Vehicle obstacle avoidance method, electronic equipment and vehicle

Abstract

The invention provides a vehicle obstacle avoidance method, electronic equipment and a vehicle, which can determine the current road type according to the current position of the vehicle and can provide different obstacle avoidance control strategies for different roads so as to improve the driving safety of the vehicle on different roads. And for a slow road, because the vehicle speed is relatively slow, the vehicle does not have a collision risk at the moment, an expressway with the collision risk needs to be determined in the driving path, and whether the unmanned aerial vehicle needs to be started to assist obstacle avoidance when driving to the corresponding expressway is determined according to the current position and the first predicted vehicle speed. And for the expressway, if the vehicle has the collision risk at the moment, whether the unmanned aerial vehicle needs to be started for auxiliary obstacle avoidance or not is directly determined according to the current vehicle speed. When the first obstacle avoidance condition or the second obstacle avoidance condition is met, the probability of occurrence of the collision risk is high, the unmanned aerial vehicle is started for auxiliary obstacle avoidance, a driver can be helped to predict the front road condition in advance, the collision risk is reduced, and the driving safety is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle obstacle avoidance method, electronic equipment and a vehicle. Background Art

[0002] When a vehicle is driving at high speed, there may be some obstacles on the road that are difficult to detect with the naked eye or pedestrians who suddenly appear. Since the braking distance of the vehicle is large at high speeds, users are unable to avoid sudden obstacles or pedestrians, which greatly increases the probability of traffic accidents. Summary of the invention

[0003] In view of this, the purpose of the present application is to propose a vehicle obstacle avoidance method, electronic equipment and vehicle, which are used to avoid collision between the vehicle and obstacles or pedestrians in the blind spot of the field of vision when the vehicle speed is high, thereby improving driving safety.

[0004] Based on the above objectives, the present application provides a vehicle obstacle avoidance method, comprising:

[0005] Determining a current road type based on a current position of the vehicle;

[0006] In response to the current road type being a slow road, determining whether the expressway exists in the driving path according to the navigation information, determining a first predicted vehicle speed according to the navigation information when the expressway exists, and determining whether a first obstacle avoidance condition is satisfied according to the current position and the first predicted vehicle speed;

[0007] In response to the current road type being an expressway, determining whether a second obstacle avoidance condition is satisfied according to a current vehicle speed;

[0008] In response to satisfying the first obstacle avoidance condition or the second obstacle avoidance condition, the drone is started, and the drone is controlled to monitor the road condition according to the preset detection distance and navigation information, and obstacle avoidance control is performed according to the road condition image monitored by the drone.

[0009] Based on the same inventive concept, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the method as described above when executing the computer program.

[0010] Based on the same inventive concept, the present disclosure also provides a vehicle, comprising the electronic device as described above.

[0011] From the above, it can be seen that the vehicle obstacle avoidance method, electronic device and vehicle provided by the present application can determine the current road type according to the current position of the vehicle; when the current road type is a slow road, determine whether there is an expressway in the driving path according to the navigation information, and determine the first predicted vehicle speed according to the navigation information when there is an expressway, and determine whether the first obstacle avoidance condition is met according to the current position and the first predicted vehicle speed; when the current road type is an expressway, determine whether the second obstacle avoidance condition is met according to the current vehicle speed; when the first obstacle avoidance condition or the second obstacle avoidance condition is met, start the drone, and control the drone to monitor the road condition according to the preset detection distance and navigation information, and perform obstacle avoidance control according to the road condition image monitored by the drone. Determining the current road type according to the current position of the vehicle can provide different obstacle avoidance control strategies for different roads to improve the safety of the vehicle driving on different roads. For slow roads, since the speed is slow, the vehicle does not have a collision risk at this time, so it is necessary to determine the expressway with a collision risk in the driving path, and determine whether it is necessary to turn on the drone to assist in obstacle avoidance when driving to the corresponding expressway according to the current position and the first predicted vehicle speed. For expressways, if the vehicle is already at risk of collision, the current speed will be used to determine whether to activate the drone for obstacle avoidance. When the first obstacle avoidance condition or the second obstacle avoidance condition is met, it means that the vehicle is already or will be driving at high speed on the expressway, and the probability of collision risk is high. Activating the drone for obstacle avoidance can help the driver predict the road conditions ahead in advance, so that the user can brake in advance when obstacles or pedestrians are found, reduce the risk of collision, and improve driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 This is a flow chart of the vehicle obstacle avoidance method according to an embodiment of the present application;

[0014] Figure 2 This is a schematic diagram of segmenting a planned path according to predicted speed in an embodiment of the present application;

[0015] Figure 3 A flowchart for determining whether a first obstacle avoidance condition is met in an embodiment of the present application;

[0016] Figure 4 A flowchart for determining whether the second obstacle avoidance condition is met in an embodiment of the present application;

[0017] Figure 5This is a flow chart of drone-assisted obstacle avoidance at an intersection when driving fast in an embodiment of the present application;

[0018] Figure 6 This is a flow chart of the drone assisted obstacle avoidance when the navigation signal strength is weak in the embodiment of the present application;

[0019] Figure 7 This is a flow chart of an embodiment of the present application for performing obstacle avoidance control based on road condition images monitored by a drone;

[0020] Figure 8 This is a schematic diagram of the structure of a vehicle obstacle avoidance device according to an embodiment of the present application;

[0021] Fig. 9 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0023] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0024] It should be understood herein that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction rather than having any limiting meaning.

