Image display method and device, storage medium and electronic equipment

Abstract

The invention discloses an image display method and device, a storage medium and electronic equipment. The image display method comprises the following steps: determining vehicle driving data collected by a vehicle-mounted sensor in real time; determining display priorities of a plurality of obstacles in the current driving environment according to the vehicle driving data; and determining and displaying a target driving image according to the vehicle driving data and the display priority of each obstacle. According to the method, the display priorities of the multiple obstacles in the current driving environment are determined, the obstacle images needing more attention of a driver are preferentially displayed, the visual angle of the displayed images can be flexibly and automatically switched in the vehicle driving process without manual operation of a user, the obstacles in the emergency situation are preferentially displayed, and the user experience is improved. Therefore, the driver can obtain the dangerous obstacle information in time, and the driving safety can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent driving technology, and in particular to an image display method, device, storage medium and electronic device. Background Art

[0002] Faced with complex and ever-changing driving environments, it is crucial for safe driving for intelligent driving systems to perceive the surrounding environment in real time and accurately. Limited by the viewing angle and obstacle obstruction, it is difficult for drivers to achieve all-round monitoring. In order to solve the problems of limited viewing angle and obstacle obstruction, the relevant technology collects surrounding environment data through on-board sensors, processes and generates a 360-degree panoramic bird's-eye view, and intuitively displays it on the on-board central control screen so that the driver can view the vehicle's surrounding environment and improve driving safety. However, the image viewing angle displayed on the on-board central control screen in the relevant technology is generally fixed and requires manual operation to switch. It is impossible to flexibly and adaptively switch the viewing angle in combination with environmental changes and user needs, resulting in the driver being unable to obtain blind spot or obstacle information in a timely manner in an emergency. Summary of the invention

[0003] In order to solve the above technical problems, the present disclosure provides an image display method, device, storage medium and electronic device, which can flexibly and automatically switch viewing angles, give priority to displaying obstacles in emergency situations, so that the driver can obtain dangerous obstacle information in time and improve driving safety.

[0004] A first aspect of the present disclosure provides an image display method, comprising:

[0005] Determine the vehicle driving data collected by the vehicle-mounted sensors in real time;

[0006] Determining the display priority of multiple obstacles in the current driving environment according to the vehicle driving data;

[0007] A target driving image is determined and displayed according to the vehicle driving data and the display priority of each obstacle.

[0008] A second aspect of the present disclosure provides an image display device, comprising:

[0009] A first determination module is used to determine the vehicle driving data collected in real time by the vehicle-mounted sensor;

[0010] A second determination module, used to determine the display priority of multiple obstacles in the current driving environment according to the vehicle driving data;

[0011] A third determination module, configured to determine a target driving image according to the vehicle driving data and the display priority of each obstacle;

[0012] A display module is used to display the target driving image.

[0013] According to a third aspect of the present disclosure, a computer-readable storage medium is provided, wherein the storage medium stores a computer program for executing the image display method provided in the first aspect.

[0014] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; a memory for storing processor executable instructions; and a processor for reading executable instructions from the memory and executing the instructions to implement the image display method provided in the first aspect.

[0015] A fifth aspect of the present disclosure provides a computer program product. When instructions in the computer program product are executed by a processor, the image display method provided in the first aspect is executed.

[0016] The image display method provided by the present disclosure determines the display priority of multiple obstacles in the current driving environment according to the vehicle driving data, and gives priority to displaying the obstacle images that require more attention from the driver. The viewing angle of the displayed image can be flexibly and automatically switched during vehicle driving without manual operation by the user, and obstacles in emergency situations are displayed preferentially, so that the driver can obtain dangerous obstacle information in a timely manner, which helps to improve driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the right view displayed on the vehicle's central control screen;

[0018] Figure 2 is a schematic diagram of a target driving image displayed on a vehicle-mounted central control screen provided by an exemplary embodiment of the present disclosure;

[0019] Figure 3 is a schematic diagram of a target driving image displayed on a vehicle-mounted central control screen provided by another exemplary embodiment of the present disclosure;

[0020] Figure 4 is a schematic diagram of a target driving image displayed on a vehicle-mounted central control screen provided by another exemplary embodiment of the present disclosure;

[0021] Figure 5 is a flowchart of an image display method provided by an exemplary embodiment of the present disclosure;

[0022] Figure 6 is a flowchart of an image display method provided by another exemplary embodiment of the present disclosure;

[0023] Figure 7 is a flowchart of an image display method provided by another exemplary embodiment of the present disclosure;

[0024] Figure 8is a flowchart of an image display method provided by yet another exemplary embodiment of the present disclosure;

[0025] Fig. 9 is a flowchart of an image display method provided by another exemplary embodiment of the present disclosure;

[0026] Fig.10 is a flowchart of an image display method provided by yet another exemplary embodiment of the present disclosure;

[0027] Fig.11 is a schematic diagram of the structure of an image display device provided by an exemplary embodiment of the present disclosure;

[0028] Fig.12 is a schematic diagram of the structure of an image display device provided by another exemplary embodiment of the present disclosure;

[0029] Fig.13 is a schematic diagram of the composition structure of an image display device provided by another exemplary embodiment of the present disclosure;

[0030] Fig.14 It is a schematic diagram of the composition structure of an electronic device provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0031] To explain the present disclosure, example embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. It should be understood that the present disclosure is not limited to the example embodiments.

[0032] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

[0033] Application Overview

[0034] With the rapid development of intelligent driving technology, the functions provided by intelligent driving vehicles are becoming more and more abundant. The 360° panoramic view function displayed on the vehicle's central control screen has become a powerful assistant for drivers, especially when driving in complex scenes. The 360° panoramic image displayed on the vehicle's central control screen can greatly improve driving safety. This function collects images of the surrounding environment through multiple cameras distributed around the vehicle, and generates a 360° panoramic bird's-eye view of the vehicle's surroundings through processing by the intelligent driving system, and displays it on the vehicle's central control screen. You can also switch the perspective to display images of other perspectives around the vehicle (such as front view and rear view) on the vehicle's central control screen.

