CN113759903A - Unmanned vehicle, steering control method thereof, electronic device, and storage medium - Google Patents
Unmanned vehicle, steering control method thereof, electronic device, and storage medium Download PDFInfo
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Abstract
The application discloses unmanned vehicle and a steering control method thereof, electronic equipment and storage medium, and relates to the technical field of unmanned driving, wherein the steering control method of the unmanned vehicle comprises the following steps: acquiring a high-precision map; calculating a curve area and a curve radius according to the high-precision map; acquiring the real-time position and the real-time speed of the unmanned vehicle; and if the real-time position is located in the curve area, calculating a preset steering angle and a corrected steering angle of the vehicle according to the radius of the curve, the real-time speed, radar ranging and GPS position information between the vehicle and the adjacent guardrail on the road, and obtaining the final actual steering angle of the vehicle to reach the target of following the guardrail. And then finding the optimal steering control parameters under the condition of similar driving paths through a deep learning algorithm. The steering control method for the unmanned vehicle has the advantages of concise algorithm and high operation efficiency, and can greatly improve the steering control stability and safety of the vehicle in high-speed driving.
Description
Technical Field
The present disclosure relates to the field of unmanned vehicles, and more particularly, to an unmanned vehicle, a steering control method thereof, an electronic device, and a storage medium.
Background
The unmanned automobile is one of intelligent automobiles, is also called a wheeled mobile robot, and mainly achieves the purpose of unmanned driving by means of an intelligent driver which is mainly a computer system in the automobile. At present, the control of unmanned vehicles on common roads is mature, but the unmanned vehicles are not applied to expressways much, and the unmanned vehicles with low-speed algorithms need a large amount of SLAM point cloud analysis processing, are complex to operate and low in efficiency, and cannot meet the requirement of high-speed driving due to the fact that the driving speed of the vehicles on the expressways is high and the control response requirement is high, particularly when steering is needed.
Disclosure of Invention
The present application is directed to solving at least one of the problems in the prior art. Therefore, the unmanned vehicle and the steering control method thereof, the electronic device and the storage medium are provided, the initial steering angle of the vehicle is calculated through a mathematical model, the steering angle is subjected to closed-loop correction through real-time detection data of a sensor, and steering angle competition is continuously optimized through iteration by using a deep learning algorithm, so that the steering control stability and the steering control safety of the unmanned vehicle during high-speed driving are improved, and meanwhile, the operation efficiency of vehicle steer-by-wire is further improved.
In a first aspect, the present application provides a steering control method of an unmanned vehicle, comprising:
acquiring a high-precision map;
calculating a curve area and a curve radius according to the high-precision map;
acquiring the real-time position and the real-time speed of the unmanned vehicle;
if the real-time position is located in the curve area, obtaining a preset steering angle according to the curve radius and the real-time speed;
acquiring guardrail distance information between the unmanned vehicle and adjacent guardrails on the road;
obtaining a corrected steering angle according to the guardrail distance information;
calculating to obtain an actual steering angle according to the preset steering angle and the corrected steering angle; the preset steering angle, the corrected steering angle and the actual steering angle are all rotation angles of a steering wheel.
According to the steering control method of the unmanned vehicle in the embodiment of the first aspect of the application, at least the following beneficial effects are achieved: obtaining a high-precision map about a planned driving road of an automobile, calculating all curves in the planned driving road through image analysis processing of the high-precision map, calculating the radius of each curve, numbering the curves with the radius exceeding a threshold value in sequence, and obtaining the radius R of the curve of the x-th curvexAnd the area GPS position [ lat ] of the curvex1，lonx1]，[latx2，lonx2]. The method comprises the steps of acquiring the real-time position and the real-time speed of an unmanned vehicle in real time, when the real-time position of the unmanned vehicle is located in a curve GPS position area, namely the unmanned vehicle is located in a curve area, calculating the preset steering angle of the unmanned vehicle according to the curve radius of the curve area and the real-time speed of the unmanned vehicle, acquiring guardrail distance information of the unmanned vehicle and adjacent guardrails on a road, obtaining a corrected steering angle according to the guardrail distance information, and obtaining an actual steering angle according to the preset steering angle and the corrected steering angle. In the scheme of the invention, the preset steering angle is calculated through the mathematical model, the distance information between the vehicle and the guardrail is detected through the single-point laser radar, and the steering angle is corrected on the basis of the preset steering angle, so that the calculation efficiency of the steering angle is improved, the real-time performance of system control is ensured, the steering safety of the unmanned vehicle is improved, and the unmanned vehicle can steer on the expressway to control and controlAnd is more stable.
According to some embodiments of the first aspect of the present application, if the real-time position is located in the curve region, obtaining a preset steering angle according to the curve radius and the real-time speed includes: if the real-time position is located in the curve area and the radius of the curve is smaller than or equal to a first radius threshold, obtaining a preset steering angle according to the radius of the curve and the real-time speed; if the real-time position is located in the curve area and the curve radius is greater than a first radius threshold, the preset steering angle is set to be 0 °.
According to some embodiments of the first aspect of the present application, the first radius threshold is 1500 meters.
According to some embodiments of the first aspect of the present application, the unmanned vehicle includes a first single point lidar and a second single point lidar, the first single point lidar is disposed at a position beside a vehicle head of the unmanned vehicle, the second single point lidar is disposed at a position beside a vehicle tail of the unmanned vehicle, acquiring guardrail distance information between the unmanned vehicle and adjacent guardrails on a road includes: acquiring vehicle body distance information according to the high-precision map and the real-time position; if the vehicle body distance information is smaller than a first distance threshold value, starting the first single-point laser radar and the second single-point laser radar to measure the distance; acquiring vehicle head distance information measured by the first single-point laser radar; the distance information of the vehicle head is the distance between the side of the vehicle head of the unmanned vehicle and an adjacent guardrail on the road; acquiring the vehicle tail distance information measured by the second single-point laser radar; the vehicle tail distance information is the distance between the side of the tail of the unmanned vehicle and the adjacent guardrail on the road.
According to some embodiments of the first aspect of the present application, the deriving a corrected steering angle from the guardrail distance information comprises: and obtaining a corrected steering angle according to the information of the distance between the vehicle head and the information of the distance between the vehicle tail.
According to some embodiments of the first aspect of the present application, the corrected steering angle is calculated with a frequency greater than 20 Hz.
According to some embodiments of the first aspect of the present application, the unmanned vehicle is controlled to deflect left proximate to a left side barrier of a roadway if the real-time speed continues to exceed a first speed threshold for a first time.
In a second aspect, the present application further provides an electronic device, including: at least one memory; at least one processor; at least one program; the program is stored in the memory, and the processor executes at least one of the programs to implement the steering control method of the unmanned vehicle according to any one of the embodiments of the first aspect.
In a third aspect, the present application further provides an unmanned vehicle comprising the electronic device according to the embodiment of the second aspect.
In a fourth aspect, the present application further provides a computer-readable storage medium storing computer-executable signals for performing the steering control method of the unmanned vehicle according to any one of the embodiments of the first aspect.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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Additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a steering control method for an unmanned vehicle provided in an embodiment of the present application;
FIG. 2 is a flow chart of a steering control method for an unmanned vehicle according to another embodiment of the present application;
FIG. 3 is a flow chart of a steering control method for an unmanned vehicle according to one embodiment of the present application;
FIG. 4 is a schematic view of an electronic device provided by an embodiment of the present application;
fig. 5 is a schematic diagram of a first single-point lidar and a second single-point lidar according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
In the description of the present application, it is to be understood that the positional descriptions, such as the directions of up, down, front, rear, left, right, etc., referred to herein are based on the directions or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, and do not indicate or imply that the referred device or element must have a specific direction, be constructed and operated in a specific direction, and thus, should not be construed as limiting the present application.
In the description of the present application, if there are first and second described only for the purpose of distinguishing technical features, it is not understood that relative importance is indicated or implied or that the number of indicated technical features or the precedence of the indicated technical features is implicitly indicated or implied.
In the description of the present application, unless otherwise expressly limited, terms such as set, mounted, connected and the like should be construed broadly, and those skilled in the art can reasonably determine the specific meaning of the terms in the present application by combining the detailed contents of the technical solutions.
Referring to fig. 1, fig. 1 is a flowchart of a steering control method of an unmanned vehicle according to an embodiment of the present application. The embodiment of the application provides a steering control method of an unmanned vehicle, which comprises but is not limited to steps S110, S120, S130, S140, S150, S160 and S170:
step S110: and acquiring a high-precision map.
It can be understood that the unmanned vehicle is provided with the internet communication module, and the high-precision map can be downloaded through the internet communication module, specifically, the 5G communication module is used for obtaining the high-precision map, and the map obtaining speed is improved through the 5G network; or the high-precision map may be disposed in a separate Electronic Control Unit (ECU), or may be disposed in an ECU of the vehicle, which is not limited in this application, and the high-precision map at least includes route road information preset by the unmanned vehicle, where the route road information includes, but is not limited to, longitude and latitude information of various places on the road.
Step S120: and calculating the curve area and the curve radius according to the high-precision map.
It can be understood that, through carrying out image analysis processing on the obtained high-precision map, the curve area on the high-precision map and the curve radius corresponding to each curve area are calculated, besides, in order to reduce the burden on the unmanned processing system, the curve area and the corresponding curve radius of the preset path of the unmanned vehicle can be calculated in advance, the high-precision map which is generated in advance and is used for marking the curve area and the curve radius on each road sign can be directly obtained, the high-precision map is updated before driving each time to obtain the latest information of the road curve area and the curve radius, and each curve exceeding a threshold value is numbered and marked, when the unmanned vehicle reaches a certain curve area, the number of the curve is automatically identified, so that the curve radius can be directly obtained. Specifically, the curve area is a set of coordinates marked by longitude and latitude, which is not limited in the present application.
Step S130: acquiring the real-time position and the real-time speed of the unmanned vehicle;
it can be understood that the unmanned vehicle is provided with a GPS differential positioning module and a speed detection module, and the GPS differential positioning module is used to detect a real-time position of the unmanned vehicle, specifically, the real-time position includes real-time longitude information and real-time latitude information of the vehicle, and the speed detection module in the unmanned vehicle is used to obtain a real-time speed of the unmanned vehicle.
Step S140: and if the real-time position is located in the curve area, calculating to obtain a preset steering angle according to the radius of the curve and the real-time speed.
It will be appreciated that the real-time location of the unmanned vehicle, including the real-time longitude information and the real-time latitude information, is detected by the GPS differential positioning module of the unmanned vehicle, and that when the values of the real-time longitude information and the real-time latitude information are located in the set of longitude and latitude coordinates of the curve area, it is indicated that the unmanned vehicle is located at a curve of the road.
It can be understood that, if the longitude and latitude of the unmanned vehicle are in the longitude and latitude set of the curve area, the preset steering angle is obtained by calculating the curve radius and the real-time speed of the unmanned vehicle, and the specific calculation method of the preset steering angle obtained by the mathematical model is as follows:
where α (t) represents a real-time preset steering angle, i is a steering gear transmission ratio, i.e., a ratio of an angle of rotation of a steering wheel to an angle of rotation of wheels, is set to 12, v (t) is a real-time speed of the unmanned vehicle, and R is a real-time speed of the unmanned vehiclexIt should be noted that, in the present embodiment, the update frequency of the unmanned vehicle on the radius of the curve is 3Hz, that is, t is 0.333s, and the present application is not limited thereto, and a person skilled in the art sets the update time according to the GPS data actually applied.
In particular, for example, when the unmanned vehicle is located at a curve radius RxIn the 700m curve area, the running speed of the unmanned vehicle was detected to be 100km/h, and the preset steering angle was calculated to be 9.093 °.
Step S150: and acquiring guardrail distance information between the unmanned vehicle and adjacent guardrails on the road.
It can be understood that the guard rail distance information between the unmanned vehicle and the adjacent guard rail of the road can be obtained through a GPS differential positioning module or a ranging sensor, etc., so as to ensure the safety of vehicle driving and avoid colliding with the guard rail of the road.
Step S160: and obtaining a corrected steering angle according to the guardrail distance information.
It can be understood that the guard rail distance information is acquired through the step S150, and the corrected steering angle of the unmanned vehicle is calculated or whether the angle correction is needed is determined according to the guard rail distance information, so as to improve the accuracy of steering of the unmanned vehicle.
Step S170: obtaining an actual steering angle according to a preset steering angle and the corrected steering angle; the preset steering angle, the corrected steering angle and the actual steering angle are all rotation angles of the steering wheel.
It can be understood that the actual steering angle is the preset steering angle plus the corrected steering angle, i.e. the actual steering angle is:
γ(t)＝α(t)+β(t)
the vehicle-mounted unmanned vehicle comprises a vehicle body, a road surface, a road radius, a road surface, a.
Referring to fig. 2, fig. 2 is a flowchart of a steering control method of an unmanned vehicle according to another embodiment of the present application, where step S140 includes, but is not limited to, step S210 and step S220:
step S210: and if the real-time position coincides with the curve area and the radius of the curve is less than or equal to the first radius threshold, obtaining a preset steering angle according to the radius of the curve and the real-time speed.
Step S220: if the real-time position coincides with a curve region and the curve radius is greater than a first radius threshold (if the real-time position is not in a curve region numbered in the planned driving road), the preset steering angle is set to 0 °.
It can be understood that when the longitude and latitude coordinate values corresponding to the real-time position of the unmanned vehicle are located in the longitude and latitude coordinate set of the curve area, the size relationship between the curve radius and the first radius threshold is determined. When the radius of the curve is larger than the first radius threshold, the turning angle degree of the curve is smaller, the curve can be roughly considered as a straight road, the preset turning angle is smaller and can be ignored, namely when the radius of the curve is larger than the first radius threshold, the preset turning angle is set to be 0 degrees, and the actual turning angle is controlled to turn only according to the corrected turning angle obtained by the guardrail distance information; and when the radius of the curve is smaller than the first radius threshold, obtaining a preset steering angle according to the radius of the curve and the real-time speed of the unmanned vehicle, and obtaining an actual steering angle according to the corrected steering angle.
It can be understood that the first radius threshold is 1500 meters, that is, when the radius of the curve is greater than 1500 meters, the degree of the turning angle of the curve is small, and the calculated preset steering angle is also relatively small, in this case, the steering closed-loop feedback control can be realized by directly calculating the correction angle without compensating the preset steering angle. When the radius of the curve is larger than 1500m, the preset steering angle is not calculated and is set as a fixed value of 0 degrees, and the actual steering angle is controlled only by the corrected steering angle obtained according to the guardrail distance information, so that the operation can be simplified, and the algorithm efficiency can be improved. When the radius of the curve is smaller than 1500 meters, a preset steering angle is obtained according to the algorithm of the radius of the curve and the real-time speed of the unmanned vehicle, a corrected steering angle is obtained according to the algorithm of the guardrail distance information, and then the actual steering angle is obtained through further calculation.
It can be understood that unmanned vehicle includes GPS differential positioning module, first single-point laser radar and second single-point laser radar, and first single-point laser radar sets up in the other department of locomotive side of unmanned vehicle, and second single-point laser radar sets up in the other department of rear of a vehicle side of unmanned vehicle, and specifically, first single-point laser radar sets up in the position department that is close to the locomotive in unmanned vehicle left side, and second single-point laser radar sets up in the position department that is close to the rear of a vehicle in unmanned vehicle left side.
Referring to fig. 3, fig. 3 is a flowchart of a steering control method of an unmanned vehicle according to an embodiment of the present application, where step S150 includes, but is not limited to, step S310 to step S340:
step S310: and obtaining the distance information of the vehicle body according to the high-precision map and the real-time position.
It can be understood that the high-precision map further comprises the specific position of the guardrail on the road, the real-time position of the unmanned vehicle can be accurately detected through the GPS differential positioning module, and the distance information from the side face of the automobile to the guardrail is obtained by using the following algorithm according to the specific position of the guardrail on the road and the real-time position of the unmanned vehicle.
The difference GPS positioning module obtains longitude information and latitude information of the unmanned vehicle, and calculates a first distance information value d by using a Haversine formula with guardrail longitude and latitude data in a high-precision map0(as shown in fig. 5). Suppose the GPS position of the car (lat1, lon1), the GPS position of the guardrail (lat2, lon2), the distance function between them is:
wherein the content of the first and second substances,
wherein R is0The earth radius can be 6371km on average; d0The distance information of the vehicle body (the distance information from the side surface of the vehicle to the guardrail is calculated by using the position of the differential GPS positioning module and the vehicle width information); phi 1 ═ lon1, phi 2 ═ lon2 indicate the latitude of two points of the automobile and the guardrail; Δ λ | lat2-lat1| represents an absolute value of a difference in longitude between two points of the car and the guardrail.
Step S320: and if the vehicle body distance information is smaller than the first distance threshold value, starting the first single-point laser radar and the second single-point laser radar to measure the distance.
It can be understood that when the vehicle body distance information is less than the first distance threshold value, the first distance threshold value represents the minimum safe distance value between the unmanned vehicle and the adjacent guardrail, and when the vehicle body distance information of the unmanned vehicle is less than the first distance threshold value, the unmanned vehicle may have the risk of colliding with the adjacent guardrail, and then the first single-point laser radar and the second single-point laser radar which are more accurate in short-distance measurement are started to measure the distance so as to ensure the safe driving of the unmanned vehicle. Specifically, the first distance threshold is 2 meters, that is, when the vehicle body distance information of the unmanned vehicle is less than 2 meters, the first single-point laser radar and the second single-point laser radar which are more accurate in short-distance ranging are started to perform ranging, and this is not limited in this application.
Step S330: obtaining vehicle head distance information measured by a first single-point laser radar; the vehicle head distance information is the distance between the side of the vehicle head of the unmanned vehicle and the adjacent guardrail on the road.
Step S340: obtaining vehicle tail distance information measured by a second single-point laser radar; the tail distance information is the distance between the side of the tail of the unmanned vehicle and the adjacent guardrail on the road.
It can be understood that, carry out distance measurement to locomotive distance information and rear of a vehicle distance information between adjacent guardrail of next and road of locomotive and rear of a vehicle side and the road of unmanned vehicle respectively through first single-point laser radar and second single-point laser radar, except that more comprehensive good distance between unmanned vehicle and the adjacent guardrail of accuse, improve the security that unmanned vehicle traveles, thereby more importantly judge that the vehicle traveles the contained angle of extension line and road guardrail extension line and use the steering control algorithm to revise feedback adjustment steering angle parameter in real time.
It is understood that, in an embodiment of the present application, step S160 includes, but is not limited to, the following steps:
and obtaining a corrected steering angle according to the information of the distance between the vehicle head and the vehicle tail.
It can be understood that the vehicle head distance information and the vehicle tail distance information between adjacent guardrails on the sides of the vehicle head and the vehicle tail of the unmanned vehicle and the road are respectively calculated by the first single-point laser radar and the second single-point laser radar, the correction angle steering angle is calculated according to the vehicle head distance information and the vehicle tail distance information, and the calculation method of the correction steering angle is as follows:
wherein β (t) is the corrected steering angle, i is the steering gear ratio, i.e. the ratio of the angle of rotation of the steering wheel to the angle of rotation of the wheels, set to 12; t is the running time, i.e. the sampling time of the single-point lidar, wherein the sampling frequency of the single-point lidar is 100Hz, i.e. t is 0.01 s; v (t) is the real-time speed of the unmanned vehicle, d2(t) real-time distance information of the nose of the unmanned vehicle, d1(t) real-time distance information of the tail of the unmanned vehicle, wherein d1And d2As shown with reference to fig. 5. Where eta is d [ d ═ d2(t)-d1(t)]dt is the lateral excursion ratio, e.g. η ═ d [ d ]2(t)-d1(t)]dt is 0.25m/s, the real-time speed of the unmanned vehicle is 100km/h, and the corrected steering angle β obtained by the calculation method of the corrected steering angle is 6.19 °.
It can be understood that the calculation frequency of the corrected steering angle is required to be greater than 20Hz (that is, the sampling frequency of the single-point laser radar is selected to be greater than 20Hz) to ensure that the unmanned vehicle can adjust the corrected steering angle in time, so that the unmanned vehicle can run safely and stably, and the calculation frequency and the calculation precision of the corrected steering angle are not limited in the application.
It will be appreciated that when the unmanned vehicle is on the xth curve, the curve radius RxIn a 700m curve area, the driving speed of the unmanned vehicle is detected to be 100km/h, and the lateral offset rate eta is d [ d ]2(t)-d1(t)]dt is 0.25m/s, the preset steering angle alpha can be obtained by the calculation method of the preset steering anglex(t) is 9.093 DEG, and the corrected steering angle beta can be obtained by the calculation method of the corrected steering anglex(t) is 6.19 DEG, so that the actual steering angle gamma can be obtainedx(t) is 15.28 degrees, the transverse deviation rate eta is used as a limit value for calculating the corrected steering angle, if eta is more than or equal to 0.5m/s, the vehicle can obviously deviate from the road, and the correction angle beta is not calculated under the conditionx(t) at the same time will activateOther sensors perform new steering strategy calculations, which are not set forth or limited in this application.
Referring to fig. 5, it can be understood that the first single-point laser radar and the second laser single-point installation positioning angle ρ are set to be adjustable, the smaller the turning radius of the curve is, the smaller ρ is, the closer ρ is to 0 °, at this time, the vehicle acceleration is limited, the early warning system is started, and a driving scheme with a plurality of sensors fused together is started. If the turning radius of the curve is larger and exceeds 1500m, the maximum adjusting angle of rho is larger and approaches to 45 degrees, the predictability is enhanced, and the set rho angle is larger than or equal to 3 degrees and smaller than or equal to rho and smaller than or equal to 45 degrees, which is not limited in the application.
Specifically, the method for calculating the installation location angle ρ x of the laser radar set according to the radius of the curve is,
wherein R isxThe radius of the X-th curve of the road, b is the installation distance of the front left laser radar and the rear left laser radar, rho is the installation positioning angle of the laser radar, m is an experimental parameter, and m takes 1.1.
Specifically, the vehicle lateral deviation distance arithmetic mean
Wherein d is1(t) the actual distance from the left side of the vehicle to the guardrail is measured by the left rear single-point laser radar, and d2(t) the actual distance from the left side of the vehicle to the guardrail is measured by the left front single-point laser radar, wherein the actual distance is measured by using epsilon and 0.5d0The magnitude of the error of (1) corrects the value of p.
It can be understood that, in an embodiment of the present application, the present application provides a steering control method for an unmanned vehicle, further including, but not limited to, the following steps:
and if the real-time speed continuously exceeds the first speed threshold value within the first time, controlling the unmanned vehicle to leftwards deviate to approach the left guardrail of the road.
It can be understood that the steering control method of the unmanned vehicle provided by the application is suitable for running on a highway, when the unmanned vehicle continuously exceeds a first speed threshold value within a first time, the unmanned vehicle is represented to have run on the highway, in order to better control the steering of the unmanned vehicle at a curve, the unmanned vehicle is controlled by the system to shift to the left to be close to a left guardrail of the road for running, and the unmanned vehicle is kept from colliding with the left guardrail according to the head distance information and the tail distance information, namely the unmanned vehicle automatically drives to the leftmost lane of the road for running, so that the unmanned vehicle can run along the side, and the accuracy of automatic steering is improved.
It can be understood that the steering control method of the unmanned vehicle provided by the application can also be used for iteratively optimizing the driving path through the following deep learning algorithm, and can be used for optimizing the steering parameters and making a quick control reaction under the similar condition.
Specifically, the deep learning algorithm 1 calculates n (3 ≦ n ≦ 10) actual steering angle functions γ of the unmanned vehicle on the same path as the unmanned vehicle travels on which x curves exceeding the threshold value are present, and continuously processesxAnd (t) performing iteration with the minimum integral sum to obtain a steering scheme with a better path so as to directly apply the steering scheme next time, reduce the time for calculating the steering angle and improve the steering efficiency. For example, by comparing the integral sum of the actual steering angle functions of 10 consecutive curves of the path traveled for the first time with the integral sum of the actual steering angle functions of 10 consecutive curves traveled for the second time, if the integral sum of the actual steering angle functions of the first time is smaller than the integral sum of the actual steering angle functions of the second time, the first-time steering scheme is adopted when the path is traveled for the next time. Specifically, the calculation method of the steering stability coefficient is as follows:
where δ is the steering stability factor, γx(t) is the actual steering angle calculation function of the unmanned vehicle, and t is the travel time, i.e. the sampling time of a single-point lidar, e.g. of a single-point lidarThe sampling frequency is 100Hz, and t is 0.01 s. And calculating the integral sum of the actual steering angles of the continuous n curves to be optimal, and smoothly steering, namely, taking the integral sum as a correction value of the actual steering angle of the next time with the same parameter. I.e. delta<δt-1，γx(t)t+1＝γx(t)。
In particular, deep learning Algorithm 2, statistics γx(t) the number of times of the positive and negative coincidence change of the steering of the adjacent two sections of curve parts (namely the number of times of counting the steering wheel passing through 0 degrees) is less than optimal, the more stable the steering is, the steering can not be continuously steered, and the specific program codes are calculated as follows:
#include<iostream>
using namespace std；
int main()
{
int i＝0,n＝0,count＝0；
cout < "input array γ x (t)" < < end; // obtaining the actual steering angle γ x (t), zero does not belong to a positive or negative number
cin > > n; counting the number of positive and negative changes of the steering angle on 10 continuous curves when the steering angle is 10
int*Array＝new int[n]；
for(i＝0；i<n；i++)
{
cin>>Array[i]；
}
for(i＝0；i<n-1；i++)
{
if(Array[i]*Array[i+1]<0)
{
count++；
}
}
cout<<count<<endl；
return 0；
}
In a second aspect, referring to fig. 4, the present application further provides an electronic device comprising at least one memory; at least one processor; at least one program; the program is stored in the memory, and the processor executes at least one of the programs to implement the steering control method of the unmanned vehicle according to any one of the embodiments of the first aspect. The electronic equipment calculates the preset steering angle in a concise mode, and detects that the steering angle of the vehicle and the guardrail is corrected on the basis of the preset steering angle, so that the steering safety of the unmanned vehicle is improved, and the unmanned vehicle can run on the road more safely. Fig. 4 illustrates an example of a memory and a processor.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and signals, such as program instructions/signals corresponding to the processing modules in the embodiments of the present application. The processor executes various functional applications and data processing by running non-transitory software programs, instructions and signals stored in the memory, namely, the steering control method of the unmanned vehicle of the above-described method embodiment is realized.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data related to the steering control method of the above-described unmanned vehicle, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processing module via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more signals are stored in a memory and, when executed by the one or more processors, perform a method of steering control of an unmanned vehicle in any of the method embodiments described above. For example, the above-described method steps S110 to S170 in fig. 1, method steps S210 to S220 in fig. 2 and method steps S310 to S340 in fig. 3 are performed.
In a third aspect, the present application further provides an unmanned vehicle, including the electronic device according to the second aspect, which can calculate a steering angle of the vehicle through a mathematical model, and appropriately correct the steering angle, thereby improving the operation efficiency and the safety of unmanned steering.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform a steering control method for an unmanned vehicle in the above method embodiments. For example, the above-described method steps S110 to S170 in fig. 1, method steps S210 to S220 in fig. 2 and method steps S310 to S340 in fig. 3 are performed.
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 the 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 units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
From the above description of embodiments, those of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable signals, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable signals, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "specifically," or "some examples" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The embodiments of the present application have been described in detail with reference to the drawings, but the present application is not limited to the embodiments, and various changes can be made without departing from the spirit of the present application within the knowledge of those skilled in the art.
Claims (10)
1. A steering control method of an unmanned vehicle, characterized by comprising:
acquiring a high-precision map;
calculating a curve area and a curve radius according to the high-precision map;
acquiring the real-time position and the real-time speed of the unmanned vehicle;
if the real-time position is located in the curve area, obtaining a preset steering angle according to the curve radius and the real-time speed;
acquiring guardrail distance information between the unmanned vehicle and adjacent guardrails on the road;
obtaining a corrected steering angle according to the guardrail distance information;
obtaining an actual steering angle according to the preset steering angle and the corrected steering angle; the preset steering angle, the corrected steering angle and the actual steering angle are all rotation angles of a steering wheel.
2. The steering control method of the unmanned vehicle of claim 1, wherein if the real-time position is in the curve region, obtaining a preset steering angle according to the curve radius and the real-time speed comprises:
if the real-time position is located in the curve area and the radius of the curve is smaller than or equal to a first radius threshold, obtaining a preset steering angle according to the radius of the curve and the real-time speed;
if the real-time position is located in the curve area and the curve radius is greater than a first radius threshold, the preset steering angle is set to be 0 °.
3. The steering control method of the unmanned vehicle of claim 2, wherein the first radius threshold is 1500 meters.
4. The steering control method of an unmanned vehicle according to claim 1, wherein the unmanned vehicle includes a first single-point lidar and a second single-point lidar, the first single-point lidar is disposed at a vehicle head side of the unmanned vehicle, the second single-point lidar is disposed at a vehicle tail side of the unmanned vehicle, and the acquiring of the guard rail distance information between the unmanned vehicle and an adjacent guard rail on a road includes:
acquiring vehicle body distance information according to the high-precision map and the real-time position;
if the vehicle body distance information is smaller than a first distance threshold value, starting the first single-point laser radar and the second single-point laser radar to measure the distance;
acquiring vehicle head distance information measured by the first single-point laser radar; the distance information of the vehicle head is the distance between the side of the vehicle head of the unmanned vehicle and an adjacent guardrail on the road;
acquiring the vehicle tail distance information measured by the second single-point laser radar; the vehicle tail distance information is the distance between the side of the tail of the unmanned vehicle and the adjacent guardrail on the road.
5. The steering control method of the unmanned vehicle according to claim 4, wherein the deriving a corrected steering angle from the guard rail distance information includes:
and obtaining a corrected steering angle according to the information of the distance between the vehicle head and the information of the distance between the vehicle tail.
6. The steering control method of an unmanned vehicle according to claim 5, wherein the calculation frequency of the corrected steering angle is greater than 20 Hz.
7. The steering control method of the unmanned vehicle according to claim 1, characterized by further comprising:
and if the real-time speed continuously exceeds a first speed threshold value within the first time, controlling the unmanned vehicle to leftwards deviate to approach a left guardrail of the road.
8. An electronic device, comprising:
at least one memory;
at least one processor;
at least one program;
the programs are stored in the memory, and the processor executes at least one of the programs to implement the steering control method of the unmanned vehicle of any one of claims 1 to 7.
9. An unmanned vehicle comprising the electronic device of claim 8.
10. A computer-readable storage medium storing computer-executable signals for performing the steering control method of an unmanned vehicle according to any one of claims 1 to 7.
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| CN202110967071.9A CN113759903A (en) | 2021-08-23 | 2021-08-23 | Unmanned vehicle, steering control method thereof, electronic device, and storage medium |
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| CN202110967071.9A CN113759903A (en) | 2021-08-23 | 2021-08-23 | Unmanned vehicle, steering control method thereof, electronic device, and storage medium |
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| CN115891977A (en) * | 2023-02-22 | 2023-04-04 | 北京易控智驾科技有限公司 | Method and device for controlling understeer of unmanned mining vehicle, electronic equipment and storage medium |
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| CN116412814A (en) * | 2023-06-12 | 2023-07-11 | 旷智中科(北京)技术有限公司 | Image construction navigation auxiliary system based on laser radar |
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Application publication date: 20211207 |