CN117944668A - Obstacle avoidance method and device for automatic driving vehicle - Google Patents
Obstacle avoidance method and device for automatic driving vehicle Download PDFInfo
- Publication number
- CN117944668A CN117944668A CN202211285714.2A CN202211285714A CN117944668A CN 117944668 A CN117944668 A CN 117944668A CN 202211285714 A CN202211285714 A CN 202211285714A CN 117944668 A CN117944668 A CN 117944668A
- Authority
- CN
- China
- Prior art keywords
- obstacle
- automatic driving
- distance
- driving vehicle
- autonomous vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 230000001133 acceleration Effects 0.000 claims description 66
- 230000035484 reaction time Effects 0.000 claims description 40
- 230000033001 locomotion Effects 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 description 17
- 230000015654 memory Effects 0.000 description 17
- 238000010586 diagram Methods 0.000 description 13
- 238000012545 processing Methods 0.000 description 12
- 230000002093 peripheral effect Effects 0.000 description 10
- 238000004891 communication Methods 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 230000003287 optical effect Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 239000000919 ceramic Substances 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000010409 thin film Substances 0.000 description 1
Abstract
The application discloses an obstacle avoidance method and device for an automatic driving vehicle, and belongs to the technical field of automatic driving. The method comprises the following steps: determining a road right result of the automatic driving vehicle aiming at an adjacent lane, calculating a safe distance between the automatic driving vehicle and an obstacle according to the road right result, wherein the obstacle and the automatic driving vehicle run according to a target direction, and the obstacle is positioned behind the automatic driving vehicle in the target direction; determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the safety distance and the actual distance, wherein the actual distance is the distance between the automatic driving vehicle and the obstacle; and controlling the automatic driving vehicle to carry out obstacle avoidance driving according to an obstacle avoidance mode. Compared with the obstacle avoidance mode of the automatic driving vehicle which is determined only according to the current speed of the obstacle, the safety distance between the automatic driving vehicle and the obstacle is calculated based on the road right result of the automatic driving vehicle for the adjacent lane, the obstacle avoidance mode is determined according to the safety distance, the probability of collision between the automatic driving vehicle and the obstacle can be reduced, and the safety is high.
Description
Technical Field
The embodiment of the application relates to the technical field of automatic driving, in particular to an obstacle avoidance method and device for an automatic driving vehicle.
Background
With the continuous development of automatic driving technology, automatic driving vehicles gradually enter the public view. One of the performances of the automatic driving vehicle is to avoid obstacles in time during the driving process, namely avoid the obstacles so as to avoid causing traffic accidents. Therefore, it is important how to control an autonomous vehicle to avoid an obstacle.
Disclosure of Invention
The embodiment of the application provides an obstacle avoidance method and device for an automatic driving vehicle, which can be used for controlling the automatic driving vehicle to avoid obstacle. The technical scheme is as follows:
In one aspect, an embodiment of the present application provides a method for avoiding an obstacle for an autonomous vehicle, the method including:
determining a road right result of an automatic driving vehicle aiming at an adjacent lane, and calculating a safety distance between the automatic driving vehicle and an obstacle according to the road right result, wherein the obstacle and the automatic driving vehicle run according to a target direction, and the obstacle is positioned behind the automatic driving vehicle in the target direction;
Determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the safety distance and an actual distance, wherein the actual distance is the distance between the automatic driving vehicle and the obstacle;
And controlling the automatic driving vehicle to perform obstacle avoidance driving according to the obstacle avoidance mode.
In one possible implementation manner, the determining the road right result of the automatic driving vehicle for the adjacent lane includes:
determining a proportion of the autonomous vehicle occupying an adjacent lane;
and determining a road right result of the automatic driving vehicle for the adjacent lane based on the ratio of the automatic driving vehicle to occupy the adjacent lane.
In one possible implementation manner, the calculating the safe distance between the autonomous vehicle and the obstacle according to the road right result includes:
Calculating a first distance between the autonomous vehicle and the obstacle according to a first parameter based on the road right result indicating that the autonomous vehicle has the road right of the adjacent lane;
The determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance comprises the following steps:
And determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
In one possible implementation manner, the calculating the safe distance between the autonomous vehicle and the obstacle according to the road right result includes:
calculating a second distance between the autonomous vehicle and the obstacle according to a second parameter based on the road right result indicating that the autonomous vehicle does not have the road right of the adjacent lane and the obstacle has the road right of the adjacent lane;
The determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance comprises the following steps:
and determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the second distance and the actual distance.
In one possible implementation manner, the calculating the safe distance between the autonomous vehicle and the obstacle according to the road right result includes:
Based on the road right result, indicating that the automatic driving vehicle does not have the road right of the adjacent lane and the obstacle does not have the road right of the adjacent lane, calculating a first distance between the automatic driving vehicle and the obstacle according to a first parameter;
The determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance comprises the following steps:
And determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
In one possible implementation manner, determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance includes:
determining that the obstacle avoidance mode of the automatic driving vehicle is to rob the obstacle based on the first distance being smaller than the actual distance;
And determining that the obstacle avoidance mode of the automatic driving vehicle is to yield the obstacle based on the fact that the first distance is larger than the actual distance.
In one possible implementation, the first parameter includes S 1,S2,S3, and the S 1 represents a distance traveled during the obstacle reaction time; the S 2 represents the distance travelled after the obstacle reaction time; the S 3 represents the distance travelled by the autonomous vehicle;
said calculating a first distance between said autonomous vehicle and said obstacle according to a first parameter comprises:
Calculating a first distance between the autonomous vehicle and the obstacle according to the following formula based on the S 1,S2,S3;
d＝S1+S2-S3
Wherein d represents the first distance.
In one possible implementation, the
Wherein v r represents the speed of the obstacle; a r represents the minimum acceleration in the acceleration value interval during the acceleration movement of the obstacle; and p represents the minimum reaction time in the obstacle reaction time value interval after the automatic driving vehicle brakes.
In one possible implementation, the
Wherein a r1 represents the maximum acceleration in the acceleration value interval when braking after the obstacle reaction time.
In one possible implementation, the
Wherein the v f represents the speed of the autonomous vehicle; and a f represents the minimum acceleration in the acceleration value interval when the automatic driving vehicle brakes.
