CN111797780B - Vehicle following track planning method, device, server and storage medium - Google Patents
Vehicle following track planning method, device, server and storage medium Download PDFInfo
- Publication number
- CN111797780B CN111797780B CN202010651790.5A CN202010651790A CN111797780B CN 111797780 B CN111797780 B CN 111797780B CN 202010651790 A CN202010651790 A CN 202010651790A CN 111797780 B CN111797780 B CN 111797780B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- driving
- information
- following
- driving vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000004590 computer program Methods 0.000 claims description 8
- 238000001914 filtration Methods 0.000 claims description 7
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- 230000002093 peripheral effect Effects 0.000 description 10
- 238000010586 diagram Methods 0.000 description 9
- 230000003287 optical effect Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 239000013307 optical fiber Substances 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000000644 propagated effect Effects 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Electromagnetism (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Traffic Control Systems (AREA)
Abstract
The embodiment of the invention discloses a vehicle following track planning method, a device, a server and a storage medium, wherein when a driving vehicle runs on a lane, if a lane line is unclear, driving information of the driving vehicle and surrounding environment information of surrounding vehicles are obtained, a predicted point of the driving vehicle is determined according to the driving information, the surrounding environment information and map information of the driving vehicle, whether the driving vehicle meets a vehicle following planning condition is further determined based on the predicted point and historical running information of the surrounding vehicles, and if the driving vehicle meets the vehicle following planning condition, a vehicle following track is generated based on the current running position, the predicted point and a running constraint condition of the driving vehicle. Through the mode, the interference of surrounding vehicles to the driving vehicle in the following process can be eliminated before the vehicle following track is generated, the stability of the driving vehicle in the following process is improved, the reliable vehicle following track is generated, and the safety of the vehicle in the automatic driving process is further improved.
Description
Technical Field
The embodiment of the invention relates to a vehicle technology, in particular to a method, a device, a server and a storage medium for planning a vehicle following track.
Background
In an L3 level autopilot system, the hands and eyes may be disengaged from the steering system for a certain period of time. However, due to the accuracy of the sensors, the L3 autopilot system does not have more accurate control inputs than the autopilot system above the L4 level, so when lane line information disappears, in order to keep the driver able to take over the vehicle after a certain time, a feasible planned path needs to be designed for the lateral control of the vehicle.
The existing following track planning mode is basically to directly send the position of the front vehicle to the vehicle as the input of the lateral control of the vehicle, but on one hand, the input aiming point of the lateral control of the vehicle is often changed and is not fixed in length, and can not be changed randomly, and the direct sending of the position of the front vehicle to the control layer may exceed the control capability, on the other hand, the influence of the surrounding environment on the front vehicle is not considered for judgment, that is, the track of the front vehicle and the surrounding vehicles are not predicted. Therefore, the reliability of the following track generated by the method is poor, and the automatic driving vehicle has great potential safety hazard in the driving process.
Disclosure of Invention
The embodiment of the invention provides a vehicle following track planning method, a vehicle following track planning device, a server and a storage medium, which are used for generating a reliable vehicle following track and further improving the safety of a vehicle in an automatic driving process.
In a first aspect, an embodiment of the present invention provides a method for planning a track following a vehicle, including:
when a lane line on which a driving vehicle runs is not clear, acquiring driving information of the driving vehicle and surrounding environment information of surrounding vehicles;
determining a predicted point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle;
determining whether the driving vehicle meets following planning conditions or not based on the predicted points and historical driving information of surrounding vehicles;
and if the driving vehicle meets the following planning condition, generating a following track based on the current driving position of the driving vehicle, the predicted point and the driving constraint condition.
In a second aspect, an embodiment of the present invention further provides a tracking planning apparatus, including:
the information acquisition module is used for acquiring the driving information of the driving vehicle and the surrounding environment information of surrounding vehicles when the lane line of the driving vehicle is not clear;
the prediction point determining module is used for determining a prediction point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle;
the following plan determining module is used for determining whether the driving vehicle meets following plan conditions or not based on the predicted points and historical driving information of surrounding vehicles;
and the vehicle following track generating module is used for generating a vehicle following track based on the current running position of the driving vehicle, the predicted point and the running constraint condition if the driving vehicle accords with the vehicle following planning condition.
In a third aspect, an embodiment of the present invention further provides a server, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the computer program, implements the method for planning a trajectory for following a vehicle according to any one of the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the computer-executable instructions, when executed by a computer processor, implement the tracking planning method according to any one of the first aspect.
According to the technical scheme provided by the embodiment, when the driving vehicle runs on the lane, if the lane line is not clear, the driving information of the driving vehicle and the surrounding environment information of the surrounding vehicle are obtained, the prediction point of the driving vehicle is determined according to the driving information, the surrounding environment information and the map information of the driving vehicle, whether the driving vehicle meets the following planning condition or not is further determined based on the prediction point and the historical running information of the surrounding vehicle, and if the driving vehicle meets the following planning condition, the following track is generated based on the current running position, the prediction point and the running constraint condition of the driving vehicle. Through the mode, the interference of surrounding vehicles to the driving vehicle in the following process can be eliminated before the vehicle following track is generated, the stability of the driving vehicle in the following process is improved, the reliable vehicle following track is generated, and the safety of the vehicle in the automatic driving process is further improved.
Drawings
Fig. 1 is a schematic flow chart of a method for planning a track following a vehicle according to an embodiment of the present invention;
FIG. 2 is a plan view of a vehicle following on a straight road according to a first embodiment of the present invention;
FIG. 3 is a plan view of a vehicle following a curved road according to a first embodiment of the present invention;
fig. 4 is a schematic logic diagram of a planned following trajectory according to an embodiment of the present invention;
fig. 5 is a schematic flow chart of planning a car following track according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a tracking planning apparatus according to a second embodiment of the present invention;
fig. 7 is a schematic structural diagram of a server according to a third embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a schematic flow diagram of a method for planning a following trajectory according to an embodiment of the present invention, where the embodiment is applicable to a situation where a following path is generated when a lane line through which a vehicle is driven is unclear, and the method may be executed by a following trajectory planning device, where the device may be implemented by software and/or hardware and is generally integrated in a following trajectory planning terminal or a server. Referring specifically to fig. 1, the method may include the steps of:
and S110, when the lane line where the driving vehicle runs is not clear, acquiring the driving information of the driving vehicle and the surrounding environment information of the surrounding vehicle.
Alternatively, the driving information may include a first traveling speed, first position information, a first traveling direction, and first route information of the driving vehicle, and the surrounding environment information includes at least one of a second traveling speed, second position information, a second traveling direction, and second route information of the surrounding vehicle. The surrounding vehicles may include vehicles located around the driven vehicle. The driving vehicle can automatically run in the first gear, the second gear, the third gear or the fourth gear, and the driving vehicle in the embodiment preferably selects the third gear for driving.
Alternatively, it is also necessary to determine whether the lane line on which the driven vehicle travels is clear before acquiring the driving information of the driven vehicle and the surrounding environment information of the surrounding vehicles. Specifically, the method for judging whether the lane line of the driving vehicle is clear comprises the following steps: obtaining map information of a driving vehicle, and determining whether a driving lane line is clear according to the map information; and if the driving lane line is not clear, receiving the driving information and the surrounding environment information sent by the vehicle-mounted sensor. Optionally, the current driving position of the driving vehicle may be located by Global Positioning System (GPS) location, base station location, wireless location, and the like to obtain map information of the driving vehicle, the server newly determines whether the lane line is clear according to the map of the driving vehicle, and receives the driving information and the surrounding environment information sent by the vehicle-mounted sensor if the lane line is not clear, and then generates a following path according to the driving information and the surrounding environment information.
And S120, determining a predicted point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle.
Optionally, vehicle dynamics models corresponding to the driving vehicle and the surrounding vehicle may be determined according to the driving information and the surrounding environment information, respectively; and inputting the driving information and the surrounding environment information into the corresponding vehicle dynamics model to obtain the kinematics information, and calculating the kinematics information and the map information based on a Kalman filtering algorithm to obtain a predicted point of the driving vehicle.
Specifically, the method comprises the steps of inputting driving information into a vehicle dynamic model of a driving vehicle, calculating kinematic information of the driving vehicle, inputting surrounding environment information into a vehicle dynamic model of a surrounding vehicle (such as a front vehicle closest to the driving vehicle), calculating kinematic information of the surrounding vehicle, and carrying out filtering calculation on the kinematic information through a Kalman filtering algorithm according to the kinematic information of the driving vehicle and the surrounding vehicle and map information to obtain a predicted point of the driving vehicle. Optionally, the kinematic information includes a driving route, a driving direction, and the like.
