CN118144781A - Virtual lane line generation method, control method, device, vehicle and medium - Google Patents
Virtual lane line generation method, control method, device, vehicle and medium Download PDFInfo
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Abstract
The method comprises the steps of obtaining lane line data of two sides of a current target lane of a first vehicle, determining sensing lane reference line information of the target lane based on the lane line data, obtaining vehicle state information of the first vehicle, determining predicted track information of the first vehicle based on the vehicle state information, obtaining historical track information of a second vehicle, which is the nearest vehicle in the same lane as the first vehicle and in front of the first vehicle in the running direction, determining virtual lane line information of the current target lane of the first vehicle based on the sensing lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, and controlling the first vehicle transversely by the virtual lane line information.
Description
Technical Field
The disclosure relates to the technical field of automobiles, in particular to a virtual lane line generation method, a vehicle control method, electronic equipment, a vehicle and a computer storage medium.
Background
The advanced driving assistance system (ADVANCED DRIVING ASSISTANCE SYSTEM, ADAS) senses the surrounding environment by using a sensor arranged on the automobile, and performs static and dynamic object identification, detection and tracking according to the sensing result, so that a driver can perceive possible danger in advance, and the comfort and safety of automobile driving are improved.
Advanced driving assistance systems may typically provide longitudinal functions (such as forward collision warning, automatic emergency braking, etc.) as well as lateral functions (such as lane departure warning functions, lane departure assistance systems, etc.), for which it is often necessary to rely on the perceived outcome of a lane line, the use of which may be affected if the lane line is blocked or not.
Disclosure of Invention
The embodiment of the disclosure provides at least a method for generating a virtual lane, a control method, electronic equipment, a vehicle and a storage medium, which can improve the generation precision of the virtual lane, thereby improving the use stability of the transverse function of the vehicle.
The embodiment of the disclosure provides a method for generating virtual lane lines, which comprises the following steps:
Lane line data of two sides of a target lane where a first vehicle is currently located are obtained, and perceived lane reference line information of the target lane is determined based on the lane line data;
Acquiring vehicle state information of the first vehicle, and determining predicted track information of the first vehicle based on the vehicle state information;
acquiring historical track information of a second vehicle, wherein the second vehicle is the nearest vehicle which is positioned on the same lane as the first vehicle and is positioned in front of the first vehicle in the running direction;
And determining virtual lane line information of a target lane where the first vehicle is currently located based on the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, wherein the virtual lane line information is used for transversely controlling the first vehicle.
In the embodiment of the disclosure, based on the perceived lane reference line information, the predicted track information of the first vehicle and the history track information of the second vehicle, the virtual lane line information of the target lane where the first vehicle is currently located is determined, so that the accuracy of the virtual lane line information can be improved, and the accuracy of the first vehicle in transverse control is improved.
Further, even if the lane line is blocked or no lane line exists, the virtual lane line information can be normally generated according to the three factors, and the first vehicle is subjected to the transverse control function based on the virtual lane line information, so that the stability of the transverse control function of the vehicle is improved.
In one possible implementation manner, the determining virtual lane line information of the target lane where the first vehicle is currently located based on the perceived lane reference line information, the predicted track information of the first vehicle, and the historical track information of the second vehicle includes:
Based on a preset weight coefficient, weighting and fusing the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle to obtain virtual lane reference line information of the target lane;
And determining the virtual lane line information based on the virtual lane reference line information.
In the embodiment of the disclosure, the perceived lane reference line information, the predicted track information of the first vehicle and the history track information of the second vehicle are weighted and fused based on the preset weight coefficient, so that the accuracy of the virtual lane reference line information is improved, and further, because the virtual lane line information is determined based on the virtual lane reference line information, the accuracy of the virtual lane line information can be improved.
In one possible embodiment, the weight coefficients include a first weight coefficient corresponding to the perceived lane reference line information, a second weight coefficient corresponding to predicted trajectory information of the first vehicle, and a third weight coefficient corresponding to historical trajectory information of the second vehicle; the first weight coefficient is proportional to the accuracy of the environmental data perceived by the perception component of the first vehicle, and the second weight coefficient is determined by the first weight coefficient and the third weight coefficient.
In the embodiment of the disclosure, the first weight coefficient is in direct proportion to the precision of the environmental data perceived by the perception component of the first vehicle, for example, if the precision of the environmental data perceived by the perception component of the first vehicle is lower, the precision of the perceived lane reference line information is lower, and the corresponding first weight coefficient is smaller, so that the influence of the perceived lane reference line information on the precision of the virtual lane line information can be reduced, and the precision of the virtual lane line information is improved.
In one possible embodiment, the third weight coefficient is determined to be 0 if the second vehicle is not present in front of the first vehicle traveling direction in the target lane in which the first vehicle is located.
In the embodiment of the disclosure, if the second vehicle does not exist in the target lane where the first vehicle is located, the third weight coefficient is determined to be 0, which indicates that the history track information of the second vehicle does not exist, so that the history track information of the second vehicle is not needed when the virtual lane line information is generated, which is beneficial to improving the accuracy of the virtual lane line information.
In one possible embodiment, the vehicle state information includes steering angle information of a steering wheel of the first vehicle and speed information of the first vehicle; the determining predicted trajectory information of the first vehicle based on the vehicle state information includes:
The predicted track information of the first vehicle is determined based on the steering angle information of the steering wheel of the first vehicle, the speed information of the first vehicle, and the current position of the first vehicle.
In the embodiment of the disclosure, the predicted track information of the first vehicle is determined based on the steering angle information, the speed information and the current position of the steering wheel of the first vehicle, so that the accuracy of the predicted track information can be improved.
In one possible embodiment, the historical track information of the second vehicle is obtained by:
Acquiring a plurality of position information of the second vehicle relative to the first vehicle in a history period;
And performing curve fitting on the plurality of position information to obtain the historical track information of the second vehicle.
In the embodiment of the disclosure, the historical track information of the second vehicle is obtained by performing curve fitting on the plurality of pieces of position information of the second vehicle relative to the first vehicle in the historical time period, so that the accuracy of the historical track information can be improved.
In one possible embodiment, the virtual lane line information includes left virtual lane line information and right virtual lane line information; the determining the virtual lane line information based on the virtual lane reference line information includes:
Acquiring lane width information of the target lane;
And respectively adjusting the virtual lane reference line information based on the lane width information of the target lane to obtain the left virtual lane line information and the right virtual lane line information.
In the embodiment of the disclosure, after the virtual lane reference line information is obtained, the virtual lane reference line information is adjusted based on the lane width information of the target lane, so that the accuracy of the left virtual lane line information and the right virtual lane line information can be improved.
The embodiment of the disclosure provides a vehicle control method, which comprises the following steps:
obtaining virtual lane line information of a target lane where a first vehicle is currently located, wherein the virtual lane line information is obtained based on the virtual lane line generating method in any one of the previous embodiments;
and transversely controlling the first vehicle based on the virtual lane line information.
In the embodiment of the disclosure, the virtual lane line information is determined based on three factors of the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, so that the accuracy of the virtual lane line information can be improved, and the accuracy of the first vehicle in transverse control can be improved.
Further, even if the lane line is blocked or no lane line exists, the virtual lane line information can be normally generated according to the three factors, and the first vehicle is subjected to the transverse control function based on the virtual lane line information, so that the stability of the transverse control function of the vehicle is improved.
And transversely controlling the first vehicle based on the virtual lane line information of the target lane where the first vehicle is currently located, so that the accuracy of transverse control of the vehicle can be improved.
The embodiment of the disclosure provides a virtual lane line generating device, which comprises:
The sensing reference line determining module is used for acquiring lane line data of two sides of a target lane where the first vehicle is currently located and determining sensing lane reference line information of the target lane based on the lane line data;
The prediction track information determining module is used for acquiring the vehicle state information of the first vehicle and determining the prediction track information of the first vehicle based on the vehicle state information;
The historical track information acquisition module is used for acquiring historical track information of a second vehicle, wherein the second vehicle is the nearest vehicle which is positioned on the same lane as the first vehicle and is positioned in front of the first vehicle in the running direction;
The virtual lane line determining module is used for determining virtual lane line information of a target lane where the first vehicle is currently located based on the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, and the virtual lane line information is used for transversely controlling the first vehicle.
In one possible implementation manner, the virtual lane line determining module is specifically configured to:
Based on a preset weight coefficient, weighting and fusing the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle to obtain virtual lane reference line information of the target lane;
And determining the virtual lane line information based on the virtual lane reference line information.
In one possible embodiment, the weight coefficients include a first weight coefficient corresponding to the perceived lane reference line information, a second weight coefficient corresponding to predicted trajectory information of the first vehicle, and a third weight coefficient corresponding to historical trajectory information of the second vehicle; the first weight coefficient is proportional to the accuracy of the environmental data perceived by the perception component of the first vehicle, and the second weight coefficient is determined by the first weight coefficient and the third weight coefficient.
In one possible embodiment, the third weight coefficient is determined to be 0 if the second vehicle is not present in front of the first vehicle traveling direction in the target lane in which the first vehicle is located.
In one possible embodiment, the vehicle state information includes steering angle information of a steering wheel of the first vehicle and speed information of the first vehicle; the predicted track information determining module is specifically configured to:
The predicted track information of the first vehicle is determined based on the steering angle information of the steering wheel of the first vehicle, the speed information of the first vehicle, and the current position of the first vehicle.
In one possible implementation, the apparatus further includes a historical track information generation module; the history track information generating module is specifically configured to:
Acquiring a plurality of position information of the second vehicle relative to the first vehicle in a history period;
And performing curve fitting on the plurality of position information to obtain the historical track information of the second vehicle.
In one possible embodiment, the virtual lane line information includes left virtual lane line information and right virtual lane line information; the virtual lane line determining module is specifically configured to:
Acquiring lane width information of the target lane;
And respectively adjusting the virtual lane reference line information based on the lane width information of the target lane to obtain the left virtual lane line information and the right virtual lane line information.
The embodiment of the disclosure also provides a vehicle control device, including:
The obtaining module is configured to obtain virtual lane line information of a target lane where the first vehicle is currently located, where the virtual lane line information is obtained based on the virtual lane line generating method in any one of the foregoing embodiments;
and the control module is used for transversely controlling the first vehicle based on the virtual lane line information.
The disclosed embodiments also provide an electronic device including a processor, a memory, and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory in communication over the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the method of generating a virtual lane line as in any of the foregoing embodiments, or performing the method of controlling a vehicle as in the foregoing embodiments.
The disclosed embodiments also provide a vehicle including a controller including:
a memory configured to store instructions; and
A processor configured to call the instructions from the memory and to enable the method of generating a virtual lane line, or the method of controlling a vehicle, of any of the preceding embodiments when executing the instructions.
The disclosed embodiments also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the virtual lane line generation method described in any one of the possible implementations.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the aspects of the disclosure.
The foregoing objects, features and advantages of the disclosure will be more readily apparent from the following detailed description of the preferred embodiments taken in conjunction with the accompanying drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for the embodiments are briefly described below, which are incorporated in and constitute a part of the specification, these drawings showing embodiments consistent with the present disclosure and together with the description serve to illustrate the technical solutions of the present disclosure. It is to be understood that the following drawings illustrate only certain embodiments of the present disclosure and are therefore not to be considered limiting of its scope, for the person of ordinary skill in the art may admit to other equally relevant drawings without inventive effort.
Fig. 1 shows a flowchart of a method for generating a virtual lane line according to an embodiment of the present disclosure;
FIG. 2 illustrates a schematic diagram of a target lane provided by an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart of a vehicle control method provided by an embodiment of the present disclosure;
Fig. 4 is a schematic structural diagram of a virtual lane line generating apparatus according to an embodiment of the present disclosure;
Fig. 5 is a schematic structural diagram of another virtual lane line generating apparatus according to an embodiment of the present disclosure;
fig. 6 shows a schematic structural view of a vehicle control apparatus provided by an embodiment of the present disclosure;
fig. 7 shows a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure.
The advanced driving assistance system (ADVANCED DRIVING ASSISTANCE SYSTEM, ADAS) senses the surrounding environment by using a sensor arranged on the automobile, and performs static and dynamic object identification, detection and tracking according to the sensing result, so that a driver can perceive possible danger in advance, and the comfort and safety of automobile driving are improved.
Advanced driving assistance systems may generally provide a longitudinal function, which refers to a function related to vehicle longitudinal control, i.e., acceleration/deceleration, such as a forward collision warning function, an automatic emergency braking function, etc., a lateral function, which refers to a function related to vehicle lateral control, i.e., steering, such as a lane departure warning function, a lane departure assistance system, etc., and a combined function, which refers to a combination of an adaptive cruise control function and a lane keeping assistance function.
It has been found that for a lateral function, which generally needs to depend on the perceived result of a lane line, the use of the lateral function may be affected if the lane line is blocked or if there is no lane line.
Based on the above study, the present disclosure provides a method for generating a virtual lane line, a vehicle-mounted device, a vehicle and a storage medium, which acquire lane line data on two sides of a target lane where a first vehicle is currently located, and determine perceived lane reference line information of the target lane based on the lane line data; acquiring vehicle state information of the first vehicle, and determining predicted track information of the first vehicle based on the vehicle state information; acquiring historical track information of a second vehicle, wherein the second vehicle is the nearest vehicle which is positioned on the same lane as the first vehicle and is positioned in front of the first vehicle in the running direction; and determining virtual lane line information of a target lane where the first vehicle is currently located based on the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, wherein the virtual lane line information is used for transversely controlling the first vehicle.
In the embodiment of the disclosure, based on the perceived lane reference line information, the predicted track information of the first vehicle and the history track information of the second vehicle, the virtual lane line information of the target lane where the first vehicle is currently located is determined, so that the accuracy of the virtual lane line information can be improved, and the accuracy of the first vehicle in transverse control is improved.
Further, even if the lane line is blocked or no lane line exists, the virtual lane line information can be normally generated according to the three factors, and the first vehicle is subjected to the transverse control function based on the virtual lane line information, so that the stability of the transverse control function of the vehicle is improved.
For the convenience of understanding the present embodiment, first, an execution body of the virtual lane line generating method provided by the embodiment of the present disclosure will be described in detail. The execution main body of the virtual lane line generating method provided by the embodiment of the disclosure is a vehicle, and the vehicle can comprise various controllers, and in the running process of the vehicle, the controllers generate the virtual lane line for automatic driving and transversely control the vehicle based on the virtual lane line. Specifically, the controller may be a whole vehicle controller, or may be other domain controllers of a vehicle, for example, a vehicle body domain controller, a cabin domain controller, an intelligent driving domain controller, or the like, which is not particularly limited.
The vehicle may be an automobile powered by a power battery. Specifically, the vehicle may include a Battery electric vehicle (BEV, battery ELECTRIC VEHICLE), a Hybrid electric vehicle (HEV, hybrid ELECTRIC VEHICLE), a Plug-In Hybrid ELECTRIC VEHICLE (PHEV), and the like, without specific limitation. The types of vehicles include, but are not limited to, cars, coaches, vans, tractors, and the like, and are not limited thereto. Wherein, cars, buses, trucks, etc. may be collectively referred to as automobiles. In the embodiment of the present application, an automobile is taken as an example for explanation.
In other embodiments, the execution subject may also be an electronic device, which may be a terminal device or a server. The terminal device may also be a vehicle-mounted device, a mobile device, a user terminal, a handheld device, a computing device, a wearable device, an AR (Augmented Reality ) display device, a VR (Virtual Reality) display device, or the like. If the execution subject is a server, the server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, big data, an artificial intelligence platform, and the like. In addition, the method for generating the virtual lane line can also be realized by a mode that a processor calls computer readable instructions stored in a memory.
The method for generating the virtual lane line provided by the embodiment of the application is described in detail below with reference to the accompanying drawings. Referring to fig. 1, a flowchart of a method for generating a virtual lane line according to an embodiment of the present disclosure is shown, where the method includes steps S101 to S104, where:
S101, lane line data of two sides of a target lane where a first vehicle is currently located are obtained, and perceived lane reference line information of the target lane is determined based on the lane line data.
Here, the lane line data may be acquired through a sensing part provided on the first vehicle, wherein the sensing part may include a radar part and/or an image acquisition part, wherein the radar part is mounted on the body of the vehicle, and is used for sensing an object in an external environment of the first vehicle, and the object may include lane lines, vehicles, pedestrians, and various static objects (such as trees, walls, buildings), parking spaces, and the like. Alternatively, the radar component may be an ultrasonic radar, a laser radar, or a millimeter wave radar, and the specific type may be determined according to actual requirements, which is not limited herein.
The image acquisition component is used for acquiring an image of the environment where the first vehicle is located. Alternatively, the image acquisition component may be a pan-around camera, so as to improve the coverage range of the image capturing angle. Image capturing components include, but are not limited to, infrared cameras, depth cameras, fisheye cameras, pinhole cameras, RGB sensors, structured light sensors, and the like.
In some embodiments, the number of the sensing components may be set according to actual requirements, which is not limited herein. For example, the sensing component may include a plurality of radar components, and the plurality of radar components may be distributed in different orientations of the body of the vehicle, such that the environment in which the first vehicle is located may be detected from a plurality of angles.
In the embodiment of the disclosure, the perceived lane reference line information refers to lane centerline information, that is, lane centerline information determined according to perceived lane line data.
Alternatively, since the left lane line and the right lane line are provided on both sides of the target lane, the lane line data perceived by the perception component may include the left lane line data and the right lane line data, so that when the perceived lane reference line information of the target lane is determined based on the lane line data, the perceived lane reference line information of the target lane may be determined according to the left lane line data and the right lane line data.
The left lane line data may include a position of each point on the left lane line relative to the first vehicle, the right lane line data may include a position of each point on the right lane line relative to the first vehicle, so that curve fitting may be performed on a position of each point on the left lane line relative to the first vehicle to obtain left perceived lane line information, and curve fitting may be performed on a position of each point on the right lane line relative to the first vehicle to obtain right perceived lane line information, and then the perceived lane reference line information may be determined based on the left perceived lane line information and the right perceived lane line information.
Here, in curve fitting each point on the left lane line and curve fitting each point on the right lane line, fitting may be performed based on a preset lane line expression, where the preset lane line expression is as shown in formula (1):
y＝C0+C1·x+C2·x2+C3·x3 (1)
wherein C0 is the intercept, C1 is the tangent of the included angle, C2 is one half of the real-time curvature, and C3 is the rate of change of the curvature.
In this way, when fitting the position of each point on the left lane line with respect to the first vehicle based on the above-described lane line expression, a left lane line expression for characterizing the left perceived lane line information can be obtained as shown in formula (2):
yl＝C0l+C1l·x+C2l·x2+C3l·x3 (2)
Similarly, when fitting the position of each point on the right lane line with respect to the first vehicle based on the above-described lane line expression, a right lane line expression for characterizing the right perceived lane line information can be obtained as shown in formula (3):
yr＝C0r+C1r·x+C2r·x2+C3r·x3 (3)
It should be noted that the meanings of the polynomial coefficients in the formula (2) and the formula (3) are the same as those of the formula (1), and are not described here.
In this way, after the left lane line expression and the right lane line expression are obtained, the perceived lane reference line information can be determined, specifically, the perceived lane reference line expression for representing the perceived lane reference line information can be obtained by averaging, for example, the polynomial coefficients of the left lane line expression and the right lane line expression are respectively averaged, as shown in formula (4):
yc＝C0c+C1c·x+C2c·x2+C3c·x3 (4)
Wherein the method comprises the steps of ,C0c＝(C0l+C0r)/2,C1c＝(C1l+C1r)/2,C2c＝(C2l+C2r)/2,C3c＝(C3l+C3r)/2.
For example, please refer to fig. 2, which is a schematic diagram of a target lane according to an embodiment of the disclosure. As shown in fig. 2, a first vehicle 100 travels in a target lane 10, the target lane 10 including a left lane line 11 and a right lane line 12, and the perceived lane reference line may be a broken line 13 in the figure.
In other embodiments, if the first vehicle has only one lane line in the current driving section in the target lane, the acquired lane line data may include only one lane line data, in which case, lane width information of the target lane may be acquired, and perceived lane reference line information of the target lane may be determined based on the lane width information and the lane line data.
S102, acquiring vehicle state information of the first vehicle, and determining predicted track information of the first vehicle based on the vehicle state information.
The vehicle state information may include, among other things, steering angle information of a steering wheel of the first vehicle and speed information of the first vehicle.
Here, the rotation angle information of the steering wheel may be acquired by an angle sensor in the sensing part, and the speed information of the first vehicle may be acquired by an inertia sensor (INNERTIAL MEASUREMENT UNIT, IMU) in the sensing part.
Alternatively, when the predicted track information of the first vehicle is determined based on the vehicle state information, the predicted track information of the first vehicle may be determined based on the steering angle information of the steering wheel of the first vehicle, the speed information of the first vehicle, and the current position of the first vehicle.
Specifically, the method may comprise the following steps (1) to (2):
(1) Based on the steering angle information of the steering wheel of the first vehicle, the speed information of the first vehicle and the current position of the first vehicle, the position of the first vehicle at other moments in a preset time period after the current moment is predicted.
Here, the transmission ratio of the first vehicle may be acquired, wherein the transmission ratio refers to the transmission ratio between the steering wheel and the wheels of the first vehicle, and then the steering angle information of the wheels is determined based on the steering angle information of the steering wheel of the first vehicle and the transmission ratio, as shown in formula (5):
θw＝θs/kr (5)
Wherein, θ s is the rotation angle information of the steering wheel of the first vehicle, k r is the transmission ratio of the first vehicle, and θ w is the rotation angle information of the wheels.
After the corner information of the wheels is obtained, the wheelbase of the first vehicle can be obtained, the turning radius of the first vehicle is determined based on the wheelbase of the first vehicle and the corner information of the wheels, and then the positions of the first vehicle at other moments in a preset time period after the current moment are determined based on the turning radius, the speed information of the first vehicle and the current position of the first vehicle.
The duration of the preset time period may be set according to actual requirements, for example, the period between the acquisition moments of the sensing component is 1 second, and the duration of the preset time period may be 10 seconds or 20 seconds, which is not limited herein.
For the determination of the turning radius, please refer to formula (6):
r＝L/sin(θw) (6)
Wherein L is the wheelbase of the first vehicle, and r is the turning radius.
The position at other times can be determined by equation (7):
Wherein x 0,y0 is the predicted track point of the first vehicle at the i-1 time, Δt is the duration between adjacent times, and v is the speed information of the first vehicle.
Thus, the positions of other moments within the preset time period can be determined according to the above formula (7).
(2) And performing curve fitting on the positions of all the moments in the preset time period to obtain the predicted track information of the first vehicle.
After the positions of all the moments in the preset time period are obtained, curve fitting can be carried out on the positions of all the moments based on a preset lane line expression, and the predicted track information of the first vehicle is obtained.
Wherein, the preset lane line expression is shown in the formula (1) described in the foregoing.
It should be noted that, since the predicted track of the first vehicle is approximately parallel to the lane line of the target lane where the first vehicle is currently located, the predicted track information of the first vehicle may be obtained by directly performing curve fitting on the positions at each time based on the preset lane line expression, and in this embodiment, the predicted track information of the first vehicle is represented by the formula (8):
ye＝C0e+C1e·x+C2e·x2+C3e·x3 (8)
the meaning of each polynomial coefficient in the formula (8) is shown in the formula (1), and will not be described herein.
For example, referring again to fig. 2, the predicted track information of the first vehicle is shown as virtual 14.
S103, historical track information of a second vehicle is acquired, wherein the second vehicle is the nearest vehicle which is positioned on the same lane as the first vehicle and is positioned in front of the first vehicle in the running direction.
For example, referring again to fig. 2, the second vehicle 200 is also traveling on the target lane 10, and its second vehicle 200 is located at the nearest vehicle in front of the traveling direction of the first vehicle 100, and its history is the dotted line 15.
In the present embodiment, the track expression for characterizing the history track information of the second vehicle is as shown in formula 9:
yo＝C0o+C1o·x+C2o·x2+C3o·x3 (9)
The meaning of each polynomial coefficient in the formula (9) is shown in the formula (1), and will not be described herein.
In some embodiments, the historical track information of the second vehicle may be obtained by the following steps (a) - (B):
(A) A plurality of positional information of the second vehicle relative to the first vehicle over a historical period of time is acquired.
Here, the history period refers to a preset period before the current time, wherein the duration of the preset period is not limited, and may be, for example, 2 seconds, 5 seconds, 10 seconds, 15 seconds, etc., and is not limited herein.
In this embodiment, the plurality of pieces of position information of the second vehicle with respect to the first vehicle in the history period may be determined based on the perceived environmental data in the history period.
In other embodiments, the plurality of location information of the second vehicle relative to the first vehicle over the historical period of time may also be obtained by a positioning system (e.g., GPS), without limitation.
(B) And performing curve fitting on the plurality of position information to obtain the historical track information of the second vehicle.
It will be appreciated that after obtaining a plurality of position information of the second vehicle relative to the first vehicle over the historical time period, curve fitting may be performed on the plurality of position information to obtain historical track information of the second vehicle.
It should be appreciated that each location information corresponds to a track point, and that a plurality of track points may form historical track information.
Here, since the predicted track of the first vehicle is approximately parallel to the lane line of the target lane where the first vehicle is currently located, when curve fitting is performed on the plurality of position information, curve fitting may be performed on the plurality of position information directly based on a preset lane line expression, so as to obtain the history track information of the second vehicle.
Wherein, the preset lane line expression is shown in the formula (1) described in the foregoing.
That is, each positional information is input into the formula (1), so that the coefficients of the polynomials can be determined, thereby obtaining the history track information of the second vehicle.
S104, determining virtual lane line information of a target lane where the first vehicle is currently located based on the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, wherein the virtual lane line information is used for transversely controlling the first vehicle.
Based on the foregoing, the lateral control refers to steering control of the steering wheel of the first vehicle.
It can be understood that after the perceived lane reference line information, the predicted track information of the first vehicle, and the historical track information of the second vehicle are obtained, the virtual lane line information of the target lane where the first vehicle is currently located can be determined based on the three information.
In some embodiments, the perceived lane reference line information, the predicted track information of the first vehicle, and the historical track information of the second vehicle may be weighted and fused based on a preset weight coefficient to obtain virtual lane reference line information of the target lane, and then the virtual lane reference line information is determined based on the virtual lane reference line information.
The preset weight coefficient comprises a first weight coefficient corresponding to the sensing lane reference line information, a second weight coefficient corresponding to the predicted track information of the first vehicle and a third weight coefficient corresponding to the history track information of the second vehicle.
Here, the first weight coefficient is proportional to the accuracy of the environmental data perceived by the perceived component of the first vehicle, and the second weight coefficient is determined by the first weight coefficient and the third weight coefficient.
It will be understood that, if the accuracy of the environmental data perceived by the perception component of the first vehicle is higher, the first weight coefficient is larger, if the accuracy of the environmental data perceived by the perception component of the first vehicle is lower, the first weight coefficient is smaller, and it should be noted that, since the sum of the weight coefficients is 1, a corresponding floating interval, for example, [0,0.8], may be set for the first weight coefficient, for example, if two lane lines of the target lane on which the first vehicle runs are severely blocked or lack lane lines, the reference of the environmental data currently perceived is illustrated as being lower, and therefore, the first weight coefficient may be set to be smaller, for example, 0.5, if one lane line in the target lane is blocked, the first weight coefficient may be set to 0.2 or 0.15, or the like, and specifically, may be adaptively set according to the accuracy.
In the present embodiment, the sum of the first weight coefficient, the second weight coefficient, and the third weight coefficient is 1, and if the first weight coefficient is set to α and the second weight coefficient is set to β, the third weight coefficient is set to (1- α - β).
Based on the above formula (4), formula (8), formula (9), and each weight coefficient, a virtual lane reference line expression for characterizing virtual lane reference line information can be obtained, as shown in formula (10):
yt＝α·yc+β·yo+(1-α-β)·ye (10)
Wherein y t is virtual lane reference line information, y c is perceived lane reference line information, y o is historical track information of the second vehicle, and y e is predicted track information of the first vehicle.
It should be understood that if the second vehicle does not exist in the target lane, the history track information of the second vehicle cannot be determined, and the second weight coefficient β corresponding to the history track information of the second vehicle is 0, where the virtual lane reference line expression is shown in formula (11):
yt＝α·yc+(1-α)·ye (11)
Based on the foregoing, the expression of the perceived lane reference information y c and the predicted trajectory information y e of the first vehicle are similar, and thus, the virtual lane reference expression for characterizing the virtual lane reference information is finally obtained as shown in formula (12):
yt＝C0t+C1t·x+C2t·x2+C3t·x3 (12)
The meaning of each polynomial coefficient is shown in formula (1), and will not be described herein.
For example, please continue to refer to fig. 2, the virtual lane reference line information is shown as a dashed line 16 in fig. 2.
Further, when determining the virtual lane line information based on the virtual lane reference line information, the following steps (a) to (b) may be included:
(a) And acquiring lane width information of the target lane.
Alternatively, the lane width information of the target lane may be obtained by sensing the target lane in real time through the sensing component, and in other embodiments, if any lane line is currently absent in the target lane, the lane width information may also be obtained by sensing a path traveled in the target lane, which is not limited herein.
(B) And respectively adjusting the virtual lane reference line information based on the lane width information of the target lane to obtain the left virtual lane line information and the right virtual lane line information.
It is understood that the virtual lane line information includes left virtual lane line information and right virtual lane line information.
Based on the foregoing, since the virtual lane reference line information refers to lane center line information, after the virtual lane reference line information is obtained, the virtual lane reference line information can be adjusted according to the lane width information of the target lane, so as to obtain left virtual lane line information and right virtual lane line information.
Here, the left virtual lane line expression for characterizing the left virtual lane line information is as shown in formula (13):
ytl＝(C0t+w/2)+C1t·x+C2t·x2+C3t·x3 (13)
The right virtual lane line expression for characterizing the right virtual lane line information is shown in formula (14):
ytr＝(C0t-w/2)+C1t·x+C2t·x2+C3t·x3 (14)
In this way, after the left virtual lane line information and the right virtual lane line information are obtained, the first vehicle can be laterally controlled based on the left virtual lane line information and the right virtual lane line information.
In addition, the embodiment of the disclosure provides a vehicle control method, and an execution subject of the method is a vehicle in general. In other embodiments, the execution body may be an in-vehicle device, and the in-vehicle device may be provided in the vehicle. The in-vehicle device may be a vehicle machine, a terminal device for display of vehicle functions, interaction, or the like.
Specifically, referring to fig. 3, the vehicle control method includes the following steps S301 to S302:
S301, virtual lane line information of a target lane where the first vehicle is currently located is obtained, wherein the virtual lane line information is obtained based on the virtual lane line generating method in the previous embodiment.
S302, transversely controlling the first vehicle based on the virtual lane line information.
In this embodiment, by acquiring the virtual lane line information of the target lane where the first vehicle is currently located, even if the accuracy of the environmental data sensed by the sensing component is low, for example, if the lane line is blocked or lacks, the first vehicle can be laterally controlled according to the virtual lane line information, so that the stability of the lateral function can be improved.
It will be appreciated by those skilled in the art that in the above-described method of the specific embodiments, the written order of steps is not meant to imply a strict order of execution but rather should be construed according to the function and possibly inherent logic of the steps.
Based on the same inventive concept, the embodiment of the disclosure further provides a virtual lane line generating device corresponding to the virtual lane line generating method, and since the principle of solving the problem by the device in the embodiment of the disclosure is similar to that of the virtual lane line generating method in the embodiment of the disclosure, the implementation of the device can refer to the implementation of the method, and the repetition is omitted.
Referring to fig. 4, a schematic structural diagram of a virtual lane line generating apparatus according to an embodiment of the present disclosure is shown, where the virtual lane line generating apparatus 400 includes:
The sensing reference line determining module 410 is configured to obtain lane line data on two sides of a target lane where the first vehicle is currently located, and determine sensing lane reference line information of the target lane based on the lane line data;
A predicted track information determining module 420, configured to obtain vehicle state information of the first vehicle, and determine predicted track information of the first vehicle based on the vehicle state information;
a history track information obtaining module 430, configured to obtain history track information of a second vehicle, where the second vehicle is a nearest vehicle that is in the same lane as the first vehicle and is located in front of the first vehicle in a traveling direction;
The virtual lane line determining module 440 is configured to determine virtual lane line information of a target lane where the first vehicle is currently located, based on the perceived lane reference line information, the predicted track information of the first vehicle, and the historical track information of the second vehicle, where the virtual lane line information is used for performing lateral control on the first vehicle.
In one possible implementation, the virtual lane line determination module 440 is specifically configured to:
Based on a preset weight coefficient, weighting and fusing the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle to obtain virtual lane reference line information of the target lane;
And determining the virtual lane line information based on the virtual lane reference line information.
In one possible embodiment, the weight coefficients include a first weight coefficient corresponding to the perceived lane reference line information, a second weight coefficient corresponding to predicted trajectory information of the first vehicle, and a third weight coefficient corresponding to historical trajectory information of the second vehicle; the first weight coefficient is proportional to the accuracy of the environmental data perceived by the perception component of the first vehicle, and the second weight coefficient is determined by the first weight coefficient and the third weight coefficient.
In one possible embodiment, the third weight coefficient is determined to be 0 if the second vehicle is not present in front of the first vehicle traveling direction in the target lane in which the first vehicle is located.
In one possible embodiment, the vehicle state information includes steering angle information of a steering wheel of the first vehicle and speed information of the first vehicle; the predicted trajectory information determining module 420 is specifically configured to:
The predicted track information of the first vehicle is determined based on the steering angle information of the steering wheel of the first vehicle, the speed information of the first vehicle, and the current position of the first vehicle.
Referring to fig. 5, another virtual lane line generating apparatus according to an embodiment of the present disclosure further includes a historical track information generating module 450; the historical track information generating module 450 is specifically configured to:
Acquiring a plurality of position information of the second vehicle relative to the first vehicle in a history period;
And performing curve fitting on the plurality of position information to obtain the historical track information of the second vehicle.
In one possible embodiment, the virtual lane line information includes left virtual lane line information and right virtual lane line information; the virtual lane line determining module 440 is specifically configured to:
Acquiring lane width information of the target lane;
And respectively adjusting the virtual lane reference line information based on the lane width information of the target lane to obtain the left virtual lane line information and the right virtual lane line information.
Referring to fig. 6, a schematic structural diagram of a vehicle control device according to an embodiment of the disclosure is provided, and as shown in fig. 6, the vehicle control device 600 includes:
an obtaining module 610, configured to obtain virtual lane line information of a target lane where the first vehicle is currently located, where the virtual lane line information is obtained based on the virtual lane line generating method in any one of the foregoing embodiments;
The control module 620 is configured to laterally control the first vehicle based on the virtual lane line information.
The process flow of each module in the apparatus and the interaction flow between the modules may be described with reference to the related descriptions in the above method embodiments, which are not described in detail herein.
Based on the same technical concept, the embodiment of the disclosure also provides electronic equipment. Referring to fig. 7, a schematic structural diagram of an electronic device 700 according to an embodiment of the disclosure includes a processor 701, a memory 702, and a bus 703. The memory 702 is configured to store execution instructions, including a memory 7021 and an external memory 7022; the memory 7021 is also referred to as an internal memory, and is used for temporarily storing operation data in the processor 701 and data exchanged with an external memory 7022 such as a hard disk, and the processor 701 exchanges data with the external memory 7022 via the memory 7021.
In the embodiment of the present application, the memory 702 is specifically configured to store application program codes for executing the scheme of the present application, and the execution is controlled by the processor 701. That is, when the electronic device 700 is in operation, communication between the processor 701 and the memory 702 via the bus 703 causes the processor 701 to execute the application code stored in the memory 702, thereby performing the methods described in any of the previous embodiments.
The Memory 702 may be, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), programmable Read Only Memory (Programmable Read-Only Memory, PROM), erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.
The processor 701 may be an integrated circuit chip having signal processing capabilities. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but may also be a digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field programmable gate array (Field Programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It should be understood that the illustrated structure of the embodiment of the present application does not constitute a specific limitation on the electronic device 700. In other embodiments of the application, electronic device 700 may include more or fewer components than shown, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.
The present disclosure also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of generating a virtual lane line in the method embodiment described above or performs the method of controlling a vehicle in the method embodiment described above. Wherein the storage medium may be a volatile or nonvolatile computer readable storage medium.
The embodiments of the present disclosure further provide a computer program product, where the computer program product carries a program code, where instructions included in the program code may be used to execute the method for generating a virtual lane line in the method embodiment or execute the vehicle control method in the method embodiment, and specifically, reference may be made to the method embodiment, and details thereof are not repeated herein.
Wherein the above-mentioned computer program product may be realized in particular by means of hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied as a computer storage medium, and in another alternative embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK), or the like.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again. In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown 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 units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in essence or a part contributing to the prior art or a part of the technical solution, or in the form of a software product stored in a storage medium, including several instructions for causing a vehicle-mounted device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present disclosure. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.
Finally, it should be noted that: the foregoing examples are merely specific embodiments of the present disclosure, and are not intended to limit the scope of the disclosure, but the present disclosure is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, it is not limited to the disclosure: any person skilled in the art, within the technical scope of the disclosure of the present disclosure, may modify or easily conceive changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features thereof; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the disclosure, and are intended to be included within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (11)
1. The method for generating the virtual lane line is characterized by comprising the following steps of:
Lane line data of two sides of a target lane where a first vehicle is currently located are obtained, and perceived lane reference line information of the target lane is determined based on the lane line data;
Acquiring vehicle state information of the first vehicle, and determining predicted track information of the first vehicle based on the vehicle state information;
acquiring historical track information of a second vehicle, wherein the second vehicle is the nearest vehicle which is positioned on the same lane as the first vehicle and is positioned in front of the first vehicle in the running direction;
And determining virtual lane line information of a target lane where the first vehicle is currently located based on the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle, wherein the virtual lane line information is used for transversely controlling the first vehicle.
2. The method of claim 1, wherein the determining virtual lane-line information for a target lane in which the first vehicle is currently located based on the perceived lane-reference information, the predicted trajectory information for the first vehicle, and the historical trajectory information for the second vehicle comprises:
Based on a preset weight coefficient, weighting and fusing the perceived lane reference line information, the predicted track information of the first vehicle and the historical track information of the second vehicle to obtain virtual lane reference line information of the target lane;
And determining the virtual lane line information based on the virtual lane reference line information.
3. The method of claim 2, wherein the weight coefficients include a first weight coefficient corresponding to the perceived lane reference information, a second weight coefficient corresponding to predicted trajectory information of the first vehicle, and a third weight coefficient corresponding to historical trajectory information of the second vehicle; the first weight coefficient is proportional to the accuracy of the environmental data perceived by the perception component of the first vehicle, and the second weight coefficient is determined by the first weight coefficient and the third weight coefficient.
4. A method according to claim 3, wherein the third weight coefficient is determined to be 0 if the second vehicle is not present in front of the first vehicle traveling direction in the target lane in which the first vehicle is located.
5. The method of any one of claims 1-4, wherein the vehicle state information includes steering angle information of a steering wheel of the first vehicle and speed information of the first vehicle; the determining predicted trajectory information of the first vehicle based on the vehicle state information includes:
The predicted track information of the first vehicle is determined based on the steering angle information of the steering wheel of the first vehicle, the speed information of the first vehicle, and the current position of the first vehicle.
6. The method according to claim 1, wherein the historical track information of the second vehicle is obtained by:
Acquiring a plurality of position information of the second vehicle relative to the first vehicle in a history period;
And performing curve fitting on the plurality of position information to obtain the historical track information of the second vehicle.
7. The method of claim 2, wherein the virtual lane line information comprises left virtual lane line information and right virtual lane line information; the determining the virtual lane line information based on the virtual lane reference line information includes:
Acquiring lane width information of the target lane;
And respectively adjusting the virtual lane reference line information based on the lane width information of the target lane to obtain the left virtual lane line information and the right virtual lane line information.
8. A vehicle control method characterized by comprising:
Obtaining virtual lane line information of a target lane where a first vehicle is currently located, wherein the virtual lane line information is obtained based on the virtual lane line generation method according to any one of claims 1-7;
and transversely controlling the first vehicle based on the virtual lane line information.
9. An electronic device comprising a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor in communication with the memory via the bus when the electronic device is in operation, the machine-readable instructions when executed by the processor performing the method of generating a virtual lane as claimed in any one of claims 1 to 7 or the method of controlling a vehicle as claimed in claim 8.
10. A vehicle comprising a controller, the controller comprising:
a memory configured to store instructions; and
A processor configured to invoke the instructions from the memory and when executing the instructions is capable of implementing the virtual lane line generation method of any one of claims 1-7 or the vehicle control method of claim 8.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, performs the virtual lane line generation method according to any one of claims 1 to 7 or the vehicle control method according to claim 8.
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