In another aspect, there is provided an autonomous vehicle obstacle avoidance device, the device comprising:
The calculation module is used for determining a road right result of the automatic driving vehicle for an adjacent lane, calculating a safety distance between the automatic driving vehicle and an obstacle according to the road right result, wherein the obstacle and the automatic driving vehicle run according to a target direction, and the obstacle is positioned behind the automatic driving vehicle in the target direction;
The determining module is used for determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the safety distance and an actual distance, wherein the actual distance is the distance between the automatic driving vehicle and the obstacle;
and the control module is used for controlling the automatic driving vehicle to carry out obstacle avoidance driving according to the obstacle avoidance mode.
In one possible implementation, the calculation module is configured to determine a proportion of the adjacent lanes occupied by the autonomous vehicle;
and determining a road right result of the automatic driving vehicle for the adjacent lane based on the ratio of the automatic driving vehicle to occupy the adjacent lane.
In one possible implementation, the calculating module is configured to calculate a first distance between the autonomous vehicle and the obstacle according to a first parameter based on the road right result indicating that the autonomous vehicle has a road right of an adjacent lane;
And the determining module is used for determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
In one possible implementation, the calculating module is configured to calculate, based on the road right result, a second distance between the autonomous vehicle and the obstacle according to a second parameter, the autonomous vehicle not having the road right of the adjacent lane and the obstacle having the road right of the adjacent lane;
and the determining module is used for determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the second distance and the actual distance.
In one possible implementation, the calculating module is configured to calculate, according to a first parameter, a first distance between the autonomous vehicle and the obstacle based on the road right result indicating that the autonomous vehicle does not have the road right of the adjacent lane and that the obstacle does not have the road right of the adjacent lane;
And the determining module is used for determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
In a possible implementation manner, the determining module is configured to determine that the obstacle avoidance manner of the autonomous vehicle is to rob the obstacle based on the first distance being smaller than the actual distance;
And determining that the obstacle avoidance mode of the automatic driving vehicle is to yield the obstacle based on the fact that the first distance is larger than the actual distance.
In one possible implementation, the first parameter includes S 1,S2,S3, and the S 1 represents a distance traveled during the obstacle reaction time; the S 2 represents the distance travelled after the obstacle reaction time; the S 3 represents the distance travelled by the autonomous vehicle;
the calculation module is used for calculating a first distance between the automatic driving vehicle and the obstacle according to the following formula based on the S 1,S2,S3;
d＝S1+S2-S3
Wherein d represents the first distance.
In one possible implementation, the
Wherein v r represents the speed of the obstacle; a r represents the minimum acceleration in the acceleration value interval during the acceleration movement of the obstacle; and p represents the minimum reaction time in the obstacle reaction time value interval after the automatic driving vehicle brakes.
In one possible implementation, the
Wherein a r1 represents the maximum acceleration in the acceleration value interval when braking after the obstacle reaction time.
In one possible implementation, the
Wherein the v f represents the speed of the autonomous vehicle; and a f represents the minimum acceleration in the acceleration value interval when the automatic driving vehicle brakes.
In another aspect, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one computer program, the at least one computer program loaded and executed by the processor, to cause the computer device to implement any one of the above autonomous vehicle obstacle avoidance methods.
In another aspect, there is also provided a computer readable storage medium having at least one computer program stored therein, the at least one computer program being loaded and executed by a processor to cause the computer to implement any of the above-described autonomous vehicle obstacle avoidance methods.
In another aspect, a computer program product or computer program is provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions such that the computer device performs any of the autonomous vehicle obstacle avoidance methods described above.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
In the embodiment of the application, the safety distance between the automatic driving vehicle and the obstacle is calculated based on the road right result of the automatic driving vehicle for the adjacent lane, and the obstacle avoidance mode of the automatic driving vehicle is determined according to the comparison result of the safety distance and the actual distance. Compared with the method for determining the obstacle avoidance mode of the automatic driving vehicle only according to the current speed of the obstacle, the method can reduce the probability of collision between the automatic driving vehicle and the obstacle, and has higher safety.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic illustration of an implementation environment provided by an embodiment of the present application;
FIG. 2 is a flow chart of an autonomous vehicle obstacle avoidance method provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of an automatic driving vehicle road right situation provided by an embodiment of the present application;
FIG. 4 is a schematic diagram of an automatic driving vehicle road right situation provided by an embodiment of the present application;
FIG. 5 is a schematic illustration of an autonomous vehicle road right situation provided by an embodiment of the present application;
FIG. 6 is a logic judgment diagram of an obstacle avoidance method for an autonomous vehicle according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an obstacle avoidance device for an autonomous vehicle according to an embodiment of the present application;
Fig. 8 is a schematic structural diagram of a server according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of a terminal according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.
The embodiment of the application provides an obstacle avoidance method for an automatic driving vehicle, and please refer to fig. 1, which is a schematic diagram illustrating an implementation environment of the method provided by the embodiment of the application. The implementation environment may include: a terminal 11 and a server 12.
The terminal 11 is provided with an application program or a webpage capable of controlling the autonomous vehicle to avoid the obstacle, and when the application program or the webpage needs to control the autonomous vehicle to avoid the obstacle, the method provided by the embodiment of the application can be used for controlling. The server 12 may store speed information of the autonomous vehicle to be controlled to avoid the obstacle, and the terminal 11 may obtain the speed information of the autonomous vehicle to be controlled to avoid the obstacle from the server 12. Of course, the terminal 11 may store the acquired speed information.
Alternatively, the terminal 11 may be a smart device such as a cellular phone, tablet computer, personal computer, or the like. The server 12 may be a server, a server cluster comprising a plurality of servers, or a cloud computing service center. The terminal 11 establishes a communication connection with the server 12 through a wired or wireless network.
Alternatively, the terminal 11 may be any electronic product that can perform man-machine interaction with a user through one or more modes of a keyboard, a touch pad, a touch screen, a remote controller, a voice interaction or handwriting device, such as a PC (Personal Computer ), a mobile phone, a smart phone, a PDA (Personal DIGITAL ASSISTANT, a Personal digital assistant), a wearable device, a PPC (Pocket PC), a tablet computer, a smart car machine, a smart television, a smart speaker, etc. The server 12 may be a server, a server cluster comprising a plurality of servers, or a cloud computing service center. The terminal 11 establishes a communication connection with the server 12 through a wired or wireless network.
