based on execution feedback information, status feedback information, route recommendation data, risk warning information, and driving operation guidance information. The central control screen displays visual content such as recommended routes, virtual guide lines, vehicle status icons, and text prompts; the voice prompts output concise and timely auditory commands or status descriptions, ensuring that the user accurately receives key information without distraction, thereby enhancing the novice driver's perception of vehicle status and road environment and their operational confidence.

[0143] It should be noted that after activating the novice driving mode, the system will automatically load and coordinate the operation of all auxiliary function modules. Entering novice driving mode does not simply activate a single function; rather, it deeply integrates and coordinates the four major systems—data acquisition module 110, navigation, augmented reality vision assistance, and voice interaction—to form an organically unified assisted driving system. The modules share data in real time, act as triggers for each other, and collaboratively output feedback.

[0144] Furthermore, this application also provides a vehicle, which 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, it implements the aforementioned novice driver assistance method. Specifically, the processor is configured to: after detecting the activation of the novice driving mode, call the data acquisition module 110 to collect vehicle control events, status data, and location information; evaluate and sort navigation routes based on a road difficulty database; automatically trigger a real-scene assistance sub-mode when entering a difficult road section or when the user performs a steering operation, and generate environmental perception results by fusing camera, radar, and high-precision map data; and further display guidance information on the central control screen and / or AR HUD through the interaction module 160, while outputting structured voice prompts to achieve multimodal collaborative guidance.

[0145] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for assisting a novice driver, characterized by, The method is applied to a vehicle and comprises: determining whether to enter a novice driving mode; after entering the novice driving mode, acquiring control events and state data of the vehicle in real time; based on the control events, outputting execution feedback information corresponding to the control events to a user; determining whether the state data satisfies a trigger condition; when the state data satisfies the trigger condition, outputting corresponding state feedback information to the user.

2. The method of claim 1, wherein, The method of outputting execution feedback information corresponding to the control events to the user comprises: determining an execution device corresponding to the vehicle according to the control events; waiting for a first preset time length to acquire an execution result of the execution device; based on the execution result, outputting execution feedback information of the control events to the user.

3. The method of claim 1, wherein, The method of determining whether the state data satisfies the trigger condition comprises: recording a reference time when the vehicle starts or state feedback information is output to the user; determining whether a difference between a current time and the reference time is greater than or equal to a second preset time length; when the difference between the current time and the reference time is greater than or equal to the second preset time length, determining that the state data satisfies the trigger condition.

4. The method of claim 1, wherein, The method of determining whether the state data satisfies the trigger condition comprises: recording a value of the state data at this time as a historical value when the vehicle starts or state feedback information is output to the user; calculating a difference between a value of the current state data and the historical value; determining whether a ratio between the difference and the historical value is greater than or equal to a preset ratio; when the ratio between the difference and the historical value is greater than or equal to the preset ratio, determining that the state data satisfies the trigger condition.

5. The method of claim 1, wherein, The method of outputting corresponding state feedback information to the user comprises: reading a corresponding early warning threshold value according to a category of the state data; comparing a value of the current state data with the early warning threshold value to obtain a determination result; based on the current state data and the determination result, outputting corresponding state feedback information to the user.

6. The method of claim 1, wherein, The method further comprises: after entering the novice driving mode, acquiring vehicle position data in real time; based on a destination input by the user and the vehicle position data, acquiring corresponding map data from a road traffic difficulty database; based on the destination, the vehicle position data and the map data, generating a plurality of navigation paths; for each of the navigation paths, acquiring a corresponding feature label group from the road traffic difficulty database; calculating a number of feature labels contained in each of the feature label groups; in order from few to many of the number of feature labels, recommending the navigation paths to the user.

7. The method of claim 6, wherein, The method further comprises: acquiring a navigation path selected by the user; determining whether the navigation path contains the feature label; when the navigation path contains the feature label, obtaining a road segment containing the feature label from the navigation path; based on the vehicle position data, calculating distances from the vehicle to entrances of the road segments; determining whether the distances are less than or equal to a preset distance threshold value; when the distances are less than or equal to the distance threshold value, issuing a reminder to the user.

8. The method of claim 6, wherein, The method further comprises: determining whether a user performs a steering operation or whether the vehicle enters a road segment containing the feature label; when a user performs a steering operation or the vehicle enters a road segment containing the feature label, entering a real scene assistance sub-mode; after entering the real scene assistance sub-mode, obtaining environment perception data around the vehicle; based on the environment perception data, generating an assistance strategy; based on the assistance strategy, outputting driving operation guidance information to the user.

9. A novice driver assist system, characterised in that, The system for implementing the new driver assistance driving method of any one of claims 1-8, the system comprising: a starting module for confirming whether to enter a new driver driving mode; a data acquisition module for acquiring control event and state data of the vehicle after entering the new driver driving mode; an execution feedback module for generating execution feedback information corresponding to the control event based on the control event; a state feedback module for determining whether the state data satisfies a trigger condition and generating corresponding state feedback information according to the state data when the trigger condition is satisfied; an interaction module for interacting with the user according to the execution feedback information and the state feedback information.

10. A vehicle characterized by comprising: The vehicle comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the new driver assistance driving method of any one of claims 1-8 when executing the computer program.

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