Vehicle surrounding environment display method, computer program product and electronic equipment

Abstract

The invention provides a vehicle surrounding environment display method, a computer program product and electronic equipment, and according to the vehicle surrounding environment display method provided by the invention, if free space detection is carried out on a surrounding area of a vehicle, a spatial position with a preset traffic facility can be divided into target nodes belonging to a preset node type; if yes, determining a target node set containing target nodes belonging to the same preset traffic facility according to node information of each target node obtained by performing free space detection on the peripheral area of the vehicle; and displaying the image of the surrounding environment of the vehicle, which carries the identification information of the preset traffic facility corresponding to the target node set, based on the node position information of the target node contained in the target node set.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a vehicle surrounding environment display method, a computer program product, and an electronic device. Background Art

[0002] With the continuous development of technology, people are gradually beginning to use in-vehicle equipment to collect data about the vehicle's surroundings. By analyzing and processing the collected data, they generate and display the vehicle's surrounding environment images, allowing drivers and passengers to quickly understand the vehicle's surroundings and real-time road conditions. However, current vehicle surrounding environment images typically do not identify traffic facilities such as water-filled guardrails, crash buckets, and traffic cones around the vehicle. This not only easily affects the user's comprehensive perception of the vehicle's surroundings, but may even increase the risk of traffic accidents. Summary of the Invention

[0003] Based on this, the present invention provides a method for displaying the vehicle's surrounding environment, a computer program product and an electronic device. When the vehicle's surrounding environment display method is used, when there are preset traffic facilities in the area surrounding the vehicle, an image of the vehicle's surrounding environment carrying identification information for the above-mentioned preset traffic facilities can be displayed, which is conducive to improving the user's comprehensive perception of the vehicle's surrounding environment, thereby improving the user experience and vehicle operation safety.

[0004] In one aspect, the present invention provides a method for displaying a vehicle's surrounding environment, the method comprising:

[0005] Obtaining node information of a target node obtained by performing free space detection on an area surrounding the vehicle; wherein one target node corresponds to a spatial position belonging to a preset node type in the area surrounding the vehicle;

[0006] Determining, based on the node information of the target node, a target node set including the target node belonging to the same preset transportation facility;

[0007] Based on the node position information of the target node included in the target node set, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set is displayed.

[0008] Furthermore, in some embodiments, obtaining node information of a target node obtained by performing free space detection on an area surrounding the vehicle includes:

[0009] Obtain node information of the initial node obtained by performing free space detection on the area surrounding the vehicle;

[0010] Filtering nodes that meet preset conditions from the initial nodes according to the node information of the initial nodes to obtain the target node;

[0011] The preset conditions include: the node type is a preset node type associated with the preset traffic facility;

[0012] Alternatively, the preset conditions include: the node type is a preset node type associated with the preset traffic facility, and the node is located in a preset surrounding area of ​​the lane line of the lane where the vehicle is located.

[0013] Furthermore, in some embodiments, obtaining node information of an initial node obtained by performing free space detection on an area surrounding the vehicle includes:

[0014] Acquiring vehicle surrounding environment data of the vehicle; wherein the vehicle surrounding environment data includes at least one of: an image of the vehicle surrounding environment collected by an image acquisition device, and perception data of the vehicle surrounding environment collected by a radar device;

[0015] Inputting the vehicle surrounding environment data into a free space detection model built based on a deep learning algorithm to obtain node information of the initial node output by the free space detection model; wherein the node information at least includes: node type information and node location information of the initial node; or,

[0016] Node information of the initial node obtained by processing the vehicle surrounding environment data using the free space detection model is received.

[0017] Furthermore, in some embodiments, the filtering out nodes that meet preset conditions from the initial nodes based on the node information of the initial nodes to obtain the target node includes:

[0018] Obtaining lane line position information of the lane in which the vehicle is located; wherein the lane line position information is obtained by performing target detection on an image of the vehicle's surrounding environment, or the lane line position information is determined based on the vehicle's estimated driving trajectory data and preset lane width data;

[0019] Determining, based on the lane line position information, position information of a preset surrounding area of ​​the lane line of the lane in which the vehicle is located;

[0020] According to the node position information of the initial node and the position information of the preset surrounding area of ​​the lane line, it is determined whether the initial node is located in the preset surrounding area of ​​the lane line.

[0021] Furthermore, in some embodiments, determining the position information of a preset surrounding area of ​​the lane line of the lane in which the vehicle is located based on the lane line position information includes:

[0022] Determining, based on lane line position information of a specific lane line in a lane in which the vehicle is located, position information of a first area with a first width to the left of the specific lane line, and position information of a second area with a second width to the right of the specific lane line, thereby obtaining position information of a preset surrounding area of ​​the specific lane line;

[0023] If the specific lane marking is a left lane marking, the first width is greater than the second width, and the first width is less than or equal to the lane width of the lane in which the vehicle is located;

[0024] If the specific lane marking is the right lane marking, the first width is smaller than the second width, and the second width is smaller than or equal to the lane width of the lane in which the vehicle is located.

[0025] Furthermore, in some embodiments, determining, based on the node information of the target node, a target node set including the target node belonging to the same preset transportation facility includes:

[0026] According to the node information of the target nodes, clustering processing is performed on the target nodes to obtain at least one target node set; wherein the node information of the target nodes at least includes node position information of the target nodes.

[0027] Furthermore, in some embodiments, the displaying of the vehicle's surrounding environment image carrying identification information of the preset traffic facilities corresponding to the target node set based on the node location information of the target node included in the target node set includes:

[0028] Determining, based on the node position information of each target node included in the target node set, a target area where the preset traffic facilities corresponding to the target node set are located in the image of the vehicle's surrounding environment;

[0029] generating identification information for the preset traffic facility at the target area, and obtaining an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facility;

[0030] The target device is used to display an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facilities.

