CN112325898A - Path planning method, device, equipment and storage medium - Google Patents

Path planning method, device, equipment and storage medium Download PDF

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Publication number
CN112325898A
CN112325898A CN202110010426.5A CN202110010426A CN112325898A CN 112325898 A CN112325898 A CN 112325898A CN 202110010426 A CN202110010426 A CN 202110010426A CN 112325898 A CN112325898 A CN 112325898A
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obstacle
self
moment
state
time
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CN112325898B (en
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包晗
朱晓龙
王劲
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Ciic Technology Co ltd
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Ciic Technology Co ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/3453Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical

Abstract

The embodiment of the invention discloses a path planning method, a device, equipment and a storage medium; the embodiment of the invention can acquire the driving intention information, the self state information and the environment information and determine a road reference coordinate system; screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information; projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system; determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information; constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period; and planning the path according to the dynamic boundary point set to obtain a planned path. In the embodiment of the invention, the interaction condition with the low-speed dynamic barrier is considered in the path planning, so that the driving efficiency can be improved by the scheme.

Description

Path planning method, device, equipment and storage medium
Technical Field
The invention relates to the technical field of computers, in particular to a path planning method, a path planning device, a path planning equipment and a storage medium.
Background
The intelligent automobile mainly depends on an intelligent driver which is mainly a computer system in the automobile to achieve the purpose of unmanned driving. On the basis of a certain environment model, after a starting point and a target point of the intelligent automobile are given, the intelligent automobile can plan an effective path which is free of collision and can safely reach the target point according to performance indexes. When planning a path, not only static obstacles but also dynamic obstacles need to be processed.
At present, the intelligent automobile is not reasonable enough in processing low-speed dynamic obstacles, so that the driving efficiency is low.
Disclosure of Invention
The embodiment of the invention provides a path planning method, a path planning device, a path planning equipment and a storage medium, which can improve the driving efficiency.
The embodiment of the invention provides a path planning method, which comprises the following steps:
acquiring driving intention information, self state information and environment information, and determining a road reference coordinate system, wherein the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects;
screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system;
determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period;
and planning the path according to the dynamic boundary point set to obtain a planned path.
An embodiment of the present invention further provides a path planning apparatus, including:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring driving intention information, self state information and environment information, and determining a road reference coordinate system, the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects;
the screening unit is used for screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
the projection unit is used for projecting the bypassing obstacle in the road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system;
the interaction unit is used for determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
the construction unit is used for constructing a dynamic boundary point set according to the interaction state between the construction unit and the bypassing obstacle in a preset evaluation period;
and the planning unit is used for planning the path according to the dynamic boundary point set to obtain a planned path.
In some embodiments, the environment information includes an obstacle motion state of the detouring obstacle, the static boundary point set of the detouring obstacle includes boundary points of the obstacle, the self state information includes a self motion speed and a self position, the self position includes a distance relative to an origin of a reference line in the road reference coordinate system, and the preset evaluation period includes a plurality of time instants;
the interaction unit is specifically configured to perform the following steps:
according to
Figure 100002_DEST_PATH_IMAGE001
The self-movement speed and the self-position of the moment are predicted
Figure 100002_DEST_PATH_IMAGE002
A first position of a time relative to an origin;
predicting the position of the obstacle according to the obstacle motion state of the obstacle and the boundary point of the obstacle
Figure 277553DEST_PATH_IMAGE002
A second position of the time relative to the origin;
according to
Figure 982203DEST_PATH_IMAGE002
First position of time and
Figure 524043DEST_PATH_IMAGE002
the second position determination of the moment between itself and the obstacle
Figure 23158DEST_PATH_IMAGE002
The interaction state at the moment.
In some embodiments, the second location comprises a second minimum distance and a second maximum distance, the second minimum distance being the minimum distance from the origin in the boundary points of the obstacle, the second maximum distance being the maximum distance from the origin in the boundary points of the obstacle; the interaction unit is specifically configured to perform the following steps:
determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than the first distance threshold
Figure 384869DEST_PATH_IMAGE002
The interaction state at the moment is a proximity state;
determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than a second distance threshold
Figure 627631DEST_PATH_IMAGE002
The interaction state at the moment is a contact state;
determining that the distance between the obstacle and the obstacle is greater than a third distance threshold when the difference between the first position and the second maximum distance is greater than the third distance threshold
Figure 758398DEST_PATH_IMAGE002
The interactive state at the moment is the overtaking state;
when the interaction state between the self and the obstacle at the historical moment is the overtaking state, determining that the interaction state between the self and the obstacle is in the overtaking state
Figure 428414DEST_PATH_IMAGE002
The interactive state of the time is an neglected state, and the historical time is
Figure 41536DEST_PATH_IMAGE002
Any time before the time.
In some embodiments, the interaction unit is specifically configured to perform the following steps:
determining the interaction state between the self and the barrier at the historical moment;
when the interaction state between the self and the obstacle at the historical moment is a contact state, determining that the self and the obstacle are in the contact state
Figure 556831DEST_PATH_IMAGE002
The interactive state at the moment is the overtaking state.
In some embodiments, the interaction unit is specifically configured to perform the following steps:
determining an obstacle type of the obstacle;
determine the obstacle in
Figure 73263DEST_PATH_IMAGE002
The speed of the moment;
when the type of the obstacle is the first type and the obstacle is at
Figure 648601DEST_PATH_IMAGE002
Determining whether the speed is lower than a preset speed threshold value
Figure 250483DEST_PATH_IMAGE002
The interaction state at the moment is a contact state.
In some embodiments, the interaction unit is specifically configured to perform the following steps:
is determined to be
Figure 100002_DEST_PATH_IMAGE003
Limiting the speed of the moment;
determining a shift time from a predetermined acceleration, the shift time being indicative of a slave shift
Figure 100628DEST_PATH_IMAGE003
The self-movement speed of the moment is changed to
Figure 471566DEST_PATH_IMAGE003
The time required for limiting the speed of the moment;
determining
Figure 483384DEST_PATH_IMAGE002
Time and
Figure 41405DEST_PATH_IMAGE003
the time difference between the moments;
when the speed change time is larger than the time difference, according to the time difference,
Figure 931126DEST_PATH_IMAGE003
The self-movement speed and the self-position of the moment are obtained
Figure 890991DEST_PATH_IMAGE002
A first position of a time relative to an origin;
when the speed change time is not more than the time difference, according to the time difference, the speed change time,
Figure 339290DEST_PATH_IMAGE003
The self-movement speed and the self-position of the moment are obtained
Figure 915765DEST_PATH_IMAGE002
A first position of the time relative to the origin.
In some embodiments, the interaction unit is specifically configured to perform the following steps:
is determined at
Figure 842133DEST_PATH_IMAGE002
The self-movement speed of the moment;
according to the time difference,
Figure 922084DEST_PATH_IMAGE003
The self-movement speed of the moment and
Figure 275705DEST_PATH_IMAGE002
determining a first position increment according to the self-movement speed of the moment;
based on a first position increment and
Figure 339476DEST_PATH_IMAGE003
self-position of time, determining
Figure 568070DEST_PATH_IMAGE002
A first position of time.
In some embodiments, the interaction unit is specifically configured to perform the following steps:
is determined at
Figure 236949DEST_PATH_IMAGE002
The self-movement speed of the moment;
according to the speed change time,
Figure 27050DEST_PATH_IMAGE003
The self-movement speed of the moment and
Figure 312538DEST_PATH_IMAGE002
determining a second position increment based on the self-movement speed of the moment;
according to the sum of the speed change time and the time difference
Figure 315129DEST_PATH_IMAGE002
Determining a third position increment according to the self-movement speed of the moment;
based on the second position increment, the third position increment and
Figure 369673DEST_PATH_IMAGE003
self-position of time, determining
Figure 65096DEST_PATH_IMAGE002
A first position of time.
In some embodiments, the obstacle motion state of the obstacle includes heading and obstacle speed; the interaction unit is specifically configured to perform the following steps:
determining the minimum distance between the boundary point of the obstacle and the origin and the maximum distance between the boundary point of the obstacle and the origin;
projecting the speed of the obstacle along a reference line according to the orientation of the obstacle to obtain a speed component;
according to the velocity component,
Figure 572301DEST_PATH_IMAGE002
Determining a second minimum distance according to the minimum distance between the moment and the boundary point of the obstacle;
according to the velocity component,
Figure 644162DEST_PATH_IMAGE002
The maximum distance between the time and the boundary point of the obstacle determines the second maximum distance.