[0025] Based on the description of the above background technology, the related technology also has the following situations:

[0026] Braking distance is one of the key parameters to measure the braking performance of a vehicle. It indicates the distance traveled by a vehicle from the beginning of braking to the complete stop of the vehicle when the vehicle is traveling at a certain speed. It is the distance traveled by the vehicle from the moment the driver suddenly steps on the brake pedal to the moment the vehicle stops completely at a certain initial speed. The shorter the braking distance, the better the braking performance of the vehicle.

[0027] Theoretically, when the vehicle brakes, if the tires are locked (i.e. the braking force is greater than or equal to the maximum friction between the tires and the ground and can be maintained until the vehicle stops), the braking distance of the vehicle has nothing to do with the mass of the vehicle. The braking distance of the vehicle mainly depends on the friction between the tires and the ground and the initial speed when braking. The magnitude of the friction depends on the friction coefficient. Assuming the friction coefficient is μ, the braking distance S = V 2 / 2gμ, it can be seen that the braking distance is proportional to the square of the speed and inversely proportional to the friction coefficient. When the friction coefficient is constant, the braking distance depends on the vehicle speed. If the vehicle speed increases by 1 times, the braking distance will theoretically increase by 4 times. If the braking force F is less than the maximum friction between the tire and the ground, the braking distance S=(mV 2 ) / 2F, under the premise that the vehicle mass m and the braking force F remain unchanged, if the vehicle speed increases by 1 times, the braking distance will theoretically increase to 4 times (the actual value may have a certain deviation, because as the braking distance increases, the friction coefficient between the tire and the ground will change).

[0028] Therefore, when a vehicle is driving at high speed, there may be some obstacles on the road that are difficult to detect with the naked eye or pedestrians that suddenly appear, and a collision accident may occur due to untimely braking. The main reason for the collision between the vehicle and obstacles or pedestrians is the high speed. When the user finds an obstacle or pedestrian, the brakes are applied immediately. The braking distance corresponding to the high speed will also be relatively large, which will cause the vehicle to be unable to enter a stationary state before the collision, and then collide with the obstacle or pedestrian, causing safety risks. However, for roads that allow high-speed driving, driving at a low speed all the time will also result in a poor driving experience for users, so other obstacle avoidance solutions are needed to prevent users from colliding with obstacles or pedestrians when driving at high speeds.

[0029] The vehicle obstacle avoidance method, electronic device and vehicle provided in the embodiment of the present application can determine the current road type according to the current position of the vehicle and provide different obstacle avoidance control strategies for different roads to improve the safety of the vehicle on different roads. For slow roads, the vehicle does not have a collision risk at this time, so it is necessary to determine the expressway with a collision risk in the driving path, and determine whether it is necessary to turn on the drone to assist in obstacle avoidance when driving to the corresponding expressway according to the current position and the first predicted vehicle speed. For expressways, the vehicle already has a collision risk at this time, and it is directly determined whether it is necessary to start the drone for assisted obstacle avoidance according to the current vehicle speed. When the first obstacle avoidance condition or the second obstacle avoidance condition is met, it means that the vehicle is already or is about to travel at high speed on the expressway, and the probability of collision risk is high. Starting the drone for assisted obstacle avoidance can help the driver predict the road conditions ahead in advance, so that the user can brake in advance when an obstacle or pedestrian is found, reduce the risk of collision, and improve driving safety.

[0030] The vehicle obstacle avoidance method provided by the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0031] In some embodiments, Figure 1 As shown, a vehicle obstacle avoidance method includes:

[0032] Step 101: Determine the current road type according to the current position of the vehicle.

[0033] In specific implementation, due to the different probabilities of collision risks on different roads, for example, highways are wide and there are no high number of obstacles blocking the line of sight, and guardrails are generally installed on both sides of the road to prevent pedestrians from suddenly rushing out. When users drive vehicles at high speed on highways, they have a wide field of vision and almost no blind spots. Users can subjectively judge whether there is a possibility of collision, and since there are almost no interference factors that affect the user's subjective judgment, the user's subjective judgment has a high degree of credibility. Therefore, there is almost no risk of collision when driving at high speed on highways, and there is no need to start a drone for auxiliary obstacle avoidance.

[0034] For some rural roads and some scenic roads, due to the high speed limit of the road, vehicles are allowed to travel quickly, but there may be dense trees and other obstacles on both sides of the road that block the user's field of vision, causing interference to the user's subjective judgment, making it impossible for the user to understand the subsequent road conditions and unable to perceive whether there are intersections or other obstacles behind the obstructed field of vision. If there are obstacles or pedestrians behind the obstructed field of vision, or there is an intersection, and there are vehicles or non-motor vehicles at the intersection, after the user's field of vision is restored, due to the high speed and long braking distance, the user will not avoid in time, and then a collision accident will occur. In addition, some rural roads and scenic roads may have large potholes or some obstacles that are not easy to detect. When the vehicle is driving at high speed, when the driver finds an obstacle on the road, if the braking distance is greater than the distance between the vehicle and the obstacle, it will lead to a collision risk, and it is necessary to start the drone to assist in obstacle avoidance.

[0035] For some slow roads with low speed limits or suitable for driving at a lower speed, since the vehicle is traveling at a slower speed and the braking distance is shorter, users can complete braking before the collision to avoid a collision. At this time, there is no need to turn on the drone for auxiliary obstacle avoidance.

[0036] Therefore, the current road type determined according to the current position can preliminarily determine whether there is a collision risk at the current moment. The process of determining the current road type is as follows:

[0037] In some embodiments, determining the current road type according to the current position of the vehicle includes:

[0038] Step 1011: Determine the planned path and speed information of the planned path according to the navigation data.

[0039] In specific implementation, after the user enters the destination in the navigation software, the navigation software will provide the user with multiple paths to choose from. After the user performs the selection operation, the path selected by the user from the starting location to the destination is the planned path, and the planned path selected by the user can be determined by reading the navigation data. After the user selects the planned path, the navigation software will obtain the path information corresponding to the planned path, which includes the speed information of the planned path, congestion information, whether there is construction, etc., among which the speed information of the planned path is the speed value of the vehicle traveling on different sections of the planned path (generally the predicted value of the average speed).

[0040] For example, Figure 2 As shown, the handover position represents the dividing position of the vehicle speed value, that is, the vehicle speed value V1 between the starting position and the handover position is different from the vehicle speed value V2 between the handover position and the destination, and there is a large gap between the vehicle speed value V1 and the vehicle speed value V2 (if the speed difference between the vehicle speed value V1 and the vehicle speed value V2 is small, they can be divided into the same speed section).

[0041] Step 1012: Segment the planned path according to the speed information to obtain a plurality of speed sections with different predicted speeds, and determine a target section including the current position.

[0042] In specific implementation, the predicted vehicle speed is the statistical value of the average vehicle speed of different vehicles traveling on the planned route collected by the navigation software. According to the vehicle speed information, the predicted vehicle speed of the first section between the starting position and the handover position is V1, and the predicted vehicle speed of the second section between the handover position and the destination is V2. Among them, if the current position is between the starting position and the handover position, the first section is used as the target section; if the current position is between the handover position and the destination, the second section is used as the target section.

[0043] Step 1013: In response to the target road section being a non-highway, determining a target predicted vehicle speed corresponding to the target road section.

[0044] In specific implementation, the highway is wide and there are no obstacles such as a large number that block the line of sight. When the user drives the vehicle at high speed on the highway, he has a wide field of vision and almost no blind spots. The user's subjective judgment is highly credible, so there is almost no risk of collision when driving at high speed on the highway, and there is no need to start the drone for auxiliary obstacle avoidance. Therefore, if driving on the highway, turn off the drone's auxiliary obstacle avoidance function. Therefore, it is only necessary to start the drone for auxiliary obstacle avoidance on non-highways, so first you need to make sure that the target section is not a highway. After determining that the target section is not a highway, you need to determine the type of the target section based on the target predicted speed corresponding to the target section. If the target section is the first section, the target predicted speed is V1; if the target section is the second section, the target predicted speed is V2.

[0045] Step 1014: In response to the target predicted vehicle speed being less than or equal to a preset vehicle speed threshold, a slow road is determined as the current road type.

[0046] In specific implementation, the vehicle speed threshold is the maximum value of the vehicle speed at which the user will not collide with obstacles within the field of view after actively braking. If the friction coefficient between the tire and the ground is 0.8, the relationship between the vehicle speed and the braking distance is shown in Table 1:

[0047] Table 1 Relationship between vehicle speed and braking distance when the friction coefficient is 0.8

[0048] Vehicle speed (km / h) Braking distance (m) Vehicle speed (km / h) Braking distance (m) 20 2.0 90 39.7 30 4.7 120 70.9 40 7.9 150 110.7 50 12.3 180 159.4 60 17.7 200 196.8 70 24.1 250 307.6 80 31.5

[0049] If 12.3 meters is used as the safe braking distance for the user to actively brake without colliding with obstacles within the field of vision, then the vehicle speed threshold corresponding to the safe braking distance is 50km / h.

[0050] like Figure 2 As shown, if the target section is the first section between the starting position and the handover position, the corresponding target predicted speed is V1. If the target predicted speed is less than or equal to the preset speed threshold, it means that the vehicle is traveling at a lower speed when traveling on the target section, and the corresponding braking distance is shorter. The user brakes after finding an obstacle or pedestrian. The user can complete the braking before the collision to avoid a collision. At this time, there is no need to turn on the drone for auxiliary obstacle avoidance. It is determined that there is no collision risk, and the slow road without collision risk is determined as the current road type.

[0051] Step 1015: In response to the target predicted vehicle speed being greater than a preset vehicle speed threshold, determining an expressway as the current road type.

[0052] In specific implementation, if the target road section is the second road section between the handover location and the destination, the corresponding target predicted speed is V2. If the target predicted speed is greater than the preset speed threshold, it means that the vehicle is traveling at a higher speed when traveling on the target road section, and the corresponding braking distance is longer. The user brakes after finding an obstacle or pedestrian. Due to the high speed and long braking distance, the vehicle will not avoid in time, and a collision accident will occur. In addition, some rural roads and scenic roads may have large potholes or some obstacles that are not easy to detect. When the vehicle is traveling at high speed, if the braking distance is greater than the distance between the vehicle and the obstacle, it will lead to a collision risk, and it is necessary to start the drone for auxiliary obstacle avoidance. The highway where the drone needs to be started for auxiliary obstacle avoidance is determined as the current road type.

[0053] Step 102: In response to the current road type being a slow road, determine whether there is an expressway in the driving path based on navigation information, determine a first predicted vehicle speed based on the navigation information when there is an expressway, and determine whether a first obstacle avoidance condition is met based on the current position and the first predicted vehicle speed.

