Vehicle early warning and control method and related device thereof

Abstract

The invention relates to a vehicle early warning and control method and a related device thereof, and the method comprises the steps: obtaining sensor data collected by a sensor in the driving process of a vehicle, and extracting obstacle information from the sensor data; determining the relative position of the obstacle and the vehicle according to the position information of the obstacle; collecting a plurality of distances between the obstacle and the vehicle in real time; and according to the early warning distance corresponding to the relative position and the distance corresponding to the relative position, determining the risk level of the obstacle, and according to the risk level of the obstacle and the relative position, performing different control operations on the vehicle. According to the scheme provided by the invention, the distance between the obstacle near the vehicle and the vehicle can be monitored in real time, whether the vehicle and the obstacle are scratched or not is predicted, reminding is carried out, the vehicle is automatically controlled to carry out emergency processing, and the driving safety of the vehicle is ensured.

Description

Technical Field

[0001] The present application relates to the field of automobile safe driving technology, and in particular to a vehicle early warning and control method and related devices thereof. Background Art

[0002] With the expansion of cities and the improvement of people's living standards, cars have entered ordinary people's homes and become the main means of transportation in cities. Scratches are a common form of traffic accidents during driving. The main reason is that the driver does not focus on the obstacles on the side of the vehicle, or the driver does not accurately control the distance between the obstacle and the vehicle, or the obstacle is located in the driver's blind spot, which leads to the occurrence of scratches when the vehicle turns or approaches the obstacle.

[0003] At present, the collision warning systems of most vehicles can remind drivers to a certain extent to prevent collision risks. However, since obstacles may be located in various directions of the vehicle, the current monitoring system cannot set the warning distance according to the location of the obstacle and determine the dangerous distance between the vehicle and the obstacle, which reduces the driving safety of the vehicle. Summary of the invention

[0004] In order to solve or partially solve the problems existing in the related technologies, the present application provides a vehicle early warning and control method and related devices, which can monitor the distance between the obstacles near the vehicle and the vehicle in real time, and predict whether the vehicle and the obstacle will have a scratch incident and give a reminder and automatically control the vehicle to avoid the obstacle, so that the driver can react in time and avoid obstacles during driving, thereby improving driving safety and enhancing the driver's driving experience.

[0005] In a first aspect, the present application provides a vehicle early warning and control method, comprising acquiring sensor data collected by a sensor of a vehicle during driving, and extracting obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes position information of the obstacle; determining the relative position of the obstacle to the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; calculating the early warning distance corresponding to each relative position of the obstacle to the vehicle according to the relative position of the obstacle to the vehicle, the obstacle information, the vehicle information of the vehicle, and the road information on which the vehicle is located; collecting multiple distances between the obstacle and the vehicle in real time, wherein each distance corresponds to one relative position; for each relative position, determining the risk level of the obstacle according to the early warning distance corresponding to the relative position and the distance corresponding to the relative position, and performing different control operations on the vehicle according to the risk level of the obstacle and the relative position.

[0006] In combination with the first aspect, in a possible implementation of the first aspect, the warning distance between the obstacle and the vehicle is calculated based on the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle and the road information on which the vehicle is located, including: obtaining the calibration coefficient and information type required for calculating the warning distance based on the relative position of the obstacle and the vehicle, different relative positions corresponding to different calibration coefficients and the information types; extracting the target vehicle information, target obstacle information, and the target distance between the obstacle and the vehicle corresponding to the information type from the vehicle information and the obstacle information; calculating the warning distance at the relative position based on the calibration coefficient, the target vehicle information, the target obstacle information and the target distance, the warning distance being positively correlated with the calibration coefficient, the target vehicle information, the target obstacle information and the target distance.

[0007] In combination with the first aspect, in a possible implementation of the first aspect, the calibration coefficient and information type required for calculating the warning distance are obtained based on the relative position of the obstacle and the vehicle, including: if the relative position is that the obstacle is located in front of or behind the vehicle, then the information type is a longitudinal information type; if the relative position is that the obstacle is located to the left or right of the vehicle, then the information type is a lateral information type.

[0008] In combination with the first aspect, in a possible implementation manner of the first aspect, extracting the target vehicle information, target obstacle information, and the target distance between the obstacle and the vehicle corresponding to the information type from the vehicle information and the obstacle information includes: if the information type is a longitudinal information type, then extracting the longitudinal speed of the obstacle, the longitudinal speed of the vehicle, the longitudinal acceleration of the vehicle, the longitudinal slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle from the vehicle information and the obstacle information; if the information type is a lateral information type, then extracting the lateral speed of the obstacle, the lateral speed of the vehicle, the lateral acceleration of the vehicle, the lateral slope of the road on which the vehicle is located, and the lateral distance between the obstacle and the vehicle from the vehicle information and the obstacle information.

[0009] In combination with the first aspect, in a possible implementation manner of the first aspect, calculating the warning distance at the relative position according to the calibration coefficient, the target vehicle information, the target obstacle information, and the target distance includes: calculating the warning distance when the relative position is that the obstacle is located in front of the vehicle by the following formula:

[0010]

[0011] Among them, k x1 , k x2 , k x3 , k x4 is the first calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_x is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d1 is the first distance constant;

[0012] The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located behind the vehicle:

[0013]

[0014] Among them, k x5 , k x6 , k x7 , k x8 is the second calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, and v obj_y is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a xis the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d2 is the second distance constant.