[0031] Furthermore, in some embodiments, determining, based on the node position information of each target node included in the target node set, a target area where the preset traffic facilities corresponding to the target node set are located in the image of the vehicle's surrounding environment includes:

[0032] Determining the location information of a designated facility portion of a preset transportation facility corresponding to the target node set according to the node location information of each target node included in the target node set;

[0033] Determine the target area where the preset traffic facility is located in the image of the vehicle's surrounding environment based on the location information of the designated facility and the preset size information of the preset traffic facility; or

[0034] Determining actual size information of preset transportation facilities and location information of designated facility parts corresponding to the target node set based on node location information of each target node included in the target node set;

[0035] According to the position information of the designated facility part and the actual size information, a target area where the preset traffic facility is located in the image of the vehicle's surrounding environment is determined.

[0036] Furthermore, in some embodiments, the displaying of the vehicle's surrounding environment image carrying the identification information of the preset traffic facility by the target device includes:

[0037] Using a screen device carried by the vehicle to display an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facilities; or,

[0038] The intelligent terminal device is used to display the vehicle's surrounding environment image carrying the identification information of the preset traffic facilities.

[0039] Furthermore, in some embodiments, the above method further comprises:

[0040] Determining, based on the target nodes included in the target node set, whether the preset traffic facilities corresponding to the target node set are credible traffic facilities, and obtaining a determination result;

[0041] The display of the vehicle's surrounding environment image carrying identification information of the preset traffic facilities corresponding to the target node set includes:

[0042] If the judgment result indicates that the preset traffic facilities corresponding to the target node set are credible traffic facilities, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set is displayed.

[0043] Furthermore, in some embodiments, determining whether the preset transportation facilities corresponding to the target node set are credible transportation facilities includes:

[0044] Determining whether the number of the target nodes included in the target node set is greater than or equal to a preset number; and / or,

[0045] Determine whether the distance between the preset traffic facilities corresponding to the target node set and the vehicle is less than or equal to a preset distance.

[0046] Furthermore, in some embodiments, the preset traffic facilities include: at least one of a water-filled guardrail, a crash barrel, and a traffic cone.

[0047] Furthermore, in some embodiments, the above method further comprises:

[0048] Planning a driving trajectory for the vehicle according to the preset traffic facilities corresponding to the target node set; and / or,

[0049] Controlling the vehicle according to the preset traffic facilities corresponding to the target node set; and / or,

[0050] According to the preset traffic facilities corresponding to the target node set, a collision warning is issued to the vehicle.

[0051] On the other hand, the present invention further provides a computer program product, which includes a computer program, and when the computer program is executed, the steps of the above method are implemented.

[0052] On the other hand, the present invention further provides an electronic device comprising: a processor and a memory; wherein the memory stores computer-readable instructions, and the computer-readable instructions are suitable for being loaded by the processor and executing the steps of the above method.

[0053] Furthermore, in some embodiments, the electronic device includes at least one of an image acquisition device, a radar device, and a domain controller.

[0054] According to the vehicle surrounding environment display method provided by the present invention, if the spatial position where the preset traffic facilities exist can be divided into target nodes belonging to the preset node type when free space detection is performed on the area surrounding the vehicle, a target node set including target nodes belonging to the same preset traffic facility can be determined based on the node information of each target node obtained by free space detection on the area surrounding the vehicle; so as to display the vehicle surrounding environment image carrying the identification information of the preset traffic facilities corresponding to the target node set based on the node position information of the target nodes included in the target node set, which is conducive to improving the user's comprehensive perception of the vehicle surrounding environment in combination with the vehicle surrounding environment image, and thus can improve the user experience and the safety of the vehicle driving process.

[0055] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic flow chart of a method for displaying a vehicle's surrounding environment provided by an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of an image of the surrounding environment of a vehicle provided by an embodiment of the present invention;

[0058] Figure 3 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] In the description of one or more embodiments of the present invention, the term "including" and similar terms should be understood as open inclusion, i.e., "including but not limited to." The term "based on" should be understood as "based at least in part on." The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment." The terms "first," "second," etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0061] With the continuous development of science and technology, cars have gradually begun to be equipped with some data acquisition equipment to collect data about the car's surrounding environment. By analyzing and processing the collected data about the car's surrounding environment, an image of the car's surrounding environment can be generated and displayed, so that drivers and passengers can quickly grasp the car's surrounding environment and real-time road conditions. However, although the current vehicle surrounding environment image can identify the lane information around the car, or the location information of the car's drivable and non-drivable areas, or the location information of common traffic participants such as motor vehicles, non-motor vehicles and pedestrians around the car, it does not identify the location information of traffic facilities such as water-filled guardrails, crash buckets and traffic cones around the car. This not only easily affects the user's comprehensive perception of the vehicle's surrounding environment, but may even increase the risk of traffic accidents.

[0062] Based on this, the present invention proposes a method for displaying the vehicle's surrounding environment. If the spatial positions where preset traffic facilities exist can be divided into target nodes belonging to preset node types when free space detection is performed on the area surrounding the vehicle, a target node set including target nodes belonging to the same preset traffic facility can be determined based on the node information of each target node obtained from the free space detection on the area surrounding the vehicle; so as to display the vehicle's surrounding environment image carrying the identification information of the preset traffic facilities corresponding to the target node set based on the node position information of the target nodes included in the target node set, which is conducive to improving the user's comprehensive perception of the vehicle's surrounding environment in combination with the vehicle's surrounding environment image, and thus can improve the user experience and the safety of the vehicle driving process.

[0063] See Figure 1 , which is a flow chart of a method for displaying a vehicle's surrounding environment provided by an embodiment of the present invention. From a program perspective, the execution subject of this process can be a program installed on an onboard device, a vehicle controller, or a vehicle. Alternatively, the execution subject of this process can also be an onboard device, a vehicle controller, or a vehicle, or other device capable of communicating with the onboard device, vehicle controller, or vehicle, without specific limitation.

[0064] The following is for Figure 1 The process shown in FIG. 1 is described in detail. The vehicle surrounding environment display method may specifically include the following steps:

[0065] Step S102 , obtaining node information of a target node obtained by performing free space detection on the area surrounding the vehicle; wherein one target node corresponds to a spatial position belonging to a preset node type in the area surrounding the vehicle.

[0066] In embodiments of the present invention, free space detection (FSD) for an automobile may refer to the process of identifying obstacles and non-drivable surfaces around the vehicle to demarcate a safe driving area (i.e., a drivable area) around the vehicle. Because FSD provides the vehicle's autonomous driving and assisted driving functions with environmental awareness, it can help the vehicle plan a safe driving path, reducing traffic accidents and road congestion.

