CN113587950A - Method and device for planning static path of automatic driving automobile and storage medium - Google Patents

Method and device for planning static path of automatic driving automobile and storage medium Download PDF

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CN113587950A
CN113587950A CN202110990214.8A CN202110990214A CN113587950A CN 113587950 A CN113587950 A CN 113587950A CN 202110990214 A CN202110990214 A CN 202110990214A CN 113587950 A CN113587950 A CN 113587950A
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intersection
automatic driving
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feature points
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CN113587950B (en
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李升波
余冬杰
任彦刚
关阳
成波
占国建
兰志前
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Tsinghua University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492—Special 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

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Abstract

The present disclosure provides a method, an apparatus and a storage medium for planning a static path of an autonomous vehicle, including: selecting a plurality of groups of feature points according to the road topology of the intersection and the number of expected exits of the driving route in the intersection, wherein the number of the groups of the feature points is consistent with the number of the expected exits, and each group of the feature points comprises a plurality of intersection internal feature points and intersection external feature points; inputting a plurality of groups of feature points into a path calculation function to obtain corresponding different candidate static continuous paths; and setting an expected passing rate and an expected stopping rate for each candidate static continuous path, distributing the running rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths, and outputting the finally planned static discrete paths. The method provides a plurality of candidate paths for decision control tasks such as automatic driving automobile path tracking and the like, and ensures high calculation efficiency in online application.

Description

Method and device for planning static path of automatic driving automobile and storage medium
Technical Field
The disclosure belongs to the technical field of decision planning of an automatic driving automobile, and particularly relates to a static path planning method, a static path planning device and a storage medium of the automatic driving automobile.
Background
The automobile intelligent and driving auxiliary system has great potential in the aspects of improving safety, reducing oil consumption, improving traffic efficiency and the like. High-level intelligent driving relies on high real-time decision and control.
The conventional vehicle decision method mainly uses the series connection of submodules such as motion prediction, behavior selection, path planning and the like, and a feasible path is finally obtained after respective operation. However, the flow decomposition method cannot guarantee real-time performance when processing a large-scale dynamic obstacle avoidance task, and the method has poor universality and needs to design different schemes for different scenes.
Disclosure of Invention
The present disclosure is directed to solving one of the problems set forth above.
Therefore, the static path planning method for the autonomous vehicle, which is suitable for intersections, can provide a plurality of candidate paths for decision control tasks such as path tracking of the autonomous vehicle and the like and ensures high calculation efficiency in online application, provided by the embodiment of the first aspect of the disclosure, includes:
selecting a plurality of groups of feature points according to the road topology of the intersection and the number of expected exits of the driving route in the intersection, wherein the number of the groups of the feature points is consistent with the number of the expected exits, and each group of the feature points comprises a plurality of intersection internal feature points and a plurality of intersection external feature points;
inputting a plurality of groups of feature points into a path calculation function to obtain corresponding different candidate static continuous paths;
and setting an expected passing rate and an expected stopping rate for each candidate static continuous path, distributing the running rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths, and outputting the finally planned static discrete paths.
The method for planning the static path of the automatic driving automobile provided by the embodiment of the first aspect of the disclosure has the following characteristics and beneficial effects:
according to the method, only static traffic information such as road topology structures and traffic rules is considered when the route of the automatic driving automobile is planned, and a plurality of candidate routes and corresponding expected speeds are planned through the road topology in the scene of the intersection.
Static traffic information is only considered in static path planning, dynamic barriers are not considered, static paths and expected speeds can be generated in advance, and candidate path information is directly acquired during driving for subsequent tracking control and other purposes, so that the method has the characteristics of high-efficiency online calculation and strong expansibility.
In some embodiments, the intersection external feature points are selected according to the following steps:
setting the expected exit number of the driving route in the intersection as the number N of candidate static continuous paths, and recording the midpoint coordinates of the lane start lines of the N expected exits as X1，4，X2，4，...，Xi，4，...，XN，4I ∈ {1, 2, 3,..., N }; recording the coordinate of the middle point of a lane stop line of an entrance where an automatic driving automobile is positioned as X1Copying N times to X1，1，X2，1，...，Xi，1，...，XN，1(ii) a From Xi，1The departure is moved in the opposite direction to the entry lane of the autonomous vehicle1Obtaining X1，0，X2，0，...，Xi，0，...，XN，0(ii) a From Xi，4The departure is moved by a distance l in the direction of travel parallel to the exit lane2Obtaining X1，5，X2，5，...，Xi，5，...，XN，5(ii) a Selecting Xi，0、Xi，1、Xi，4And Xi，5And the corresponding feature point is used as the external feature point of the intersection of the ith candidate static continuous path.
In some embodiments, the characteristic points inside the intersection are selected according to the following steps:
setting the coordinates of the characteristic points in the crossroad of the ith candidate static continuous path as Xi，2And Xi，3Selecting the internal feature points of the intersection according to the following formula:
Figure BDA0003232049070000021
Figure BDA0003232049070000022
wherein, theta1Is the angle between the driving direction of the entrance lane and the horizontal axis of the coordinate axis of the intersection, thetai，2And the included angle between the driving direction of the ith candidate exit lane and the horizontal axis of the coordinate axis of the intersection is shown.
In some embodiments, each intersection internal feature point and each intersection external feature point are classified according to N expected exits to obtain feature point groups of N candidate paths
Figure BDA0003232049070000023
In some embodiments, for the ith candidate static continuous path, it will be at Xi，0And Xi，1Path between, at Xi，1And Xi，4Path between and at Xi，4And Xi，5The paths between are respectively noted
Figure BDA0003232049070000024
And
Figure BDA0003232049070000025
the path computation functions used are respectively as follows:
Figure BDA0003232049070000026
Figure BDA0003232049070000031
wherein, t1、t2And t3Are respectively and
Figure BDA0003232049070000032
and
Figure BDA0003232049070000033
corresponding parameters;
will be provided with
Figure BDA0003232049070000034
And
Figure BDA0003232049070000035
sequentially connected end to form a static continuous path of the ith intersection
Figure BDA0003232049070000036
In some embodiments, the allocating a driving rate to the autonomous vehicle according to the current state of the autonomous vehicle and the phase of the signal lamp specifically includes:
3-1-1) autopilot from automobile Xi，0If the automobile is driven to X in the automatic drivingi，1Previously, the signal light was always green, or the signal light was always yellow and the autonomous vehicle could be driven beyond the stop line for the remaining yellow time, then the autonomous vehicle was set to drive to X at the desired traffic ratei，1Executing step 3-1-2); if the automobile is driven to X in the automatic drivingi，1Previously, the signal light was always red, or the signal light was yellow and the autonomous vehicle could not travel beyond the stop line for the remaining yellow time, then the autonomous vehicle was set to travel to X at the desired stop ratei，1Executing step 3-1-2); if the automobile is driven to X in the automatic drivingi，1Before, the phase of the signal lamp is changed, the driving speed of the automatic driving automobile is jumped to the expected stopping speed or the expected passing speed when the phase of the signal lamp is changed until the automatic driving automobile drives to Xi，1Executing step 3-1-2);
3-1-2) autopilot vehicle at Xi，1If the signal lamp is yellow or green, the automatic driving automobile is set to drive to X at the expected traffic speedi，5(ii) a If the signal lamp is red, the automatic driving automobile is set to drive at the expected stopping speed until the signal lamp is changed into green, and the automatic driving automobile is set to drive to X at the expected passing speedi，5。
In some embodiments, the candidate paths containing the speed information of the automatic driving automobile are discretized by means of equal time distance or equal space distance.
The static path planning device for the automatic driving automobile provided by the embodiment of the second aspect of the disclosure comprises:
the characteristic point selection module is used for selecting a plurality of groups of characteristic points according to the road topology of the intersection and the expected exit number of the driving route in the intersection, the group number of the characteristic points is consistent with the expected exit number, and each group of the characteristic points comprises a plurality of intersection internal characteristic points and a plurality of intersection external characteristic points;
the path calculation module is used for inputting a path calculation function by a plurality of groups of feature points to obtain corresponding different candidate static continuous paths; and
and the discrete processing module is used for setting an expected passing rate and an expected stopping rate for each candidate static continuous path, distributing a driving rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths and outputting the finally planned static discrete paths.
A storage medium provided in an embodiment of a third aspect of the present disclosure is characterized in that the computer-readable storage medium stores computer instructions, where the computer instructions are configured to cause the computer to execute the above static path planning method for an autonomous vehicle.
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Fig. 1 is an overall flowchart of a static path planning method for an autonomous vehicle according to an embodiment of the first aspect of the disclosure;
fig. 2 is a schematic diagram of static path planning according to an embodiment of the first aspect of the disclosure;
fig. 3 (a), (b), and (c) are static continuous path planning results corresponding to left turn, straight going, and right turn, respectively, in the first aspect of the present disclosure;
FIG. 4 is a graph of two types of expected rates selected in an embodiment of the first aspect of the present disclosure;
FIG. 5 is a schematic diagram of a desired rate hopping state machine employed in an embodiment of a first aspect of the present disclosure;
fig. 6 (a) and (b) are schematic diagrams of two continuous path discretization methods adopted in the embodiment of the first aspect of the disclosure;
fig. 7 is a schematic structural diagram of a static path planning apparatus for an autonomous vehicle according to an embodiment of the second aspect of the present disclosure;
fig. 8 is a schematic structural diagram of an electronic device provided in an embodiment of a third aspect of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
On the contrary, this application is intended to cover any alternatives, modifications, equivalents, and alternatives that may be included within the spirit and scope of the application as defined by the appended claims. Furthermore, in the following detailed description of the present invention, certain specific details are set forth in order to provide a better understanding of the present application. It will be apparent to one skilled in the art that the present application may be practiced without these specific details.
Referring to fig. 1, the method for planning the static path of the autonomous vehicle provided by the embodiment of the disclosure includes the following steps:
selecting a plurality of groups of feature points according to the road topology of the intersection and the number of expected exits of the driving route in the intersection, wherein the number of the groups of the feature points is consistent with the number of the expected exits, and each group of the feature points comprises a plurality of intersection internal feature points and a plurality of intersection external feature points;
inputting the obtained multiple groups of feature points into a path calculation function to obtain corresponding different candidate static continuous paths;
and setting an expected passing rate and an expected stopping rate for each obtained candidate static continuous path, distributing the running rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths, and outputting the finally planned static discrete paths.
The static path planning method for the automatic driving automobile, provided by the embodiment of the disclosure, is suitable for an intersection scene, and is shown in fig. 2. In the embodiment, according to the road topology of the intersection and the number of expected exits of the driving route, the corresponding number of groups of feature points is calculated, which specifically comprises the following steps:
1-1) selecting external feature points of the intersection: setting the number N of expected exits (namely the number of feasible exits in the planned passing direction of the intersection scene) of the driving route in the intersection as the number of candidate static continuous paths, and recording the coordinates of the middle points of the start lines of the lanes of the N expected exits as X1，4，X2，4，...，Xi，4，...，XN，4I ∈ {1, 2, 3.,. N }. Recording the coordinate of the middle point of a lane stop line of an entrance where an automatic driving automobile is positioned as X1Copying N times to X1，1，X2，1，...，Xi，1，...，XN，1. From Xi，1The departure is moved in the opposite direction to the entry lane of the autonomous vehicle1(the distance value is judged according to the length of the straight road, usually 10-30m) to obtain X1，0，X2，0，...，Xi，0，...，XN，0(ii) a From Xi，4The starting point moves a certain distance l along the driving direction of the parallel exit lane2(the value ranges are the same as l1) Obtaining X1，5，X2，5，...，Xi，5，...，XN，5。
1-2) selecting internal feature points of the intersection: according to the intersectionAnd (4) road topology, and calculating the characteristic points of each characteristic point group in the intersection. The internal characteristic points are selected according to the following rules: get
Figure BDA0003232049070000051
Trisection point P, Q, respectively toward Xi，0Xi，1And Xi，4Xi，sMaking a perpendicular line to obtain the internal characteristic points of the intersection, and respectively marking the coordinates as Xi，2、Xi，3The specific calculation formula is as follows:
Figure BDA0003232049070000052
wherein, theta1Is the angle between the driving direction of the entrance lane and the horizontal axis of the coordinate axis of the intersection, thetai，2And the included angle between the driving direction of the ith candidate exit lane and the horizontal axis of the coordinate axis of the intersection is shown.
1-3) classifying the internal characteristic points and the external characteristic points of each intersection according to N expected exits to obtain a characteristic point group of N candidate paths
Figure BDA0003232049070000053
As shown in fig. 2. Hereinbefore Xi，jIs a two-dimensional vector, i.e.
Figure BDA0003232049070000054
The jth feature point representing the ith candidate path, and the superscript (k) representing the kth component of the vector. The value range of i is {1, 2.., N }, and N is the number of expected exits of the driving route of the self-vehicle; the value range of j is {0, 1, 2.., 5 }.
In some embodiments, the method includes inputting the obtained multiple groups of feature points into a bezier curve path computation function to obtain corresponding different candidate static continuous paths, and specifically includes the following steps:
2-1) calculating the internal path of the intersection: for each set of feature points, the static continuous path inside the intersection is calculated as follows:
Figure BDA0003232049070000061
wherein the content of the first and second substances,
Figure BDA0003232049070000062
representing the intersection internal path segment of the ith candidate static continuous path, wherein i belongs to {1, 2, 3.., N }; t is t2Is the road junction internal path section parameter.
2-2) splicing external paths of the intersection: straight line lane sections outside the intersection are directly connected to obtain a straight line section path:
Figure BDA0003232049070000063
wherein the content of the first and second substances,
Figure BDA0003232049070000064
a first intersection external path segment that is the ith candidate static continuous path,
Figure BDA0003232049070000065
i belongs to {1, 2, 3.,. N }, which is a second intersection external path segment of the ith candidate static continuous path; t is t1And t3Respectively, a first intersection external path section parameter and a second intersection external path section parameter.
Three continuous smooth paths are formed according to
Figure BDA0003232049070000066
Are connected end to obtain N continuous smooth static continuous paths of the intersection
Figure BDA0003232049070000067
In some embodiments, the planned static continuous paths corresponding to left turn, straight line, and right turn are shown in fig. 3 (a), (b), and (c), respectively.
In some embodiments, step 3) comprises the steps of:
3-1) path rate curve setting: driving an autonomous vehicle to Xi，0Recording the speed as an initial speed, and starting to set the expected speed of the automatic driving automobile for the static continuous path planned in the step 2). As shown in FIG. 4, there are two rate profiles to choose from, including a desired rate of traffic at which the autonomous vehicle is expected to continue traveling and a desired rate of stopping at which the autonomous vehicle is expected to stop. Each time a discrete time step t has elapsed0(common values are 0.1s and 0.05s), and the driving speed of the automatic driving automobile is selected according to the jump relation of the finite-state machine in the figure 5. The state jump judgment rule comprises A-signal lamp phase and B-if A is in yellow light, whether the driving can exceed the stop line in the residual yellow light time. The rule A comprises that the current signal lamp is at a red lamp, the current signal lamp is at a green lamp and the current signal lamp is at a yellow lamp, which are respectively marked as A-red, A-green and A-yellow; rule B includes that the autonomous vehicle can travel beyond the stop line for the remaining yellow light time and that the autonomous vehicle cannot travel beyond the stop line for the remaining yellow light time, noted B-yes and B-no, respectively. The method for judging whether the vehicle can run over the stop line is commonly used in a constant-speed recursion model: if tyellow×vcurrent≥dstopIf so, then a determination is made that the stop line can be crossed, otherwise no, where tyellowFor the remaining yellow lamp time, vcurrentFor the current vehicle speed, dstopTo automatically drive the distance of the car to the stop-line.
Automatically driving the vehicle to Xi，0And carrying out expected rate selection and jumping according to the rule as shown in FIG. 4:
3-1-1) autopilot from automobile Xi，0If the automobile is driven to X in the automatic drivingi，1Previously, the state was always A-green, or (shown as "OR" in "|" -FIG. 5) A-yellow and (in FIG. 5 "&&"shown as" and ") B-is, then the autonomous vehicle is set to travel to X at the desired rate of passagei，1Executing step 3-1-2); if the automobile is driven to X in the automatic drivingi，1Before, the state was always A-Red, or A-yellow and B-No, then the auto-driven vehicle was set to travel to X at the desired stopping ratei，1Executing step 3-1-2); if the automobile is automatically drivenTravel to Xi，1Before the state is changed, the running speed of the automatic driving automobile is jumped to the expected stopping speed or the expected passing speed when the state is changed until the automatic driving automobile runs to Xi，1Step 3-1-2) is performed.
3-1-2) if the current state is A-yellow or A-green, setting the automatic driving automobile to drive to X at the expected traffic speedi，5(ii) a If the current state is A-red, the automatic driving automobile is set to drive at the expected stopping speed until the current state is A-green, and the automatic driving automobile is set to drive to X at the expected passing speedi，5。
3-2) path discretization output: after the static continuous path and the corresponding rate are obtained according to the above steps, in order to save the calculation time and space consumption of the path, the continuous path needs to be discretized. Common path discretization methods include equal time distance discretization and equal space distance discretization, which are described below:
a) referring to fig. 6 (a), the equal time distance dispersion method: the method expects the vehicle to pass through any two adjacent path points at the same time, and the time is defined as delta t (the common value is 0.01 s). According to the desired velocity curve, the desired velocities v at different spatial positions can be obtainedref. At the starting point X of the pathi，0As the first discrete path point
Figure BDA0003232049070000071
Looking up the expected rate curve to obtain
Figure BDA0003232049070000072
Then the next path point
Figure BDA0003232049070000073
Of (2) is
Figure BDA0003232049070000074
Then according to
Figure BDA0003232049070000075
Is obtained by searching the expected speed curve
Figure BDA0003232049070000076
Further obtain
Figure BDA0003232049070000077
Angle determines next path point
Figure BDA0003232049070000078
Recursion is carried out until a discrete path point sequence is obtained
Figure BDA0003232049070000079
From the starting point, finding the next point on the continuous path at a distance Δ may use a numerical solution or the like to obtain an approximate numerical solution.
b) Referring to fig. 6 (b), the iso-spatial distance dispersion method: at the starting point X of the pathi，0As the first discrete path point
Figure BDA00032320490700000710
Directly solving the next discrete point with the curve distance delta tau on the continuous path by a numerical calculation method
Figure BDA00032320490700000711
Recalculating distance
Figure BDA00032320490700000712
Is the next discrete point of Δ τ
Figure BDA00032320490700000713
Repeating recursion until obtaining discrete path point sequence
Figure BDA00032320490700000714
In the above-mentioned context,
Figure BDA00032320490700000715
for the p-th discrete point on the ith path,
Figure BDA00032320490700000716
as a waypoint
Figure BDA00032320490700000717
The corresponding desired rate of the rate of change,
according to the static discrete path obtained by the discretization method, the expected speed of each path point is obtained from the expected speed curve
Figure BDA0003232049070000081
Calculating the waypoints according to
Figure BDA0003232049070000082
Desired vehicle heading angle
Figure BDA0003232049070000083
Figure BDA0003232049070000084
The paths output by the static path planning method are arranged according to the sequence of the path points
Figure BDA0003232049070000085
The expected speed and the vehicle heading angle of the N candidate static discrete paths and the corresponding discrete points are total, and each path comprises M discrete points.
The static path planning device for the automatic driving automobile provided by the embodiment of the disclosure has a structure shown in fig. 7, and comprises:
the characteristic point selection module is used for selecting a plurality of groups of characteristic points according to the road topology of the intersection and the expected exit number of the driving route in the intersection, the group number of the characteristic points is consistent with the expected exit number, and each group of the characteristic points comprises a plurality of intersection internal characteristic points and a plurality of intersection external characteristic points;
the path calculation module is used for inputting the obtained multiple groups of feature points into a path calculation function to obtain corresponding different candidate static continuous paths; and
and the discrete processing module is used for setting an expected passing rate and an expected stopping rate for each obtained candidate static continuous path, distributing a driving rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths and outputting the finally planned static discrete paths.
In order to implement the foregoing embodiments, the present disclosure further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to execute the method for planning a static path of an autonomous vehicle according to the foregoing embodiments.
Referring now to FIG. 8, a block diagram of an electronic device 100 suitable for use in implementing embodiments of the present disclosure is shown. It should be noted that the electronic device 100 includes an autonomous driving vehicle static path planning system, wherein the electronic device in the embodiment of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a vehicle navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, a server, and the like. The electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 8, the electronic device 100 may include a processing means (e.g., a central processing unit, a graphic processor, etc.) 101 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)102 or a program loaded from a storage means 108 into a Random Access Memory (RAM) 103. In the RAM 103, various programs and data necessary for the operation of the electronic apparatus 100 are also stored. The processing device 101, the ROM 102, and the RAM 103 are connected to each other via a bus 104. An input/output (I/O) interface 105 is also connected to bus 104.
Generally, the following devices may be connected to the I/O interface 105: input devices 106 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, etc.; an output device 107 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 108 including, for example, magnetic tape, hard disk, etc.; and a communication device 109. The communication means 109 may allow the electronic device 100 to communicate wirelessly or by wire with other devices to exchange data. While fig. 5 illustrates an electronic device 100 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, the present embodiments include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 109, or installed from the storage means 108, or installed from the ROM 102. The computer program, when executed by the processing device 101, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: selecting a plurality of groups of feature points according to the road topology of the intersection and the number of expected exits of the driving route in the intersection, wherein the number of the groups of the feature points is consistent with the number of the expected exits, and each group of the feature points comprises a plurality of intersection internal feature points and a plurality of intersection external feature points; inputting the obtained multiple groups of feature points into a path calculation function to obtain corresponding different candidate static continuous paths; and setting an expected passing rate and an expected stopping rate for each obtained candidate static continuous path, distributing the running rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths, and outputting the finally planned static discrete paths.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, python, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by a program instructing associated hardware to complete, and the developed program may be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (9)

1. A static path planning method for an automatic driving automobile is characterized by comprising the following steps:
selecting a plurality of groups of feature points according to the road topology of the intersection and the number of expected exits of the driving route in the intersection, wherein the number of the groups of the feature points is consistent with the number of the expected exits, and each group of the feature points comprises a plurality of intersection internal feature points and a plurality of intersection external feature points;
inputting a plurality of groups of feature points into a path calculation function to obtain corresponding different candidate static continuous paths;
and setting an expected passing rate and an expected stopping rate for each candidate static continuous path, distributing the running rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths, and outputting the finally planned static discrete paths.
2. The method of claim 1, wherein the intersection exterior feature points are selected according to the following steps:
setting the expected exit number of the driving route in the intersection as the number N of candidate static continuous paths, and recording the midpoint coordinates of the lane start lines of the N expected exits as X1，4，X2，4，...，Xi，4，...，XN，4I ∈ {1, 2, 3,..., N }; recording the coordinate of the middle point of a lane stop line of an entrance where an automatic driving automobile is positioned as X1Copying N times to X1，1，X2，1，...，Xi，1，...，XN，1(ii) a From Xi，1The departure is moved in the opposite direction to the entry lane of the autonomous vehicle1Obtaining X1，0，X2，0，...，Xi，0，...，XN，0(ii) a From Xi，4The departure is moved by a distance l in the direction of travel parallel to the exit lane2Obtaining X1，5，X2，5，...，Xi，5，...，XN，5(ii) a Selecting Xi，0、Xi，1、Xi，4And Xi，5And the corresponding feature point is used as the external feature point of the intersection of the ith candidate static continuous path.
3. The method of claim 2, wherein the intersection interior feature points are selected according to the following steps:
intersection internal characteristic point coordinate system with ith candidate static continuous pathIs other than Xi，2And Xi，3Selecting the internal feature points of the intersection according to the following formula:
Figure FDA0003232049060000011
Figure FDA0003232049060000012
wherein, theta1Is the angle between the driving direction of the entrance lane and the horizontal axis of the coordinate axis of the intersection, thetai，2And the included angle between the driving direction of the ith candidate exit lane and the horizontal axis of the coordinate axis of the intersection is shown.
4. The method of claim 3, wherein the feature points within each intersection and the feature points outside the intersection are classified according to N prospective exits to obtain a set of feature points for N candidate routes
Figure FDA0003232049060000021
5. The method of claim 4, wherein the ith candidate static continuous path is located at Xi，0And Xi，1Path between, at Xi，1And Xi，4Path between and at Xi，4And Xi，5The paths between are respectively noted
Figure FDA0003232049060000022
And
Figure FDA0003232049060000023
the path computation functions used are respectively as follows:
Figure FDA0003232049060000024
Figure FDA0003232049060000025
wherein, t1、t2And t3Are respectively and
Figure FDA0003232049060000026
and
Figure FDA0003232049060000027
corresponding parameters;
will be provided with
Figure FDA0003232049060000028
And
Figure FDA0003232049060000029
sequentially connected end to form a static continuous path of the ith intersection
Figure FDA00032320490600000210
6. The method for planning the static path of the autonomous vehicle according to claim 4, wherein the step of assigning the driving rate to the autonomous vehicle according to the current state of the autonomous vehicle and the phase of the signal light comprises:
3-1-1) autopilot from automobile Xi，0If the automobile is driven to X in the automatic drivingi，1Previously, the signal light was always green, or the signal light was always yellow and the autonomous vehicle could be driven beyond the stop line for the remaining yellow time, then the autonomous vehicle was set to drive to X at the desired traffic ratei，1Executing step 3-1-2); if the automobile is driven to X in the automatic drivingi，1Previously, signal lights were always red or yellow and self-illuminatingIf the vehicle cannot drive beyond the stop line within the remaining yellow light time, the autonomous vehicle is set to drive to X at the desired stop ratei，1Executing step 3-1-2); if the automobile is driven to X in the automatic drivingi，1Before, the phase of the signal lamp is changed, the driving speed of the automatic driving automobile is jumped to the expected stopping speed or the expected passing speed when the phase of the signal lamp is changed until the automatic driving automobile drives to Xi，1Executing step 3-1-2);
3-1-2) autopilot vehicle at Xi，1If the signal lamp is yellow or green, the automatic driving automobile is set to drive to X at the expected traffic speedi，5(ii) a If the signal lamp is red, the automatic driving automobile is set to drive at the expected stopping speed until the signal lamp is changed into green, and the automatic driving automobile is set to drive to X at the expected passing speedi，5。
7. The method of claim 1, wherein the plurality of candidate paths containing the velocity information of the autonomous vehicle are discretized by equal temporal distance or equal spatial distance.
8. An autonomous vehicle static path planning apparatus, comprising:
the characteristic point selection module is used for selecting a plurality of groups of characteristic points according to the road topology of the intersection and the expected exit number of the driving route in the intersection, the group number of the characteristic points is consistent with the expected exit number, and each group of the characteristic points comprises a plurality of intersection internal characteristic points and a plurality of intersection external characteristic points;
the path calculation module is used for inputting a path calculation function by a plurality of groups of feature points to obtain corresponding different candidate static continuous paths; and
and the discrete processing module is used for setting an expected passing rate and an expected stopping rate for each candidate static continuous path, distributing a driving rate for the automatic driving automobile according to the current state of the automatic driving automobile and the phase position of the signal lamp to obtain a plurality of candidate paths containing the speed information of the automatic driving automobile, discretizing the candidate paths and outputting the finally planned static discrete paths.
9. A storage medium storing computer instructions for causing a computer to perform the method of static path planning for an autonomous vehicle of any of claims 1 to 7.
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