[0015] In combination with the first aspect, in a possible implementation manner of the first aspect, calculating the warning distance at the relative position according to the calibration coefficient, the target vehicle information, the target obstacle information, and the target distance includes:

[0016] The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located on the left side of the vehicle:

[0017]

[0018] Among them, k y1 , k y2 , k y3 , k y4 is the third calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, and v obj_y is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d3 is the third distance constant; the warning distance when the relative position is that the obstacle is located to the right of the vehicle is calculated by the following formula:

[0019]

[0020] Among them, k y5 , k y6 , k y7 , k y8 is the fourth calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, and v obj_x is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d4 is the fourth distance constant.

[0021] In combination with the first aspect, in a possible implementation of the first aspect, for each relative position, the risk level of the obstacle is determined based on the warning distance corresponding to the relative position and the distance corresponding to the relative position, and different control operations are performed on the vehicle based on the risk level of the obstacle and the relative position.

[0022] , including: determining the risk level of the obstacle according to the warning distances corresponding to the relative positions of the obstacle and the vehicle; if the distance between the obstacle and the vehicle is less than the warning distance, and the distance between the obstacle and the vehicle is at the distance corresponding to the risk level, then giving a corresponding alarm reminder according to the risk level; if the distance between the obstacle and the vehicle is at the distance corresponding to the highest risk level, then performing different control operations on the vehicle according to the relative position between the obstacle and the vehicle, and the control operations at least include decelerating, accelerating, steering, and braking the vehicle.

[0023] In a second aspect, the present application provides a vehicle early warning and control device, comprising an acquisition module, for acquiring sensor data collected by a sensor during the driving process of the vehicle, and extracting obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes the position information of the obstacle; a determination module, for determining the relative position of the obstacle and the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; a calculation module, for calculating the early warning distance corresponding to each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle, and the road information on which the vehicle is located; an acquisition module, for real-time acquisition of multiple distances between the obstacle and the vehicle, wherein each distance corresponds to one relative position; and a reminder module, for determining the risk level of the obstacle for each relative position according to the early warning distance corresponding to the relative position and the distance corresponding to the relative position, and performing different control operations on the vehicle according to the risk level of the obstacle and the relative position.

[0024] In combination with the second aspect, in a possible implementation of the second aspect, the calculation module is also used to obtain the calibration coefficient and information type required to calculate the warning distance according to the relative position of the obstacle and the vehicle, different relative positions correspond to different calibration coefficients and the information types; extract the target vehicle information, target obstacle information, and the target distance between the obstacle and the vehicle corresponding to the information type from the vehicle information and the obstacle information; calculate the warning distance at the relative position according to the calibration coefficient, the target vehicle information, the target obstacle information and the target distance, and the warning distance is positively correlated with the calibration coefficient, the target vehicle information, the target obstacle information and the target distance.

[0025] In combination with the second aspect, in a possible implementation of the second aspect, the calculation module is also used to extract the longitudinal speed of the obstacle, the longitudinal speed of the vehicle, the longitudinal acceleration of the vehicle, the longitudinal slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle from the vehicle information and the obstacle information if the information type is a longitudinal information type; and extract the lateral speed of the obstacle, the lateral speed of the vehicle, the lateral acceleration of the vehicle, the lateral slope of the road on which the vehicle is located, and the lateral distance between the obstacle and the vehicle from the vehicle information and the obstacle information if the information type is a lateral information type.

[0026] In combination with the second aspect, in a possible implementation manner of the second aspect, the calculation module is further used to calculate the warning distance when the relative position is the obstacle located in front of the vehicle by using the following formula:

[0027]

[0028] Among them, k x1 , k x2 , k x3 , k x4 is the first calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_x is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d1 is the first distance constant;

[0029] The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located behind the vehicle:

[0030]

[0031] Among them, k x5 , k x6 , k x7 , k x8 is the second calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, and v obj_y is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d2 is the second distance constant.

[0032] In combination with the second aspect, in a possible implementation manner of the second aspect, the calculation module is further used to calculate the warning distance when the relative position is that the obstacle is located on the left side of the vehicle by using the following formula:

[0033]

[0034] Among them, k y1 , k y2 , k y3 k y4 , is the third calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, v obj_y is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d3 is the third distance constant;

[0035] The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located on the right side of the vehicle:

[0036]

[0037] Among them, k y5 , k y6 , k y7 , k y8 is the fourth calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, and v obj_x is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d4 is the fourth distance constant.

[0038] In combination with the second aspect, in a possible implementation method of the second aspect, the reminder module is also used to determine the risk level of the obstacle according to the warning distances corresponding to the relative positions of the obstacle and the vehicle; if the distance between the obstacle and the vehicle is less than the warning distance, and the distance between the obstacle and the vehicle is at the distance corresponding to the risk level, a corresponding alarm reminder is performed according to the risk level; if the distance between the obstacle and the vehicle is at the distance corresponding to the highest risk level, different control operations are performed on the vehicle according to the relative position between the obstacle and the vehicle, and the control operations at least include decelerating, accelerating, steering, and braking the vehicle.