[0067] Currently, when performing free space detection processing on the area surrounding the vehicle, classification processing can generally be performed on each spatial position within the area surrounding the vehicle to obtain node information of the spatial node corresponding to each spatial position. The node information of the spatial node can generally include node type information reflecting the category of the object at the spatial position corresponding to the spatial node, as well as position information reflecting the spatial position corresponding to the spatial node. Of course, other node attribute information may also be included, which is not specifically limited.

[0068] In actual applications, depending on the type of objects present at a spatial location, the node type information of the spatial node corresponding to the spatial location may often be different. For example, when there is a passable road surface at a certain spatial location, the node type information of the spatial node corresponding to the spatial location may be a first node type; when there are traffic participants such as motor vehicles and non-motor vehicles at a certain spatial location, the node type information of the spatial node corresponding to the spatial location may be a second node type; and when there are preset traffic facilities at a certain spatial location, the node type information of the spatial node corresponding to the spatial location may be a third node type. It is understandable that the node type information of the spatial nodes corresponding to different types of objects can be set according to actual needs, and there is no specific limitation on this.

[0069] In an embodiment of the present invention, in order to facilitate the subsequent identification of preset traffic facilities existing in the surrounding area of ​​the vehicle in the image of the surrounding environment of the vehicle, the node information of the target node obtained by free space detection of the surrounding area of ​​the vehicle and consistent with the node type (i.e., the preset node type) to which the preset traffic facilities belong can be obtained, so as to accurately determine the position, size, and quantity of the preset traffic facilities existing in the surrounding area of ​​the vehicle based on the node information of each target node existing around the vehicle. In addition, the preset traffic facilities may include but are not limited to: water-filled guardrails, other guardrails (for example, iron guardrails), at least one of crash barrels and traffic cones. In addition, the surrounding area of ​​the vehicle may include the front area of ​​the vehicle, and in addition, it may also include the side area and rear area of ​​the vehicle. There is no specific limitation on this.

[0070] Step S104 : determining a target node set including the target nodes belonging to the same preset transportation facility according to the node information of the target nodes.

[0071] In an embodiment of the present invention, depending on the actual situation, there may be one or more preset traffic facilities in the area surrounding the vehicle. Therefore, the target nodes obtained in step S102 may belong to the same preset traffic facility or to different preset traffic facilities. In order to accurately distinguish and identify the preset traffic facilities in the environment surrounding the vehicle, the target nodes belonging to the same preset traffic facility can be grouped into the same target node set based on the node information of the target nodes in the area surrounding the vehicle, and the target nodes belonging to different preset traffic facilities can be grouped into different target node sets, so as to accurately identify a preset traffic facility in the vicinity of the vehicle based on a target node set.

[0072] Step S106 : Based on the node position information of the target node included in the target node set, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set is displayed.

[0073] In an embodiment of the present invention, since a target node can correspond to a spatial location within the area surrounding the vehicle, the node location information of the target node can generally reflect the location information of a spatial location within the area surrounding the vehicle. Therefore, based on the node location information of the target nodes included in the target node set, the location information of the preset traffic facilities corresponding to the target node set within the area surrounding the vehicle can be determined, and an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set can be generated and displayed.

[0074] Figure 1 The method in the embodiment of the present invention displays an image of the vehicle's surrounding environment that carries identification information of preset traffic facilities existing around the vehicle, so that the user can know the deployment location of the preset traffic facilities existing around the vehicle by viewing the image of the vehicle's surrounding environment, thereby improving the user's comprehensive perception of the vehicle's surrounding environment in combination with the image of the vehicle's surrounding environment, thereby improving the user's safety when driving the vehicle, and is conducive to improving the user experience.

[0075] Furthermore, the relevant node information obtained from free-space detection of the area surrounding the vehicle can be used to assist in the execution of the vehicle's autonomous or assisted driving functions. Furthermore, the image of the vehicle's surroundings can also reflect or influence the vehicle's autonomous or assisted driving process. By improving the content displayed in the image of the vehicle's surroundings, not only can the user's trust in the vehicle's Advanced Driving Assistance System (ADAS) be enhanced, thereby improving the user experience, but it can even improve the vehicle control accuracy of the vehicle's ADAS, thereby enhancing vehicle operation safety.

[0076] In some feasible implementations, obtaining the node information of the target node obtained by performing free space detection on the area surrounding the vehicle may include:

[0077] Obtain node information of the initial node obtained by performing free space detection on the area surrounding the vehicle.

[0078] According to the node information of the initial node, nodes that meet a preset condition are screened out from the initial nodes to obtain the target node.

[0079] The preset condition may include: the node type is a preset node type associated with the preset traffic facility.

[0080] Alternatively, the preset condition may include: the node type is a preset node type associated with the preset traffic facility, and the node is located in a preset surrounding area of ​​the lane line of the lane where the vehicle is located.

[0081] In an embodiment of the present invention, the node type of the spatial node corresponding to the area where the preset traffic facility is located, which is generated when performing automobile free space detection, can generally be predetermined to obtain the preset node type associated with the preset traffic facility.

[0082] In actual applications, the preset traffic facilities may include but are not limited to: water-filled guardrails, other guardrails (e.g., iron guardrails), crash barrels, and traffic cones, and the preset node types associated with the preset traffic facilities are usually related to the labeled data of the training samples used in the free space detection algorithm / model training. For example, when the labeled data for the preset traffic facilities in the training sample is a pole type, the pole type can be used as the preset node type. Alternatively, when the labeled data for the preset traffic facilities in the training sample is type 3, type 3 can be used as the preset node type, without specific limitation.

[0083] In an embodiment of the present invention, since the node types of the initial nodes obtained by free space detection in the area surrounding the vehicle are not necessarily the preset node types belonging to the preset traffic facilities, the node type information in the node information of the initial nodes can be combined to filter out the initial nodes whose node types are the preset node types to obtain the required target nodes.

