CN114545950A - Control method of unmanned intelligent vehicle - Google Patents
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
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Abstract
The invention provides a control method of an unmanned intelligent vehicle, which comprises the steps of setting a corresponding information acquisition area according to the running speed of the intelligent vehicle; acquiring an image to be processed in the information acquisition area; determining whether an obstacle exists in the image to be processed; when an obstacle exists in the image to be processed, acquiring the position and the type of the obstacle; determining the moving speed of the obstacle according to the relative position change between the obstacle and the intelligent vehicle; and controlling the running state of the intelligent vehicle according to the type of the obstacle and the moving speed of the obstacle. Therefore, the obstacle is identified from the image to be processed through the acquired image to be processed, the intelligent vehicle is controlled to turn, decelerate or emergently brake and other operations based on the type of the obstacle and the moving speed of the obstacle, and the automatic path planning of the intelligent vehicle in an unknown environment is realized, so that the intelligent vehicle is prevented from colliding with the obstacle, and the intelligent vehicle is ensured to safely travel to a destination.
Description
Technical Field
The invention relates to the technical field of automatic unmanned driving, in particular to a control method of an unmanned intelligent vehicle.
Background
The unmanned automobile is an intelligent automobile which senses the surrounding environment of the automobile through a vehicle-mounted sensing system, automatically plans a driving route, controls the steering and the speed of the automobile and controls the automobile to reach a preset destination according to road, automobile position and obstacle information obtained through sensing.
In the prior art, when the unmanned vehicle travels, the unmanned vehicle can avoid when encountering an obstacle, however, the emergency capacity of the unmanned vehicle is poor, the unmanned vehicle cannot be controlled according to actual road conditions, traffic accidents are easy to happen, and the safety is poor.
Disclosure of Invention
In view of this, the invention provides a method for controlling an unmanned intelligent vehicle.
In order to solve the technical problems, the invention adopts the technical scheme that:
a control method of an unmanned intelligent vehicle comprises the following steps:
s101, setting a corresponding information acquisition area according to the running speed of the intelligent trolley;
s102, acquiring an image to be processed in the information acquisition area;
s103, determining whether an obstacle exists in the image to be processed;
s104, when an obstacle exists in the image to be processed, acquiring the position and the type of the obstacle;
s105, determining the moving speed of the obstacle according to the relative position change between the obstacle and the intelligent vehicle;
and S106, controlling the running state of the intelligent vehicle according to the type of the obstacle and the moving speed of the obstacle.
Optionally, in the present invention, before the step S103, an initial image set without obstacles is further obtained, where the initial image set includes a plurality of initial images.
Optionally, in the present invention, the S103 specifically includes:
calculating the similarity of each initial image and the image to be processed;
determining the initial image with the highest similarity with the image to be processed;
judging whether the similarity between the initial image and the image to be processed is greater than a first threshold value;
if so, judging that no barrier exists in the image to be processed;
and if not, an obstacle exists in the image to be processed.
Optionally, in the present invention, the S102 further includes performing filtering processing on the image to be processed.
Alternatively, in the present invention, the obstacle types include a pedestrian, a vehicle, and a stationary obstacle.
Optionally, in the present invention, the S104 specifically includes:
when an obstacle exists in the image to be processed and the type of the obstacle is a pedestrian, determining a search area by taking the pedestrian as a center;
judging whether a moving object and a traction rope for connecting the moving object and the pedestrian exist in the search area;
if yes, judging that the barrier type is upgraded from a pedestrian to a pedestrian traction pet model;
if not, the obstacle type is judged to be a pedestrian.
Optionally, in the present invention, the search area is: and taking the pedestrian as a circle center and the first parameter as a radius area.
Optionally, in the present invention, the S106 specifically includes:
when the type of the obstacle is a pedestrian and the moving speed of the pedestrian is greater than a first preset speed value, controlling the intelligent car to brake emergently;
and when the barrier type is that the pedestrian pulls the pet model and the moving speed of the pedestrian or the pet is greater than a first preset speed value, controlling the intelligent car to brake emergently.
Optionally, in the present invention, the S106 further includes:
when the type of the obstacle is a static obstacle and the static obstacle is positioned in the center of a road, calculating a first distance between the static obstacle and one side of the road, and if the first distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn left or right to avoid the static obstacle; if the first distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again;
when the type of the obstacle is a static obstacle and the static obstacle is positioned on the left side of the road, calculating a second distance between the static obstacle and the right side of the road, and if the second distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn right to avoid the static obstacle; if the second distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again;
when the type of the obstacle is a static obstacle and the static obstacle is positioned on the right side of the road, calculating a third distance between the static obstacle and the left side of the road, and if the third distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn left to avoid the static obstacle; and if the third distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again.
