CN115285116A - Vehicle obstacle avoidance method and device, electronic equipment and readable storage medium - Google Patents
Vehicle obstacle avoidance method and device, electronic equipment and readable storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0953—Predicting travel path or likelihood of collision the prediction being responsive to vehicle dynamic parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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Abstract
The application discloses a vehicle obstacle avoidance method, a vehicle obstacle avoidance device, electronic equipment and a readable storage medium, which are applied to the technical field of vehicles, wherein the vehicle obstacle avoidance method comprises the following steps: when a risk obstacle is detected in a front traveling area of a vehicle, acquiring obstacle information of the risk obstacle, vehicle information, road information in the front traveling area and lane occupation information, wherein the road information comprises lane line information; identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information; and controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type. The application solves the technical problem that the control safety of the vehicle is low.
Description
Technical Field
The present application relates to the field of vehicle technologies, and in particular, to a vehicle obstacle avoidance method and apparatus, an electronic device, and a readable storage medium.
Background
With the rapid development of science and technology, intelligent auxiliary driving technology is developed more and more mature, at present, static obstacles such as roadblocks and the like appear in a front traveling area of a vehicle in the driving process, a planned route of the vehicle is usually determined through the positions of the obstacles, the real scene of vehicle driving is complex and changeable, the planned route is determined only through a single obstacle position, and when the vehicle cannot change lanes or the road condition is poor, the condition that the vehicle collides with the static obstacles easily occurs, so that the control safety of the vehicle is low.
Disclosure of Invention
The application mainly aims to provide a vehicle obstacle avoidance method, a vehicle obstacle avoidance device, an electronic device and a readable storage medium, and aims to solve the technical problem that in the prior art, the control safety of a vehicle is low.
In order to achieve the above object, the present application provides a vehicle obstacle avoidance method, which is applied to a vehicle obstacle avoidance device, and the vehicle obstacle avoidance method includes:
when a risk obstacle is detected in a front traveling area of a vehicle, acquiring obstacle information of the risk obstacle, vehicle information, road information in the front traveling area and lane occupation information, wherein the road information comprises lane line information;
identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information;
and controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
In order to realize the above-mentioned purpose, this application still provides a vehicle keeps away barrier device, the vehicle keeps away barrier device and is applied to the vehicle and keeps away barrier equipment, the vehicle keeps away the barrier device and includes:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring obstacle information, vehicle information, road information and lane occupation information of a risk obstacle when the risk obstacle is detected in a front travelling area of a vehicle, and the road information comprises lane line information;
the selection module is used for identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information;
and the control module is used for controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
The present application further provides an electronic device, the electronic device including: the present invention relates to a vehicle obstacle avoidance system, and a computer program product, wherein the vehicle obstacle avoidance system comprises a memory, a processor, and a program of the vehicle obstacle avoidance system stored on the memory and operable on the processor, wherein the program of the vehicle obstacle avoidance system when executed by the processor implements the steps of the vehicle obstacle avoidance system as described above.
The application also provides a computer readable storage medium, on which a program for implementing the vehicle obstacle avoidance method is stored, and when executed by a processor, the program for implementing the vehicle obstacle avoidance method implements the steps of the vehicle obstacle avoidance method as described above.
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the vehicle obstacle avoidance method as described above.
Compared with a method for determining a planned route of a vehicle through the position of an obstacle, the method comprises the steps of obtaining obstacle information, vehicle information, road information in a front traveling area and lane occupation information of the risk obstacle when the risk obstacle is detected to exist in the front traveling area of the vehicle, wherein the road information comprises lane line information; identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information; according to the obstacle avoidance strategy determined according to the vehicle obstacle avoidance scene type, the vehicle is controlled to avoid obstacles, the vehicle obstacle avoidance scene type where the vehicle is located is identified through obstacle information, vehicle information, road information and lane occupation information, the obstacle avoidance strategy is determined, the obstacle avoidance strategy with high safety is matched for the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupation information, and when the method for determining the planned route of the vehicle through the position of the obstacle is adopted, the technical defect that the vehicle and a static obstacle collide easily occurs when the vehicle cannot change the lane or the road condition is poor due to the fact that the real scene of vehicle driving is complex and changeable, the planned route is determined only through the position of the single obstacle is avoided, and the control safety of the vehicle is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flowchart illustrating a first embodiment of a vehicle obstacle avoidance method according to the present application;
fig. 2 is a schematic view of a scene related to the vehicle obstacle avoidance method of the present application;
fig. 3 is a schematic view of another scenario involved in the vehicle obstacle avoidance method of the present application;
fig. 4 is a schematic view of another scenario involved in the vehicle obstacle avoidance method of the present application;
FIG. 5 is a schematic view of another scenario involved in the vehicle obstacle avoidance method of the present application;
fig. 6 is a schematic structural diagram of a hardware operating environment related to a vehicle obstacle avoidance method in an embodiment of the present application.
The objectives, features, and advantages of the present application will be further described with reference to the accompanying drawings.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments of the present application are described in detail below with reference to the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Example one
In a first embodiment of the vehicle obstacle avoidance method, referring to fig. 1, the vehicle obstacle avoidance method includes:
step S10, when a risk obstacle is detected in a front travelling area of a vehicle, acquiring obstacle information, vehicle information, road information and lane occupation information of the risk obstacle, wherein the road information comprises lane line information;
in this embodiment, it should be noted that the front traveling area is an area where a vehicle in an approach to an original planned path of the vehicle advances, the risk obstacle is a static obstacle having a collision risk with the vehicle, the risk obstacle may be a road barrier, and the number of the risk obstacles may be one or multiple.
Exemplarily, step S10 includes: acquiring a region image of a front traveling region of the vehicle, and determining obstacle information of a risk obstacle, road information in the front traveling region and lane occupancy information according to the region image, wherein the region image comprises a risk obstacle image, a lane line image and a road image, or the obstacle information of the risk obstacle, the road information in the front traveling region and the lane occupancy information are sensed by a millimeter wave radar sensor; and collecting vehicle information of the vehicle.
Alternatively, the step of acquiring the area image of the forward traveling area of the vehicle may be: through the vehicle event data recorder of vehicle gathers regional image, perhaps, through external the camera of vehicle gathers regional image, wherein, the camera can be the monocular camera, also can be for two mesh cameras, still can be for other many meshes cameras.
It can be understood that, when sensing through the millimeter wave radar sensor, because the visualization of radar wave is relatively poor, it is relatively poor to the acquisition information accuracy of obstacle information and road information, and when adopting monocular camera or vehicle event data recorder, because it is relatively poor to shoot the precision, the condition that the acquisition information accuracy of obstacle information and road information is relatively poor appears easily, and then lead to the risk increase that vehicle and risk obstacle bump, and then make the control security of vehicle low, moreover regional image be the image of the position of advancing of vehicle, consequently to other many cameras, there is the unnecessary cost, so preferably adopt the binocular camera to gather regional image, compromise the control security of vehicle and the control cost of vehicle.
In step S10, the vehicle information includes wheel information and vehicle width, and when it is detected that a dangerous obstacle exists in a forward traveling area of the vehicle, the vehicle information, road information in the forward traveling area, and lane occupancy information of the dangerous obstacle are acquired, where the road information includes lane line information:
s11, acquiring a risk obstacle image carrying risk obstacle information in the front traveling area, a lane line image carrying lane line information in the front traveling area and a road image carrying road information in the front traveling area;
exemplarily, step S11 includes: the method comprises the steps of collecting risk obstacle images carrying risk obstacle information in a front travelling area, lane line images carrying lane line information in the front travelling area and road images carrying road information in the front travelling area through a binocular camera of the vehicle arranged outside.
Step S12, determining a first distance between the risk obstacle and the vehicle, the number of obstacles of the risk obstacle, an obstacle color, an obstacle size, and an obstacle shape according to the risk obstacle image, and using the first distance, the number of obstacles, the obstacle color, the obstacle size, and the obstacle shape as the obstacle information;
exemplarily, step S12 includes: according to the risk obstacle image and a binocular camera vision recognition algorithm, calculating to obtain a distance parallel to a lane line between the risk obstacle and the vehicle, and obtaining a first distance between the risk obstacle and the vehicle; obtaining the number of obstacles, the color of the obstacles, the size of the obstacles and the shape of the obstacles of the risk obstacles by inputting the image of the risk obstacles into a preset image recognition model, and integrating the first distance, the number of the obstacles, the color of the obstacles, the size of the obstacles and the shape of the obstacles to obtain the information of the obstacles, wherein the preset image recognition model comprises a number recognition model, a size recognition model and a shape recognition model.
When the color of the obstacle is a red and white combined color and the shape of the obstacle is a cone, the risk obstacle is judged to be a road obstacle, and the road obstacle is set by the national regulation standard and has a regular shape and size, so that the calculation result of the first distance between the risk obstacle and the vehicle is accurate, the selected vehicle obstacle avoidance scene type is accurate, and the control safety of the vehicle is improved.
Step S13, taking the lane line distance between the risk barrier and the lane line in the front traveling area as the lane occupation information;
exemplarily, step S13 includes: and calculating to obtain the lane line distance between the risk obstacle and the lane line in the front traveling region according to the risk obstacle image and a binocular camera vision recognition algorithm, and taking the lane line distance as the lane occupation information.
Step S14, acquiring the vehicle model of the vehicle, and determining the wheel information and the vehicle width of the vehicle according to the vehicle model;
exemplarily, step S14 includes: the method comprises the steps of obtaining the vehicle model of the vehicle, obtaining the vehicle width, the tire material and the tire size of the vehicle according to the vehicle model, and integrating the tire material and the tire size to obtain wheel information of the vehicle.
