Navigation control method of vehicle and cloud server

Abstract

The invention discloses a vehicle navigation control method and a cloud server. The method is applied to a cloud server, and comprises the following steps: acquiring positioning information of a target vehicle and navigation route information of the target vehicle; if based on the positioning information of the target vehicle and the navigation route information of the target vehicle, determining that a to-be-passed navigation road section or intersection within a preset distance from the target vehicle is a target road section or a target intersection, or determining that the target vehicle is currently positioned in the target road section in the navigation route, sending a first control instruction to the target vehicle; wherein the target road section or the target intersection is one of the following road sections or intersections of which the yaw probability reaches a first preset threshold value; the yaw probability reaches a first preset threshold value, and the familiarity degree of the vehicle account number corresponding to the target vehicle to the target road section or the target intersection is lower than a second preset threshold value; presetting a road section or an intersection according to a preset rule; and customizing a road section or an intersection according to the custom instruction.

Description

Technical Field

[0001] The present invention relates to the field of vehicle navigation, and in particular, to a navigation control method for a vehicle and a cloud server. Background Art

[0002] Currently, in a vehicle's driving assistance system, a Head-Up Display (HUD), as a technology that directly projects vehicle information and navigation prompts in the line of sight in front of the driver (user), has been widely used to improve driving safety and convenience.

[0003] In the related art, there are certain limitations in the design of the HUD system, especially in the integration and application of the Augmented Reality (AR) function. When the AR navigation function (such as AR navigation) is required to assist in accurately guiding the vehicle during vehicle driving, the driver needs to manually activate or switch to the AR navigation mode. The above operations not only increase the complexity of the AR navigation mode operation of the HUD, but more importantly, performing such operations during driving may cause the driver to temporarily lose focus on the road conditions, increasing the risk of traffic accidents. Therefore, there is still a technical problem of poor navigation effect of the cloud server controlling the vehicle.

[0004] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of the present invention provide a navigation control method for a vehicle and a cloud server, so as to at least solve the technical problem of poor navigation effect of the cloud server controlling the vehicle.

[0006] According to one aspect of an embodiment of the present invention, a navigation control method for a vehicle is provided. The method is applied to a cloud server and includes: obtaining the positioning information of a target vehicle and the navigation route information of the target vehicle; if it is determined, based on the positioning information of the target vehicle and the navigation route information of the target vehicle, that a navigation section or intersection within a preset distance from the target vehicle is a target section or target intersection, or it is determined that the target vehicle is currently located at a target section in the navigation route, then sending a first control instruction to the target vehicle, where the first control instruction is used to control the display state of an augmented reality display client to switch from a first state to a second state and / or output a prompt message, and the augmented reality display client is installed on the target vehicle; wherein, the target section or target intersection is one of the following sections or intersections: a section or intersection with a yaw probability reaching a first preset threshold; a section or intersection with a yaw probability reaching a first preset threshold and the familiarity of the in-vehicle account corresponding to the target vehicle with the target section or target intersection being lower than a second preset threshold; a section or intersection preset according to a preset rule; a section or intersection customized according to a custom instruction; the yaw probability is used to represent the degree of the probability of historical vehicles yawing when passing through the target section or target intersection; if the first state is the navigation closed state of the augmented reality display client, then the second state is the navigation opened state of the augmented reality display client; or, if the first state is the navigation normal display state of the augmented reality display client, then the second state is the navigation enhanced display state of the augmented reality display client.

[0007] Optionally, the method further includes: after determining that the display state of the augmented reality display client has switched to the second state, if it is determined that the driving data of the target vehicle meets a preset condition, then sending a second control instruction to the target vehicle, where the second control instruction is used to control the display state of the augmented reality display client to switch from the second state to the first state.

[0008] Optionally, the driving data meeting the preset condition includes at least one of the following: the driving duration of the target vehicle after entering the target section or passing through the target intersection is greater than a duration threshold; the driving distance of the target vehicle after entering the target section or passing through the target intersection is greater than a distance threshold; the driving position of the target vehicle after entering the target section or passing through the target intersection is outside a certain area range corresponding to the target section or target intersection.

[0009] Optionally, if it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if corresponding target road information is matched from a database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, and a first control instruction is sent to the target vehicle, where the corresponding target road information is the information of the target section or target intersection within a preset distance from the positioning information.

[0010] Optionally, if it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from a database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, and based on the positioning information of the target vehicle, a preset number of first control instructions corresponding to the preset number of target road information are periodically sent to the target vehicle, where the corresponding target road information is the information of the target section or target intersection within a preset distance from the positioning information, and the preset number is less than or equal to the number of at least one corresponding target road information.

[0011] Optionally, if it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from a database based on the navigation route information of the target vehicle, it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, and all the first control instructions corresponding to all the target road information are sent to the target vehicle, where the corresponding target road information is the information of the target section or target intersection within a preset distance from the positioning information.

[0012] Optionally, if it is determined that the target vehicle is currently located at a target section in the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if corresponding target road information is matched from a database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that the target vehicle is currently located at a target section in the navigation route, and a first control instruction is sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located.

[0013] Optionally, if it is determined that the target vehicle is currently located at a target section in the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that the target vehicle is currently located at a target section in the navigation route, and based on the positioning information of the target vehicle, a preset number of first control instructions corresponding to the preset number of target road information are periodically sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located, and the preset number is less than or equal to the number of at least one corresponding target road information.

[0014] Optionally, if it is determined that the target vehicle is currently located at a target section in the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle, it is determined that the target vehicle is currently located at a target section in the navigation route, and all the first control instructions corresponding to all the target road information are sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located.

[0015] Optionally, the step of sending a first control instruction to the target vehicle includes: sending a first control instruction to the target vehicle based on the familiarity of the in-vehicle account, where the familiarity is used to represent the familiarity degree of the in-vehicle account with the target section or the target intersection.

[0016] Optionally, the step of sending a first control instruction to the target vehicle based on the familiarity of the in-vehicle account includes: in response to the familiarity being lower than a second preset threshold, sending a first control instruction to the target vehicle; the method further includes: in response to the familiarity being higher than or equal to the second preset threshold, prohibiting sending a first control instruction to the target vehicle.

[0017] Optionally, the method further includes: determining the number of driving times of the target vehicle associated with the in-vehicle account at the target section or the target intersection; in response to the number of driving times being greater than a first number threshold and the number of yaw times of the target vehicle being less than a second number threshold when the target vehicle yaws on the target section, determining that the familiarity is higher than or equal to the second preset threshold; in response to the number of driving times being less than or equal to the first number threshold, and / or, the number of yaw times being greater than or equal to the second number threshold, determining that the familiarity is lower than the second preset threshold.

[0018] Optionally, obtain the positioning information of the target vehicle and the navigation route information of the target vehicle, including: in response to a target request of the target vehicle, obtain the positioning information of the target vehicle and the navigation route information of the target vehicle, where the target request is generated based on the navigation route information of the target vehicle and the in-vehicle account of the target vehicle.

[0019] According to another aspect of the embodiments of the present invention, there is also provided a cloud server, including: a memory storing an executable program; a processor for running the above program to implement the methods in various embodiments of the present invention.

[0020] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, the computer-readable storage medium including a stored executable program, wherein when the executable program runs, it controls the device where the computer-readable storage medium is located to execute the methods in various embodiments of the present invention.

[0021] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, including a computer program, where the computer program implements the methods in various embodiments of the present invention when executed by a processor.

[0022] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, including a non-volatile computer-readable storage medium, the non-volatile computer-readable storage medium storing a computer program, where the computer program implements the methods in various embodiments of the present invention when executed by a processor.

[0023] According to another aspect of the embodiments of the present invention, there is also provided a computer program, where the computer program implements the methods in various embodiments of the present invention when executed by a processor.

[0024] In the embodiments of the present invention, the positioning information of the target vehicle and the navigation route information can be obtained through the cloud server, and based on the navigation route information and the positioning information, determine that the navigation section or intersection within a preset distance from the target vehicle is the target section or target intersection, or if it is determined through the navigation route information and the positioning information that the target vehicle is currently located at a target section in the navigation route, a first control instruction can be sent to the target vehicle, and the target vehicle uses the first control instruction to switch the display state of the augmented reality display client from the first state to the second state, or can also output a corresponding prompt message to prompt the switch of the display state.

[0025] In the embodiments of the present invention, through the above method, precise assistance for the driver at some special target road sections or target intersections is achieved. By dynamically adjusting the display state of the augmented reality display client, the transmission efficiency of navigation information and driving safety are effectively improved. The above method is based on the positioning and navigation route information of the target vehicle, and can intelligently identify road sections and intersections with a relatively high probability of yaw or unfamiliar to the driver that the target vehicle is about to pass through, or the target vehicle is in the above special road sections, so as to timely turn on or strengthen the AR navigation display, or output targeted prompt information, ensuring that the driver can timely notice the key situations of the above special road sections or intersections, and reducing the occurrence of yaw events and dangerous events of the target vehicle. Through the above cloud server to analyze the conditions during the driving process of the target vehicle and perform intelligent control, not only the driving experience of the driver of the target vehicle is optimized, unnecessary information interference is avoided, but also the driving safety level in the environment of special road sections and intersections is significantly improved. The technical effect of improving the navigation effect of the cloud server controlling the vehicle is achieved, and the technical problem of poor navigation effect of the cloud server controlling the vehicle is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0027] Figure 1 is a flowchart of a navigation control method for a vehicle shown according to an embodiment of the present invention;

[0028] Figure 2 is a flowchart of a method for automatically turning on and off AR guidance in combination with a navigation route shown according to an embodiment of the present invention;

[0029] FIG. 3(a) is a schematic diagram of a complex intersection shown according to an embodiment of the present invention;

[0030] FIG. 3(b) is a schematic diagram of a three-way intersection shown according to an embodiment of the present invention;

[0031] FIG. 3(c) is a schematic diagram of a complex overpass shown according to an embodiment of the present invention;

[0032] FIG. 3(d) is a schematic diagram of an elevated fork shown according to an embodiment of the present invention;

[0033] Figure 4 is a structural block diagram of a navigation control device for a vehicle shown according to an embodiment of the present invention;

[0034] Figure 5 is a structural block diagram of an autonomous vehicle shown according to an embodiment of the present invention. Detailed implementation manners

[0035] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0036] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0037] According to an embodiment of the present invention, an embodiment of a navigation control method for a vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0038] An embodiment of the present application provides a navigation control method for a vehicle. This method can be used to provide an augmented reality navigation function for a target vehicle in a preset application scenario to guide the target vehicle to travel. The above-mentioned preset application scenarios can include the following scenarios in the vehicle field: commuting autonomous driving scenario, artificial intelligence (AI) chauffeuring scenario for household cars, automatic parking assist (APA) scenario (such as memory parking for self-owned parking spaces in the garage, intelligent parking for designated parking spaces in the parking lot, etc.), navigation guided pilot (NGP) scenario in urban or highway areas. In addition, the above-mentioned preset application scenarios can also include, but are not limited to: the autonomous driving scenario that requires the use of augmented reality navigation function for intelligent driving trucks or driverless trucks in the logistics transportation field, the autonomous driving scenario that requires the use of augmented reality navigation function for autonomous agricultural vehicles in the agricultural machinery field, the autonomous driving scenario that requires the use of augmented reality navigation function for unmanned aerial vehicles, and the autonomous driving scenario that requires the use of augmented reality navigation function for intelligent robots (such as cleaning robots, service robots, delivery robots, etc.).

[0039] When the above-mentioned preset application scenario is a scenario in other fields except the vehicle field, those skilled in the art should be able to understand that the vehicle in the above-mentioned vehicle navigation control method can be replaced with other objects (such as agricultural machinery, unmanned aerial vehicles, robots, etc.). Correspondingly, guiding the above-mentioned vehicle to travel using the augmented reality navigation function is replaced with navigating other objects and guiding other objects to move, fly or travel. On this basis, an embodiment of the present application takes the vehicle field as an example to exemplarily illustrate the specific implementation manner of the above-mentioned vehicle navigation control method.

[0040] Figure 1 is a flowchart of a navigation control method for a vehicle shown according to an embodiment of the present invention. As Figure 1 shown, this method is applied to the cloud server 30. The cloud server 30 interacts with the target vehicle 10 through the network 20. This method includes the following steps:

[0041] Step S102, obtain the positioning information of the target vehicle and the navigation route information of the target vehicle.

[0042] In the technical solution provided in step S102 of the present invention above, the target vehicle is a vehicle equipped with an augmented reality display client. The augmented reality display client can be an augmented reality head-up display (AR HUD) client, or can also be called an AR display client, which may include an application (APP) for providing an AR navigation (AR guidance) function, or can also be called an AR HUD client APP. The AR HUD client can run on the target vehicle and can be used to provide an AR navigation function to the target vehicle to guide its driving. Among them, AR HUD is an extension and upgrade of HUD technology, integrating augmented reality technology, which can superimpose driving information on the real-time scene of the road ahead, enabling the target vehicle to provide a more intuitive and contextual display. The target vehicle can be connected to the cloud server through the network. The target vehicle can be called the vehicle side, and the cloud server can be called the cloud side.

[0043] Optionally, the positioning information can be used to timely determine the section where the target vehicle is located and the approaching intersection, so as to decide whether to enhance the display or provide special prompt information. The positioning information can be the current geographical location information of the target vehicle, including longitude and latitude coordinates, direction, speed, etc., and can be obtained through the Global Positioning System (GPS), Beidou, etc.

[0044] Optionally, the navigation route information not only determines how the driver of the target vehicle travels from the starting point to the end point, but also involves multiple dimensions such as the road conditions along the way, driving behavior prediction, and time planning, which have a direct impact on driving safety, efficiency, and experience. The navigation route information can include the geographical location information of the road where the target vehicle is located, road type, road condition information, road signs and markings, environmental characteristics, and road geometric characteristics. Here is only an example for illustration and no specific limitation is made. For example, the navigation route information can include the coordinates, names, and addresses of the starting point and the end point (destination) in the navigation route, key points or points of interest (POIs) passed by, road type and road attributes, estimated driving time, driving instructions and suggestions, real-time data feedback, as well as regulations and restrictions, etc.

[0045] Optionally, the starting point and the ending point can usually be determined automatically by user input or the target vehicle based on other information (such as map markers, historical driving records, etc.). Waypoints can include, but are not limited to, gas stations, restaurants, scenic spots, hospitals, schools, etc. POIs have different types, each type serving specific needs (such as dining, medical, leisure, etc.), and it is also possible to predict which POIs are more likely to be visited based on user preferences and historical behavior, and highlight them in the navigation route. Road types can include highways, urban streets, rural roads, etc., and different road types affect driving speed, driving behavior, and possible obstacles. Road attributes can include road width, number of lanes, speed limit, whether it is a one-way street, whether it is a toll road, etc. Road surface conditions can include road conditions (flat, potholed, slippery, etc.), road construction, traffic signs, and markings. Driving instructions and suggestions can include specific driving operation instructions such as turning, going straight, changing lanes, etc., for example, turning at which intersection, when to merge, etc., to guide the driver to drive safely and efficiently. Real-time data can include real-time traffic data, such as real-time traffic flow, accident information, construction conditions, etc., for dynamically adjusting the navigation route to avoid congested or unsafe sections, and can also include real-time environmental data, such as weather forecast, visibility, road surface slipperiness, etc., and can also include user feedback, that is, it is possible to collect the driver's feedback on the route, such as reporting wrong routes, suggesting improvements, etc.