[0054] In specific implementation, if the current road type is a slow road, it means that the vehicle does not have a collision risk at the current moment. At this time, it continues to determine whether there is an expressway in the subsequent driving stage of the driving path. If there is no expressway, it means that the user has been driving on a low-speed road throughout the entire driving process. There is no collision risk during the entire driving process, and the corresponding drone assisted obstacle avoidance function is directly turned off. If there is an expressway, it means that the vehicle will subsequently enter the expressway from the slow road. In order to ensure safety after entering the expressway, it is necessary to predict the collision risk in advance. At this time, it is necessary to determine the first predicted speed based on the navigation information. The first predicted speed is the predicted speed of the expressway obtained by the navigation software when the current road type is a slow road and there is an expressway in the future.

[0055] Based on the first predicted speed, it can be preliminarily determined whether there is a risk of collision after entering the expressway. If the predicted value of the first predicted speed is greater than the speed threshold, it means that after entering the expressway, if the user drives the vehicle at a speed greater than or equal to the first predicted speed, there will be a risk of collision, and the first obstacle avoidance condition is determined to be met. Otherwise, there is no risk of collision. Based on the current position, the distance of the vehicle from entering the expressway can be determined to determine the specific time to start the drone-assisted obstacle avoidance.

[0056] For slow roads, the vehicle does not have the risk of collision at this time, so it is necessary to determine the expressways with collision risks in the driving path, and determine whether it is necessary to turn on the drone-assisted obstacle avoidance when driving to the corresponding expressway based on the current position and the first predicted vehicle speed to ensure that the vehicle will not have the risk of collision after entering the expressway.

[0057] Step 103: In response to the current road type being an expressway, determining whether a second obstacle avoidance condition is satisfied according to the current vehicle speed.

[0058] In specific implementation, if the current road type is an expressway, it means that the vehicle has already traveled to a section where fast driving is allowed and most vehicles are traveling at a speed greater than the speed threshold. At this time, it is possible to determine whether there is a collision risk based on the current speed of the vehicle, because as long as the user travels at a lower speed, the braking distance will be smaller. When the user finds that there is a collision risk, the collision can be avoided by braking control. Therefore, it is possible to determine whether the second obstacle avoidance condition is met based on the current speed. For expressways, if the vehicle already has a collision risk at this time, it is directly determined based on the current speed whether the drone needs to be started for auxiliary obstacle avoidance to ensure that there is no collision risk when the vehicle is driving on the expressway.

[0059] Step 104: In response to satisfying the first obstacle avoidance condition or the second obstacle avoidance condition, the drone is started, and the drone is controlled to monitor the road condition according to the preset detection distance and navigation information, and obstacle avoidance control is performed according to the road condition image monitored by the drone.

[0060] During specific implementation, if the first obstacle avoidance condition is met, it means that you are about to enter an expressway and you need to determine the specific road conditions of the expressway. At this time, you need to start the engine to assist in obstacle avoidance. The drone detects the road conditions at a distance in front of the vehicle to identify intersections and obstacles on the expressway, and displays the road condition images sent by the drone to the driver. The driver can predict the road intersections and obstacles ahead in advance based on the road condition images, so as to achieve early braking, reduce the risk of collision, and ensure the safety of the vehicle's fast driving on the expressway.

[0061] If the second obstacle avoidance condition is met, it means that the vehicle is already traveling at a relatively fast speed on the expressway, and the specific road conditions of the expressway need to be determined. At this time, the engine needs to be started to assist in obstacle avoidance. The drone detects the road conditions at a distance in front of the vehicle to identify intersections and obstacles on the expressway, and displays the road condition images sent by the drone to the driver. The driver can predict the road intersections and obstacles ahead in advance based on the road condition images, so as to achieve early braking, reduce the risk of collision, and ensure the safety of the vehicle's fast driving on the expressway.

[0062] Therefore, when the first obstacle avoidance condition or the second obstacle avoidance condition is met, it means that the vehicle is already or is about to travel at high speed on the expressway, and the probability of collision risk is high. Starting the drone for auxiliary obstacle avoidance can help the driver predict the road conditions ahead in advance, so that the user can brake in advance when obstacles or pedestrians are found, reduce the risk of collision, and improve driving safety.

[0063] In summary, the vehicle obstacle avoidance method provided by the embodiment of the present application can determine the current road type according to the current position of the vehicle and provide different obstacle avoidance control strategies for different roads to improve the safety of the vehicle on different roads. For slow roads, the vehicle does not have a collision risk at this time, so it is necessary to determine the expressway with a collision risk in the driving path, and determine whether it is necessary to turn on the drone to assist in obstacle avoidance when driving to the corresponding expressway based on the current position and the first predicted vehicle speed. For expressways, the vehicle already has a collision risk at this time, so it is directly determined based on the current vehicle speed whether it is necessary to start the drone for assisted obstacle avoidance. When the first obstacle avoidance condition or the second obstacle avoidance condition is met, it means that the vehicle is already or is about to travel at high speed on the expressway, and the probability of a collision risk is high. Starting the drone for assisted obstacle avoidance can help the driver predict the road conditions ahead in advance, so that the user can brake in advance when an obstacle or pedestrian is found, reduce the risk of collision, and improve driving safety.

