CN115309170A - Method, device and system for planning track by considering comfort constraint - Google Patents
Method, device and system for planning track by considering comfort constraint Download PDFInfo
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Abstract
The invention discloses a method, a device and a system for planning a track in consideration of comfort constraint, wherein the method comprises the following steps: calculating the coordinates of projection points projected from the self vehicle to a reference line according to the global position of the self vehicle and the information of the reference line, and sampling to obtain discrete original reference points; step two, obtaining a path optimization result by constructing and calculating a cost function and constraint of vehicle driving path planning, and calculating an orientation angle and a curvature corresponding to the path planning according to the path optimization result to obtain a smoothed path; thirdly, obtaining a speed optimization result by constructing and calculating a cost function and a constraint of the vehicle running speed plan, and calculating an orientation angle and a curvature corresponding to the speed plan according to the speed optimization result to obtain a smoothed speed; and step four, fusing the smoothed speed and the path to obtain a smooth track with speed information. The invention can carry out constraint optimization on the planned path and speed of the automatic driving vehicle and realize the riding comfort experience of automatic driving.
Description
Technical Field
The invention belongs to the field of trajectory planning of automatic driving, and relates to a method, a device and a system for trajectory planning considering comfort constraint.
Background
In the field of trajectory planning of automatic driving, path planning and speed planning are generally decoupled and solved, and trajectory planning is taken as an important ring in automatic driving, so that not only is the safety of a final vehicle driving trajectory determined, but also the comfort of automatic driving and riding is reflected. Most of the existing trajectory planning algorithms are solved by constructing an optimization problem, and a comfort item is put into a cost function (soft constraint) of the optimization problem, so that the planning result in some scenes cannot completely meet the comfort requirement of riding.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a track planning method, a device and a system considering comfort constraint, which can carry out constraint optimization on a planned path and speed of an automatic driving vehicle and realize riding comfort experience of automatic driving, and the specific technical scheme is as follows:
a trajectory planning method taking comfort constraints into account, comprising the steps of:
calculating a projection point coordinate projected to a reference line by the self-vehicle according to the positioned self-vehicle global position and the information of the reference line, and sampling the projection point coordinate to a fixed length at equal intervals to obtain a plurality of discrete original reference points;
step two, optimizing the path plan by constructing and calculating a cost function and constraint of the vehicle driving path plan to obtain a path optimization result, and calculating an orientation angle and a curvature corresponding to the path plan according to the path optimization result to obtain a smoothed path;
thirdly, optimizing the planned speed by constructing and calculating a cost function and constraint of the vehicle running speed plan to obtain a speed optimization result, and calculating an orientation angle and a curvature corresponding to the speed plan to obtain a smoothed speed;
and step four, fusing the smoothed speed and the smoothed path to obtain a smooth track with speed information.
Further, the step one specifically includes the following sub-steps:
step 1.1: according to the global position of the vehicle given by the positioning module of the vehicleAnd purpose of decision givingThe information of the marking lane is used for calculating the coordinate of the reference point of the projection of the self-vehicle on the original lane central line as the reference line) The coordinate of the closest point of the bicycle from the reference line;
step 1.2: for the input reference line information, from the projection point coordinates of the matched reference line) To begin withFor sampling intervals that are sampled equidistantly to a fixed length, comprising n discrete reference points ()、(), …,() In whichWhich represents the coordinates of a rectangular coordinate system,representing a vectorThe included angle between the X axis and the X axis in the rectangular coordinate system,represented as the curvature of the reference line at discrete points.
Further, the second step specifically includes the following sub-steps:
step 2.1: constructing a cost function for path planningThe path cost function comprises two parts, wherein the first part is similar cost of the variable to be optimized and the reference point of the original reference lineThe second part is the smoothing costAs follows:
wherein,for variables to be optimized: ()、(),…,();As the original reference line reference point ()、(),…,();The similar cost weight is in negative correlation with the wheel base L value of the vehicle and in positive correlation with the maximum steering capacity of the vehicle;smoothing the cost weight, which is a fixed value weight;
the similar costSetting the Euclidean distance between a variable to be optimized and an original reference point, wherein the expression is as follows:
the smoothing costSetting the degree of similarity of straight lines between three points, wherein the expression is as follows:
step 2.2: constructing safety constraint of path planning to obtain each variable to be optimized () And (3) deviating from the transverse and longitudinal constraints of the original reference point, wherein the expression is as follows:
step 2.3: constructing curvature constraint of path planning according to vehicle type parameters, wherein the curvature relation between discrete points meets the minimum turning radius constraint of a vehicle, and the expression is as follows:
can be converted into:
wherein,is the distance between the two points and is,setting the minimum turning radius as the constraint of the vehicle parameters;
step 2.4: according to the path cost function obtained in the step 2.1 and the constraint conditions obtained in the step 2.2 and the step 2.3, the final path optimization result is obtained by solving the nonlinear optimization path containing the constraint conditionsI.e. the smoothed roadRadial point coordinate information;
step 2.5: using the path optimization results of step 2.4Calculating the orientation angle and curvature corresponding to the path point, and finally outputting a series of smoothed path point information (),(),…,() I.e. the output smooth path.