[0046] For example, road types can be highways, urban roads, rural roads, tunnels, and bridges, etc. Road condition information can include congestion on the road, accident information, construction areas, road closure conditions, etc. Road signs and markings can include traffic lights, stop signs, speed limit signs, road centerlines, and lane lines, etc. Environmental characteristics can include weather conditions, light conditions, and surrounding obstacles on the road. Road geometric characteristics can include the slope, curvature, intersections, and roundabouts of the road.

[0047] It should be noted that the specific information included in the above navigation route information is only for illustrative purposes and is not specifically limited here. As long as it can be used to reflect the real-time driving state of the target vehicle on the road and is used to determine whether the AR navigation function is required to assist driving on the current road where the target vehicle is located, it is within the protection scope of the embodiments of the present invention.

[0048] In this embodiment, if it is necessary to control the AR HUD in the target vehicle to turn on or off the AR navigation to guide the target vehicle to drive, the target vehicle can detect its own positioning information and the navigation route information of this driving, and transmit the positioning information and the navigation route information to the cloud server through the network. That is, the cloud server can obtain the positioning information and the navigation route information of the target vehicle.

[0049] Optionally, corresponding detection devices can be deployed for the target vehicle in advance and connected to the AR HUD client. During the driving process of the target vehicle, the navigation route information and positioning information are detected in real time through the above detection devices, and then the navigation route information and positioning information are transmitted to the cloud server through the network.

[0050] Optionally, high-precision map data, including information such as road networks, POIs, and traffic rules, can be accessed in the target vehicle. If the user needs to drive the target vehicle according to the navigation route, the destination, waypoints, and POI points to be reached can be input. Based on the above information such as the starting point and destination, as well as the real-time or predicted traffic conditions, a route algorithm (such as the A* algorithm) can be applied to calculate the shortest, fastest, or congestion-avoiding navigation route. At the same time, the navigation route planning can also be adjusted according to the user's historical driving records and preference settings (such as whether to prefer highways, whether to bypass traffic congestion, etc.).

[0051] For example, if the navigation route information includes geographical location information, the precise geographical location information of locations such as the starting point, destination, and waypoints can be captured in real time using the GPS or Beidou positioning system. If the road information includes road types, road signs and markings, or environmental characteristics, the road signs and markings of the road where the target vehicle is currently located can be recognized in real time using the cameras deployed on the target vehicle, and the road environment can also be monitored using radar. Combining with the high-precision map data, the above road information can be recognized.

[0052] It should be noted that the above methods for obtaining navigation route information and the deployed detection devices are only for illustrative purposes and are not specifically limited here. Corresponding settings can be made according to the actual road information to be collected.

[0053] Step S104: If it is determined that the navigation section or intersection to be passed within a preset distance from the target vehicle is the target section or target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, or if it is determined that the target vehicle is currently located at the target section in the navigation route, a first control instruction is sent to the target vehicle.

[0054] In the technical solution provided in step S104 of the present invention above, the first control instruction is used to control the display state of the augmented reality display client to switch from the first state to the second state and / or output a prompt message, and the augmented reality display client is installed on the target vehicle; wherein, the target section or target intersection is one of the following sections or intersections: a section or intersection with a yaw probability reaching a first preset threshold; a section or intersection with a yaw probability reaching the first preset threshold and the familiarity of the in-vehicle account corresponding to the target vehicle with the target section or target intersection being lower than a second preset threshold; a section or intersection preset according to a preset rule; a section or intersection customized according to a custom instruction; the yaw probability is used to represent the degree of the probability of historical vehicles yawing when passing through the target section or target intersection; if the first state is the navigation off state of the augmented reality display client, then the second state is the navigation on state of the augmented reality display client; or, if the first state is the navigation normal display state of the augmented reality display client, then the second state is the navigation enhanced display state of the augmented reality display client. The first control instruction can also be called the HUD switching instruction.

[0055] Optionally, the preset distance can reflect the range for early judgment and prompt to trigger the AR HUD client to perform AR navigation guidance. The setting of the preset distance can comprehensively consider factors such as vehicle speed, road type, and driver reaction time to ensure that when the target vehicle approaches the target intersection, a warning and guidance can be given in a timely manner, while avoiding premature or late prompts, thereby effectively reducing the yaw risk and improving driving safety and driving experience. The preset distance can be a dynamically adjusted value, and can be adjusted in real time according to the actual situation of the vehicle driving, such as the speed limit of the current section, whether the vehicle has decelerated or accelerated, etc., to achieve the required prompt effect. For example, when the vehicle is driving at a high speed, the preset distance may be set farther so that the driver has enough time to make a decision; while in scenarios such as urban driving that require low-speed driving, the preset distance can be appropriately shortened to reduce unnecessary prompts to the driver and improve the efficiency and practical value of information output. It should be noted that the conditions considered for setting the preset distance above are only for illustrative purposes and are not specifically limited here.

[0056] Optionally, if the first state is the navigation closed state, when the HUD changes from closed to on, the HUD is not actually in the working mode. That is to say, the HUD itself is closed and does not provide any visual information to the driver. The above first state is formed because the driver manually closed the HUD before, or it is default to be closed in some situations to save energy and avoid visual interference. Different from the above situation where the HUD changes from closed to on, the HUD can always be in the on state, but the content displayed by the HUD does not include navigation information. That is, at this time, the driver is using other functions of the HUD, such as displaying vehicle status, entertainment information, etc.; or automatically adjusting the display content according to the driver's preference and the current driving environment (such as low visibility conditions) to avoid unnecessary information from distracting the driver's attention. That is, when the HUD is always in the on state, the navigation interface is not displayed until it switches to the second state and starts to display the navigation interface. At this time, the second state is the navigation on state, that is, the second state means that the HUD is activated and starts to display the navigation interface.

[0057] Optionally, if the first state is the navigation normal display state, in the navigation normal display state, the augmented reality display client provides navigation information to the driver in a more gentle and conventional way. That is, the navigation information provided in the navigation normal display state is ordinary navigation information. The first state is applicable to the situation where the driver is familiar with the current road section or the road conditions are simple. The display of information pays more attention to reducing the visual burden and keeping the driver's continuous attention on the road.

[0058] For example, in the first state, the color, brightness, and contrast of the navigation information display elements can be adjusted to ensure that the information is clearly visible under different lighting conditions, but it will not be too dazzling or distracting to the driver. In some cases, such as approaching a turning point or having an important road sign, the navigation indicator can be slightly flashed to remind the driver, but the above flashing effect is usually gentle and will not cause visual interference. In places that require extra attention, such as speed limit areas, school areas, etc., short reminder messages can be displayed, but the above reminder messages usually do not occupy much space to avoid affecting the driver's sight of the road. Simple animation effects can also be used to represent navigation instructions, such as the smooth rotation of the turning arrow, to make the instructions more intuitive, but the complexity of the animation will not be too high to avoid distraction. In the normal display state, information unrelated to the current driving can be filtered out, such as only retaining necessary information such as the navigation route and vehicle speed to reduce the driver's information processing burden. In the normal display state, a small part of the front windshield can also be used to display information, thereby reducing the interference to the driving vision.

[0059] Optionally, if the target vehicle enters a more complex section or intersection with a higher yaw risk, or the section where the target vehicle is currently traveling is the target section, the display state of the HUD can be switched to the second state (navigation enhancement display state). The purpose of the second state is to attract and focus the driver's attention through more prominent and dynamic visual cues, ensuring that key navigation information can be provided to the driver in a timely manner. That is to say, the navigation information provided in the navigation enhancement display state is AR navigation information, which can also be referred to as detailed navigation information or augmented reality information.

[0060] For example, in the second state, the color saturation, brightness, and contrast of the information can be significantly increased, making the navigation information clearly visible and eye-catching under various lighting conditions. More frequent and obvious flashing effects, as well as more vivid animation effects, such as a highlighted and flashing turning arrow, a dynamically simulated route inside a roundabout, etc., can be used to enhance the driver's reception of the information. A tooltip containing detailed information, such as the intersection name, exit direction, lane change suggestion, etc., can also be displayed to help the driver make the right decision. The information can be further filtered to only retain the content closely related to the current driving decision, such as specific navigation instructions at an intersection, and the above key information may be magnified or highlighted. For a more complex target section or target intersection, the display range of the HUD is automatically expanded from a small area to a larger area to provide a more comprehensive navigation perspective, especially in scenarios such as complex roundabouts or overpasses where the driver needs to observe all around. The above adjustment of the HUD display range can also be triggered according to the user's needs. It should be noted that the adjustment of the size of the HUD display range here needs to ensure the safety of the driver driving the target vehicle and is not an unlimited adjustment to avoid blocking the driver's line of sight and causing potential safety hazards.

[0061] It should be noted that the above display of navigation information in the first state and the second state is only for illustrative purposes and is not specifically limited here. The difference between the first state and the second state reflects the intelligent strategy of the augmented reality display client to adjust the presentation method of navigation information to meet the driver's needs in different driving scenarios. This flexibility not only helps to improve the driving experience but also provides crucial safety support at the target section and target intersection. By dynamically adjusting the displayed navigation information, appropriate navigation assistance can be provided without affecting the driver's attention to the road.

[0062] Optionally, the prompt information is the information output by the augmented reality display client to remind the driver when a target road section or intersection is detected. The prompt information can be used to prompt the display state to be switched from the first state to the second state, or to prompt the driver that the current road section is the target road section, or the intersection that the vehicle is about to pass through is the target intersection. Since the above-mentioned target intersection or target road section is prone to errors, through the above prompt information, the driver can be prompted to concentrate on driving the target vehicle in advance, or to prompt whether the driver is willing to turn on the AR HUD to provide clearer navigation. The above prompt information can be visual, for example, highlighting key routes or intersections in the AR display; it can also be auditory, such as a voice warning; it can also be text, for example, displaying text prompts on the interface of the augmented reality display client. According to the characteristics of the target road section or intersection, as well as the current state of the driver, select an appropriate prompt method to ensure the effective transmission of the prompt information.

[0063] It should be noted that the content and prompt method of the above prompt information are only for illustrative purposes and are not specifically limited here. As long as the prompt information sent to the driver when the road section where the target vehicle is located is the target road section, or the intersection that the target vehicle is about to reach is the target intersection, it is within the protection scope of the embodiments of the present invention.

[0064] For example, when approaching a turning point, text can be displayed and a voice prompt can be given, such as "Turn right, 200 meters from the target", or AR technology can be used at a complex intersection to superimpose arrow indications on the actual road to guide the driver to turn accurately. When the target vehicle needs to change lanes from the current lane to another lane to enter a ramp or exit, a prompt can be given, such as "Please prepare to change lanes to the left lane", or AR can be used to display lane lines and lane change signals to help the driver complete the lane change smoothly and safely. When entering a speed limit area or a school area, "Speed limit 30 km / h ahead" can be displayed, or the speed limit sign can be highlighted with a dynamic visual effect to remind the driver to slow down.

[0065] It should be noted that the prompt method and prompt content of the above prompt information are only for illustrative purposes and are not specifically limited here.

[0066] Optionally, the yaw probability refers to the likelihood of a vehicle yawing at a specific road section or intersection in history. It can be calculated based on the historical driving data of a large number of users (big data, cloud data). By analyzing the driving behaviors of multiple users on the same road section or route, the yaw situation at this road section or intersection can be determined. That is to say, the yaw probability can be determined through big data statistical methods. It can also be calculated based on the in-vehicle data of the target vehicle (the driving records of a single vehicle). It can also be calculated based on known specific conditions that may cause yaw. This method does not require a large amount of historical driving data but is determined based on existing experience or known traffic rules. That is to say, the yaw probability can be obtained by screening through preset rules. Among them, the preset rules can include road complexity, driver experience, real-time traffic conditions, and weather conditions. By analyzing the yaw probability, it is possible to identify which road sections or intersections require special attention and assistance, so as to automatically adjust the display status of the augmented reality display client when approaching the above-mentioned road sections or intersections, provide more detailed navigation information and prompts, and help the driver make correct driving decisions. The setting of the yaw probability helps to reduce unnecessary information output, avoid information overload, and at the same time ensure sufficient guidance at high-risk locations.

[0067] Optionally, an intersection can refer to the place where roads intersect (such as where a road intersects with a railway, a highway intersects with a highway, an urban road intersects with a highway, etc.). The target intersection can be an intersection with a high yaw probability, or an intersection with a high yaw probability and a low familiarity of the driver of the target vehicle, or an intersection customized by the driver of the target vehicle by executing corresponding custom instructions. That is to say, the target intersection can be any intersection where a driver is prone to yaw or make wrong driving decisions, including but not limited to fork intersections, crossroads, complex intersections, complex overpasses, elevated fork intersections, highway entrances and exits, three-way intersections, around roundabouts, etc. The above-mentioned target intersections become potential yaw points due to the complexity of the structure, the density of information, or the unfamiliarity of the driver. By analyzing historical data (such as comprehensively analyzing the yaw situations of multiple drivers driving to this intersection in historical periods) and driver behaviors (the operations performed by the driver when driving to the target intersection), it is possible to identify which intersections require special attention. In the embodiments of the present invention, the target intersection refers to an intersection that is identified as having potential high yaw risk, complexity, and unfamiliarity based on historical data, driver behaviors, and preset rules.

[0068] For example, at a fork in the road, the road splits into two or more roads in different directions at a certain point, where the driver needs to make a decision whether to turn or go straight. Target intersections are identified based on the complexity of the fork and the historical deviation probability. Forks within a preset distance from the target vehicle's current position can be analyzed to determine whether they are prone to deviation. For example, a poorly marked fork with multiple exits, where many drivers often take the wrong path, can be identified as a target intersection. At an intersection, two or more roads intersect at right angles, forming a four-way intersection. Some complex intersections may have only one left-turn lane, and the second straight-ahead lane is followed by a road section where left turns are prohibited. In such cases, if the driver misses the left turn, they will be unable to return to the intended navigation route. Whether an intersection is a target intersection can be determined based on the deviation probability and preset rules. For example, at a certain intersection, historical data shows that the yaw rate of left-turning vehicles is high and drivers are less familiar with the intersection. This intersection can be marked as a target intersection.

[0069] For another example, complex intersections include, but are not limited to, the aforementioned forks and crossroads, as well as those with a large number of lanes, complex markings, multiple forks, or special traffic rules. At complex intersections, drivers may find it difficult to quickly determine the correct direction of travel or lane changes, which can lead to yaw. Complex intersections can be pre-set as target intersections based on preset rules, such as intersections where the number of lanes exceeds a certain threshold, or where the complexity of ground markings exceeds a preset standard. Complex intersections within a preset distance from the target vehicle will be identified to provide enhanced navigation prompts. Complex overpasses have problems such as structural complexity and upper and lower obscurations. Due to their structural complexity, complex overpasses typically contain multi-layered, multi-directional ramps and main bridges, forming a complex three-dimensional spatial structure. The aforementioned complexity makes it difficult for drivers to understand the entire layout of the overpass in a short period of time, especially in conditions of heavy traffic and high speeds, where the driver's attention is distracted and it is difficult to accurately determine the correct direction of travel. Regarding upper and lower obstructions, the obstruction of the upper road on a complex overpass can affect the driver's visual identification of exits on the lower or surrounding roads. This obstruction is particularly pronounced during changing lighting conditions or in poor weather, increasing the risk of yaw. In other words, due to the complex structure of a complex overpass, the interplay of upper and lower obstructions makes it difficult for drivers to identify the correct route, potentially confusing even experienced drivers. Therefore, complex overpasses can be marked as target intersections.

[0070] As an alternative example, the specific height and structure of elevated intersections may limit a driver's visibility. Especially when a target vehicle approaches an elevated intersection, the driver may not be able to see the exit or road signs ahead, making it more difficult to determine the exit and travel direction. In other words, due to the height and structure of elevated intersections, drivers can easily be confused when determining exits and travel directions, especially in unfamiliar areas. Therefore, complex interchanges can be marked as target intersections. Highway entrances and exits typically have heavy traffic, especially during peak hours, when vehicles are densely packed. Drivers also need to consider the dynamics of surrounding vehicles when making decisions, increasing operational complexity and risk. In other words, highway entrances and exits experience heavy traffic and require quick decisions on whether to turn or exit. Drivers can easily miss critical intersections due to delayed reaction while driving at high speeds. Therefore, highway entrances and exits can be marked as target intersections. Compared to two-way intersections, three-way intersections offer more route options, requiring drivers to choose from three or more roads, increasing the difficulty of decision-making. At a three-way intersection, if there are no clear and unambiguous road signs, drivers may hesitate due to uncertainty and miss the right time to turn, resulting in off-course or dangerous driving. Therefore, a three-way intersection can be marked as a target intersection.

[0071] As another optional example, a roundabout, also known as a turntable or circular intersection, is a traffic intersection design that aims to guide traffic to converge and diverge in a low-speed, continuous manner through a continuous circular road to improve traffic efficiency and safety. However, the traffic environment around the roundabout is complex, and the superposition of multiple factors may confuse drivers when passing through, especially for drivers who are not familiar with the roundabout. That is, if key information such as the number of lanes, exit locations, markings, traffic lights, etc. around the roundabout is not clear enough, users may find it difficult to quickly determine the next driving action while driving. Therefore, the area around the roundabout can be marked as a target intersection.

[0072] It should be noted that the above target intersections are only examples and are not specifically limited here. As long as it can ensure driving safety and requires intelligent automatic triggering of AR guidance by the ARHUD client, the intersection is within the scope of protection of the embodiments of the present invention.

[0073] Optionally, the target road section can be a road section with a relatively high yaw probability, or a road section with a relatively high yaw probability and a relatively low familiarity of the driver of the target vehicle, or a road section customized by the driver of the target vehicle by executing corresponding custom instructions. The target road section can refer to a road section determined to require enhanced navigation prompts based on vehicle positioning and navigation route information. The above-mentioned target road sections can include long solid line sections on highways, complex road combinations in cities, road sections with special traffic rules or high-risk driving behaviors, and fork sections. It is judged whether it is a target road section according to preset rules or the driver's familiarity with the road section to provide necessary navigation assistance.

[0074] For example, in a straight section of a highway, if there is a solid line area several kilometers long ahead, then this road section can be a long solid line section on the highway, and one or more important exits are included within the solid line area. For instance, on the right side of a section of highway, there is an exit leading to the urban area, but there is a 2-kilometer-long solid line area before that. The driver must complete the lane change to the right lane before entering the solid line area, otherwise they will miss the exit. In the above situation, the driver can be reminded to prepare for the lane change in the dotted line area (usually ranging from several hundred meters to several kilometers before the solid line) in advance to avoid missing the exit. The complexity of the long solid line section lies in the difficulty and time sensitivity of the lane change operation for the driver before entering the solid line area. If the lane change operation is improper or too late, the driver will miss the exit and have to take a detour, increasing the driving cost and potential safety risks. The above-mentioned long solid line section on the highway can be marked as a target road section.

[0075] Taking another example, in the city, if there is a section of road composed of multiple intersections closely connected, including various road elements such as straight, turning, and roundabouts, and traffic lights and traffic signs are dense, the above-mentioned complex road combination in the city can be marked as a target road section. The complexity of the complex road combination in the city lies in the diversity of the roads, the density of traffic signals, and the rapid and continuous decisions that the driver needs to make. The above-mentioned road sections usually have a relatively high traffic flow. The driver needs to frequently change lanes while paying attention to traffic signals and signs to avoid violations and traffic accidents. The above-mentioned complex road combination in the city on the highway can be marked as a target road section. In the city, if the driver needs to pass through a fork section of a multi-directional roundabout, for example, a four-way roundabout, there are lane bifurcations inside the roundabout, the number and position of lanes in each direction are different, and the traffic rules inside the roundabout may be more complex than those at ordinary intersections. The above-mentioned fork section can be marked as a target road section.

[0076] As an optional example, in some urban or rural roads, there may be special traffic rules. For example, one-way streets during specific time periods, no-go zones for specific vehicle types, etc. In addition, some sections of the road may be areas with high-risk driving behaviors due to road design (such as sharp turns, blind spots), weather conditions (such as rain, snow, fog), or traffic conditions (such as construction, congestion). For example, an urban road becomes a one-way street between 7 am and 9 am, and there are dense pedestrians and bicycles on both sides of the road. Drivers need to pay special attention to the traffic rules and pedestrian safety during this specific period. The complexity of sections with special traffic rules lies in that drivers need to understand and abide by the above rules, otherwise they may face fines or other legal consequences. The complexity of sections with high-risk driving behaviors lies in that drivers need to be highly vigilant to cope with potential dangers, such as avoiding pedestrian collisions and controlling the stability of the target vehicle on slippery roads. The above sections with special traffic rules or high-risk driving behaviors can be marked as target sections.

[0077] It should be noted that the above target sections are only for illustrative purposes and are not specifically limited here. As long as it can ensure driving safety and requires intelligent automatic triggering of AR guidance for the AR HUD client, it is within the protection scope of the embodiments of the present invention.

[0078] Optionally, the length of the section can be determined based on different strategies. For example, the section length can be calculated starting from the intersection position, or it can be calculated starting from a certain distance from the intersection position, depending on the characteristics of the section and the navigation target.

[0079] Optionally, the strategy of calculating the section length starting from the intersection position is applicable to sections starting from the intersection with specific complexity or risk. For example, a roundabout, a complex intersection, or a high-traffic highway exit. The above sections usually require drivers to make complex decisions, such as correct lane selection and timely lane changes. Calculating the section length starting from the starting point of the intersection can ensure that necessary navigation information and suggestions are provided at the initial stage when the driver enters the section, which helps the driver quickly adapt to the section environment and make accurate driving decisions. For example, when approaching a roundabout, the section length may be calculated starting from the entrance of the roundabout, and based on this, lane suggestions, exit directions, etc. are provided to ensure that the driver can pass through the roundabout smoothly and choose the correct exit direction.

[0080] Optionally, for the strategy of calculating the length of a road segment starting from a certain distance from the intersection position, it is applicable to road segments that have started to change or have potential complexity before approaching the intersection. For example, on a highway, an exit may be located several hundred meters to several kilometers before the start of the solid line area. The target vehicle needs to complete a lane change before entering the solid line area, otherwise it will miss the exit. In the above situation, the length of the road segment can be calculated starting from a position a certain distance from the intersection (such as the dotted line part before the solid line area), so as to provide lane change suggestions and exit direction information to the driver in advance, ensuring that the driver has enough time and space to react and avoid missing the exit. For example, if there is a highway exit 2 kilometers ahead, the length of the road segment can be calculated starting from a position 2 kilometers from the exit, and based on this, lane change suggestions and exit direction information can be provided to ensure that the driver completes the necessary lane change before entering the solid line area.

[0081] It should be noted that the above strategy for determining the length of the road segment is only for illustrative purposes and is not specifically limited here. It can be determined based on the characteristics of the road segment (such as complexity, risk) and the needs of the driver (such as early decision-making, quick adaptation).

[0082] In this embodiment, after the cloud server obtains the navigation route information and positioning information of the target vehicle, the cloud server can, based on the navigation route information and positioning information, determine whether the navigation road segment or intersection to be passed within the preset distance of the target vehicle is the target road segment or target intersection, or can determine whether the road segment where the target vehicle is currently located is the target road segment.

[0083] Optionally, if it is determined based on the positioning information and navigation route information of the target vehicle that the navigation road segment or intersection to be passed within the preset distance of the target vehicle is the target road segment or target intersection, or if it is determined that the target vehicle is currently located in the target road segment on the navigation route, a corresponding first control instruction can be generated and sent to the target vehicle through the network. Based on the first control instruction, the target vehicle switches the display state of the AR HUD from the first state to the second state, and can also output corresponding prompt information.

[0084] Optionally, the dynamic display state switching of the AR HUD is determined according to the road segment characteristics and driving scenarios where the vehicle is located, aiming to provide appropriate driving assistance.

[0085] Optionally, when the target vehicle approaches the target road section or the target intersection, the cloud server can automatically determine the distance between the target vehicle and the upcoming target road section or target intersection based on the real-time positioning information and navigation route information of the target vehicle. If the distance is less than a preset threshold, it is regarded that the target vehicle is about to enter the target road section or reach the target intersection. Among them, the selection of the preset distance needs to comprehensively consider the following factors: the reaction time of the driver, the complexity of the road section, the predictability of traffic signals, etc. Regarding the reaction time of the driver, the preset distance should be sufficient for the driver to have enough time to understand and make appropriate driving decisions. For example, it may take 10 to 15 seconds for the driver to complete a lane change action from receiving the information. Therefore, the preset distance should at least cover the driving distance within the above reaction time. Regarding the complexity of the road section, the more complex the road section is, such as multi-lane, multi-exit roundabouts, merge points on highways, etc., the longer the preset distance should be to give the driver more preparation time. For example, in front of a roundabout with multiple exits, the preset distance may be set to 1 kilometer to ensure that the driver has enough time to understand and plan the correct lane and exit. Regarding the predictability of traffic signals, in road sections where traffic signals are predictable (such as traffic lights), the preset distance may be shorter, while in road sections where traffic signals are difficult to predict (such as busy intersections), the preset distance should be set longer.

[0086] Optionally, in the case where the target vehicle approaches the target road section or the target intersection, the display state of the AR HUD can be switched from the first state to the second state through the first control instruction issued by the cloud server.

[0087] Optionally, when the target vehicle is currently passing through or located in a target road section that requires special attention (such as a one-way street, a construction area, a road section with special traffic rules, etc.), the display state of the AR HUD can also be switched from the first state to the second state through the first control instruction to provide enhanced navigation information. In the above cases, not only may the significance of the information be increased, but specific guidance will also be provided according to the characteristics of the road section, such as reminders of special traffic rules, warnings of high-risk driving behaviors, and provision of detailed road conditions.

[0088] In the embodiments of the present application, whether the target vehicle is about to enter the target road section or intersection, or is currently located in the target road section, the dynamic display state switching strategy of the AR HUD is to provide more abundant, prominent and direct navigation information for the driver at critical moments, assist the driver in making correct driving decisions, thereby improving driving safety, reducing the risk of yaw and enhancing the overall driving experience. Through the above real-time judgment and the method of issuing the first control instruction, the advantages of AR technology are fully utilized to seamlessly integrate virtual information into the real driving environment, realizing intelligent driving assistance. Through the above analysis, the display state switching of the AR HUD is not only based on the dynamic evaluation of the preset distance, but also takes into account the characteristics of the current road section and the needs of the driver, which is a highly context-aware and personalized navigation assistance mechanism. It can provide timely and effective information guidance for the driver in complex or high-risk driving environments.

[0089] In practical applications, the implementation of the above intelligent AR HUD display state switching strategy can rely on a precise target vehicle positioning system, real-time traffic information update, an intelligent driving behavior prediction model, and an efficient AR navigation information rendering technology. Through the combination of the above technologies, it is possible to provide a suitable driving assistance experience on the premise of ensuring the safety of the driver, and help the driver drive more safely in various complex driving environments.

[0090] In the above steps S102 to S104 of the present application, the positioning information and navigation route information of the target vehicle can be obtained through the cloud server, and based on the navigation route information and the positioning information, the navigation section or intersection within a preset distance from the target vehicle to be passed is determined as the target section or target intersection. Or if it is determined through the navigation route information and the positioning information that the target vehicle is currently located at the target section in the navigation route, a first control instruction can be sent to the target vehicle, and the target vehicle uses the first control instruction to switch the display state of the augmented reality display client from the first state to the second state, or can also output corresponding prompt information to prompt the switching of the display state. In this embodiment, by analyzing the conditions during the driving process of the target vehicle through the above cloud server and performing intelligent control, not only the driving experience of the driver of the target vehicle is optimized, unnecessary information interference is avoided, but also the driving safety level in the environment of special sections and intersections is significantly improved. The above method is based on the positioning and navigation route information of the target vehicle, and can intelligently identify sections and intersections with a relatively high probability of deviation or unfamiliar to the driver that the target vehicle is about to pass, or the target vehicle is in the above special sections, so as to timely turn on or strengthen the AR navigation display, or output targeted prompt information to ensure that the driver can timely notice the key situations of the above special sections or intersections, and reduce the occurrence of target vehicle deviation events and dangerous events. The technical effect of improving the navigation effect of the cloud server controlling the vehicle is achieved, and the technical problem of poor navigation effect of the cloud server controlling the vehicle is solved.

[0091] Next, in this embodiment, after the display state of the augmented reality display client is switched to the second state, the process of further determining under what circumstances the display state is switched back to the first state will be further described.

[0092] As an optional implementation manner, the method further includes: after determining that the display state of the augmented reality display client is switched to the second state, if it is determined that the driving data of the target vehicle meets the preset conditions, a second control instruction is sent to the target vehicle, where the second control instruction is used to control the display state of the augmented reality display client to be switched from the second state to the first state. The second control instruction can also be referred to as a HUD switching instruction.

[0093] In this embodiment, after the display state of the augmented reality display client is switched from the first state to the second state by the first control instruction, if it is determined that the driving data of the target vehicle meets the preset conditions, the cloud server may send a second control instruction to the target vehicle, and the target vehicle may, based on the received second control instruction, switch the display state of the augmented reality display client from the second state to the first state. Among them, the second control instruction can be used to control the display state of the augmented reality display client to switch from the second state to the first state. The first state means that the AR display client is in an active or enhanced display state, that is, during the driving of the target vehicle, navigation, road conditions, safety prompts and other information are provided in the driver's field of vision through augmented reality technology to assist the driver in better understanding the surrounding environment and making safer driving decisions. The second state means that the AR display client is switched to a non-enhanced display state, which may be because augmented reality information is not required for the current road section (such as a straight road section), or to reduce the driver's visual interference. For example, the driver is performing an operation that requires high concentration. In the second state, the AR display client may only provide basic navigation instructions or completely turn off the augmented reality information display.