Optionally, in the present invention, the S106 further includes:
and when the type of the obstacle is a vehicle and the moving speed of the vehicle is greater than a second preset speed value, controlling the intelligent trolley to run at a reduced speed.
The invention has the advantages and positive effects that:
therefore, in the invention, the obstacle is identified from the image to be processed through the acquired image to be processed, and the operations such as steering, deceleration or emergency braking of the intelligent vehicle are controlled based on the type of the obstacle and the moving speed of the obstacle, so that the automatic path planning of the intelligent vehicle in an unknown environment is realized, the intelligent vehicle is prevented from colliding with the obstacle, and the intelligent vehicle is ensured to safely travel to the destination.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a control method of an unmanned intelligent vehicle according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When a component is referred to as being "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When a component is referred to as being "disposed on" another component, it can be directly on the other component or intervening components may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
A method for controlling an unmanned intelligent vehicle, as shown in fig. 1, includes:
s101, setting a corresponding information acquisition area according to the running speed of the intelligent trolley;
s102, acquiring an image to be processed in the information acquisition area;
s103, determining whether an obstacle exists in the image to be processed;
s104, when an obstacle exists in the image to be processed, acquiring the position and the type of the obstacle;
s105, determining the moving speed of the obstacle according to the relative position change between the obstacle and the intelligent vehicle;
and S106, controlling the running state of the intelligent vehicle according to the type of the obstacle and the moving speed of the obstacle.
Therefore, in the invention, the obstacle is identified from the image to be processed through the acquired image to be processed, and the operations such as steering, deceleration or emergency braking of the intelligent vehicle are controlled based on the type of the obstacle and the moving speed of the obstacle, so that the automatic path planning of the intelligent vehicle in an unknown environment is realized, the intelligent vehicle is prevented from colliding with the obstacle, and the intelligent vehicle is ensured to safely run to a destination.
In S101, the intelligent vehicle has different driving speeds and different corresponding information acquisition areas. For example, when the driving speed of the intelligent vehicle is 100 steps, the corresponding information acquisition area may be, but is not limited to, an information acquisition area fifty meters ahead of the intelligent vehicle; when the driving speed of the intelligent vehicle is 80 steps, the corresponding information acquisition area can be but is not limited to an information acquisition area which is forty meters ahead of the intelligent vehicle.
Optionally, in the present invention, before the step S103, an initial image set without obstacles is further obtained, where the initial image set includes a plurality of initial images.
It should be noted that, the initial image is also subjected to filtering processing, so that various interference noises in the initial image can be effectively removed, and a clear initial image with good effect is obtained.
Optionally, in the present invention, the S103 specifically includes:
calculating the similarity of each initial image and the image to be processed;
determining the initial image with the highest similarity to the image to be processed;
judging whether the similarity between the initial image and the image to be processed is greater than a first threshold value;
if so, judging that no barrier exists in the image to be processed;
and if not, an obstacle exists in the image to be processed.
To illustrate, the initial image set includes image packets of each road segment, and each image packet includes initial images at a plurality of positions.
Wherein each image packet corresponds to a latitude and longitude range.
In the process of advancing of the intelligent trolley, the actual position of the intelligent trolley is required to be obtained in real time while the image to be processed is obtained, and the fact that the actual position of the intelligent trolley falls in which longitude and latitude range is judged, so that the image packet corresponding to the longitude and latitude range is called, and whether the obstacle exists in the image to be processed or not is favorably determined subsequently by calculating the similarity of the image to be processed and a plurality of initial images in the image packet.
How to determine whether an obstacle exists in the image to be processed will be specifically described below.
For example: the description will be given by taking an example in which the image packet includes five initial images at different positions, the five initial images being a first initial image, a second initial image, a third initial image, a fourth initial image and a fifth initial image, respectively.
Specifically, the similarity H1 of the first initial image and the image to be processed is calculated;
calculating the similarity H2 of the second initial image and the image to be processed;
calculating the similarity H3 of the third initial image and the image to be processed;
calculating the similarity H4 of the fourth initial image and the image to be processed;
calculating the similarity H5 of the fifth initial image and the image to be processed;
if H5> H4> H3> H2> H1, determining that the similarity between the fifth initial image and the image to be processed is the highest;
when the similarity between the fifth initial image and the image to be processed is greater than a first threshold value, indicating that no obstacle exists in the image to be processed;
when the similarity between the fifth initial image and the image to be processed is smaller than a first threshold value, indicating that an obstacle exists in the image to be processed;
therefore, after the obstacle is determined to exist in the image to be processed, the type of the obstacle is determined according to the pixel area of the image to be processed, which is different from the fifth initial image, specifically, the pixel area is the outline information of the obstacle, and the type of the obstacle can be determined according to the outline information of the obstacle;
and determining the position of the obstacle according to the central point of the pixel area of the image to be processed, which is different from the fifth initial image, specifically, determining the position coordinate of the central point in the image to be processed, where the coordinate position is the position of the obstacle.
After the type and the position of the obstacle are determined, the driving state of the intelligent vehicle is controlled subsequently.
Therefore, in the invention, when the intelligent trolley continuously travels, the initial image corresponding to the current position of the intelligent trolley is called according to the actual position of the intelligent trolley, and whether the obstacle is contained in the image to be processed is determined by calculating the similarity between the initial image and the image to be processed, so that the speed of identifying the obstacle is increased, and the calculated amount is reduced.
Optionally, in the present invention, the S102 further includes performing filtering processing on the image to be processed.
Therefore, when the similarity of the image to be processed and the initial image is calculated, the accuracy of the data is improved, and whether the obstacle exists in the image to be processed or not is determined in a follow-up mode.
Alternatively, in the present invention, the obstacle types include a pedestrian, a vehicle, and a stationary obstacle.
Optionally, in the present invention, the S104 specifically includes:
when an obstacle exists in the image to be processed and the type of the obstacle is a pedestrian, determining a search area by taking the pedestrian as a center;
judging whether a moving object and a traction rope for connecting the moving object and the pedestrian exist in the search area;
if yes, judging that the barrier type is upgraded from a pedestrian to a pedestrian traction pet model;
if not, the obstacle type is judged to be a pedestrian.
Optionally, in the present invention, the search area is: and taking the pedestrian as a circle center and the first parameter as a radius area.
For example, the first parameter is 2 meters.
When a pedestrian exists in the image to be processed, searching in a searching region which takes the pedestrian as a circle center and takes the first parameter 2 meters as a radius, and determining whether a moving object and a traction rope for connecting the moving object and the pedestrian exist in the searching region;
if the barrier type exists, the current barrier type is upgraded from the pedestrian to a pedestrian traction pet model;
if not, the current obstacle type is the pedestrian.
Optionally, in the present invention, the S106 specifically includes:
when the type of the obstacle is a pedestrian and the moving speed of the pedestrian is greater than a first preset speed value, controlling the intelligent car to brake emergently;
and when the barrier type is that the pedestrian pulls the pet model and the moving speed of the pedestrian or the pet is greater than a first preset speed value, controlling the intelligent car to brake emergently.
The first preset speed value can be set according to actual requirements, so that the design flexibility is improved, and the requirements of different conditions are met.
As will be specifically explained below by way of example.
The obstacle types of example 1 and example 2 were both pedestrians.
Example 1, the first preset speed value may be set to 5 kilometers per hour, and when the moving speed of the pedestrian is greater than the first preset speed value, the intelligent car brakes emergently;
example 2, the first preset speed value may be set to 3.5 kilometers per hour, and when the moving speed of the pedestrian is greater than the first preset speed value, the speed of the smart car is halved, specifically, when the current vehicle speed is 60 steps, the speed of the smart car is reduced to 30 steps.
The barrier types of example 3 and example 4 were both pedestrian traction pet models.
Example 3, the first preset speed value may be set to 5 kilometers per hour, and when the moving speed of the pedestrian or the pet is greater than the first preset speed value, the intelligent vehicle is controlled to emergency brake;
example 4, the first preset speed value may be set to 3.5 kilometers per hour, and when the moving speed of the pedestrian or the pet is greater than the first preset speed value, the speed of the smart car is halved, specifically, when the current vehicle speed is 60 steps, the speed of the smart car is reduced to 30 steps.
It should be noted that, if the type of the obstacle is a pedestrian, when the intelligent vehicle is restarted after emergency braking, it is necessary to ensure that the width of the intelligent vehicle does not intersect with the search area which uses the pedestrian as a circle center and uses the first parameter as a radius during the traveling process of the intelligent vehicle, so that the occurrence of collision accidents between the intelligent vehicle and the pedestrian is avoided.
In addition, if the type of the obstacle is a model for dragging the pet by the pedestrian, when the intelligent car is restarted after emergency braking, the width of the intelligent car is required to be ensured not to intersect with a search area which takes the pedestrian as a circle center and a second parameter as a radius, wherein the second parameter is the sum of the first parameter and the length of the traction rope, namely, the traction rope is considered when the intelligent car is driven, so that the intelligent car cannot roll the pet even if the pet runs back and forth around the pedestrian in the road, and the safety is improved.
Optionally, in the present invention, the S106 further includes:
when the type of the obstacle is a static obstacle and the static obstacle is positioned in the center of a road, calculating a first distance between the static obstacle and one side of the road, and if the first distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn left or right to avoid the static obstacle; if the first distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again;
when the type of the obstacle is a static obstacle and the static obstacle is positioned on the left side of the road, calculating a second distance between the static obstacle and the right side of the road, and if the second distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn right to avoid the static obstacle; if the second distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again;
when the type of the obstacle is a static obstacle and the static obstacle is positioned on the right side of the road, calculating a third distance between the static obstacle and the left side of the road, and if the third distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn left to avoid the static obstacle; and if the third distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again.
Wherein, static barrier can be understood as a static barrier such as a stone pier.
In addition, when the first distance, the second distance and the third distance are all smaller than the width of the intelligent trolley, the intelligent trolley stops advancing, and the global route needs to be updated, so that the intelligent trolley can be prevented from being stuck by an obstacle in the advancing process.
Therefore, when the static obstacle exists in the image to be processed, the intelligent trolley turns to avoid the static obstacle according to the position of the static obstacle, and the static obstacle is prevented from being collided.
Optionally, in the present invention, the S106 further includes:
and when the type of the obstacle is a vehicle and the moving speed of the vehicle is greater than a second preset speed value, controlling the intelligent trolley to run at a reduced speed.
The second preset speed value can be set according to actual requirements, so that the design flexibility is improved, and the requirements of different conditions are met.
Example 5, the second preset speed value may be set to 80 kilometers per hour, and when the moving speed of the vehicle is greater than the second preset speed value, the intelligent vehicle emergently brakes;
example 6, the second preset speed value may be set to 60 kilometers per hour, and when the moving speed of the vehicle is greater than the second preset speed value, the intelligent vehicle decelerates thirty percent; and if the current vehicle speed is 100 steps, the speed of the intelligent vehicle is reduced to 70 steps.
Example 7, the second preset speed value may be set to 50 kilometers per hour, and when the moving speed of the vehicle is greater than the second preset speed value, the intelligent vehicle decelerates forty percent; and if the current vehicle speed is 100 steps, the speed of the intelligent vehicle is reduced to 60 steps.
Therefore, according to the intelligent vehicle control system, the intelligent vehicle is controlled to decelerate or stop emergently according to different moving speeds of the vehicle, so that the safe running of the intelligent vehicle is ensured, and the collision with the vehicle is avoided.
The working principle and the working process of the invention are as follows:
acquiring an initial image set without obstacles, wherein the initial image set comprises a plurality of initial images, and each initial image is subjected to filtering processing; acquiring an image to be processed in a corresponding information acquisition area according to the current running speed of the intelligent trolley, and filtering the image to be processed; calculating the similarity between each initial image and the image to be processed, determining the initial image with the highest similarity with the image to be processed, judging whether the similarity between the initial image and the image to be processed is greater than a first threshold value, if so, judging that no obstacle exists in the image to be processed, and if not, judging that an obstacle exists in the image to be processed; after determining that an obstacle exists in the processed image, acquiring an obstacle position and an obstacle type, wherein the obstacle type comprises a pedestrian, a vehicle and a static obstacle; when an obstacle exists in the image to be processed and the type of the obstacle is a pedestrian, determining an area with the pedestrian as a circle center and a first parameter as a radius as a search area, judging whether a moving object and a traction rope for connecting the moving object and the pedestrian exist in the search area, if so, judging that the type of the obstacle is upgraded from the pedestrian to a pedestrian traction pet model, and if not, judging that the type of the obstacle is the pedestrian; when the type of the obstacle is a pedestrian and the moving speed of the pedestrian is greater than a first preset speed value, controlling the intelligent car to brake emergently; when the barrier type is that a pedestrian pulls the pet model and the moving speed of the pedestrian or the pet is greater than a first preset speed value, controlling the intelligent car to brake emergently; when the type of the obstacle is a static obstacle, controlling and controlling the intelligent trolley to steer according to the position of the static obstacle; and when the type of the obstacle is a vehicle and the moving speed of the vehicle is greater than a second preset speed value, controlling the intelligent trolley to run at a reduced speed.
Therefore, in the invention, the obstacle is identified from the image to be processed through the acquired image to be processed, and the operations such as steering, deceleration or emergency braking of the intelligent vehicle are controlled based on the type of the obstacle and the moving speed of the obstacle, so that the automatic path planning of the intelligent vehicle in an unknown environment is realized, the intelligent vehicle is prevented from colliding with the obstacle, and the intelligent vehicle is ensured to safely travel to the destination.
The embodiments of the present invention have been described in detail, but the description is only for the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention should be covered by the present patent.
Claims (10)
1. A control method of an unmanned intelligent vehicle is characterized by comprising the following steps:
s101, setting a corresponding information acquisition area according to the running speed of the intelligent trolley;
s102, acquiring an image to be processed in the information acquisition area;
s103, determining whether an obstacle exists in the image to be processed;
s104, when an obstacle exists in the image to be processed, acquiring the position and the type of the obstacle;
s105, determining the moving speed of the obstacle according to the relative position change between the obstacle and the intelligent vehicle;
and S106, controlling the running state of the intelligent vehicle according to the type of the obstacle and the moving speed of the obstacle.
2. The method as claimed in claim 1, further comprising obtaining an initial image set without obstacles before S103, wherein the initial image set comprises a plurality of initial images.
3. The method for controlling the unmanned intelligent vehicle as claimed in claim 2, wherein the step S103 specifically comprises:
calculating the similarity of each initial image and the image to be processed;
determining the initial image with the highest similarity to the image to be processed;
judging whether the similarity between the initial image and the image to be processed is greater than a first threshold value;
if yes, judging that no obstacle exists in the image to be processed;
and if not, an obstacle exists in the image to be processed.
4. The method as claimed in claim 3, wherein the step S102 further includes filtering the image to be processed.
5. The method as claimed in any one of claims 1 to 4, wherein the obstacle types include pedestrians, vehicles and stationary obstacles.
6. The method for controlling the unmanned intelligent vehicle as claimed in claim 5, wherein the step S104 specifically comprises:
when an obstacle exists in the image to be processed and the type of the obstacle is a pedestrian, determining a search area by taking the pedestrian as a center;
judging whether a moving object and a traction rope for connecting the moving object and the pedestrian exist in the search area;
if yes, judging that the barrier type is upgraded from a pedestrian to a pedestrian traction pet model;
if not, the obstacle type is judged to be a pedestrian.
7. The method for controlling the unmanned intelligent vehicle as claimed in claim 6, wherein the search area is: and taking the pedestrian as a circle center and the first parameter as a radius area.
8. The method as claimed in claim 7, wherein the step S106 specifically includes:
when the type of the obstacle is a pedestrian and the moving speed of the pedestrian is greater than a first preset speed value, controlling the intelligent car to brake emergently;
and when the barrier type is that the pedestrian pulls the pet model and the moving speed of the pedestrian or the pet is greater than a first preset speed value, controlling the intelligent car to brake emergently.
9. The method as claimed in claim 8, wherein the S106 further comprises:
when the type of the obstacle is a static obstacle and the static obstacle is positioned in the center of a road, calculating a first distance between the static obstacle and one side of the road, and if the first distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn left or right to avoid the static obstacle; if the first distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again;
when the type of the obstacle is a static obstacle and the static obstacle is positioned on the left side of the road, calculating a second distance between the static obstacle and the right side of the road, and if the second distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn right to avoid the static obstacle; if the second distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again;
when the type of the obstacle is a static obstacle and the static obstacle is positioned on the right side of the road, calculating a third distance between the static obstacle and the left side of the road, and if the third distance is larger than the width of the intelligent trolley, controlling the intelligent trolley to turn left to avoid the static obstacle; and if the third distance is smaller than or equal to the width of the intelligent trolley, the intelligent trolley performs route planning again.
10. The method as claimed in claim 9, wherein the S106 further includes:
and when the type of the obstacle is a vehicle and the moving speed of the vehicle is greater than a second preset speed value, controlling the intelligent trolley to run at a reduced speed.
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| CN202210205507.5A CN114545950A (en) | 2022-03-03 | 2022-03-03 | Control method of unmanned intelligent vehicle |
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| CN202210205507.5A CN114545950A (en) | 2022-03-03 | 2022-03-03 | Control method of unmanned intelligent vehicle |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115185285A (en) * | 2022-09-06 | 2022-10-14 | 深圳市信诚创新技术有限公司 | Automatic obstacle avoidance method, device and equipment for dust collection robot and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115185285A (en) * | 2022-09-06 | 2022-10-14 | 深圳市信诚创新技术有限公司 | Automatic obstacle avoidance method, device and equipment for dust collection robot and storage medium |
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