[0084] Furthermore, when a pre-set traffic facility is located at a greater distance from the vehicle, for example, multiple lanes away from the vehicle's lane, the collision risk posed by the pre-set traffic facility is often lower. This leads users to pay more attention to the pre-set traffic facilities located within and near the vehicle's lane. Therefore, the initial node can also be selected as the target node if the node type is a pre-set node type associated with a pre-set traffic facility and the initial node is located within the pre-set surrounding area of ​​the lane line of the vehicle's lane, providing greater flexibility.

[0085] In some feasible implementations, obtaining node information of an initial node obtained by performing free space detection on an area surrounding the vehicle may include:

[0086] Acquire vehicle surrounding environment data of the vehicle; wherein the vehicle surrounding environment data includes: an image of the vehicle surrounding environment collected by an image acquisition device, and at least one of the vehicle surrounding environment perception data collected by a radar device.

[0087] Input the vehicle surrounding environment data into a free space detection model built based on a deep learning algorithm to obtain the node information of the initial node output by the free space detection model; wherein the node information at least includes: node type information and node location information of the initial node. Or,

[0088] Node information of the initial node obtained by processing the vehicle surrounding environment data using the free space detection model is received.

[0089] In an embodiment of the present invention, in order to achieve robust and accurate scene understanding, the vehicle can generally be equipped with an image acquisition device and / or a radar device for sensing the vehicle's surrounding environment, so that the vehicle's surrounding environment images captured by the above-mentioned image acquisition device and / or the vehicle's surrounding environment perception data captured by the radar device can be combined to perform free space detection on the vehicle, which is conducive to improving the accuracy of the free space detection results.

[0090] In the embodiments of the present invention, deep learning algorithms have become the core technology of the free space detection process due to their powerful feature learning capabilities, multimodal data fusion advantages and end-to-end real-time reasoning performance. They are gradually being applied to the free space detection process in the fields of autonomous driving, robot navigation, drone inspection, smart warehousing, etc.

[0091] Based on this, a free space detection model for identifying vehicle drivable areas (i.e., free spaces) and non-drivable areas can be built in advance using a deep learning algorithm. In addition, the free space detection model can be trained using training samples (e.g., vehicle surrounding environment image samples and / or radar perception data samples collected for the vehicle surrounding environment) and corresponding annotation data (e.g., data reflecting the node types corresponding to each spatial position in the sample), so that the trained free space detection model can be used to process the vehicle surrounding environment data of the vehicle to obtain node information of each initial node existing around the vehicle, including corresponding node type information and node position information. In actual applications, the node information of the initial node can also include optical flow information at the spatial position corresponding to the initial node, as well as information on size ratio changes caused by different distances from the vehicle, etc., without specific limitation.

[0092] Among them, one of the initial nodes usually corresponds to a preset spatial position in the area surrounding the vehicle; for example, when the vehicle surrounding environment data of the vehicle is the vehicle surrounding environment image, if the free space detection model is used to classify each N*M non-overlapping pixel area as a drivable area or a non-drivable area, then one of the initial nodes can correspond to the spatial position reflected by an N*M pixel area in the vehicle surrounding environment image. Alternatively, when the vehicle surrounding environment data of the vehicle is the vehicle surrounding environment perception data collected by the radar equipment, if the free space detection model is used to classify each X*Y*Z non-overlapping point cloud area as a drivable area or a non-drivable area, then one of the initial nodes can correspond to the spatial position reflected by an X*Y*Z point cloud area in the radar coordinate system. It can be understood that the size of the preset spatial position corresponding to one of the initial nodes can be based on actual needs and is not specifically limited to this.

[0093] In practical applications, Figure 1 The execution subject of the method can carry out or call the free space detection model built based on the deep learning algorithm to process the vehicle's surrounding environment data using the free space detection model to generate node information of each initial node. Or, Figure 1The execution subject of the method can also obtain the node information of each initial node obtained by other devices using the free space detection model to process the vehicle surrounding environment data of the vehicle from other vehicle-mounted devices, vehicle controllers or cloud servers. It has good flexibility and is not specifically limited to this.

[0094] In some feasible implementations, filtering out nodes that meet preset conditions from the initial nodes based on the node information of the initial nodes to obtain the target node may include:

[0095] Obtain lane line position information of the lane in which the vehicle is located; wherein the lane line position information is obtained by performing target detection on the image of the vehicle's surrounding environment, or the lane line position information is determined based on the vehicle's estimated driving trajectory data and preset lane width data.

[0096] Based on the lane line position information, position information of a preset surrounding area of ​​the lane line of the lane where the vehicle is located is determined.

[0097] According to the node position information of the initial node and the position information of the preset surrounding area of ​​the lane line, it is determined whether the initial node is located in the preset surrounding area of ​​the lane line.

[0098] In an embodiment of the present invention, when an image of the vehicle's surrounding environment can be acquired and the image of the vehicle's surrounding environment includes a lane line image, target detection processing can be performed on the image of the vehicle's surrounding environment to obtain the lane line position information of the lane in which the vehicle is located, with good accuracy.

[0099] However, when the image of the vehicle's surrounding environment is not collected, or the image of the vehicle's surrounding environment does not contain a lane line image (for example, an intersection area, a newly built road area where lane lines have not yet been drawn, etc.), it is usually impossible to obtain the lane line position information of the lane in which the vehicle is located by performing target detection on the image of the vehicle's surrounding environment. However, since users are usually more concerned about the preset traffic facilities in the area where the vehicle is about to pass, the vehicle's estimated driving trajectory data can also be regarded as the position data of the lane centerline of the lane in which the vehicle is located, so as to combine the preset lane width data to generate the virtual lane in which the vehicle is located, and then use the lane line position data of the virtual lane as the lane line position information of the lane in which the vehicle is located, which has good flexibility.

[0100] In an embodiment of the present invention, a positional relationship between a preset surrounding area of ​​the lane line of the vehicle's lane and the lane line of the vehicle's lane can be pre-set. Thus, after obtaining the position information of the lane line of the vehicle's lane, the position information of the preset surrounding area of ​​the lane line of the vehicle's lane can be determined. Subsequently, based on the position information of the preset surrounding area of ​​the lane line of the vehicle's lane and the node position information of the initial node, it can be determined whether the initial node is within the preset surrounding area of ​​the lane line of the vehicle's lane. This is convenient, fast, and highly accurate.