[0094] Optionally, the preset condition is the key basis for determining whether to switch the display state of the AR display client from the second state back to the first state. The preset conditions may include, but are not limited to: road information changes, driver attention state, traffic condition changes, driver requests, and target vehicle state changes.

[0095] For example, regarding road information changes, when the target vehicle enters a complex road section (such as a roundabout or a fork) from a non-complex road section (such as a straight road), the AR display client can be triggered to switch from the second state to the first state based on the road information changes to provide additional navigation information to assist the driver. Regarding the driver's attention state, if the target vehicle (vehicle end) or the cloud server (cloud) detects that the driver's attention has returned to a sufficient level, for example, the driver is no longer performing a task that requires high concentration, the state switch can be triggered to re-enable the AR display function and provide necessary navigation information to the driver. Regarding traffic condition changes, when the traffic condition changes from congestion to smooth, or from night driving to day driving, the state of the AR display client can be adjusted according to the above changes to adapt to the new driving environment. Regarding the driver-triggered request, the driver can actively request to turn on the AR display function through voice commands, gesture recognition or other interaction methods, and in response to the driver's request, switch the display state from the second state to the first state. Regarding target vehicle state changes, when the state of the target vehicle (such as battery power, fuel) reaches a certain preset threshold, it can be considered that the driver needs more information to make a decision. Therefore, the state of the AR display client is switched back to the first state to provide more detailed state information of the target vehicle.

[0096] It should be noted that the content included in the above preset conditions is only for illustrative purposes, and there is no specific limitation here. As long as it can be used to measure the conditions for the augmented reality display client to switch from the second state to the first state, it is within the protection scope of the embodiments of the present invention.

[0097] Optionally, this embodiment refines the display state management strategy of the augmented reality display client under different driving conditions to ensure that the driver obtains augmented reality navigation information when needed, and at the same time reduces information interference when not needed, so as to improve driving safety and driving experience.

[0098] Optionally, the purpose of implementing the above switching logic is to reduce unnecessary information interference while ensuring the driver's information needs, and ensure driving safety.

[0099] Optionally, from the perspective of safety, in an environment where the driver needs to concentrate highly or the AR display information may cause interference, the AR display client can be switched to the second state to avoid the driver being distracted by receiving too much information and reduce the potential risk of traffic accidents.

[0100] Optionally, from the perspective of efficiency, in sections or situations where the driver needs additional information assistance (such as complex intersections, bad weather), the AR display client is switched to the first state to provide augmented reality information to help the driver make driving decisions more quickly and accurately, improving navigation efficiency and driving experience.

[0101] Optionally, from the perspective of personalization, through the comprehensive judgment of the cloud and the vehicle terminal, the display state of the AR display client can be dynamically adjusted based on the driver's driving habits, preferences, and current driving conditions to achieve personalized driving assistance and meet the needs of different drivers.

[0102] In the embodiments of the present invention, after the display state of the augmented reality display client is switched to the second state, if it is determined through the cloud server that the driving data of the target vehicle meets the preset conditions, a second control instruction can be sent to the target vehicle, and through the second control instruction, the display state can be switched back from the second state to the first state. Through the above method, it reflects the careful consideration and intelligent management in terms of improving driving safety and driving experience. By dynamically adjusting the display of navigation information in the AR display client, it ensures that the driver obtains necessary navigation support under complex road conditions, and at the same time avoids information overload in simple or sensitive situations, improving the overall efficiency and comfort of driving.

[0103] The following further describes the preset conditions satisfied by the driving data in this embodiment.

[0104] As an alternative embodiment, the driving data meeting the preset conditions includes at least one of the following: the driving duration of the target vehicle after entering the target section or passing through the target intersection is greater than the duration threshold, the driving distance of the target vehicle after entering the target section or passing through the target intersection is greater than the distance threshold, and the driving position of the target vehicle after entering the target section or passing through the target intersection is outside a certain area range corresponding to the target section or the target intersection.

[0105] In this embodiment, the driving data is used to analyze and understand the driving state of the target vehicle and the interaction between the target vehicle and the surrounding environment. The driving data includes at least one of the following: driving duration, driving distance, and driving position. The above driving data together constitutes the basis for perceiving the driving situation. The driving duration reflects the length of time the target vehicle travels in a specific section or driving situation. The driving distance refers to the physical length that the target vehicle travels in a specific section or driving situation. The driving position refers to the precise position of the target vehicle. The preset conditions may include that the driving duration of the target vehicle after entering the target section or passing through the target intersection is greater than the duration threshold, or that the driving distance of the target vehicle after entering the target section or passing through the target intersection is greater than the distance threshold, or that the driving position of the target vehicle after entering the target section or passing through the target intersection is outside a certain area range corresponding to the target section or the target intersection.

[0106] Optionally, whether the driving data meets the preset conditions is an important basis for determining whether to switch the display state of the augmented reality display client. The design of the preset conditions aims to ensure that the driver can obtain necessary auxiliary information in specific situations while avoiding interference in unnecessary situations.

[0107] Optionally, for the preset condition that the driving duration after entering the target section or passing through the target intersection is greater than the duration threshold, it can include two cases: a fixed duration threshold and an adjustable duration threshold.

[0108] Optionally, in the case of a fixed duration threshold, the duration threshold at this time is a preset fixed time, for example, 30 seconds or 1 minute. After the target vehicle enters the target section or passes through the target intersection, timing starts. If the driving duration of the target vehicle after entering the target section or passing through the target intersection exceeds the above duration threshold, it will be determined that the driver does not need the assistance of the AR navigation information of the augmented reality display client. Therefore, the state of the AR display client is switched back from the second state to the first state.

[0109] Optionally, when the duration threshold is adjustable, the duration threshold at this time can be adjusted according to dynamic factors such as the road characteristics of the section where the target vehicle is traveling, the driving speed of the target vehicle, and the real-time traffic conditions. For example, in a congested section, the duration threshold can be set to a longer time because the driver needs more time to process road conditions, and the augmented reality information of the AR display client can provide additional driving assistance. In a smooth section, the duration threshold may be set to a shorter time to reduce unnecessary information interference.

[0110] Optionally, for the preset condition that the driving distance after entering the target section or passing through the target intersection is greater than the distance threshold, the distance threshold can be used to measure the driving distance of the target vehicle after entering the target section or passing through the target intersection. When the driving distance exceeds the distance threshold, it can be considered that the driver has left the area that requires additional AR navigation information assistance. Therefore, the state of the AR display client can be switched from the second state back to the first state, that is, the augmented reality information display is turned off, or the navigation enhanced display state is switched to the navigation normal display state.

[0111] Optionally, for the driving position after entering the target section or passing through the target intersection, for the preset condition of being outside a certain area range corresponding to the target section or target intersection, the area range can be defined by setting a virtual boundary centered on the target section or target intersection. When the driving position of the target vehicle exceeds the above virtual boundary, it will be determined that the driver has left the interval that requires the AR navigation information provided by the augmented reality display client, and a second control instruction can be sent to the target vehicle to switch the state of the AR display client from the second state to the first state, that is, turn off the augmented reality information display. The area range is similar to the concept of the driving distance threshold, but more precisely considers information such as geographical location and lane distribution, which helps to provide a more accurate display state switch at complex intersections or sections. The setting of the area range takes into account complex geographical locations and lane layouts, which helps to provide a more precise display state switch at places such as complex intersections in the city or bifurcation points on highways, and avoids unnecessary information interference for drivers on simple sections or after completing key driving operations.

[0112] In summary, the setting that the above three types of driving data meet the preset conditions aims to dynamically adjust the display state of the AR display client based on the driving conditions and environmental conditions of the target vehicle, so as to balance the relationship between information support and information interference. When the driver needs additional information assistance, for example, when entering a complex section or passing through a complex intersection, the second control instruction is delayed to switch the state of the AR display client from the first state to the second state, ensuring that the driver has enough time to process the augmented reality information and make safe driving decisions. When the driver has left the area that requires additional augmented reality information assistance (for example, the driving time is too long, the driving distance is too far, or the driving position exceeds the set range), the augmented reality information display is turned off in a timely manner to avoid interference caused by information overload to the driver and ensure driving safety. By dynamically adjusting the duration threshold and distance threshold, it is possible to better adapt to different road environments and traffic conditions and provide more personalized driving assistance services.

[0113] In the embodiment of the present invention, the setting that the driving data meets the preset conditions is a key strategy for managing the state of the AR display client. By comprehensively considering the driver's information needs, road environment, and traffic conditions, the display of AR navigation information is dynamically adjusted, aiming to improve driving safety, efficiency, and comfort.

[0114] The following further describes the judgment process of this embodiment for determining whether a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information and navigation information, so as to determine whether to send the first control instruction.

[0115] As an optional implementation manner, step S104, if it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending the first control instruction to the target vehicle includes: if the corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, and the first control instruction is sent to the target vehicle, where the corresponding target road information is the information of the target section or target intersection within a preset distance from the positioning information.

[0116] In this embodiment, in the process of determining that the navigation section or intersection to be passed within a preset distance from the target vehicle is the target section or target intersection based on the positioning information and navigation information of the target vehicle and sending a first control instruction to the target vehicle, the cloud server may match the target road information from the database based on the navigation route information and positioning information. If the target road information is matched, it may be determined that the navigation section or intersection to be passed within a preset distance from the target vehicle is the target section or target intersection, and then a first control instruction may be sent to the target vehicle. Among them, the target road information is the information of the target section or intersection within a preset distance from the positioning information.

[0117] Optionally, the target road information may be the information of the target section or intersection within a preset distance from the positioning information. The target road information may include map data, real-time traffic conditions, traffic rules and suggestions, pedestrian and obstacle detection, etc. of the target road and target intersection. The map data may include lane layout, turning direction, road sign information, etc. of the target section or intersection. The real-time traffic conditions may be the traffic congestion conditions, construction information, accident scenes, etc. of the target section and target intersection. The traffic rules and suggestions may include traffic rules such as speed limits and prohibited left turns at the target section and target intersection, as well as safety suggestions provided to the driver according to the traffic conditions. The pedestrian and obstacle detection may provide detection information of pedestrians, bicycles, and obstacles in school areas or crosswalks. The generation and provision of the target road information are aimed at enhancing the driving safety and efficiency of the driver at specific sections or intersections. By identifying and displaying the complexity of the target section or intersection in advance, the driver can make driving decisions more calmly, reducing possible driving errors and traffic accidents.

[0118] It should be noted that the information of the target section and target road included in the above target road information is only for illustrative purposes and is not specifically limited this time. As long as it is the information used to prompt which sections and intersections on the navigation route of the target vehicle are the target sections and target intersections, it is within the protection scope of the embodiments of the present invention.

[0119] Optionally, this embodiment elaborates on how the cloud server dynamically determines whether the section or intersection that the target vehicle is about to pass through is the target section or target intersection based on the positioning information and navigation route information, which is an important reference for providing information to the augmented reality display client.

[0120] Optionally, when the target vehicle is in a driving state and using the navigation function, the target vehicle can obtain and upload the GPS positioning information and the current navigation route information of the target vehicle to the cloud server in real time. Among them, the GPS positioning information of the target vehicle includes the current longitude and latitude coordinates of the vehicle, which are used to accurately locate the position of the target vehicle; while the navigation route information includes the expected driving path and destination of the target vehicle, helping to understand the driving intention and direction of the target vehicle.

[0121] Optionally, after the cloud server receives the positioning information and navigation route information uploaded by the target vehicle, it can deeply analyze the above positioning information and navigation route information, analyze the current section where the target vehicle corresponding to the positioning information is located, and determine the upcoming section and passing intersections in combination with the navigation route information, match them with the target road information stored in the database, determine whether the section or intersection to be passed within a preset distance from the current position of the target vehicle is the target section or target intersection, and incorporate the relevant information of the above target section or target intersection into the first control instruction and feedback it to the target vehicle. Among them, the preset distance is comprehensively determined according to factors such as the driving speed of the target vehicle, the complexity of the road conditions, and the information provision requirements of the AR display client.

[0122] Optionally, the cloud server can combine real-time traffic data, road conditions information, historical driving data, etc. to analyze the driving scenarios that the target vehicle is about to face, and identify complex sections or intersections, such as roundabouts, fork roads, construction areas, etc. Match the position and driving direction of the target vehicle with the map data to determine whether the section or intersection that the target vehicle is approaching is a preset situation trigger point, for example, approaching a highway exit, a busy urban traffic area, etc. Through the feedback of the cloud server, the target vehicle can obtain detailed information about the section or intersection within a preset distance ahead, including but not limited to: road complexity, such as information about turns, fork points, number of lanes, etc. of the section or intersection. Traffic conditions, such as real-time traffic congestion, construction, accidents, etc., and predicted traffic change trends. Safety tips, such as potential hazards that may exist in the section or intersection.

[0123] Optionally, after the cloud server receives the positioning information and navigation route information sent by the target vehicle, it can determine that the section or intersection to be passed within a preset distance from the current position of the target vehicle is the target section or target intersection. The selection of the preset distance should take into account the driving speed of the target vehicle and the reaction time of the driver to receive information, ensuring that the driver has enough time to make corresponding driving decisions based on the received information. For example, if the target vehicle is approaching a complex roundabout intersection and the information feedback by the cloud server indicates that the roundabout is within the next 100 meters, the roundabout is determined as the target intersection. The augmented reality display client will adjust the display state in advance according to the above information, turn on the augmented display function, and provide the driver with detailed navigation information about the roundabout, including lane selection, turning instructions, traffic signal status, etc., to help the driver pass the intersection safely.

[0124] Optionally, through the above analysis by the cloud server, the recognition strategy for the target road section or target intersection can be dynamically adjusted, as well as the information provision strategy of the augmented reality display client, to achieve personalized driving assistance. For example, at different times and under different weather conditions, the preset distance may vary; on sections where the driver is more familiar, the preset distance may be shorter, while on sections where the driver is less familiar, the preset distance may be longer. In addition, the cloud server can also optimize the information provision strategy based on the historical driving data and driver preferences of the target vehicle. For example, provide fewer navigation prompts for experienced drivers and more detailed driving guidance for inexperienced drivers.

[0125] In the embodiment of the present invention, by analyzing the positioning information and navigation route information through the cloud server, it is possible to identify in advance the complex road sections or intersections that the target vehicle is about to pass through, dynamically determine the target road section or target intersection, thereby providing an important basis for the information provision strategy of the augmented reality display client and achieving safer and more efficient driving assistance. The in-depth analysis ability and data integration ability of the cloud server provide strong technical support for the above process, enabling the navigation control of the target vehicle to adapt to the complex and changeable driving environment and providing a personalized driving experience.