Step S15, determining the linearity and the color of a lane line in the front traveling area according to the lane line image, and taking the linearity and the color as the lane line information;
exemplarily, step S15 includes: according to the lane line image and a preset image recognition model, recognizing to obtain the linearity and the color of a lane line in the front traveling area, classifying the lane line according to the linearity and the color to obtain a lane line classification result, and using the lane line classification result as lane line information.
And step S15, determining the road condition information according to the road image, wherein the road condition information at least comprises one of road mud information, road slippery degree and road depression degree.
Exemplarily, step S15 includes: and inputting the road image into a preset image recognition model to obtain the road mud information, the road wet and slippery degree and the road depression degree of the road in the front advancing area.
Step S20, recognizing the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information;
as an example, step S20 includes: and judging the obstacle avoidance scene of the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupation information to obtain a vehicle obstacle avoidance scene corresponding to the vehicle.
As an example, step S20 includes: and constructing a vehicle obstacle avoidance scene feature vector according to the obstacle information, the vehicle information, the road information and the lane occupation information, and mapping the vehicle obstacle avoidance scene feature vector to a vehicle obstacle avoidance scene type where the vehicle is located through a preset vehicle obstacle avoidance scene determination model.
Optionally, generating an obstacle type tag of the risk obstacle according to the obstacle size, the obstacle color and the obstacle shape, generating a lane line type tag of each lane line according to the lane line information, and generating a road type tag of the road according to the road mud information, the road wet and slippery degree and the road sag degree; and splicing the first distance, the lane line distance, the number of obstacles, the obstacle type label, the lane line type label and the road type label into the vehicle obstacle avoidance scene feature vector.
It can be understood that when the road surface condition is that the road surface is muddy, the road surface muddy condition affects the driving condition of the vehicle, such as when the vehicle is driven on a muddy road, the vehicle is easy to skid or get deep into a mud pit; when the road surface condition is that the road surface is slippery, the vehicle is easy to slip and even turn over when the vehicle runs on a slippery road section; when the road surface condition is a concave road surface, such as when the vehicle runs on a concave road section, the vehicle collision condition is easy to occur, so that the collision risk of the vehicle colliding with a risk obstacle is increased, and the control safety of the vehicle is low.
According to the method and the device, the vehicle obstacle avoidance scene determining between the vehicle and the risk obstacle is influenced by various factors, according to the obstacle information of the risk obstacle, the vehicle information and the road information, the vehicle obstacle avoidance scene feature vectors corresponding to the matching of the vehicle and the risk obstacle are provided, the influence of various factors on the vehicle obstacle avoidance scene determining is fully considered, and the vehicle obstacle avoidance scene feature vectors are input values used for determining the vehicle obstacle avoidance scene, so that more decision bases are provided for determining the vehicle obstacle avoidance scene of the vehicle and the risk obstacle, and the accuracy of the vehicle obstacle avoidance scene determining is improved.
In step S20, the step of identifying the vehicle obstacle avoidance scene type according to the obstacle information, the vehicle information, the road information, and the lane occupancy information includes:
the step of identifying the type of the vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupancy information comprises:
step S21, determining a target driving lane and a target driving state of the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupation information;
as an example, step S21 includes: judging whether the vehicle needs to change lanes or not according to the vehicle information and the lane occupancy information, if the vehicle does not need to change lanes, taking an original driving lane corresponding to the vehicle as a target driving lane, judging whether the vehicle can safely pass through the target driving lane or not, and if the vehicle can safely pass through the target driving lane, taking a running state as a target driving state of the vehicle; if the vehicle cannot safely pass through the target driving lane, taking the parking state as the target driving state of the vehicle; if the vehicle needs to change lanes, judging whether the vehicle can change to an adjacent lane and safely pass through the adjacent lane according to the road information, if so, taking the adjacent lane as the target driving lane, and taking the traveling state as the target driving state of the vehicle; and if the vehicle cannot change to the adjacent lane and/or cannot safely pass through the adjacent lane, taking the original driving lane as the target driving lane and the parking state as the target driving state of the vehicle.
As an example, step S21 includes: and mapping the vehicle obstacle avoidance scene feature vector into a driving state label and a driving lane label of the vehicle through a preset vehicle state model.
And S22, identifying the type of the vehicle obstacle avoidance scene where the vehicle is located according to the target driving lane and the target driving state.
Exemplarily, step S22 includes: and acquiring an original driving lane of the vehicle, and identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the original driving lane, the target driving lane and the target driving state.
In step S22, the vehicle obstacle avoidance scene types include a first vehicle obstacle avoidance scene, a second vehicle obstacle avoidance scene, and a third vehicle obstacle avoidance scene, the target driving state includes a parking state and a traveling state, and the step of identifying the vehicle obstacle avoidance scene type where the vehicle is located according to the target driving lane and the target driving state includes:
step A10, acquiring an original driving lane of the vehicle;
step A20, if the original driving lane is consistent with the target driving lane and the target driving state is a traveling state, selecting the first vehicle obstacle avoidance scene as a vehicle obstacle avoidance scene type where the vehicle is located;
step A30, if the original driving lane is inconsistent with the target driving lane and the target driving state is a driving state, selecting the second vehicle obstacle avoidance scene as a vehicle obstacle avoidance scene type where the vehicle is located;
and A40, if the original driving lane is consistent with the target driving lane and the target driving state is a parking state, selecting the third vehicle obstacle avoidance scene as the vehicle obstacle avoidance scene type where the vehicle is located.
Exemplarily, the steps a10 to a40 include: acquiring an original driving lane of the vehicle; judging whether the vehicle running state is a parking state or not, and if the vehicle running state is the parking state, selecting the third vehicle obstacle avoidance scene as the vehicle obstacle avoidance scene type where the vehicle is located; if the vehicle driving state is not the parking state, judging whether the original driving lane is consistent with the target driving lane, and if the original driving lane is consistent with the target driving lane, selecting the first vehicle obstacle avoidance scene as the vehicle obstacle avoidance scene type where the vehicle is located; and if the original driving lane is inconsistent with the target driving lane, selecting the second vehicle obstacle avoidance scene as the vehicle obstacle avoidance scene type where the vehicle is located.
And S30, controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
Exemplarily, step S30 includes: determining an obstacle avoidance strategy corresponding to the vehicle according to the type of the vehicle obstacle avoidance scene, controlling the vehicle to avoid the risk obstacle according to the obstacle avoidance strategy, and outputting alarm information, wherein the alarm information can be optical prompt and/or acoustic prompt.
As an example, referring to fig. 2, fig. 2 includes: the binocular camera and the cone barrel identification and response system are characterized in that the cone barrel identification and response system and the binocular camera are used, the number of cone barrels, the shapes of the cone barrels and the colors of the cone barrels are obtained according to visual identification algorithm identification, the transverse distance of the cone barrels, the longitudinal distance of the cone barrels and the transverse distance of lane lines are obtained according to binocular parallax principle calculation, and therefore cone barrel identification results are obtained according to the number of the cone barrels, the shapes of the cone barrels, the colors of the cone barrels, the transverse distance of the cone barrels, the longitudinal distance of the cone barrels and the transverse distance of the lane lines, and corresponding response strategies are selected through the response system according to the cone barrel identification results.
Compared with a method for determining a planned route of a vehicle through the position of an obstacle, the method for avoiding the obstacle by the vehicle obtains obstacle information, vehicle information, road information and lane occupation information of the risk obstacle when the risk obstacle is detected in a front travelling area of the vehicle, wherein the road information comprises lane line information; identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information; according to the obstacle avoidance strategy determined according to the type of the vehicle obstacle avoidance scene, the vehicle is controlled to avoid obstacles, the type of the vehicle obstacle avoidance scene where the vehicle is located is identified through obstacle information, vehicle information, road information and lane occupation information, so that the obstacle avoidance strategy is determined, the obstacle avoidance strategy with high safety is matched for the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupation information, and the technical defect that the vehicle and a static obstacle collide easily occurs when the vehicle cannot change lanes or the road condition is poor due to the fact that the real scene of vehicle driving is complex and changeable and the planned route is determined only through the position of a single obstacle when the method for determining the planned route of the vehicle through the position of the obstacle is adopted is avoided, and the control safety of the vehicle is improved.
Example two
Further, based on the first embodiment of the present application, in another embodiment of the present application, the same or similar contents to the first embodiment described above may be referred to the above description, and are not repeated herein. On this basis, in step S30, the step of controlling the vehicle to avoid the obstacle according to the obstacle avoidance strategy determined by the vehicle obstacle avoidance scene type includes:
step S31, if the vehicle obstacle avoidance scene type is a first vehicle obstacle avoidance scene, controlling the vehicle to detour the risk obstacle in the target driving lane;
step S32, if the vehicle obstacle avoidance scene type is a second vehicle obstacle avoidance scene, controlling the vehicle to change from the original driving lane to the target driving lane;
and S33, if the type of the vehicle obstacle avoidance scene is a third vehicle obstacle avoidance scene, controlling the vehicle to decelerate and brake.
Exemplarily, steps S31 to S33 include: if the vehicle obstacle avoidance scene type is a first vehicle obstacle avoidance scene, determining a planned route of the vehicle according to the vehicle information, the obstacle information and the lane occupation information, and controlling the vehicle to detour the risk obstacle in the target driving lane according to the planned route, wherein the planned route comprises driving positions of the vehicle at the next time step, steering wheel angles corresponding to the driving positions and driving speeds corresponding to the driving positions; if the vehicle obstacle avoidance scene type is a second vehicle obstacle avoidance scene, determining a planned route of the vehicle according to the road information, and controlling the vehicle to change the original driving lane into the target driving lane according to the planned route; and if the type of the vehicle obstacle avoidance scene is a third vehicle obstacle avoidance scene, controlling the vehicle to decelerate and brake.
Wherein, in step S32, the step of controlling the vehicle to change from the original driving lane to the target driving lane includes:
step B10, collecting lane images carrying target driving lane information;
step B20, determining target lane occupation information of the target driving lane according to the lane image;
and B30, generating a planned route of the vehicle according to the target lane occupation information, and controlling the vehicle to change from the original driving lane to the target driving lane according to the planned route.
Exemplarily, the steps B10 to B30 include: acquiring a lane image carrying target driving lane information behind the vehicle through a camera arranged outside the vehicle, identifying target driving lane occupation conditions of other vehicles in the target driving lane according to the lane image to obtain the target lane occupation information, determining each driving position of the vehicle at the next time step, a steering wheel angle corresponding to each driving position and a driving speed corresponding to each driving position according to the target lane occupation information, constructing a planned route of the vehicle according to each driving position, the steering wheel angle corresponding to each driving position and the driving speed corresponding to each driving position, and controlling the vehicle to change the original driving lane into the target driving lane according to the planned route.
In step S10, before the step of acquiring obstacle information, vehicle information, and road information in the forward travel area when it is detected that a dangerous obstacle exists in the forward travel area of the vehicle, the method further includes:
step C10, acquiring a region image of a forward traveling region of the vehicle, and determining a second distance between an obstacle and the vehicle according to the region image if the obstacle exists in the region image;
exemplarily, step C10 includes: acquiring a region image of a front traveling region of the vehicle, judging whether an obstacle exists in the front traveling region of the vehicle according to the region image, if so, calculating a second distance between the obstacle and the vehicle according to the region image, and if not, returning to the executing step: acquiring a region image of a forward traveling region of the vehicle, or sensing whether an obstacle exists in the forward traveling region of the vehicle through a millimeter wave radar sensor; if an obstacle exists in the front traveling region, sensing a second distance between the obstacle and the vehicle through the millimeter wave radar sensor, and if the obstacle does not exist in the front traveling region, returning to the execution step: whether an obstacle exists in a forward traveling area of the vehicle is sensed by a millimeter wave radar sensor.
Alternatively, the step of acquiring the area image of the forward traveling area of the vehicle may be: through the vehicle event data recorder of vehicle gathers regional image, perhaps, through external arranging in the camera of vehicle gathers regional image, wherein, the camera can be monocular camera, also can be two mesh cameras, still can be other many meshes cameras.
Step C20, judging whether the second distance is smaller than or equal to a preset distance threshold value;
step C30, if yes, judging that a risk obstacle exists in a front travelling area of the vehicle;
and C40, if not, judging that no risk obstacle exists in the front travelling area of the vehicle, and returning to the execution step: acquiring a region image of a forward travel region of the vehicle.
In this embodiment, it should be noted that the preset distance threshold is a preset critical value of a second distance between the obstacle and the vehicle, which is used for determining that there is a possibility of collision between the vehicle and the obstacle.
Exemplarily, the step C20 to the step C40 include: judging whether the second distance is smaller than or equal to a preset distance threshold value; if the second distance is smaller than or equal to a preset distance threshold value, determining that a risk obstacle exists in a front travelling area of the vehicle, and executing a step S10; if the second distance is greater than a preset distance threshold value, judging that no risk obstacle exists in a front travelling area of the vehicle, and returning to the execution step: acquiring an area image of a forward traveling area of the vehicle, or returning to the execution step: sensing, by the millimeter wave radar sensor, a second distance between the obstacle and the vehicle.
As an example, referring to fig. 3, when the original driving lane and the planned lane are consistent, a front cone danger signal is transmitted to the intelligent driving controller through a binocular camera, the intelligent driving controller performs lateral control on the vehicle through an EPS (Electric Power Steering), avoids the cone in the original driving lane, outputs an optical danger signal prompt through a meter, and outputs an acoustic danger signal prompt through a buzzer.
As an example, referring to fig. 4, when the original driving lane and the planned lane are not the same, the binocular camera determines whether a dotted lane line exists and identifies whether there is danger information of a front cone, and if there is a dotted lane line and there is a danger signal of a front cone, the intelligent driving controller performs lateral control on the vehicle through the EPS, changes the original driving lane of the vehicle into the planned lane, performs longitudinal control on the vehicle through an EBS (electronic Brake System), controls the vehicle to decelerate, outputs an optical danger signal prompt through the meter, and outputs an acoustic danger signal prompt through the buzzer.
As an example, referring to fig. 5, when each of the collision risks is greater than or equal to a preset collision risk threshold, a front cone barrel danger signal is sent to the intelligent driving controller through the binocular camera, the intelligent driving controller performs longitudinal control on the vehicle through the EBS, controls the vehicle to decelerate and stop, outputs a danger signal optical prompt through the instrument, and outputs a danger signal acoustic prompt through the buzzer.
Compared with a method for determining a planned route of a vehicle through the position of an obstacle, the method for avoiding the obstacle by the vehicle obtains obstacle information, vehicle information, road information in a front traveling area and lane occupation information of the risk obstacle when the risk obstacle is detected in the front traveling area of the vehicle, wherein the road information comprises lane line information; identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information; according to the obstacle avoidance strategy determined according to the type of the vehicle obstacle avoidance scene, the vehicle is controlled to avoid obstacles, the type of the vehicle obstacle avoidance scene where the vehicle is located is identified through obstacle information, vehicle information, road information and lane occupation information, so that the obstacle avoidance strategy is determined, the obstacle avoidance strategy with high safety is matched for the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupation information, and the technical defect that the vehicle and a static obstacle collide easily occurs when the vehicle cannot change lanes or the road condition is poor due to the fact that the real scene of vehicle driving is complex and changeable and the planned route is determined only through the position of a single obstacle when the method for determining the planned route of the vehicle through the position of the obstacle is adopted is avoided, and the control safety of the vehicle is improved.
EXAMPLE III
The embodiment of the application still provides a barrier device is kept away to vehicle, barrier device is kept away to vehicle is applied to vehicle and keeps away barrier equipment, the barrier device is kept away to vehicle includes:
the system comprises an acquisition module, a judgment module and a display module, wherein the acquisition module is used for acquiring obstacle information, vehicle information, road information and lane occupation information of a risk obstacle when the risk obstacle exists in a front travelling area of a vehicle, and the road information comprises lane line information;
the selection module is used for identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information;
and the control module is used for controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
Optionally, the vehicle information includes wheel information and vehicle width, the road information further includes road condition information, and the obtaining module is further configured to:
acquiring a risk obstacle image carrying risk obstacle information in the front traveling area, a lane line image carrying lane line information in the front traveling area and a road image carrying road information in the front traveling area;
determining a first distance between the risk obstacle and the vehicle, the number of obstacles of the risk obstacle, an obstacle color, an obstacle size, and an obstacle shape from the risk obstacle image, and using the first distance, the number of obstacles, the obstacle color, the obstacle size, and the obstacle shape as the obstacle information;
taking the lane line distance between the risk obstacle and the lane line in the front traveling region as the lane occupation information;
acquiring the vehicle model of the vehicle, and determining the wheel information and the vehicle width of the vehicle according to the vehicle model;
according to the lane line image, determining the linearity and the color of a lane line in the front traveling area, and taking the linearity and the color as the lane line information;
and determining the road condition information according to the road image, wherein the road condition information at least comprises one of road mud information, road slippery degree and road depression degree.
Optionally, the selecting module is further configured to:
determining a target driving lane and a target driving state of the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupation information;
and identifying the type of the vehicle obstacle avoidance scene where the vehicle is located according to the target driving lane and the target driving state.
Optionally, the vehicle obstacle avoidance scene types include a first vehicle obstacle avoidance scene, a second vehicle obstacle avoidance scene, and a third vehicle obstacle avoidance scene, the target driving state includes a parking state and a traveling state, and the selection module is further configured to:
acquiring an original driving lane of the vehicle;
if the original driving lane is consistent with the target driving lane and the target driving state is a traveling state, selecting the first vehicle obstacle avoidance scene as a vehicle obstacle avoidance scene type where the vehicle is located;
if the original driving lane is inconsistent with the target driving lane and the target driving state is a traveling state, selecting the second vehicle obstacle avoidance scene as the vehicle obstacle avoidance scene type where the vehicle is located;
and if the original driving lane is consistent with the target driving lane and the target driving state is a parking state, selecting the third vehicle obstacle avoidance scene as the type of the vehicle obstacle avoidance scene where the vehicle is located.
Optionally, the control module is further configured to:
if the vehicle obstacle avoidance scene type is a first vehicle obstacle avoidance scene, controlling the vehicle to detour the risk obstacle in the target driving lane;
if the vehicle obstacle avoidance scene type is a second vehicle obstacle avoidance scene, controlling the vehicle to change from the original driving lane to the target driving lane;
and if the type of the vehicle obstacle avoidance scene is a third vehicle obstacle avoidance scene, controlling the vehicle to decelerate and brake.
Optionally, the control module is further configured to:
collecting a lane image carrying target driving lane information;
determining target lane occupation information of the target driving lane according to the lane image;
and generating a planned route of the vehicle according to the target lane occupation information, and controlling the vehicle to change from the original driving lane to the target driving lane according to the planned route.
Optionally, before the step of obtaining obstacle information of a risk obstacle, vehicle information, road information in the forward traveling area, and lane occupancy information when it is detected that the risk obstacle exists in the forward traveling area of the vehicle, where the road information includes lane line information, the vehicle obstacle avoidance apparatus is further configured to:
acquiring an area image of a forward traveling area of the vehicle, and determining a second distance between an obstacle and the vehicle according to the area image if the obstacle exists in the area image;
judging whether the second distance is smaller than or equal to a preset distance threshold value or not;
if yes, determining that a risk obstacle exists in a front travelling area of the vehicle;
if not, judging that no risk obstacle exists in the front travelling area of the vehicle, and returning to the execution step: acquiring a region image of a forward travel region of the vehicle.
The vehicle obstacle avoidance device provided by the application adopts the vehicle obstacle avoidance method in the embodiment, and solves the technical problem that the control safety of a vehicle is low. Compared with the prior art, the vehicle obstacle avoidance device provided by the embodiment of the application has the same beneficial effects as the vehicle obstacle avoidance method provided by the embodiment, and other technical features of the vehicle obstacle avoidance device are the same as those disclosed by the embodiment method, and are not repeated herein.
Example four
An embodiment of the present application provides an electronic device, which includes: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the vehicle obstacle avoidance method in the above embodiments.
Referring now to FIG. 6, shown is a schematic diagram of an electronic device suitable for use in implementing embodiments of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 6, the electronic device may include a processing means (e.g., a central processing unit, a graphic processor, etc.) that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) or a program loaded from a storage means into a Random Access Memory (RAM). In the RAM, various programs and data necessary for the operation of the electronic apparatus are also stored. The processing device, the ROM, and the RAM are connected to each other by a bus. An input/output (I/O) interface is also connected to the bus.
Generally, the following systems may be connected to the I/O interface: input devices including, for example, touch screens, touch pads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, and the like; output devices including, for example, liquid Crystal Displays (LCDs), speakers, vibrators, and the like; storage devices including, for example, magnetic tape, hard disk, etc.; and a communication device. The communication means may allow the electronic device to communicate wirelessly or by wire with other devices to exchange data. While the figures illustrate an electronic device with various systems, it is to be understood that not all illustrated systems are required to be implemented or provided. More or fewer systems may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means, or installed from a storage means, or installed from a ROM. The computer program, when executed by a processing device, performs the functions defined in the methods of the embodiments of the present disclosure.
The electronic equipment provided by the application adopts the vehicle obstacle avoidance method in the embodiment, and the technical problem that the control safety of a vehicle is low is solved. Compared with the prior art, the beneficial effects of the electronic device provided by the embodiment of the application are the same as the beneficial effects of the vehicle obstacle avoidance method provided by the embodiment, and other technical features of the electronic device are the same as those disclosed by the embodiment method, which are not repeated herein.
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the foregoing description of embodiments, the particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
EXAMPLE five
The present embodiment provides a computer-readable storage medium having stored thereon computer-readable program instructions for performing the method of the vehicle obstacle avoidance method in the above-described embodiments.
The computer readable storage medium provided by the embodiments of the present application may be, for example, a usb disk, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the above. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present embodiment, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer-readable storage medium may be embodied in an electronic device; or may be separate and not incorporated into the electronic device.
The computer readable storage medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: when a risk obstacle is detected in a front traveling area of a vehicle, acquiring obstacle information of the risk obstacle, vehicle information, road information in the front traveling area and lane occupation information, wherein the road information comprises lane line information; identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information; and controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present disclosure may be implemented by software or hardware. Wherein the names of the modules do not in some cases constitute a limitation of the unit itself.
The computer-readable storage medium stores computer-readable program instructions for executing the vehicle obstacle avoidance method, and solves the technical problem that the control safety of the vehicle is low. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the embodiment of the application are the same as the beneficial effects of the vehicle obstacle avoidance method provided by the implementation, and are not described herein again.
EXAMPLE six
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the vehicle obstacle avoidance method as described above.
The application provides a computer program product has solved the low technical problem of control security of vehicle. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the application are the same as those of the vehicle obstacle avoidance method provided by the embodiment, and are not repeated herein.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A vehicle obstacle avoidance method is characterized by comprising the following steps:
when a risk obstacle is detected in a front traveling area of a vehicle, acquiring obstacle information of the risk obstacle, vehicle information, road information in the front traveling area and lane occupation information, wherein the road information comprises lane line information;
identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information;
and controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
2. The vehicle obstacle avoidance method according to claim 1, wherein the vehicle information includes wheel information and vehicle width, the road information further includes road condition information, and the acquiring obstacle information of a risk obstacle, vehicle information, road information in a forward traveling area of the vehicle, and lane occupancy information when it is detected that the risk obstacle exists in the forward traveling area, wherein the road information includes lane line information includes:
acquiring a risk obstacle image carrying risk obstacle information in the front traveling area, a lane line image carrying lane line information in the front traveling area and a road image carrying road information in the front traveling area;
determining a first distance between the risk obstacle and the vehicle, the number of obstacles of the risk obstacle, an obstacle color, an obstacle size, and an obstacle shape from the risk obstacle image, and using the first distance, the number of obstacles, the obstacle color, the obstacle size, and the obstacle shape as the obstacle information;
taking the lane line distance between the risk barrier and the lane line in the front traveling area as the lane occupation information;
acquiring the vehicle model of the vehicle, and determining the wheel information and the vehicle width of the vehicle according to the vehicle model;
according to the lane line image, determining the linearity and the color of a lane line in the front traveling area, and taking the linearity and the color as the lane line information;
and determining the road condition information according to the road image, wherein the road condition information at least comprises one of road mud information, road slippery degree and road depression degree.
3. The vehicle obstacle avoidance method according to claim 2, wherein the step of identifying a vehicle obstacle avoidance scene type in which the vehicle is located according to the obstacle information, the vehicle information, the road information, and the lane occupancy information includes:
determining a target driving lane and a target driving state of the vehicle according to the obstacle information, the vehicle information, the road information and the lane occupancy information;
and identifying the type of the vehicle obstacle avoidance scene where the vehicle is located according to the target driving lane and the target driving state.
4. The vehicle obstacle avoidance method according to claim 3, wherein the vehicle obstacle avoidance scene types include a first vehicle obstacle avoidance scene, a second vehicle obstacle avoidance scene, and a third vehicle obstacle avoidance scene, the target driving state includes a parking state and a traveling state, and the step of identifying the vehicle obstacle avoidance scene type in which the vehicle is located according to the target driving lane and the target driving state includes:
acquiring an original driving lane of the vehicle;
if the original driving lane is consistent with the target driving lane and the target driving state is a traveling state, selecting the first vehicle obstacle avoidance scene as a vehicle obstacle avoidance scene type where the vehicle is located;
if the original driving lane is inconsistent with the target driving lane and the target driving state is a driving state, selecting the second vehicle obstacle avoidance scene as a vehicle obstacle avoidance scene type where the vehicle is located;
and if the original driving lane is consistent with the target driving lane and the target driving state is a parking state, selecting the third vehicle obstacle avoidance scene as the vehicle obstacle avoidance scene type where the vehicle is located.
5. The vehicle obstacle avoidance method according to claim 4, wherein the step of controlling the vehicle to avoid the obstacle according to the obstacle avoidance strategy determined by the vehicle obstacle avoidance scene type includes:
if the vehicle obstacle avoidance scene type is a first vehicle obstacle avoidance scene, controlling the vehicle to detour the risk obstacle in the target driving lane;
if the vehicle obstacle avoidance scene type is a second vehicle obstacle avoidance scene, controlling the vehicle to change from the original driving lane to the target driving lane;
and if the type of the vehicle obstacle avoidance scene is a third vehicle obstacle avoidance scene, controlling the vehicle to decelerate and brake.
6. The vehicle obstacle avoidance method of claim 5, wherein the step of controlling the vehicle to change from the original driving lane to the target driving lane comprises:
collecting a lane image carrying target driving lane information;
determining target lane occupation information of the target driving lane according to the lane image;
and generating a planned route of the vehicle according to the target lane occupation information, and controlling the vehicle to change from the original driving lane to the target driving lane according to the planned route.
7. The vehicle obstacle avoidance method according to claim 1, wherein, when it is detected that a dangerous obstacle exists in a forward traveling area of the vehicle, obstacle information of the dangerous obstacle, vehicle information, road information in the forward traveling area, and lane occupancy information are acquired, wherein the road information includes lane line information, before the step of:
acquiring an area image of a forward traveling area of the vehicle, and determining a second distance between an obstacle and the vehicle according to the area image if the obstacle exists in the area image;
judging whether the second distance is smaller than or equal to a preset distance threshold value or not;
if yes, determining that a risk obstacle exists in a front travelling area of the vehicle;
if not, judging that no risk obstacle exists in the front travelling area of the vehicle, and returning to the execution step: acquiring a region image of a forward traveling region of the vehicle.
8. A vehicle obstacle avoidance device, characterized in that the vehicle obstacle avoidance device includes:
the system comprises an acquisition module, a judgment module and a display module, wherein the acquisition module is used for acquiring obstacle information, vehicle information, road information and lane occupation information of a risk obstacle when the risk obstacle exists in a front travelling area of a vehicle, and the road information comprises lane line information;
the selection module is used for identifying the type of a vehicle obstacle avoidance scene where the vehicle is located according to the obstacle information, the vehicle information, the road information and the lane occupation information;
and the control module is used for controlling the vehicle to avoid the obstacle according to an obstacle avoiding strategy determined by the vehicle obstacle avoiding scene type.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the vehicle obstacle avoidance method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a program for implementing a vehicle obstacle avoidance method, which is executed by a processor to implement the steps of the vehicle obstacle avoidance method according to any one of claims 1 to 7.
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| CN115798261A (en) * | 2022-11-22 | 2023-03-14 | 上海木蚁机器人科技有限公司 | Vehicle obstacle avoidance control method, device and equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115798261A (en) * | 2022-11-22 | 2023-03-14 | 上海木蚁机器人科技有限公司 | Vehicle obstacle avoidance control method, device and equipment |
| CN115798261B (en) * | 2022-11-22 | 2023-11-07 | 上海木蚁机器人科技有限公司 | Vehicle obstacle avoidance control method, device and equipment |
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