The embodiment of the invention also provides electronic equipment, which comprises a processor and a memory, wherein the memory stores a plurality of instructions; the processor loads instructions from the memory to perform the steps of any of the path planning methods provided by the embodiments of the present invention.
The embodiment of the present invention further provides a computer-readable storage medium, where multiple instructions are stored in the computer-readable storage medium, and the instructions are suitable for being loaded by a processor to perform steps in any one of the path planning methods provided in the embodiments of the present invention.
The embodiment of the invention can acquire the driving intention information, the self state information and the environment information and determine a road reference coordinate system; screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information; projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system; determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information; constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period; and planning the path according to the dynamic boundary point set to obtain a planned path.
In the invention, the intelligent automobile can screen out the obstacles needing to be bypassed from the traffic participation objects according to the driving intention of the obstacles; projecting the barrier to a road reference coordinate system to obtain a static boundary point set; then, in an evaluation period, predicting the interaction state between the intelligent automobile and the bypassing obstacle according to the static boundary point set and the state information of the intelligent automobile; and constructing a dynamic boundary point set according to the interaction state, and using the dynamic boundary point set considering the interaction condition for path planning to obtain a planned path of the intelligent automobile. Therefore, the driving efficiency of the intelligent automobile is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1a is a scene schematic diagram of a path planning method according to an embodiment of the present invention;
fig. 1b is a schematic flow chart of a path planning method according to an embodiment of the present invention;
FIG. 1c is a schematic view of a road reference frame provided by an embodiment of the present invention;
FIG. 1d is a schematic diagram of a reference speed limit provided by an embodiment of the present invention;
FIG. 1e is a schematic diagram of an obstacle according to an embodiment of the present invention;
FIG. 1f is a schematic diagram of a speed change scenario provided by an embodiment of the present invention;
FIG. 1g is a schematic diagram of an inter-prediction guideline provided by an embodiment of the invention;
FIG. 1h is a diagram of a dynamic boundary point set according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be 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 invention.
The embodiment of the invention provides a path planning method, a path planning device, a path planning equipment and a storage medium. The path planning apparatus may be specifically integrated in an Electronic device, and the Electronic device may be a vehicle-mounted terminal (Electronic Control Unit, ECU), or may be a server or other devices. The server may be a single server, or a server cluster composed of a plurality of servers.
In some embodiments, the electronic device may be a device installed on an intelligent vehicle (e.g. an unmanned vehicle), such as an intelligent driver, and referring to fig. 1a, the electronic device is an example of an intelligent driver integrated with a path planning apparatus. The electronic equipment acquires driving intention information, self state information and environment information, and determines a road reference coordinate system, wherein the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects; screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information; projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system; determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information; constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period; and planning the path according to the dynamic boundary point set to obtain a planned path. The interaction condition between the vehicle and the low-speed dynamic barrier is considered in the path planning, and therefore the driving efficiency can be improved by the scheme.
The following are detailed below. The numbers in the following examples are not intended to limit the order of preference of the examples.
The embodiment of the invention provides a path planning method, and relates to an unmanned technology in the field of artificial intelligence. Among them, Artificial Intelligence (AI) is a technology for simulating a human perception environment using a digital computer, acquiring knowledge, and using the knowledge, which can make a machine have functions similar to human perception, reasoning, and decision making. The artificial intelligence technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning, deep learning and the like.
The unmanned technology is a comprehensive body of multiple leading-edge subjects such as a sensor, a computer, artificial intelligence, communication, navigation positioning, mode recognition, machine vision, intelligent control and the like, and refers to a technology which can guide and decide a vehicle driving task without testing the physical driving operation of a driver, replace the testing of the control behavior of the driver and enable the vehicle to complete the function of safe driving. According to the function module of the unmanned automobile, the key technologies of the unmanned automobile comprise environment perception, navigation positioning, path planning, decision control and the like. The scheme mainly relates to path planning, and the path planning is a bridge for information perception and intelligent control of unmanned vehicles and is a basis for realizing autonomous driving. The task of path planning is to find a collision-free path from an initial state including a position and a posture to a target state according to a certain evaluation standard in an environment with obstacles.
In this embodiment, a path planning method is provided, as shown in fig. 1b, a specific flow of the path planning method may be as follows:
101. the electronic device acquires the driving intention information, the self-state information and the environment information, and determines a road reference coordinate system.
The environment information is used for representing the information of the real-time perceived surrounding environment in the driving process of the intelligent automobile, and can include information of traffic participation objects on the driving road of the intelligent automobile. The traffic participation object comprises motor vehicles, non-motor vehicles, pedestrians and the like around the intelligent automobile; the information of the traffic participation object includes a position, a motion state (speed, orientation), and the like of the traffic participation object. The electronic device can acquire the environment information through an environment sensing module, and the environment sensing module can be a laser radar, a camera, a millimeter wave radar and other devices.
The self-state information is used for representing the self-motion state of the intelligent automobile and can comprise self-motion speed, self-position, attitude information and the like. The electronic device may obtain the self-state information through a vehicle-mounted device, which may be an inertial navigation device, a GPS positioning device, a wheel speed meter, or the like. It should be noted that, in this embodiment, the device itself refers to an intelligent automobile or a device installed on an intelligent automobile.
The driving intent information is used to characterize the driving intent of the traffic participant, which may include crossing roads, temporary parking, permanent parking, and giving way to other traffic participants, etc. The driving intention information can be decision information of the previous period or can be obtained through a prediction module and a signal lamp. The decision information of the previous cycle is the decision information output by the previous cycle of the current path planning cycle of the intelligent automobile, such as yield information output by an Expectation-maximization path planning (EM plan) algorithm; the decision information represents the driving intention of the traffic participant, for example, the decision information represents that the driving intention of the traffic participant is temporary parking. The prediction module may be a device that integrates a prediction algorithm, which may be an integral part of the electronic device; the predicted lateral span of the trajectory of the traffic-engaging object, as output by the prediction module, may determine whether the travel intent of the traffic-engaging object is to traverse a road. The signal lamp may indicate the driving intention of the traffic participant, and if the signal lamp is a red light, it indicates that the driving intention of the traffic participant is temporary parking. In some embodiments, traffic-engaging objects whose travel intent is to be temporarily stopped may be observed, such as by adding different periodic delays to see if the travel intent will transition to a permanent stop.
In some embodiments, the electronic device also obtains high-precision map information, which may include road traffic speed limits, curvature speed limits for passing curves, road centerlines, road boundary points, road dashed solid lines, stop lines, zebra stripes, intersections, and the like.
In some embodiments, the electronic device determines a road reference coordinate system. For example, the road reference coordinate system may be a freiner (Frenet) coordinate system, as shown in fig. 1c, which is a schematic diagram of a road reference coordinate system provided in this example; the road coordinate system comprises a reference line(s), and the reference line can be a line (group) which is generated smoothly according to a road center line and can be used for driving the intelligent automobile; the road coordinate system further comprises a transverse line (perpendicular to the reference line)l) The lateral distance is denoted by d; the road coordinate system further comprises an origin, which may be the starting point of the smart car, for example. Optionally, the reference speed limit of each point on the reference line can be determined by the road traffic speed limit and the curvature speed limit of the curve passing through in the map information
Figure DEST_PATH_IMAGE004
Fig. 1d is a schematic diagram of a reference speed limit provided in this embodiment, where s represents a reference line.
102. The electronic equipment screens out at least one obstacle to detour from the traffic participant according to the driving intention information.
The detour obstacle is used for representing objects which can be detoured by the intelligent automobile in the traffic participant, such as a static traffic participant and a traffic participant running along a road. It should be noted that the specific number of the bypassing obstacles is not limited, and there may be one or more than one bypassing obstacles. In some embodiments, if the traffic on the driving road of the smart car is less involved, there may be no obstacle detouring, i.e. the number of obstacle detouring is zero.
In some embodiments, after screening traffic participants whose driving intentions are temporary stops, crossing roads, and giving way to other traffic participants, the remaining traffic participants are detour obstacles. Therefore, the traffic participation objects are screened, and the efficiency of path planning can be improved. In some embodiments, the traffic participant may be marked with an obstacle type, wherein the obstacle type includes a first type and a second type, the obstacle type of the detour obstacle is the first type, and the obstacle type of the traffic participant whose driving is intended to temporarily stop, cross the road, and give way to other traffic participants is the second type, which may also be referred to as a blocking obstacle.