[0035] In the prior art, the image viewing angle displayed on the vehicle's central control screen is generally fixed, and the user needs to manually operate on the screen to switch to other viewing angles. During driving, the driver's manual switching of the screen display image will distract the driver from driving, posing a safety hazard. Especially in emergency situations where there are dangerous obstacles around the vehicle, manually switching the viewing angle may cause a traffic accident, but not switching the viewing angle will cause the driver to be unable to obtain blind spot or obstacle information in a timely manner, which may also cause a safety accident.

[0036] In order to solve the problem in the related art that the viewing angle of the image displayed on the vehicle central control screen is fixed and manual operation is required to switch the viewing angle, the present disclosure provides an image display method, which determines the display priority of multiple obstacles in the current driving environment according to the vehicle driving data, and gives priority to displaying obstacle images that require more attention from the driver. The viewing angle of the displayed image can be flexibly and automatically switched during vehicle driving without manual operation by the user, and obstacles in emergency situations are displayed preferentially, so that the driver can obtain information about dangerous obstacles in a timely manner, which helps to improve driving safety.

[0037] Exemplary Systems

[0038] First, the application scenarios of the present disclosure are introduced. During driving, the intelligent driving vehicle collects environmental information around the vehicle through multiple sensors installed around the vehicle, and generates a 360° panoramic bird's-eye view, point cloud map, or thermal image around the vehicle through the intelligent driving system. The driver can view the blind spots or obstacle information around the vehicle through the panoramic map, point cloud map, thermal image or any perspective map displayed on the vehicle's central control screen to improve driving safety.

[0039] Among them, the sensors around the vehicle may include on-board cameras, laser radars, millimeter-wave radars, ultrasonic radars, infrared sensors and other sensors. The types and dimensions of the various data collected by different types of sensors are different. For example, the types of images collected by on-board cameras and the types of echo signals collected by ultrasonic radars are different. For example, the dimensions of two-dimensional images collected by on-board cameras and three-dimensional point clouds collected by millimeter-wave radars are different. The data from various sensors are processed by the intelligent driving system to generate panoramic images, point cloud images, thermal images or any perspective images. For example, Figure 1 This is a schematic diagram of the right view of the vehicle's central control screen display. Figure 1 As shown, in the right view, the driver cannot intuitively see the distance between the vehicle and the pedestrian 1 through the image displayed on the vehicle's central control screen.

[0040] In the related art, in order to know the distance between the vehicle and the pedestrian 1, the driver needs to manually operate the on-board central control screen to switch the viewing angle to a top view, a front view, or a rear view. During driving, the driver's manual switching of the screen display image will distract the driver from driving, posing a safety hazard. Especially in an emergency situation where there are pedestrians 1 around the vehicle who may be close to the vehicle, looking down at the screen when manually switching the viewing angle may cause a traffic accident, but not switching the viewing angle will cause the driver to be unable to obtain the distance between the vehicle and the pedestrian 1 in a timely manner, which may also cause a safety accident.

[0041] In the embodiment of the present disclosure, the vehicle driving data collected by the vehicle-mounted sensor in real time is first obtained; then, according to the vehicle driving data, the current driving environment is determined. Figure 1 The display priority of multiple obstacles such as other vehicles and pedestrians around the vehicle is determined; finally, the target driving image is determined and displayed according to the vehicle driving data and the display priority of each obstacle. Figure 1 Among the obstacles such as other vehicles and pedestrians around the vehicle, pedestrian 1 has the highest display priority, then a target driving image for pedestrian 1 is determined according to the vehicle driving data, and the target driving image is displayed on the vehicle middle screen. For example, Figure 2 The target driving image shown is a top view. The driver can flexibly and automatically switch the viewing angle of the displayed image during the driving process without manual operation. Figure 2 The top view shown can obtain dangerous obstacle information in a timely manner, which helps to improve driving safety.

[0042] For example, when displaying the target driving image, it can be as follows Figure 2 The full screen display of the target driving image can also be shown as Figure 3 As shown, in the current display image (i.e. Figure 1 The target driving image is displayed in a pop-up window on the right view shown in FIG. Figure 4 As shown, the target driving image is displayed in full screen, and the current display image is displayed in a pop-up window. In actual applications, other possible displays can also be used for display, which is not limited in the embodiments of the present disclosure.

[0043] Exemplary Methods

[0044] Figure 5 FIG. 1 is a flow chart of an image display method provided by an exemplary embodiment of the present disclosure. This embodiment can be applied to electronic devices, such as Figure 5 As shown, the image display method may include the following steps:

[0045] Step S501, determining the vehicle driving data collected in real time by the vehicle-mounted sensor.

[0046] The image display method provided by the embodiments of the present disclosure can be applied to an intelligent driving system, and specifically can be applied to an image display device in an intelligent driving system.

[0047] In addition to the image display device, the intelligent driving system also includes a plurality of vehicle-mounted sensors installed on the intelligent driving vehicle, which are used to collect vehicle driving data in real time.

[0048] Exemplarily, the vehicle-mounted sensors may include a first sensor for collecting driving data of the vehicle and a second sensor for collecting surrounding environment data of the vehicle.

[0049] Exemplarily, the first sensor may include, but is not limited to: a gear position sensor and a wheel speed sensor, wherein the gear position sensor is used to detect the gear position state of the vehicle, and the wheel speed sensor is used to monitor the wheel speed in real time.

[0050] Exemplarily, the second sensor may include but is not limited to at least one of the following: a vehicle-mounted camera, a laser radar, a millimeter-wave radar, an ultrasonic radar, an infrared sensor, a light sensor, etc. There may be multiple various vehicle-mounted sensors, which are arranged at different positions around the vehicle to obtain environmental information around the vehicle. Specifically, the vehicle-mounted camera is used to collect image data of the vehicle's surroundings, the laser radar is used to collect point cloud data of the vehicle's surroundings, and the millimeter-wave radar and ultrasonic radar are mainly used to collect data such as the distance and speed of surrounding obstacles. Infrared sensors are used to monitor obstacles such as pedestrians and animals in dark environments such as at night. The light sensor is used to monitor the light intensity of the current driving environment.