[0101] In some feasible implementations, determining the position information of a preset surrounding area of ​​the lane line of the lane in which the vehicle is located based on the lane line position information may include:

[0102] Based on the lane line position information of the specific lane line in the lane where the vehicle is located, the position information of a first area with a first width to the left of the specific lane line and the position information of a second area with a second width to the right of the specific lane line are determined to obtain the position information of a preset surrounding area of ​​the specific lane line.

[0103] If the specific lane marking is the left lane marking, the first width may be greater than the second width, and the first width may be less than or equal to the lane width of the vehicle's lane; if the specific lane marking is the right lane marking, the first width may be less than the second width, and the second width may be less than or equal to the lane width of the vehicle's lane. This minimizes the area of ​​the preset surrounding area of ​​the lane marking of the vehicle's lane while accurately identifying target nodes belonging to preset traffic facilities that may exist near the lane marking of the vehicle's lane. This reduces computational effort and conserves computing resources while ensuring accurate identification of the preset traffic facilities. Of course, the first and second widths may also take other values, and this is not specifically limited.

[0104] In practical applications, the faster the vehicle's longitudinal speed, the greater the distance it typically travels within a fixed timeframe. Consequently, the greater the collision risk posed by pre-set traffic facilities that are farther from the vehicle. Therefore, it may be necessary to display pre-set traffic facilities that are farther from the vehicle in the image of the vehicle's surroundings, so that the driver and passengers can easily understand the comprehensive distribution of pre-set traffic facilities based on the image of the vehicle's surroundings. Based on this, the first width of the first area and the second width of the second area in the pre-set area surrounding the lane line of the vehicle's lane can be positively correlated with the vehicle's longitudinal speed.

[0105] Furthermore, since the vehicle gradually moves away from the right lane line of its lane as it accelerates to the left, the collision risk posed to the vehicle by the pre-set traffic facilities in the pre-set area surrounding the right lane line of its lane gradually decreases, while the collision risk posed to the vehicle by the pre-set traffic facilities in the pre-set area surrounding the left lane line of its lane gradually increases. Therefore, the size of the pre-set area surrounding the right lane line of its lane can be appropriately reduced, and the size of the pre-set area surrounding the left lane line of its lane can be appropriately increased. Similarly, when the vehicle accelerates to the right, the size of the pre-set area surrounding the left lane line of its lane can be appropriately reduced, and the size of the pre-set area surrounding the right lane line of its lane can be appropriately increased. Based on this, the first width of the first area and the second width of the second area in the pre-set area surrounding the lane line of its lane can also be determined in conjunction with the vehicle's lateral speed. This provides flexibility and is not specifically limited.

[0106] Figure 2 This is a schematic diagram of an image of the surrounding environment of the vehicle provided in an embodiment of the present invention. Figure 2 The content in the following example illustrates the principle of target node selection. Figure 2 As shown, it is assumed that the lane in which the vehicle is located has a left lane line 201 and a right lane line 202. Then, the area 203 with a first width on the left side of the left lane line 201 and the area 204 with a second width on the right side can be used as the preset surrounding area of ​​the left lane line 201. Similarly, the area 205 with a first width on the left side of the right lane line 202 and the area 206 with a second width on the right side can also be used as the preset surrounding area of ​​the right lane line 202. Subsequently, if any initial node obtained by performing free space detection on the area surrounding the vehicle is located in the preset surrounding area of ​​the left lane line 201 or the preset surrounding area of ​​the right lane line 202, and the node type is a preset node type associated with a preset traffic facility, then the initial node can be used as the target node.

[0107] In some feasible implementations, determining, based on the node information of the target node, a target node set including target nodes belonging to the same preset transportation facility may include:

[0108] According to the node information of the target nodes, clustering processing is performed on the target nodes to obtain at least one target node set; wherein the node information of the target nodes at least includes node position information of the target nodes.

[0109] In an embodiment of the present invention, under normal circumstances, the spatial positions corresponding to target nodes belonging to the same preset traffic facility are usually close to each other, while the spatial positions corresponding to target nodes belonging to different preset traffic facilities are usually far from each other. Based on this, the target nodes existing around the vehicle can be clustered in combination with the node position information of each target node, so as to identify whether each target node belongs to the same preset traffic facility according to the distance between the spatial positions corresponding to the target nodes, so that the target nodes belonging to the same preset traffic facility can be accurately divided into the same target node set, and the target nodes belonging to different preset traffic facilities can be divided into different target node sets, which is convenient and fast.

[0110] In practical applications, since the target node can be a node corresponding to a certain spatial position around the vehicle obtained by free space detection of the vehicle's surrounding environment image, and the mapping relationship between the two-dimensional image coordinate system corresponding to the vehicle's surrounding environment image and the preset three-dimensional coordinate system (for example, the world coordinate system, the radar coordinate system) can also be predetermined, the node position information of the target node can include both its two-dimensional coordinate data in the two-dimensional image coordinate system and its three-dimensional coordinate data in the preset three-dimensional coordinate system, and there is no specific limitation on this.

[0111] Similarly, when the target node is a node corresponding to a certain spatial position around the vehicle obtained by performing free space detection on the vehicle's surrounding environment perception data collected by the radar equipment, since the mapping relationship between the radar coordinate system and the preset three-dimensional coordinate system (for example, the world coordinate system) and the preset two-dimensional coordinate system (for example, the image coordinate system) can be determined in advance, the node position information of the target node can also include its three-dimensional coordinate data in the radar coordinate system, the preset three-dimensional coordinate system, etc., and of course, it can also include its two-dimensional coordinate data in the preset two-dimensional coordinate system, and there is no specific limitation on this.

[0112] In practical applications, the node information of the target node may also include optical flow information, size ratio change information, etc. Since the above information can also reflect the relevant characteristics of the material existing at the spatial position corresponding to the target node, in addition to clustering processing based on the node position information of the target node, clustering processing can also be performed based on other node information of the target node, which is conducive to improving the accuracy of the generated target node sets.