103. The electronic equipment projects the bypassing obstacle in the road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system.
The static boundary point set is used for representing a set of boundary points of the obstacle projected in the road reference coordinate system, namely the static boundary point set is composed of boundary points of a plurality of obstacles, and the obstacle is any obstacle in the bypassing obstacles. Taking the boundary point of an obstacle in the Frenet coordinate system as an example, the boundary point of the obstacle: (
Figure DEST_PATH_IMAGE005
Boundary points) can be expressed as
Figure DEST_PATH_IMAGE006
. Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE007
a minimum distance in the s-direction from the origin of a contour characterizing the obstacle;
Figure DEST_PATH_IMAGE008
a maximum distance in the s-direction from the origin of a contour characterizing the obstacle;
Figure DEST_PATH_IMAGE009
for characterizing the profile of an obstacle inlA minimum distance from the origin in the direction;
Figure DEST_PATH_IMAGE010
for watchesThe contour of the obstacle islThe distance in the direction from the origin is greatest.
In some embodiments, the boundary points of the obstacle may be derived from the contour of the obstacle; the contour of the intelligent automobile in the actual road is projected in the road reference coordinate system to obtain the contour in the road reference coordinate system, as shown in fig. 1e, which is a schematic diagram of the contour of the obstacle provided by the embodiment of the present invention. s represents a reference line which is,lthe rectangle can be used for representing the outline of the obstacle projected in the road reference coordinate system. Traversing the contour of the obstacle in the road reference coordinate system, finding the points with the maximum distance and the minimum distance in the s direction relative to the origin, anlAnd obtaining the boundary point of the obstacle by the point with the maximum distance and the point with the minimum distance relative to the origin in the direction.
It should be noted that the execution sequence of step 102 and step 103 is not limited, and step 102 may be executed first and then step 103 may be executed; or, the step 103 may be executed first, and then the step 102 is executed, so as to obtain the static boundary point set of the traffic participation object, and then the traffic participation object is screened.
104. The electronic equipment determines the interaction state between the electronic equipment and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the state information of the electronic equipment.
The preset evaluation period is used for representing a time range for performing iterative operation on the interaction state between the self and the bypassing obstacle, and when the iterative time exceeds the evaluation period, the operation for determining the interaction state between the self and the bypassing obstacle is stopped. The preset evaluation period comprises a plurality of moments; for example, the preset period may include a time of day
Figure DEST_PATH_IMAGE011
. The value of the preset evaluation period can be set in a user-defined mode according to the actual situation.
Figure DEST_PATH_IMAGE012
Time of day and
Figure DEST_PATH_IMAGE013
the moment is any moment in a preset evaluation period,
Figure 68059DEST_PATH_IMAGE013
time of day is composed of
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The time and the iteration step are obtained as follows:
Figure DEST_PATH_IMAGE014
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE015
and
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for characterizing the time difference (iteration step),
Figure DEST_PATH_IMAGE017
for representing the preset time of the heavy interest, the time of the heavy interest can be set according to the practical application in a customized way, such as 5 seconds. It should be noted that, because it is important to preset the first few seconds of the evaluation period, the step size of iteration is small; thus, it is possible to provide
Figure 53519DEST_PATH_IMAGE015
Can be compared with
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The value of (2) is small, the step length of time iteration after the preset evaluation period is increased, and the operation efficiency can be improved. Optionally, an iteration distance threshold may also be preset, and the value of the iteration distance threshold may be set in a user-defined manner according to actual application; when iterative operation is carried out, when the distance of the intelligent automobile relative to the origin is larger than a preset iterative distance threshold value, the operation of determining the interaction state between the intelligent automobile and the bypassing obstacle is stopped.
In some embodiments, since the detouring obstacle belongs to the traffic participant, the obstacle motion state of the detouring obstacle, which includes the obstacle speed and the orientation, may be included in the environment information. The static boundary point set of the bypassing obstacle comprises boundary points of the obstacle, the self state information comprises self movement speed and self position, and the self position comprises a distance relative to an origin of a reference line in a road reference coordinate system. Specific embodiments of determining the interaction state between the obstacle and the obstacle during the preset evaluation period refer to the following steps S1-S3:
it should be noted that, in the present embodiment, in the preset evaluation period, the step of determining the interaction state between the smart vehicle itself and the obstacle around may be performed iteratively, so as to obtain the interaction states between the smart vehicle itself and all the obstacle around at all times in the preset evaluation period. The present embodiment only determines between itself and an obstacle
Figure 427048DEST_PATH_IMAGE013
The interaction state of the time is taken as an example for detailed explanation, and
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at the moment of division within a preset evaluation period
Figure DEST_PATH_IMAGE018
At any time other than the time, the obstacle is any obstacle in the detour obstacles.
S1: according to
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The self-movement speed and the self-position of the moment are predicted
Figure 126779DEST_PATH_IMAGE013
A first position of the time relative to the origin.
Wherein the first location is used for characterizing
Figure 276001DEST_PATH_IMAGE013
The distance of the smart car from the origin at the moment, e.g. in the rear axle of the smart carThe distance of the heart from the origin.
In some embodiments of the present invention, the,
Figure 484128DEST_PATH_IMAGE012
the moment is any moment in a preset evaluation period. When k is 0, it is
Figure 453221DEST_PATH_IMAGE018
At the moment of time, the time of day,
Figure 139417DEST_PATH_IMAGE018
the time is used for representing that the intelligent automobile is in an initial motion state, wherein the initial motion state can be a state of the intelligent automobile at a planning initial point, and the planning initial point is a starting point of path planning. For example,
Figure 143146DEST_PATH_IMAGE018
the initial state information at the time may include a position of itself as
Figure DEST_PATH_IMAGE019
Speed of self-movement
Figure DEST_PATH_IMAGE020
Figure 817447DEST_PATH_IMAGE018
The speed limit of the moment and the position of the barrier; wherein the content of the first and second substances,
Figure 8257DEST_PATH_IMAGE019
the method is used for representing the distance parallel to the direction of a reference line obtained by projecting an initial planning point in a Frenet coordinate system;
Figure 763723DEST_PATH_IMAGE020
to plan an initial speed; according to the reference line
Figure DEST_PATH_IMAGE021
Obtaining the reference speed limit of the intelligent automobile at the current road position
Figure DEST_PATH_IMAGE022
The intelligent automobile is
Figure 418696DEST_PATH_IMAGE018
Speed limit of time
Figure DEST_PATH_IMAGE023
(ii) a Position of blocking obstacle
Figure DEST_PATH_IMAGE024
Taken to be infinite.
Figure DEST_PATH_IMAGE025
The self-state information of the time can be passed
Figure 797987DEST_PATH_IMAGE018
The initial state information of the time is obtained, and so on, so the embodiment only uses
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Time of day and
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the time of day is elaborated.
In some embodiments, the prediction is in
Figure 482412DEST_PATH_IMAGE013
An embodiment of the first position of the time relative to the origin may refer to the following steps:
a. is determined to be
Figure 468822DEST_PATH_IMAGE012
The speed limit of the moment.
In some embodiments, self-in can be obtained by the following formula
Figure 634224DEST_PATH_IMAGE012
Speed limit of the moment:
Figure DEST_PATH_IMAGE026
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE027
for characterizing
Figure DEST_PATH_IMAGE028
The speed limit of the moment of time is,
Figure DEST_PATH_IMAGE029
for characterizing time of day
Figure 846941DEST_PATH_IMAGE012
And the reference speed of a point on the reference line corresponding to the intelligent automobile at the moment. Alternatively,
Figure DEST_PATH_IMAGE030
can be between itself and the obstacle
Figure 679768DEST_PATH_IMAGE012
For determining the interaction state at the moment, the specific implementation may refer to step S3, which is not described herein again.
b. Determining a shift time from a predetermined acceleration, the shift time being indicative of a slave shift
Figure 837080DEST_PATH_IMAGE012
The self-movement speed of the moment is changed to
Figure 755358DEST_PATH_IMAGE012
Time required for speed limitation of time of day.