[0051] Exemplarily, corresponding to the vehicle-mounted sensors, the vehicle driving data may include vehicle data and environmental data. The vehicle data is the data collected by the first sensor, which may include but is not limited to: gear status, wheel speed, tire pressure, tire temperature, battery temperature, etc. The environmental data is the data collected by the second sensor, which may include but is not limited to: image data, point cloud data, millimeter wave data, ultrasonic data, infrared data, light intensity, etc.

[0052] Step S502: Determine the display priority of multiple obstacles in the current driving environment according to the vehicle driving data.

[0053] According to the vehicle driving data collected in the previous step, target detection is performed to identify obstacles in the current driving environment. Generally, the driving environment of the vehicle includes multiple obstacles, and the image processing device determines the display priority of these obstacles based on the vehicle driving data.

[0054] For example, the display priority may be related to factors such as obstacle type, distance, speed, motion trend, and vehicle status. The image processing device may determine the display priority of each obstacle based on one or more of the factors such as obstacle type, distance, speed, motion trend, and vehicle status, or other factors. Generally, the higher the potential collision risk of an obstacle, the higher its corresponding display priority.

[0055] For example, the vehicle's current driving environment is Figure 1 As shown, the obstacles in the current driving environment include vehicle 1, vehicle 2, pedestrian 1, pedestrian 2 and pedestrian 3. According to the vehicle driving data, the display priority of these obstacles is determined from high to low as pedestrian 1>vehicle 1>vehicle 2>pedestrian 2>pedestrian 3.

[0056] Step S503: determining a target driving image according to the vehicle driving data and the display priority of each obstacle.

[0057] Based on the vehicle driving data and the display priority of each obstacle, a target driving image is generated, and the target driving image may include a target obstacle. The target obstacle is an obstacle whose display priority satisfies the display condition. Exemplarily, the display condition may be to display the obstacle with the highest display priority, or to display the obstacles whose display priority exceeds a preset threshold, or to display each obstacle after distinguishing and marking them according to different display priorities. In actual applications, other conditions may also be used, which are not limited in the embodiments of the present disclosure.

[0058] Exemplarily, the determined target driving image may be Figure 2 , Figure 3 or Figure 4 The image shown may also be an image from another perspective. The target driving image includes a target obstacle, such as pedestrian 1. The driver determines from the target driving image that the distance between pedestrian 1 and the vehicle is large, and the vehicle can pass safely. Alternatively, the driver determines from the target driving image that the distance between pedestrian 1 and the vehicle is small, and needs to slow down to ensure driving safety.

[0059] In some embodiments, the target obstacle in the target driving image can be enlarged, colored, circled, etc. to present the target obstacle more clearly, ensuring that the driver can obtain more intuitive and accurate obstacle information for reference and quick decision-making.

[0060] Step S504: display the target driving image.

[0061] The image display device outputs the target driving image on the vehicle's central control screen. The target driving image is determined and displayed by display priority. The viewing angle of the displayed image can be flexibly and automatically switched during vehicle driving without the need for manual operation by the driver. The driver can obtain blind spot or dangerous obstacle information in a timely manner based on the target driving image for reference and decision-making, which helps to improve driving safety.

[0062] The image display method provided by the embodiment of the present disclosure first determines the vehicle driving data collected in real time by the vehicle-mounted sensor; then determines the display priority of multiple obstacles in the current driving environment based on the vehicle driving data; and finally determines and displays the target driving image based on the vehicle driving data and the display priority of each obstacle. By determining the display priority of multiple obstacles in the current driving environment, the obstacle images that require more attention from the driver are displayed first, and the viewing angle of the displayed image can be flexibly and automatically switched during the driving process of the vehicle without manual operation by the user, and obstacles in emergency situations are displayed first, so that the driver can obtain dangerous obstacle information in a timely manner, which helps to improve driving safety and can solve the problem in the related technology that the user needs to manually operate to switch the viewing angle of the image displayed on the vehicle central control screen.

[0063] In some embodiments, based on the above embodiments, step S502 in the above embodiments, "determining the display priority of multiple obstacles in the current driving environment according to the vehicle driving data", may include: Figure 6 The following steps S5021 to S5023 are shown:

[0064] Step S5021, determining the vehicle state according to the vehicle data in the vehicle driving data.

[0065] The vehicle data may include not only the gear position and wheel speed, but also the engine status, which may include the engine off status, the start-up stationary status, the forward driving status, the reverse driving status, and the parking driving status.

[0066] The current state of the vehicle is determined according to the gear state, engine state and wheel speed included in the vehicle data. For example, when the engine state is off, the vehicle can be considered to be in an off state; when the engine state is running and the wheel speed is 0, the vehicle can be considered to be in a starting and stationary state; when the gear is in the forward gear and the wheel speed is greater than 0, the vehicle can be considered to be in a forward driving state; when the gear is in the reverse gear and the wheel speed is less than 0, the vehicle can be considered to be in a reverse driving state; when the gear is in the parking gear, the vehicle can be considered to be in a parking driving state.

[0067] Step S5022: performing collision risk assessment based on the environment data and vehicle data in the vehicle driving data to determine the collision risk levels of multiple obstacles in the current driving environment.

[0068] Among them, based on the above embodiment, the vehicle data may also include the vehicle position and steering angle. The environmental data may include image data, point cloud data, millimeter wave data, ultrasonic data, infrared data, and light intensity. According to the environmental data and vehicle data in the vehicle driving data, the collision risk of each obstacle in the current driving environment is evaluated to obtain the collision risk level of each obstacle. The greater the collision risk corresponding to the obstacle, the higher its collision risk level.

[0069] Step S5023, determining the display priority of multiple obstacles in the current driving environment according to the vehicle state and the collision risk levels of the multiple obstacles.

[0070] The display priority refers to the display priority of each obstacle. On the vehicle display screen, the obstacle images with high priority are displayed first, and the obstacles with low priority are displayed later.

[0071] For example, the display priority of each obstacle is determined according to the current vehicle state of the vehicle and the collision risk level of multiple obstacles in the current driving environment. For example, when the vehicle is in an ignition-off state or a static state, the collision possibility of obstacles around the vehicle is balanced for the vehicle. At this time, the weights of obstacles around the vehicle can be set to be the same, and the display priority of each obstacle can be determined according to the collision risk level of each obstacle. For example, the higher the collision risk level of the obstacle, the higher the display priority; the lower the collision risk level of the obstacle, the lower the display priority.