[0064] In some embodiments, Figure 3 As shown, determining whether the first obstacle avoidance condition is met according to the current position and the first predicted vehicle speed includes:

[0065] Step 301: Determine the intersection position of the slow road and the fast road.

[0066] In specific implementation, when driving on a slow road, since the average speed of vehicles on the first section corresponding to the slow road is relatively low, the user will be reminded that the current road conditions are more suitable for slow-driving vehicles, and since the objective condition is that the remaining vehicles are driving at a slow speed, it is difficult for the user to drive at a higher speed, so the user will generally drive at a slower speed (for example, less than 50 km / h) on the slow road. If the traffic conditions on the subsequent second section of the planned path improve, the second section objectively allows the user to drive at a faster speed (for example, greater than 50 km / h). At this time, the slow road becomes an expressway, and the segmentation position of the first section and the second section is the intersection of the slow road and the expressway. After passing the intersection, the user enters the expressway, and is allowed to drive at a faster speed on the expressway. The braking distance is large, and there is a corresponding collision risk. Therefore, it is necessary to determine the intersection position to achieve the switching of the judgment results of whether there is a collision risk and whether there is no collision risk.

[0067] Step 302: Determine the interval distance between the current position and the handover position.

[0068] In specific implementation, since there is a risk of collision when entering the expressway after passing the handover position, risk avoidance needs to be performed in advance. Therefore, the interval distance between the current position and the handover position needs to be determined to determine how far there is to enter the expressway where there is a risk of collision.

[0069] Step 303: In response to the interval distance being less than or equal to a preset distance threshold, determining that a first obstacle avoidance condition is satisfied.

[0070] In specific implementation, if the interval distance is less than or equal to a preset distance threshold (for example, 2km), it means that the vehicle is about to enter an expressway. Since the first predicted speed corresponding to the expressway is greater than the speed threshold, there is a risk of collision after entering the expressway, and risk avoidance needs to be performed in advance. At this time, a drone needs to be started for auxiliary obstacle avoidance, so that the drone can obtain the road condition image of the expressway in advance, so that the driver can understand the road condition of the expressway in advance, slow down or brake in advance, avoid collision with obstacles or pedestrians, and ensure driving safety.

[0071] Step 304: In response to the interval distance being greater than a preset distance threshold, when the interval distance is less than or equal to the distance threshold, determine a second predicted vehicle speed based on the navigation information, and determine whether the first obstacle avoidance condition is met based on the first predicted vehicle speed and the second predicted vehicle speed.

[0072] In specific implementation, if the interval distance is less than or equal to the preset distance threshold (for example, 2km), it means that the vehicle is still a long distance away from entering the expressway, and it will take a long time to enter the expressway. However, the traffic conditions of the second section of the planned route will change over time (for example, during rush hour, there are more vehicles, the traffic conditions are poor, and the predicted speed is low). Because the speed prediction is obtained by counting the real-time speed of vehicles traveling on the road, the predicted speed changes dynamically. Therefore, it is necessary to perform a close-range speed prediction again when the interval distance is less than or equal to the distance threshold to obtain the second predicted speed. The second predicted speed is used to verify the validity of the first predicted speed. It has been determined that there is indeed a risk of collision after entering the expressway, avoiding the use of drones to assist in obstacle avoidance in low-speed sections, avoiding the frequent start and stop of drones caused by switching between high and low speed sections in short distances, improving the overall obstacle avoidance effect, and improving driving safety. The specific validity verification process is as follows:

[0073] In some embodiments, determining whether the first obstacle avoidance condition is satisfied according to the first predicted vehicle speed and the second predicted vehicle speed includes:

[0074] Step 3041: In response to the first predicted vehicle speed being less than or equal to the second predicted vehicle speed, determining that the first obstacle avoidance condition is satisfied.

[0075] In specific implementation, if the first predicted vehicle speed is less than or equal to the second predicted vehicle speed, it means that the short-distance predicted vehicle speed is greater than the long-distance predicted vehicle speed, which means that the vehicles on the expressway are traveling at a faster speed, the braking distance is increased, and the possibility of untimely braking is higher, resulting in a greater probability of collision risk. Therefore, there is still a collision risk on the expressway, and it is necessary to avoid the risk in advance before entering the expressway. Therefore, to determine that the first obstacle avoidance condition is met, it is necessary to start the drone for auxiliary obstacle avoidance, so as to obtain the road condition image of the expressway in advance through the drone, so that the driver can understand the road condition of the expressway in advance, slow down or brake in advance, avoid collision with obstacles or pedestrians, and ensure driving safety.

[0076] Step 3042: In response to the first predicted vehicle speed being greater than the second predicted vehicle speed, determining a vehicle speed difference between the first predicted vehicle speed and the second predicted vehicle speed.

[0077] In specific implementation, if the first predicted speed is greater than the second predicted speed, it means that the predicted speed at a short distance is greater than the predicted speed at a long distance, indicating that the vehicles on the expressway are traveling at a slower speed, and the braking distance is reduced, which may cause the expressway to become a slow road. In this case, there is no need to avoid risks in advance. There are two situations that can cause the second predicted speed to become smaller. In the first case, since the predicted speed is dynamically changing, the predicted speed is allowed to fluctuate to a certain extent. It may be a reasonable dynamic change caused by the predicted speed fluctuation, indicating that the first speed is valid, and it is not that the expressway has become a slow road, and the risk of collision needs to be avoided in advance. The second case is that the expressway changes its road type due to special circumstances and becomes a slow road. For example, a car accident occurred on the second section, which was originally an expressway, causing vehicles to slow down when passing through the second section to avoid the accident vehicle. At this time, since all vehicles are traveling at a low speed on the second section, the road type of the second section has changed from an expressway to a slow road, and there is no need to avoid collision risks in advance.