[0039] A third aspect of the present application provides an electronic device, including:

[0040] Processor; and

[0041] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the method as described above.

[0042] A fourth aspect of the present application provides a computer-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor is caused to execute the method as described above.

[0043] The technical solution provided by this application may have the following beneficial effects:

[0044] The vehicle early warning and control method and related devices of the present application include: obtaining sensor data collected by a sensor of a vehicle during driving, and extracting obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes the position information of the obstacle; determining the relative position of the obstacle and the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; calculating the relative position of each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle, and the road information on which the vehicle is located The system can monitor the distance between the obstacle and the vehicle in real time, predict whether there will be a scratch between the vehicle and the obstacle, and give a reminder, so that the driver can react in time and avoid obstacles during driving, thereby improving driving safety and enhancing the driving experience of the driver.

[0045] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0047] Figure 1 It is a flow chart of a vehicle warning and control method shown in an embodiment of the present application;

[0048] Figure 2is a structural schematic diagram of a vehicle warning and control device shown in an embodiment of the present application;

[0049] Figure 3 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0051] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The singular forms of "a", "a", "an" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in this article refers to and includes any or all possible combinations of one or more associated listed items.

[0052] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0053] Among the related technologies, although the vehicle collision warning system can reduce the risk of collision to a certain extent, it still has some shortcomings in terms of all-round monitoring of obstacles, dynamic risk assessment, danger distance determination and emergency handling.

[0054] At present, the collision warning systems of most vehicles can remind drivers to a certain extent to prevent collision risks. However, since obstacles may be located in various directions of the vehicle, the current monitoring system cannot set the warning distance according to the location of the obstacle and determine the dangerous distance between the vehicle and the obstacle, which reduces the driving safety of the vehicle.

[0055] In response to the above problems, the embodiments of the present application provide a vehicle warning and control method and related devices, which can monitor the distance between obstacles near the vehicle and the vehicle in real time, and predict whether a scratch will occur between the vehicle and the obstacle and provide a reminder, so that the driver can react in time and avoid obstacles during driving, thereby improving driving safety and enhancing the driver's driving experience.

[0056] The technical solution of the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0057] Figure 1 It is a flow chart of the vehicle warning and control method shown in the embodiment of the present application.

[0058] See also Figure 1 , a vehicle early warning and control method, comprising:

[0059] S110: Acquire sensor data collected by a sensor during the driving of the vehicle, and extract obstacle information of at least one obstacle from the sensor data, where the obstacle information at least includes position information of the obstacle.

[0060] Specifically, the vehicle's sensors may include lidar, millimeter-wave radar, high-definition cameras, ultrasonic sensors, etc. The sensors can perform 360-degree monitoring of the vehicle's surroundings without blind spots and obtain data information about the vehicle's surroundings. The lidar is used to obtain three-dimensional point cloud data of the surrounding environment, the millimeter-wave radar is used to detect the distance and speed of obstacles, the high-definition camera is used to capture information such as traffic signals and road signs, and the ultrasonic sensor is used to detect close-range obstacles. It can obtain sensor data from at least one sensor of the vehicle, such as obtaining sensor data collected by the lidar alone, or obtaining sensor data collected by the lidar and sensor data from the high-definition camera at the same time.

[0061] Specifically, the sensor data collected by the sensor can be preprocessed, for example, the sensor data can be denoised, etc. In the process of processing the sensor data collected by multiple sensors, the multiple sensor data can be fused to obtain more accurate environmental data around the vehicle. After the sensor data is preprocessed and fused, obstacle information of at least one obstacle around the vehicle can be extracted from the sensor data. It can be understood that the sensor data can be processed by algorithms such as Kalman filtering, extended Kalman filtering, and particle filtering, and can be used to estimate the motion state of dynamic obstacles.

[0062] Specifically, in the sensor data collected by the sensor, the obstacle information may include the obstacle's location information, speed information, information about the distance from the vehicle, etc. For example, by fusing the three-dimensional point cloud data obtained by the lidar and the obstacle's speed information obtained by the millimeter-wave radar, more accurate obstacle location information, speed information, etc. can be obtained.

[0063] S120: Determine the relative position of the obstacle and the vehicle according to the position information of the obstacle, where the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle.

[0064] Specifically, during the driving process of the vehicle, the obstacle can be located at any position around the vehicle, and the position information of the obstacle can be divided into being located in front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle. It can be understood that when the obstacle is located at the upper left, upper right, etc. of the vehicle, since the vehicle is in the driving process, according to the speed of the vehicle or the speed of the obstacle, it can be predicted that the obstacle will be located in front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle within a period of time. That is, no matter where the obstacle is at a certain relative position of the vehicle at the current moment, the position information of the obstacle can always be defined as being located in front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle; for example, when the obstacle is in motion, the obstacle is not located at any position of the front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle, and the speed of the obstacle is consistent with the speed of the vehicle. It can be understood that the obstacle will not collide with the vehicle at the current moment.

[0065] S130: Calculate a warning distance corresponding to each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle and the road information on which the vehicle is located.

[0066] Specifically, the obstacle information may include the location information and speed information of the obstacle. The vehicle information of the vehicle may include the vehicle type, for example, whether the vehicle is a truck, a bus, etc., the vehicle speed, the road on which the vehicle is located, the vehicle size, and other information. The road information on which the vehicle is located may include road information such as the slope, curvature, and width of the road. By obtaining the relative position of the obstacle and the vehicle, it is determined whether the obstacle is located in front of the vehicle, behind the vehicle, to the left of the vehicle, or to the right of the vehicle. Combined with the obstacle information, vehicle information, and road information, the warning distance between the obstacle and the vehicle can be calculated. It can be understood that the warning distance between the obstacle and the vehicle will change according to the relative position of the obstacle and the vehicle.

[0067] In a possible implementation, according to the relative position of the obstacle and the vehicle, the calibration coefficient and information type required for calculating the warning distance are obtained, and different relative positions correspond to different calibration coefficients and information types; from the vehicle information and obstacle information, the target vehicle information, the target obstacle information, and the target distance between the obstacle and the vehicle corresponding to the information type are extracted; according to the calibration coefficient, the target vehicle information, the target obstacle information and the target distance, the warning distance at the relative position is calculated, and the warning distance is positively correlated with the calibration coefficient, the target vehicle information, the target obstacle information and the target distance.

[0068] Specifically, after obtaining the obstacle information and the relative position of the obstacle and the vehicle, the calibration coefficient for calculating the warning distance between the obstacle and the vehicle can be obtained. The calibration coefficient can be directly obtained from the database or set according to actual needs. When the obstacle is located in front of the vehicle, behind the vehicle, to the left of the vehicle, and to the right of the vehicle, the calibration coefficient corresponding to the warning distance is different. The calibration coefficient can be one or more, and the relevant information type is obtained. The information type can be the relative position relationship between the vehicle and the obstacle.

[0069] Specifically, according to the vehicle information and obstacle information, the corresponding target vehicle information, target obstacle information, and target distance between the obstacle and the vehicle can be obtained from different information types. The vehicle actually in motion has corresponding target vehicle information, target obstacle information, and target distance between the obstacle and the vehicle in the information type. According to the above information, the warning distance between the target obstacle and the target vehicle when they are in a relative position can be calculated, and the warning distance can be used as the warning distance between the obstacle and the vehicle when they are in a relative position at the current moment.

[0070] In a possible implementation, if the relative position is that the obstacle is located in front of or behind the vehicle, the information type is a longitudinal information type. When the obstacle is in front of or behind the vehicle, target obstacle information, target vehicle information, etc. of the obstacle and the vehicle in the longitudinal information type can be obtained; if the relative position is that the obstacle is located on the left or right of the vehicle, the information type is a lateral information type. When the obstacle is on the left or right of the vehicle, target obstacle information, target vehicle information, etc. of the obstacle and the vehicle in the lateral information type can be obtained.

[0071] In a possible implementation, if the information type is a longitudinal information type, the longitudinal speed of the obstacle, the longitudinal speed of the vehicle, the longitudinal acceleration of the vehicle, the longitudinal slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle are extracted from the vehicle information and the obstacle information; if the information type is a lateral information type, the lateral speed of the obstacle, the lateral speed of the vehicle, the lateral acceleration of the vehicle, the lateral slope of the road on which the vehicle is located, and the lateral distance between the obstacle and the vehicle are extracted from the vehicle information and the obstacle information.

[0072] Specifically, the vehicle's longitudinal speed, longitudinal acceleration, and longitudinal slope of the road on which the vehicle is located can be obtained from the vehicle information; the longitudinal speed of the obstacle and the longitudinal distance between the obstacle and the vehicle can be obtained from the obstacle information; the longitudinal warning distance between the obstacle and the vehicle can be calculated based on the longitudinal speed of the obstacle, the longitudinal speed of the vehicle, the longitudinal acceleration of the vehicle, the longitudinal slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle. The longitudinal warning distance can include the longitudinal warning distance when the obstacle is located in front of the vehicle and the longitudinal warning distance when the obstacle is located behind the vehicle.

[0073] Specifically, the vehicle's lateral speed, lateral acceleration, and lateral slope of the road on which the vehicle is located can be obtained from the vehicle information; the lateral speed of the obstacle and the lateral distance between the obstacle and the vehicle can be obtained from the obstacle information; the lateral warning distance between the obstacle and the vehicle can be calculated based on the lateral speed of the obstacle, the lateral speed of the vehicle, the lateral acceleration of the vehicle, the lateral slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle; the lateral warning distance can include the lateral warning distance when the obstacle is located on the left side of the vehicle and the lateral warning distance when the obstacle is located on the right side of the vehicle.

[0074] In a possible implementation, the warning distance when the relative position is that the obstacle is located in front of the vehicle can be calculated by the following formula:

[0075]

[0076] Among them, k x1 , k x2 , k x3 , k x4 is the first calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_x is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, d1 is the first distance constant, k x1 , k x2 , k x3 , k x4The values ​​of k can be different. x1 , k x2 , k x3 , k x4 The value of can be determined according to the type of vehicle, and the first distance constant can be set according to different scenarios.

[0077] In a possible implementation, the warning distance when the relative position is that the obstacle is located behind the vehicle can be calculated by the following formula:

[0078]

[0079] Among them, k x5 , k x6 , k x7 , k x8 is the second calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_y is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, d2 is the second distance constant, k x5 , k x6 , k x7 , k x8 The values ​​of k can be different. x5 , k x6 , k x7 , k x8 The value of can be determined according to the type of vehicle, and the second distance constant can be set according to different scenarios.

[0080] In a possible implementation, the warning distance when the relative position is that the obstacle is located on the left side of the vehicle can be calculated by the following formula:

[0081]

[0082] Among them, k y1 , k y2 , k y3 , k y4 is the third calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, v obj_y is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, d3 is the third distance constant, k y1 , k y2 , k y3 , k y4 The values ​​of k can be different.y1 , k y2 , k y3 , k y4 The value of can be determined according to the type of vehicle, and the third distance constant can be set according to different scenarios.

[0083] In a possible implementation, the warning distance when the relative position is that the obstacle is located to the right of the vehicle can be calculated by the following formula:

[0084]

[0085] Among them, k y5 , k y6 , k y7 , k y8 is the fourth calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, v obj_x is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, d4 ​​is the fourth distance constant, k y5 , k y6 , k y7 , k y8 The values ​​of k can be different. y5 , k y6 , k y7 , k y8 The value of can be determined according to the type of vehicle, and the fourth distance constant can be set according to different scenarios.

[0086] S140: Collect multiple distances between the obstacle and the vehicle in real time, each distance corresponding to a relative position.

[0087] Specifically, the position of the vehicle may change during driving, and the position of the obstacle may also change. The relative distance between the obstacle and the vehicle may change in real time. Multiple distances between the obstacle and the vehicle can be determined in real time, each distance corresponding to a relative position. The relative position between the obstacle and the vehicle can be determined in real time based on multiple distances, and the warning distance between the vehicle and the obstacle can be calculated.

[0088] S150: For each relative position, determine the risk level of the obstacle according to the warning distance corresponding to the relative position and the distance corresponding to the relative position, and perform different control operations on the vehicle according to the risk level of the obstacle and the relative position.

[0089] Specifically, when the vehicle and the obstacle are in a relative position at a certain moment, when the distance between the vehicle and the obstacle enters the warning distance, the vehicle can give a reminder based on the relative position. For example, obstacle A is located 10 meters to the left of the vehicle, please pay attention to avoid it, etc. Voice reminders, screen display reminders, etc. can be given.

[0090] In a possible implementation, the risk level of the obstacle is determined based on the warning distances corresponding to the relative positions of the obstacle and the vehicle; if the distance between the obstacle and the vehicle is less than the warning distance and the distance between the obstacle and the vehicle is at a distance corresponding to the risk level, a corresponding alarm reminder is given according to the risk level; if the distance between the obstacle and the vehicle is at a distance corresponding to the highest risk level, different control operations are performed on the vehicle according to the relative position between the obstacle and the vehicle, and the control operations at least include decelerating, accelerating, steering, and braking the vehicle.

[0091] Specifically, the risk level of the obstacle can be determined according to the warning distance corresponding to the relative position of the obstacle and the vehicle. The risk level can be set to four levels: no risk, low risk, medium risk, and high risk. It can be divided according to the distance between the vehicle and the obstacle being a multiple of 1, 2 / 3, and 1 / 3 of the warning distance. The no risk level can be (+∞, 1], (1, 2 / 3] is a low risk level, (2 / 3, 1 / 3] is a medium risk level, and (1 / 3, 0) is a high risk level.

[0092] Specifically, corresponding alarm reminders can be made according to the risk level of the distance between the vehicle and the obstacle. For example, when the vehicle system detects that obstacles in different directions are at a low risk level, the driver is first warned through sound and visual prompts, and the location of the danger source is informed; when the vehicle system detects that obstacles in different directions are at a medium risk level, the system will gradually increase the reminder intensity, such as vibrating the seat or steering wheel, and inform the location of the danger source; when the vehicle system detects that obstacles in different directions are at a high risk level, if the driver still does not respond, the system can automatically take emergency measures and inform the location of the danger source. Furthermore, different emergency measures can be taken according to the relative position between the obstacle and the vehicle. For obstacles located in front, the vehicle system performs emergency processing operations such as deceleration and steering according to actual working conditions; for obstacles located in the rear, the vehicle system performs emergency processing operations such as acceleration and steering according to actual working conditions; for obstacles located on the left, the vehicle system performs emergency processing operations such as deceleration, acceleration, and right turn according to actual working conditions; for obstacles located on the right, the vehicle system performs emergency processing operations such as deceleration, acceleration, and left turn according to actual working conditions. It is understandable that the vehicle system may be provided with a black box function, which may automatically save relevant data and video for subsequent analysis after the vehicle is at risk of collision or emergency treatment.

[0093] The vehicle warning and control method of the present application includes: obtaining sensor data collected by a sensor during the driving process of the vehicle, and extracting obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes the position information of the obstacle; determining the relative position of the obstacle and the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; calculating the warning distance corresponding to each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle, and the road information on which the vehicle is located; collecting multiple distances between the obstacle and the vehicle in real time, wherein each distance corresponds to a relative position; for each relative position, performing an alarm reminder on the relative position according to the warning distance corresponding to the relative position and the distance corresponding to the relative position, so as to monitor the distance between the obstacle near the vehicle and the vehicle in real time, and predict whether a scratch event will occur between the vehicle and the obstacle and give a reminder, so that the driver can react in time and avoid obstacles during driving, thereby improving driving safety and enhancing the driving experience of the driver.

[0094] Corresponding to the aforementioned application function implementation method embodiment, the present application also provides a vehicle safety distance warning device, an electronic device and corresponding embodiments.

[0095] Figure 2 It is a schematic diagram of the structure of the vehicle warning and control device 200 shown in an embodiment of the present application.

[0096] See also Figure 2 A vehicle warning and control device 200 includes an acquisition module 210, a determination module 220, a calculation module 230, a collection module 240, and a reminder module 250.

[0097] The acquisition module 210 is used to acquire sensor data collected by a sensor during the driving process of the vehicle, and extract obstacle information of at least one obstacle from the sensor data, where the obstacle information at least includes position information of the obstacle.

[0098] Specifically, the vehicle's sensors may include lidar, millimeter-wave radar, high-definition cameras, ultrasonic sensors, etc. The sensors can perform 360-degree monitoring of the vehicle's surroundings without blind spots and obtain data information about the vehicle's surroundings. The lidar is used to obtain three-dimensional point cloud data of the surrounding environment, the millimeter-wave radar is used to detect the distance and speed of obstacles, the high-definition camera is used to capture information such as traffic signals and road signs, and the ultrasonic sensor is used to detect close-range obstacles. It can obtain sensor data from at least one sensor of the vehicle, such as obtaining sensor data collected by the lidar alone, or obtaining sensor data collected by the lidar and sensor data from the high-definition camera at the same time.

[0099] The determination module 220 is used to determine the relative position of the obstacle and the vehicle according to the position information of the obstacle, and the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle.

[0100] Specifically, during the driving process of the vehicle, the obstacle can be located at any position around the vehicle, and the position information of the obstacle can be divided into being located in front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle. It can be understood that when the obstacle is located at the upper left, upper right, etc. of the vehicle, since the vehicle is in the driving process, according to the speed of the vehicle or the speed of the obstacle, it can be predicted that the obstacle will be located in front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle within a period of time. That is, no matter where the obstacle is at a certain relative position of the vehicle at the current moment, the position information of the obstacle can always be defined as being located in front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle; for example, when the obstacle is in motion, the obstacle is not located at any position of the front of the vehicle, located behind the vehicle, located on the left of the vehicle, and located on the right of the vehicle, and the speed of the obstacle is consistent with the speed of the vehicle. It can be understood that the obstacle will not collide with the vehicle at the current moment.

[0101] The calculation module 230 is used to calculate the warning distance corresponding to each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle and the road information on which the vehicle is located.

[0102] Specifically, the obstacle information may include the location information and speed information of the obstacle. The vehicle information of the vehicle may include the vehicle type, for example, whether the vehicle is a truck, a bus, etc., the vehicle speed, the road on which the vehicle is located, the vehicle size, and other information. The road information on which the vehicle is located may include road information such as the slope, curvature, and width of the road. By obtaining the relative position of the obstacle and the vehicle, it is determined whether the obstacle is located in front of the vehicle, behind the vehicle, to the left of the vehicle, or to the right of the vehicle. Combined with the obstacle information, vehicle information, and road information, the warning distance between the obstacle and the vehicle can be calculated. It can be understood that the warning distance between the obstacle and the vehicle will change according to the relative position of the obstacle and the vehicle.

[0103] In a possible implementation, the calculation module 230 is also used to obtain the calibration coefficient and information type required for calculating the warning distance based on the relative position of the obstacle and the vehicle, and different relative positions correspond to different calibration coefficients and information types; extract the target vehicle information, target obstacle information, and target distance between the obstacle and the vehicle corresponding to the information type from the vehicle information and obstacle information; calculate the warning distance at the relative position based on the calibration coefficient, target vehicle information, target obstacle information and target distance, and the warning distance is positively correlated with the calibration coefficient, target vehicle information, target obstacle information and target distance.

[0104] In a possible implementation, the calculation module 230 is also used to extract the longitudinal speed of the obstacle, the longitudinal speed of the vehicle, the longitudinal acceleration of the vehicle, the longitudinal slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle from the vehicle information and the obstacle information if the information type is a longitudinal information type; and to extract the lateral speed of the obstacle, the lateral speed of the vehicle, the lateral acceleration of the vehicle, the lateral slope of the road on which the vehicle is located, and the lateral distance between the obstacle and the vehicle from the vehicle information and the obstacle information if the information type is a lateral information type.

[0105] In a possible implementation, the calculation module 230 is further configured to calculate the warning distance when the relative position is that the obstacle is located in front of the vehicle by using the following formula:

[0106]

[0107] Among them, k x1 , k x2 , k x3 , k x4 is the first calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_x is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d1 is the first distance constant;

[0108] The warning distance when the relative position is the obstacle behind the vehicle is calculated by the following formula:

[0109]

[0110] Among them, k x5 , k x6 , k x7 , k x8 is the second calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_y is the longitudinal velocity of the obstacle, v xis the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d2 is the second distance constant.

[0111] In a possible implementation, the calculation module 230 is further configured to calculate the warning distance when the relative position is that the obstacle is located on the left side of the vehicle by using the following formula:

[0112]

[0113] Among them, k y1 , k y2 , k y3 k y4 , is the third calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, v obj_y is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d3 is the third distance constant;

[0114] The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located to the right of the vehicle:

[0115]

[0116] Among them, k y5 , k y6 , k y7 , k y8 is the fourth calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, v obj_x is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d4 is the fourth distance constant.

[0117] The acquisition module 240 is used to acquire multiple distances between obstacles and vehicles in real time, each distance corresponding to a relative position.

[0118] Specifically, the position of the vehicle will change during driving, and the position of the obstacle may also change. The relative distance between the obstacle and the vehicle can change in real time. Multiple distances between the obstacle and the vehicle can be calculated in real time, each distance corresponds to a relative position, and the relative position between the obstacle and the vehicle can be determined in real time based on multiple distances, and the warning distance between the vehicle and the obstacle can be calculated.

[0119] The reminder module 250 is used to issue an alarm reminder on the relative position for each relative position according to the warning distance corresponding to the relative position and the distance corresponding to the relative position.

[0120] Specifically, when the vehicle and the obstacle are in a relative position at a certain moment, when the distance between the vehicle and the obstacle enters the warning distance, the vehicle can remind the vehicle based on the relative position. For example, obstacle A is 10 meters to the left of the vehicle, please pay attention to avoid it, etc., and voice reminders, screen display reminders, etc. can be given.

[0121] In a possible implementation, the reminder module 250 is also used to determine the risk level of the obstacle based on the warning distances corresponding to the relative positions of the obstacle and the vehicle; if the distance between the obstacle and the vehicle is less than the warning distance, and the distance between the obstacle and the vehicle is at the distance corresponding to the risk level, a corresponding alarm reminder is performed according to the risk level; if the distance between the obstacle and the vehicle is at the distance corresponding to the highest risk level, different control operations are performed on the vehicle according to the relative position between the obstacle and the vehicle, and the control operations at least include decelerating, accelerating, steering, and braking the vehicle.

[0122] The vehicle warning and control device of the present application comprises: obtaining sensor data collected by a sensor during the driving process of the vehicle, and extracting obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes the position information of the obstacle; determining the relative position between the obstacle and the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; calculating the warning distance corresponding to each relative position between the obstacle and the vehicle according to the relative position between the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle, and the road information on which the vehicle is located; collecting multiple distances between the obstacle and the vehicle in real time, wherein each distance corresponds to a relative position; for each relative position, performing an alarm reminder on the relative position according to the warning distance corresponding to the relative position and the distance corresponding to the relative position, so as to monitor the distance between the obstacle near the vehicle and the vehicle in real time, and predict whether a scratch event will occur between the vehicle and the obstacle and give a reminder, so that the driver can react in time and avoid obstacles during driving, thereby improving driving safety and enhancing the driving experience of the driver.

[0123] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0124] Figure 3 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application.

[0125] See also Figure 3 , the electronic device 300 includes a memory 310 and a processor 320.

[0126] The processor 320 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0127] The memory 310 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. Among them, ROM can store static data or instructions required by the processor 320 or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory 310 may include any combination of computer-readable storage media, including various types of semiconductor storage chips (such as DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 310 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0128] The memory 310 stores executable codes, and when the executable codes are processed by the processor 320 , the processor 320 can execute part or all of the methods described above.

[0129] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0130] Alternatively, the present application can also be implemented as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) on which executable code (or computer program or computer instruction code) is stored. When the executable code (or computer program or computer instruction code) is executed by a processor of an electronic device (or server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0131] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A vehicle early warning and control method, characterized in that: include: Acquire sensor data collected by a sensor of the vehicle during driving, and extract obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes position information of the obstacle; Determining the relative position of the obstacle and the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; Calculating a warning distance corresponding to each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle, and the road information on which the vehicle is located; Collecting multiple distances between the obstacle and the vehicle in real time, each distance corresponding to one relative position; For each relative position, the risk level of the obstacle is determined according to the warning distance corresponding to the relative position and the distance corresponding to the relative position, and different control operations are performed on the vehicle according to the risk level of the obstacle and the relative position.

2. The method according to claim 1, characterized in that The calculating the warning distance between the obstacle and the vehicle according to the relative position between the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle and the road information on which the vehicle is located comprises: According to the relative position of the obstacle and the vehicle, a calibration coefficient and information type required for calculating the warning distance are obtained, where different relative positions correspond to different calibration coefficients and information types; Extracting target vehicle information, target obstacle information, and a target distance between the obstacle and the vehicle corresponding to the information type from the vehicle information and the obstacle information; The warning distance at the relative position is calculated according to the calibration coefficient, the target vehicle information, the target obstacle information and the target distance, and the warning distance is positively correlated with the calibration coefficient, the target vehicle information, the target obstacle information and the target distance.

3. The method according to claim 2, characterized in that The obtaining, according to the relative position of the obstacle and the vehicle, the calibration coefficient and the information type required for calculating the warning distance includes: If the relative position is that the obstacle is located in front of or behind the vehicle, the information type is a longitudinal information type; If the relative position is that the obstacle is located on the left or right of the vehicle, the information type is a lateral information type.

4. The method according to claim 3, characterized in that The extracting target vehicle information, target obstacle information, and target distance between the obstacle and the vehicle corresponding to the information type from the vehicle information and the obstacle information includes: If the information type is a longitudinal information type, extracting the longitudinal speed of the obstacle, the longitudinal speed of the vehicle, the longitudinal acceleration of the vehicle, the longitudinal slope of the road on which the vehicle is located, and the longitudinal distance between the obstacle and the vehicle from the vehicle information and the obstacle information; If the information type is a lateral information type, the lateral speed of the obstacle, the lateral speed of the vehicle, the lateral acceleration of the vehicle, the lateral slope of the road on which the vehicle is located, and the lateral distance between the obstacle and the vehicle are extracted from the vehicle information and the obstacle information.

5. The method according to claim 4, characterized in that The step of calculating the warning distance at the relative position according to the calibration coefficient, the target vehicle information, the target obstacle information and the target distance includes: The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located in front of the vehicle: Among them, k x1 , k x2 , k x3 , k x4 is the first calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, v obj_x is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d1 is the first distance constant; The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located behind the vehicle: Among them, k x5 , k x6 , k x7 , k x8 is the second calibration coefficient, Δx is the longitudinal distance between the obstacle and the vehicle, and v obj_y is the longitudinal velocity of the obstacle, v x is the longitudinal velocity of the vehicle, a x is the longitudinal acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, θ is the longitudinal slope of the road on which the vehicle is located, and d2 is the second distance constant.

6. The method according to claim 4, characterized in that The step of calculating the warning distance at the relative position according to the calibration coefficient, the target vehicle information, the target obstacle information and the target distance includes: The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located on the left side of the vehicle: Among them, k y1 , k y2 , k y3 , k y4 is the third calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, and v obj_y is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d3 is the third distance constant; The relative position is calculated by the following formula to obtain the warning distance when the obstacle is located on the right side of the vehicle: Among them, k y5 , k y6 , k y7 , k y8 is the fourth calibration coefficient, Δy is the lateral distance between the obstacle and the vehicle, and v obj_x is the lateral velocity of the obstacle, v y is the lateral velocity of the vehicle, a y is the lateral acceleration of the vehicle, ρ is the curvature of the road on which the vehicle is located, β is the lateral slope of the road on which the vehicle is located, and d4 is the fourth distance constant.

7. The method according to any one of claims 1 to 6, characterized in that: For each of the relative positions, determining the risk level of the obstacle according to the warning distance corresponding to the relative position and the distance corresponding to the relative position, and performing different control operations on the vehicle according to the risk level of the obstacle and the relative position, including: Determining the risk level of the obstacle according to the warning distances respectively corresponding to the relative positions of the obstacle and the vehicle; If the distance between the obstacle and the vehicle is less than the warning distance, and the distance between the obstacle and the vehicle is at a distance corresponding to the risk level, a corresponding alarm reminder is issued according to the risk level; If the distance between the obstacle and the vehicle is at a distance corresponding to the highest risk level, different control operations are performed on the vehicle according to the relative position between the obstacle and the vehicle, and the control operations at least include decelerating, accelerating, steering, and braking the vehicle.

8. A vehicle warning and control device, characterized in that: include: an acquisition module, used to acquire sensor data collected by a sensor of the vehicle during driving, and extract obstacle information of at least one obstacle from the sensor data, wherein the obstacle information at least includes position information of the obstacle; a determination module, configured to determine the relative position of the obstacle and the vehicle according to the position information of the obstacle, wherein the relative position includes the obstacle being located in front of the vehicle, the obstacle being located behind the vehicle, the obstacle being located to the left of the vehicle, and the obstacle being located to the right of the vehicle; a calculation module, configured to calculate a warning distance corresponding to each relative position of the obstacle and the vehicle according to the relative position of the obstacle and the vehicle, the obstacle information, the vehicle information of the vehicle and the road information on which the vehicle is located; A collection module, used for collecting multiple distances between the obstacle and the vehicle in real time, each distance corresponding to one relative position; The reminder module is used to, for each relative position, issue an alarm reminder on the relative position according to the warning distance corresponding to the relative position and the distance corresponding to the relative position.

9. An electronic device, characterized in that: include: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: An executable code is stored thereon, and when the executable code is executed by a processor of an electronic device, the processor is caused to execute the method as claimed in any one of claims 1 to 7.

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