[0126] Optionally, the cloud server receives the positioning information and navigation route information of the target vehicle in real time, and the cloud further matches the target road information from its database. The database can contain rich geographical information, traffic data, historical driving records, etc., covering different types of road section information such as urban road networks, highways, and rural roads, as well as the characteristics of each road section or intersection, such as complexity, yaw probability, accident rate, etc. By matching with the vehicle's navigation route information, the cloud can identify which road sections or intersections have special navigation requirements, that is, the target road section or target intersection. After matching the target road information, the cloud server can further filter out all the navigation road sections or intersections to be passed within the preset distance from the target vehicle. The selection of the preset distance is crucial. It needs to be close enough to ensure the immediacy and pertinence of the information, but not too close to miss the opportunity for advance preparation. Usually, the preset distance will be dynamically adjusted according to the speed of the target vehicle, road conditions, and safety requirements.

[0127] Optionally, the cloud server generates a corresponding first control instruction for the matched target road information and sends it to the target vehicle. Unlike a cloud server that processes only one road section or intersection at a time, the cloud server sends a single first control instruction that covers all road sections or intersections with special navigation requirements within a preset distance. The advantage of this method is that the target vehicle can receive the first control instruction once, allowing the target vehicle to independently process the first control instruction at the appropriate time, avoiding frequent network communications and command responses, improving the overall efficiency of the navigation process and the driver's experience. For example, the cloud server sends only one control instruction to the target vehicle along the navigation route. This first control instruction includes all target road sections and intersections on the navigation route. During driving, the target vehicle can determine whether it is traveling on the target road section or intersection that meets the first control instruction based on its own positioning information. If the road section or intersection it is traveling on is after the target road section or intersection included in the first control instruction, it can adjust the ARHUD display status according to its own needs.

[0128] In an embodiment of the present invention, all target road information on the navigation route corresponding to the navigation route information is sent to the target vehicle as a first control instruction at one time, thereby ensuring the comprehensiveness and continuity of the navigation information. The driver can not only obtain navigation guidance for the road section or intersection that is about to be reached, but also have some understanding of the special requirements of multiple subsequent road sections or intersections, which is conducive to planning driving behavior in advance and reducing accidents and uncertainties during driving. The above method embodies the effective collaboration between the cloud server and the target vehicle. The cloud server is responsible for data analysis and the generation of the first control instruction, while the target vehicle is responsible for the reception and execution of the first control instruction. The above division of labor and cooperation not only improves the response speed and accuracy of the navigation control, but also reduces the data processing burden of the target vehicle itself, so that the target vehicle can focus on executing the control instruction and improve driving safety.

[0129] In practical application, this method can significantly improve drivers' ability to navigate complex road conditions and enhance their driving experience. Through precise data analysis and the push of first control commands from a cloud server, the target vehicle can appropriately switch to augmented reality navigation mode, providing more intuitive and accurate navigation information, helping drivers navigate their target road sections or intersections more safely and efficiently.

[0130] The following further describes the process of how this embodiment determines that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or intersection based on the positioning information and navigation route information of the target vehicle, thereby sending the first control instruction.

[0131] As an alternative embodiment, in step S104, when determining that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information and navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from the database based on the navigation route information and positioning information of the target vehicle, then determining that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, and based on the positioning information of the target vehicle, periodically sending a preset number of first control instructions corresponding to the preset number of target road information to the target vehicle, where the corresponding target road information is the information of the target section or target intersection within a preset distance from the positioning information, and the preset number is less than or equal to the number of at least one corresponding target road information.

[0132] In this embodiment, in the process of determining that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection based on the positioning information and navigation route information, and thus sending a first control instruction to the target vehicle, if the cloud server determines that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, it can periodically send a preset number of first control instructions corresponding to the preset number of target road information to the target vehicle based on the positioning information. Wherein, the preset number is less than or equal to the number of at least one corresponding target road information.

[0133] Optionally, this embodiment describes how, through the interaction between the target vehicle and the cloud server, the cloud server receives and processes a preset number of target road information, generates a first control instruction, and periodically sends the first control instruction to the target vehicle to dynamically identify the target section or intersection ahead, so as to determine whether to turn on the AR navigation to guide the target vehicle to drive.

[0134] Optionally, the target vehicle can send the current positioning information and expected navigation route information of the vehicle to the cloud server. The positioning information includes the real-time geographical coordinates of the vehicle, and the navigation route information covers the driving path of the target vehicle from the current position to the destination. After receiving the above positioning information and navigation route information, the cloud server can perform in-depth analysis by combining multi-source information such as real-time traffic data, weather conditions, and historical driving data.

[0135] Optionally, after the cloud server receives the positioning information and navigation route information of the target vehicle, it can predict the multiple road sections or intersections that the target vehicle will pass through in the next period of time based on the vehicle's driving direction and speed, and generate detailed information of the above-mentioned road sections or intersections, that is, target road information, and then generate corresponding first control instructions. The above-mentioned first control instructions are issued to the target vehicle periodically, rather than once. Periodically receiving a preset number of first control instructions means that the target road information can be regularly updated according to the driving status of the target vehicle and environmental changes, ensuring the timeliness and accuracy of the target road information. Among them, the preset number of target road information is determined comprehensively based on the target vehicle's driving speed, predicted distance and information processing capabilities, to ensure that the driver can receive enough but not too much information, which not only meets driving needs but also does not cause information overload.

[0136] Optionally, after determining the target road information, the cloud server can filter out detailed information of the target road section or target intersection within a preset distance from the current position of the target vehicle from a large amount of target road information in the database based on the real-time positioning information of the target vehicle. The preset distance is a dynamically adjusted parameter that can be set according to the target vehicle's driving speed, road complexity, and the driver's reaction time to the information to ensure that the driver has enough time to react according to the information displayed by the AR. The above matching process ensures that the AR display client only displays the most relevant and urgent road information to the driver, reduces the interference of irrelevant information, and improves the practicality of the target road information and driving safety. For example, when approaching a complex intersection, the intersection's turn instructions, traffic flow, pedestrian activities and other information can be matched and displayed first to help the driver make correct driving decisions in advance.

[0137] Optionally, the cloud server receives real-time positioning and navigation route information from the target vehicle, ensuring that the cloud server understands the target vehicle's current location and future travel direction. By combining the target vehicle's positioning information with its navigation route, the cloud server can construct a real-time model of the target vehicle's driving environment, providing a basis for subsequent decision-making.

[0138] Optionally, based on the target vehicle's location and navigation route information, the cloud server searches a database for information about all upcoming road sections or intersections within a preset distance from the current location, i.e., the target road information. The database contains a rich set of road attributes, including but not limited to road type, complexity, safety level, and historical deviation probability. This information helps the cloud server determine which road sections or intersections are challenging for the driver and may require augmented reality navigation support.

[0139] Optionally, the cloud server analyzes the target road information to determine which sections or intersections are target sections or target intersections, that is, sections with special navigation requirements. The above method is completed by comparing the road information with a preset complexity or yaw probability threshold, ensuring that only sections or intersections that truly require augmented reality navigation support are identified as target sections or target intersections.

[0140] Optionally, for the area determined to be a target section or target intersection, the cloud server generates a preset number of first control instructions. For example, an instruction to instruct the HUD to switch to the augmented reality display mode. The preset number refers to the upper limit of the number of instructions sent by the server each time, which can be less than or equal to the number of target road information matched, to avoid delays or resource waste caused by processing too many instructions. Subsequently, the cloud server periodically sends the above first control instructions to the target vehicle to ensure that the navigation information is updated synchronously with the change of the target vehicle's position, and provides navigation assistance to the driver in a timely manner. The selection of the preset distance ensures that the cloud server can identify the upcoming special section or intersection in advance, and the preset number balances the sufficiency of information and processing capabilities, avoiding information overload. Periodically updating and sending the first control instructions can adapt to the dynamic driving situation of the target vehicle. Even when the speed of the target vehicle changes or the route is adjusted, the real-time and accuracy of the navigation information can be maintained. By providing augmented reality navigation support in a timely manner, the driving pressure on complex sections is reduced, and driving safety is improved. At the same time, the periodic update of the first control instructions ensures the coherence and fluency of navigation, enhancing the user experience.

[0141] For example, if the first control instruction contains the detailed information of 5 complex target sections that the target vehicle will pass through in the next 10 minutes, then during the process of the target vehicle driving to the corresponding complex target sections in the future, or before driving to the complex target sections, the corresponding augmented reality navigation display is triggered based on the above first control instruction to provide visual navigation assistance to the driver.

[0142] In the embodiments of the present invention, by periodically receiving the first control instruction, the target vehicle can dynamically adjust the content displayed by the AR to adapt to the changing driving environment and the needs of the driver. In addition, the cloud server can also provide personalized driving assistance information based on the driver's personal driving habits, preferences, and historical driving data. For example, it can provide more simplified navigation prompts for experienced drivers, more detailed driving guidance for novice drivers, and adjust the display style and content of the information according to the driver's personal preferences. The cloud server can accurately identify the target road section or intersection, ensuring that the HUD provides augmented reality navigation at the most needed location, thus avoiding waste of resources. The mechanism for sending a preset number of first control instructions reduces unnecessary network communication and improves the overall response speed and efficiency of the navigation control process. Periodically sending the first control instruction ensures that the target vehicle can continuously receive the latest navigation data. Even in case of emergencies during driving, it can promptly adjust the navigation strategy and provide real-time navigation assistance.

[0143] In summary, this embodiment elaborates on the interaction strategy between the cloud service and the target vehicle. By precisely matching the target road information, a preset number of first control instructions, and the periodic update mechanism, it provides efficient and accurate augmented reality navigation support for the driver, significantly enhancing driving safety and the user experience.

[0144] The following further describes the process of determining the navigation road section or intersection to be passed within a preset distance from the target vehicle as the target road section or intersection based on the positioning information and navigation route information of the target vehicle, and thus sending the first control instruction to the target vehicle.

[0145] As an optional implementation manner, in step S104, if it is determined that the navigation road section or intersection to be passed within a preset distance from the target vehicle is the target road section or target intersection based on the positioning information and navigation route information of the target vehicle, then the steps of sending the first control instruction to the target vehicle include: if at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle, then determine the navigation road section or intersection to be passed within a preset distance from the target vehicle as the target road section or target intersection, and send all the first control instructions corresponding to all the target road information to the target vehicle, where the corresponding target road information is the information of the target road section or intersection within a preset distance from the positioning information.

[0146] In this embodiment, in the process of determining that the section where the target vehicle is currently located is the target section based on the positioning information and navigation route information of the target vehicle, and thus sending the first control instruction to the target vehicle, if it is determined that the navigation section or intersection to be passed within the preset distance from the target vehicle is the target section or intersection, then all the first control instructions corresponding to all the target road information on the navigation route can be sent to the target vehicle.

[0147] Optionally, the above embodiment describes the strategy for the target vehicle to interact with the cloud server to receive all the first control instructions on the entire navigation route at one time.

[0148] Optionally, after the target vehicle plans the complete navigation route information, it can upload the above navigation route information to the cloud server, including the starting point, ending point, and each section and intersection passed through. After receiving the navigation route information, the cloud server uses its powerful data processing ability to analyze the sections and intersections on the entire route, identify the sections or intersections that may have special navigation requirements or challenges, that is, the target road information, generate the corresponding first control instructions, and send the above first control instructions to the target vehicle at one time.

[0149] In the embodiment of the present invention, once the target vehicle receives all the first control instructions, even if it encounters unstable network or network disconnection during subsequent driving, the target vehicle can still navigate based on the downloaded first control instructions, provide AR display, and will not affect the driver's access to key navigation information, thereby improving the continuity and reliability of navigation. By receiving all the first control instructions at one time, the frequent data interaction with the cloud server can be significantly reduced, the impact of network latency on real-time navigation can be reduced, and at the same time, the data transmission volume can be reduced, saving communication resources. All the pre-received first control instructions enable the target vehicle to quickly respond to changes in the driving environment and provide instant driving assistance information without waiting for the cloud to update data in real time. For example, when suddenly encountering a construction section ahead, the target vehicle can immediately call the detailed data of the construction section from the existing target road information to remind the driver to pay attention to safety. Receiving all the first control instructions at one time reduces the frequent communication between the target vehicle and the cloud server, improving the overall efficiency, especially in areas with poor network conditions, the advantages of the above strategy are more obvious.

[0150] In summary, the target vehicle receives all the first control instructions from the cloud server at one time, which not only ensures the continuity and reliability of navigation, but also improves the efficiency and flexibility in coping with changes in the driving environment, providing a more stable, personalized and intelligent navigation experience for the driver.

[0151] The following further describes the process of determining, based on the positioning information and navigation route information of the target vehicle, a navigation section or intersection to be passed within a preset distance from the target vehicle as the target section or intersection, and sending a first control instruction to the target vehicle.

[0152] As an optional implementation, step S104, if it is determined that the target vehicle is currently located at the target section in the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending a first control instruction to the target vehicle includes: if the corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that the target vehicle is currently located at the target section in the navigation route, and a first control instruction is sent to the target vehicle, wherein the corresponding target road information is the information of the target section where the positioning information is located.

[0153] In this embodiment, in the process of sending the first control instruction to the target vehicle, if it is determined that the target vehicle is currently located at the target section in the navigation route, the first control instruction can be sent to the target vehicle, wherein the target road information can be information of the target section where the positioning information is located.

[0154] Optionally, the target road information may include information such as the target road segment's type and characteristics, traffic rules and recommendations, real-time traffic conditions, safety warnings, driving history and preferences, and the road segment's environment and facilities. The road segment type and characteristics can be used to identify the target road segment's type, such as a regular road, roundabout, complex intersection, tunnel, or bridge, as well as specific geometric features of the road segment (such as the number of lanes and the angle of the fork). Traffic rules and recommendations can include traffic regulations for the target road segment, such as speed limits, no left turns, and priority. Real-time traffic conditions can provide real-time traffic conditions on the target road segment, including traffic congestion, accident scenes, and road construction. Safety warnings can provide potential safety risk warnings based on the characteristics of the road segment, such as school zones, crosswalks, and wildlife areas. Driving history and preferences can combine the target vehicle driver's driving history and preferences to provide more personalized road information, such as the driver's previous deviation records on the road segment and the driver's preferences for AR navigation. The road section environment and facilities describe the environmental characteristics of the target road section and the facilities along the way, such as service areas, gas stations, hospitals, etc., as well as environmental information such as the weather and lighting conditions of the road section.

[0155] It should be noted that the target road section information included in the above target road information is only for illustration and is not specifically limited at this time. As long as the information is used to indicate whether the road section where the vehicle is located is the target road section, it is within the protection scope of the embodiment of the present invention.

[0156] Optionally, this embodiment illustrates the process by which the target vehicle dynamically determines whether the road section it is currently on is the target road section through real-time interaction with the cloud server. The above process makes full use of the computing power and data processing advantages of the cloud server.

[0157] Optionally, when the target vehicle is traveling on the planned navigation route, the target vehicle periodically, according to specific events (such as before entering a complex road section) or in real-time, sends the real-time positioning information and the current navigation route information of the target vehicle to the cloud server. After the cloud server receives the positioning information and navigation route information of the target vehicle, it can utilize its powerful data processing ability, combine historical driving data, map data, real-time traffic information, etc., analyze the road section characteristics around the current position of the target vehicle, and identify whether the current road section belongs to the predefined target road section. If the cloud server determines that the target vehicle is currently located in a predefined target road section, it can send a first control instruction to the target vehicle, which includes the detailed target road information of this road section.