[0113] In some feasible implementations, displaying the vehicle's surrounding environment image carrying identification information of the preset traffic facilities corresponding to the target node set based on the node location information of the target node included in the target node set may include:

[0114] According to the node position information of each target node included in the target node set, a target area where the preset traffic facilities corresponding to the target node set are located in the image of the vehicle's surrounding environment is determined.

[0115] Identification information for the preset traffic facility is generated at the target area, and an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facility is obtained.

[0116] The target device is used to display an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facilities.

[0117] In an embodiment of the present invention, under normal circumstances, the spatial location corresponding to the target node is the spatial location where the preset traffic facility exists. Therefore, the node location information of each target node belonging to the same preset traffic facility contained in a single target node set can be combined to determine the location of the preset traffic facility in space, and then the target area where the preset traffic facility is located in the image of the vehicle's surrounding environment can be determined. Subsequently, the target area in the image of the vehicle's surrounding environment can be marked according to a preset marking method to indicate the presence of the preset traffic facility in the target area, so that the user can be aware of the preset traffic facilities around the vehicle by viewing the image of the vehicle's surrounding environment displayed at the target device.

[0118] In actual applications, there can be many types of identification information for preset traffic facilities carried in the target area in the image of the vehicle's surrounding environment. For example, an identification box can be drawn at the edge of the target area as identification information for the preset traffic facilities, or a preset pattern can be drawn or a specified color can be filled in the target area as identification information for the preset traffic facilities, or text information such as the name or number of the preset traffic facility can be displayed in the target area as identification information for the preset traffic facilities. It has good flexibility and no specific limitation is imposed on this.

[0119] In practical applications, in order to clearly and completely display the vehicle's surrounding environment, the vehicle's surrounding environment image may carry, in addition to identification information for pre-set traffic facilities, identification information for lane lines around the vehicle, identification information for traffic participants around the vehicle, identification information for the vehicle's following targets or other warning targets, etc., without specific limitations. Furthermore, the vehicle's surrounding environment image may typically be a simulated image of the vehicle's surrounding environment generated by an application installed on the vehicle. Of course, the vehicle's surrounding environment image may also be an image directly captured by an image acquisition device, without specific limitations.

[0120] In some feasible implementations, determining, based on the node position information of each target node included in the target node set, the target area where the preset traffic facilities corresponding to the target node set are located in the image of the vehicle's surrounding environment may include:

[0121] According to the node position information of each target node included in the target node set, the position information of the designated facility part of the preset traffic facility corresponding to the target node set is determined.

[0122] According to the location information of the designated facility and the preset size information of the preset traffic facility, the target area where the preset traffic facility is located in the image of the vehicle's surrounding environment is determined. Or,

[0123] According to the node position information of each target node included in the target node set, the actual size information of the preset traffic facilities and the position information of the designated facility parts corresponding to the target node set are determined.

[0124] According to the position information of the designated facility part and the actual size information, a target area where the preset traffic facility is located in the image of the vehicle's surrounding environment is determined.

[0125] In an embodiment of the present invention, since a single target node set includes target nodes identified for the same preset traffic facility, and the spatial position commonly occupied by these target nodes can be simply regarded as the spatial position occupied by the preset traffic facility, the position information of the designated facility portion at the preset traffic facility corresponding to the target node set can be determined based on the node position information of the target nodes included in the target node set. The designated facility portion can be set according to actual needs, for example, it can be the center position of the preset traffic facility (which can be the position where the average value of the coordinates of the target nodes included in the target node set is located), or it can be the left / right endpoint, front / rear endpoint, etc. of the preset traffic facility (which can be the position where the target node with the largest / smallest coordinates included in the target node set is located), and there is no specific limitation on this.

[0126] In embodiments of the present invention, the preset size information of the preset traffic facility can generally be predetermined based on the actual conditions of the preset traffic facility. Thus, after determining the location information of the designated facility portion of the preset traffic facility, the area in the vehicle's surrounding image that contains the designated facility portion and corresponds to the preset size of the preset traffic facility can be used as the target area for the preset traffic facility, which is convenient and quick.

[0127] Alternatively, since the preset sizes of the same preset traffic facility can often be multiple, for example, water-filled guardrails of different lengths may be deployed on the road, or crash barrels of different diameters may be deployed; or, there may also be a situation where multiple preset traffic facilities of the same type are connected to form a preset traffic facility of a larger size, for example, multiple water-filled guardrails are connected by clips or rods, or multiple water-filled guardrails are placed closely adjacent to each other. In this case, multiple water-filled guardrails constitute a longer-sized water-filled guardrail, and the various target nodes detected for the above-mentioned longer-sized water-filled guardrails can be divided into the same target node set. On this basis, the actual size information of the preset traffic facility corresponding to the target node set can also be determined based on the node position information of each target node contained in a single target node set, so that the area in the vehicle's surrounding environment image that contains the above-mentioned designated facility part and corresponds to the actual size of the preset traffic facility can be used as the target area where the preset traffic facility is located, with good accuracy.

[0128] In some feasible implementations, displaying the vehicle's surrounding environment image carrying the identification information of the preset traffic facility using the target device may include:

[0129] The vehicle's onboard screen device is used to display the vehicle's surrounding environment image carrying the identification information of the preset traffic facilities. Or,

[0130] The intelligent terminal device is used to display the vehicle's surrounding environment image carrying the identification information of the preset traffic facilities.

[0131] In an embodiment of the present invention, the vehicle's own screen devices (e.g., human-machine interface HMI, co-pilot screen, rear screen) can be used to display images of the vehicle's surrounding environment that carry identification information for preset traffic facilities, or the vehicle's surrounding environment images can be sent to the user's smart terminal device (e.g., a smart phone) or the vehicle's own smart terminal device (e.g., a car-mounted portable computer) for display, which has good flexibility and is conducive to improving user experience.

[0132] In some possible implementations, Figure 1 The method may further include:

[0133] According to the target nodes included in the target node set, it is determined whether the preset traffic facilities corresponding to the target node set are credible traffic facilities, and a determination result is obtained.

[0134] Correspondingly, the displaying of the vehicle's surrounding environment image carrying the identification information of the preset traffic facilities corresponding to the target node set may include:

[0135] If the judgment result indicates that the preset traffic facilities corresponding to the target node set are credible traffic facilities, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set is displayed.

[0136] In an embodiment of the present invention, when the number of target nodes included in a single target node set is small, the target node set may be a target node set that is incorrectly generated due to environmental interference, detection algorithm accuracy, etc., which makes the credibility of the preset traffic facilities corresponding to the target node set poor. In addition, when the distance between the target nodes included in the target node set and the vehicle is relatively far, under the influence of factors such as radar signal attenuation, low spatial resolution of distant objects in the image, and increased environmental interference, the credibility of the preset traffic facilities corresponding to the target node set will often be poor. At this time, if the identification information for the preset traffic facilities with poor credibility is displayed in the image of the vehicle's surrounding environment, it may mislead the user, thereby affecting the user's trust in the image of the vehicle's surrounding environment.

[0137] Based on this, after combining the relevant information of the target nodes contained in a single target node set and determining that the preset traffic facilities corresponding to the target node set are credible traffic facilities, identification information for the preset traffic facilities corresponding to the target node set can be generated in the vehicle's surrounding environment image, which is conducive to improving the reliability of the identification information for the preset traffic facilities carried in the vehicle's surrounding environment image. The credible traffic facilities can refer to preset traffic facilities that are likely to exist, which will not be elaborated on here.

[0138] In actual applications, according to actual needs, only the first number of trusted traffic facilities closest to the vehicle within the preset surrounding area of ​​the left lane line of the lane where the vehicle is located, and the second number of trusted traffic facilities closest to the vehicle within the preset surrounding area of ​​the right lane line of the lane where the vehicle is located are displayed. The first number and the second number can be set according to actual needs, for example, 1-N, and there is no specific limitation on this.

[0139] In some feasible implementations, determining whether the preset transportation facilities corresponding to the target node set are credible transportation facilities may include:

[0140] Determine whether the number of target nodes included in the target node set is greater than or equal to a preset number. And / or,

[0141] Determine whether the distance between the preset traffic facilities corresponding to the target node set and the vehicle is less than or equal to a preset distance.

[0142] In the embodiment of the present invention, the preset number and the preset distance can be set according to actual needs. For example, the preset number can be several to dozens, and the preset distance can be several meters to tens of meters, etc., and there is no specific limitation on this.

[0143] Figure 2 This is a schematic diagram of an image of the surrounding environment of the vehicle provided in an embodiment of the present invention. Figure 2 The content in this section provides examples to illustrate the principles of screening the preset traffic facilities that need to be marked. Figure 2 As shown, assume that there are three target node sets (e.g., set 207, set 208, and set 209) in the area surrounding the vehicle. If the preset number is 3, then since the number of target nodes (i.e., black five-pointed stars) included in set 209 is less than the preset number, it is not necessary to carry the identification information of the preset traffic facilities corresponding to set 209 in the image of the vehicle's surrounding environment.

[0144] Assuming that, based on the target nodes included in set 207, it is determined that the distance between the preset traffic facilities corresponding to set 207 and the vehicle is greater than the preset distance, it is not necessary to carry the identification information of the preset traffic facilities corresponding to set 207 in the vehicle's surrounding environment image.

[0145] However, since the number of target nodes (i.e., black five-pointed stars) included in set 208 is greater than the preset number, if it is determined based on the various target nodes included in set 208 that the distance between the preset traffic facilities corresponding to set 208 and the vehicle is less than the preset distance, it is necessary to carry the identification information of the preset traffic facilities corresponding to set 208 in the image of the vehicle's surrounding environment.

[0146] In some possible implementations, Figure 1 The method may further include:

[0147] Planning a driving trajectory for the vehicle according to the preset traffic facilities corresponding to the target node set; and / or,

[0148] Controlling the vehicle according to the preset traffic facilities corresponding to the target node set; and / or,

[0149] According to the preset traffic facilities corresponding to the target node set, a collision warning is issued to the vehicle.

[0150] In the embodiment of the present invention, since the preset traffic facilities around the vehicle may bring collision risks to the vehicle, thereby affecting the driving safety of the vehicle, it is possible to combine the use of Figure 1The preset traffic facilities corresponding to the target node set identified by the method are used to plan the vehicle's driving trajectory, thereby obtaining a more accurate vehicle driving trajectory planning result. In addition, it can also be combined with the use of Figure 1 The preset traffic facilities corresponding to the target node set identified by the method are used to control the vehicle's driving to reduce the vehicle's driving risk. Figure 1 The preset traffic facilities corresponding to the target node set identified by the method provide collision warnings to the vehicle, so that the driver and passengers can timely perceive the more comprehensive collision risks faced by the vehicle, which is conducive to improving user experience.

[0151] The present invention also provides a computer program product, which includes a computer program. When the computer program is executed, it implements the steps of the vehicle surrounding environment display method as described in the above embodiments. The specific execution process can be found in the specific descriptions of the above embodiments and will not be repeated here.

[0152] In one embodiment, the present invention further provides Figure 3 The structural diagram of the electronic device shown in FIG. Figure 3 At the hardware level, the electronic device may include a processor 31 and a memory 35. It may also include an internal bus 32, a network interface 33, memory 34, and other hardware required for its operation. The processor 31 may read the corresponding computer program from the memory 35, store it in the memory, and then execute it to implement the above-mentioned vehicle surrounding environment display method. The specific execution process can be found in the detailed description of the above-mentioned embodiments and will not be repeated here.

[0153] In a feasible implementation, the electronic device may include at least one of an image acquisition device, a radar device, and a domain controller. Of course, the electronic device may also include other devices and a vehicle controller, which is not specifically limited.

[0154] Finally, the various embodiments of the present invention are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the computer program product and electronic device embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant portions, reference can be made to the descriptions of the method embodiments.

[0155] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for displaying a vehicle's surrounding environment, comprising: Obtaining node information of a target node obtained by performing free space detection on an area surrounding the vehicle; wherein one target node corresponds to a spatial position belonging to a preset node type in the area surrounding the vehicle; Determining, based on the node information of the target node, a target node set including the target node belonging to the same preset transportation facility; Based on the node position information of the target node included in the target node set, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set is displayed.

