Vehicle navigation method and device, computer equipment, storage medium and program product

Abstract

The invention relates to a vehicle navigation method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: in the driving process of a target vehicle, sending vehicle associated data of the target vehicle to a cloud; wherein the vehicle associated data comprises vehicle end state data and travel data of the target vehicle, and sensor data collected by a vehicle-mounted sensor in the target vehicle; receiving a target three-dimensional model issued by the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle associated data and road condition data collected by roadside equipment of a road where the target vehicle is located; the target three-dimensional model comprises a driving route of the target vehicle; and displaying the target three-dimensional model in the form of a holographic image through a vehicle-mounted display device in the target vehicle for navigation of the target vehicle. By adopting the method, rich navigation route information can be provided for a driver.

Description

Technical Field

[0001] The present application relates to the field of information processing technology, and in particular to a vehicle navigation method, device, computer equipment, storage medium and program product. Background Art

[0002] With the acceleration of urbanization and the continuous increase in the number of cars, problems such as traffic congestion and frequent accidents are becoming increasingly prominent.

[0003] In recent years, vehicle-road-cloud integration technology has become an important development direction in the field of intelligent transportation. Through the deep integration of vehicles, road infrastructure and cloud platforms, it has realized the real-time collection, processing and sharing of traffic data, providing the possibility for the development of more advanced navigation systems.

[0004] However, most of the navigation systems currently on the market are still at the level of two-dimensional maps and voice prompts, unable to provide drivers with intuitive and comprehensive traffic environment information, and unable to promote the development of intelligent transportation systems. Summary of the invention

[0005] Based on this, it is necessary to provide a vehicle navigation method, device, computer equipment, storage medium and program product to address the above technical problems, which can provide drivers with intuitive and comprehensive traffic environment information.

[0006] In a first aspect, the present application provides a vehicle navigation method, the method comprising:

[0007] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0008] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0009] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0010] In one of the embodiments, the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; and the vehicle environment model is constructed based on sensor data.

[0011] In one of the embodiments, the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0012] In one embodiment, after displaying the target three-dimensional model in the form of a holographic image through an on-board display device in the target vehicle, the method further includes:

[0013] When an abnormal driving event is detected, a warning prompt message is added to the displayed target three-dimensional model.

[0014] In one embodiment, adding warning information to the displayed target three-dimensional model includes:

[0015] When it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0016] In one embodiment, when an abnormal driving event is detected, after adding warning information to the displayed target three-dimensional model, the method further includes:

[0017] If no response operation to the warning prompt information is detected within the set time, the avoidance operation will be performed according to the danger avoidance strategy corresponding to the abnormal driving event.

[0018] In a second aspect, the present application further provides a vehicle navigation device, the device comprising:

[0019] A sending module is used to send vehicle-related data of the target vehicle to the cloud during the driving process of the target vehicle; wherein the vehicle-related data includes vehicle-side status data and travel data of the target vehicle, and sensor data collected by the on-board sensors of the target vehicle;

[0020] A receiving module, used for receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0021] The navigation module is used to display the target three-dimensional model in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0022] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0023] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0024] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0025] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0026] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0027] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0028] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0029] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0030] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0031] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0032] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0033] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0034] The above-mentioned vehicle navigation method, device, computer equipment, storage medium and program product send the vehicle-related data of the target vehicle to the cloud; further, the cloud can determine the driving route of the target vehicle in real time based on the vehicle-related data of the target vehicle, map data and the road condition data collected by the roadside equipment of the road where the target vehicle is located, and complete the construction of the target three-dimensional model; further, the target vehicle receives the target three-dimensional model constructed by the cloud, and displays it in the form of a holographic image through the on-board display. This solution constructs a target three-dimensional model by integrating vehicle-related data, map data and the road condition data collected by the roadside equipment of the road where the target vehicle is located, laying a data foundation for the three-dimensional display of the navigation route; further, the navigation route is presented in the form of a holographic image to the on-board display device, which can improve the driver's navigation experience while achieving a more intuitive and comprehensive display of the navigation route. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] FIG1 is a diagram of an application environment of a vehicle navigation method provided in an embodiment of the present application;

[0037] FIG2 is a schematic diagram of a flow chart of a vehicle navigation method provided in an embodiment of the present application;

[0038] FIG3 is a flow chart of another vehicle navigation method provided in an embodiment of the present application;

[0039] FIG4 is a structural block diagram of a vehicle navigation device provided in an embodiment of the present application;

[0040] FIG5 is an internal structure diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] The vehicle navigation method provided by the embodiment of the present application can be applied in the application environment as shown in Figure 1. Among them, the target vehicle 102 communicates with the cloud 104 through the network. The data storage system can store the data that the cloud 104 needs to process. The data storage system can be integrated on the cloud 104 or placed on other network servers. The target vehicle 102 sends the vehicle-related data of the target vehicle to the cloud 104; then, the cloud 104 builds a target three-dimensional model based on the vehicle-related data, map data and the road condition data collected by the roadside equipment of the road where the target vehicle is located, and sends the target three-dimensional model to the target vehicle 102, and displays the target three-dimensional model through the target vehicle 102 to realize the navigation of the vehicle. Among them, the cloud 104 has powerful data processing and analysis capabilities, can receive and process massive road condition data from the target vehicle 102 and road infrastructure in real time, and through advanced technologies such as data mining and machine learning, deeply analyze the traffic data, extract valuable information and laws, and provide strong support for route navigation.

[0043] In an exemplary embodiment, as shown in FIG. 2 , a vehicle navigation method is provided, and the method is applied to the target vehicle 102 in FIG. 1 as an example for explanation. Optionally, the method can be executed by a control unit in the target vehicle 102, and specifically can include the following steps:

[0044] S201, while the target vehicle is driving, sending vehicle-related data of the target vehicle to the cloud.

[0045] Among them, the vehicle-related data may include but is not limited to the vehicle-side status data and travel data of the target vehicle, as well as the sensor data collected by the on-board sensors in the target vehicle.

[0046] Optionally, the vehicle-side status data may include but is not limited to data such as remaining power and / or remaining fuel, total mileage and tire pressure; travel data may include but is not limited to data such as the starting point and target point; sensor data may include but is not limited to accelerator data, rate sensor data, suspension sensor data, high-definition camera data, lidar data and millimeter-wave radar data, etc.

[0047] Exemplarily, during the driving process of the target vehicle, the vehicle-related data of the target vehicle can be collected regularly, such as the time interval for collecting the vehicle-related data of the target vehicle can be 10 minutes; further, each time the vehicle-related data of the target vehicle is collected, the collected vehicle-related data can be sent to the cloud 104 through the communication management module of the target vehicle, so that the cloud 104 can analyze the vehicle-related data.

[0048] It should be noted that the vehicle-related data of the target vehicle can come from various types of sensor data installed on the target vehicle to accurately reproduce the road shape, obstacle location, pedestrian dynamics and other contents.

[0049] S202, receiving the target three-dimensional model sent from the cloud.

[0050] Among them, the target three-dimensional model is constructed in the cloud based on map data, vehicle-related data and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes but is not limited to the driving route of the target vehicle.

[0051] It should be noted that the cloud 104 fits the target vehicle's driving environment based on the sensor data in the vehicle-related data and the road condition data collected by the roadside equipment of the target vehicle. Furthermore, through the three-dimensional reconstruction technology of the cloud 104, the fitted target vehicle's driving environment, vehicle-side status data, and travel data can be converted into a high-precision three-dimensional model. Then, based on the travel data and three-dimensional model of the target vehicle, a target three-dimensional model including the driving route can be obtained to achieve multi-angle and multi-level navigation display and navigation interaction.

[0052] Exemplarily, the cloud 104 compresses and encrypts the constructed target three-dimensional model, and sends the processed target three-dimensional model to the target vehicle 102 through high-speed communication technology. The target vehicle 102 receives the target three-dimensional model through the communication management module; then, the on-board computing unit on the target vehicle decompresses and decrypts the received target three-dimensional model for navigation of the target vehicle.

[0053] S203, displaying the target three-dimensional model in the form of a holographic image through an on-board display device in the target vehicle for navigation of the target vehicle.

[0054] Among them, the vehicle-mounted display equipment may include but is not limited to vehicle-mounted display screens, windshields, special screens and special glasses, etc., with characteristics such as high brightness, wide viewing angle and low latency to ensure that the driver can view navigation information clearly and comfortably under various light and driving speeds.

[0055] For example, the target three-dimensional model can be directly displayed in the form of a holographic image through the vehicle display screen; the target three-dimensional model can also be projected to a suitable position on the windshield; the target three-dimensional model can also be viewed in the form of a holographic image by wearing special glasses and other equipment, all of which can achieve a true restoration of the road environment and perform multi-angle and multi-level display and interaction. It should be noted that the display form of the holographic image can be combined with AR and / or VR technology, and by integrating the three-dimensional model with the virtual environment, it can provide the driver with intuitive and comprehensive navigation information.

[0056] The above-mentioned vehicle navigation method sends the vehicle-related data of the target vehicle to the cloud; further, the cloud can determine the driving route of the target vehicle in real time based on the vehicle-related data of the target vehicle, map data and the road condition data collected by the roadside equipment of the road where the target vehicle is located, and complete the construction of the target three-dimensional model; further, the target vehicle receives the target three-dimensional model constructed by the cloud, and displays it in the form of a holographic image through the on-board display. This solution constructs a target three-dimensional model by integrating vehicle-related data, map data and the road condition data collected by the roadside equipment of the road where the target vehicle is located, laying a data foundation for the three-dimensional display of the navigation route; further, the navigation route is presented in the form of a holographic image to the on-board display device, which can improve the driver's navigation experience while achieving a more intuitive and comprehensive display of the navigation route.

[0057] Based on the above-mentioned embodiments, the embodiment of the present application explains the target three-dimensional model in the above-mentioned embodiment S202 in detail. Specifically, the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after the route is planned based on the vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; the vehicle environment model is constructed based on sensor data.

[0058] Among them, road condition data can represent data such as road conditions, traffic flow, and pedestrian behavior in real time, and can come from intelligent sensing devices deployed in road infrastructure, such as roadside cameras, radars, and traffic lights.

[0059] Optionally, the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0060] Exemplarily, the cloud constructs the initial vehicle environment model based on the sensor data in the vehicle-related data, such as generating the initial vehicle environment model through algorithms such as point cloud registration and surface reconstruction; further, based on the road condition data, the key driving objects in the vehicle environment model are identified, wherein the key driving objects may include but are not limited to cars, electric vehicles, motorcycles, bicycles, pedestrians, guardrails and traffic lights, etc., such as the key driving objects can be identified based on the driving speed of each object in the road condition data and the captured driving picture and other data, and the vehicle environment model can also be semantically segmented and object recognized to extract key information such as roads, pedestrians and vehicles, and the optimization of the vehicle environment model can be completed, and the initial three-dimensional model can be obtained. Further, based on the map data in the cloud, the vehicle-side status data and travel data in the vehicle-related data, such as the starting location, target location, remaining power and / or remaining fuel, and driver preferences of the target vehicle, the most suitable driving route for the target vehicle can be determined, and then, the navigation information including the driving route of the target vehicle can be added to the initial three-dimensional model to obtain the target three-dimensional model.

[0061] It should be noted that in the process of constructing the initial vehicle environment model based on the sensor data in the vehicle-related data, an advanced sensor fusion algorithm can be used to synchronize the time and space of the data from different sensors to achieve seamless fusion of multi-source data and improve the integrity and accuracy of the three-dimensional vehicle environment reconstruction. Among them, the data in the sensor fusion algorithm is the data after data denoising to ensure the validity of the data; optionally, a denoising algorithm can be used to denoise the data, such as median filtering and Gaussian filtering algorithms.

[0062] In an embodiment of the present application, by comprehensively analyzing the vehicle status data, travel data, map data and sensor data, and constructing a target three-dimensional model including the target vehicle's driving route based on the results of the comprehensive analysis, a foundation is laid for achieving accurate navigation and three-dimensional display of the navigation route.

[0063] Based on the above embodiment, the present application embodiment explains the above embodiment S202 in detail. The present application embodiment involves the process after displaying the target three-dimensional model, specifically including: when an abnormal driving event is detected, adding warning prompt information to the displayed target three-dimensional model.

[0064] Among them, abnormal driving events may include but are not limited to sudden deceleration of the vehicle in front, insufficient remaining power and / or remaining fuel, and abnormal braking response; early warning prompt information may include but is not limited to warning reminders and accident rehearsal scenarios.

[0065] Optionally, when it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0066] Furthermore, if no response operation to the warning prompt information is detected within the set time period, an avoidance operation is performed according to the danger avoidance strategy corresponding to the abnormal driving event.

[0067] Exemplarily, the cloud can monitor the target vehicle in real time and make a real-time judgment on the probability of an accident involving the target vehicle by receiving vehicle-related data sent by the target vehicle in real time; if the probability of an accident involving the target vehicle is judged to be greater than a preset threshold, it is determined that an abnormal driving event is detected, that is, early warning information is added to the target three-dimensional model, and the latest target three-dimensional model is sent to the target vehicle; further, the early warning information in the target three-dimensional model can be displayed through the on-board display device in the target vehicle to remind the driver to pay attention to abnormal situations; further, if the driver is not detected to perform a corresponding operation on the early warning information within a predetermined period of time, in order to prevent an accident from occurring, the on-board computing unit on the target vehicle will determine the most appropriate avoidance operation from the preset danger avoidance strategy based on the abnormal driving event, and automatically execute the avoidance operation.

[0068] In the embodiment of the present application, by introducing early warning prompt information into the target three-dimensional model, accurate route navigation is achieved while ensuring driving safety.

[0069] Based on the above embodiment, this embodiment provides an optional example of a vehicle navigation method. As shown in FIG3 , the specific implementation process is as follows:

[0070] S301, while the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud.

[0071] Among them, vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, as well as sensor data collected by the on-board sensors in the target vehicle.

[0072] S302, receiving the target three-dimensional model sent from the cloud.

[0073] Among them, the target three-dimensional model is constructed in the cloud based on map data, vehicle-related data and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes the driving route of the target vehicle.

[0074] It should be noted that the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; the vehicle environment model is constructed based on sensor data.

[0075] The initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0076] S303, displaying the target three-dimensional model in the form of a holographic image through an on-board display device in the target vehicle.

[0077] S304: When an abnormal driving event is detected, a warning prompt message is added to the displayed target three-dimensional model.

[0078] Optionally, when it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0079] S305: If no response operation to the warning prompt information is detected within the set time period, an avoidance operation is performed according to a danger avoidance strategy corresponding to the abnormal driving event.

[0080] The specific process of the above S301-S305 can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0081] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0082] Based on the same inventive concept, the embodiment of the present application also provides a vehicle navigation device for implementing the vehicle navigation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle navigation device embodiments provided below can refer to the limitations on the vehicle navigation method above, and will not be repeated here.

[0083] In an exemplary embodiment, as shown in FIG. 4 , a vehicle navigation device 1 is provided, comprising: a sending module 10, a receiving module 20 and a navigation module 30, wherein:

[0084] The sending module 10 is used to send the vehicle-related data of the target vehicle to the cloud during the driving process of the target vehicle; wherein the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors in the target vehicle.

[0085] The receiving module 20 is used to receive the target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes the driving route of the target vehicle.

[0086] The navigation module 30 is used to display the target three-dimensional model in the form of a holographic image through an on-board display device in the target vehicle for navigation of the target vehicle.

[0087] In one embodiment, the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; the vehicle environment model is constructed based on sensor data.

[0088] In one embodiment, the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0089] In one embodiment, the vehicle navigation device 1 specifically further includes:

[0090] The abnormal event module is used to add warning prompt information to the displayed target three-dimensional model when an abnormal driving event is detected.

[0091] In one embodiment, the abnormal event module is further used to:

[0092] When it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0093] In one embodiment, the abnormal event module is further used to:

[0094] If no response operation to the warning prompt information is detected within the set time, the avoidance operation will be performed according to the danger avoidance strategy corresponding to the abnormal driving event.

[0095] Each module in the above vehicle navigation device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0096] In an exemplary embodiment, a computer device is provided, which may be a target vehicle, and its internal structure diagram may be shown in FIG5. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external vehicle and / or the cloud in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a vehicle navigation method is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0097] Those skilled in the art will understand that the structure shown in FIG. 5 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0098] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0099] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0100] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0101] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0102] In one embodiment, the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; the vehicle environment model is constructed based on sensor data.

[0103] In one embodiment, the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0104] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0105] When an abnormal driving event is detected, a warning prompt message is added to the displayed target three-dimensional model.

[0106] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0107] When it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0108] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0109] If no response operation to the warning prompt information is detected within the set time, the avoidance operation will be performed according to the danger avoidance strategy corresponding to the abnormal driving event.

[0110] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0111] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0112] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0113] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0114] In one embodiment, the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; the vehicle environment model is constructed based on sensor data.

[0115] In one embodiment, the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0116] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0117] When an abnormal driving event is detected, a warning prompt message is added to the displayed target three-dimensional model.

[0118] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0119] When it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0120] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0121] If no response operation to the warning prompt information is detected within the set time, the avoidance operation will be performed according to the danger avoidance strategy corresponding to the abnormal driving event.

[0122] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0123] When the target vehicle is driving, the vehicle-related data of the target vehicle is sent to the cloud; the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle;

[0124] Receiving a target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes a driving route of the target vehicle;

[0125] The target three-dimensional model is displayed in the form of a holographic image through the on-board display device in the target vehicle for navigation of the target vehicle.

[0126] In one embodiment, the target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on vehicle status data, travel data and map data; the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data; the vehicle environment model is constructed based on sensor data.

[0127] In one embodiment, the initial three-dimensional model is obtained by optimizing the vehicle environment model using road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

[0128] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0129] When an abnormal driving event is detected, a warning prompt message is added to the displayed target three-dimensional model.

[0130] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0131] When it is detected that the probability of an accident occurring to the target vehicle is greater than a set threshold, early warning information of the accident rehearsal scenario is added to the displayed target three-dimensional model.

[0132] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0133] If no response operation to the warning prompt information is detected within the set time, the avoidance operation will be performed according to the danger avoidance strategy corresponding to the abnormal driving event.

[0134] It should be noted that the information (including but not limited to vehicle information, route information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0135] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0136] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0137] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle navigation method, characterized in that: The method comprises: During the driving process of the target vehicle, the vehicle-related data of the target vehicle is sent to the cloud; wherein the vehicle-related data includes the vehicle-side status data and travel data of the target vehicle, and the sensor data collected by the on-board sensors of the target vehicle; Receiving the target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, the vehicle-related data, and road condition data collected by roadside equipment on the road where the target vehicle is located; the target three-dimensional model includes the driving route of the target vehicle; The target three-dimensional model is displayed in the form of a holographic image through an on-board display device in the target vehicle to facilitate navigation of the target vehicle.

2. The method according to claim 1, characterized in that: The target three-dimensional model is obtained by adding navigation information to the initial three-dimensional model in the cloud; wherein the navigation information includes the driving route of the target vehicle, and the navigation information is obtained after route planning based on the vehicle-side status data, the travel data and the map data; The initial three-dimensional model is obtained by optimizing the vehicle environment model using the road condition data; the vehicle environment model is constructed based on the sensor data.

3. The method according to claim 2, characterized in that The initial three-dimensional model is obtained by optimizing the vehicle environment model using the road condition data and identifying key objects of the optimized vehicle environment model; wherein the key objects include driving objects on the road where the target vehicle is located.

4. The method according to claim 1, characterized in that: After displaying the target three-dimensional model in the form of a holographic image through the on-board display device in the target vehicle, the method further includes: When an abnormal driving event is detected, a warning prompt message is added to the displayed target three-dimensional model.

5. The method according to claim 4, characterized in that The adding of warning information to the displayed target three-dimensional model includes: When it is detected that the probability of the target vehicle having an accident is greater than a set threshold, early warning prompt information of the accident rehearsal scene is added to the displayed target three-dimensional model.

6. The method according to claim 4, characterized in that In the case where an abnormal driving event is detected, after adding warning prompt information to the displayed target three-dimensional model, the method further includes: If no response operation to the warning prompt information is detected within the set time period, an avoidance operation is performed according to the danger avoidance strategy corresponding to the abnormal driving event.

7. A vehicle navigation device, characterized in that: The device comprises: A sending module, used to send vehicle-related data of the target vehicle to the cloud during the driving process of the target vehicle; wherein the vehicle-related data includes vehicle-side status data and travel data of the target vehicle, and sensor data collected by the on-board sensors of the target vehicle; A receiving module, used for receiving the target three-dimensional model sent from the cloud; wherein the target three-dimensional model is constructed by the cloud based on map data, the vehicle-related data and the road condition data collected by the roadside equipment of the road where the target vehicle is located; the target three-dimensional model includes the driving route of the target vehicle; The navigation module is used to display the target three-dimensional model in the form of a holographic image through an on-board display device in the target vehicle for navigation of the target vehicle.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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