[0078] Therefore, it is necessary to determine the speed difference between the first predicted speed and the second predicted speed, and determine the reason why the second predicted speed is lower than the first predicted speed based on the size of the speed difference, so as to avoid starting the drone to assist in obstacle avoidance on a low-speed road and avoid wasting resources.

[0079] Step 3043: In response to the vehicle speed difference being greater than or equal to a preset difference threshold, determining that the first obstacle avoidance condition is not satisfied.

[0080] During specific implementation, if the vehicle speed difference is greater than or equal to the preset difference threshold and exceeds the range of normal fluctuations, it means that the second section, which is an expressway, has switched road types due to other reasons. At this time, the expressway becomes a slow road. It is determined that there is no collision risk in the second section and there is no need to avoid the collision risk in advance. It is determined that the first obstacle avoidance condition is not met and there is no need to avoid the risk in advance.

[0081] At this time, if the speed difference is greater than the difference threshold and greater than the preset maximum difference, it means that the second predicted speed of the second section of the road is greatly deviated from the first predicted speed, and a more serious traffic accident may have occurred on the second section of the road. At this time, the user can be actively prompted whether to start the drone for road condition monitoring, so as to obtain the road condition image ahead in advance through the drone, so that the driver can understand the road condition ahead in advance and avoid serious traffic accidents on the road ahead, which may make it impossible to pass ahead. The user can be guided to change the planned route to ensure that the destination can be reached within the accurate estimated time, thereby improving the user experience while ensuring the user's driving safety.

[0082] Step 3044: In response to the vehicle speed difference being less than a preset difference threshold, determining that the first obstacle avoidance condition is satisfied.

[0083] In specific implementation, if the speed difference is less than the preset difference threshold, it means that the second predicted speed becomes smaller due to normal fluctuations, and the judgment of the first predicted speed is accurate. It is necessary to avoid risks in advance before entering the expressway to ensure that the first obstacle avoidance condition is met.

[0084] By checking between the second predicted vehicle speed and the first predicted vehicle speed, it is ensured that the drone-assisted obstacle avoidance will not be activated on a slow road, thus avoiding ineffective obstacle avoidance control and reducing waste of resources.

[0085] In some embodiments, Figure 4 As shown, determining whether the second obstacle avoidance condition is met according to the current vehicle speed includes:

[0086] Step 401: In response to the current vehicle speed being less than a preset vehicle speed threshold, determining that the second obstacle avoidance condition is not satisfied.

[0087] In specific implementation, if the current vehicle speed is less than the preset vehicle speed threshold, it means that the user chooses to drive slowly on the expressway, the braking distance is small, the risk is controllable, and there is no need to turn on the drone for auxiliary obstacle avoidance, and it is determined that the second obstacle avoidance condition is not met.

[0088] Step 402: In response to the current vehicle speed being greater than or equal to a preset vehicle speed threshold, determining whether the vehicle is in a flight restricted area based on the current position.

[0089] In specific implementation, if the current vehicle speed is greater than or equal to the preset speed threshold, it means that the user chooses to drive fast on the expressway, the braking distance is large, and there is a risk of uncontrolled collision. It is necessary to turn on the drone for auxiliary obstacle avoidance. However, it is necessary to first determine whether the vehicle is in a restricted flight area to avoid illegal startup of the drone.

[0090] Step 403: In response to the vehicle being in the flight restricted area, it is determined that the second obstacle avoidance condition is not satisfied, and a deceleration prompt is issued.

[0091] In specific implementation, the vehicle is in a restricted flight area, indicating that the current location prohibits the drone from taking off, and it is determined that the second obstacle avoidance condition is not met, and a deceleration prompt is given to prompt the user to slow down to reduce the braking distance, avoid collision risks, and improve driving safety.

[0092] Step 404: In response to the vehicle not being in the flight restricted area, determining that a second obstacle avoidance condition is satisfied.

[0093] During specific implementation, the vehicle is not in a restricted flight area, indicating that the current position allows the drone to take off. It is determined that the second obstacle avoidance condition is met, and the drone is started for auxiliary obstacle avoidance. The drone is controlled to detect road conditions at a preset distance in front of the vehicle to identify intersections and obstacle images and distances and other information and feed it back to the user. The user can predict the intersection and obstacle information ahead in advance, and then brake or slow down in advance when there are obstacles, reducing the risk of collision and improving driving safety.

[0094] In some embodiments, Figure 5 As shown, after determining that the current road type is an expressway, the method further includes:

[0095] Step 501: Determine whether there is an intersection within a preset navigation distance based on the current position and navigation information.

[0096] During specific implementation, some sections of the intersection have no prompts or the prompts are not obvious, or there are blind spots (buildings / trees) blocking the view, etc., and it is difficult for users to perceive the existence of intersections on the road ahead. If there are vehicles or pedestrians at the intersection, the increased braking distance at high speeds will result in untimely avoidance, and there is a great risk of collision, causing losses to both parties. Therefore, it is necessary to understand the road conditions of intersections on the highway in advance. Therefore, it is necessary to first determine whether there is an intersection within the preset navigation distance (for example, 1.5km), because there is no practical reference significance for monitoring intersections that are too far in advance, because as the distance to the intersection gets closer, the visible length of the remaining roads in the intersection within the user's field of view becomes smaller, and the user's perception of whether there will be vehicles or pedestrians at the remaining intersections becomes weaker. Therefore, it is only necessary to monitor the corresponding intersection when the vehicle is about to enter the intersection to ensure the effectiveness of advance monitoring.