Those skilled in the art will appreciate that the above-described terminal 11 and server 12 are only examples, and that other terminals or servers that may be present in the present application or in the future are applicable and within the scope of the present application and are incorporated herein by reference.
The embodiment of the application provides an obstacle avoidance method for an automatic driving vehicle, which can be applied to the implementation environment shown in the figure 1. As shown in fig. 2, taking the application of the method to a terminal as an example, the method includes steps 201-203.
In step 201, a road right result of the autonomous vehicle for the adjacent lane is determined, a safe distance between the autonomous vehicle and an obstacle is calculated according to the road right result, the obstacle and the autonomous vehicle travel in a target direction, and the obstacle is located behind the autonomous vehicle in the target direction.
In an exemplary embodiment, before determining the road right result of the autonomous vehicle for the adjacent lane, it is determined whether the current scene of the autonomous vehicle is an obstacle avoidance scene. For example, if the autonomous vehicle travels in a target direction (e.g., the autonomous vehicle travels from east to west, then the target direction is west), and there is an obstacle in the forward region of the autonomous vehicle in the target direction, then the current scene may be determined to be an obstacle avoidance scene. The embodiment of the application does not limit the type of the obstacle, for example, the obstacle may be a running vehicle or a pedestrian. The range size of the area in front of the autonomous vehicle may be empirically set or determined from input information. For example, the area in front of the autonomous vehicle may be an area within 30 meters in front of the autonomous vehicle, or may be a semicircular area in front of the autonomous vehicle with a radius of 30 meters around the autonomous vehicle.
The embodiment of the present application also does not limit the method of determining the obstacle in the area in front of the autonomous vehicle, and it is possible to determine whether the obstacle exists in the area by radar-emitting laser scanning, for example. The radar may be mounted on the roof of the autonomous vehicle, or may be mounted in front of or behind the autonomous vehicle, for example, and the mounting position of the radar is not limited by the embodiment of the present application. After the radar finishes scanning the area in front of the automatic driving vehicle, the scanning result is uploaded to the terminal, and the terminal can determine whether the current scene is an obstacle avoidance scene according to the scanning result.
Based on the fact that the current scene of the automatic driving vehicle is an obstacle avoidance scene, the road right result of the automatic driving vehicle for the adjacent lanes needs to be further determined. In one possible implementation, determining a road right result of an autonomous vehicle for an adjacent lane includes: determining a proportion of the autonomous vehicle occupying an adjacent lane; and determining the road right result of the automatic driving vehicle for the adjacent lane based on the proportion of the automatic driving vehicle occupying the adjacent lane.
For example, if the proportion of the autonomous vehicle occupying the adjacent lane is greater than a threshold, determining that the autonomous vehicle has the road right of the adjacent lane; similarly, if the proportion of the automatic driving vehicle occupying the adjacent lane is smaller than the threshold value, determining that the automatic driving vehicle does not have the road right of the adjacent lane. The threshold value range may be set empirically, or may be set based on a scene. For example, the value range of the threshold may be 0-1, and the size of the threshold is not limited in the embodiment of the present application, so long as the threshold is within the value range. For example, the threshold may be 1/2 or 1/3, and taking a threshold size of 1/2 as an example, when the ratio of the autonomous vehicle occupying the adjacent lane is greater than 1/2, it may be determined that the autonomous vehicle has the right of way of the adjacent road.
After the road right result of the automatic driving vehicle for the adjacent lane is determined, the safety distance between the automatic driving vehicle and the obstacle is calculated according to the road right result. In one possible implementation, calculating a safe distance between the autonomous vehicle and the obstacle according to the road right result includes: the method includes calculating a first distance between the autonomous vehicle and the obstacle according to a first parameter based on a road right result indicating that the autonomous vehicle has a road right of an adjacent lane.
Illustratively, a case where the road right result indicates that the autonomous vehicle has the road right of the adjacent lane can be seen in fig. 3 as follows. Fig. 3 is a schematic diagram of an autonomous vehicle road right situation. In fig. 3, 301 is an obstacle 1 located in front of an autonomous vehicle in a target direction; 302 is an autonomous vehicle; reference numeral 303 denotes an obstacle 2 located behind the autonomous vehicle in the target direction. As can be seen from fig. 3, the autonomous vehicle and the obstacle 2 travel in the same direction, and the autonomous vehicle has the right of way of the adjacent lane, and the obstacle 2 has no right of way of the adjacent lane. Further, fig. 3 only shows one possible case where the autonomous vehicle has the adjacent road right, and does not constitute an overall definition of the right where the autonomous vehicle has the adjacent lane, that is, as long as the autonomous vehicle has the adjacent lane right, whether or not the obstacle behind the autonomous vehicle has the adjacent lane right, at this time, the autonomous vehicle may be instructed to have the right of the adjacent lane based on the right result, and the first distance between the autonomous vehicle and the obstacle may be calculated according to the first parameter. Optionally, the first distance is a safe distance. The safety distance meets the requirements of emergency braking of the automatic driving vehicle, and the obstacle behind the automatic driving vehicle accelerates in the reaction time and decelerates after the reaction time by a distance which is just not collided.
In one possible implementation, the first parameter includes S 1,S2,S3,S1 representing a distance travelled within the obstacle reaction time; s 2 represents the distance travelled after the obstacle reaction time; s 3 represents the distance travelled by the autonomous vehicle; calculating a first distance between the autonomous vehicle and the obstacle according to a first parameter, comprising: calculating a first distance between the autonomous vehicle and the obstacle according to the following formula based on S 1,S2,S3;
d＝S1+S2-S3
Wherein d represents the first distance.
In one possible implementation of the present invention,Wherein v r represents the speed of the obstacle; a r represents the minimum acceleration in the acceleration value interval during the acceleration movement of the obstacle; p represents the minimum reaction time in the obstacle reaction time value interval after the automatic driving vehicle brakes.
In one possible implementation of the present invention,Wherein a r1 represents the maximum acceleration in the acceleration value interval when braking after the obstacle reaction time.
In one possible implementation of the present invention,Where v f denotes the speed of the autonomous vehicle; a f represents the minimum acceleration in the acceleration take-off interval when the autonomous vehicle is braked.
In the embodiment of the application, the first distance is the distance that the automatic driving vehicle does not collide with the obstacle after the automatic driving vehicle suddenly brakes with the minimum acceleration and the obstacle does accelerated motion with the maximum acceleration in the shortest reaction time and brakes with the minimum acceleration after the reaction time.
The embodiment of the application does not limit the acceleration value interval during the acceleration movement of the obstacle, the reaction time value interval of the obstacle, the acceleration value interval during the braking after the reaction time of the obstacle and the acceleration value interval during the braking of the automatic driving vehicle, wherein the value intervals can be set according to experience and can be flexibly adjusted according to application scenes, and the acceleration value interval during the acceleration movement of the obstacle can be 1-1.5m/s 2.
In one possible implementation, calculating a safe distance between the autonomous vehicle and the obstacle according to the road right result includes: and indicating that the automatic driving vehicle does not have the road right of the adjacent lane based on the road right result, and calculating a second distance between the automatic driving vehicle and the obstacle according to a second parameter, wherein the obstacle has the road right of the adjacent lane.
Illustratively, the case where the road right result indicates that the autonomous vehicle does not have the road right of the adjacent lane, and the obstacle has the road right of the adjacent lane can be seen as follows fig. 4, fig. 4 being a schematic diagram of a case of the road right of the autonomous vehicle. In fig. 4, 401 is an obstacle 1 located in front of an autonomous vehicle in a target direction; 402 is an autonomous vehicle; reference numeral 403 denotes an obstacle 2 located behind the autonomous vehicle in the target direction. As can be seen from fig. 4, the autonomous vehicle and the obstacle 2 travel in the same direction, and the autonomous vehicle does not have the right of way of the adjacent lane, and the obstacle 2 has the right of way of the adjacent lane. At this time, a second distance between the autonomous vehicle and the obstacle may be calculated in accordance with the second parameter.
In one possible implementation, the second parameter includes S 1′,S2′,S3′;S1' representing a distance travelled within the obstacle reaction time; s 2' represents the distance travelled after the obstacle reaction time; s 3' represents the distance travelled by the autonomous vehicle; calculating a second distance between the autonomous vehicle and the obstacle according to a second parameter, comprising: calculating a second distance between the autonomous vehicle and the obstacle according to the following formula based on S 1′,S2′,S3';
d′＝S1′+S2′-S3′
Wherein d' represents the second distance.
In one possible implementation of the present invention,Wherein a r′ represents the maximum acceleration in the acceleration value interval when the obstacle accelerates; p' represents the maximum reaction time in the range of obstacle reaction time values after braking of the autonomous vehicle.
In one possible implementation of the present invention,Wherein a r1′ represents the minimum acceleration in the acceleration value interval when braking after the obstacle reaction time.
In one possible implementation of the present invention,Wherein a f' represents the maximum acceleration in the acceleration value interval when the automatic driving vehicle brakes.
In the embodiment of the application, the second distance is the distance that the automatic driving vehicle does not collide with the obstacle after the automatic driving vehicle is braked at the maximum acceleration and the obstacle does acceleration motion at the maximum acceleration in the longest reaction time and the maximum acceleration is used for braking after the reaction time.
In one possible implementation, calculating a safe distance between the autonomous vehicle and the obstacle according to the road right result includes: and based on the road right result, indicating that the automatic driving vehicle does not have the road right of the adjacent lane and the obstacle does not have the road right of the adjacent lane, and calculating a first distance between the automatic driving vehicle and the obstacle according to the first parameter.
Illustratively, a case where the road right result indicates that the autonomous vehicle does not have the road right of the adjacent lane, and the obstacle does not have the road right of the adjacent lane can be seen in fig. 5 as follows. Fig. 5 is a schematic diagram of an autonomous vehicle road right situation. In fig. 5, 501 is an obstacle 1 located in front of an autonomous vehicle in a target direction; 502 is an autonomous vehicle; reference numeral 503 denotes an obstacle 2 located behind the autonomous vehicle in the target direction. As can be seen from fig. 5, the autonomous vehicle and the obstacle 2 travel in the same direction, and the autonomous vehicle does not have the right of way of the adjacent lane, nor does the obstacle 2 have the right of way of the adjacent lane. At this time, a first distance between the autonomous vehicle and the obstacle may be calculated according to the first parameter. The calculation method of the first distance is described in detail above, and will not be described herein.
In step 202, an obstacle avoidance mode of the autonomous vehicle is determined according to a comparison result of the safe distance and the actual distance, where the actual distance is a distance between the autonomous vehicle and the obstacle.
After the safe distance between the automatic driving vehicle and the obstacle is calculated according to the road right result of the automatic driving vehicle for the adjacent lanes, the safe distance and the actual distance can be compared, and the obstacle avoidance mode of the automatic driving vehicle is determined according to the comparison result. If the safety distance is smaller than the actual distance, determining that the obstacle avoidance mode of the automatic driving vehicle is a robbery obstacle; if the safety distance is greater than the actual distance, the obstacle avoidance mode of the automatic driving vehicle can be determined to be an obstacle avoidance mode. The embodiment of the application does not limit the measurement mode of the actual distance between the autonomous vehicle and the obstacle, and the current actual distance between the autonomous vehicle and the obstacle can be obtained by radar scanning behind the autonomous vehicle, for example.
Illustratively, according to the teachings of step 201, when the road right result indicates that the autonomous vehicle has adjacent lane road rights, a first distance between the autonomous vehicle and the obstacle is calculated according to a first parameter. At this time, in one possible implementation manner, determining the obstacle avoidance manner of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance includes: and determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
Determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the first distance and the actual distance, wherein the obstacle avoidance mode comprises the following steps: based on the fact that the first distance is smaller than the actual distance, determining that an obstacle avoidance mode of the automatic driving vehicle is a robbery obstacle; and determining that the obstacle avoidance mode of the automatic driving vehicle is an obstacle avoidance mode based on the fact that the first distance is larger than the actual distance.