2. The method according to claim 1, wherein obtaining node information of a target node obtained by performing free space detection on an area surrounding the vehicle comprises: Obtain node information of the initial node obtained by performing free space detection on the area surrounding the vehicle; Filtering nodes that meet preset conditions from the initial nodes according to the node information of the initial nodes to obtain the target node; The preset conditions include: the node type is a preset node type associated with the preset traffic facility; Alternatively, the preset conditions include: the node type is a preset node type associated with the preset traffic facility, and the node is located in a preset surrounding area of ​​the lane line of the lane where the vehicle is located.

3. The method according to claim 2, wherein obtaining node information of an initial node obtained by performing free space detection on an area surrounding the vehicle comprises: Acquiring vehicle surrounding environment data of the vehicle; wherein the vehicle surrounding environment data includes at least one of: an image of the vehicle surrounding environment collected by an image acquisition device, and perception data of the vehicle surrounding environment collected by a radar device; Inputting the vehicle surrounding environment data into a free space detection model built based on a deep learning algorithm to obtain node information of the initial node output by the free space detection model; wherein the node information at least includes: node type information and node location information of the initial node; or, Node information of the initial node obtained by processing the vehicle surrounding environment data using the free space detection model is received.

4. The method according to claim 2, wherein the step of filtering out nodes that meet a preset condition from the initial nodes based on the node information of the initial nodes to obtain the target node comprises: Obtaining lane line position information of the lane in which the vehicle is located; wherein the lane line position information is obtained by performing target detection on an image of the vehicle's surrounding environment, or the lane line position information is determined based on the vehicle's estimated driving trajectory data and preset lane width data; Determining, based on the lane line position information, position information of a preset surrounding area of ​​the lane line of the lane in which the vehicle is located; According to the node position information of the initial node and the position information of the preset surrounding area of ​​the lane line, it is determined whether the initial node is located in the preset surrounding area of ​​the lane line.

5. The method according to claim 4, wherein determining the position information of a preset surrounding area of ​​the lane line of the lane in which the vehicle is located based on the lane line position information comprises: Determining, based on lane line position information of a specific lane line in a lane in which the vehicle is located, position information of a first area with a first width to the left of the specific lane line, and position information of a second area with a second width to the right of the specific lane line, thereby obtaining position information of a preset surrounding area of ​​the specific lane line; If the specific lane marking is a left lane marking, the first width is greater than the second width, and the first width is less than or equal to the lane width of the lane in which the vehicle is located; If the specific lane marking is the right lane marking, the first width is smaller than the second width, and the second width is smaller than or equal to the lane width of the lane in which the vehicle is located.

6. The method according to claim 1, wherein determining, based on the node information of the target node, a target node set including the target node belonging to the same preset transportation facility comprises: According to the node information of the target nodes, clustering processing is performed on the target nodes to obtain at least one target node set; wherein the node information of the target nodes at least includes node position information of the target nodes.

7. The method according to claim 1, wherein the displaying, based on the node location information of the target node included in the target node set, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set comprises: Determining, based on the node position information of each target node included in the target node set, a target area where the preset traffic facilities corresponding to the target node set are located in the image of the vehicle's surrounding environment; generating identification information for the preset traffic facility at the target area, and obtaining an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facility; The target device is used to display an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facilities.

8. The method according to claim 7, wherein determining, based on the node position information of each target node included in the target node set, a target area where preset traffic facilities corresponding to the target node set are located in the vehicle surrounding environment image comprises: Determining the location information of a designated facility portion of a preset transportation facility corresponding to the target node set according to the node location information of each target node included in the target node set; Determining a target area where the preset traffic facility is located in the image of the vehicle's surrounding environment based on the location information of the designated facility and the preset size information of the preset traffic facility; or, Determining actual size information of preset transportation facilities and location information of designated facility parts corresponding to the target node set based on node location information of each target node included in the target node set; According to the position information of the designated facility part and the actual size information, a target area where the preset traffic facility is located in the image of the vehicle's surrounding environment is determined.

9. The method according to claim 7, wherein the step of displaying the vehicle's surrounding environment image carrying the identification information of the preset traffic facility using the target device comprises: Using a screen device carried by the vehicle to display an image of the vehicle's surrounding environment carrying the identification information of the preset traffic facilities; or, The intelligent terminal device is used to display the vehicle's surrounding environment image carrying the identification information of the preset traffic facilities.

10. The method according to claim 1, further comprising: Determining, based on the target nodes included in the target node set, whether the preset traffic facilities corresponding to the target node set are credible traffic facilities, and obtaining a determination result; The display of the vehicle's surrounding environment image carrying identification information of the preset traffic facilities corresponding to the target node set includes: If the judgment result indicates that the preset traffic facilities corresponding to the target node set are credible traffic facilities, an image of the vehicle's surrounding environment carrying identification information of the preset traffic facilities corresponding to the target node set is displayed.

11. The method according to claim 10, wherein determining whether the preset transportation facilities corresponding to the target node set are credible transportation facilities comprises: Determining whether the number of the target nodes included in the target node set is greater than or equal to a preset number; and / or, Determine whether the distance between the preset traffic facilities corresponding to the target node set and the vehicle is less than or equal to a preset distance.

12. The method according to any one of claims 1 to 11, wherein the preset traffic facilities include: At least one of a water-filled guardrail, a crash barrel, and a traffic cone.

13. The method according to claim 12, further comprising: Planning a driving trajectory for the vehicle according to the preset traffic facilities corresponding to the target node set; and / or, Controlling the vehicle according to the preset traffic facilities corresponding to the target node set; and / or, According to the preset traffic facilities corresponding to the target node set, a collision warning is issued to the vehicle.

14. A computer program product comprising a computer program, wherein when the computer program is executed, the steps of the method according to any one of claims 1 to 13 are implemented.

15. An electronic device comprising: A processor and a memory; wherein the memory stores computer-readable instructions, and the computer-readable instructions are suitable for being loaded by the processor and executing the steps of the method according to any one of claims 1 to 13.

16. The electronic device according to claim 15, comprising: At least one of an image acquisition device, a radar device, and a domain controller.

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