The preset acceleration can be set according to practical application, and can be a negative value or a positive value; when the preset acceleration is a negative value, the intelligent automobile is indicated to need to be driven
Figure 125159DEST_PATH_IMAGE012
The self-movement speed of the moment is decelerated to
Figure 812492DEST_PATH_IMAGE012
Limiting the speed of the moment; when the preset acceleration is a positive value, the fact that the intelligent automobile needs to be driven is indicated
Figure 140705DEST_PATH_IMAGE012
The self-movement speed of the moment is accelerated to
Figure 15121DEST_PATH_IMAGE012
The speed limit of the moment. The shift time can be determined by:
Figure DEST_PATH_IMAGE031
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE032
for characterizing
Figure 17974DEST_PATH_IMAGE012
The self-movement speed of the moment;
Figure DEST_PATH_IMAGE033
for characterizing shift times;
Figure DEST_PATH_IMAGE034
for characterizing a preset acceleration. In some embodiments, from
Figure 356551DEST_PATH_IMAGE012
The self-movement speed of the moment is changed to
Figure 855666DEST_PATH_IMAGE012
The following four scenarios may occur for the speed limit at the time, as shown in fig. 1f, which is a speed change scenario provided in this embodiment. FIG. 1f is a schematic diagram of a smart car
Figure 217377DEST_PATH_IMAGE012
After the time is accelerated according to the preset acceleration, the time is quickly reached
Figure 194560DEST_PATH_IMAGE012
And (5) limiting the speed at any moment and then carrying out uniform motion. FIG. 1f shows a schematic representation of a smart car
Figure 590907DEST_PATH_IMAGE012
After the time is accelerated according to the preset acceleration
Figure DEST_PATH_IMAGE035
The moment is not reached yet
Figure 290616DEST_PATH_IMAGE012
The speed limit of the moment. FIG. 1f shows a schematic representation of a smart car
Figure 139623DEST_PATH_IMAGE012
After the speed is reduced according to the preset acceleration at any moment, the speed is quickly reduced
Figure 920497DEST_PATH_IMAGE012
And (5) limiting the speed of the moment, and then performing a uniform motion picture. FIG. 1f (IV) is used to characterize the Smart Car
Figure 171350DEST_PATH_IMAGE012
After the time is decelerated according to the preset acceleration
Figure 12267DEST_PATH_IMAGE035
The moment is not reached yet
Figure 348571DEST_PATH_IMAGE012
The speed limit of the moment.
c. Determining
Figure 933136DEST_PATH_IMAGE035
Time and
Figure 304074DEST_PATH_IMAGE012
the time difference between the moments. The time difference can be obtained by the following formula:
Figure DEST_PATH_IMAGE036
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE037
for characterizing the time difference; for example,
Figure 348516DEST_PATH_IMAGE037
the value may be
Figure DEST_PATH_IMAGE038
Or
Figure DEST_PATH_IMAGE039
d. When the speed change time is larger than the time difference, according to the time difference,
Figure 968853DEST_PATH_IMAGE012
The self-movement speed and the self-position of the moment are obtained
Figure 357109DEST_PATH_IMAGE035
A first position of the time relative to the origin.
Specifically, the sum of the acceleration may be preset
Figure 316975DEST_PATH_IMAGE012
The self-movement speed of the moment is determined
Figure 499694DEST_PATH_IMAGE035
The self-movement speed at the moment is shown as the following formula:
Figure DEST_PATH_IMAGE040
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE041
for characterizing
Figure 607328DEST_PATH_IMAGE035
Self-movement of timeAnd (4) moving speed.
According to the time difference,
Figure 32231DEST_PATH_IMAGE012
The self-movement speed of the moment and
Figure 112182DEST_PATH_IMAGE035
determining a first position increment according to the self-movement speed of the moment; based on a first position increment and
Figure 465803DEST_PATH_IMAGE012
self-position of time, determining
Figure 263995DEST_PATH_IMAGE035
A first position of time. The first position increment is used for representing the distance traveled by the intelligent automobile in the acceleration movement process when the speed change time is larger than the time difference.
In some embodiments, when the shift time is greater than the time difference, the first position may be calculated by:
Figure DEST_PATH_IMAGE042
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE043
for characterizing the first location or locations of the object,
Figure DEST_PATH_IMAGE044
for characterizing
Figure 56370DEST_PATH_IMAGE012
The position of the person at the moment of time,
Figure 990828DEST_PATH_IMAGE041
for characterizing
Figure 780930DEST_PATH_IMAGE035
The speed of the movement itself at the moment.
e. When the speed change time is not more than the time difference, according to the time difference, the speed change time,
Figure 36724DEST_PATH_IMAGE012
The self-position and self-movement speed of the moment are obtained
Figure 570473DEST_PATH_IMAGE035
A first position of the time relative to the origin.
Is determined at
Figure 625017DEST_PATH_IMAGE035
The self-movement speed of the moment, at which the self-movement speed is equal to
Figure 320441DEST_PATH_IMAGE012
The time limit is shown as follows:
Figure DEST_PATH_IMAGE045
according to the speed change time,
Figure 358804DEST_PATH_IMAGE012
The self-movement speed of the moment and
Figure 430665DEST_PATH_IMAGE035
determining a second position increment based on the self-movement speed of the moment; according to the sum of the speed change time and the time difference
Figure 74136DEST_PATH_IMAGE035
Determining a third position increment according to the self-movement speed of the moment; based on the second position increment, the third position increment and
Figure 206040DEST_PATH_IMAGE012
self-position of time, determining
Figure 934962DEST_PATH_IMAGE035
A first position of time. Wherein the second position increment is used forThe distance of the intelligent automobile in the accelerating process is shown when the speed change time is not more than the time difference value, and the third position increment is the distance of the intelligent automobile
Figure DEST_PATH_IMAGE046
The distance traveled by the vehicle.
In some embodiments, when the shift time is not greater than the time difference, the first position may be calculated by:
Figure DEST_PATH_IMAGE047
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE048
for characterizing the shift time.
S2: predicting the position of the obstacle according to the obstacle motion state of the obstacle and the boundary point of the obstacle
Figure 636945DEST_PATH_IMAGE035
A second position of the time relative to the origin.
Wherein the second position comprises a second minimum distance and a second maximum distance, the second minimum distance is the minimum distance from the boundary point of the obstacle to the origin, and the second maximum distance is the maximum distance from the boundary point of the obstacle to the origin. If not specifically stated, the boundary point of the obstacle in this embodiment is indicated as
Figure DEST_PATH_IMAGE049
The boundary points of the obstacle at the moment.
In some embodiments, a minimum distance of a boundary point of the obstacle from the origin is determined, and a maximum distance of the boundary point of the obstacle from the origin is determined. The minimum distance may be in
Figure 931660DEST_PATH_IMAGE049
At the boundary points of the obstacle at the moment
Figure DEST_PATH_IMAGE050
(ii) a The minimum distance may be at
Figure 500045DEST_PATH_IMAGE049
At the boundary points of the obstacle at the moment
Figure DEST_PATH_IMAGE051
The obstacle motion state of the obstacle includes heading and obstacle speed. And according to the orientation of the obstacle, projecting the speed of the obstacle along a reference line to obtain a speed component. In some embodiments, a point P closest to the rear of the obstacle on the reference line is determined, an angular difference between the orientation of the obstacle and the orientation of the point P is calculated, and the speed of the obstacle is projected along the reference line to obtain a speed component. As shown in the following formula:
Figure DEST_PATH_IMAGE052
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE053
for characterizing the point P on the reference line;
Figure DEST_PATH_IMAGE054
the distance between the P point and the origin of the reference line is represented; a is used for characterizing the obstacle;
Figure DEST_PATH_IMAGE055
the minimum distance of the boundary point for characterizing the obstacle from the origin of the reference line.
Figure DEST_PATH_IMAGE056
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE057
for characterizing a velocity component;
Figure DEST_PATH_IMAGE058
an obstacle speed for characterizing an obstacle;
Figure DEST_PATH_IMAGE059
for characterizing the orientation of the obstacle;
Figure DEST_PATH_IMAGE060
for characterizing the orientation of the P point.
According to the velocity component,
Figure DEST_PATH_IMAGE061
The minimum distance between the time of day and the boundary point of the obstacle determines the second minimum distance. The second minimum distance is calculated by:
Figure DEST_PATH_IMAGE062
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE063
for characterizing the second minimum distance.
According to the velocity component,
Figure 559005DEST_PATH_IMAGE061
The maximum distance between the time and the boundary point of the obstacle determines the second maximum distance. The second maximum distance is calculated by:
Figure DEST_PATH_IMAGE064
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE065
for characterizing the second maximum distance;
Figure DEST_PATH_IMAGE066
for characterizing in
Figure DEST_PATH_IMAGE067
The maximum distance of the boundary point of the obstacle from the origin at the moment.
S3: according to
Figure 566144DEST_PATH_IMAGE061
First position of time and
Figure 449787DEST_PATH_IMAGE061
the second position determination of the moment between itself and the obstacle
Figure 392335DEST_PATH_IMAGE061
The interaction state at the moment.
The interaction state is used for representing interaction conditions which may occur between the intelligent automobile and the obstacle detouring in the driving process; the interaction state comprises a proximity state, a contact state, a passing state and an ignoring state.
In some embodiments, determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than the first distance threshold
Figure 862893DEST_PATH_IMAGE061
The interaction state at the moment is the proximity state. Wherein the approaching state is used for representing that the intelligent automobile approaches the obstacle. The first distance threshold value can be set in a self-defined manner according to the actual application condition; for example, the first distance threshold may be
Figure DEST_PATH_IMAGE068
Is used for representing the distance from the center of the rear axle of the intelligent automobile to the head of the intelligent automobile,
Figure DEST_PATH_IMAGE069
the intelligent automobile is a positive number, and the value of the positive number can be set in a user-defined mode according to the actual application condition, for example, different values are set according to whether the intelligent automobile follows the obstacle or not. Can be expressed by the following formula:
Figure DEST_PATH_IMAGE070
thus, it is determined that
Figure 408144DEST_PATH_IMAGE061
The speed limit of the moment is
Figure DEST_PATH_IMAGE071
. Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE072
the speed increment is used for representing the speed increment, the value of the speed increment can be set by self according to the practical application condition,
Figure DEST_PATH_IMAGE073
is arranged as
Figure DEST_PATH_IMAGE074
. Namely, the self-moving speed of the intelligent automobile is slightly higher than the moving speed of the obstacle, and the intelligent automobile approaches the obstacle.
In some embodiments, determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than the second distance threshold
Figure 739768DEST_PATH_IMAGE061
The interaction state at the moment is a contact state. And the contact state is used for representing that the distance between the intelligent automobile and the obstacle is smaller than a second distance threshold value. The second distance threshold value can be set in a self-defined manner according to the actual application condition; for example, the second distance threshold may be
Figure DEST_PATH_IMAGE075
Figure DEST_PATH_IMAGE076
Is a positive number, the value of which can be self-defined according to the actual application situation, such as the
Figure 679649DEST_PATH_IMAGE076
A value of less than
Figure DEST_PATH_IMAGE077
The value of (c). Can be expressed by the following formula:
Figure DEST_PATH_IMAGE078
wherein the content of the first and second substances,
Figure 932776DEST_PATH_IMAGE076
the value of can confirm the time of rotating the steering wheel when the intelligent automobile need overtake the barrier to optimize the route of detouring, make the action of intelligent automobile more reasonable, high-efficient and safety.
Optionally, when the difference between the second minimum distance and the first position is smaller than the second distance threshold, it is further required to determine the type of the obstacle, and determine that the obstacle is at the first position
Figure 422663DEST_PATH_IMAGE061
The speed of the moment. When the type of the obstacle is the first type and the obstacle is at
Figure 280897DEST_PATH_IMAGE061
The speed of the moment is lower than a preset speed threshold value, and the situation between the self and the barrier can be determined
Figure 96407DEST_PATH_IMAGE061
The interaction state at the moment is a contact state. The value of the preset speed threshold value can be set in a user-defined mode according to the actual application condition; for example, setting the value of the preset speed threshold value to be a value lower than the self-movement speed of the intelligent automobile; or setting the value of the preset speed threshold as the value of the percentage of the reference speed limit.
Thus, the intelligent car is determined to be
Figure 275977DEST_PATH_IMAGE061
The speed limit of the moment is
Figure DEST_PATH_IMAGE079
Namely, if the intelligent automobile does not drive along with the obstacle, the speed limit of the intelligent automobile is recovered to the reference speed limit, and the intelligent automobile can be ready to overtake the obstacle. In addition, if the obstacle is in the oblique front of the smart car, then it is intelligentThe automobile can also overtake obstacles. In some embodiments, the smart car is in the zone
Figure DEST_PATH_IMAGE080
The speed change from the speed limit in the approaching state to the speed limit in the contacting state is completed.
Alternatively, a touch flag may be set, and the value of the flag is true, so that the touch state and the passing state can be distinguished.
It should be noted that when the type of the obstacle is the second type, and the obstacle is in
Figure 366293DEST_PATH_IMAGE061
When the speed at the moment is not lower than the preset speed threshold, the smart car will follow the obstacle to run, as shown in (a) in fig. 1g, and follow indicates the obstacle followed by the smart car. Thus, the intelligent car is determined to be
Figure 79034DEST_PATH_IMAGE061
The speed limit of the moment is
Figure DEST_PATH_IMAGE081
Namely, the speed of the intelligent automobile is consistent with the speed of the obstacle.
In some embodiments, determining that there is a difference between the first location and the second maximum distance greater than a third distance threshold between the first location and the obstacle
Figure 331024DEST_PATH_IMAGE061
The interactive state at the moment is the overtaking state. The overtaking state is used for representing that the intelligent automobile overtakes the obstacle. The third distance threshold value can be set in a self-defined manner according to the actual application condition; for example, the third distance threshold may be
Figure DEST_PATH_IMAGE082
Figure DEST_PATH_IMAGE083
Is used for representing the center of the rear axle of the intelligent automobile to the tail of the intelligent automobileThe distance of (a) to (b),
Figure DEST_PATH_IMAGE084
the value of the positive number can be set by self according to the practical application condition. Can be expressed by the following formula:
Figure DEST_PATH_IMAGE085
Figure 854016DEST_PATH_IMAGE084
the value of the direction indicator determines that the interaction state is a critical condition of the overtaking state, and determines the time point when the direction wheel returns to the positive state when the intelligent automobile bypasses the obstacle; when the distance that the rear of a vehicle of intelligent automobile was walked around the barrier is greater than the third distance threshold value promptly, the interactive state is the overtaking state, then intelligent automobile need not to keep certain distance with the barrier transversely again.
Optionally, when the difference between the first position and the second maximum distance is greater than a third distance threshold, determining an interaction state between the obstacle and the self and the obstacle at the historical time; when the interaction state between the self and the obstacle at the historical moment is a contact state, determining that the self and the obstacle are in the contact state
Figure 951285DEST_PATH_IMAGE061
The interactive state at the moment is the overtaking state. Wherein the historical time is
Figure 252953DEST_PATH_IMAGE061
Any time before the time. Namely, the intelligent automobile needs to contact with the obstacle first and then overtake the obstacle.
Thus, the determination of the smart car is that the smart car is
Figure 410265DEST_PATH_IMAGE061
The speed limit of the moment is
Figure DEST_PATH_IMAGE086
That is, after the intelligent automobile bypasses the obstacle, the speed limit of the intelligent automobileReverting to the reference speed limit.
Optionally, a touch flag is set, and the value of the flag is false, so that the overtaking state can be distinguished from the touch state.
In some embodiments, when the interaction state between the self and the obstacle at the historical moment is the overtaking state, the fact that the self and the obstacle are in the overtaking state is determined
Figure 328543DEST_PATH_IMAGE061
The interactive state at the moment is the ignore state. The neglected state is used for representing that the intelligent automobile ignores the obstacle, and no processing is performed, namely after the intelligent automobile overtakes the obstacle, the interaction condition between the intelligent automobile and the obstacle is not considered.
Optionally, after the interaction state between the intelligent automobile and the obstacle around is determined, the obstacle can be marked according to the interaction state. For example, according to the interaction state between itself and the detour obstacle in the preset evaluation period, the corresponding detour obstacle is marked, and the interaction prediction guideline (st _ chase _ line) can be obtained, as shown in fig. 1g (b), which is a schematic diagram of the interaction prediction guideline provided by the embodiment of the invention. When the interaction state is the approaching state, marking the corresponding barrier as the apreach; when the interaction state is a contact state, marking the corresponding barrier as touching; when the interaction state is the overtaking state, marking the corresponding barrier as overriding; and when the interactive state is the neglected state, marking the corresponding obstacle as the ignore. In some embodiments, if the obstacle is a barrier obstacle, the barrier obstacle is marked as a will stop. In some embodiments, the interactive predictive guidance lines may also include end point information, traffic light stop line information.
In some embodiments, if the interaction state between the smart car and the barrier is a close state, the smart car starts to slow down; if the interaction state between the intelligent automobile and the barrier is a contact state, setting
Figure DEST_PATH_IMAGE087
I.e. blockingThe position of the obstacle is equal to
Figure 495082DEST_PATH_IMAGE061
The position of the intelligent automobile is constantly.
105. The electronic equipment constructs a dynamic boundary point set according to the interaction state between the electronic equipment and the bypassing obstacle in a preset evaluation period.
The dynamic boundary point set may include a boundary point set in which an interaction state of the detour obstacle is a contact state and a boundary point set in which an interaction state is an overtaking state.
In some embodiments, within a preset evaluation period, when the interaction state between the intelligent vehicle and the bypassing obstacle is determined to be a contact state or a passing state, the time, the bypassing obstacle identification, the boundary point of the bypassing obstacle and the position of the intelligent vehicle are recorded. Therefore, a boundary point set of the bypassing obstacle in the contact state and a boundary point set of the bypassing obstacle in the overtaking state are obtained, and the boundary point set of the bypassing obstacle in the contact state and the boundary point set of the bypassing obstacle in the overtaking state are arranged in time sequence, so that a dynamic boundary point set can be obtained. Fig. 1h is a schematic diagram of a dynamic boundary point set provided in this embodiment. The points a, b, c, d, e and f respectively correspond to the identifiers of the bypassing obstacles, the dots are used for representing the boundary points of the bypassing obstacles marked as overraking, and the dots with the pentagons are used for representing the boundary points of the bypassing obstacles marked as touchhing. As shown in the figure, when the interaction state between the vehicle and the obstacle d is the overtaking state and the interaction state between the vehicle and the obstacle e is the contact state at the same time, the boundary point of the obstacle d is arranged before the boundary point of the obstacle e. If the interaction state between the obstacle and the obstacle is only the overtaking state, such as the obstacle a, the boundary point of the obstacle a is expanded to the direction s by a smaller value. If the interaction state between the self and the obstacle is only a contact state, such as the obstacle f, the boundary point of the obstacle f is temporarily removed from the dynamic boundary set, and the interaction condition with the obstacle f is ignored.
106. And the electronic equipment plans the path according to the dynamic boundary point set to obtain a planned path.
According to the obtained dynamic boundary point set, carrying out equally-spaced discretization on the reference line in the s direction, and calculating each discrete point
Figure DEST_PATH_IMAGE088
Feasible area of
Figure DEST_PATH_IMAGE089
(ii) a And performing quadratic programming on the segmented cubic polynomial in the feasible region to generate a smooth programming path. In some embodiments, the specific implementation of path planning may refer to the description of the EM planner algorithm, which is not described herein again.
The embodiment of the invention can acquire the driving intention information, the self state information and the environment information and determine a road reference coordinate system; screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information; projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system; determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information; constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period; and planning the path according to the dynamic boundary point set to obtain a planned path.
In the invention, the intelligent automobile can screen out the obstacles needing to be bypassed from the traffic participation objects according to the driving intention of the obstacles; projecting the barrier to a road reference coordinate system to obtain a static boundary point set; then, in an evaluation period, predicting the interaction state between the intelligent automobile and the bypassing obstacle according to the static boundary point set and the state information of the intelligent automobile; and constructing a dynamic boundary point set according to the interaction state, and using the dynamic boundary point set considering the interaction condition for path planning to obtain a planned path of the intelligent automobile. Therefore, the driving efficiency of the intelligent automobile is improved.
In order to better implement the method, an embodiment of the present invention further provides a path planning apparatus, where the path planning apparatus may be specifically integrated in an electronic device, and the electronic device may be a vehicle-mounted terminal, a server, or other devices.
For example, in this embodiment, a method according to an embodiment of the present invention will be described in detail by taking an example in which a path planning apparatus is specifically integrated in a vehicle-mounted terminal.
For example, as shown in fig. 2, the path planning apparatus may include an obtaining unit 201, a screening unit 202, a projecting unit 203, an interacting unit 204, a constructing unit 205, and a planning unit 206, as follows:
acquisition unit 201
An acquiring unit 201, configured to acquire driving intention information, self-state information, and environment information, and determine a road reference coordinate system, where the environment information includes information of traffic-participating objects on a driving road, and the driving intention information is used to represent driving intents of the traffic-participating objects;
(II) screening Unit 202
The screening unit 202 is used for screening at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
(III) projection Unit 203
The projection unit 203 is configured to project the detour obstacle in the road reference coordinate system to obtain a static boundary point set of the detour obstacle in the road reference coordinate system;
(IV) interaction unit 204
The interaction unit 204 is configured to determine an interaction state between the self and the bypassing obstacle within a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
(V) construction Unit 205
The building unit 205 is configured to build a dynamic boundary point set according to an interaction state between the building unit and a bypassing obstacle within a preset evaluation period;
(sixth) planning Unit 206
And the planning unit 206 is configured to perform path planning according to the dynamic boundary point set to obtain a planned path.
In some embodiments, the environment information includes an obstacle motion state of the detouring obstacle, the static boundary point set of the detouring obstacle includes boundary points of the obstacle, the self state information includes a self motion speed and a self position, the self position includes a distance relative to an origin of a reference line in the road reference coordinate system, and the preset evaluation period includes a plurality of time instants;
the interaction unit 204 is specifically configured to perform the following steps:
according to
Figure DEST_PATH_IMAGE090
The self-movement speed and the self-position of the moment are predicted
Figure DEST_PATH_IMAGE091
A first position of a time relative to an origin;
predicting the position of the obstacle according to the obstacle motion state of the obstacle and the boundary point of the obstacle
Figure 277355DEST_PATH_IMAGE091
A second position of the time relative to the origin;
according to
Figure 605568DEST_PATH_IMAGE091
First position of time and
Figure 479983DEST_PATH_IMAGE091
the second position determination of the moment between itself and the obstacle
Figure 919055DEST_PATH_IMAGE091
The interaction state at the moment.
In some embodiments, the second location comprises a second minimum distance and a second maximum distance, the second minimum distance being the minimum distance from the origin in the boundary points of the obstacle, the second maximum distance being the maximum distance from the origin in the boundary points of the obstacle; the interaction unit 204 is specifically configured to perform the following steps:
when the second minimum distance is equal toDetermining that the difference between the first position and the obstacle is smaller than a first distance threshold value
Figure 195316DEST_PATH_IMAGE091
The interaction state at the moment is a proximity state;
determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than a second distance threshold
Figure 694430DEST_PATH_IMAGE091
The interaction state at the moment is a contact state;
determining that the distance between the obstacle and the obstacle is greater than a third distance threshold when the difference between the first position and the second maximum distance is greater than the third distance threshold
Figure 56141DEST_PATH_IMAGE091
The interactive state at the moment is the overtaking state;
when the interaction state between the self and the obstacle at the historical moment is the overtaking state, determining that the interaction state between the self and the obstacle is in the overtaking state
Figure 298904DEST_PATH_IMAGE091
The interactive state of the time is an neglected state, and the historical time is
Figure 459364DEST_PATH_IMAGE091
Any time before the time.
In some embodiments, the interaction unit 204 is specifically configured to perform the following steps:
determining the interaction state between the self and the barrier at the historical moment;
when the interaction state between the self and the obstacle at the historical moment is a contact state, determining that the self and the obstacle are in the contact state
Figure 129380DEST_PATH_IMAGE091
The interactive state at the moment is the overtaking state.
In some embodiments, the interaction unit 204 is specifically configured to perform the following steps:
determining an obstacle type of the obstacle;
determine the obstacle in
Figure 712808DEST_PATH_IMAGE091
The speed of the moment;
when the type of the obstacle is the first type and the obstacle is at
Figure 759262DEST_PATH_IMAGE091
Determining whether the speed is lower than a preset speed threshold value
Figure 10114DEST_PATH_IMAGE091
The interaction state at the moment is a contact state.
In some embodiments, the interaction unit 204 is specifically configured to perform the following steps:
is determined to be
Figure 851031DEST_PATH_IMAGE090
Limiting the speed of the moment;
determining a shift time from a predetermined acceleration, the shift time being indicative of a slave shift
Figure 187335DEST_PATH_IMAGE090
The self-movement speed of the moment is changed to
Figure 771900DEST_PATH_IMAGE091
The time required for limiting the speed of the moment;
determining
Figure 877259DEST_PATH_IMAGE091
Time and
Figure 390542DEST_PATH_IMAGE090
the time difference between the moments;
when the speed change time is larger than the time difference, according to the time difference,
Figure 214142DEST_PATH_IMAGE090
Of time of dayThe self-movement speed and the self-position are obtained
Figure 336819DEST_PATH_IMAGE091
A first position of a time relative to an origin;
when the speed change time is not more than the time difference, according to the time difference, the speed change time,
Figure 827843DEST_PATH_IMAGE090
The self-movement speed and the self-position of the moment are obtained
Figure 744983DEST_PATH_IMAGE091
A first position of the time relative to the origin.
In some embodiments, the interaction unit 204 is specifically configured to perform the following steps:
is determined at
Figure 55879DEST_PATH_IMAGE091
The self-movement speed of the moment;
according to the time difference,
Figure 716667DEST_PATH_IMAGE090
The self-movement speed of the moment and
Figure 62198DEST_PATH_IMAGE091
determining a first position increment according to the self-movement speed of the moment;
based on a first position increment and
Figure 415819DEST_PATH_IMAGE090
self-position of time, determining
Figure 214011DEST_PATH_IMAGE091
A first position of time.
In some embodiments, the interaction unit 204 is specifically configured to perform the following steps:
is determined at
Figure 200463DEST_PATH_IMAGE091
The self-movement speed of the moment;
according to the speed change time,
Figure 400500DEST_PATH_IMAGE090
The self-movement speed of the moment and
Figure 659443DEST_PATH_IMAGE091
determining a second position increment based on the self-movement speed of the moment;
according to the sum of the speed change time and the time difference
Figure 944931DEST_PATH_IMAGE091
Determining a third position increment according to the self-movement speed of the moment;
based on the second position increment, the third position increment and
Figure 213101DEST_PATH_IMAGE090
self-position of time, determining
Figure 267645DEST_PATH_IMAGE091
A first position of time.
In some embodiments, the obstacle motion state of the obstacle includes heading and obstacle speed; the interaction unit 204 is configured to perform the following steps:
determining the minimum distance between the boundary point of the obstacle and the origin and the maximum distance between the boundary point of the obstacle and the origin;
projecting the speed of the obstacle along a reference line according to the orientation of the obstacle to obtain a speed component;
according to the velocity component,
Figure 963068DEST_PATH_IMAGE091
Determining a second minimum distance according to the minimum distance between the moment and the boundary point of the obstacle;
according to the velocity component,
Figure 470273DEST_PATH_IMAGE091
Of the time and the boundary point of the obstacleThe maximum distance determines the second maximum distance.
In a specific implementation, the above units may be implemented as independent entities, or may be combined arbitrarily to be implemented as the same or several entities, and the specific implementation of the above units may refer to the foregoing method embodiments, which are not described herein again.
In the invention, the intelligent automobile can screen out the obstacles needing to be bypassed from the traffic participation objects according to the driving intention of the obstacles; projecting the barrier to a road reference coordinate system to obtain a static boundary point set; then, in an evaluation period, predicting the interaction state between the intelligent automobile and the bypassing obstacle according to the static boundary point set and the state information of the intelligent automobile; and constructing a dynamic boundary point set according to the interaction state, and using the dynamic boundary point set considering the interaction condition for path planning to obtain a planned path of the intelligent automobile. Therefore, the driving efficiency of the intelligent automobile is improved.
The embodiment of the invention also provides the electronic equipment which can be equipment such as a vehicle-mounted terminal, a server and the like.
In some embodiments, the path planning apparatus may also be integrated in a plurality of electronic devices, for example, the path planning apparatus may be integrated in a plurality of servers, and the path planning method of the present invention is implemented by the plurality of servers.
In this embodiment, a detailed description will be given by taking an example that the electronic device of this embodiment is an intelligent driver, for example, as shown in fig. 3, it shows a schematic structural diagram of the intelligent driver according to an embodiment of the present invention, specifically:
the smart pilot may include components such as a processor 301 of one or more processing cores, memory 302 of one or more computer-readable storage media, a power source 303, an input module 304, and a communication module 305. Those skilled in the art will appreciate that the smart driver configuration shown in FIG. 3 does not constitute a limitation of the smart driver and may include more or fewer components than shown, or some components in combination, or a different arrangement of components. Wherein:
the processor 301 is a control center of the intelligent driver, connects various parts of the whole intelligent driver by using various interfaces and lines, and executes various functions and processes data of the intelligent driver by running or executing software programs and/or modules stored in the memory 302 and calling data stored in the memory 302, thereby performing overall monitoring of the intelligent driver. In some embodiments, processor 301 may include one or more processing cores; in some embodiments, processor 301 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 301.
The memory 302 may be used to store software programs and modules, and the processor 301 executes various functional applications and data processing by operating the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the smart driver, and the like. Further, the memory 302 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.
The smart pilot further includes a power supply 303 for supplying power to the various components, and in some embodiments, the power supply 303 may be logically connected to the processor 301 through a power management system, so as to manage charging, discharging, and power consumption management functions through the power management system. The power supply 303 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
The smart pilot may also include an input module 304, the input module 304 operable to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
The smart driver may also include a communication module 305, and in some embodiments the communication module 305 may include a wireless module, through which the smart driver may wirelessly transmit over short distances to provide wireless broadband internet access to the user. For example, the communication module 305 may be used to assist a user in emailing, browsing web pages, accessing streaming media, and the like.
Although not shown, the smart pilot may further include a display unit and the like, which will not be described in detail herein. Specifically, in this embodiment, the processor 301 in the smart driver loads an executable file corresponding to a process of one or more application programs into the memory 302 according to the following instructions, and the processor 301 runs the application programs stored in the memory 302, thereby implementing various functions as follows:
acquiring driving intention information, self state information and environment information, and determining a road reference coordinate system, wherein the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects;
screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system;
determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period;
and planning the path according to the dynamic boundary point set to obtain a planned path.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
Therefore, in the invention, the intelligent automobile can screen the obstacles needing to be bypassed from the traffic participation objects according to the driving intention of the obstacles; projecting the barrier to a road reference coordinate system to obtain a static boundary point set; then, in an evaluation period, predicting the interaction state between the intelligent automobile and the bypassing obstacle according to the static boundary point set and the state information of the intelligent automobile; and constructing a dynamic boundary point set according to the interaction state, and using the dynamic boundary point set considering the interaction condition for path planning to obtain a planned path of the intelligent automobile. Therefore, the driving efficiency of the intelligent automobile is improved.
It will be understood by those skilled in the art that all or part of the steps in the methods of the above embodiments may be performed by instructions or by related hardware controlled by the instructions, which may be stored in a readable storage medium and loaded and executed by a processor.
To this end, the present invention provides a readable storage medium, in which a plurality of instructions are stored, where the instructions can be loaded by a processor to execute the steps in any one of the path planning methods provided by the embodiments of the present invention. For example, the instructions may perform the steps of:
acquiring driving intention information, self state information and environment information, and determining a road reference coordinate system, wherein the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects;
screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
projecting the bypassing obstacle in a road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system;
determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in a preset evaluation period;
planning the path according to the dynamic boundary point set to obtain a planned path
Wherein the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the storage medium can execute the steps in any of the path planning methods provided in the embodiments of the present invention, the beneficial effects that can be achieved by any of the path planning methods provided in the embodiments of the present invention can be achieved, which are detailed in the foregoing embodiments and will not be described herein again.
The path planning method, apparatus, device and readable storage medium provided by the embodiments of the present invention are described in detail above, and a specific example is applied in the present disclosure to explain the principle and the implementation of the present invention, and the description of the above embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (12)

1. A method of path planning, comprising:
acquiring driving intention information, self state information and environment information, and determining a road reference coordinate system, wherein the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects;
screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
projecting the bypassing obstacle in the road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system;
determining an interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in the preset evaluation period;
and planning a path according to the dynamic boundary point set to obtain a planned path.
2. The path planning method according to claim 1, wherein the environment information includes an obstacle motion state of the detour obstacle, the set of static boundary points of the detour obstacle includes boundary points of the obstacle, the self-state information includes a self-motion speed and a self-position, the self-position includes a distance from an origin of a reference line in the road reference coordinate system, and the preset evaluation period includes a plurality of time instants;
the determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information comprises:
according to
Figure DEST_PATH_IMAGE001
The self-movement speed and the self-position of the moment are predicted
Figure DEST_PATH_IMAGE002
A first position of a time relative to the origin;
predicting the obstacle at the obstacle according to the obstacle motion state and the boundary point of the obstacle
Figure 651470DEST_PATH_IMAGE002
A second position of the time relative to the origin;
according to the above
Figure 99769DEST_PATH_IMAGE002
A first position of a moment and the
Figure 145086DEST_PATH_IMAGE002
A second position determination of the moment between itself and the obstacle
Figure 71453DEST_PATH_IMAGE002
The interaction state at the moment.
3. The path planning method according to claim 2, wherein the second position includes a second minimum distance and a second maximum distance, the second minimum distance being a minimum distance from the origin among the boundary points of the obstacle, the second maximum distance being a maximum distance from the origin among the boundary points of the obstacle;
according to the above
Figure 151405DEST_PATH_IMAGE002
A first position of a moment and the
Figure 3561DEST_PATH_IMAGE002
A second position determination of the moment between itself and the obstacle
Figure 801753DEST_PATH_IMAGE002
The interaction state of the moment comprises:
determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than a first distance threshold
Figure 531811DEST_PATH_IMAGE002
The interaction state at the moment is a proximity state;
determining that there is a difference between itself and the obstacle when the difference between the second minimum distance and the first position is less than a second distance threshold
Figure 731848DEST_PATH_IMAGE002
The interaction state at the moment is a contact state;
determining that there is a difference between itself and the obstacle when the difference between the first location and the second maximum distance is greater than a third distance threshold
Figure 990791DEST_PATH_IMAGE002
The interactive state at the moment is the overtaking state;
determining that the interaction state between the obstacle and the self is in the overtaking state when the interaction state between the obstacle and the self at the historical moment is in the overtaking state
Figure 276279DEST_PATH_IMAGE002
The interactive state of the time is an neglected state, and the historical time is the history time
Figure 278870DEST_PATH_IMAGE002
Any time before the time.
4. A path planning method according to claim 3 in which the determination is between itself and the obstacle
Figure 333414DEST_PATH_IMAGE002
The interactive state at the moment is a overtaking state, and comprises the following steps:
determining the interaction state between the obstacle and the self at the historical moment;
determining that the interaction state between the self and the obstacle at the historical moment is a contact state when the interaction state between the self and the obstacle at the historical moment is a contact state
Figure 294417DEST_PATH_IMAGE002
The interactive state at the moment is the overtaking state.
5. A path planning method according to claim 3 in which the determination itself and the determination location are determinedBetween said obstacles
Figure 568666DEST_PATH_IMAGE002
The interaction state at the moment is a contact state, and comprises the following steps:
determining an obstacle type of the obstacle;
determining that the obstacle is at the
Figure 109368DEST_PATH_IMAGE002
The speed of the moment;
when the type of the obstacle is a first type and the obstacle is in the first type
Figure 283998DEST_PATH_IMAGE002
Determining that the distance between the obstacle and the obstacle is less than a predetermined threshold value
Figure 884743DEST_PATH_IMAGE002
The interaction state at the moment is a contact state.
6. A path planning method according to claim 2 in which said basis is
Figure DEST_PATH_IMAGE003
The self-movement speed and the self-position of the moment are predicted
Figure 410403DEST_PATH_IMAGE002
A first position of a time relative to the origin, comprising:
determine itself in said
Figure 20375DEST_PATH_IMAGE003
Limiting the speed of the moment;
determining a shift time from a preset acceleration, the shift time being indicative of a time from the preset acceleration
Figure 49511DEST_PATH_IMAGE003
The self-movement speed of the moment is changed to
Figure 86738DEST_PATH_IMAGE003
The time required for limiting the speed of the moment;
determining the
Figure 568534DEST_PATH_IMAGE002
Time of day and
Figure 716619DEST_PATH_IMAGE003
the time difference between the moments;
when the speed change time is larger than the time difference value, the speed change time is based on the time difference value and the time difference value
Figure 98797DEST_PATH_IMAGE003
The self-movement speed and the self-position of the moment are obtained
Figure 572503DEST_PATH_IMAGE002
A first position of a time relative to the origin;
when the speed change time is not more than the time difference value, the speed change time is determined according to the time difference value, the speed change time and the speed change time
Figure 541596DEST_PATH_IMAGE003
The self-movement speed and the self-position of the moment are obtained
Figure 493372DEST_PATH_IMAGE002
A first position of a time relative to the origin.
7. A path planning method according to claim 6 in which said time difference is a function of said time difference
Figure 231521DEST_PATH_IMAGE003
Speed and self-movement of timeBody position obtained at
Figure 876129DEST_PATH_IMAGE002
A first position of a time relative to the origin, comprising:
is determined at
Figure 332518DEST_PATH_IMAGE002
The self-movement speed of the moment;
according to the time difference value, the
Figure 822405DEST_PATH_IMAGE003
The speed of the movement of the moment itself and the said
Figure 415060DEST_PATH_IMAGE002
Determining a first position increment according to the self-movement speed of the moment;
according to the first position increment and the
Figure 732034DEST_PATH_IMAGE003
The self position of the moment of time, determining the
Figure 410140DEST_PATH_IMAGE002
A first position of time.
8. The path planning method according to claim 6, wherein said time difference is based on said time difference, said shift time, and said
Figure 969298DEST_PATH_IMAGE003
The self-movement speed and the self-position of the moment are obtained
Figure 416460DEST_PATH_IMAGE002
A first position of a time relative to the origin, comprising:
is determined at
Figure 137291DEST_PATH_IMAGE002
The self-movement speed of the moment;
according to the speed change time and the speed change time
Figure 568272DEST_PATH_IMAGE003
The speed of the movement of the moment itself and the said
Figure 399962DEST_PATH_IMAGE002
Determining a second position increment based on the self-movement speed of the moment;
according to the speed change time, the time difference value and the speed change time
Figure 232789DEST_PATH_IMAGE002
Determining a third position increment according to the self-movement speed of the moment;
according to the second position increment, the third position increment and the
Figure 124521DEST_PATH_IMAGE003
The self position of the moment of time, determining the
Figure 541334DEST_PATH_IMAGE002
A first position of time.
9. The path planning method according to claim 3, wherein the obstacle motion state of the obstacle includes a heading and an obstacle speed, and the obstacle is predicted to be present at the obstacle based on the obstacle motion state of the obstacle and a boundary point of the obstacle
Figure 442294DEST_PATH_IMAGE002
A second position of the time relative to the reference line, comprising:
determining a minimum distance from the origin among the boundary points of the obstacle and a maximum distance from the origin among the boundary points of the obstacle;
projecting the speed of the obstacle along the reference line according to the orientation of the obstacle to obtain a speed component;
according to said velocity component, said
Figure 598469DEST_PATH_IMAGE002
Determining a second minimum distance according to the minimum distance between the moment and the boundary point of the obstacle;
according to said velocity component, said
Figure 926682DEST_PATH_IMAGE002
The maximum distance between the time and the boundary point of the obstacle determines a second maximum distance.
10. A path planning apparatus, comprising:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring driving intention information, self state information and environment information, and determining a road reference coordinate system, the environment information comprises information of traffic participation objects on a driving road, and the driving intention information is used for representing driving intentions of the traffic participation objects;
the screening unit is used for screening out at least one bypassing obstacle from the traffic participation objects according to the driving intention information;
the projection unit is used for projecting the bypassing obstacle in the road reference coordinate system to obtain a static boundary point set of the bypassing obstacle in the road reference coordinate system;
the interaction unit is used for determining the interaction state between the self and the bypassing obstacle in a preset evaluation period according to the static boundary point set of the bypassing obstacle and the self state information;
the construction unit is used for constructing a dynamic boundary point set according to the interaction state between the self and the bypassing obstacle in the preset evaluation period;
and the planning unit is used for planning a path according to the dynamic boundary point set to obtain a planned path.
11. An electronic device comprising a processor and a memory, the memory storing a plurality of instructions; the processor loads instructions from the memory to perform the steps of the path planning method according to any of claims 1 to 9.
12. A computer readable storage medium storing instructions adapted to be loaded by a processor to perform the steps of the path planning method according to any one of claims 1 to 9.
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