And S130, determining whether the driving vehicle meets the following planning condition or not based on the prediction point and the historical driving information of the surrounding vehicles.
It will be appreciated that when the driving vehicle is driving on a lane, the surrounding vehicles may not follow the lane line plan strictly, which may make some of the predicted points determined in the previous step inconsistent with the following plan condition. Based on the above, the present embodiment determines the travel path of the peripheral vehicle, the distance to the driven vehicle, and the predicted path point of the peripheral vehicle at each time point based on the historical travel information of the peripheral vehicle before generating the following track, and determines the predicted point closer to the path point of the peripheral vehicle or the predicted point located in the lane line of the peripheral vehicle if the distance between the path point of the peripheral vehicle and the predicted point of the driven vehicle is closer or the predicted point of the driven vehicle is located in the lane line of the peripheral vehicle, so that the predicted point located in the lane line of the peripheral vehicle does not meet the following planning condition; and if the overall predicted points of the driven vehicle are regular, determining that the driven vehicle meets the following planning condition, and generating a following track according to any predicted point. By the method, before the vehicle following path is generated, whether the driving vehicle meets the vehicle following condition or not is accurately predicted according to the predicted point and the historical driving information of the surrounding vehicles, a vehicle following path is prevented from being directly generated to enable the driving vehicle to track the front vehicle, interference of the surrounding vehicles to the driving vehicle in the vehicle following process can be eliminated, and the stability of the driving vehicle in the vehicle following process is also improved.
Fig. 2 shows a plan view of following a straight road by a driving vehicle, and fig. 3 shows a plan view of following a curved road by a driving vehicle. The method comprises the steps that a predicted point A, B, C is included in fig. 2, a predicted point D, E, F is included in fig. 3, the predicted points in fig. 2 are all on a traveling path of a driving vehicle, and a predicted point F in fig. 3 deviates from the traveling path of the driving vehicle and is close to a left driving vehicle, so that the predicted point F of the driving vehicle is determined not to meet the generation condition of a car following track, and a predicted point D and a predicted point E meet the generation condition of the car following track, and the car following track can be generated according to the predicted point D and the predicted point E.
And S140, if the driving vehicle meets the following planning condition, generating a following track based on the current driving position, the predicted point and the driving constraint condition of the driving vehicle.
Alternatively, the following route may be generated according to the following manner: and taking the current driving position as a starting point, the predicted point as an end point, and a driving constraint condition as a constraint value, and calculating a following track by adopting a Bezier curve based on the starting point, the end point and the constraint value, wherein the driving constraint condition comprises an execution mechanism constraint, a vehicle dynamics constraint, an initial state constraint and a target state constraint. The bezier curve in this embodiment may be a third-order bezier curve, a fourth-order bezier curve, or a multi-order bezier curve, and the fourth-order bezier curve or the multi-order bezier curve is preferably used in this embodiment to calculate the following trajectory.
The executing mechanism constraint is to ensure the continuous front wheel turning angle of the driving vehicle, namely the continuous curvature, and simultaneously ensure that the steering mechanism can execute the track, the curvature is bounded, and the boundary is determined by the steering capacity of the driving vehicle; the vehicle dynamics constraint may be understood as a front wheel steering angle constraint, the expression for which is: delta<min(δ rmax ,δ mmax ) Wherein, delta mmax Is limited by the maximum front-wheel steering angle, delta, constrained by the steering mechanism of the vehicle itself rmax Is obtained by δ = arctan (l/r), δ being a steering angle of the driven vehicle, l being a wheel base of the driven vehicle, r being a turning radius,
wherein V X As longitudinal speed of the vehicle, a ymax Is the lateral maximum acceleration; the expression for the initial state constraint is: x =0, y =0, heading =0, where heading is the heading of the driven vehicle; the expression for the target state constraint is: x = x f ,y＝y f ，heading＝h f Wherein x is f ，y f Is the predicted position of the end point relative to the driven vehicle, h f Is the heading of the target vehicle end position relative to the driven vehicle.
In order to generate a smooth following track, the embodiment may adopt a polynomial curve to fit the bezier curve, and input the current driving position, the predicted point, and the driving constraint condition to the fitted bezier curve to obtain the following track. That is, the current travel position is used as the starting point of the polynomial-fitted bezier curve, the predicted point is used as the ending point of the polynomial-fitted bezier curve, and the following trajectory of the driven vehicle is generated in combination with the travel constraint condition.
Fig. 4 is a logic diagram of a planned following trajectory, fig. 5 is a flow diagram of the planned following trajectory, and a process of generating the following trajectory is explained with reference to fig. 4 and 5. As shown in fig. 4 and 5, when the driving vehicle automatically drives in the third gear, whether the lane line is clear is judged according to the map information of the driving vehicle, and if the lane line is clear, the driving vehicle automatically drives along the lane line; if the lane lines are not clear, judging whether the driving vehicle meets the planning conditions, specifically calculating a predicted point of the driving vehicle according to the surrounding environment information, the vehicle information, corresponding vehicle dynamic models of the driving vehicle and the surrounding vehicles, and combining a Kalman filtering algorithm and map information, and judging whether the driving vehicle meets the planning conditions according to the predicted point and historical driving information of the surrounding vehicles; and if the following trajectory meets the planning conditions, planning the following trajectory according to the Bezier curve, and fitting the Bezier curve by adopting a polynomial curve to obtain the following trajectory of the driven vehicle.
Further, after the following track is generated through the steps, the server can send the following track to a steering wheel of the driving vehicle, so that the steering wheel controls the driving vehicle to transversely follow the driving vehicle according to the following track under the set driving gear. It is understood that the driving gear may be the third gear as described in the foregoing steps. In this embodiment, when driving the vehicle when third gear automatic drive, the server will follow the track as the lateral control input of the steering wheel of driving the vehicle, and the steering wheel carries out lateral control to driving the vehicle according to following the track, can the certain degree release driver's hand, the situation of eyes, when making driving the vehicle and driving at the unclear road of lane line, can reduce the number of times that the driver took over greatly when reducing the potential safety hazard, and then promote the comfort that the driver drove.
According to the technical scheme provided by the embodiment, when the driving vehicle runs on the lane, if the lane line is not clear, the driving information of the driving vehicle and the surrounding environment information of the surrounding vehicle are obtained, the predicted point of the driving vehicle is determined according to the driving information, the surrounding environment information and the map information of the driving vehicle, whether the driving vehicle meets the following planning condition or not is further determined based on the predicted point and the historical running information of the surrounding vehicle, and if the driving vehicle meets the following planning condition, the following track is generated based on the current running position, the predicted point and the running constraint condition of the driving vehicle. Through the mode, the interference of surrounding vehicles to the driving vehicle in the following process can be eliminated before the vehicle following track is generated, the stability of the driving vehicle in the following process is improved, the reliable vehicle following track is generated, and the safety of the vehicle in the automatic driving process is further improved.
Example two
Fig. 6 is a schematic structural diagram of a tracking planning apparatus according to a second embodiment of the present invention. Referring to fig. 6, the apparatus includes: the tracking system comprises an information acquisition module 210, a predicted point determination module 220, a following plan determination module 230 and a following track generation module 240.
The information acquiring module 210 is configured to acquire driving information of a driving vehicle and surrounding environment information of surrounding vehicles when a lane line on which the driving vehicle runs is unclear; a predicted point determining module 220, configured to determine a predicted point of the driving vehicle according to the driving information, the surrounding environment information, and map information of the driving vehicle; a following plan determination module 230, configured to determine whether the driving vehicle meets following plan conditions based on the predicted point and historical driving information of surrounding vehicles; and a following track generating module 240, configured to generate a following track based on the current driving position of the driving vehicle, the predicted point, and the driving constraint condition if the driving vehicle meets the following planning condition.
On the basis of the foregoing technical solutions, the following trajectory generating module 240 is further configured to calculate a following trajectory by using the current driving position as a starting point, the predicted point as an end point, and the driving constraint condition as a constraint value, based on the starting point, the end point, and the constraint value, and using a bezier curve, where the driving constraint condition includes an actuator constraint, a vehicle dynamics constraint, an initial state constraint, and a target state constraint.
On the basis of the foregoing technical solutions, the following trajectory generation module 240 is further configured to fit the bezier curve by using a polynomial curve, and input the current driving position, the predicted point, and the driving constraint condition to the fitted bezier curve to obtain the following trajectory.
On the basis of the above technical solutions, the predicted point determining module 220 is further configured to determine vehicle dynamics models corresponding to the driving vehicle and the surrounding vehicle according to the driving information and the surrounding environment information, respectively;
and inputting the driving information and the surrounding environment information into corresponding vehicle dynamic models to obtain kinematic information, and calculating the kinematic information and the map information based on a Kalman filtering algorithm to obtain predicted points of the driving vehicle.
On the basis of the above technical solutions, the apparatus further includes: a driving lane line definition judging module; the driving lane line definition judging module is used for acquiring map information of a driving vehicle and determining whether the driving lane line is clear or not according to the map information;
and if the driving lane line is not clear, receiving the driving information and the surrounding environment information sent by the vehicle-mounted sensor.
On the basis of the above technical solutions, the apparatus further includes: a vehicle following track sending module; the vehicle following track sending module is used for sending the vehicle following track to a steering wheel for driving a vehicle, so that the steering wheel controls the driving vehicle to transversely follow the vehicle according to the vehicle following track under a set driving gear.
In addition to the above technical solutions, the driving information includes a first traveling speed, a first position information, and a first traveling direction of the driving vehicle, and the surrounding environment information includes at least one of a second traveling speed, a second position information, and a second traveling direction of the surrounding vehicle.
According to the technical scheme provided by the embodiment, when the driving vehicle runs on the lane, if the lane line is not clear, the driving information of the driving vehicle and the surrounding environment information of the surrounding vehicle are obtained, the prediction point of the driving vehicle is determined according to the driving information, the surrounding environment information and the map information of the driving vehicle, whether the driving vehicle meets the following planning condition or not is further determined based on the prediction point and the historical running information of the surrounding vehicle, and if the driving vehicle meets the following planning condition, the following track is generated based on the current running position, the prediction point and the running constraint condition of the driving vehicle. Through the mode, the interference of surrounding vehicles to the driving vehicle in the following process can be eliminated before the vehicle following track is generated, the stability of the driving vehicle in the following process is improved, the reliable vehicle following track is generated, and the safety of the vehicle in the automatic driving process is further improved.
EXAMPLE III
Fig. 7 is a schematic structural diagram of a server according to a third embodiment of the present invention. FIG. 7 illustrates a block diagram of an exemplary server 12 suitable for use in implementing embodiments of the present invention. The server 12 shown in fig. 7 is only an example, and should not bring any limitation to the function and the scope of use of the embodiment of the present invention.
As shown in FIG. 7, the server 12 is in the form of a general purpose computing device. The components of the server 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by server 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The server 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 7, and commonly referred to as a "hard drive"). Although not shown in FIG. 7, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set of program modules (e.g., following trajectory planning device information acquisition module 210, predicted point determination module 220, following trajectory determination module 230, and following trajectory generation module 240) configured to perform the functions of embodiments of the present invention.
A program/utility 44 having a set of program modules 46 (e.g., an information acquisition module 210, a predicted point determination module 220, a following plan determination module 230, and a following trajectory generation module 240 of a following trajectory planning device), such program modules 46 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, may be stored, for example, in memory 28, each of which examples or some combination may include an implementation of a network environment. Program modules 46 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The server 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with the server 12, and/or with any devices (e.g., network card, modem, etc.) that enable the server 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the server 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with the other modules of the server 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the server 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing a tracking planning method provided by an embodiment of the present invention, the method including:
when a lane line on which a driving vehicle runs is not clear, acquiring driving information of the driving vehicle and surrounding environment information of surrounding vehicles;
determining a predicted point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle;
determining whether the driving vehicle meets following planning conditions or not based on the predicted points and historical driving information of surrounding vehicles;
and if the driving vehicle meets the following planning condition, generating a following track based on the current driving position of the driving vehicle, the predicted point and the driving constraint condition.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, to implement a tracking planning method provided by the embodiment of the present invention.
Of course, those skilled in the art can understand that the processor may also implement the technical solution of the method for planning the trajectory of the vehicle provided in any embodiment of the present invention.
Example four
The fourth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for planning a track following track according to the fourth embodiment of the present invention, where the method includes:
when a lane line for driving the vehicle is not clear, acquiring driving information of the driving vehicle and surrounding environment information of surrounding vehicles;
determining a predicted point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle;
determining whether the driving vehicle meets following planning conditions or not based on the predicted points and historical driving information of surrounding vehicles;
and if the driving vehicle meets the following planning condition, generating a following track based on the current driving position of the driving vehicle, the predicted point and the driving constraint condition.
Of course, the computer program stored on the computer-readable storage medium according to the embodiments of the present invention is not limited to the above method operations, and may also perform related operations in a method for planning a trajectory of a vehicle according to any of the embodiments of the present invention.
Computer storage media for embodiments of the present invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: 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 context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device.
The computer-readable signal medium may include driving information, surrounding environment information, map information, historical driving information, etc., in which computer-readable program code is carried. Such propagated driving information, surrounding environment information, map information, and history travel information. 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, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, or the like, as well as 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).
It should be noted that, in the embodiment of the following trajectory planning apparatus, the modules included in the embodiment are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (7)
1. A method for planning a track following a vehicle is characterized by comprising the following steps:
when a lane line for driving the vehicle is not clear, acquiring driving information of the driving vehicle and surrounding environment information of surrounding vehicles;
determining a predicted point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle;
determining whether the driving vehicle meets following planning conditions or not based on the predicted points and historical driving information of surrounding vehicles;
if the driving vehicle meets the following planning condition, generating a following track based on the current driving position of the driving vehicle, the predicted point and the driving constraint condition;
the determining a predicted point of the driving vehicle according to the driving information, the surrounding environment information, and the map information of the driving vehicle includes:
respectively determining vehicle dynamic models corresponding to the driving vehicle and the surrounding vehicle according to the driving information and the surrounding environment information;
inputting the driving information and the surrounding environment information into corresponding vehicle dynamics models to obtain kinematics information, and calculating the kinematics information and the map information based on a Kalman filtering algorithm to obtain a predicted point of a driving vehicle;
the generating of the following track based on the current traveling position of the driven vehicle, the predicted point, and the traveling constraint condition includes:
calculating a following track by using a Bezier curve based on the starting point, the end point and the constraint value by taking the current running position as the starting point, the predicted point as the end point and the running constraint condition as the constraint value, wherein the running constraint condition comprises an execution mechanism constraint, a vehicle dynamics constraint, an initial state constraint and a target state constraint;
the driving information includes a first traveling speed, first position information, and a first traveling direction of a driving vehicle, and the surrounding environment information includes at least one of a second traveling speed, second position information, and a second traveling direction of a surrounding vehicle;
the kinematic information includes: a travel route and a travel direction.
2. The method of claim 1, wherein calculating a car following trajectory based on the start point, the end point, and the constraint value and using a bezier curve comprises:
and fitting the Bezier curve by adopting a polynomial curve, and inputting the current driving position, the predicted point and the driving constraint condition into the fitted Bezier curve to obtain the following track.
3. The method according to claim 1, further comprising, before acquiring the driving information of the driven vehicle and the surrounding environment information of the surrounding vehicle:
obtaining map information of a driving vehicle, and determining whether the driving lane line is clear according to the map information;
and if the driving lane line is not clear, receiving the driving information and the surrounding environment information sent by the vehicle-mounted sensor.
4. The method of claim 1, further comprising:
and sending the following track to a steering wheel for driving the vehicle, so that the steering wheel controls the driving vehicle to transversely follow the vehicle according to the following track under a set driving gear.
5. A following trajectory planning device, comprising:
the information acquisition module is used for acquiring the driving information of the driving vehicle and the surrounding environment information of surrounding vehicles when the lane line of the driving vehicle is not clear;
the prediction point determining module is used for determining a prediction point of the driving vehicle according to the driving information, the surrounding environment information and the map information of the driving vehicle;
the following plan determining module is used for determining whether the driving vehicle meets following plan conditions or not based on the predicted points and historical driving information of surrounding vehicles;
the vehicle following track generation module is used for generating a vehicle following track based on the current running position of the driving vehicle, the predicted point and the running constraint condition if the driving vehicle meets the vehicle following planning condition;
the predicted point determination module is further to: respectively determining vehicle dynamic models corresponding to the driving vehicle and the surrounding vehicle according to the driving information and the surrounding environment information; inputting the driving information and the surrounding environment information into corresponding vehicle dynamics models to obtain kinematics information, and calculating the kinematics information and the map information based on a Kalman filtering algorithm to obtain a predicted point of a driving vehicle;
the vehicle following track generation module is further configured to calculate a vehicle following track by using the current driving position as a starting point, the predicted point as an end point, and the driving constraint condition as a constraint value, based on the starting point, the end point and the constraint value, and using a bezier curve, wherein the driving constraint condition includes an execution mechanism constraint, a vehicle dynamics constraint, an initial state constraint and a target state constraint;
wherein the driving information includes a first traveling speed, first position information, and a first traveling direction at which the vehicle is driven, and the surrounding environment information includes at least one of a second traveling speed, second position information, and a second traveling direction at which the surrounding vehicle is driven;
the kinematic information includes: a travel route and a travel direction.
6. A server comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the method for tracking trajectory planning according to any of claims 1 to 4.
7. A storage medium containing computer-executable instructions, which when executed by a computer processor implement the method of tracking planning as claimed in any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010651790.5A CN111797780B (en) | 2020-07-08 | 2020-07-08 | Vehicle following track planning method, device, server and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010651790.5A CN111797780B (en) | 2020-07-08 | 2020-07-08 | Vehicle following track planning method, device, server and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111797780A CN111797780A (en) | 2020-10-20 |
| CN111797780B true CN111797780B (en) | 2022-12-02 |
Family
ID=72809709
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010651790.5A Active CN111797780B (en) | 2020-07-08 | 2020-07-08 | Vehicle following track planning method, device, server and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111797780B (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112528807B (en) * | 2020-12-04 | 2023-12-19 | 深圳市优必选科技股份有限公司 | Method and device for predicting running track, electronic equipment and storage medium |
| CN112721952B (en) * | 2021-01-29 | 2022-07-05 | 重庆长安汽车股份有限公司 | Complex road section driving control method and device for L3-grade automatic driving automobile, automobile and computer storage medium |
| CN113119996B (en) * | 2021-03-19 | 2022-11-08 | 京东鲲鹏(江苏)科技有限公司 | Trajectory prediction method and apparatus, electronic device and storage medium |
| CN113060146B (en) * | 2021-05-12 | 2023-04-07 | 中国第一汽车股份有限公司 | Longitudinal tracking control method, device, equipment and storage medium |
| CN113353078B (en) * | 2021-06-24 | 2024-10-18 | 中汽创智科技有限公司 | Method and device for determining lane-line-free automatic vehicle following track |
| CN113483775B (en) * | 2021-06-30 | 2024-06-14 | 上海商汤临港智能科技有限公司 | Path prediction method and device, electronic equipment and computer readable storage medium |
| CN113415274B (en) * | 2021-07-14 | 2022-07-05 | 重庆长安汽车股份有限公司 | Automatic driving following track planning system, method, vehicle and storage medium |
| CN114550133B (en) * | 2022-02-14 | 2025-01-10 | 重庆长安汽车股份有限公司 | Target tracking post-processing method based on vehicle physical kinematics model and vehicle |
| CN115218902B (en) * | 2022-04-02 | 2024-02-02 | 广州汽车集团股份有限公司 | Track planning method, device, equipment and storage medium |
| CN115320589B (en) * | 2022-10-13 | 2023-02-10 | 青岛慧拓智能机器有限公司 | Following speed planning method, device, chip, terminal, electronic equipment and medium |
| CN117657213A (en) * | 2023-11-20 | 2024-03-08 | 北京集度科技有限公司 | Path planning method, path planning device, vehicle, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9672734B1 (en) * | 2016-04-08 | 2017-06-06 | Sivalogeswaran Ratnasingam | Traffic aware lane determination for human driver and autonomous vehicle driving system |
| CN109669461A (en) * | 2019-01-08 | 2019-04-23 | 南京航空航天大学 | Automatic driving vehicle decision system and its method for planning track under a kind of complex working condition |
| CN109866752A (en) * | 2019-03-29 | 2019-06-11 | 合肥工业大学 | Double mode parallel vehicles track following driving system and method based on PREDICTIVE CONTROL |
| CN110136254A (en) * | 2019-06-13 | 2019-08-16 | 吉林大学 | Driving assistance information display method based on dynamic probabilistic driving map |
| CN110502012A (en) * | 2019-08-20 | 2019-11-26 | 武汉中海庭数据技术有限公司 | His a kind of wheel paths prediction technique, device and storage medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10427676B2 (en) * | 2017-05-31 | 2019-10-01 | GM Global Technology Operations LLC | Trajectory planner for autonomous driving using bézier curves |
| CN109606384B (en) * | 2018-12-29 | 2021-04-20 | 百度在线网络技术（北京）有限公司 | Vehicle control method, device, equipment and storage medium |
| CN111169469B (en) * | 2019-10-08 | 2021-03-12 | 中国第一汽车股份有限公司 | Vehicle trajectory planning method and device, storage medium and automobile |
| CN111123952B (en) * | 2019-12-31 | 2021-12-31 | 华为技术有限公司 | Trajectory planning method and device |
-
2020
- 2020-07-08 CN CN202010651790.5A patent/CN111797780B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9672734B1 (en) * | 2016-04-08 | 2017-06-06 | Sivalogeswaran Ratnasingam | Traffic aware lane determination for human driver and autonomous vehicle driving system |
| CN109669461A (en) * | 2019-01-08 | 2019-04-23 | 南京航空航天大学 | Automatic driving vehicle decision system and its method for planning track under a kind of complex working condition |
| CN109866752A (en) * | 2019-03-29 | 2019-06-11 | 合肥工业大学 | Double mode parallel vehicles track following driving system and method based on PREDICTIVE CONTROL |
| CN110136254A (en) * | 2019-06-13 | 2019-08-16 | 吉林大学 | Driving assistance information display method based on dynamic probabilistic driving map |
| CN110502012A (en) * | 2019-08-20 | 2019-11-26 | 武汉中海庭数据技术有限公司 | His a kind of wheel paths prediction technique, device and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| Learning Human-Like Trajectory Planning on Urban Two-Lane Curved Roads From Experienced Drivers;Aoxue Li等;《IEEE Access》;20190523;1-11 * |
| 智能车定位与路径优化方法研究;黄江亮;《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》;20181215;C035-110 * |
| 考虑交通车辆运动不确定性的轨迹规划方法研究;孙浩;《中国博士学位论文全文数据库 工程科技Ⅱ辑》;20171115;C035-13 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111797780A (en) | 2020-10-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111797780B (en) | Vehicle following track planning method, device, server and storage medium | |
| JP6861239B2 (en) | PID embedded LQR for self-driving vehicles | |
| JP6861238B2 (en) | How to determine the lane change trajectory of an autonomous vehicle | |
| CN113928340B (en) | Obstacle avoidance method and device applied to vehicle, electronic equipment and storage medium | |
| CN111775940B (en) | Automatic channel changing method, device, equipment and storage medium | |
| US10990101B2 (en) | Method for drifting correction for planning a path for autonomous driving vehicles | |
| CN114194217B (en) | Automatic driving method and device for vehicle, electronic equipment and storage medium | |
| JP6779326B2 (en) | Methods and systems for generating baselines used in self-driving vehicles using multiple threads | |
| US10549752B2 (en) | Deceleration curb-based direction checking and lane keeping system for autonomous driving vehicles | |
| CN112020014A (en) | Lane change track planning method, device, server and storage medium | |
| CN110341688B (en) | Front wheel steering angle compensation method and device, vehicle-mounted equipment and storage medium | |
| JP7189691B2 (en) | Vehicle cruise control system | |
| CN112141110A (en) | Vehicle lane changing method, device, equipment and storage medium | |
| CN113734201B (en) | Vehicle redundancy control method, device, electronic equipment and medium | |
| US10732632B2 (en) | Method for generating a reference line by stitching multiple reference lines together using multiple threads | |
| KR20220017481A (en) | Road Model Manifold for 2D Trajectory Planner | |
| CN116552564A (en) | Method and device for determining driving track, electronic equipment and readable storage medium | |
| CN116001811A (en) | Track planning method, device and equipment for automatic driving vehicle | |
| CN113602263A (en) | Vehicle avoidance method, device, in-vehicle equipment and storage medium | |
| JP6080998B1 (en) | Vehicle control information generation apparatus and vehicle control information generation method | |
| CN110411463A (en) | On-vehicle navigation apparatus receives the emergency navigational system and method under star failure state | |
| CN110450788A (en) | A kind of driving mode switching method, device, equipment and storage medium | |
| CN114194201A (en) | Vehicle control method and device, electronic equipment and storage medium | |
| CN112172819A (en) | A vehicle lane changing method, device, device and storage medium | |
| CN113008255B (en) | Navigation method and navigation device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |