CN112237513A

CN112237513A - Carrier control method, carrier control device, electronic equipment and storage medium

Info

Publication number: CN112237513A
Application number: CN202011120604.1A
Authority: CN
Inventors: 李建国; 张扬; 张青来; 刘伯锋; 姜士伟; 程晨航; 李永强; 廖香成
Original assignee: Jiangsu Bangbang Intelligent Technology Co ltd
Current assignee: Jiangsu Bangbang Intelligent Technology Co ltd
Priority date: 2020-10-19
Filing date: 2020-10-19
Publication date: 2021-01-19
Anticipated expiration: 2040-10-19
Also published as: CN116238485A; CN112237513B

Abstract

The application provides a vehicle control method, a vehicle control device, an electronic device and a storage medium, wherein a sensor is used for detecting the driving environment of a vehicle to determine a detection result, then a target driving scene and a corresponding target control parameter are determined according to the detection result, and finally the vehicle is controlled to safely drive in the target driving scene according to the target control parameter. The technical problems that the traveling scene of the mobility aid carrier of the old or the disabled cannot be intelligently identified and the driving is automatically assisted according to the traveling scene are solved, and the technical effects of improving the use experience and the use safety of the mobility aid carrier, such as an electric wheelchair, used by the old or the disabled are achieved.

Description

Carrier control method, carrier control device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of automatic control, and in particular, to a carrier control method and apparatus, an electronic device, and a storage medium.

Background

With the increase of the population of the old, the demand of the transportation vehicles for the old or the disabled, such as the electric folding wheel chairs, is more and more, and the demand is higher and higher.

The control system of the existing transportation vehicle such as the electric wheelchair only simply responds to the control command of the operating lever or the operating button to execute the most basic operations such as advancing, braking and the like, but in a complex driving environment such as turning around of an elevator car and driving on a pothole road surface, various problems in the driving process are completely solved by depending on the driving level of a user, or additional auxiliary personnel are needed to perform manual intervention.

Therefore, the user of the transportation vehicle cannot well and independently cope with the complex driving environment, and the technical problem that the use experience of the transportation vehicle of the user is poor is caused.

Disclosure of Invention

The application provides a vehicle control method, a vehicle control device, electronic equipment and a storage medium, and aims to solve the technical problems that in the prior art, a mobility vehicle of middle-aged and elderly people or disabled people cannot intelligently identify a driving scene, and driving assistance is automatically performed according to the driving scene.

In a first aspect, the present application provides a vehicle control method, including:

detecting the driving environment of the vehicle by using a sensor to determine a detection result;

determining a target driving scene and corresponding target control parameters according to the detection result;

and controlling the vehicle to safely run in the target running scene according to the target control parameters.

In one possible design, the detecting result includes an obstacle distance, and the determining the target driving scene and the corresponding target control parameter according to the detecting result includes:

determining obstacle types according to the obstacle distances;

determining the target driving scene according to the obstacle category;

and determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, wherein the target control parameters comprise the obstacle avoidance control parameters.

Optionally, the target driving scenario includes: normal driving scenes, road surface unevenness scenes and narrow space scenes.

In one possible design, the sensor includes: first ground sensor and second ground sensor, first ground sensor and second ground sensor are used for detecting the oblique line distance of sensor to road surface, and is corresponding, obstacle distance includes first oblique line distance and second oblique line distance, first oblique line distance is greater than second oblique line distance, according to obstacle distance confirms the obstacle classification, include:

if the fluctuation range of the first oblique line distance and the second oblique line distance is smaller than a preset fluctuation threshold value, determining that the obstacle type is barrier-free, and determining that the corresponding target driving scene is a normal driving scene.

Optionally, the determining the obstacle category according to the obstacle distance includes:

if the first fluctuation amplitude of the first oblique line distance is larger than or equal to the preset fluctuation threshold value, and the second fluctuation amplitude of the second oblique line distance is smaller than the preset fluctuation threshold value, determining that the obstacle type is a pit or a bulge, and determining that the corresponding road surface rough scene is a pit or a bulge.

In one possible design, the determining the obstacle category according to the obstacle distance includes:

if the difference value between the average change rate of the first slash distance and the average change rate of the second slash distance is smaller than a preset change rate difference value, determining that the obstacle type is a gentle slope, and determining that the corresponding road surface rough scene is a gentle slope road surface;

if the difference value between the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is larger than or equal to the preset change rate difference value, determining that the obstacle type is an uneven ramp obstacle, and the corresponding uneven road scene is an uneven ramp road;

and if the difference value between the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is greater than or equal to the preset change rate difference value, determining that the obstacle type is an uneven ramp obstacle, and determining that the corresponding uneven road scene is an uneven ramp road.

Optionally, the sensor includes a gyroscope, the detection result includes a gradient, and the determining the obstacle category according to the obstacle distance includes:

if the difference value between the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is smaller than the preset change rate difference value, and the slope is smaller than the preset slope threshold value, determining that the obstacle type is a downhill gentle slope, and determining that the corresponding road surface rough scene is a downhill gentle slope road surface

And if the difference value between the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is greater than or equal to a preset change rate difference value, and the gradient is smaller than a preset gradient threshold value, determining that the obstacle type is an uneven downhill obstacle, and determining that the corresponding uneven road scene is an uneven downhill road.

Optionally, the detection result includes a vehicle speed, and determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model includes:

determining a preset safe speed according to the target driving scene and the obstacle distance by using a preset obstacle avoidance model;

and determining a braking control command according to the preset safe speed so as to enable the speed of the vehicle to be reduced below the preset safe speed, wherein the obstacle avoidance control parameters comprise the braking control command.

In a possible design, when the first slant line distance is greater than a first preset threshold and the second slant line distance is less than a second preset threshold, the obstacle is a pit.

In one possible design, the determining the obstacle category according to the obstacle distance further includes:

if the difference value between the fixed angle of the first ground sensor and/or the second ground sensor and the gradient is smaller than a preset angle threshold value, determining that the obstacle type is a second gentle slope in a downhill gentle slope road surface;

correspondingly, the determining the obstacle avoidance control parameter includes: determining that the current running state parameters of the vehicle are unchanged;

if the difference value between the fixed angle of the first ground sensor and/or the second ground sensor and the gradient is larger than or equal to a preset angle threshold value, determining that the obstacle category is a pit in a downhill and gentle slope road surface;

correspondingly, the determining the obstacle avoidance control parameter includes: and determining a braking control command so that the speed of the vehicle is less than or equal to a preset safety threshold value.

In one possible design, the sensor includes: a side sensor, said obstacle distance comprising a lateral distance, said determining an obstacle category from said obstacle distance comprising: if the lateral distance is smaller than a narrow space threshold value, determining that the obstacle category is an obstacle which cannot be crossed, and determining that the corresponding target driving scene is the narrow space scene.

In one possible design, the determining, by using a preset obstacle avoidance model, an obstacle avoidance control parameter according to the obstacle distance and the target driving scene includes:

determining that the carrier can turn around by using the preset obstacle avoidance model according to the side distance, the carrier width and the adjustable head threshold; then the process of the first step is carried out,

and determining automatic turning control parameters by using the preset obstacle avoidance model, wherein the obstacle avoidance control parameters comprise the automatic turning control parameters.

In a possible design, the determining that the vehicle can turn around according to the side distance, the vehicle width, and the adjustable threshold by using the preset obstacle avoidance model includes:

and if the sum of the lateral distance and the width of the carrier is greater than or equal to the adjustable head threshold value, determining that the carrier can turn around.

In one possible design, the sensor further includes a forward-backward sensor, the obstacle distance includes a forward distance and a backward distance, and the determining that the vehicle can turn around further includes:

judging the size relationship between the lateral distance and a direct turning threshold value;

if the lateral distance is greater than or equal to the direct turning threshold, determining a backward distance adjustment value according to the forward distance and the backward distance;

correspondingly, the obstacle avoidance control parameter comprises the backward distance adjustment value.

Optionally, after determining the size relationship between the lateral distance and the direct turning threshold, the method further includes:

if the lateral distance is smaller than the direct turning threshold, adjusting the backward distance of the carrier according to the backward distance adjustment value;

determining a lateral distance adjustment parameter according to the lateral distance by using the obstacle avoidance model;

correspondingly, the carrier is controlled to adjust the lateral distance according to the lateral distance adjusting parameter in a preset adjusting mode, so that the lateral distance is larger than or equal to the direct turning threshold.

In one possible design, the preset adjustment manner includes:

controlling the vehicle to rotate left or right the rotation angle in the lateral distance adjustment parameter;

controlling the vehicle to rotate reversely by the rotation angle;

determining a backward distance adjustment value according to the forward distance and the backward distance;

correspondingly, controlling the backward distance of the carrier to reach a preset backward reserved value according to the backward distance adjusting value.

In one possible design, the sensor includes a distance sensor at least covering four directions of the vehicle, the target driving scene further includes an obstacle avoidance scene, and determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model includes:

if the detection result of the distance sensor is smaller than the downshift distance, determining a speed control gear of the vehicle, wherein the obstacle avoidance control parameter comprises the speed control gear;

if the detection result is smaller than the sensitivity control distance, reducing the speed or direction control instruction input by the user according to a preset proportion to be a corresponding control numerical value;

the downshift distance is greater than or equal to the sensitivity control distance.

In one possible design, the reducing the speed or direction control command input by the user in the preset proportion is a corresponding control value, and includes:

and multiplying the control numerical value of the control rocker by a preset attenuation coefficient.

Optionally, before the detecting the driving environment of the vehicle by using the sensor to determine the detection result, the method further includes:

setting the gear of the carrier to be a preset gear corresponding to a preset mode in response to a preset mode starting instruction input by a user;

correspondingly, the target control parameter is a product of an original control parameter obtained according to a preset control model and a correction coefficient, and the correction coefficient corresponds to the preset model.

In one possible design, the preset mode includes: the correction coefficient corresponding to the novice mode is smaller than 1, and the correction coefficient corresponding to the emergency mode is larger than 1.

In a second aspect, the present application provides a vehicle control apparatus, comprising:

the detection module is used for detecting the running environment of the vehicle by using the sensor so as to determine a detection result;

the processing module is used for determining a target driving scene and corresponding target control parameters according to the detection result;

and the control module is used for controlling the vehicle to safely run in the target running scene according to the target control parameters.

In one possible design, the detection result includes an obstacle distance, and the processing module is configured to determine a target driving scenario and a corresponding target control parameter according to the detection result, and includes:

the processing module is used for determining the obstacle category according to the obstacle distance;

the processing module is further used for determining the target driving scene according to the obstacle category;

the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, where the target control parameter includes the obstacle avoidance control parameter.

In one possible design, the sensor includes: first ground sensor and second ground sensor, first ground sensor and second ground sensor are used for detecting the sensor to the slash distance of road surface, and is corresponding, obstacle distance includes first slash distance and second slash distance, first slash distance is greater than second slash distance, processing module still is used for the basis obstacle distance confirms the obstacle classification, includes:

the processing module is further configured to determine that the obstacle type is obstacle-free and the corresponding target driving scene is a normal driving scene if the fluctuation amplitudes of the first oblique line distance and the second oblique line distance are smaller than a preset fluctuation threshold value.

Optionally, the processing module is further configured to determine an obstacle category according to the obstacle distance, and includes:

Optionally, the sensor includes a gyroscope, the detection result includes a gradient, and the processing module is further configured to determine the obstacle category according to the obstacle distance, including:

the processing module is further configured to determine that the obstacle type is a downhill and gentle slope if a difference between the average change rate of the first diagonal distance and the average change rate of the second diagonal distance is smaller than a preset change rate difference and the slope is smaller than a preset slope threshold, and the corresponding road surface rough scene is a downhill and gentle slope road surface;

Optionally, the detection result includes a vehicle speed, and the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, and the determining includes:

the processing module is further used for determining a preset safe speed according to the target driving scene and the obstacle distance by using a preset obstacle avoidance model;

the processing module is further configured to determine a braking control instruction according to the preset safe speed, so that the vehicle speed is reduced below the preset safe speed, and the obstacle avoidance control parameter includes the braking control instruction.

In one possible design, the processing module is further configured to determine an obstacle category according to the obstacle distance, and further includes:

correspondingly, the processing module is configured to determine an obstacle avoidance control parameter, and includes: determining that the current running state parameters of the vehicle are unchanged;

correspondingly, the processing module is configured to determine an obstacle avoidance control parameter, and includes: and determining a braking control command so that the speed of the vehicle is less than or equal to a preset safety threshold value.

In one possible design, the sensor includes: a side sensor, the obstacle distance comprising a lateral distance, the processing module configured to determine an obstacle category from the obstacle distance, comprising: if the lateral distance is smaller than a narrow space threshold value, determining that the obstacle category is an obstacle which cannot be crossed, and determining that the corresponding target driving scene is the narrow space scene.

In a possible design, the processing module is further configured to determine, by using a preset obstacle avoidance model, an obstacle avoidance control parameter according to the obstacle distance and the target driving scene, and includes:

the processing module is further configured to determine that the carrier can turn around according to the side distance, the carrier width and the adjustable threshold by using the preset obstacle avoidance model; then the process of the first step is carried out,

the processing module is further configured to determine automatic turning control parameters by using the preset obstacle avoidance model, where the obstacle avoidance control parameters include the automatic turning control parameters.

In one possible design, the processing module is further configured to determine, by using the preset obstacle avoidance model, that the vehicle can turn around according to the side distance, the vehicle width, and the adjustable head threshold, and includes:

In one possible design, the sensor further includes a forward-backward sensor, the obstacle distance includes a forward distance and a backward distance, and the processing module is further configured to determine that the vehicle can turn around, and further includes:

the processing module is further used for judging the size relationship between the lateral distance and the direct turning threshold value;

the processing module is further configured to determine a backward distance adjustment value according to the forward distance and the backward distance if the lateral distance is greater than or equal to the direct turning threshold;

Optionally, the processing module is further configured to, after determining a size relationship between the lateral distance and the direct turning threshold, further include:

the processing module is further configured to determine a lateral distance adjustment parameter according to the lateral distance by using the obstacle avoidance model;

In one possible design, the preset adjustment manner includes:

the control module is further used for controlling the rotation angle in the lateral distance adjustment parameter when the vehicle rotates leftwards or rightwards;

the control module is further used for controlling the vehicle to rotate reversely by the rotation angle;

the processing module is further configured to determine a backward distance adjustment value according to the forward distance and the backward distance again;

correspondingly, the control module is further configured to control the carrier according to the backward distance adjustment value, wherein the backward distance of the carrier reaches a preset backward reserved value.

In one possible design, the sensor includes a distance sensor at least covering four directions of the vehicle, the target driving scene further includes an obstacle avoidance scene, and the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, including:

the processing module is further configured to determine a speed control gear of the vehicle if a detection result of the distance sensor is smaller than a downshift distance, where the obstacle avoidance control parameter includes the speed control gear;

the processing module is further used for reducing a corresponding control numerical value of a speed or direction control instruction input by a user according to a preset proportion if the detection result is smaller than the sensitivity control distance;

In one possible design, the processing module is further configured to reduce, by a preset ratio, a control value corresponding to a speed or direction control command input by a user, and includes:

the processing module is further used for responding to a preset mode starting instruction input by a user and setting the gear of the carrier to be a preset gear corresponding to a preset mode;

In a third aspect, the present application provides an electronic device comprising:

a memory for storing program instructions;

and a processor, configured to call and execute the program instructions in the memory, and execute any one of the possible vehicle control methods provided in the first aspect.

In a fourth aspect, the present application provides a storage medium, where a computer program is stored, where the computer program is configured to execute any one of the possible vehicle control methods provided in the first aspect.

The application provides a vehicle control method, a vehicle control device, an electronic device and a storage medium, wherein a sensor is used for detecting the driving environment of a vehicle to determine a detection result, then a target driving scene and a corresponding target control parameter are determined according to the detection result, and finally the vehicle is controlled to safely drive in the target driving scene according to the target control parameter. The technical problems that the existing transportation vehicle for the old or the disabled cannot intelligently identify the driving scene and automatically drive for assistance according to the driving scene are solved, and the technical effects of improving the use experience and the use safety of the transportation vehicle for the old or the disabled such as an electric wheelchair are achieved.

Drawings

In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.

Fig. 1 is a schematic view of a vehicle usage scenario provided in the present application;

fig. 2 is a schematic flowchart of a vehicle control method according to the present application;

fig. 3 is a schematic flowchart of a second vehicle control method according to the present application;

fig. 4A-4B are schematic views illustrating application scenarios of the vehicle control method according to the embodiment of the present disclosure when the vehicle is traveling on a pothole road;

fig. 5 is a schematic flowchart of a third vehicle control method according to the present application;

fig. 6 is a schematic flowchart of a fourth vehicle control method according to the present application;

fig. 7 is a flowchart illustrating a fifth vehicle control method according to the present application;

fig. 8 is a schematic structural diagram of a vehicle control device according to the present application;

fig. 9 is a schematic structural diagram of an electronic device provided in the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, including but not limited to combinations of embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any inventive step are within the scope of the present application.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

With the common occurrence of the aging phenomenon of the population, the proportion of the elderly in the population of the society is gradually increased. Due to the contradiction between the travel demand of the old and the physiological aging, the demand for a transportation vehicle such as an electric wheelchair is generated. Similarly, for some disabled people with physiological disorders, the carrier is an indispensable tool for their independent lives.

However, the existing transportation vehicles such as electric wheelchairs only have simple control over a motor in the electric wheelchairs, and can only depend on the vehicle users to control the transportation vehicles in the relatively complex driving scenes such as pothole roads, long slope roads, narrow spaces (such as elevator rooms and supermarket escalators) and the like, or the nursing staff must perform auxiliary operation, so that the use experience of the vehicle users is seriously influenced.

Therefore, how to make vehicle control intelligent, automatically recognize complex driving scenes, and perform automatic auxiliary control according to the characteristics of each driving scene becomes a technical problem which needs to be solved urgently.

The following describes a vehicle control method provided in the present application with reference to the accompanying drawings to solve the above technical problems.

Fig. 1 is a schematic view of a vehicle usage scenario provided in the present application. As shown in fig. 1, the vehicle is an electric folding wheelchair 100, and a sensor 101 is mounted on the electric folding wheelchair 100, so that a user can drive the electric folding wheelchair 100 to travel in various complex environments, such as a rough road scene and a narrow space scene. And each scene can be subdivided into various sub-scenes such as a ramp scene, a pit scene and the like, and the vehicle control method provided by the application enables the vehicle to automatically identify various target driving scenes and provides intelligent driving assistance for users.

The following describes the vehicle control method provided in the present application in detail.

Fig. 2 is a flowchart illustrating a vehicle control method according to the present application. As shown in fig. 2, a vehicle control method provided in the embodiment of the present application includes the following specific steps:

s201, detecting the running environment of the vehicle by using a sensor to determine a detection result.

In this step, the sensor is mounted in a manner including: the vehicle control system is mounted on a vehicle and/or worn on a user, and uploads detected environmental data, namely a detection result, to the vehicle control system in a wireless transmission mode. The sensor includes: radar, infrared probes, gyroscopes, cameras, laser rangefinders, and the like.

In this embodiment, the carrier includes: electric wheelchairs, electric folding wheelchairs, electric vehicles for riding instead of walk and the like.

S202, determining a target driving scene and corresponding target control parameters according to the detection result.

In this embodiment, the detection result includes an obstacle distance, which is a measurement distance from the sensor to an obstacle, and the obstacle includes: fences, pits, bumps, ramps, stairs, walls, etc.

The method comprises the following specific steps:

determining obstacle types according to the obstacle distances;

determining a target driving scene according to the types of the obstacles;

and determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model.

In this embodiment, the target control parameter includes an obstacle avoidance control parameter.

The target travel scenario includes: normal driving scenes, road surface unevenness scenes and narrow space scenes.

It should be noted that the obstacle distance measured by the sensor may be a vertical distance or an inclined distance, for example, when a pit is measured by an infrared probe or a laser range finder, the obstacle distance is a distance of an inclined line from the sensor to the ground.

And S203, controlling the vehicle to safely run in the target running scene according to the target control parameters.

In this step, the control system controls some series of execution devices on the vehicle according to the generated target control parameters, such as controlling the output power of the motor, the response speed of the joystick, the maximum speed of the vehicle, automatic braking, voice prompt, etc., so that the vehicle can automatically and intelligently assist the user in driving, and avoid some potential safety hazards that are difficult to find by the user, such as stairs, pits, raised deceleration strips, etc.

The embodiment of the application provides a vehicle control method, which comprises the steps of detecting a driving environment of a vehicle by using a sensor to determine a detection result, then determining a target driving scene and a corresponding target control parameter according to the detection result, and finally controlling the vehicle to safely drive in the target driving scene according to the target control parameter. The technical problems that the traveling scene of the mobility aid carrier of the old or the disabled cannot be intelligently identified and the driving is automatically assisted according to the traveling scene are solved, and the technical effects of improving the use experience and the use safety of the mobility aid carrier, such as an electric wheelchair, used by the old or the disabled are achieved.

In order to better understand the application of the vehicle control method in different driving scenarios, the above target driving scenarios are described in more detail with reference to specific embodiments.

Fig. 3 is a flowchart illustrating a second vehicle control method according to the present application. As shown in fig. 3, the method includes the following specific steps:

s301, detecting the running environment of the vehicle by using a sensor to determine a detection result, wherein the detection result comprises an obstacle distance.

In this embodiment, the sensor includes: the sensor comprises a first ground sensor and a second ground sensor, wherein the first ground sensor and the second ground sensor are used for detecting the oblique line distance from the sensor to the road surface.

The detection result comprises an obstacle distance, the obstacle distance comprises a first oblique line distance and a second oblique line distance, and the first oblique line distance is larger than the second oblique line distance.

Fig. 4A-4B are schematic views illustrating application scenarios of the vehicle control method according to the embodiment of the present disclosure when the vehicle is traveling on a pothole road. As shown in fig. 4A, a first sensor 401 and a second sensor 402 are mounted on an armrest of a vehicle 400, and an implementation manner of the first sensor 401 and the second sensor 402 includes: the installation angles of the first sensor 401 and the second sensor 402 are different, so that the included angles between the first oblique line distance H1 and the second oblique line distance H2 measured by the first sensor 401 and the second sensor 402 and the road surface are different, further the lengths of the H1 and the H2 are different, as shown in FIG. 4B, H1 is larger than H2, it can be understood that H1 can also be smaller than or equal to H2 in another possible situation, or the installation angles of the first sensor 401 and the second sensor 402 can be dynamically adjusted, and the measurement angles can be automatically changed according to different driving scenes and according to the judgment requirements.

It should also be noted that the first sensor 401 and the second sensor 402 can also be mounted at the same position on the carrier 400, such as on a handle. The first sensor 401 and the second sensor 402 may also be a sensor array formed by a plurality of sensors, and a person skilled in the art may select the installation position of the sensors and the number of the sensors according to practical situations, which is not limited in the present application.

S302, determining the obstacle type according to the obstacle distance, and determining a target driving scene according to the obstacle type.

In a possible implementation manner, if the fluctuation amplitudes of the first oblique line distance and the second oblique line distance are smaller than a preset fluctuation threshold, it is determined that the obstacle type is obstacle-free, and the corresponding target driving scene is a normal driving scene.

As shown in fig. 4A, as the vehicle 400 moves, the first oblique distance H1 and the second oblique distance H2 both fluctuate due to the road surface bump, and when the fluctuation is small, the road surface is considered to be in a flat range under normal driving bump, and a preset fluctuation threshold is set as a determination condition for whether the road surface is flat. The skilled person can select the specific value of the preset fluctuation threshold according to practical situations, and the method is not limited herein.

In another possible implementation manner, if the first fluctuation amplitude of the first oblique line distance is greater than or equal to a preset fluctuation threshold value, and the second fluctuation amplitude of the second oblique line distance is smaller than the preset fluctuation threshold value, the obstacle category is determined to be a pit or a bulge, and the corresponding road surface rough scene is a pit or a bulge.

As shown in fig. 4B, the range detected by the first sensor 401 is farther than the range detected by the second sensor 402, and the area range is limited for the pits or bumps. Therefore, the first sensor 401 will first detect that the first slope distance H1 changes, i.e. the first fluctuation range exceeds the preset fluctuation threshold, but the second sensor 402 still detects a flat road surface, i.e. the second fluctuation range of the second slope distance H2 is smaller than the preset fluctuation threshold, so that the false determination of the pit or the slope can be effectively prevented. In the prior art, generally, only one sensor is arranged to detect the fluctuation amount of the diagonal distance in front, or the sensors with the same installation inclination angles are arranged on the left and right to detect the fluctuation amount of the diagonal distance to judge whether a pit exists in front, but the arrangement can easily cause that the pit is mistaken for a ramp, or the ramp is mistaken for a pit or a bump, so that wrong judgment is brought to a user when whether the lower part is a step is identified, a falling accident is caused, and the use experience of the user is influenced.

Further, when the first diagonal distance is greater than a first preset threshold value and the second diagonal distance is less than a second preset threshold value, the obstacle is a pit.

In another possible implementation manner, if a difference value between the average change rate of the first diagonal distance and the average change rate of the second diagonal distance is smaller than a preset change rate difference value, it is determined that the obstacle category is a gentle slope, and the corresponding road surface rough scene is a gentle slope road surface. And if the difference value of the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is larger than or equal to the preset change rate difference value, determining the obstacle type to be an uneven ramp obstacle, such as a pit or a bulge or a step in a ramp.

When the vehicle enters the road surface of the ramp, the ramp still has fluctuation, namely the gradient value changes with different positions, such as pits or bosses, and steps can exist. It is now necessary to identify whether the ramp is a gentle slope or whether the ramp is uneven, such as a depression or a protrusion or a step in the slope. Since the first slant line distance is greater than the second slant line distance in this embodiment, if a rough ramp obstacle is encountered, the average change rate of the first slant line distance in a preset time period will change, which causes the difference between the average change rate of the first slant line distance and the average change rate of the second slant line distance to increase, and if the difference is greater than or equal to the preset change rate difference, the control system determines that the rough ramp obstacle is encountered.

It should be noted that the slope may be an ascending slope or a descending slope.

Further, the slope in the gyroscope can be introduced to assist in judging uphill and downhill. Namely, the sensor includes a gyroscope, the detection result includes a gradient, and the determining the obstacle category according to the obstacle distance includes:

if the difference value between the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is smaller than a preset change rate difference value, and the gradient is smaller than a preset gradient threshold value, determining that the obstacle type is a downhill gentle slope, and determining that the corresponding road surface rough scene is a downhill gentle slope road surface;

Similarly, a similar determination may be made with a gyroscope for an uphill slope.

Still further, for uneven conditions on the ramp, further identification can be made. If the difference value between the fixed angle of the first ground sensor and/or the second ground sensor and the gradient is smaller than a preset angle threshold value, determining that the obstacle type is a second gentle slope in a downhill gentle slope road surface;

And S303, determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model.

In this step, specifically, the method includes:

determining a preset safe speed according to a target driving scene and an obstacle distance by using a preset obstacle avoidance model;

and determining a braking control command according to a preset safe speed so as to enable the speed of the vehicle to be reduced below the preset safe speed, wherein the obstacle avoidance control parameters comprise the braking control command.

For example, in this embodiment, the target driving scene is an uneven road scene, if the uneven road scene is a gentle slope scene, the preset safe speed may be set to the minimum operating speed, and if the uneven road scene is an uneven ramp scene, or a pit, a bump, or a step scene, the preset safe speed may be set to zero, that is, the vehicle is controlled to automatically stop so as to avoid a drop accident.

And S304, controlling the vehicle to safely run in the target running scene according to the target control parameters.

The principle of this step is similar to that of S203, and for specific explanation and principle introduction, reference may be made to S203 and will not be repeated herein.

The embodiment of the application provides a vehicle control method, which is used for automatically identifying concrete conditions such as concave pits, convex bumps, steps and uneven ramps when a vehicle runs on an uneven road surface scene, and further controlling the vehicle to take corresponding safe running control measures. The technical problems that the traveling scene of the mobility aid carrier of the old or the disabled cannot be intelligently identified and the driving is automatically assisted according to the traveling scene are solved, and the technical effects of improving the use experience and the use safety of the mobility aid carrier, such as an electric wheelchair, used by the old or the disabled are achieved.

The following describes an example of intelligent control of a vehicle operating in a narrow space with reference to fig. 5.

Fig. 5 is a flowchart illustrating a third vehicle control method according to an embodiment of the present disclosure. As shown in fig. 5, the method includes the following specific steps:

s501, detecting the running environment of the vehicle by using a sensor to determine a detection result, wherein the detection result comprises an obstacle distance.

In this embodiment, the sensor includes: a side sensor, the obstacle distance comprising a lateral distance. The lateral distance includes: left side distance and right side distance. I.e. the distance separating the obstacle from the left and right sides of the vehicle.

In one possible design, side sensors are provided at the front left, rear left, front right and rear right of the vehicle, which may be radars, infrared detectors, laser rangefinders, etc. Of course, the number and specific type of the side sensors can be selected by those skilled in the art according to actual situations, and the application is not limited herein.

And S502, determining the obstacle type according to the obstacle distance.

In this embodiment, the method specifically includes:

and if the lateral distance is smaller than the narrow space threshold value, determining the obstacle type as the non-stridable obstacle.

And S503, determining a target driving scene according to the obstacle type.

In this embodiment, if the obstacle type is the non-stridable obstacle, the target driving scene is the narrow space scene.

S504, determining that the carrier can turn around according to the side distance, the carrier width and the adjustable head threshold value by using a preset obstacle avoidance model.

In this embodiment, a narrow space scene is taken as an example to illustrate that the vehicle turns around in the elevator car, and the method specifically includes:

It should be noted that, in the above-mentioned turning-around determining method, at least one method for determining that the vehicle can turn around in the present application may be further configured to establish a two-dimensional or three-dimensional turning model according to a geometric relationship between the lateral distance and the vehicle, so as to analyze a spatial condition of turning around in the turning model, thereby obtaining a turning-around threshold. The method and conditions for determining the possibility of turning around can be selected by those skilled in the art according to practical situations, and the application is not limited.

In one possible design, the sensors on the vehicle further include a forward-backward sensor, the obstacle distance includes a forward distance and a backward distance, and after determining that the vehicle can turn around, the method further includes:

judging the size relationship between the lateral distance and the threshold value capable of directly turning around;

if the lateral distance is greater than or equal to the threshold value of direct turning, determining a backward distance adjustment value according to the forward distance and the backward distance; correspondingly, the obstacle avoidance control parameter comprises a backward distance adjustment value.

The purpose of this step is to adjust the distance of the rear of the vehicle from an obstacle, such as an elevator wall, to a safe distance, such as 0.5m, after it is determined that the vehicle can turn around directly.

If the lateral distance is smaller than the direct turning threshold, adjusting the backward distance of the carrier according to a backward distance adjustment value; determining a lateral distance adjustment parameter according to the lateral distance by using an obstacle avoidance model; correspondingly, controlling the backward distance of the carrier to reach a preset backward reserved value according to the backward distance adjusting value.

The purpose of this step is when confirming that the vehicle can not turn around directly, cause the reason that can not turn around at this moment probably the left and right distance distributes unevenly, one side is narrower, therefore can give the position adjustment instruction to the vehicle, so that the vehicle can change the distribution with the wall of elevator room namely left and right distance of the barrier.

Specifically, for an implementation manner of the preset adjustment manner, the specific steps include:

controlling the vehicle to rotate reversely by the rotation angle;

Specifically, the vehicle is controlled to rotate leftwards or rightwards and then rotate in the direction of gyration, and the rotation is repeated in a cycle, so that the vehicle is adjusted to move leftwards and rightwards horizontally, and the rotation angle can be 30-45 degrees each time. The fine adjustment of the horizontal left-right distance can be realized by the rotary moving mode.

The front-rear direction sensor is a sensor that can detect the front and rear of the vehicle, and includes: sonar radar, infrared detectors, laser rangefinders, and the like. The number of sensors for detecting the front and the rear can be selected by the skilled person according to the actual situation. In a possible design, a rotatable sensor can be further mounted on the carrier, so that whether obstacles exist in the environment in front of and behind the carrier and in the surrounding environment or not can be periodically detected.

For "determining the size relationship between the lateral distance and the directly adjustable threshold", when the lateral distance includes the left distance and the right distance, a possible implementation manner is to select the minimum value of the left distance and the right distance to compare the size of the left distance and the right distance with the directly adjustable threshold.

And S505, determining automatic turn-around control parameters by using a preset obstacle avoidance model.

In this embodiment, the obstacle avoidance control parameter includes an automatic turning control parameter, and the target control parameter is an obstacle avoidance control parameter.

It should be noted that, in the construction of the preset obstacle avoidance model, a person skilled in the art can obtain the preset obstacle avoidance model through modes such as experimental modeling according to the specific overall dimension of the carrier according to the actual situation, and the specific implementation mode of the preset ratio model is not limited in the present application.

And S506, controlling the vehicle to safely run in a target running scene according to the target control parameters, wherein the target control parameters comprise automatic turn-around control parameters.

In this step, after the control system calculates the operation control mode of automatic turnaround, the control command can be sent to the controller of the execution mechanism, so that the vehicle can realize automatic turnaround in narrow environments such as elevator rooms.

It can be understood that if the analysis result obtained through the analysis operation of the control system is that automatic turning cannot be realized, or the vehicle still cannot meet the requirement of automatic turning after the adjustment of the left-right and/or front-back distance of the vehicle is performed, a prompt message is sent to the user, wherein the prompt message comprises a voice prompt.

The embodiment of the application provides a vehicle control method, which is used for controlling the automatic turning of a vehicle in a narrow space such as an elevator car. The technical problems that the mobility vehicles of the old or the disabled cannot identify narrow space scenes and turn around automatically are solved, and the technical effects of improving the use experience and the use safety of the mobility vehicles such as the electric wheelchair for the old or the disabled are achieved.

Fig. 6 is a flowchart illustrating a fourth vehicle control method according to the present application. As shown in fig. 6, the method includes the following specific steps:

s601, detecting the running environment of the vehicle by using a sensor to determine a detection result, wherein the detection result comprises an obstacle distance.

In this embodiment, the sensor includes a distance sensor that covers at least four directions of the front, rear, left, and right of the vehicle. The distance sensor may be a radar, an infrared detector, a laser rangefinder, or the like.

S602, determining the obstacle type according to the obstacle distance, and determining a target driving scene according to the obstacle type.

In the present embodiment, the target driving scene includes an obstacle avoidance scene.

For example, when the vehicle runs between escalators of supermarkets or supermarkets, due to the fact that the walkways are narrow and small, obstacles such as pedestrians or goods may exist, at the same time, whether the obstacles exist around the vehicle or not can be judged through the distance sensor, and therefore obstacle avoidance scenes can be identified.

And S603, if the detection result of the distance sensor is smaller than the downshift distance, determining the speed control gear of the vehicle.

In this embodiment, the obstacle avoidance control parameter includes a speed control gear.

Specifically, when an obstacle is detected in front of the vehicle, the control system can control the vehicle to shift down and reduce the speed.

And S604, if the detection result is smaller than the sensitivity control distance, reducing the control value corresponding to the speed or direction control instruction input by the user according to a preset proportion.

In this embodiment, the method specifically includes:

In the embodiment, the carrier is provided with the control rocker, a user controls the traveling direction and the traveling speed of the carrier by using the control rocker, and when obstacles exist around the carrier, the control sensitivity of the control rocker can be reduced, that is, the control value of the control rocker is multiplied by the preset attenuation coefficient. Therefore, the driving safety of the carrier can be improved, and the collision accident caused by misoperation of a user is avoided.

Note that the downshift distance in S603 to S604 is greater than or equal to the sensitivity control distance.

S605, controlling the vehicle to safely run in a target running scene according to target control parameters, wherein the target control parameters comprise: speed control gear and control parameters adjusted according to the target driving scene.

In the step, the vehicle can be ensured to safely run in the obstacle avoidance scene by controlling the form speed of the vehicle and carrying out sensitivity adjustment on input commands of a user, such as input of a control rocker.

The embodiment of the application provides a vehicle control method, which comprises the steps of detecting a driving environment of a vehicle by using a sensor to determine a detection result, then determining an obstacle type according to an obstacle distance, determining a target driving scene according to the obstacle type, then determining a speed control gear of the vehicle if the detection result of a distance sensor is smaller than a downshift distance, reducing a control value corresponding to a speed or direction control instruction input by a user according to a preset proportion if the detection result is smaller than a sensitivity control distance, and finally controlling the vehicle to safely drive in the target driving scene according to a target control parameter. The technical problem of old person or disabled personage's the carrier of riding instead of walk keeps away the barrier in narrow and small space scene is solved, reached and improved old person or disabled personage and used the carrier of riding instead of walk and experienced and the technical effect of safety in utilization like electric wheelchair.

Fig. 7 is a flowchart illustrating a fifth vehicle control method according to the present application. As shown in fig. 7, the method includes the following specific steps:

and S701, responding to a preset mode starting instruction input by a user, and setting the gear of the carrier to be a preset gear corresponding to the preset mode.

In this embodiment, the preset mode includes: a novice mode and an emergency mode.

In the novice mode, the operating speed of the vehicle is limited to the lowest speed so that the user can safely make a driving attempt when using the vehicle for the first time.

In the emergency mode, if the user needs to deal with the emergency, the vehicle can be set to cruise at the highest speed.

S702, detecting the running environment of the vehicle by using a sensor to determine a detection result.

And S703, determining a target driving scene and a corresponding target control parameter according to the detection result, wherein the target control parameter is the product of the original control parameter and the correction coefficient obtained according to a preset control model.

In this step, the correction coefficient corresponds to a preset pattern. Specifically, when the preset mode includes: and when the novice mode and the emergency mode are in the emergency mode, the correction coefficient corresponding to the novice mode is smaller than 1, and the correction coefficient corresponding to the emergency mode is larger than 1.

And S704, controlling the vehicle to safely run in the target running scene according to the target control parameters.

The specific implementation principle and the noun explanation of steps S702 to S703 may refer to steps S201 to S203 of the vehicle control method shown in fig. 2, which are not described herein again.

According to the carrier control method provided by the embodiment of the application, different scene processing results with different control response speeds are set for different preset modes, so that a user can use the carrier more flexibly and more variously, and the use convenience and diversity of the user are improved as much as possible on the premise of ensuring the safety of the user.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments can be implemented by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps including the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Fig. 8 is a schematic structural diagram of a positioning device provided in the present application. The positioning means may be implemented by software, hardware or a combination of both.

As shown in fig. 8, the vehicle control apparatus 800 includes:

a detection module 801, configured to detect a driving environment of a vehicle by using a sensor to determine a detection result;

a processing module 802, configured to determine a target driving scene and corresponding target control parameters according to the detection result;

and a control module 803, configured to control the vehicle to safely travel in the target travel scene according to the target control parameter.

In one possible design, the detection result includes an obstacle distance, and the processing module 802 is configured to determine a target driving scenario and corresponding target control parameters according to the detection result, including:

the processing module 802 is configured to determine an obstacle category according to the obstacle distance;

the processing module 802 is further configured to determine the target driving scene according to the obstacle category;

the processing module 802 is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, where the target control parameter includes the obstacle avoidance control parameter.

In one possible design, the sensor includes: first ground sensor and second ground sensor, first ground sensor and second ground sensor are used for detecting the sensor to the slash distance of road surface, and are corresponding, obstacle distance includes first slash distance and second slash distance, first slash distance is greater than second slash distance, processing module 802, still be used for the basis obstacle distance confirms the obstacle classification, include:

the processing module 802 is further configured to determine that the obstacle type is an obstacle-free type and the corresponding target driving scene is a normal driving scene if the fluctuation amplitudes of the first oblique line distance and the second oblique line distance are smaller than a preset fluctuation threshold.

Optionally, the processing module 802 is further configured to determine an obstacle category according to the obstacle distance, where the determining includes:

Optionally, the sensor includes a gyroscope, the detection result includes a gradient, and the processing module 802 is further configured to determine a category of the obstacle according to the obstacle distance, including:

the processing module 802 is further configured to determine that the obstacle type is a downhill and gentle slope if a difference between the average change rate of the first diagonal distance and the average change rate of the second diagonal distance is smaller than a preset change rate difference and the slope is smaller than a preset slope threshold, where the corresponding road surface rough scene is a downhill and gentle slope road surface;

Optionally, the detection result includes a vehicle speed, and the processing module 802 is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, where the determining includes:

the processing module 802 is further configured to determine a preset safe speed according to the target driving scene and the obstacle distance by using a preset obstacle avoidance model;

the processing module 802 is further configured to determine a braking control instruction according to the preset safe speed, so that the vehicle speed is reduced below the preset safe speed, where the obstacle avoidance control parameter includes the braking control instruction.

In one possible design, the processing module 802 is further configured to determine an obstacle category according to the obstacle distance, and further includes:

correspondingly, the processing module 802 is configured to determine an obstacle avoidance control parameter, and includes: determining that the current running state parameters of the vehicle are unchanged;

correspondingly, the processing module 802 is configured to determine an obstacle avoidance control parameter, and includes: and determining a braking control command so that the speed of the vehicle is less than or equal to a preset safety threshold value.

In one possible design, the sensor includes: a side sensor, the obstacle distance including a lateral distance, the processing module 802 configured to determine an obstacle category according to the obstacle distance, including: if the lateral distance is smaller than a narrow space threshold value, determining that the obstacle category is an obstacle which cannot be crossed, and determining that the corresponding target driving scene is the narrow space scene.

In a possible design, the processing module 802 is further configured to determine, by using a preset obstacle avoidance model, an obstacle avoidance control parameter according to the obstacle distance and the target driving scenario, where the determining includes:

the processing module 802 is further configured to determine, by using the preset obstacle avoidance model, that the carrier can turn around according to the side distance, the carrier width, and the adjustable threshold; then the process of the first step is carried out,

the processing module 802 is further configured to determine an automatic turning control parameter by using the preset obstacle avoidance model, where the obstacle avoidance control parameter includes the automatic turning control parameter.

In one possible design, the processing module 802 is further configured to determine that the vehicle can turn around according to the side distance, the vehicle width, and the adjustable head threshold by using the preset obstacle avoidance model, where the determining includes:

In one possible design, the sensors further include a forward-backward sensor, the obstacle distance includes a forward distance and a backward distance, and the processing module 802 is further configured to determine that the vehicle can turn around, and further include:

the processing module 802 is further configured to determine a size relationship between the lateral distance and a threshold value that can be directly turned around;

the processing module 802 is further configured to determine a backward distance adjustment value according to the forward distance and the backward distance if the lateral distance is greater than or equal to the direct turning threshold;

Optionally, the processing module 802 is further configured to, after determining a size relationship between the lateral distance and the direct turning threshold, further include:

the processing module 802 is further configured to determine a lateral distance adjustment parameter according to the lateral distance by using the obstacle avoidance model;

In one possible design, the preset adjustment manner includes:

the control module 803 is further configured to control the rotation angle in the lateral distance adjustment parameter for the left or right rotation of the vehicle;

the control module 803 is further configured to control the vehicle to rotate reversely by the rotation angle;

the processing module 802 is further configured to determine a backward distance adjustment value according to the forward distance and the backward distance again;

correspondingly, the control module 803 is further configured to control the backward distance of the carrier to reach a preset backward reserved value according to the backward distance adjustment value.

In a possible design, the sensors include distance sensors at least covering four directions of the vehicle, the target driving scene further includes an obstacle avoidance scene, and the processing module 802 is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, including:

the processing module 802 is further configured to determine a speed control gear of the vehicle if a detection result of the distance sensor is smaller than a downshift distance, where the obstacle avoidance control parameter includes the speed control gear;

the processing module 802 is further configured to reduce, according to a preset ratio, that the speed or direction control instruction input by the user is a corresponding control value if the detection result is smaller than the sensitivity control distance;

In one possible design, the processing module 802 is further configured to reduce, by a preset ratio, a speed or direction control command input by a user to a corresponding control value, where the speed or direction control command is a corresponding control value, and the method includes:

the processing module 802 is further configured to set a gear of the vehicle to a preset gear corresponding to a preset mode in response to a preset mode start instruction input by a user;

It should be noted that the vehicle control device provided in the embodiment shown in fig. 8 can execute the method provided in any of the above method embodiments, and the specific implementation principle, technical features, technical term explanations, and technical effects thereof are similar and will not be described herein again.

Fig. 9 is a schematic structural diagram of an electronic device provided in the present application. As shown in fig. 9, the electronic device 900 may include: at least one processor 901 and memory 902. Fig. 9 shows an electronic device as an example of a processor.

And a memory 902 for storing programs. In particular, the program may include program code including computer operating instructions.

Memory 902 may comprise high-speed RAM memory and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The processor 901 is configured to execute computer-executable instructions stored in the memory 902 to implement the methods described in the above method embodiments.

The processor 901 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

Alternatively, the memory 902 may be separate or integrated with the processor 901. When the memory 902 is a device independent from the processor 901, the electronic device 700 may further include:

a bus 903 for connecting the processor 901 and the memory 902. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. Buses may be classified as address buses, data buses, control buses, etc., but do not represent only one bus or type of bus.

Alternatively, in a specific implementation, if the memory 902 and the processor 901 are integrated into a chip, the memory 902 and the processor 901 may complete communication through an internal interface.

The present application also provides a computer-readable storage medium, which may include: various media that can store program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, specifically, the computer-readable storage medium stores program instructions for the vehicle control method in the above embodiments.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle control method, comprising:

2. The vehicle control method according to claim 1, wherein the detection result includes an obstacle distance, and the determining a target driving scenario and corresponding target control parameters according to the detection result includes:

determining obstacle types according to the obstacle distances;

determining the target driving scene according to the obstacle category;

3. The vehicle control method according to claim 2, wherein the target travel scenario includes: normal driving scenes, road surface unevenness scenes and narrow space scenes.

4. The vehicle control method according to claim 3, wherein the sensor includes: first ground sensor and second ground sensor, first ground sensor and second ground sensor are used for detecting the oblique line distance of sensor to road surface, and is corresponding, obstacle distance includes first oblique line distance and second oblique line distance, first oblique line distance is greater than second oblique line distance, according to obstacle distance confirms the obstacle classification, include:

5. The vehicle control method according to claim 4, wherein the determining an obstacle category according to the obstacle distance includes:

6. The vehicle control method according to claim 5, wherein the determining an obstacle category according to the obstacle distance includes:

7. The vehicle control method according to claim 5, wherein the sensor includes a gyroscope, the detection result includes a gradient, and the determining the obstacle category according to the obstacle distance includes:

8. The vehicle control method according to any one of claims 5 to 7, wherein the detection result includes a vehicle speed, and determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model includes:

9. The vehicle control method according to claim 5, wherein the obstacle is a pit when the first slant line distance is greater than a first predetermined threshold and the second slant line distance is less than a second predetermined threshold.

10. The vehicle control method according to claim 7, wherein the determining an obstacle category according to the obstacle distance further comprises:

11. The vehicle control method according to claim 3, wherein the sensor includes: a side sensor, said obstacle distance comprising a lateral distance, said determining an obstacle category from said obstacle distance comprising: if the lateral distance is smaller than a narrow space threshold value, determining that the obstacle category is an obstacle which cannot be crossed, and determining that the corresponding target driving scene is the narrow space scene.

12. The vehicle control method according to claim 11, wherein the determining, by using a preset obstacle avoidance model, an obstacle avoidance control parameter according to the obstacle distance and the target driving scene includes:

13. The vehicle control method according to claim 12, wherein the determining that the vehicle can turn around according to the side distance, the vehicle width, and an adjustable head threshold by using the preset obstacle avoidance model comprises:

14. The vehicle control method according to claim 13, wherein the sensors further include a forward-backward sensor, the obstacle distance includes a forward distance and a backward distance, and the determining that the vehicle can turn around further includes:

15. The vehicle control method according to claim 14, wherein after determining the magnitude relationship between the lateral distance and the direct turnaround threshold, the method further comprises:

16. The vehicle control method according to claim 15, wherein the preset adjustment manner comprises:

controlling the vehicle to rotate reversely by the rotation angle;

17. The vehicle control method according to claim 3, wherein the sensors include distance sensors covering at least four directions of the vehicle, front, rear, left, and right, the target driving scene further includes an obstacle avoidance scene, and determining obstacle avoidance control parameters according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model includes:

18. The vehicle control method according to claim 17, wherein the reducing the control value corresponding to the speed or direction control command input by the user according to the predetermined ratio comprises:

19. The vehicle control method according to claim 1, further comprising, before the detecting a driving environment of the vehicle with the sensor to determine a detection result:

20. The vehicle control method according to claim 19, wherein the preset mode comprises: the correction coefficient corresponding to the novice mode is smaller than 1, and the correction coefficient corresponding to the emergency mode is larger than 1.

21. A vehicle control device, comprising:

22. An electronic device, comprising:

a processor; and the number of the first and second groups,

a memory for storing executable instructions of the processor;

wherein the processor is configured to execute a vehicle control method of any one of claims 1 to 20 via execution of the executable instructions.

23. A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the vehicle control method according to any one of claims 1 to 20.