[0158] Optionally, after the target vehicle receives the target road information fed back by the cloud server, it can confirm that the target vehicle is indeed located in the target road section of the navigation route according to the road section characteristics described in the target road information. The above confirmation process provides clear instructions for the driver, informing the special nature of the current road section and the driving strategy to be adopted.

[0159] Optionally, the cloud server can adopt the method of immediate calculation and immediate response. Specifically, the cloud server only calculates whether the current or the next upcoming road section or intersection of the target vehicle is the preset target road section / intersection each time. If the cloud determines that this road section / intersection indeed has special navigation requirements (such as complex turns, high yaw probability, multi-lane selection, etc.) based on the real-time positioning information and navigation route information of the target vehicle, then the cloud server will immediately generate and send a first control instruction to instruct the HUD of the target vehicle to switch to the augmented reality navigation mode.

[0160] In the embodiment of the present invention, through the above method, it is ensured that the cloud server can immediately respond to the change of the real-time position of the target vehicle and provide necessary navigation assistance in a timely manner. Since only one road section or intersection is calculated and processed each time, the computing burden is reduced, the decision-making speed is accelerated, and the network latency is reduced. The sending of the first control instruction is based on the immediate needs of the target vehicle, ensuring that the activation of the augmented reality navigation function is targeted at the current or the next upcoming driving challenges, and improving the pertinence and effectiveness of the navigation.

[0161] Optionally, based on the real-time positioning information and navigation route information of the target vehicle, the cloud server matches the corresponding target road information from its database. The database stores detailed information about various road sections, including but not limited to the difficulty level of the road, the probability of deviation, historical accident records, etc. By analyzing the above information, the cloud server determines whether the target vehicle is currently located on a road section with special navigation requirements. If it is confirmed that the target vehicle is located on the target road section, the cloud server sends a first control instruction to the target vehicle to enable the augmented reality navigation function of the HUD.

[0162] In the embodiment of the present invention, by utilizing the rich information in the database, the cloud server can make more accurate decisions and identify which road sections truly require augmented reality navigation support. The cloud server not only considers the current positioning information but also combines the navigation route information to ensure that all preset target road sections can be correctly identified and processed during the driving of the target vehicle. By matching the target road information, the cloud server can provide customized navigation assistance according to the actual driving route of each target vehicle, enhancing the user experience.

[0163] The following further describes the process of how to determine the target road section where the target vehicle is currently located in the navigation route based on the positioning information and navigation route information of the target vehicle, so as to send the first control instruction to the target vehicle.

[0164] As an optional implementation manner, in step S104, if it is determined that the target vehicle is currently located on the target road section in the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending the first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that the target vehicle is currently located on the target road section in the navigation route, and based on the positioning information of the target vehicle, a preset number of first control instructions corresponding to the preset number of target road information are periodically sent to the target vehicle, where the corresponding target road information is the information of the target road section where the positioning information is located, and the preset number is less than or equal to the number of at least one corresponding target road information.

[0165] In this embodiment, if it is determined that the target vehicle is currently located on the target road section in the navigation route, a preset number of first control instructions corresponding to the target road information can be periodically sent to the target vehicle based on the positioning information of the target vehicle.

[0166] Optionally, this embodiment elaborates another efficient and practical strategy for the interaction between the cloud service and the target vehicle, which is used to enable the augmented reality navigation mode of the HUD in a timely manner when the target vehicle is located in a specific complex section. The strategy of the above real-time example is divided into two parts: immediate calculation and instruction sending, and periodic instruction update based on database matching.

[0167] Optionally, based on the real-time positioning information and navigation route information of the target vehicle, the cloud server determines whether the target vehicle is located on the target section of the navigation route. If the determination is yes, the cloud server immediately sends a preset number of first control instructions to the target vehicle. Among them, the preset number is a balance between the cloud computing resources and the processing capacity of the target vehicle, and the preset number is less than or equal to the number of target road information matched with the current position of the target vehicle. Through the above method, it is ensured that there will be no delay or excessive resource occupation due to processing too many instructions. The immediate sending of the first control instruction enables the augmented reality navigation mode to be quickly started when the vehicle enters the target section, providing immediate and targeted navigation assistance.

[0168] In the embodiment of the present invention, the cloud server can quickly respond to the position change of the target vehicle to ensure the timely activation of the augmented reality navigation mode. The sending mechanism of the preset number of first control instructions optimizes the use of cloud resources, and also considers the processing capacity of the cloud server, improving the overall efficiency of navigation control. It ensures the provision of augmented reality navigation support on the target section, specifically addressing the navigation needs of complex sections and improving driving safety.

[0169] Optionally, the cloud server not only focuses on the current location of the target vehicle, but also matches a series of sections or intersections to be passed within a preset distance from the target vehicle in its database. The above sections have special navigation requirements and are defined as target road information. The cloud server can periodically generate and send a preset number of first control instructions based on the real-time positioning information of the target vehicle, instructing the HUD to switch to the augmented reality navigation mode.

[0170] In the embodiment of the present invention, the update frequency of the first control instruction can be maintained through the above method to adapt to the dynamic change of the vehicle position. It is ensured that the target vehicle can receive the latest navigation data and get ready before approaching the target section. By periodically sending instructions, the cloud server can notify the target vehicle in advance of the upcoming complex section, providing forward-looking navigation assistance. Based on the rich road information in the database, the cloud server makes more accurate decisions, improving the accuracy and effectiveness of navigation assistance. The combination of "preset number" and "periodic" sending of the first control instruction optimizes the information transmission efficiency from the cloud server to the target vehicle, while avoiding overload when processing the first control instruction.

[0171] In summary, through the complementarity of the above two strategies, an intelligent navigation system that can both respond immediately to changes in the position of the target vehicle and provide forward-looking navigation assistance is jointly constructed. The immediate calculation and instruction sending strategy is applicable to the immediate scenario where the target vehicle suddenly enters or is located in a complex section, ensuring the rapid activation of the HUD augmented reality navigation mode. The periodic instruction sending strategy based on database matching, on the other hand, focuses more on providing early notification of upcoming complex sections, giving the driver sufficient preparation time while maintaining the continuity and update of navigation information. By combining the above two strategies, comprehensive coverage of the navigation needs of the target vehicle can be achieved, improving driving safety and navigation efficiency.

[0172] The following further describes the process of sending all the first control instructions to the target vehicle at one time after determining that the target vehicle is currently located in the target section of the navigation route in this embodiment.

[0173] As an optional implementation manner, in step S104, if it is determined that the target vehicle is currently located in the target section of the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, the step of sending the first control instruction to the target vehicle includes: if at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle, it is determined that the target vehicle is currently located in the target section of the navigation route, and all the first control instructions corresponding to all the target road information are sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located.

[0174] In this embodiment, in the process of determining that the target vehicle is currently located in the target section of the navigation route based on the positioning information and navigation route information of the target vehicle, the cloud server can send all the first control instructions corresponding to all the target sections in the navigation route to the target vehicle at one time.

[0175] Optionally, this embodiment describes a strategy for the interaction between the target vehicle and the cloud server, which allows the target vehicle to receive all the first control instructions on the entire navigation route at one time.

[0176] Optionally, at the start of the journey or when the navigation route changes, the target vehicle can send the planned navigation route information to the cloud server. After receiving the navigation route information of the target vehicle, the cloud server conducts in-depth analysis, identifies all the target sections in the entire route that may pose challenges or require extra attention, integrates the target road information, formulates the corresponding first control instructions, and sends them to the target vehicle at one time. This means that before starting to drive, the target vehicle already has the first control instructions for switching the display state of the AR HUD in the critical target sections on the entire navigation route, without the need to frequently request updates during the driving process.

[0177] Optionally, during the driving of the target vehicle, the on-vehicle positioning system is continuously used to update its position information. When the target vehicle approaches or enters the target road section, the target vehicle can automatically match the road section information that most conforms to the current positioning information from all the received first control instructions, so as to confirm the target road section where the target vehicle is currently located, and then perform the operation of switching the display state of the AR HUD indicated by the above first control instruction.

[0178] In the embodiment of the present invention, receiving all the first control instructions at one time avoids the delay and interruption caused by frequently requesting information updates during driving, and ensures the coherence and real-time nature of the driving assistance information. When generating the target road information, the cloud server can take into account the historical driving behaviors and preferences of the driver of the target vehicle, as well as the characteristics of the target vehicle and the characteristics of the entire navigation route, so as to provide more personalized driving assistance information and enhance the driving experience. By obtaining the detailed information of the target road section in advance, the driver can have enough time to understand and prepare. Especially when approaching a complex road section, the driver can make safer driving decisions and reduce the risk of accidents. The method of receiving the first control instructions at one time reduces the number of interactions with the cloud, saves network bandwidth resources, which is especially beneficial for environments with unstable network connections or large delays, and improves the overall efficiency and stability. In summary, the strategy of the target vehicle receiving all the first control instructions at one time can significantly improve the timeliness, personalization and safety of driving assistance, while reducing network resource consumption.

[0179] The following further describes other steps included in this embodiment.

[0180] As an optional implementation manner, step S104, the step of sending the first control instruction to the target vehicle includes: sending the first control instruction to the target vehicle based on the familiarity of the in-vehicle account, where the familiarity is used to represent the familiarity of the in-vehicle account with the target road section or target intersection.

[0181] In this embodiment, during the process of sending the first control instruction to the target vehicle, the familiarity of the in-vehicle account of the target vehicle can be obtained, and the first control instruction is sent to the corresponding target vehicle through the familiarity, where the familiarity can be used to represent the familiarity of the in-vehicle account with the target road section or target intersection.

[0182] Optionally, when the cloud server decides whether to send the first control instruction for the HUD augmented reality navigation mode to the target vehicle, this embodiment not only considers the complexity or risk of the road section (such as the yaw probability reaching the preset threshold), but also combines the familiarity information of the driver (reflected by the in-vehicle account). The above embodiment further enriches the personalization and refinement of navigation assistance.

[0183] Optionally, the cloud server can evaluate the complexity and risk based on the attributes of the road section or intersection that the target vehicle is currently passing through or about to pass through. For example, if the yaw probability of a certain road section (i.e., the likelihood that the driver deviates from the predetermined route on this road section) reaches a preset threshold, or the road section is predefined as a high-complexity road section (such as highway exits, multi-lane intersections, complex urban intersections, etc.), or the road section is marked as a custom attention road section by the user (the user may mark certain road sections that require special attention based on personal experience or preferences), the cloud server can regard this road section or intersection as a target road section or intersection that needs attention.

[0184] Optionally, the cloud server can further analyze the user's familiarity with the target road section or intersection (identified by the in-vehicle account). Familiarity reflects the user's driving experience with this road section or intersection, and is usually comprehensively evaluated based on the user's driving history data, such as the number of times the user has driven on this road section, whether there is a yaw record, the average driving time, etc. If the user's familiarity is high, the cloud server may think that the user can drive through this road section more proficiently. On the contrary, additional navigation assistance may be required.

[0185] Optionally, based on the above analysis results, the cloud server can decide whether to send a first control instruction to the target vehicle. If the cloud evaluates that the yaw probability of the target road section or intersection is high and the user's familiarity is low, then the cloud will send a first control instruction to the target vehicle, instructing the HUD to enable the augmented reality navigation mode to provide more detailed and intuitive navigation guidance. On the contrary, if the user's familiarity is high, even if the yaw probability of the road section is relatively large, the cloud may also judge that the user does not need additional navigation assistance, thus avoiding unnecessary switching of the HUD display state and improving the navigation efficiency and the driver's experience.

[0186] For example, the cloud server can collect and analyze a large amount of data, including but not limited to road section attribute data, user driving history data, and real-time positioning information of the target vehicle, to accurately evaluate the complexity of the road section and the driver's familiarity. Collect the user's driving history data, including the number of times of driving on different road sections, yaw records, etc., and the attribute data of the road section, such as yaw probability, complexity level, etc. Use machine learning algorithms to analyze the user's driving habits, evaluate the user's familiarity with specific road sections, and at the same time analyze the potential risks of the road section. According to the real-time positioning information of the target vehicle and combining with the historical analysis results, the cloud can make an immediate decision on whether to send a first control instruction when the target vehicle approaches or enters a high-risk road section. If the decision result is that a first control instruction needs to be sent, the cloud server will send an instruction to the target vehicle through the wireless network, instructing the HUD to switch to the augmented reality navigation mode.

[0187] It should be noted that the above processes and methods for determining familiarity are only for illustrative purposes and are not specifically limited here. As long as they can determine whether to generate a process and method for switching the display state of the AR HUD at the above-mentioned road section or intersection according to the targeted familiarity of different drivers with the road section or intersection, they are within the protection scope of the embodiments of the present invention.

[0188] In the embodiments of the present invention, by using the familiarity of the driver, the cloud server can provide more personalized navigation assistance, making the activation of the augmented reality navigation mode more in line with the actual needs of the driver. Through the dual analysis of road section complexity and user familiarity, the refined management of navigation assistance is realized, avoiding the ineffective allocation of resources and reducing the interference of HUD mode switching on the driving experience. When the driver is not familiar with complex road sections or intersections, timely providing augmented reality navigation assistance can significantly improve driving safety and reduce the risks of deviation and traffic accidents. By combining the analysis of road section complexity and user familiarity, a more accurate and personalized navigation assistance strategy can be achieved. The above method not only improves driving safety but also optimizes the driving experience, reflecting the progress of intelligent navigation in personalized service and refined management.

[0189] The following further describes the process of sending the first control instruction to the corresponding target vehicle based on the familiarity of the in-vehicle device account in this embodiment.

[0190] As an optional implementation manner, the steps of sending the first control instruction to the target vehicle based on the familiarity of the in-vehicle device account include: in response to the familiarity being lower than the second preset threshold, sending the first control instruction to the target vehicle; the method further includes: in response to the familiarity being higher than or equal to the second preset threshold, prohibiting sending the first control instruction to the target vehicle.

[0191] In this embodiment, during the process of sending the first control instruction to the corresponding target vehicle based on the familiarity of the in-vehicle device account, the magnitude of the familiarity can be judged. If the familiarity is lower than the second preset threshold, the first control instruction can be sent to the target vehicle. Conversely, if the familiarity is higher than or equal to the second preset threshold, sending the first control instruction to the corresponding target vehicle is prohibited.

[0192] Optionally, this embodiment elaborates on a key link of the decision-making mechanism of the cloud server, that is, how to decide whether and when to send the first control instruction for activating the HUD augmented reality navigation to the target vehicle based on the yaw probability of the road section and the familiarity of the driver.

[0193] Optionally, the cloud server determines the yaw probability of a specific road section by analyzing the historical driving data of the road section. The yaw probability refers to the likelihood that a driver deviates from the predetermined route on this road section and can be statistically obtained based on past driving records. If the yaw probability of a road section reaches a preset threshold, the cloud server can automatically mark it as a high-risk road section, which may be due to factors such as complex intersections, variable lanes, or frequent turns. The cloud server can further evaluate the driver's familiarity with the target road section or intersection through the in-vehicle account (i.e., the driver's driving records and preference information). The level of familiarity determines whether the driver needs additional navigation assistance on this road section. The driver's driving history data, number of trips, yaw records, and personal preferences are all included in the factors of familiarity.

[0194] Optionally, the cloud server uses the yaw probability of the road section and the driver's familiarity as decision-making bases to determine whether to send a first control instruction to the target vehicle to activate the HUD augmented reality navigation function. The above decision-making mechanism considers various factors, ensuring that the sending of the first control instruction is based on both the risk assessment of the road section itself and the comprehensive consideration of the driver's personal capabilities and preferences. If the yaw probability of a road section is high, but the cloud server detects that the driver is also very familiar with this road section, it may mean that the driver has mastered the driving skills on this road section. Therefore, the cloud server may decide not to send the first control instruction to avoid unnecessary activation of the HUD. On the contrary, if the yaw probability of the road section is high and the driver is not familiar with this road section, the cloud server will send a first control instruction to the target vehicle to activate the HUD augmented reality navigation to provide detailed visual navigation information to help the driver better understand and cope with the complexity of the road section.

[0195] Optionally, for predefined road sections (such as known high-difficulty road sections) and custom road sections (road sections manually marked by the user that require special attention), the cloud server will give higher priority in decision-making. Even if the driver is relatively familiar with this road section, it may trigger the sending of the first control instruction to ensure that sufficient navigation assistance is provided on all high-risk road sections.

[0196] In the embodiment of the present invention, the decision-making mechanism of the cloud server considers the driver's personal capabilities and the characteristics of the road section, can provide personalized navigation assistance, and at the same time ensures driving safety on high-risk road sections. By accurately judging when to activate the HUD augmented reality navigation, it avoids waste of resources and reduces unnecessary startups and data transmissions. When timely and accurate navigation assistance can be provided when the driver needs it, the driver's trust and satisfaction with the target vehicle and the cloud server will be significantly improved. By comprehensively analyzing the yaw probability of the road section and the driver's familiarity to decide the sending of the first control instruction, it can effectively improve driving safety and user experience.

[0197] The following further describes other steps included in this embodiment.

[0198] As an alternative implementation, the method further includes: determining the number of driving times of the target vehicle associated with the in-vehicle infotainment (IVI) account on the target road section or at the target intersection; in response to the number of driving times being greater than the first number threshold and the number of yaw occurrences of the target vehicle on the target road section being less than the second number threshold, determining that the familiarity is higher than or equal to the second preset threshold; in response to the number of driving times being less than or equal to the first number threshold, and / or the number of yaw occurrences being greater than or equal to the second number threshold, determining that the familiarity is lower than the second preset threshold.

[0199] In this embodiment, the number of driving times of the target vehicle of the IVI account on the target road section or at the target intersection can be determined. If the number of driving times is greater than the first number threshold and the number of yaw occurrences of the target vehicle on the target road section is less than the second number threshold, it can be determined that the familiarity is higher than or equal to the second preset threshold. If the number of driving times is less than the first number threshold, and / or the number of yaw occurrences is greater than or equal to the second number threshold, it can be determined that the familiarity is lower than the second preset threshold.

[0200] Optionally, this embodiment describes how to quantify the driver's familiarity with a specific road section or intersection and how to decide whether to provide augmented reality navigation assistance based on this familiarity. The above process is carried out by analyzing the number of driving times of the target vehicle associated with the IVI account on the target road section or intersection and the frequency of yaw occurrences on these road sections.

[0201] Optionally, the cloud server can count the number of driving times of the target vehicle associated with the IVI account on the target road section or at the target intersection. The number of driving times reflects the driver's direct experience of this road section and is an important indicator for evaluating familiarity. For example, the more times a vehicle drives on a specific road section or at a specific intersection, the higher the driver's familiarity with this road section or intersection. The cloud server can also analyze the number of yaw occurrences of the target vehicle on the target road section. The number of yaw occurrences refers to the number of times of deviating from the predetermined route when driving on this road section and can be used as an inverse indicator reflecting the driver's mastery of the road section, that is, the more the number of yaw occurrences, the lower the familiarity. The cloud server sets the first number threshold and the second number threshold as the criteria for judging the level of familiarity.

[0202] Optionally, if the number of driving times is greater than the first number threshold and the number of yaw times is less than the second number threshold, it is determined that the driver's familiarity with the target road section or intersection is higher than or equal to the second preset threshold. This means that the driver has rich driving experience on this road section and can accurately follow the route in most cases, so additional augmented reality navigation assistance is not required. If the number of driving times is less than or equal to the first number threshold, or the number of yaw times is greater than or equal to the second number threshold, it is determined that the driver's familiarity with the target road section or intersection is lower than the second preset threshold. This indicates that the driver may lack sufficient experience or has yawed multiple times on this road section, with a relatively high yaw risk. At this time, augmented reality navigation assistance can be considered.

[0203] In the embodiment of the present invention, by quantifying the number of driving times and the number of yaw times, the driver's familiarity with a specific road section can be accurately evaluated, and a personalized navigation assistance strategy can be provided. When the driver is not familiar with the road section or frequently yaws, enabling the augmented reality navigation function in a timely manner can significantly reduce the yaw probability and improve driving safety. Avoid wasting resources, such as frequent data transmission and unnecessary switching of the HUD mode, on road sections where the driver is already familiar and can drive safely, thus improving the overall resource utilization efficiency and the user's driving experience. In summary, quantifying familiarity by analyzing the number of driving times and the number of yaw times of the target vehicle associated with the in-vehicle computer account on the target road section is a data-driven personalized decision-making mechanism that improves driving safety and efficiency.

[0204] The process of how the cloud server in this embodiment obtains the positioning information and navigation route information of the target vehicle will be further described below.

[0205] As an optional implementation manner, step S102, obtaining the positioning information and navigation route information of the target vehicle, includes: in response to a target request of the target vehicle, obtaining the positioning information and navigation route information of the target vehicle, where the target request is generated based on the navigation route information of the target vehicle and the in-vehicle computer account of the target vehicle.

[0206] In this embodiment, during the process of obtaining the positioning information and navigation route information of the target vehicle, the positioning information and navigation route information can be obtained based on the target request of the target vehicle. Among them, the target request can be generated based on the navigation route information of the target vehicle and the in-vehicle computer account of the target vehicle.

[0207] Optionally, the target request is generated by a navigation control client on the target vehicle, and its generation is typically based on two key pieces of information: the navigation route information of the target vehicle and the in-vehicle account of the target vehicle. When the target vehicle starts or is in motion, the navigation control client will automatically generate and send a target request to the cloud server according to the current driving route and the in-vehicle account registered by the target vehicle. The target request contains the driving plan of the target vehicle and the driver identity information, so that the cloud server can accurately identify and respond to the needs of the target vehicle.

[0208] Optionally, after receiving the target request, the cloud server can parse the navigation route information and the in-vehicle account information therein for further processing. For example, the cloud server parses the information in the target request to identify the current positioning information (i.e., the current location) of the target vehicle and the navigation route to be traveled. Based on the parsed positioning information and navigation route information, the server will further match and analyze the detailed data of the road sections or intersections that the target vehicle is about to travel through, including road section attributes, traffic conditions, historical yaw data, etc. At the same time, the cloud server can also retrieve the driving history and preferences of the driver based on the in-vehicle account information to evaluate the driver's familiarity with the upcoming road sections. According to the above analysis results, the cloud server generates a control strategy to determine whether to send a first control instruction to the target vehicle. The generation of the control strategy takes into account the complexity of the road section and the driver's familiarity to ensure the necessity and effectiveness of navigation assistance. Once the control strategy determines that a first control instruction needs to be sent, the cloud server can immediately generate and send an instruction to the target vehicle, instructing its HUD or other navigation assistance devices to perform mode switching or provide specific navigation information.

[0209] In the embodiment of the present invention, based on the positioning information and navigation route information acquisition mechanism of the target request, it can ensure that the cloud server responds to the needs of the target vehicle in real time and provides personalized navigation assistance strategies. When the target vehicle is about to pass through a complex or high-risk road section, timely navigation assistance can significantly improve driving safety and reduce the occurrence of yaw and traffic accidents. By accurately analyzing the needs, unnecessary information transmission and device activation are avoided, the utilization of resources is optimized, and the interference with the driving experience is reduced. In summary, the positioning information and navigation route information acquisition mechanism based on the target request is the key to realizing personalized, safe and efficient navigation assistance. The above mechanism provides navigation services based on the driver's own needs and driving ability through real-time data transmission, fine data analysis and personalized decision generation.

[0210] In an embodiment of the present invention, the positioning information and navigation route information of a target vehicle can be obtained through a cloud server, and based on the navigation route information and the positioning information, a navigation section or intersection within a preset distance from the target vehicle is determined as a target section or target intersection. Alternatively, if it is determined through the navigation route information and the positioning information that the target vehicle is currently located at a target section in the navigation route, a first control instruction can be sent to the target vehicle. The target vehicle uses the first control instruction to switch the display state of the augmented reality display client from a first state to a second state, or can also output corresponding prompt information to prompt the switching of the display state. In this embodiment, by analyzing the conditions during the driving process of the target vehicle through the above cloud server and performing intelligent control, not only is the driving experience of the driver of the target vehicle optimized, unnecessary information interference is avoided, but also the driving safety level in the environment of special sections and intersections is significantly improved. The above method is based on the positioning and navigation route information of the target vehicle, and can intelligently identify sections and intersections with a relatively high probability of yaw or unfamiliar to the driver that the target vehicle is about to pass through, or the target vehicle is in the above special sections, so as to timely turn on or strengthen the AR navigation display, or output targeted prompt information to ensure that the driver can timely notice the key situations of the above special sections or intersections, and reduce the occurrence of yaw events and dangerous events of the target vehicle. The technical effect of improving the navigation effect of the cloud server controlling the vehicle is achieved, and the technical problem of poor navigation effect of the cloud server controlling the vehicle is solved.

[0211] The technical solutions of the embodiments of the present invention will be illustrated below in conjunction with preferred embodiments.

[0212] Currently, in the automotive industry, AR HUD for realistic navigation and information display is a competitive area for each car manufacturer. It solves the driving risks caused by the driver looking down at the instrument panel and the large screen for users, and also more intuitively demonstrates the technical strength of the car manufacturer. The information displayed on the HUD screen is classified into two categories: Windshield Head-Up Display (WHUD) and AR for realistic navigation. The WHUD area displays two-dimensional elements such as vehicle speed, gear, and Turn-by-Turn (TBT) navigation. AR for realistic navigation mainly directly expresses guidance by displaying elements such as a realistic guidance light carpet and three-dimensional arrows. Because it is realistic, it is easier to understand, but at the same time, it has the disadvantages of blocking the user's eyes and interfering with the user's driving. It is difficult to achieve both guiding value for each user and not interfering with the user only from the design of a single product, and it is also difficult for the manual switch to allow the user to manually turn it on each time. An automatic intelligent solution is urgently needed to solve this problem.

[0213] However, an embodiment of the present invention proposes a method for automatically turning on and off AR guidance in combination with a navigation route. By analyzing the characteristics of the navigation route, the AR guidance is intelligently turned on and off, achieving the purpose of automatically turning off when there is no need to interfere with the user's driving and automatically turning on when AR is needed to fit the real-world guidance. This allows users to generally feel the intelligent and considerate service of the AR HUD product, enhancing the user experience of the AR HUD product. It achieves the technical effect of improving the navigation effect of the vehicle controlled by the cloud server and solves the technical problem of poor navigation effect of the vehicle controlled by the cloud server.

[0214] The method of the embodiment of the present invention will be further illustrated by examples below.

[0215] Figure 2 It is a flowchart of a method for automatically turning on and off AR guidance in combination with a navigation route shown according to an embodiment of the present invention. As Figure 2 shown, this method can be implemented through the interaction of a navigation client APP a, an intelligent navigation cloud service b, and an AR HUD client APP c. The navigation client APP a can run as a navigation APP in the car cockpit, log in with the in-vehicle account, be responsible for the user to initiate navigation, display the navigation route, search for nearby points of interest (POI), etc. In the embodiment of the present invention, it is mainly responsible for uploading the navigation route and yaw event information. The intelligent navigation cloud service b is used to record the navigation route and yaw information of the in-vehicle account and provide intelligent computing services for the AR HUD client APP c. The AR HUD client APP c is responsible for uploading the information of the forward road section, receiving the result of whether to turn on the AR navigation service returned by the intelligent navigation cloud service, and executing whether to turn on the AR navigation.

[0216] Optionally, as Figure 2 shown, this method may include:

[0217] Step S201, upload the user's personal navigation route.

[0218] In this embodiment, after the navigation client APP a initiates navigation, it can upload the point information of the navigation route (link) of the current user.

[0219] Step S202, count the navigation route and times.

[0220] In this embodiment, after the intelligent navigation cloud service b receives the information sent by the navigation client APP a, it stores it and counts the personal route and times.

[0221] Step S203, upload the yaw position.

[0222] In this embodiment, after the navigation client APP a has a yaw in the driving route, it can upload the yaw position to the intelligent navigation cloud service b.

[0223] Step S204: Count the deviated sections of the personal navigation route.

[0224] In this embodiment, after receiving the information sent by the navigation client APPa, the intelligent navigation cloud service b stores it and counts the deviated sections of the personal navigation route.

[0225] Step S205: Count the sections that are prone to deviation.

[0226] In this embodiment, the intelligent navigation cloud service counts the deviation information sent by the navigation clients of each user, and counts the sections that are prone to deviation. The proportion of the number of deviations to the number of driving times is greater than 20%, which is used as the sections that are prone to deviation.

[0227] Step S206: Request to determine whether AR guidance needs to be enabled for the current section.

[0228] In this embodiment, during the user's driving process, the AR HUD client APP c actively sends a request to the intelligent navigation cloud service every other section, requesting to determine whether AR navigation needs to be enabled for the current section.

[0229] Step S207: Determine whether the current section is a section prone to deviation.

[0230] In this embodiment, after receiving the request, the intelligent cloud service b determines whether the current section belongs to the sections prone to deviation. If it is a section prone to deviation, step S209 can be executed; otherwise, step S208 can be executed.

[0231] Step S208: No need to enable AR guidance.

[0232] In this embodiment, if it is not a section prone to deviation, the result that the AR HUD client APP c does not need to turn on AR navigation is returned.

[0233] Step S209: Determine whether the current section is a familiar section.

[0234] In this embodiment, if it is a section prone to deviation, it is determined whether the current user is familiar with this section. The judgment basis is that the number of driving times on this section is greater than 10 times, and there is no deviation in the last 30% of the driving experiences. If the current section is a familiar section, step S210 is executed; otherwise, step S211 is executed.

[0235] Step S210: No need to enable AR guidance.

[0236] In this embodiment, if it is a familiar section, the result that the AR HUD client APP c does not need to turn on AR navigation is returned.

[0237] Step S211: AR guidance needs to be enabled.

[0238] In this embodiment, if not, a result indicating that the ARHUD client APP c needs to enable AR navigation is returned.

[0239] Figure 3(a) is a schematic diagram of a complex intersection according to an embodiment of the present invention. As shown in Figure 3(a), the intersection is an intersection where two or more roads intersect at right angles to form four directions. Some complex intersections may have only one left turn lane, and the second straight road is followed by a road section where left turns are not allowed. In the above case, if the driver misses the left turn, he will not be able to return to the predetermined navigation route. Whether an intersection is a target intersection can be measured based on the yaw probability and preset rules. For example, at a certain intersection, historical data shows that the yaw rate of left-turning vehicles is high, and the driver is less familiar with the intersection. The intersection can be marked as a target intersection.

[0240] Figure 3(b) is a schematic diagram of a three-way intersection according to an embodiment of the present invention. As shown in Figure 3(b), compared to a two-way intersection, a three-way intersection offers more route options. Drivers must choose from three or more roads, which increases the difficulty of decision-making. At a three-way intersection, without clear and unambiguous road signs, drivers may hesitate due to uncertainty and miss the appropriate time to turn, resulting in erroneous or dangerous driving. Therefore, a three-way intersection can be marked as a target intersection.

[0241] Figure 3(c) is a schematic diagram of a complex overpass according to an embodiment of the present invention. As shown in Figure 3(c), complex overpasses present problems such as structural complexity and upper and lower obstructions. Regarding structural complexity, complex overpasses typically include multiple layers of ramps and main bridges in multiple directions, forming a complex three-dimensional spatial structure. This complexity makes it difficult for drivers to quickly understand the entire layout of the overpass. Especially in conditions of heavy traffic and high speeds, drivers' attention is distracted, making it difficult to accurately determine the correct direction of travel. Regarding upper and lower obstructions, obstructions on the upper level of a complex overpass may affect the driver's visual recognition of exits on the lower level or surrounding roads. This obstruction effect is particularly pronounced during periods of changing light or poor weather conditions, increasing the risk of yaw. In other words, due to the complex structure of a complex overpass and the mutually obstructed road conditions above and below, it is difficult for drivers to identify the correct route, and even experienced drivers may become confused. Therefore, complex overpasses can be marked as target intersections.

[0242] FIG. 3(d) is a schematic diagram of an elevated intersection according to an embodiment of the present invention. As shown in FIG. 3(d), the specific height and structure of the elevated intersection may limit the driver's sight distance. Especially when the target vehicle approaches the elevated intersection, the driver may not be able to see the exit or road signs ahead, which will increase the difficulty of judging the exit and driving direction. That is to say, due to its height and structural characteristics, the elevated intersection is likely to cause confusion for the driver when judging the exit and driving direction, especially in an unfamiliar area. Therefore, complex overpasses can be marked as target intersections.

[0243] In an embodiment of the present invention, the positioning information and navigation route information of the target vehicle can be obtained through a cloud server, and based on the navigation route information and positioning information, the navigation section or intersection to be passed within a preset distance from the target vehicle is determined as the target section or target intersection. Or if it is determined through the navigation route information and positioning information that the target vehicle is currently located on the target section of the navigation route, a first control instruction can be sent to the target vehicle, and the target vehicle uses the first control instruction to switch the display state of the augmented reality display client from the first state to the second state, or corresponding prompt information can also be output to prompt the switch of the display state. In this embodiment, by analyzing the situation of the target vehicle during driving through the above cloud server and performing intelligent control, not only the driving experience of the driver of the target vehicle is optimized, unnecessary information interference is avoided, but also the driving safety level in the environment of special sections and intersections is significantly improved. The above method is based on the positioning and navigation route information of the target vehicle, and can intelligently identify the sections and intersections with a relatively high probability of yaw or unfamiliar to the driver that the target vehicle is about to pass through, or the target vehicle is in the above special sections, so as to timely turn on or strengthen the AR navigation display, or output targeted prompt information to ensure that the driver can timely notice the key situations of the above special sections or intersections, and reduce the occurrence of yaw events and dangerous events of the target vehicle. The technical effect of improving the navigation effect of the cloud server controlling the vehicle is achieved, and the technical problem of poor navigation effect of the cloud server controlling the vehicle is solved.

[0244] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0245] According to another aspect of the embodiment of the present invention, corresponding to the embodiment of the navigation control method of the vehicle above, this specification also provides a navigation control device for a vehicle. Figure 4is a structural block diagram of a navigation control device of a vehicle shown according to an embodiment of the present invention. As Figure 4 shown, the navigation control device 400 of the vehicle may include: an acquisition unit 402 and a transmission unit 404.

[0246] The acquisition unit 402 is configured to acquire the positioning information of the target vehicle and the navigation route information of the target vehicle.

[0247] The transmission unit 404 is configured to, if it is determined based on the positioning information of the target vehicle and the navigation route information of the target vehicle that a navigation section or intersection within a preset distance from the target vehicle to be passed is a target section or a target intersection, or it is determined that the target vehicle is currently located at a target section in the navigation route, send a first control instruction to the target vehicle.

[0248] In the navigation control device of the vehicle in this embodiment, the positioning information and the navigation route information of the target vehicle can be obtained through a cloud server, and based on the navigation route information and the positioning information, it is determined that a navigation section or intersection within a preset distance from the target vehicle to be passed is a target section or a target intersection, or if it is determined through the navigation route information and the positioning information that the target vehicle is currently located at a target section in the navigation route, a first control instruction can be sent to the target vehicle. The target vehicle uses the first control instruction to switch the display state of the augmented reality display client from a first state to a second state, or can also output corresponding prompt information to prompt the switch of the display state. In this embodiment, by analyzing the conditions during the driving process of the target vehicle through the above cloud server and performing intelligent control, not only the driving experience of the driver of the target vehicle is optimized, unnecessary information interference is avoided, but also the driving safety level in the environment of special sections and intersections is significantly improved. The above method is based on the positioning and navigation route information of the target vehicle, and can intelligently identify sections and intersections with a relatively high probability of deviation or unfamiliar to the driver that the target vehicle is about to pass through, or the target vehicle is in the above special sections, so as to timely turn on or strengthen the AR navigation display, or output targeted prompt information to ensure that the driver can timely notice the key situations of the above special sections or intersections, and reduce the occurrence of target vehicle deviation events and dangerous events. The technical effect of improving the navigation effect of the cloud server controlling the vehicle is achieved, and the technical problem of poor navigation effect of the cloud server controlling the vehicle is solved.

[0249] Figure 5 is a structural block diagram of an autonomous vehicle shown according to an embodiment of the present invention. As Figure 5 shown, the components of the autonomous vehicle 500 include but are not limited to a memory 510 and a processor 520. The processor 520 and the memory 510 are connected through a bus 530, and the database 560 is used to store data.

[0250] The autonomous vehicle 500 may also include an access device 540, which enables the autonomous vehicle 500 to communicate via one or more networks 550. Examples of such networks include the Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of wired or wireless network interface (e.g., network interface controller (NIC)), such as an IEEE 802.5 Wireless Local Area Network (WLAN) wireless interface, Worldwide Interoperability for Microwave Access (Wi-MAX) interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, Bluetooth interface, Near Field Communication (NFC) interface, and so on.

[0251] In one embodiment of the present disclosure, the above components of the autonomous vehicle 500 and Figure 5 other components not shown may also be connected to each other, for example, via a bus. It should be understood that Figure 5 the block diagram of the autonomous vehicle shown is for illustrative purposes only and is not a limitation on the scope of the present disclosure. Those skilled in the art may add or replace other components as needed.

[0252] According to another aspect of the embodiments of the present invention, there is also provided a cloud server, including: a memory storing an executable program; a processor for running the above program to obtain the positioning information of a target vehicle and the navigation route information of the target vehicle; if, based on the positioning information of the target vehicle and the navigation route information of the target vehicle, it is determined that a navigation section or intersection within a preset distance from the target vehicle is a target section or target intersection, or if it is determined that the target vehicle is currently located at a target section in the navigation route, then a first control instruction is sent to the target vehicle.

[0253] Embodiments of the present application also provide a computer-readable storage medium, which includes an executable program stored therein. When the executable program runs, it controls the device where the computer-readable storage medium is located to execute the methods in various embodiments of the present invention.

[0254] Embodiments of the present application also provide a computer program product, including a computer program which, when executed by a processor, implements the methods in various embodiments of the present invention.

[0255] Embodiments of the present application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program which, when executed by a processor, implements the methods in various embodiments of the present invention.

[0256] Embodiments of the present application also provide a computer program which, when executed by a processor, implements the methods in the above-mentioned various embodiments of the present invention.

[0257] In the above embodiments of the present invention, the descriptions of the various embodiments have their own focuses. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0258] In the several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in electrical or other forms.

[0259] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0260] In addition, the functional units in various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0261] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs.

[0262] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A navigation control method for a vehicle, characterized in that, Applied to a cloud server, including: Obtain the positioning information of the target vehicle and the navigation route information of the target vehicle; If, based on the positioning information of the target vehicle and the navigation route information of the target vehicle, it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, or it is determined that the target vehicle is currently located at a target section in the navigation route, then send a first control instruction to the target vehicle, where the first control instruction is used to control the display state of the augmented reality display client to switch from a first state to a second state and / or output a prompt message, and the augmented reality display client is installed on the target vehicle; Among them, the target section or the target intersection is one of the following sections or intersections: a section or intersection with a yaw probability reaching a first preset threshold; a section or intersection with a yaw probability reaching the first preset threshold and the familiarity of the vehicle-mounted account corresponding to the target vehicle with the target section or the target intersection being lower than a second preset threshold; a section or intersection preset according to a preset rule; a section or intersection customized according to a custom instruction; the yaw probability is used to represent the degree of the probability of historical vehicles passing by the target section or the target intersection and yawing; If the first state is the navigation closed state of the augmented reality display client, then the second state is the navigation open state of the augmented reality display client; Or, if the first state is the navigation normal display state of the augmented reality display client, then the second state is the navigation enhanced display state of the augmented reality display client.

2. The method according to claim 1, wherein The method further includes: After determining that the display state of the augmented reality display client switches to the second state, if it is determined that the driving data of the target vehicle meets a preset condition, then send a second control instruction to the target vehicle, where the second control instruction is used to control the display state of the augmented reality display client to switch from the second state to the first state.

3. The method according to claim 2, wherein The driving data meeting the preset condition includes at least one of the following: The driving duration of the target vehicle after entering the target section or passing through the target intersection is greater than a duration threshold, the driving distance of the target vehicle after entering the target section or passing through the target intersection is greater than a distance threshold, and the driving position of the target vehicle after entering the target section or passing through the target intersection is outside a certain area range corresponding to the target section or the target intersection.

4. The method according to claim 1, wherein The step of, if, based on the positioning information of the target vehicle and the navigation route information of the target vehicle, it is determined that a navigation section or intersection to be passed within a preset distance from the target vehicle is a target section or target intersection, then sending a first control instruction to the target vehicle includes: If corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, then a navigation section or intersection to be passed within a preset distance from the target vehicle is determined as the target section or the target intersection, and the first control instruction is sent to the target vehicle, where the corresponding target road information is the information of the target section or the target intersection within a preset distance from the positioning information.

5. The method according to claim 1, characterized in that, The step of, if a navigation section or intersection to be passed within a preset distance from the target vehicle is determined as the target section or the target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, then sending the first control instruction to the target vehicle includes: If at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, then a navigation section or intersection to be passed within a preset distance from the target vehicle is determined as the target section or the target intersection, and based on the positioning information of the target vehicle, the preset number of the first control instructions corresponding to the preset number of the target road information are periodically sent to the target vehicle, where the corresponding target road information is the information of the target section or the target intersection within a preset distance from the positioning information, and the preset number is less than or equal to the number of at least one corresponding target road information.

6. The method according to claim 1, characterized in that, The step of, if a navigation section or intersection to be passed within a preset distance from the target vehicle is determined as the target section or the target intersection based on the positioning information of the target vehicle and the navigation route information of the target vehicle, then sending the first control instruction to the target vehicle includes: If at least one corresponding target road information is matched from the database based on the navigation route information of the target vehicle, then a navigation section or intersection to be passed within a preset distance from the target vehicle is determined as the target section or the target intersection, and all the first control instructions corresponding to all the target road information are sent to the target vehicle, where the corresponding target road information is the information of the target section or the target intersection within a preset distance from the positioning information.

7. The method according to claim 1, characterized in that, The step of, if it is determined that the target vehicle is currently located at a target section in the navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle, then sending the first control instruction to the target vehicle includes: If corresponding target road information is matched from the database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, then it is determined that the target vehicle is currently located at the target section in the navigation route, and the first control instruction is sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located.

8. The method according to claim 1, wherein The step of sending a first control instruction to the target vehicle if it is determined that the target vehicle is currently located on a target section of a navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle includes: If at least one corresponding target road information is matched from a database based on the navigation route information of the target vehicle and the positioning information of the target vehicle, it is determined that the target vehicle is currently located on the target section of the navigation route, and based on the positioning information of the target vehicle, the preset number of the first control instructions corresponding to the preset number of the target road information is periodically sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located, and the preset number is less than or equal to the number of at least one corresponding target road information.

9. The method according to claim 1, characterized in that The step of sending a first control instruction to the target vehicle if it is determined that the target vehicle is currently located on a target section of a navigation route based on the positioning information of the target vehicle and the navigation route information of the target vehicle includes: If at least one corresponding target road information is matched from a database based on the navigation route information of the target vehicle, it is determined that the target vehicle is currently located on the target section of the navigation route, and all the first control instructions corresponding to all the target road information are sent to the target vehicle, where the corresponding target road information is the information of the target section where the positioning information is located.

10. The method according to claim 1, characterized in that The step of sending a first control instruction to the target vehicle includes: Sending the first control instruction to the target vehicle based on the familiarity of the in-vehicle account, where the familiarity is used to represent the familiarity degree of the in-vehicle account with the target section or the target intersection.

11. The method according to claim 10, wherein The step of sending the first control instruction to the target vehicle based on the familiarity of the in-vehicle account includes: In response to the familiarity being lower than the second preset threshold, sending the first control instruction to the target vehicle; The method further includes: prohibiting sending the first control instruction to the target vehicle in response to the familiarity being higher than or equal to the second preset threshold.

12. The method according to claim 11, wherein The method further includes: Determining the number of driving times of the target vehicle associated with the in-vehicle account on the target section or the target intersection; In response to the number of driving times being greater than the first number threshold and the number of yaw times of the target vehicle deviating from the course on the target section being less than the second number threshold, determining that the familiarity is higher than or equal to the second preset threshold; In response to the number of driving times being less than or equal to the first number threshold, and / or, the number of yaw times being greater than or equal to the second number threshold, determining that the familiarity is lower than the second preset threshold.

13. The method according to any one of claims 1 to 12, characterized in that, Obtaining the positioning information of the target vehicle and the navigation route information of the target vehicle includes: In response to a target request of the target vehicle, obtain the positioning information of the target vehicle and the navigation route information of the target vehicle, where the target request is generated based on the navigation route information of the target vehicle and the in-vehicle account of the target vehicle.

14. A cloud server, characterized in that, Comprising: A memory storing an executable program; A processor for running the program, where when the program runs, it executes the method according to any one of claims 1 to 13.

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