CN110789517A - Automatic driving lateral control method, device, equipment and storage medium - Google Patents

Automatic driving lateral control method, device, equipment and storage medium Download PDF

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Publication number
CN110789517A
CN110789517A CN201911188226.8A CN201911188226A CN110789517A CN 110789517 A CN110789517 A CN 110789517A CN 201911188226 A CN201911188226 A CN 201911188226A CN 110789517 A CN110789517 A CN 110789517A
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China
Prior art keywords
vehicle
controlled
current
lane
information
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CN201911188226.8A
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Chinese (zh)
Inventor
刘法勇
徐春梅
时利
张一营
徐毅林
曾伟
陈旭
谢欣燕
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Anhui Jianghuai Automobile Group Corp
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Anhui Jianghuai Automobile Group Corp
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Priority to CN201911188226.8A priority Critical patent/CN110789517A/en
Publication of CN110789517A publication Critical patent/CN110789517A/en
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/02Control of vehicle driving stability
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/10Path keeping
    • B60W30/12Lane keeping
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00Input parameters relating to overall vehicle dynamics
    • B60W2520/12Lateral speed
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00Input parameters relating to overall vehicle dynamics
    • B60W2520/14Yaw

Abstract

The invention relates to the technical field of automatic driving, and discloses a method, a device, equipment and a storage medium for automatic driving lateral control, wherein the method comprises the following steps: the method comprises the steps of obtaining the current speed of a vehicle to be controlled, obtaining the current image information of a preset area in front of the vehicle to be controlled, extracting lane line information of a lane where the vehicle to be controlled is located from the current image information, calculating the curvature of a current road according to the lane line information, calculating a pre-aiming distance according to the current speed and the curvature of the current road, and performing transverse control on the vehicle to be controlled according to the pre-aiming distance, so that a proper pre-aiming distance is selected according to the current speed and the front road condition of the vehicle, a good transverse control effect of the vehicle is achieved, and the technical problem of how to determine the proper pre-aiming distance in real time to perform transverse control on the vehicle is solved.

Description

Automatic driving lateral control method, device, equipment and storage medium
Technical Field
The invention relates to the technical field of automatic driving, in particular to an automatic driving lateral control method, device, equipment and storage medium.
Background
The automatic driving of the vehicle is a complex control process, the research is convenient in the industry, the automatic driving is divided into longitudinal control and transverse control according to the direction, the transverse control mainly controls the driving direction of the vehicle to ensure that the vehicle automatically keeps running near the center of a lane, in the research of the transverse control of the vehicle, the vehicle is sometimes equivalent to a mass point at the center of mass of the vehicle to ensure that the mass point is near the center of the lane, but the vehicle in motion is controlled according to the position relation of the vehicle path at the moment, the performance effect of the vehicle is delayed to a certain degree, the control effect is not good, some prejudgment needs to be added, a point is selected in front of the driving of the vehicle to replace the vehicle, the point is controlled at the center of the lane to improve the control effect, the mass point is called a pre-aiming point, and the distance between the pre-aiming point and the center of the center.
At present, the conventional scheme is that a fixed preview distance is adopted to complete the determination of a preview point, but the selection of the preview distance is fixed and is a fixed value for various different working conditions, when the vehicle speed is higher, the preview distance can appear smaller, and the small deviation at the preview point can cause larger change, the vehicle is easy to snake, so that the transverse control effect of the vehicle is poor, serious or even unstable, when the vehicle speed is slower, the preview distance also has certain influence on the transverse control of the vehicle, when the preview distance of the vehicle is fixed, the vehicle can only pass through a curve with curvature in a specific range, when the curvature of the curve is too large, the fixed preview distance can possibly cause insufficient steering, and when the curvature of the curve is smaller, the curve can possibly cause overlarge steering, and the applicable conditions and scenes of the technical scheme are very limited.
Therefore, the technical problem of how to determine the proper pre-aiming distance in real time to control the vehicle transversely exists in essence.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide an automatic driving transverse control method, device, equipment and storage medium, aiming at solving the technical problem of how to determine a proper pre-aiming distance in real time to carry out transverse control on a vehicle.
In order to achieve the above object, the present invention provides an automatic driving lateral control method including the steps of:
the method comprises the steps of obtaining the current speed of a vehicle to be controlled and obtaining the current image information of a preset area in front of the vehicle to be controlled;
extracting lane line information of a lane where the vehicle to be controlled is located from the current image information;
calculating the curvature of the current road according to the lane line information;
calculating a pre-aiming distance according to the current vehicle speed and the current road curvature;
and carrying out transverse control on the vehicle to be controlled according to the pre-aiming distance.
Preferably, the performing lateral control on the vehicle to be controlled according to the pre-aiming distance specifically includes:
taking a point which is in front of the centroid of the vehicle to be controlled and is spaced by the pre-aiming distance as a pre-aiming point, and determining a lane central line according to the lane line information;
and carrying out transverse control on the vehicle to be controlled according to the preview point and the lane central line.
Preferably, the performing lateral control on the vehicle to be controlled according to the preview point and the lane center line specifically includes:
calculating the vertical distance between the pre-aiming point and the center line of the lane;
judging whether the vertical distance is larger than a preset distance threshold value or not;
and performing transverse control on the vehicle to be controlled according to the judgment result.
Preferably, the performing lateral control on the vehicle to be controlled according to the determination result specifically includes:
when the vertical distance is larger than a preset distance threshold, calculating a deviation value of the vertical distance and the preset distance threshold;
calculating a target front wheel steering angle according to the deviation value;
and carrying out transverse control on the vehicle to be controlled according to the target front wheel steering angle.
Preferably, the calculating a pre-aiming distance according to the current vehicle speed and the current road curvature specifically includes:
carrying out fuzzy processing on the current vehicle speed and the current road curvature to obtain fuzzy parameters;
inputting the fuzzy parameters into a preset fuzzy rule table to obtain a target numerical value;
and calculating the pre-aiming distance according to the target numerical value.
Preferably, the extracting lane line information of the lane where the vehicle to be controlled is located from the current image information specifically includes:
carrying out image recognition processing on the current image information to obtain front road information;
and extracting lane line information of a lane where the vehicle to be controlled is located from the front road information.
Preferably, the calculating the curvature of the current road according to the lane line information specifically includes:
fitting the lane line information through a preset polynomial equation to obtain shape parameter information of a road in front of the vehicle to be controlled;
and calculating the curvature of the current road according to the shape parameter information.
Further, in order to achieve the above object, the present invention also proposes an automatic driving lateral control device including:
the information acquisition module is used for acquiring the current speed of a vehicle to be controlled and acquiring the current image information of a preset area in front of the vehicle to be controlled;
the lane information module is used for extracting lane line information of a lane where the vehicle to be controlled is located from the current image information;
the road curvature module is used for calculating the curvature of the current road according to the lane line information;
the pre-aiming distance module is used for calculating a pre-aiming distance according to the current vehicle speed and the current road curvature;
and the transverse control module is used for transversely controlling the vehicle to be controlled according to the pre-aiming distance.
Further, to achieve the above object, the present invention also proposes an automatic driving lateral control apparatus comprising: a memory, a processor and an autopilot lateral control program stored on the memory and executable on the processor, the autopilot lateral control program being configured with steps implementing the autopilot lateral control method as described above.
Furthermore, to achieve the above object, the present invention also proposes a storage medium having stored thereon an automatic driving lateral control program which, when executed by a processor, implements the steps of the automatic driving lateral control method as described above.
According to the automatic driving transverse control method provided by the invention, the current speed of a vehicle to be controlled is obtained, the current image information of a preset area in front of the vehicle to be controlled is obtained, the lane line information of a lane where the vehicle to be controlled is located is extracted from the current image information, the current road curvature is calculated according to the lane line information, the pre-aiming distance is calculated according to the current speed and the current road curvature, and the vehicle to be controlled is transversely controlled according to the pre-aiming distance, so that the proper pre-aiming distance is selected according to the current speed and the front road condition of the vehicle, a good transverse control effect of the vehicle is realized, and the technical problem of how to determine the proper pre-aiming distance in real time to transversely control the vehicle is solved.
Drawings
FIG. 1 is a schematic diagram of an automatic driving lateral control device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of an automatic driving lateral control method of the present invention;
FIG. 3 is a schematic flow chart of a second embodiment of an automatic driving lateral control method of the present invention;
FIG. 4 is a schematic diagram of the preview point and the lane center line of the second embodiment of the automatic driving lateral control method of the present invention;
FIG. 5 is a schematic flow chart of a third embodiment of an automatic driving lateral control method of the present invention;
fig. 6 is a functional block diagram of the automatic driving lateral control device according to the first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an automatic driving lateral control device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the automatic driving lateral control apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may comprise a Display screen (Display), an input unit such as keys, and the optional user interface 1003 may also comprise a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The Memory 1005 may be a Random Access Memory (RAM) Memory or a non-volatile Memory (e.g., a magnetic disk Memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 does not constitute a limitation of the automatic driving lateral control apparatus and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and an automatic driving lateral control program.
In the automatic driving lateral control apparatus shown in fig. 1, the network interface 1004 is mainly used for connecting an external network and performing data communication with other network apparatuses; the user interface 1003 is mainly used for connecting to a user equipment and performing data communication with the user equipment; the apparatus of the present invention calls the automatic driving lateral control program stored in the memory 1005 by the processor 1001, and performs the following operations:
the method comprises the steps of obtaining the current speed of a vehicle to be controlled and obtaining the current image information of a preset area in front of the vehicle to be controlled;
extracting lane line information of a lane where the vehicle to be controlled is located from the current image information;
calculating the curvature of the current road according to the lane line information;
calculating a pre-aiming distance according to the current vehicle speed and the current road curvature;
and carrying out transverse control on the vehicle to be controlled according to the pre-aiming distance.
Further, processor 1001 may invoke an autopilot lateral control program stored in memory 1005, and also perform the following operations:
taking a point which is in front of the centroid of the vehicle to be controlled and is spaced by the pre-aiming distance as a pre-aiming point, and determining a lane central line according to the lane line information;
and carrying out transverse control on the vehicle to be controlled according to the preview point and the lane central line.
Further, processor 1001 may invoke an autopilot lateral control program stored in memory 1005, and also perform the following operations:
calculating the vertical distance between the pre-aiming point and the center line of the lane;
judging whether the vertical distance is larger than a preset distance threshold value or not;
and performing transverse control on the vehicle to be controlled according to the judgment result.
Further, processor 1001 may invoke an autopilot lateral control program stored in memory 1005, and also perform the following operations:
when the vertical distance is larger than a preset distance threshold, calculating a deviation value of the vertical distance and the preset distance threshold;
calculating a target front wheel steering angle according to the deviation value;
and carrying out transverse control on the vehicle to be controlled according to the target front wheel steering angle.
Further, processor 1001 may invoke an autopilot lateral control program stored in memory 1005, and also perform the following operations:
carrying out fuzzy processing on the current vehicle speed and the current road curvature to obtain fuzzy parameters;
inputting the fuzzy parameters into a preset fuzzy rule table to obtain a target numerical value;
and calculating the pre-aiming distance according to the target numerical value.
Further, processor 1001 may invoke an autopilot lateral control program stored in memory 1005, and also perform the following operations:
carrying out image recognition processing on the current image information to obtain front road information;
and extracting lane line information of a lane where the vehicle to be controlled is located from the front road information.
Further, processor 1001 may invoke an autopilot lateral control program stored in memory 1005, and also perform the following operations:
fitting the lane line information through a preset polynomial equation to obtain shape parameter information of a road in front of the vehicle to be controlled;
and calculating the curvature of the current road according to the shape parameter information.
In the embodiment, the current speed of the vehicle to be controlled is obtained, the current image information of the preset area in front of the vehicle to be controlled is obtained, the lane line information of the lane where the vehicle to be controlled is located is extracted from the current image information, the current road curvature is calculated according to the lane line information, the pre-aiming distance is calculated according to the current speed and the current road curvature, and the vehicle to be controlled is controlled transversely according to the pre-aiming distance, so that the proper pre-aiming distance is selected according to the current speed and the front road condition of the vehicle, a good transverse control effect of the vehicle is realized, and the technical problem of how to determine the proper pre-aiming distance in real time to control the vehicle transversely is solved.
Based on the hardware structure, the embodiment of the automatic driving lateral control method is provided.
Referring to fig. 2, fig. 2 is a flowchart illustrating an automatic driving lateral control method according to a first embodiment of the present invention.
In a first embodiment, the automatic driving lateral control method includes the steps of:
and step S10, acquiring the current speed of the vehicle to be controlled, and acquiring the current image information of a preset area in front of the vehicle to be controlled.
It should be noted that the execution main body of the present embodiment may be an automatic driving lateral control device, and may also be other devices that can implement the same or similar functions.
It CAN be understood that the current vehicle speed of the vehicle to be controlled CAN be obtained by a vehicle speed sensor, read from a vehicle CAN bus signal, or obtained by other means, which is not limited in this embodiment.
It can be understood that the current image information of the preset area in front of the vehicle to be controlled may be acquired by a camera installed in the middle of a front windshield of the vehicle, or may be acquired by a vehicle data recorder, or may be acquired by other methods, which is not limited in this embodiment.
It should be understood that the vision sensor mainly comprises a light source, a lens, an image sensor, an analog-to-digital converter, an image processor, an image memory and the like, the main function of the vision sensor is to obtain enough most original images to be processed by a machine vision system, the image sensor is used for converting images collected by the lens into digital or analog signals to be output, the vision sensor is a core component of vision detection, the vision sensor mainly comprises a charge coupled device image sensor and a metal oxide semiconductor image sensor, the image sensor with high cost performance is selected according to research objects and application occasions and simultaneously the vehicle-mounted practical situation is fully considered, and the hardware connection mode of signals of the vision sensor and automatic driving transverse control equipment is that the signals of the vision sensor are connected through a CAN network.
And step S20, extracting the lane line information of the lane where the vehicle to be controlled is located from the current image information.
It should be understood that the current image information may include various images, for example, there may be a front vehicle image, a pedestrian image, a roadside building image, a front road image, etc., and of course, more or less image information may be included, which is not limited in this embodiment.
It can be understood that the subsequent steps only need to use the lane line information of the lane where the vehicle to be controlled is located, and therefore, the lane where the vehicle to be controlled is located needs to be determined first, then the front road information is extracted from the current image information, and the lane line information corresponding to the lane where the vehicle to be controlled is located is extracted from the front road information.
And step S30, calculating the curvature of the current road according to the lane line information.
It should be noted that, specifically, calculating the curvature of the current road according to the lane line information includes fitting the lane line information by a preset polynomial equation to obtain shape parameter information of the road in front of the vehicle to be controlled, and calculating the curvature of the current road according to the shape parameter information.
It should be understood that the shape parameter information of the road in front of the vehicle to be controlled can be obtained by fitting the lane line information, and the curvature of the current road can be calculated according to the shape parameter information.
And step S40, calculating the pre-aiming distance according to the current vehicle speed and the current road curvature.
It should be noted that the curvature of the current road is obtained from the outside in real time, and the current vehicle speed is the longitudinal control of the vehicle, so the key to coordinate the relationship between the three is how to adaptively adjust the pre-aiming distance according to the change of the curvature of the current road and the longitudinal vehicle speed, and there is no definite mathematical relationship between the three, so the pre-aiming distance is obtained by adopting a fuzzy control method in the scheme.
And step S50, performing transverse control on the vehicle to be controlled according to the pre-aiming distance.
It will be appreciated that an appropriate home point may be selected based on the home distance so that the vehicle to be controlled is controlled laterally by the home point.
In the embodiment, the current speed of the vehicle to be controlled is obtained, the current image information of the preset area in front of the vehicle to be controlled is obtained, the lane line information of the lane where the vehicle to be controlled is located is extracted from the current image information, the current road curvature is calculated according to the lane line information, the pre-aiming distance is calculated according to the current speed and the current road curvature, and the vehicle to be controlled is controlled transversely according to the pre-aiming distance, so that the proper pre-aiming distance is selected according to the current speed and the front road condition of the vehicle, a good transverse control effect of the vehicle is realized, and the technical problem of how to determine the proper pre-aiming distance in real time to control the vehicle transversely is solved.
In an embodiment, as shown in fig. 3, the second embodiment of the automatic driving lateral control method according to the present invention is proposed based on the first embodiment, and the step S50 includes:
and S501, taking a point which is in front of the centroid of the vehicle to be controlled and is spaced by the pre-aiming distance as a pre-aiming point, and determining a lane central line according to the lane line information.
It should be understood that the center line of the lane, i.e. the center line of the lane, the preview point is a point spaced from the center of mass of the vehicle to be controlled, and a coordinate system is established for illustration, as shown in fig. 4, a vehicle coordinate system 2 is established on the vehicle 1, the origin is at the center of mass of the vehicle, the x-axis is the longitudinal symmetry axis of the vehicle, the forward direction is positive, the y-axis is the left side of the driver, within the range of lane line 3, the automatic driving transverse control keeps the vehicle running near the center line 4 of the lane, the point spaced from the preview distance 6 in front of the center of mass of the vehicle is the preview point 5, the distance between the preview point 5 and the center line 4 of the lane is controlled, the distance between the vehicle 1 and the center line 4 of the lane is reduced at the next moment, the distance is kept within the acceptable range, and the transverse control of the automatic driving vehicle is realized, the distance between the vehicle 1 and the center line 4 of, and obtaining a target front wheel steering angle by using the deviation at the preview point 5 through a transverse control algorithm, so that the reasonable steering of the vehicle is realized, and the purpose that the vehicle keeps running on the center line of the lane is achieved.
And step S502, performing transverse control on the vehicle to be controlled according to the preview point and the lane central line.
Specifically, the transverse control of the vehicle to be controlled according to the preview point and the lane center line includes calculating a vertical distance between the preview point and the lane center line, determining whether the vertical distance is greater than a preset distance threshold, calculating a deviation value between the vertical distance and the preset distance threshold when the vertical distance is greater than the preset distance threshold, calculating a target front wheel steering angle according to the deviation value, and performing transverse control on the vehicle to be controlled according to the target front wheel steering angle.
It can be understood that the vertical distance between the pre-aiming point and the center line of the lane is calculated, the vertical distance is compared with a preset distance threshold, when the vertical distance is greater than the preset distance threshold, a deviation value is calculated, a target front wheel steering angle is determined according to the deviation value, and the vehicle to be controlled is controlled transversely according to the target front wheel steering angle, so that the vertical distance between the pre-aiming point and the center line of the lane is smaller than the preset distance threshold, and the vehicle can run stably.
In the embodiment, the point which is in front of the centroid of the vehicle to be controlled and is spaced by the pre-aiming distance is used as the pre-aiming point, the lane center line is determined according to the lane line information, and the vehicle to be controlled is controlled transversely according to the pre-aiming point and the lane center line, so that the vertical distance between the pre-aiming point and the lane center line is smaller than the preset distance threshold, and the vehicle runs stably.
In an embodiment, as shown in fig. 5, a third embodiment of the automatic driving lateral control method according to the present invention is proposed based on the first embodiment or the second embodiment, and in this embodiment, the step S40 includes:
step S401, fuzzy processing is carried out on the current vehicle speed and the current road curvature, and fuzzy parameters are obtained.
It can be understood that before calculation, the current vehicle speed and the current road curvature need to be subjected to fuzzy processing to obtain fuzzy parameters, and then the pre-aiming distance is obtained according to the fuzzy parameters and a preset fuzzy rule table.
And S402, inputting the fuzzy parameters into a preset fuzzy rule table to obtain a target numerical value.
And S403, calculating the pre-aiming distance according to the target numerical value.
It should be noted that the preset fuzzy rule table may select a typical fuzzy rule form:
IF x is G and y is H,Then z=C,
wherein, the variables x and y are input, the variable z is output, G and H are input fuzzy sets of x and y respectively, C is a fuzzy set of z variable, the basic input of the method is the current speed V and the current road curvature rho of the vehicle to be controlled, the output is the pre-aiming distance L, the membership function of the fuzzy controller adopts the most common isosceles triangle membership function, the speed V range of the vehicle is (0,30) and the unit is m/s in the normal running of the vehicle, the value range of the current road curvature rho is (0,0.01) and the unit is 1/m, the range of the output pre-aiming distance L is (0,60) and the unit is m, the vehicle speed and the road curvature are averagely divided into 7 fuzzy subsets, the output pre-aiming distance is also divided into 7 fuzzy subsets, and the 7 fuzzy subsets are respectively minimum, small, and small in the fuzzy language, The fuzzy target is small, normal, large and large, so that 49 fuzzy rules are output, an algebraic product calculation method is adopted for 'and' operation in the fuzzy reasoning process, a maximum product calculation method is adopted for synthesis operation, an integral calculation method is adopted for implication operation, fuzzy quantity is converted into clear quantity, a weighted average algorithm is adopted, the fuzzy quantity is a target numerical value, and finally expected pre-aiming distance output is obtained.
In the embodiment, the current vehicle speed and the current road curvature are subjected to fuzzy processing to obtain fuzzy parameters, the fuzzy parameters are input into a preset fuzzy rule table to obtain a target numerical value, and the pre-aiming distance is calculated according to the target numerical value, so that the pre-aiming distance is calculated according to the current vehicle speed, the current road curvature and the preset fuzzy rule table.
Furthermore, an embodiment of the present invention further provides a storage medium, where an automatic driving lateral control program is stored on the storage medium, and the automatic driving lateral control program, when executed by a processor, implements the following operations:
the method comprises the steps of obtaining the current speed of a vehicle to be controlled and obtaining the current image information of a preset area in front of the vehicle to be controlled;
extracting lane line information of a lane where the vehicle to be controlled is located from the current image information;
calculating the curvature of the current road according to the lane line information;
calculating a pre-aiming distance according to the current vehicle speed and the current road curvature;
and carrying out transverse control on the vehicle to be controlled according to the pre-aiming distance.
Further, the automatic driving lateral control program when executed by the processor further implements the following operations:
taking a point which is in front of the centroid of the vehicle to be controlled and is spaced by the pre-aiming distance as a pre-aiming point, and determining a lane central line according to the lane line information;
and carrying out transverse control on the vehicle to be controlled according to the preview point and the lane central line.
Further, the automatic driving lateral control program when executed by the processor further implements the following operations:
calculating the vertical distance between the pre-aiming point and the center line of the lane;
judging whether the vertical distance is larger than a preset distance threshold value or not;
and performing transverse control on the vehicle to be controlled according to the judgment result.
Further, the automatic driving lateral control program when executed by the processor further implements the following operations:
when the vertical distance is larger than a preset distance threshold, calculating a deviation value of the vertical distance and the preset distance threshold;
calculating a target front wheel steering angle according to the deviation value;
and carrying out transverse control on the vehicle to be controlled according to the target front wheel steering angle.
Further, the automatic driving lateral control program when executed by the processor further implements the following operations:
carrying out fuzzy processing on the current vehicle speed and the current road curvature to obtain fuzzy parameters;
inputting the fuzzy parameters into a preset fuzzy rule table to obtain a target numerical value;
and calculating the pre-aiming distance according to the target numerical value.
Further, the automatic driving lateral control program when executed by the processor further implements the following operations:
carrying out image recognition processing on the current image information to obtain front road information;
and extracting lane line information of a lane where the vehicle to be controlled is located from the front road information.
Further, the automatic driving lateral control program when executed by the processor further implements the following operations:
fitting the lane line information through a preset polynomial equation to obtain shape parameter information of a road in front of the vehicle to be controlled;
and calculating the curvature of the current road according to the shape parameter information.
In the embodiment, the current speed of the vehicle to be controlled is obtained, the current image information of the preset area in front of the vehicle to be controlled is obtained, the lane line information of the lane where the vehicle to be controlled is located is extracted from the current image information, the current road curvature is calculated according to the lane line information, the pre-aiming distance is calculated according to the current speed and the current road curvature, and the vehicle to be controlled is controlled transversely according to the pre-aiming distance, so that the proper pre-aiming distance is selected according to the current speed and the front road condition of the vehicle, a good transverse control effect of the vehicle is realized, and the technical problem of how to determine the proper pre-aiming distance in real time to control the vehicle transversely is solved.
Further, referring to fig. 6, an embodiment of the present invention further provides an automatic driving lateral control device, including:
the information acquisition module 10 is configured to acquire a current vehicle speed of a vehicle to be controlled, and acquire current image information of a preset area in front of the vehicle to be controlled.
It CAN be understood that the current vehicle speed of the vehicle to be controlled CAN be obtained by a vehicle speed sensor, read from a vehicle CAN bus signal, or obtained by other means, which is not limited in this embodiment.
It can be understood that the current image information of the preset area in front of the vehicle to be controlled may be acquired by a camera installed in the middle of a front windshield of the vehicle, or may be acquired by a vehicle data recorder, or may be acquired by other methods, which is not limited in this embodiment.
It should be understood that the vision sensor mainly comprises a light source, a lens, an image sensor, an analog-to-digital converter, an image processor, an image memory and the like, the main function of the vision sensor is to obtain enough most original images to be processed by a machine vision system, the image sensor is used for converting images collected by the lens into digital or analog signals to be output, the vision sensor is a core component of vision detection, the vision sensor mainly comprises a charge coupled device image sensor and a metal oxide semiconductor image sensor, the image sensor with high cost performance is selected according to research objects and application occasions and simultaneously the vehicle-mounted practical situation is fully considered, and the hardware connection mode of signals of the vision sensor and automatic driving transverse control equipment is that the signals of the vision sensor are connected through a CAN network.
And a lane information module 20, configured to extract lane line information of a lane where the vehicle to be controlled is located from the current image information.
It should be understood that the current image information may include various images, for example, there may be a front vehicle image, a pedestrian image, a roadside building image, a front road image, etc., and of course, more or less image information may be included, which is not limited in this embodiment.
It can be understood that the subsequent steps only need to use the lane line information of the lane where the vehicle to be controlled is located, and therefore, the lane where the vehicle to be controlled is located needs to be determined first, then the front road information is extracted from the current image information, and the lane line information corresponding to the lane where the vehicle to be controlled is located is extracted from the front road information.
And the road curvature module 30 is used for calculating the curvature of the current road according to the lane line information.
It should be noted that, specifically, calculating the curvature of the current road according to the lane line information includes fitting the lane line information by a preset polynomial equation to obtain shape parameter information of the road in front of the vehicle to be controlled, and calculating the curvature of the current road according to the shape parameter information.
It should be understood that the shape parameter information of the road in front of the vehicle to be controlled can be obtained by fitting the lane line information, and the curvature of the current road can be calculated according to the shape parameter information.
And the pre-aiming distance module 40 is used for calculating the pre-aiming distance according to the current vehicle speed and the current road curvature.
It should be noted that the curvature of the current road is obtained from the outside in real time, and the current vehicle speed is the longitudinal control of the vehicle, so the key to coordinate the relationship between the three is how to adaptively adjust the pre-aiming distance according to the change of the curvature of the current road and the longitudinal vehicle speed, and there is no definite mathematical relationship between the three, so the pre-aiming distance is obtained by adopting a fuzzy control method in the scheme.
And the transverse control module 50 is used for carrying out transverse control on the vehicle to be controlled according to the pre-aiming distance.
It will be appreciated that an appropriate home point may be selected based on the home distance so that the vehicle to be controlled is controlled laterally by the home point.
In the embodiment, the current speed of the vehicle to be controlled is obtained, the current image information of the preset area in front of the vehicle to be controlled is obtained, the lane line information of the lane where the vehicle to be controlled is located is extracted from the current image information, the current road curvature is calculated according to the lane line information, the pre-aiming distance is calculated according to the current speed and the current road curvature, and the vehicle to be controlled is controlled transversely according to the pre-aiming distance, so that the proper pre-aiming distance is selected according to the current speed and the front road condition of the vehicle, a good transverse control effect of the vehicle is realized, and the technical problem of how to determine the proper pre-aiming distance in real time to control the vehicle transversely is solved.
In an embodiment, the lateral control module 50 is further configured to use a point spaced by the pre-aiming distance in front of the centroid of the vehicle to be controlled as a pre-aiming point, and determine a lane center line according to the lane line information; and carrying out transverse control on the vehicle to be controlled according to the preview point and the lane central line.
In an embodiment, the lateral control module 50 is further configured to calculate a vertical distance between the pre-aiming point and the lane center line; judging whether the vertical distance is larger than a preset distance threshold value or not; and performing transverse control on the vehicle to be controlled according to the judgment result.
In an embodiment, the lateral control module 50 is further configured to calculate a deviation value between the vertical distance and a preset distance threshold when the vertical distance is greater than the preset distance threshold; calculating a target front wheel steering angle according to the deviation value; and carrying out transverse control on the vehicle to be controlled according to the target front wheel steering angle.
In an embodiment, the preview distance module 40 is further configured to perform fuzzy processing on the current vehicle speed and the current road curvature to obtain a fuzzy parameter; inputting the fuzzy parameters into a preset fuzzy rule table to obtain a target numerical value; and calculating the pre-aiming distance according to the target numerical value.
In an embodiment, the lane information module 20 is further configured to perform image recognition processing on the current image information to obtain front road information; and extracting lane line information of a lane where the vehicle to be controlled is located from the front road information.
In an embodiment, the road curvature module 30 is further configured to perform fitting processing on the lane line information through a preset polynomial equation to obtain shape parameter information of a road in front of the vehicle to be controlled; and calculating the curvature of the current road according to the shape parameter information.
For other embodiments or specific implementation methods of the automatic driving lateral control device according to the present invention, reference may be made to the above embodiments, and details are not repeated herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product stored in a computer readable storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above, and including instructions for enabling an intelligent automatic driving lateral control device (such as a mobile phone, a computer, an automatic driving lateral control device, an air conditioner, or a network automatic driving lateral control device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. An automatic driving lateral control method characterized by comprising the steps of:
the method comprises the steps of obtaining the current speed of a vehicle to be controlled and obtaining the current image information of a preset area in front of the vehicle to be controlled;
extracting lane line information of a lane where the vehicle to be controlled is located from the current image information;
calculating the curvature of the current road according to the lane line information;
calculating a pre-aiming distance according to the current vehicle speed and the current road curvature;
and carrying out transverse control on the vehicle to be controlled according to the pre-aiming distance.
2. The automatic driving lateral control method according to claim 1, wherein the lateral control of the vehicle to be controlled according to the pre-aiming distance specifically comprises:
taking a point which is in front of the centroid of the vehicle to be controlled and is spaced by the pre-aiming distance as a pre-aiming point, and determining a lane central line according to the lane line information;
and carrying out transverse control on the vehicle to be controlled according to the preview point and the lane central line.
3. The automatic driving lateral control method according to claim 2, wherein the lateral control of the vehicle to be controlled according to the preview point and the lane center line specifically comprises:
calculating the vertical distance between the pre-aiming point and the center line of the lane;
judging whether the vertical distance is larger than a preset distance threshold value or not;
and performing transverse control on the vehicle to be controlled according to the judgment result.
4. The automatic driving lateral control method according to claim 3, wherein the lateral control of the vehicle to be controlled according to the determination result specifically comprises:
when the vertical distance is larger than a preset distance threshold, calculating a deviation value of the vertical distance and the preset distance threshold;
calculating a target front wheel steering angle according to the deviation value;
and carrying out transverse control on the vehicle to be controlled according to the target front wheel steering angle.
5. The automatic driving lateral control method of claim 1, wherein calculating a pre-address distance based on the current vehicle speed and the current road curvature, comprises:
carrying out fuzzy processing on the current vehicle speed and the current road curvature to obtain fuzzy parameters;
inputting the fuzzy parameters into a preset fuzzy rule table to obtain a target numerical value;
and calculating the pre-aiming distance according to the target numerical value.
6. The automatic driving lateral control method according to claim 1, wherein the extracting lane line information of the lane in which the vehicle to be controlled is located from the current image information specifically comprises:
carrying out image recognition processing on the current image information to obtain front road information;
and extracting lane line information of a lane where the vehicle to be controlled is located from the front road information.
7. The automatic driving lateral control method according to any one of claims 1 to 6, wherein the calculating of the current road curvature from the lane line information specifically includes:
fitting the lane line information through a preset polynomial equation to obtain shape parameter information of a road in front of the vehicle to be controlled;
and calculating the curvature of the current road according to the shape parameter information.
8. An autonomous driving lateral control apparatus, characterized in that the autonomous driving lateral control apparatus comprises:
the information acquisition module is used for acquiring the current speed of a vehicle to be controlled and acquiring the current image information of a preset area in front of the vehicle to be controlled;
the lane information module is used for extracting lane line information of a lane where the vehicle to be controlled is located from the current image information;
the road curvature module is used for calculating the curvature of the current road according to the lane line information;
the pre-aiming distance module is used for calculating a pre-aiming distance according to the current vehicle speed and the current road curvature;
and the transverse control module is used for transversely controlling the vehicle to be controlled according to the pre-aiming distance.
9. An automatic driving lateral control apparatus characterized by comprising: memory, a processor and an autopilot lateral control program stored on the memory and executable on the processor, the autopilot lateral control program being configured with steps to implement an autopilot lateral control method according to one of claims 1 to 7.
10. A storage medium, characterized in that the storage medium has stored thereon an automatic driving lateral control program which, when executed by a processor, implements the steps of the automatic driving lateral control method according to any one of claims 1 to 7.
CN201911188226.8A 2019-11-26 2019-11-26 Automatic driving lateral control method, device, equipment and storage medium Pending CN110789517A (en)

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