[0072] In the disclosed embodiment, the vehicle state and the collision risk level of multiple obstacles around the vehicle are first determined based on the vehicle driving data, and then the display priority of each obstacle is determined based on the vehicle state and the collision risk level of each obstacle. The display order of each obstacle is determined by the priority, and obstacles in emergency situations are displayed first, so that the driver can obtain dangerous obstacle information in a timely manner, thereby improving driving safety.

[0073] In one implementation, the collision risk level of each obstacle in the current driving environment can be determined according to the collision time. Based on the above embodiment, step S5022 in the above embodiment, "performing a collision risk assessment according to the environmental data and vehicle data in the vehicle driving data to determine the collision risk level of multiple obstacles in the current driving environment", can include the following steps: Figure 7 The following steps S50221 to S50223 are shown:

[0074] Step S50221, performing obstacle detection according to the environmental data in the vehicle driving data, and determining multiple obstacles in the current driving environment and motion information of each obstacle.

[0075] Exemplarily, the movement information of the obstacle may include the speed and distance of the obstacle. The image display device performs obstacle detection based on the image data and point cloud data included in the environmental data, determines multiple obstacles around the vehicle, and determines the speed of each obstacle and the distance between the obstacle and the vehicle based on the point cloud data, millimeter wave data, and ultrasonic data.

[0076] Step S50222: predicting the collision time between the vehicle and each obstacle based on the motion information of each obstacle and the vehicle data.

[0077] The speed of the vehicle is calculated based on the wheel speed included in the vehicle data. Then, the relative speed of each obstacle and the vehicle is calculated based on the speed of each obstacle and the vehicle. Finally, the time to collision (TTC) between the vehicle and each obstacle is calculated based on the relative speed and distance between each obstacle and the vehicle. The speed of the vehicle is recorded as V, and the speed of the i-th obstacle is recorded as V i , the distance between the i-th obstacle and the vehicle is recorded as d i , then the collision time TTC between the vehicle and the i-th obstacle is i , can be calculated according to the following formula (1):

[0078]

[0079] Wherein, i=2, ..., N, N is a natural number greater than 2, indicating the number of obstacles detected.

[0080] It should be noted that N can also be 0 or 1. When N is 0, that is, there is no obstacle around the vehicle, and the target driving image of any perspective can be determined based on the vehicle driving data. When N is 1, that is, there is only one obstacle around the vehicle, and the target driving image for the obstacle can be determined based on the vehicle driving data.

[0081] Step S50223, determining the collision risk level of each obstacle according to the collision time between the vehicle and each obstacle.

[0082] After the collision time between the vehicle and each obstacle is determined, the collision risk level of each obstacle is determined according to the collision time corresponding to each obstacle.

[0083] In one example, the collision time corresponding to each obstacle can be compared with the preset threshold value. When the collision time TTC of the i-th obstacle is iWhen the collision time is less than the first preset threshold, the collision risk level of the ith obstacle is determined as high risk, and the collision risk levels of the remaining obstacles whose collision time is greater than or equal to the first preset threshold are determined as low risk. The first preset threshold can be 3s (seconds).

[0084] In another example, the collision times corresponding to the obstacles may be compared, and the collision risk level of the obstacle with the shortest collision time may be determined as high risk, while the collision risk levels of the remaining obstacles except the obstacle with the shortest collision time may be determined as low risk.

[0085] In actual applications, the collision risk level of each obstacle may also be determined based on other methods, which are not limited in the embodiments of the present disclosure.

[0086] In the disclosed embodiment, the collision time between the vehicle and each obstacle is determined, and the collision risk level of each obstacle is determined based on the collision time corresponding to each obstacle, so as to provide data support for determining the display priority of the obstacles.

[0087] In another implementation, the collision risk level of each obstacle in the current driving environment can be determined according to the spatial distance. Exemplarily, obstacle detection is first performed according to the environmental data in the vehicle driving data to determine the relative distance between multiple obstacles in the current driving environment and the vehicle and each obstacle. Then, the collision risk level of each obstacle is determined according to the magnitude relationship between the relative distance corresponding to each obstacle and the second preset threshold. Specifically, when the relative distance corresponding to the obstacle is less than the second preset threshold, the collision risk level of the obstacle is determined as high risk, and the collision risk level of the remaining obstacles whose relative distance is greater than or equal to the second preset threshold among all obstacles is determined as low risk. Among them, for different types of obstacles, the corresponding second preset threshold can be different values, for example, for pedestrians, the second preset threshold can be 1m (meter), and for vehicles, the second preset threshold can be 3m (meter). In practical applications, the appropriate second preset threshold can be set in combination with specific scenarios, which is not limited in the embodiments of the present disclosure.

[0088] In another implementation, the collision risk level of each obstacle in the current driving environment can be determined based on the collision time and spatial distance. For example, if the collision time corresponding to the obstacle is less than the first preset threshold, and the relative distance is less than the second preset threshold, the collision risk level of the obstacle is determined to be high risk. If the collision time corresponding to the obstacle is less than the first preset threshold, and the relative distance is greater than or equal to the second preset threshold, or if the collision time corresponding to the obstacle is greater than or equal to the first preset threshold, and the relative distance is less than the second preset threshold, the collision risk level of the obstacle is determined to be medium risk. If the collision time corresponding to the obstacle is greater than or equal to the first preset threshold, and the relative distance is greater than or equal to the second preset threshold, the collision risk level of the obstacle is determined to be low risk.

[0089] It should be noted that in actual applications, the collision risk level of an obstacle may also be determined by other methods, which are not limited in the embodiments of the present disclosure.

[0090] In some embodiments, based on the above embodiments, step S5023 in the above embodiments, “determining the display priority of multiple obstacles in the current driving environment according to the vehicle state and the collision risk level of multiple obstacles”, may include: Figure 8 The following steps S50231 to S50234 are shown:

[0091] Step S50231, determining display weights corresponding to multiple perspectives according to the vehicle state.

[0092] For example, the main perspective that the driver focuses on is different in different driving states, and the weight of each perspective is preset according to the vehicle state and stored in the corresponding relationship table. During the driving process of the vehicle, the corresponding relationship table is queried according to the current state of the vehicle to obtain the display weight corresponding to each perspective in the current vehicle state.

[0093] Exemplarily, when setting the preset display weight of each perspective, a larger weight may be assigned to the main perspective, and a smaller weight may be assigned to the auxiliary perspective.

[0094] When the vehicle is in an ignition-off state or in a stationary state, obstacles at various viewing angles around the vehicle have the same collision risk to the vehicle, so the preset display weights of various viewing angles in the correspondence table may be equal, for example, all 1.

[0095] When the vehicle is in a forward driving state, the driver is more concerned about the collision risk of obstacles in the front view of the vehicle, followed by the collision risk of obstacles in the side view, and then the collision risk of obstacles in the rear view. Therefore, it can be set: the preset display weight of the front view > the preset display weight of the side view > the preset display weight of the rear view. For example, in the corresponding relationship table, the preset display weight of the front view can be 1.5, the preset display weight of the side view can be 1, and the preset display weight of the rear view can be 0.8.

[0096] When the vehicle is in reverse driving state, the driver is more concerned about the collision risk of obstacles in the rear view angle of the vehicle, the second is the rear-end collision risk of obstacles in the side view angle, and the third is the collision risk of obstacles in the front view angle. Therefore, it can be set: the preset display weight of the rear view angle > the preset display weight of the side view angle > the preset display weight of the front view angle. For example, the preset display weight of the rear view angle can be 1.5, the preset display weight of the side view angle can be 1, and the preset display weight of the front view angle can be 0.8.

[0097] When the vehicle is in a parking state, the driver is more concerned about the collision risk of obstacles within a certain range around the vehicle, and secondly, the collision risk of other obstacles beyond the range. Therefore, it can be set that the preset display weight of the close-range view within the preset range of the vehicle is greater than the preset display weight of the long-range view beyond the preset range of the vehicle. For example, the preset display weight of the view within 5m of the vehicle in the corresponding relationship table can be 1.5, and the preset display weight of the view outside 5m of the vehicle can be 0.8.

[0098] Step S50232, determine the viewing angle of each obstacle.

[0099] For example, the visual angle of the obstacle can be determined based on the relative distance between the obstacle and the vehicle, wherein the relative distance includes a lateral relative distance and a longitudinal relative distance, and the visual angle of the obstacle relative to the vehicle can be determined based on the ratio between the longitudinal relative distance and the lateral relative distance. Figure 1 As shown, for the vehicle, pedestrian 1 is located at the right perspective, pedestrian 2 is located at the front perspective, pedestrian 3 is located at the rear perspective, and vehicle 1 and vehicle 2 are located at the left perspective.

[0100] Step S50233, determining the display weight corresponding to each obstacle according to the display weight corresponding to each viewing angle and the viewing angle at which each obstacle is located.

[0101] For example, the display weight corresponding to each obstacle can be determined according to the display weight corresponding to each viewing angle and the viewing angle at which each obstacle is located. Figure 1For example, if the vehicle is in a forward driving state, the preset display weight of the front perspective in the corresponding relationship table is 1.5, the preset display weight of the side perspective is 1, and the preset display weight of the rear perspective is 0.8. Pedestrian 1 is located in the right perspective, pedestrian 2 is located in the front perspective, pedestrian 3 is located in the rear perspective, and vehicles 1 and 2 are located in the left perspective. Then the display weight corresponding to pedestrian 1 is 1, the display weight corresponding to pedestrian 2 is 1.5, the display weight corresponding to pedestrian 3 is 0.8, and the display weight corresponding to vehicles 1 and 2 is 1.

[0102] Step S50234: Determine the display priority of each obstacle in the current driving environment according to the display weight corresponding to each obstacle and the collision risk level of each obstacle.

[0103] In the embodiment of the present disclosure, the image display device may determine the display priority of the obstacle according to the display weight corresponding to the obstacle and the collision risk level thereof.

[0104] For example, the collision risk level of each obstacle can be a qualitative value, and the corresponding display priority is determined according to the corresponding relationship between the display weight corresponding to each obstacle and the qualitative value. For example, the display weights corresponding to each obstacle are 1.5, 1, and 0.8 as described above, and the display priority of each obstacle can be shown in the following Table 1:

[0105] Table 1 Display priority of an obstacle

[0106] Display weight corresponding to obstacles Collision risk level of obstacles Obstacle display priority 1.5 High risk 1 1.5 Medium risk 4 1.5 Low risk 7 1 High risk 2 1 Medium risk 5 1 Low risk 8 0.8 High risk 3 0.8 Medium risk 6 0.8 Low risk 9

[0107] For example, the collision risk level of each obstacle can correspond to a preset risk value, and the display value of the obstacle is calculated according to the display weight corresponding to the obstacle * the risk value corresponding to the collision risk level of the obstacle, and then the display values ​​of each obstacle are compared. The larger the display value, the higher the display priority. For example, the risk values ​​corresponding to high risk, medium risk, and low risk are 2, 1, and 0.5 respectively, and the display weights corresponding to each obstacle are 1.5, 1, and 0.8, then the display priority of each obstacle can be determined as shown in Table 2 below:

[0108] Table 2 Display priority of another obstacle

[0109]

[0110]

[0111] It should be noted that the display priorities of the obstacles may be different or partially the same. For example, if the display priorities of two obstacles are both a, then the two obstacles have the same priority and may be displayed or not.

[0112] In some embodiments, the display priority of obstacles can also be determined by considering factors such as the distance and speed of the obstacles. For example, when there are multiple obstacles with the same collision risk level in the same viewing angle, the display priority of the multiple obstacles determined in the above manner is the same. Furthermore, the display priority of multiple obstacles with the same display priority can also be determined in the order of "distance>speed", that is, the display priority of obstacles with a short distance is high, the display priority of obstacles with a long distance is low, the display priority of obstacles with a high speed is high, and the display priority of obstacles with a low speed is low.

[0113] In some embodiments, the display priority of obstacles can also be determined by considering factors such as the type and size of the obstacle. For example, a living obstacle has a high display priority, while a non-living obstacle has a low display priority. A larger obstacle has a high display priority, while a smaller obstacle has a low display priority.

[0114] In practical applications, other factors may also be considered to determine the obstacle display priority, which is not limited in the embodiments of the present disclosure.

[0115] In the disclosed embodiment, the display weight of each obstacle is determined according to the vehicle state and the viewing angle of each obstacle. The display weight of the obstacle is combined with the collision risk level of the obstacle to determine the display priority of the obstacle. The display priority of each obstacle can be clearly determined through the display priority, providing data support for determining the target driving image.

[0116] In some embodiments, based on the above embodiments, the step S503 in the above embodiments of “determining the target driving image according to the vehicle driving data and the display priority of each obstacle” may include: Fig. 9 The following steps S5031 and S5032 are shown:

[0117] Step S5031: Determine the target obstacle according to the display priority of each obstacle.

[0118] The image display device determines the target obstacle from all obstacles according to the display priority of each obstacle. For example, the obstacle with the highest display priority among all obstacles can be determined as the target obstacle, so that the driver can view the image of the target obstacle that should be paid the most attention to; or the first M obstacles in display priority among all obstacles can be determined as the target obstacle, so that the driver can view the images of multiple target obstacles.

[0119] Step S5032: determining a target driving image for the target obstacle according to the environmental data in the vehicle driving data.

[0120] After the target obstacle is determined, a target driving image for the target obstacle is determined based on the environmental data in the vehicle driving data.

[0121] Exemplarily, the target driving image may be a two-dimensional image including the target obstacle, a three-dimensional point cloud image including the target obstacle, or an infrared thermal image including the target obstacle. When displaying the target driving image, any one of the two-dimensional image, three-dimensional point cloud image, and infrared thermal image of the target obstacle may be selected for display, or a better one may be selected for display in combination with the current driving environment. For example, when driving at night, the two-dimensional image captured by the on-board camera is dark due to the influence of light. At this time, the infrared thermal image may be selected as the target driving image so that the driver can quickly see the location of the target obstacle and ensure safe driving.

[0122] For example, the target driving image may include multiple obstacles, and the target obstacles may be marked so that the driver can more intuitively and quickly distinguish the target obstacles. For example, the target obstacles may be marked by enlarging, coloring, circling, etc.

[0123] Exemplarily, the target driving image may also include text prompt information for the target obstacle, such as collision time, obstacle speed, distance and other information, so that the driver can obtain the obstacle information more intuitively.

[0124] In the disclosed embodiment, the target obstacle is determined according to the display priority, and then the target driving image for the target obstacle is obtained, and the obstacle image that requires more attention from the driver is displayed preferentially, so that the driver can obtain dangerous obstacle information in a timely manner, which helps to improve driving safety.

[0125] In some embodiments, the present disclosure further provides an image display method. Fig.10 It is a flowchart of an image display method provided by yet another exemplary embodiment of the present disclosure.

[0126] Step S1001, determining the vehicle driving data collected in real time by the vehicle-mounted sensor.

[0127] Exemplarily, the vehicle-mounted sensors may include a first sensor for collecting driving data of the vehicle and a second sensor for collecting surrounding environment data of the vehicle.

[0128] Exemplarily, the first sensor may include but is not limited to at least one of the following: a gear position sensor, a wheel speed sensor, a tire pressure sensor, a temperature sensor, etc. Among them, the gear position sensor is used to detect the gear position state of the vehicle, the wheel speed sensor is used to monitor the wheel speed in real time, and the tire pressure sensor is used to monitor the tire pressure in real time. There may be multiple temperature sensors to monitor the temperature at different locations of the vehicle, such as a temperature sensor for monitoring the tire temperature, and a temperature sensor for monitoring the battery temperature.

[0129] Exemplarily, the second sensor may include but is not limited to at least one of the following: a vehicle-mounted camera, a laser radar, a millimeter-wave radar, an ultrasonic radar, an infrared sensor, a light sensor, etc. There may be multiple various vehicle-mounted sensors, which are arranged at different positions around the vehicle to obtain environmental information around the vehicle. Specifically, the vehicle-mounted camera is used to collect image data of the vehicle's surroundings, the laser radar is used to collect point cloud data of the vehicle's surroundings, and the millimeter-wave radar and ultrasonic radar are mainly used to collect data such as the distance and speed of surrounding obstacles. Infrared sensors are used to monitor obstacles such as pedestrians and animals in dark environments such as at night. The light sensor is used to monitor the light intensity of the current driving environment.

[0130] Exemplarily, corresponding to the vehicle-mounted sensors, the vehicle driving data may include vehicle data and environmental data. The vehicle data is the data collected by the first sensor, which may include but is not limited to: gear status, wheel speed, tire pressure, tire temperature, battery temperature, etc. The environmental data is the data collected by the second sensor, which may include but is not limited to: image data, point cloud data, millimeter wave data, ultrasonic data, infrared data, light intensity, etc.

[0131] Step S1002: Determine the display priority of multiple obstacles in the current driving environment according to the vehicle driving data.

[0132] Exemplarily, the vehicle driving data may include vehicle data and environment data. Target detection is performed based on the environment data in the vehicle driving data to identify obstacles in the current driving environment. The display priority of the obstacles in the current driving environment is then determined based on the vehicle driving data.

[0133] For example, if no obstacle is detected according to the environmental data in the vehicle driving data, a target driving image of any perspective can be determined and displayed according to the vehicle driving data. If an obstacle is detected according to the environmental data in the vehicle driving data, that is, there is only one obstacle around the vehicle, a target driving image for the obstacle is determined according to the vehicle driving data.

[0134] Generally, the driving environment of the vehicle includes multiple obstacles, and the image processing device determines the display priority of these obstacles based on the vehicle driving data. In one implementation, when determining the display priority of multiple obstacles in the current driving environment, the vehicle state can be first determined based on the vehicle data in the vehicle driving data; wherein the vehicle data can include data such as gear state, wheel speed, tire pressure, tire temperature, battery temperature, engine state, etc.; the vehicle state can include engine off state, start stationary state, forward driving state, reverse driving state, and parking driving state. Then, a collision risk assessment is performed based on the environmental data and vehicle data in the vehicle driving data to determine the collision risk level of multiple obstacles in the current driving environment; finally, the display priority of multiple obstacles in the current driving environment is determined based on the vehicle state and the collision risk level of multiple obstacles.

[0135] In some embodiments, when determining the collision risk level of each obstacle in the current driving environment, the collision risk level of each obstacle in the current driving environment can be determined according to methods such as collision time and spatial distance, and the collision risk level of obstacles that meet the display conditions is determined as high risk. In actual applications, the collision risk level of obstacles can also be determined by other methods, which are not limited in the embodiments of the present disclosure.

[0136] In some embodiments, the display priority of multiple obstacles in the current driving environment can be determined according to the vehicle state and the collision risk level of each obstacle. Specifically, firstly, the display weights corresponding to multiple perspectives are determined according to the vehicle state; secondly, the perspective of each obstacle is determined; then, the display weight corresponding to each perspective and the perspective of each obstacle are determined; finally, the display priority of each obstacle in the current driving environment is determined according to the display weight corresponding to each obstacle and the collision risk level of each obstacle. In actual applications, the display priority of obstacles can also be determined by other methods, which are not limited in the embodiments of the present disclosure.

[0137] Step S1003, determining the display priority of the vehicle fault when it is determined that the vehicle has a fault based on the vehicle driving data.

[0138] In addition to displaying blind spots or obstacle information outside the vehicle, the in-vehicle central control screen can also display information inside the vehicle that requires the driver's attention, such as a low tire pressure prompt. For example, the image display device can determine whether the vehicle has a fault based on the vehicle data included in the vehicle driving data, and if the vehicle has a fault, determine the risk level of the vehicle fault.

[0139] For example, the display priority of the vehicle fault can be determined according to the type and severity of the vehicle fault. The more serious the fault (such as engine fault), the higher the risk level, and the less serious the fault (such as headlight fault), the lower the risk level.

[0140] Exemplarily, step S1002 may be executed before step S1003, or may be executed after step S1003, or may be executed concurrently, which is not limited in the embodiments of the present disclosure.

[0141] Step S1004: determining a target driving image according to the vehicle driving data, the display priority of each obstacle and the display priority of the vehicle fault.

[0142] Based on the vehicle driving data, the display priority of each obstacle and the display priority of the vehicle fault, a target driving image is generated, and the target driving image may include a target obstacle and / or vehicle fault information. The target obstacle may be an obstacle with the highest display priority, and the vehicle fault information may be an image of the current fault area of ​​the vehicle or text information of the fault.

[0143] In actual applications, the target driving image may also include more images or information that require the driver's attention. The embodiments of the present disclosure are for illustration only and are not specifically limited.

[0144] Step S1005: display the target driving image.

[0145] The image display device outputs the target driving image on the vehicle's central control screen, determines and displays the target driving image by display priority, and can flexibly and automatically switch the viewing angle of the displayed image during vehicle driving without the need for manual operation by the driver. Based on the target driving image, the driver can obtain blind spot or dangerous obstacle information, or vehicle fault information in a timely manner for reference and decision-making, which helps to improve driving safety.

[0146] The image display method provided by the embodiment of the present disclosure first determines the vehicle driving data collected in real time by the vehicle-mounted sensor; then determines the display priority of multiple obstacles in the current driving environment based on the vehicle driving data; and determines the display priority of the vehicle fault when the vehicle fails based on the vehicle driving data; finally, determines and displays the target driving image based on the vehicle driving data, the display priority of each obstacle, and the display priority of the vehicle fault. The method determines the display priority of multiple obstacles in the current driving environment and the display priority of the vehicle fault, and preferentially displays the target driving image of the obstacle or fault area that requires more attention from the driver. The method can flexibly and automatically switch the viewing angle of the displayed image during the vehicle driving process without manual operation by the user, and preferentially displays the obstacle and vehicle fault information in emergency situations, so that the driver can obtain dangerous obstacle information and vehicle fault information in a timely manner, which helps to improve driving safety.

[0147] Exemplary Devices

[0148] Fig.11 is a schematic diagram of the structure of an image display device provided by an exemplary embodiment of the present disclosure. Fig.11 As shown, the image display device 1100 may include:

[0149] The first determination module 1101 is used to determine the vehicle driving data collected in real time by the vehicle-mounted sensor;

[0150] A second determination module 1102 is used to determine the display priority of multiple obstacles in the current driving environment according to the vehicle driving data;

[0151] A third determining module 1103 is used to determine a target driving image according to the vehicle driving data and the display priority of each obstacle;

[0152] The display module 1104 is used to display the target driving image.

[0153] See also Fig.12 In some embodiments, the second determining module 1102 may include:

[0154] A first determination submodule 11021 is used to determine a vehicle state according to the vehicle data in the vehicle driving data, wherein the vehicle state includes an engine-off state, a start-up stationary state, a forward driving state, a reverse driving state, and a parking driving state;

[0155] The second determination submodule 11022 is used to perform a collision risk assessment based on the environment data in the vehicle driving data and the vehicle data, and determine the collision risk levels of multiple obstacles in the current driving environment;

[0156] The third determining submodule 11023 is used to determine the display priority of multiple obstacles in the current driving environment according to the vehicle state and the collision risk levels of the multiple obstacles.

[0157] In some embodiments, the second determining submodule 11022 may include:

[0158] A first determining unit, configured to perform obstacle detection according to the environmental data in the vehicle driving data, and determine a plurality of obstacles in the current driving environment and motion information of each obstacle;

[0159] A prediction unit, configured to predict a collision time between the vehicle and each obstacle according to the motion information of each obstacle and the vehicle data;

[0160] The second determining unit is used to determine the collision risk level of each obstacle according to the collision time between the vehicle and each obstacle.

[0161] In some embodiments, the third determining submodule 11023 may include:

[0162] A third determining unit, configured to determine display weights corresponding to a plurality of viewing angles according to the vehicle state;

[0163] A fourth determining unit, used to determine the viewing angle of each obstacle;

[0164] a fifth determining unit, configured to determine a display weight corresponding to each obstacle according to the display weight corresponding to each viewing angle and the viewing angle at which each obstacle is located;

[0165] The sixth determining unit is used to determine the display priority of each obstacle in the current driving environment according to the display weight corresponding to each obstacle and the collision risk level of each obstacle.

[0166] See also Fig.12 In some embodiments, the third determining module 1103 may include:

[0167] The fourth determination submodule 11031 is used to determine the target obstacle according to the display priority of each obstacle;

[0168] The fifth determining submodule 11032 is used to determine a target driving image for the target obstacle according to the environmental data in the vehicle driving data.

[0169] Fig.13 is a schematic diagram of the composition structure of an image display device provided by another exemplary embodiment of the present disclosure. Fig.13 As shown, the image display device 1300 may include:

[0170] The first determination module 1301 is used to determine the vehicle driving data collected in real time by the vehicle-mounted sensor;

[0171] A second determining module 1302 is used to determine the display priority of multiple obstacles in the current driving environment according to the vehicle driving data;

[0172] The third determination module 1303 is used to determine the display priority of the vehicle fault when the vehicle fault occurs according to the vehicle driving data;

[0173] A fourth determining module 1304 is used to determine a target driving image according to the vehicle driving data, the display priority of each obstacle and the display priority of the vehicle fault;

[0174] The display module 1305 is used to display the target driving image.

[0175] The beneficial technical effects corresponding to the exemplary embodiment of the present device can be found in the corresponding beneficial technical effects of the above exemplary method section, which will not be repeated here.

[0176] Exemplary Electronic Devices

[0177] Fig.14 A schematic diagram of the structure of an electronic device provided by an exemplary embodiment of the present disclosure is shown in FIG. Fig.14 As shown, the electronic device 1400 may include at least one processor 1401 and a memory 1402 .

[0178] The processor 1401 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 1400 to perform desired functions.

[0179] The memory 1402 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 1401 may execute one or more computer program instructions to implement the image display method and / or other desired functions of the various embodiments of the present disclosure described above.

[0180] In one example, the electronic device 1400 may further include: an input device 1403 and an output device 1404 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0181] The input device 1403 may also include, for example, a keyboard, a mouse, etc.

[0182] The output device 1404 can output various information to the outside, and may include, for example, a display, a speaker, a printer, a communication network and its connected remote output device, etc.

[0183] Of course, to simplify, Fig.14 Only some of the components related to the present disclosure in the electronic device 1400 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device 1400 may also include any other appropriate components.

[0184] Exemplary computer program products and computer-readable storage media

[0185] In addition to the above-mentioned methods and devices, embodiments of the present disclosure may also provide a computer program product, including computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the image display method of various embodiments of the present disclosure described in the above-mentioned "Exemplary Method" section.

[0186] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the disclosed embodiments, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0187] In addition, an embodiment of the present disclosure may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enables the processor to execute the steps of the image display method of various embodiments of the present disclosure described in the above “Exemplary Method” section.

[0188] Computer readable storage media can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium is, for example, but not limited to, a system, device or device including electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0189] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and cannot be considered as necessary for each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, rather than limitation, and the above details do not limit the present disclosure to being implemented by adopting the above specific details.

[0190] Those skilled in the art may make various changes and modifications to the present disclosure without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present disclosure claims and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. An image display method, comprising: Determine the vehicle driving data collected by the vehicle-mounted sensors in real time; Determining the display priority of multiple obstacles in the current driving environment according to the vehicle driving data; A target driving image is determined and displayed according to the vehicle driving data and the display priority of each obstacle.

2. The method according to claim 1, wherein: Determining the display priority of multiple obstacles in the current driving environment according to the vehicle driving data includes: Determining a vehicle state according to the vehicle data in the vehicle driving data, wherein the vehicle state includes an engine-off state, a start-up stationary state, a forward driving state, a reverse driving state, and a parking driving state; Performing a collision risk assessment based on the environmental data in the vehicle driving data and the vehicle data to determine the collision risk levels of multiple obstacles in the current driving environment; The display priorities of the multiple obstacles in the current driving environment are determined according to the vehicle state and the collision risk levels of the multiple obstacles.

3. The method according to claim 2, wherein: The performing collision risk assessment according to the environment data in the vehicle driving data and the vehicle data to determine the collision risk levels of multiple obstacles in the current driving environment includes: Perform obstacle detection according to the environmental data in the vehicle driving data to determine multiple obstacles in the current driving environment and motion information of each obstacle; Predicting the collision time between the vehicle and each obstacle according to the motion information of each obstacle and the vehicle data; The collision risk level of each obstacle is determined according to the collision time between the vehicle and each obstacle.

4. The method according to claim 2, wherein: The determining, according to the vehicle state and the collision risk levels of the multiple obstacles, the display priorities of the multiple obstacles in the current driving environment includes: Determining display weights corresponding to a plurality of viewing angles according to the vehicle state; Determining the viewing angle at which each of the obstacles is located; Determining the display weight corresponding to each obstacle according to the display weight corresponding to each viewing angle and the viewing angle at which each obstacle is located; The display priority of each obstacle in the current driving environment is determined according to the display weight corresponding to each obstacle and the collision risk level of each obstacle.

5. The method according to claim 1, wherein: The step of determining and displaying a target driving image according to the vehicle driving data and the display priority of each obstacle includes: Determining a target obstacle according to the display priority of each obstacle; Determining a target driving image for the target obstacle according to the environmental data in the vehicle driving data; The target driving image is displayed.

6. The method according to claim 1, further comprising: Determining the display priority of the vehicle fault when the vehicle fault occurs according to the vehicle driving data; Accordingly, determining and displaying a target driving image according to the vehicle driving data and the display priority of each obstacle includes: A target driving image is determined and displayed according to the vehicle driving data, the display priority of each obstacle and the display priority of the vehicle fault.

7. An image display device, comprising: A first determination module is used to determine the vehicle driving data collected in real time by the vehicle-mounted sensor; A second determination module, used to determine the display priority of multiple obstacles in the current driving environment according to the vehicle driving data; A third determination module, configured to determine a target driving image according to the vehicle driving data and the display priority of each obstacle; A display module is used to display the target driving image.

8. A computer-readable storage medium, wherein the storage medium stores a computer program, wherein the computer program is used to execute the image display method according to any one of claims 1 to 6.

9. An electronic device, comprising: processor; a memory for storing instructions executable by the processor; The processor is used to read the instruction from the memory and execute the instruction to implement the image display method described in any one of claims 1-6.

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