Further, the third step specifically includes the following substeps:
step 3.1: constructing a cost function and a constraint of a speed plan, wherein the speed cost function comprises three parts: the first part is the similar cost of the speed variable to be optimized and the expected speed of the current road sectionThe second part is the longitudinal acceleration cost of the variable to be optimizedThe third part is the longitudinal acceleration cost of the variable to be optimizedThe specific expression is as follows:
wherein,for variables to be optimized,For the desired speed value in the planned route section,For a cost weight similar to the desired speed,in order to be the acceleration cost weight,in order to be the acceleration cost weight,is a preset fixed sampling time length;
step 3.2: constructing a first comfort constraint of the speed plan, wherein the expression is as follows:
wherein,in order to ensure the maximum speed limit for comfort,in order to meet the maximum value of centripetal acceleration for human comfort,a curvature corresponding to each path point obtained in step 2.5;
step 3.3: constructing a second comfort constraint for the speed plan, the expression being:
step 3.4: constructing a continuity constraint of the speed plan, wherein the expression is as follows:
step 3.5: obtaining a final speed optimization result by solving the optimization speed containing the constraint condition according to the speed cost function obtained in the step 3.1 and the constraint condition obtained in the step 3.2 to the step 3.4I.e. smoothed speed information.
Further, the fourth step is specifically: according to the steps3.5 speed optimization resultsCombining the smoothed path points with the smoothed path points output in step 2.5 to obtain final planning track points (a) meeting comfort constraint),(),…,()。
A track planning system considering comfort constraint comprises a path smoothing planning module and a speed planning module, wherein the path smoothing planning module inputs set reference line information, vehicle global positioning information and vehicle parameters, then applies curvature constraint of the maximum steering capacity of a vehicle to a generated path, and outputs a smooth path meeting the constraint of the minimum turning radius of the vehicle; and the speed planning module calculates the maximum speed limit meeting the riding comfort aiming at the curvature value of the smoothed path point, takes the speed limit as the constraint condition of speed optimization, thereby solving the value of the smoothed speed, finally fuses the smoothed speed and the path and outputs a series of track points with speed information.
A trajectory planning device considering comfort constraints comprises one or more processors and is used for realizing the trajectory planning method considering the comfort constraints.
A computer-readable storage medium, having stored thereon a program which, when executed by a processor, implements a trajectory planning method as described which takes into account comfort constraints.
Has the advantages that:
the invention applies curvature constraint of the maximum steering capacity of the vehicle to the planned path, so that the smoothed path can meet the control execution capacity of different vehicles; and then speed planning is carried out, the maximum speed limit meeting the riding comfort is calculated according to the curvature value of the path point after the last step of smoothing, and the speed limit is put into a constraint of a speed optimization problem, so that the solved speed value can meet the riding comfort experience.
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FIG. 1 is a general flow diagram of a method for trajectory planning in consideration of comfort constraints according to the present invention;
FIG. 2 is a detailed flow chart of the trajectory planning method of the present invention that considers comfort constraints;
fig. 3 is a schematic structural diagram of a trajectory planning device considering comfort constraints according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and technical effects of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments of the specification.
As shown in fig. 1 and fig. 2, a trajectory planning method considering comfort constraints of the present invention includes the following steps:
step one, calculating a projection point coordinate projected to a reference line from a vehicle according to the positioned global position of the vehicle and the information of the reference line, and sampling the projection point coordinate to a fixed length at equal intervals to obtain a plurality of discrete original reference points, wherein the method specifically comprises the following substeps:
step 1.1: according to the global position of the vehicle given by the positioning module of the vehicleAnd determining the given target lane information, and calculating the projected reference point coordinates of the vehicle on a given reference line (such as the original road center line serving as the reference line)) The coordinate of the closest point of the vehicle to the reference line;
step 1.2: for the input reference line information, from the projection point coordinates of the matched reference line) To begin withFor sampling at equal intervals to a fixed length, the present embodiment takes 0.25m as the sampling interval to sample corresponding reference lines at equal intervals to 50m, and includes n discrete reference points(s) (()、(), …,() WhereinWhich represents the coordinates of a rectangular coordinate system,representing a vectorThe included angle between the X axis and the X axis in the rectangular coordinate system,represented as the curvature of the reference line at discrete points.
Step two, solving a path planning optimization problem by constructing and calculating a cost function and a constraint of vehicle driving path planning to obtain a path optimization result, namely optimizing a planned path, and calculating an orientation angle and a curvature corresponding to the path planning according to the path optimization result to obtain a smoothed path, wherein the method specifically comprises the following substeps:
step 2.1: constructing a cost function of path planning, wherein the path cost function comprises two parts, and the first part is similar cost of a variable to be optimized and an original reference line reference pointThe second part is the smoothing costAs follows:
wherein,for variables to be optimized: ()、(),…,();As the original reference line reference point ()、(),…,();The weight is similar to the cost weight, and can be designed to be in negative correlation with the wheel base L value of the vehicle and in positive correlation with the maximum steering capacity of the vehicle;a smooth cost weight, which can be set to be fixedA fixed value weight;
the similar costThe Euclidean distance between the variable to be optimized and the original reference point can be set, and the expression is as follows:
the smoothing costCan be set as the degree of similarity of straight lines between three points, and the expression is as follows:
step 2.2: constructing safety constraint of path planning to obtain each variable to be optimized () And (3) deviating from the transverse and longitudinal constraints of the original reference point, wherein the expression is as follows:
wherein,、、、is arranged at、The upper and lower bounds in the direction are constrained to ensure that the constrained optimization variable is in a safe range;
step 2.3: constructing curvature constraint of path planning according to vehicle type parameters, wherein the curvature relation between discrete points meets the minimum turning radius constraint of a vehicle, and the expression is as follows:
can be converted into:
wherein,is the distance between the two points and is,the minimum turning radius is restricted, and the minimum turning radius is set by the parameters of the vehicle;
step 2.4: according to the cost function obtained in the step 2.1 and the constraint conditions obtained in the step 2.2 and the step 2.3, the nonlinear optimization path containing the constraint is solved to obtain a final path optimization resultThe coordinate information of the smoothed path point is obtained;
step 2.5: using the path optimization results of step 2.4Calculating the orientation angle and curvature corresponding to the path point, and finally outputting a series of smoothed path point information (),(),…,() I.e. the output smooth path.
Step three, solving a speed planning optimization problem by constructing and calculating a cost function and constraint of the vehicle running speed planning to obtain a speed optimization result, namely optimizing the planned speed, and calculating an orientation angle and a curvature corresponding to the speed planning according to the speed optimization result to obtain a smoothed speed, wherein the method specifically comprises the following substeps:
step 3.1: constructing a cost function and a constraint of a speed plan, wherein the speed cost function comprises three parts: the first part is the similar cost of the speed variable to be optimized and the expected speed of the current road sectionThe second part is the longitudinal acceleration cost of the variable to be optimizedThe third part is the longitudinal acceleration cost of the variable to be optimizedThe specific expression is as follows:
wherein,for variables to be optimized,For the desired speed value in the planned route section,For a cost weight similar to the desired speed,in order to be the acceleration cost weight,in order to be the acceleration cost weight,is a preset fixed sampling time length;
step 3.2: constructing a first comfort constraint of the speed plan, wherein the expression is as follows:
wherein,in order to ensure the maximum speed limit for comfort,in order to meet the maximum value of centripetal acceleration for human comfort,a curvature corresponding to each path point obtained in step 2.5;
step 3.3: constructing a second comfort constraint for the speed plan, the expression being:
step 3.4: constructing a continuity constraint of the speed plan, wherein the expression is as follows:
step 3.5: obtaining a final speed optimization result by solving the optimized speed containing the constraint according to the speed cost function obtained in the step 3.1 and the constraint conditions obtained in the steps 3.2 to 3.4I.e. smoothed speed information.
And step four, finally, fusing the smoothed speed and the smoothed path to obtain a smooth track with speed information.
Specifically, the speed optimization result obtained according to step 3.5Combining the path points with the smoothed path points output in step 2.5 to obtain final planning trajectory points (b) meeting comfort constraints),(),…,()。
A trajectory planning system taking comfort constraints into consideration by adopting the method comprises the following steps: a path smooth planning module and a speed planning module. The path smooth planning module firstly inputs set reference line information, vehicle global positioning information and vehicle parameters, and then applies curvature constraint of the maximum steering capacity of the vehicle to the generated path, thereby outputting a smooth path meeting the constraint of the minimum turning radius of the vehicle and enabling the smooth path to meet the control execution capacities of different vehicles; the speed planning module calculates the maximum speed limit meeting the riding comfort aiming at the curvature value of the path point after smoothing, and puts the speed limit into the constraint of the speed optimization problem, thereby ensuring that the solved smooth speed value can meet the riding comfort experience, finally fusing the smoothed speed with the path, and outputting a series of track points with speed information.
Corresponding to the embodiment of the track planning method considering the comfort constraint, the invention also provides an embodiment of a track planning device considering the comfort constraint.
Referring to fig. 3, a trajectory planning apparatus considering comfort constraints according to an embodiment of the present invention includes one or more processors, and is configured to implement a trajectory planning method considering comfort constraints in the foregoing embodiment.
The embodiment of the trajectory planning device considering the comfort constraint can be applied to any equipment with data processing capability, such as computers and other equipment or devices. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. The software implementation is taken as an example, and as a logical device, the device is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory for running through the processor of any device with data processing capability. In terms of hardware, as shown in fig. 3, a hardware structure diagram of any device with data processing capability where the trajectory planning device considering comfort constraints is located according to the present invention is shown, where in addition to the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 3, any device with data processing capability where the device is located in the embodiment may also include other hardware according to the actual function of the any device with data processing capability, which is not described again.
The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present invention. One of ordinary skill in the art can understand and implement it without inventive effort.
An embodiment of the present invention further provides a computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, the method for trajectory planning considering comfort constraints in the foregoing embodiments is implemented.
The computer readable storage medium may be an internal storage unit, such as a hard disk or a memory, of any data processing capability device described in any of the foregoing embodiments. The computer readable storage medium may also be an external storage device such as a plug-in hard disk, a Smart Media Card (SMC), an SD Card, a Flash memory Card (Flash Card), etc. provided on the device. Further, the computer readable storage medium may include both internal storage units and external storage devices of any data processing capable device. The computer-readable storage medium is used for storing the computer program and other programs and data required by the arbitrary data processing-capable device, and may also be used for temporarily storing data that has been output or is to be output.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way. Although the foregoing has described the practice of the present invention in detail, it will be apparent to those skilled in the art that modifications may be made to the practice of the invention as described in the foregoing examples, or that certain features may be substituted in the practice of the invention. All changes, equivalents and the like which come within the spirit and principles of the invention are desired to be protected.
Claims (8)
1. A trajectory planning method taking into account comfort constraints, characterized by comprising the steps of:
calculating a projection point coordinate projected to a reference line by the self-vehicle according to the positioned self-vehicle global position and the information of the reference line, and sampling the projection point coordinate to a fixed length at equal intervals to obtain a plurality of discrete original reference points;
step two, optimizing the path plan by constructing and calculating a cost function and constraint of the vehicle driving path plan to obtain a path optimization result, and calculating an orientation angle and a curvature corresponding to the path plan according to the path optimization result to obtain a smoothed path;
thirdly, optimizing the planned speed by constructing and calculating a cost function and constraint of the vehicle running speed plan to obtain a speed optimization result, and calculating an orientation angle and curvature corresponding to the speed plan to obtain a smoothed speed;
and step four, fusing the smoothed speed and the smoothed path to obtain a smooth track with speed information.
2. A trajectory planning method taking into account comfort constraints, as claimed in claim 1, characterized in that said first step specifically comprises the following substeps:
step 1.1: according to the global position of the vehicle given by the positioning module of the vehicleAnd determining given target lane information, and calculating the coordinate of the reference point of the vehicle projected by taking the central line of the original road as the reference line) The coordinate of the closest point of the vehicle to the reference line;
step 1.2: for the input reference line information, from the projection point coordinates of the matched reference line) To begin withFor sampling at intervals equidistant to a fixed length, n discrete reference points are included ()、(), …,() WhereinWhich represents the coordinates of a rectangular coordinate system,representing a vectorThe included angle between the X axis and the X axis in the rectangular coordinate system,represented as the curvature of the reference line at discrete points.
3. A trajectory planning method considering comfort constraints according to claim 2, wherein the second step specifically comprises the following substeps:
step 2.1: constructing a cost function for path planningThe path cost function comprises two parts, wherein the first part is similar cost of the variable to be optimized and the reference point of the original reference lineThe second part is the smoothing costAs follows:
wherein,for variables to be optimized: ()、(),…,();Is an original reference line reference point ()、(),…,();The weight is similar to the cost weight, and is in negative correlation with the vehicle wheel base L value and in positive correlation with the maximum steering capacity of the vehicle;smoothing the cost weight, which is a fixed value weight;
the similar costSetting the Euclidean distance between the variable to be optimized and the original reference point, wherein the expression is as follows:
the smoothing costSetting the degree of similarity of straight lines between three points, wherein the expression is as follows:
step 2.2: constructing safety constraint of path planning to obtain each variable to be optimized () And (3) deviating from the transverse and longitudinal constraints of the original reference point, wherein the expression is as follows:
step 2.3: constructing curvature constraint of path planning according to vehicle type parameters, wherein the curvature relation between discrete points meets the minimum turning radius constraint of a vehicle, and the expression is as follows:
can be converted into:
wherein,is the distance between the two points and is,setting the minimum turning radius as the constraint of the vehicle parameters;
step 2.4: according to the path cost function obtained in the step 2.1 and the constraint conditions obtained in the step 2.2 and the step 2.3, the final path optimization result is obtained by solving the nonlinear optimization path containing the constraint conditionsThe coordinate information of the smoothed path point is obtained;
4. A trajectory planning method taking into account comfort constraints, as claimed in claim 3, characterized in that said step three specifically comprises the following substeps:
step 3.1: constructing a cost function and a constraint of a speed plan, wherein the speed cost function comprises three parts: the first part is the similar cost of the speed variable to be optimized and the expected speed of the road sectionThe second part is the longitudinal acceleration cost of the variable to be optimizedThe third part is the longitudinal acceleration cost of the variable to be optimizedThe specific expression is as follows:
wherein,for variables to be optimized,For the desired speed value in the planned route section,For a cost weight similar to the desired speed,in order to be the acceleration cost weight,in order to be the acceleration cost weight,is a preset fixed sampling time length;
step 3.2: constructing a first comfort constraint of the speed plan, wherein the expression is as follows:
wherein,in order to ensure the maximum speed limit for comfort,in order to meet the maximum value of centripetal acceleration for human comfort,curvature corresponding to each path point obtained in step 2.5;
step 3.3: constructing a second comfort constraint for the speed plan, the expression being:
step 3.4: constructing a continuity constraint of the speed plan, wherein the expression is as follows:
5. Consideration as set forth in claim 4The comfort-constrained trajectory planning method is characterized in that the fourth step specifically comprises the following steps: speed optimization result obtained according to step 3.5Combining the path points with the smoothed path points output in the step 2.5 to obtain final planning track points (A)),(),…,()。
6. A trajectory planning system adopting the trajectory planning method considering the comfort constraint according to any one of claims 1 to 5, comprising a path smoothing planning module and a speed planning module, wherein the path smoothing planning module inputs the set reference line information, the vehicle global positioning information and the vehicle parameters, then applies the curvature constraint of the maximum steering capacity of the vehicle to the generated path, and outputs a smooth path meeting the minimum turning radius constraint of the vehicle; and the speed planning module calculates the maximum speed limit according to the curvature value of the smoothed path point, takes the speed limit as a constraint condition of speed optimization, thereby solving the value of the smoothed speed, and finally fuses the smoothed speed and the path to output a series of track points with speed information.
7. A trajectory planning device considering comfort constraints, which is characterized by comprising one or more processors and is used for realizing the trajectory planning method considering comfort constraints, wherein the trajectory planning method considering comfort constraints is claimed in any one of claims 1 to 5.
8. A computer-readable storage medium, having stored thereon a program which, when executed by a processor, implements a trajectory planning method taking into account comfort constraints as claimed in any one of claims 1 to 5.
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