[0097] Step 502: In response to the existence of an intersection and the current vehicle speed being greater than or equal to a preset vehicle speed threshold, the drone is started to monitor the intersection and perform obstacle avoidance control based on the intersection image.

[0098] In specific implementation, if there is an intersection and the current vehicle speed is greater than or equal to the preset speed threshold, it means that for an intersection that is not easy to perceive, if there are vehicles or pedestrians at the intersection, the larger braking distance will cause untimely avoidance, which in turn leads to a collision accident. Therefore, it is necessary to start the drone to assist in obstacle avoidance at this time, so that the driver can understand the intersection ahead in advance and avoid collision with vehicles or pedestrians suddenly appearing at the intersection, thereby ensuring the user's driving safety.

[0099] In some embodiments, Figure 6 As shown, before determining the current road type according to the current position of the vehicle, it also includes:

[0100] Step 601: Determine the signal strength of the navigation signal.

[0101] During specific implementation, the determination of the predicted vehicle speed requires ensuring the signal strength of the navigation signal to ensure that the navigation software can collect the driving speeds of different vehicles in real time, and then predict the vehicle speed based on the collected speeds. Only a good signal strength can ensure the accuracy and credibility of the first predicted vehicle speed and the second predicted vehicle speed. Therefore, it is necessary to first determine the signal strength of the navigation signal to determine whether the navigation information is credible.

[0102] Step 602: In response to the signal strength being less than or equal to a preset strength threshold and the current vehicle speed being greater than or equal to a preset vehicle speed threshold, the drone is started, and the drone is controlled to monitor the road condition according to the preset detection distance and navigation information, and obstacle avoidance control is performed according to the road condition image monitored by the drone.

[0103] In specific implementation, if the signal strength is less than or equal to the preset strength threshold, the local cache map can be used for navigation, but the speed information of other vehicles cannot be collected at this time, and the dynamic prediction of the speed cannot be realized. Therefore, the predicted speed at this time is unreliable. It is directly determined whether to avoid risks in advance based on the current speed. If the speed of the front vehicle is greater than or equal to the preset speed threshold, the drone is started and controlled to monitor the road conditions according to the preset detection distance and navigation information, so that the driver can understand the road conditions ahead in advance, and perform obstacle avoidance control according to the road condition images monitored by the drone to avoid collisions. Ensure user driving safety.

[0104] In some embodiments, Figure 7 As described above, obstacle avoidance control is performed based on the road condition image monitored by the drone, including:

[0105] Step 701: Obstacle identification is performed on the road image according to a preset obstacle library.

[0106] In specific implementation, since users cannot always stare at the display screen to watch, it is necessary to identify obstacles in the road condition image according to the preset obstacle library to assist users in identifying obstacles in the road condition image and avoid users being unable to fully use the road condition image.

[0107] Step 702: In response to identifying an obstacle in the road condition image, an obstacle avoidance prompt is provided according to the obstacle distance and the obstacle avoidance distance between the vehicle and a deceleration prompt is provided.

[0108] During specific implementation, if an obstacle is identified in the road condition image, it means there is a collision risk, and the obstacle avoidance distance between the obstacle and the vehicle is determined. If the obstacle avoidance distance is less than the preset safety distance (for example, 300m), an obstacle avoidance prompt is given to inform the user that there is an obstacle ahead, and a deceleration prompt is given to reduce the braking distance, ensuring that the user can perform braking control in time to avoid collision and ensure driving safety.

[0109] When leaving the expressway or the user actively calls the drone back, the drone will be retracted and charged to ensure that the drone can continue to assist in obstacle avoidance next time. The drone can also be automatically retracted when the drone battery is low, and the user will be prompted that the drone battery is too low to assist in obstacle avoidance, and the user should be prompted to drive carefully.

[0110] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.

[0111] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0112] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a vehicle obstacle avoidance device.

[0113] refer to Figure 8 , a vehicle obstacle avoidance device, comprising:

[0114] The road classification module 10 is configured to: determine the current road type according to the current position of the vehicle;

[0115] The slow road obstacle avoidance module 20 is configured to: in response to the current road type being a slow road, determine whether there is an expressway in the driving path according to the navigation information, determine a first predicted vehicle speed according to the navigation information when there is an expressway, and determine whether a first obstacle avoidance condition is met according to the current position and the first predicted vehicle speed;

[0116] The expressway obstacle avoidance module 30 is configured to: in response to the current road type being an expressway, determine whether a second obstacle avoidance condition is satisfied according to the current vehicle speed;

[0117] The drone control module 40 is configured to: in response to satisfying the first obstacle avoidance condition or the second obstacle avoidance condition, start the drone, control the drone to monitor the road condition according to the preset detection distance and navigation information, and perform obstacle avoidance control according to the road condition image monitored by the drone.

[0118] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0119] The device of the above embodiment is used to implement the corresponding vehicle obstacle avoidance method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0120] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the vehicle obstacle avoidance method described in any of the above embodiments is implemented.

[0121] Fig. 9 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0122] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0123] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0124] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0125] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0126] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0127] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0128] The electronic device of the above embodiment is used to implement the corresponding vehicle obstacle avoidance method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0129] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the vehicle obstacle avoidance method described in any of the above embodiments.

[0130] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0131] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the vehicle obstacle avoidance method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0132] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a vehicle, including the electronic device or vehicle obstacle avoidance device of the above-mentioned embodiment, and the vehicle obstacle avoidance method described in any of the above embodiments is executed through the electronic device or vehicle obstacle avoidance device of the above-mentioned embodiment, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0133] It is understandable that before using the technical solutions of each embodiment of the present disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0134] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0135] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0136] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0137] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0138] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0139] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0140] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the protection scope of the present application.

Claims

1. A vehicle obstacle avoidance method, characterized in that: include: Determining a current road type based on a current position of the vehicle; In response to the current road type being a slow road, determining whether the expressway exists in the driving path according to the navigation information, determining a first predicted vehicle speed according to the navigation information when the expressway exists, and determining whether a first obstacle avoidance condition is satisfied according to the current position and the first predicted vehicle speed; In response to the current road type being an expressway, determining whether a second obstacle avoidance condition is satisfied according to a current vehicle speed; In response to satisfying the first obstacle avoidance condition or the second obstacle avoidance condition, the drone is started, and the drone is controlled to monitor the road condition according to the preset detection distance and navigation information, and obstacle avoidance control is performed according to the road condition image monitored by the drone.

2. The vehicle obstacle avoidance method according to claim 1, characterized in that: Determining the current road type according to the current position of the vehicle includes: Determine a planned path and speed information of the planned path according to the navigation data; Segmenting the planned path according to the speed information to obtain a plurality of speed sections with different predicted speeds, and determining a target section including the current position; In response to the target road section being a non-highway, determining a target predicted vehicle speed corresponding to the target road section; In response to the target predicted vehicle speed being less than or equal to a preset vehicle speed threshold, determining the slow road as the current road type; In response to the target predicted vehicle speed being greater than a preset vehicle speed threshold, the expressway is determined as the current road type.

3. The vehicle obstacle avoidance method according to claim 1, characterized in that: The determining whether a first obstacle avoidance condition is met according to the current position and the first predicted vehicle speed includes: Determine the intersection position of the slow road and the fast road; Determine the interval distance between the current position and the handover position; In response to the interval distance being less than or equal to a preset distance threshold, determining that the first obstacle avoidance condition is satisfied; In response to the interval distance being greater than a preset distance threshold, when the interval distance is less than or equal to the interval threshold, a second predicted vehicle speed is determined according to the navigation information, and whether the first obstacle avoidance condition is met is determined according to the first predicted vehicle speed and the second predicted vehicle speed.

4. The vehicle obstacle avoidance method according to claim 3, characterized in that: The determining whether the first obstacle avoidance condition is met according to the first predicted vehicle speed and the second predicted vehicle speed includes: In response to the first predicted vehicle speed being less than or equal to the second predicted vehicle speed, determining that the first obstacle avoidance condition is satisfied; In response to the first predicted vehicle speed being greater than the second predicted vehicle speed, determining a vehicle speed difference between the first predicted vehicle speed and the second predicted vehicle speed; In response to the vehicle speed difference being greater than or equal to a preset difference threshold, determining that the first obstacle avoidance condition is not satisfied; In response to the vehicle speed difference being less than a preset difference threshold, it is determined that the first obstacle avoidance condition is met.

5. The vehicle obstacle avoidance method according to claim 1, characterized in that: The determining whether the second obstacle avoidance condition is met according to the current vehicle speed includes: In response to the current vehicle speed being less than a preset vehicle speed threshold, determining that the second obstacle avoidance condition is not satisfied; In response to the current vehicle speed being greater than or equal to a preset vehicle speed threshold, determining whether the vehicle is in a flight restricted area according to the current position; In response to the vehicle being in a flight restricted area, determining that the second obstacle avoidance condition is not satisfied, and providing a deceleration prompt; In response to the vehicle not being in a flight-restricted area, it is determined that the second obstacle avoidance condition is satisfied.

6. The vehicle obstacle avoidance method according to claim 1, characterized in that: After determining that the current road type is an expressway, the method further includes: Determining, based on the current location and the navigation information, whether there is an intersection within a preset navigation distance; In response to the existence of an intersection and the current vehicle speed being greater than or equal to a preset vehicle speed threshold, the drone is started to monitor the intersection and perform obstacle avoidance control based on the intersection image.

7. The vehicle obstacle avoidance method according to claim 1, characterized in that: Before determining the current road type based on the vehicle's current position, it also includes: determining the signal strength of the navigation signal; In response to the signal strength being less than or equal to a preset strength threshold and the current vehicle speed being greater than or equal to a preset vehicle speed threshold, the drone is started, and the drone is controlled to monitor road conditions according to a preset detection distance and navigation information, and obstacle avoidance control is performed according to the road condition image monitored by the drone.

8. The vehicle obstacle avoidance method according to claim 1, characterized in that: The obstacle avoidance control according to the road condition image monitored by the drone includes: Performing obstacle recognition on the road condition image according to a preset obstacle library; In response to identifying an obstacle in the road condition image, an obstacle avoidance prompt is provided according to an obstacle avoidance distance between the obstacle and the vehicle, and a deceleration prompt is provided.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 9.

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