For example, when the road right result indicates that the autonomous vehicle does not have road right of an adjacent lane and the obstacle has road right of an adjacent lane, a second distance between the autonomous vehicle and the obstacle is calculated according to the second parameter. At this time, in one possible implementation manner, determining the obstacle avoidance manner of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance includes: and determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the second distance and the actual distance.
Determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the second distance and the actual distance, wherein the obstacle avoidance mode comprises the following steps: determining that the obstacle avoidance mode of the automatic driving vehicle is a robbery obstacle based on the fact that the second distance is smaller than the actual distance; and determining that the obstacle avoidance mode of the automatic driving vehicle is an obstacle avoidance mode based on the fact that the second distance is larger than the actual distance.
For example, when the road right result indicates that the autonomous vehicle does not have road rights for an adjacent lane and the obstacle does not have road rights for an adjacent lane, a first distance between the autonomous vehicle and the obstacle is calculated according to the first parameter. At this time, the possible implementation manner of determining the obstacle avoidance manner of the automatic driving vehicle according to the comparison result between the safe distance and the actual distance is described in detail above, and will not be described herein.
In step 203, the autonomous vehicle is controlled to perform obstacle avoidance driving according to the obstacle avoidance mode.
According to the content in step 202, after the obstacle avoidance mode of the automatic driving vehicle is determined according to the comparison result of the safety distance and the actual distance, the automatic driving vehicle can be controlled to perform obstacle avoidance driving according to the determined obstacle avoidance mode.
Fig. 6 is a logic judgment diagram of an obstacle avoidance method for an automatic driving vehicle, in fig. 6, step 601 is scene recognition, according to step 602, it is determined whether the current scene of the automatic driving vehicle is an obstacle avoidance scene, if the current scene is an obstacle avoidance scene, step 604 is executed, the feasibility of overtaking is calculated, if the current scene is not an obstacle avoidance scene, step 603 is executed, and the scene recognition process is exited. After calculating the possibility of overtaking, step 605 is executed, i.e. it is determined whether the autonomous vehicle can pass preferentially, if yes, step 606 is executed to make overtaking decisions, and step 608 is executed to transfer the result to the longitudinal decisions to control the obstacle avoidance mode of the autonomous vehicle, if no, step 607 is executed, the autonomous vehicle needs to give way to the obstacle, and step 608 is also executed to transfer the result to the longitudinal decisions to control the autonomous vehicle.
Before calculating the overtaking feasibility of the automatic driving vehicle, the road right is determined, that is, step 6041 is executed to determine whether the automatic driving vehicle has the road right of the adjacent lane. If the autonomous vehicle has road rights for adjacent lanes, step 6042 may be performed to aggressive calculate the feasibility of the overtaking; if the autonomous vehicle does not have the right of the adjacent lane, step 6043 is executed to determine whether the obstacle has the right of the adjacent lane. If the autonomous vehicle does not have the right of the adjacent lane and the obstacle does not have the right of the adjacent lane, step 6042 is still executed, and the overtaking feasibility is calculated in an aggressive manner; if the autonomous vehicle does not have access to the adjacent lane, the obstacle has access to the adjacent lane, step 6044 is performed to conservatively calculate the feasibility of the cut-in. The calculation of the overtaking feasibility is to calculate the safe distance between the autonomous vehicle and the obstacle, so that the aforementioned aggressive calculation of the overtaking feasibility corresponds to the first distance and, similarly, the conservative calculation of the overtaking feasibility corresponds to the second distance.
Thus, when step 6045 is performed and the safe distance is calculated, step 6046 is performed, i.e. different parameters are used for aggressive and conservative. The specific implementation of this step is already described in detail above, and will not be described here again. After calculating the safe distance between the automatically driven vehicle and the obstacle according to the aggressive mode or the conservative mode, executing step 6047, comparing whether the safe distance is larger than the actual distance, if so, executing step 6048, and performing unsafe overtaking to give way; if not, then step 6049 is performed, and the vehicle can be safely overtaken and robbed.
In the embodiment of the application, the safety distance between the automatic driving vehicle and the obstacle is calculated based on the road right result of the automatic driving vehicle for the adjacent lane, and the obstacle avoidance mode of the automatic driving vehicle is determined according to the comparison result of the safety distance and the actual distance. Compared with the method for determining the obstacle avoidance mode of the automatic driving vehicle only according to the current speed of the obstacle, the method can reduce the probability of collision between the automatic driving vehicle and the obstacle, and has higher safety.
Referring to fig. 7, an embodiment of the present application provides an obstacle avoidance apparatus for an autonomous vehicle, the apparatus comprising:
A calculation module 701, configured to determine a road right result of the autonomous vehicle for an adjacent lane, calculate a safe distance between the autonomous vehicle and an obstacle according to the road right result, wherein the obstacle and the autonomous vehicle travel in a target direction, and the obstacle is located behind the autonomous vehicle in the target direction;
The determining module 702 is configured to determine an obstacle avoidance mode of the autonomous vehicle according to a comparison result of the safety distance and an actual distance, where the actual distance is a distance between the autonomous vehicle and an obstacle;
the control module 703 is used for controlling the autonomous vehicle to perform obstacle avoidance driving according to an obstacle avoidance mode.
In one possible implementation, the calculating module 701 is configured to determine a proportion of the adjacent lanes occupied by the autonomous vehicle;
And determining the road right result of the automatic driving vehicle for the adjacent lane based on the proportion of the automatic driving vehicle occupying the adjacent lane.
In one possible implementation, the calculating module 701 is configured to calculate, according to a first parameter, a first distance between the autonomous vehicle and the obstacle based on the road right result indicating that the autonomous vehicle has a road right of an adjacent lane;
the determining module 702 is configured to determine an obstacle avoidance mode of the autonomous vehicle according to a comparison result of the first distance and the actual distance.
In a possible implementation manner, the calculating module 701 is configured to calculate, according to the second parameter, a second distance between the autonomous vehicle and the obstacle, based on the road right result indicating that the autonomous vehicle does not have the road right of the adjacent lane and the obstacle has the road right of the adjacent lane;
the determining module 702 is configured to determine an obstacle avoidance mode of the autonomous vehicle according to a comparison result of the second distance and the actual distance.
In one possible implementation, the calculating module 701 is configured to calculate, according to the first parameter, a first distance between the autonomous vehicle and the obstacle, based on the road right result indicating that the autonomous vehicle does not have the road right of the adjacent lane and the obstacle does not have the road right of the adjacent lane;
the determining module 702 is configured to determine an obstacle avoidance mode of the autonomous vehicle according to a comparison result of the first distance and the actual distance.
In one possible implementation, the determining module 702 is configured to determine that the obstacle avoidance mode of the autonomous vehicle is a robbery obstacle based on the first distance being less than the actual distance;
and determining that the obstacle avoidance mode of the automatic driving vehicle is an obstacle avoidance mode based on the fact that the first distance is larger than the actual distance.
In one possible implementation, the first parameter includes S 1,S2,S3,S1 representing a distance travelled within the obstacle reaction time; s 2 represents the distance travelled after the obstacle reaction time; s 3 represents the distance travelled by the autonomous vehicle;
A calculating module 701, configured to calculate a first distance between the autonomous vehicle and the obstacle according to the following formula based on S 1,S2,S3;
d＝S1+S2-S3
Wherein d represents the first distance.
In one possible implementation of the present invention,
Wherein v r represents the speed of the obstacle; a r represents the minimum acceleration in the acceleration value interval during the acceleration movement of the obstacle; p represents the minimum reaction time in the obstacle reaction time value interval after the automatic driving vehicle brakes.
In one possible implementation of the present invention,
Wherein a r1 represents the maximum acceleration in the acceleration value interval when braking after the obstacle reaction time.
In one possible implementation of the present invention,
Where v f denotes the speed of the autonomous vehicle; a f represents the minimum acceleration in the acceleration take-off interval when the autonomous vehicle is braked.
In the embodiment of the application, the safety distance between the automatic driving vehicle and the obstacle is calculated based on the road right result of the automatic driving vehicle for the adjacent lane, and the obstacle avoidance mode of the automatic driving vehicle is determined according to the comparison result of the safety distance and the actual distance. Compared with a device for determining the obstacle avoidance mode of the automatic driving vehicle according to the current speed of the obstacle, the device can reduce the collision probability of the automatic driving vehicle and the obstacle, and has higher safety.
It should be noted that, when the apparatus provided in the foregoing embodiment performs the functions thereof, only the division of the foregoing functional modules is used as an example, in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the apparatus and the method embodiments provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the apparatus and the method embodiments are detailed in the method embodiments and are not repeated herein.
Fig. 8 is a schematic structural diagram of a server according to an embodiment of the present application, where the server may include one or more processors 801 and one or more memories 802, where the processor 801 may be a central processing unit (Central Processing Units, CPU), and the one or more memories 802 store at least one computer program, and the at least one computer program is loaded and executed by the one or more processors 801, so that the server implements the autonomous vehicle obstacle avoidance method provided by the foregoing method embodiments. Of course, the server may also have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing the functions of the device, which are not described herein.
Fig. 9 is a schematic structural diagram of a terminal according to an embodiment of the present application. The terminal may be: smart phones, tablet computers, notebook computers or desktop computers. Terminals may also be referred to by other names as user equipment, portable terminals, laptop terminals, desktop terminals, etc.
Generally, the terminal includes: a processor 1501 and a memory 1502.
The processor 1501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, or the like. The processor 1501 may be implemented in at least one hardware form of DSP (DIGITAL SIGNAL Processing), FPGA (Field-Programmable gate array), PLA (Programmable Logic Array ). The processor 1501 may also include a main processor, which is a processor for processing data in an awake state, also called a CPU (Central Processing Unit ), and a coprocessor; a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 1501 may be integrated with a GPU (Graphics Processing Unit, image processor) for rendering and drawing of content to be displayed by the display screen. In some embodiments, the processor 1501 may also include an AI (ARTIFICIAL INTELLIGENCE ) processor for processing computing operations related to machine learning.
Memory 1502 may include one or more computer-readable storage media, which may be non-transitory. Memory 1502 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 1502 is configured to store at least one instruction for execution by processor 1501 to cause the terminal to implement the autonomous vehicle obstacle avoidance method provided by the method embodiments of the present application.
In some embodiments, the terminal may further optionally include: a peripheral interface 1503 and at least one peripheral device. The processor 1501, memory 1502 and peripheral interface 1503 may be connected by a bus or signal lines. The individual peripheral devices may be connected to the peripheral device interface 1503 via a bus, signal lines, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 1504, a display screen 1505, a camera assembly 1506, audio circuitry 1507, a positioning assembly 1508, and a power supply 1509.
A peripheral interface 1503 may be used to connect I/O (Input/Output) related at least one peripheral device to the processor 1501 and the memory 1502. In some embodiments, processor 1501, memory 1502, and peripheral interface 1503 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 1501, the memory 1502, and the peripheral interface 1503 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.
The Radio Frequency circuit 1504 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1504 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 1504 converts electrical signals to electromagnetic signals for transmission, or converts received electromagnetic signals to electrical signals. Optionally, the radio frequency circuit 1504 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuit 1504 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (WIRELESS FIDELITY ) networks. In some embodiments, the radio frequency circuit 1504 may further include NFC (NEAR FIELD Communication) related circuits, which is not limited by the present application.
Display 1505 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When display screen 1505 is a touch display screen, display screen 1505 also has the ability to collect touch signals at or above the surface of display screen 1505. The touch signal may be input to the processor 1501 as a control signal for processing. At this point, display 1505 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 1505 may be one, disposed on the front panel of the terminal; in other embodiments, the display 1505 may be at least two, respectively disposed on different surfaces of the terminal or in a folded design; in other embodiments, the display 1505 may be a flexible display disposed on a curved surface or a folded surface of the terminal. Even more, the display 1505 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The display screen 1505 may be made of materials such as an LCD (Liquid CRYSTAL DISPLAY) and an OLED (Organic Light-Emitting Diode).
The camera assembly 1506 is used to capture images or video. Optionally, the camera assembly 1506 includes a front camera and a rear camera. Typically, the front camera is disposed on the front panel of the terminal and the rear camera is disposed on the rear surface of the terminal. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize that the main camera and the depth camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 1506 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.
The audio circuitry 1507 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and the environment, converting the sound waves into electric signals, inputting the electric signals to the processor 1501 for processing, or inputting the electric signals to the radio frequency circuit 1504 for voice communication. For the purpose of stereo acquisition or noise reduction, a plurality of microphones can be respectively arranged at different parts of the terminal. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 1501 or the radio frequency circuit 1504 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, the audio circuit 1507 may also include a headphone jack.
The positioning component 1508 is for positioning a current geographic location of a terminal to enable navigation or LBS (Location Based Service, location-based services).
The power supply 1509 is used to power the various components in the terminal. The power supply 1509 may be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 1509 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.
In some embodiments, the terminal further includes one or more sensors 1510. The one or more sensors 1510 include, but are not limited to: acceleration sensor 1511, gyroscope sensor 1512, pressure sensor 1513, fingerprint sensor 1514, optical sensor 1515, and proximity sensor 1516.
The acceleration sensor 1511 can detect the magnitudes of accelerations on three coordinate axes of a coordinate system established with a terminal. For example, the acceleration sensor 1511 may be used to detect components of gravitational acceleration in three coordinate axes. The processor 1501 may control the display screen 1505 to display the user interface in a landscape view or a portrait view based on the gravitational acceleration signal acquired by the acceleration sensor 1511. The acceleration sensor 1511 may also be used for the acquisition of motion data of a game or user.
The gyro sensor 1512 may detect a body direction and a rotation angle of the terminal, and the gyro sensor 1512 may collect a 3D motion of the user on the terminal in cooperation with the acceleration sensor 1511. The processor 1501, based on the data collected by the gyro sensor 1512, may implement the following functions: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, game control, and inertial navigation.
The pressure sensor 1513 may be disposed on a side frame of the terminal and/or below the display 1505. When the pressure sensor 1513 is disposed on the side frame of the terminal, a grip signal of the terminal by the user can be detected, and the processor 1501 performs left-right hand recognition or quick operation according to the grip signal collected by the pressure sensor 1513. When the pressure sensor 1513 is disposed at the lower layer of the display screen 1505, the processor 1501 realizes control of the operability control on the UI interface according to the pressure operation of the user on the display screen 1505. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.
The fingerprint sensor 1514 is used to collect a fingerprint of a user, and the processor 1501 identifies the identity of the user based on the fingerprint collected by the fingerprint sensor 1514, or the fingerprint sensor 1514 identifies the identity of the user based on the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the processor 1501 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 1514 may be provided on the front, back or side of the terminal. When a physical key or a vendor Logo (trademark) is provided on the terminal, the fingerprint sensor 1514 may be integrated with the physical key or vendor Logo.
The optical sensor 1515 is used to collect the ambient light intensity. In one embodiment, processor 1501 may control the display brightness of display screen 1505 based on the intensity of ambient light collected by optical sensor 1515. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1505 is turned up; when the ambient light intensity is low, the display luminance of the display screen 1505 is turned down. In another embodiment, the processor 1501 may also dynamically adjust the shooting parameters of the camera assembly 1506 based on the ambient light intensity collected by the optical sensor 1515.
A proximity sensor 1516, also referred to as a distance sensor, is typically provided on the front panel of the terminal. The proximity sensor 1516 is used to collect the distance between the user and the front face of the terminal. In one embodiment, when the proximity sensor 1516 detects a gradual decrease in the distance between the user and the front face of the terminal, the processor 1501 controls the display 1505 to switch from the on-screen state to the off-screen state; when the proximity sensor 1516 detects that the distance between the user and the front face of the terminal gradually increases, the processor 1501 controls the display screen 1505 to switch from the off-screen state to the on-screen state.
It will be appreciated by those skilled in the art that the structure shown in fig. 9 is not limiting of the terminal and may include more or fewer components than shown, or may combine certain components, or may employ a different arrangement of components.
In an exemplary embodiment, a computer device is also provided, the computer device comprising a processor and a memory, the memory having at least one computer program stored therein. The at least one computer program is loaded and executed by one or more processors to cause the computer apparatus to implement any of the autonomous vehicle obstacle avoidance methods described above.
In an exemplary embodiment, there is also provided a computer-readable storage medium having stored therein at least one computer program loaded and executed by a processor of a computer device to cause the computer to implement any of the above-described autonomous vehicle obstacle avoidance methods.
In one possible implementation, the computer readable storage medium may be a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a CD-ROM (Compact Disc Read-Only Memory), a magnetic tape, a floppy disk, an optical data storage device, and so on.
In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium and the processor executes the computer instructions to cause the computer device to perform any of the autonomous vehicle obstacle avoidance methods described above.
It should be noted that, the information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data for analysis, stored data, presented data, etc.), and signals related to the present application are all authorized by the user or are fully authorized by the parties, and the collection, use, and processing of the related data is required to comply with the relevant laws and regulations and standards of the relevant countries and regions. For example, the first distance and the like involved in the present application are all acquired under a sufficient authorization.
It should be understood that references herein to "a plurality" are to two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
It should be noted that the terms "first," "second," and the like in the description and in the claims, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the above exemplary embodiments do not represent all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
The above embodiments are merely exemplary embodiments of the present application and are not intended to limit the present application, any modifications, equivalent substitutions, improvements, etc. that fall within the principles of the present application should be included in the scope of the present application.
Claims (10)
1. A method of obstacle avoidance for an autonomous vehicle, the method comprising:
determining a road right result of an automatic driving vehicle aiming at an adjacent lane, and calculating a safety distance between the automatic driving vehicle and an obstacle according to the road right result, wherein the obstacle and the automatic driving vehicle run according to a target direction, and the obstacle is positioned behind the automatic driving vehicle in the target direction;
Determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the safety distance and an actual distance, wherein the actual distance is the distance between the automatic driving vehicle and the obstacle;
And controlling the automatic driving vehicle to perform obstacle avoidance driving according to the obstacle avoidance mode.
2. The method of claim 1, wherein the determining the road right result of the autonomous vehicle for the adjacent lane comprises:
determining a proportion of the autonomous vehicle occupying an adjacent lane;
and determining a road right result of the automatic driving vehicle for the adjacent lane based on the ratio of the automatic driving vehicle to occupy the adjacent lane.
3. The method according to claim 1 or 2, wherein said calculating a safe distance between the autonomous vehicle and an obstacle from the road right result comprises:
Calculating a first distance between the autonomous vehicle and the obstacle according to a first parameter based on the road right result indicating that the autonomous vehicle has the road right of the adjacent lane;
The determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance comprises the following steps:
And determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
4. The method according to claim 1 or 2, wherein said calculating a safe distance between the autonomous vehicle and an obstacle from the road right result comprises:
calculating a second distance between the autonomous vehicle and the obstacle according to a second parameter based on the road right result indicating that the autonomous vehicle does not have the road right of the adjacent lane and the obstacle has the road right of the adjacent lane;
The determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance comprises the following steps:
and determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the second distance and the actual distance.
5. The method according to claim 1 or 2, wherein said calculating a safe distance between the autonomous vehicle and an obstacle from the road right result comprises:
Based on the road right result, indicating that the automatic driving vehicle does not have the road right of the adjacent lane and the obstacle does not have the road right of the adjacent lane, calculating a first distance between the automatic driving vehicle and the obstacle according to a first parameter;
The determining the obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the safe distance and the actual distance comprises the following steps:
And determining an obstacle avoidance mode of the automatic driving vehicle according to the comparison result of the first distance and the actual distance.
6. A method according to claim 3, wherein said determining the obstacle avoidance mode of the autonomous vehicle based on the comparison of the first distance and the actual distance comprises:
determining that the obstacle avoidance mode of the automatic driving vehicle is to rob the obstacle based on the first distance being smaller than the actual distance;
And determining that the obstacle avoidance mode of the automatic driving vehicle is to yield the obstacle based on the fact that the first distance is larger than the actual distance.
7. A method according to claim 3, wherein the first parameter comprises S 1,S2,S3, the S 1 representing the distance travelled during the obstacle reaction time; the S 2 represents the distance travelled after the obstacle reaction time; the S 3 represents the distance travelled by the autonomous vehicle;
said calculating a first distance between said autonomous vehicle and said obstacle according to a first parameter comprises:
Calculating a first distance between the autonomous vehicle and the obstacle according to the following formula based on the S 1,S2,S3;
d＝S1+S2-S3
Wherein d represents the first distance.
8. The method of claim 7, wherein the
Wherein v r represents the speed of the obstacle; a r represents the minimum acceleration in the acceleration value interval during the acceleration movement of the obstacle; and p represents the minimum reaction time in the obstacle reaction time value interval after the automatic driving vehicle brakes.
9. The method of claim 7, wherein theSaid/>
Wherein v r represents the speed of the obstacle; a r represents the minimum acceleration in the acceleration value interval during the acceleration movement of the obstacle; p represents the minimum reaction time in the obstacle reaction time value interval after the automatic driving vehicle brakes; a r1 represents the maximum acceleration in the acceleration value interval when the brake is performed after the obstacle reaction time; the v f represents the speed of the autonomous vehicle; and a f represents the minimum acceleration in the acceleration value interval when the automatic driving vehicle brakes.
10. An autonomous vehicle obstacle avoidance device, the device comprising:
The calculation module is used for determining a road right result of the automatic driving vehicle for an adjacent lane, calculating a safety distance between the automatic driving vehicle and an obstacle according to the road right result, wherein the obstacle and the automatic driving vehicle run according to a target direction, and the obstacle is positioned behind the automatic driving vehicle in the target direction;
The determining module is used for determining an obstacle avoidance mode of the automatic driving vehicle according to a comparison result of the safety distance and an actual distance, wherein the actual distance is the distance between the automatic driving vehicle and the obstacle;
and the control module is used for controlling the automatic driving vehicle to carry out obstacle avoidance driving according to the obstacle avoidance mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211285714.2A CN117944668A (en) | 2022-10-20 | 2022-10-20 | Obstacle avoidance method and device for automatic driving vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211285714.2A CN117944668A (en) | 2022-10-20 | 2022-10-20 | Obstacle avoidance method and device for automatic driving vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117944668A true CN117944668A (en) | 2024-04-30 |
Family
ID=90796728
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211285714.2A Pending CN117944668A (en) | 2022-10-20 | 2022-10-20 | Obstacle avoidance method and device for automatic driving vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117944668A (en) |
-
2022
- 2022-10-20 CN CN202211285714.2A patent/CN117944668A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110243386B (en) | Navigation information display method, device, terminal and storage medium | |
| CN110884500A (en) | Method and device for controlling vehicle, electronic equipment and storage medium | |
| EP3919337B1 (en) | Control vehicle | |
| CN111010537B (en) | Vehicle control method, device, terminal and storage medium | |
| CN116853240A (en) | Barrier early warning method, device, equipment and storage medium | |
| CN109189068B (en) | Parking control method and device and storage medium | |
| CN114789734A (en) | Perception information compensation method, device, vehicle, storage medium, and program | |
| CN117944668A (en) | Obstacle avoidance method and device for automatic driving vehicle | |
| CN113734167B (en) | Vehicle control method, device, terminal and storage medium | |
| CN111984755A (en) | Method and device for determining target parking point, electronic equipment and storage medium | |
| CN113734199B (en) | Vehicle control method, device, terminal and storage medium | |
| CN114419913B (en) | In-vehicle reminding method and device, vehicle and storage medium | |
| CN114566064B (en) | Method, device, equipment and storage medium for determining position of parking space | |
| CN114506383B (en) | Steering wheel alignment control method, device, terminal, storage medium and product | |
| CN116311976A (en) | Signal lamp control method, device, equipment and computer readable storage medium | |
| CN113361035B (en) | Four-wheel steering system simulation method and device and computer storage medium | |
| CN111294513B (en) | Photographing method and device, electronic equipment and storage medium | |
| CN115534991A (en) | Vehicle warning method, device, equipment and storage medium | |
| CN117227747A (en) | Method, device, equipment and storage medium for detecting autopilot capability | |
| CN117911482A (en) | Image processing method and device | |
| CN116452653A (en) | Method, device, equipment and computer readable storage medium for determining traffic information | |
| CN117173520A (en) | Method and device for determining three-dimensional fusion data | |
| CN114415676A (en) | Vehicle control method, device, equipment and computer readable storage medium | |
| CN116653933A (en) | Vehicle avoidance method, device, equipment and storage medium | |
| CN115959157A (en) | Vehicle control method and apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication |