A control method, device, equipment and medium for memory driving

Abstract

The present invention discloses a control method, device, equipment and medium for memory driving, and relates to the field of automatic driving technology. In the process of memory driving mapping, an optimization model is established according to the driving characteristic reference value, driving characteristic parameters and weight values ​​of the driving characteristic parameters corresponding to the driving characteristic parameters of the current vehicle, and when the value of the optimization model corresponding to the road area is the minimum value, the driving characteristic target value corresponding to the road area is obtained. After the memory driving function is turned on, the driving characteristic target value corresponding to the current road area is used to control the vehicle driving, so that the vehicle can simulate the user's driving behavior, and the optimization model is determined by taking into account a variety of driving characteristic parameters and parameter weight values, and the driving characteristic target value corresponding to the road area obtained when the optimization model is at the minimum value is used to control the vehicle driving, so that the way of controlling the vehicle is more in line with the user's behavior when driving the vehicle, and the user's experience when using the vehicle is improved.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to a control method, device, equipment and medium for memory driving. Background Art

[0002] Memory driving means that the driver drives the vehicle from the starting point to the end point, and the system will remember the route the driver drove the vehicle. When the memory is completed, when the driver uses the memory driving function, the system can drive the vehicle from the starting point to the end point.

[0003] During the memory driving process, how to enable the vehicle to simulate the user's driving behavior to improve the user experience is a technical problem that people in this field urgently need to solve. Summary of the invention

[0004] The purpose of the present invention is to provide a control method, device, equipment and medium for memory driving, which are used to solve the technical problem of vehicle simulation of user driving behavior.

[0005] In order to solve the above technical problems, the present invention provides a control method for memory driving, comprising:

[0006] In the process of memorizing the driving map, a driving characteristic reference value corresponding to the driving characteristic parameter of the current vehicle is obtained; wherein the driving characteristic parameter at least includes a parameter for representing the current vehicle's driving speed, a parameter for representing the current vehicle's driving position, or a parameter for representing the position between the current vehicle and other vehicles;

[0007] An optimization model is established according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter; wherein the optimization model is used to characterize the difference between the actual driving characteristic value and the driving characteristic reference value; the weight value is determined by the type of the road area; the type of the road area includes at least one of a straight road area type, a lane change area type, a curve area type and a junction area type;

[0008] When the value of the optimization model corresponding to the road area is a preset value, obtaining the driving characteristic target value corresponding to the road area; wherein the preset value is the minimum value of all the values ​​of the optimization model corresponding to the road area; when all the values ​​of the optimization model correspond to different actual values ​​of the driving characteristics of each driving characteristic parameter, the value of the optimization model;

[0009] When it is detected that the memory driving function is turned on, the current road area where the current vehicle is located is obtained, and the driving of the vehicle is controlled by using the driving characteristic target value corresponding to the current road area.

[0010] Preferably, the parameters used to characterize the current vehicle speed at least include a driving speed ratio, a lane change rate or an intersection passability; wherein, when there is no vehicle in front of the current vehicle, the driving speed ratio is the ratio between the current speed of the current vehicle and the speed limit on the lane; when there is a vehicle in front of the current vehicle, the driving speed ratio is the ratio between the current speed of the current vehicle and the speed of the vehicle in front; the parameters used to characterize the intersection passability at least include a speed ratio when passing a traffic light and the indicator light indication;

[0011] The parameters used to characterize the current driving position of the vehicle at least include the distance between the current vehicle and the center of the lane in which it is located;

[0012] The parameters used to characterize the position between the current vehicle and other vehicles include at least: a following threshold, a threshold for the lateral distance between the current vehicle and the adjacent vehicle, and an overtaking rate; wherein the parameters characterizing the overtaking rate include at least an allowable overtaking speed and a headway time between the current vehicle and other vehicles.

[0013] Preferably, determining the lane change rate includes:

[0014] Obtaining a first distance between the current vehicle and a common lane line before the lane change and a second distance between the current vehicle and the common lane line after the lane change; wherein the common lane line is a common lane line between the lane before the lane change and the lane after the lane change;

[0015] Acquire a third distance between the first target line and the common lane line and a fourth distance between the second target line and the common lane line; wherein the first target line is located in the lane before the lane change, and the second target line is located in the lane after the lane change; the third distance is less than half of the lane width before the lane change, and the fourth distance is less than half of the lane width after the lane change;

[0016] The lane change rate is determined according to a relationship between the first distance and the third distance, and a relationship between the second distance and the fourth distance.

[0017] Preferably, determining the lane change rate according to the relationship between the first distance and the third distance and the relationship between the second distance and the fourth distance includes:

[0018] In the case where it is detected that the first distance is greater than or equal to the third distance, and the second distance is greater than or equal to the fourth distance, the lane change rate is determined to be the ratio of the sum of the distances to the first duration; wherein the sum of the distances is the sum of the third distance and the fourth distance, the first duration is the sum of the duration of the current vehicle in the first target area and the duration of the current vehicle in the second target area, the two sides of the first target area are the first target line and the common lane line, and the two sides of the second target area are the second target line and the common lane line;

[0019] When it is detected that the first distance is less than the third distance and the second distance is greater than the fourth distance, the lane change rate is determined to be a ratio of the second distance to a second duration; wherein the second duration is a duration for which the current vehicle is in the second target area;

[0020] When it is detected that the first distance is greater than or equal to the third distance and the second distance is less than the fourth distance, the lane change rate is determined to be a ratio of the first distance to a third duration; wherein the third duration is a duration that the current vehicle is in the first target area;

[0021] When it is detected that the first distance is smaller than the third distance and the second distance is smaller than the fourth distance, the lane change rate is determined as the ratio of the width of the current vehicle to a fourth time length; wherein the fourth time length is the difference between the moment when the first edge of the current vehicle presses on the common lane line and the moment when the second edge of the current vehicle presses on the common lane line.

[0022] Preferably, determining the threshold of the lateral distance between the current vehicle and the neighboring vehicle includes:

[0023] Obtain the distance between the current vehicle and the neighboring vehicle at each target moment; wherein the target moment is each moment within the duration when the current vehicle and the neighboring vehicle are traveling side by side;

[0024] The minimum distance among all distances is obtained, and the minimum distance is used as a threshold of a lateral distance between the current vehicle and an adjacent vehicle.

[0025] Preferably, the establishing of the optimization model according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter comprises:

[0026] Determining a target driving characteristic parameter and a weight value of the target driving characteristic parameter according to the type of the road area;

[0027] Acquire a difference between each of the target driving characteristic parameters and the driving characteristic reference value corresponding to each of the target driving characteristic parameters;

[0028] The optimization model is established according to the sum of the products of each difference and the weight value of the corresponding driving characteristic parameter.

[0029] Preferably, determining the target driving characteristic parameter according to the type of the road area includes:

[0030] When it is detected that the type of the road area is a straight road area type, determining the target driving characteristic parameters including a driving speed ratio, a distance between the current vehicle and the center of the lane, a following threshold, and a threshold of a lateral distance between the current vehicle and an adjacent vehicle;

[0031] When it is detected that the type of the road area is a lane change area type, determining the target driving characteristic parameters including a driving speed ratio, a distance between the current vehicle and the center of the lane, a lane change rate, a following threshold, a threshold of a lateral distance between the current vehicle and an adjacent vehicle, and an overtaking rate;

[0032] When it is detected that the type of the road area is an intersection area type, the target driving characteristic parameters are determined to include a driving speed ratio, a distance between the current vehicle and the center of the lane, a following threshold, a threshold for the lateral distance between the current vehicle and an adjacent vehicle, and intersection passability.

[0033] In order to solve the above technical problems, the present invention further provides a control device for memory driving, comprising:

[0034] A first acquisition module is used to acquire a driving characteristic reference value corresponding to a driving characteristic parameter of the current vehicle during the process of memorizing the driving map; wherein the driving characteristic parameter at least includes a parameter for representing the current vehicle's driving speed, a parameter for representing the current vehicle's driving position, or a parameter for representing the position between the current vehicle and other vehicles;

[0035] An establishment module is used to establish an optimization model according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter; wherein the optimization model is used to characterize the difference between the actual driving characteristic value and the driving characteristic reference value; the weight value is determined by the type of road area; the type of road area includes at least one of a straight road area type, a lane change area type, a curve area type and a junction area type;

[0036] A second acquisition module is used to acquire a driving characteristic target value corresponding to the road area when the value of the optimization model corresponding to the road area is a preset value; wherein the preset value is the minimum value of all values ​​of the optimization model corresponding to the road area; and when all values ​​of the optimization model correspond to different actual values ​​of the driving characteristics of each driving characteristic parameter, the value of the optimization model;

[0037] The third acquisition module is used to acquire the current road area where the current vehicle is located when detecting that the memory driving function is turned on, and control the vehicle driving by using the driving characteristic target value corresponding to the current road area.

[0038] In order to solve the above technical problems, the present invention further provides a vehicle, comprising:

[0039] Memory for storing computer programs;

[0040] The processor is used to implement the steps of the above-mentioned memory driving control method when executing the computer program.

[0041] In order to solve the above technical problems, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned memory driving control method are implemented.

[0042] The present invention provides a control method for memory driving. In the process of memory driving mapping, an optimization model is established according to the driving characteristic reference value, driving characteristic parameter and weight value of the driving characteristic parameter corresponding to the driving characteristic parameter of the current vehicle. When the value of the optimization model corresponding to the road area is the minimum value, the driving characteristic target value corresponding to the road area is obtained. After the memory driving function is turned on, the driving of the vehicle is controlled by using the driving characteristic target value corresponding to the current road area, so that the vehicle can simulate the driving behavior of the user, and the driving characteristic target value corresponding to the road area is obtained when the value of the optimization model is the minimum value to control the driving of the vehicle, so that the way of controlling the vehicle is more in line with the behavior of the user when driving the vehicle, and the user's experience when using the vehicle is improved; in addition, when establishing the optimization model, the driving characteristic parameters considered include at least a parameter for characterizing the current vehicle speed, a parameter for characterizing the current vehicle driving position or a parameter for characterizing the position between the current vehicle and other vehicles, and a weight value is set for the driving characteristic parameter according to the type of the road area, so that the driving characteristic target value determined according to the optimization model is more in line with the user's driving behavior and the actual situation of the road, and the user's driving experience is further improved.

[0043] In addition, the present invention also provides a memory driving control device, a vehicle and a computer-readable storage medium, which have the same or corresponding technical features as the above-mentioned memory driving control method and have the same effects as above. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] FIG1 is a flow chart of a control method for memory driving provided by an embodiment of the present invention;

[0046] FIG2 is a schematic diagram of dividing a road into multiple road areas provided by an embodiment of the present invention;

[0047] FIG3 is a schematic diagram of a first lane change scenario provided by an embodiment of the present invention;

[0048] FIG4 is a schematic diagram of a second lane change scenario provided by an embodiment of the present invention;

[0049] FIG5 is a schematic diagram of a third lane change scenario provided by an embodiment of the present invention;

[0050] FIG6 is a schematic diagram of a fourth lane change scenario provided by an embodiment of the present invention;

[0051] FIG. 7 is a structural diagram of a control device for memory driving provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] The core of the present invention is to provide a control method, device, equipment and medium for memory driving, which are used to solve the technical problem of vehicle simulation of user driving behavior.

[0054] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. FIG1 is a flow chart of a control method for memory driving provided by an embodiment of the present invention. As shown in FIG1 , the method includes:

[0055] S10: in the process of memorizing the driving map, obtaining a driving characteristic reference value corresponding to the driving characteristic parameter of the current vehicle;

[0056] S11: establishing an optimization model according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter;

[0057] S12: when the value of the optimization model corresponding to the road area is a preset value, obtaining a driving characteristic target value corresponding to the road area; wherein the preset value is the minimum value of all values ​​of the optimization model corresponding to the road area; when all values ​​of the optimization model correspond to different driving characteristic actual values ​​of each driving characteristic parameter, the value of the optimization model;

[0058] S13: When it is detected that the memory driving function is turned on, the current road area where the vehicle is currently located is obtained, and the driving characteristic target value corresponding to the current road area is used to control the vehicle driving.

[0059] Memory driving includes two processes: mapping and starting the memory driving function. In the memory driving mapping process, the driving characteristic reference value corresponding to the driving characteristic parameters of the current vehicle is obtained. The driving characteristic parameters include at least a parameter for representing the current vehicle's driving speed, a parameter for representing the current vehicle's driving position, or a parameter for representing the position between the current vehicle and other vehicles.

[0060] Specifically, the parameters used to characterize the current vehicle speed include at least the driving speed ratio, lane change rate or intersection passability; wherein, the parameters used to characterize the intersection passability include at least the speed ratio when passing the traffic light and the indicator light indication. The parameters used to characterize the current vehicle position include at least the distance between the current vehicle and the center of the lane. The parameters used to characterize the position between the current vehicle and other vehicles include at least: the following threshold, the threshold of the lateral distance between the current vehicle and the adjacent vehicle, and the overtaking rate; wherein, the parameters characterizing the overtaking rate include at least the overtaking allowed vehicle speed and the headway time between the current vehicle and other vehicles.

[0061] In order to achieve precise control of the vehicle, the road is divided into multiple road areas in the embodiment of the present invention. Such as ordinary straight roads, curved roads, intersection waiting areas, crossroads, etc., that is, the type of road area at least includes one of a straight area type, a lane change area type, a curve area type and an intersection area type. Figure 2 is a schematic diagram of dividing a road into multiple road areas provided by an embodiment of the present invention. As shown in Figure 2, it includes road area one, road area two, road area three, road area four, road area five and road area six, and the corresponding road area types are straight area one, curve area one, lane change area, curve area two, straight area two and straight area three. Each road area corresponds to a driving characteristic parameter and a reference value of the driving characteristic parameter.

[0062] In implementation, the reference value of the driving characteristic parameter corresponding to each road area is determined specifically by the following method:

[0063] When determining the driving speed ratio, first, collect the maximum lane speed allowed by the current visual detection , and the actual vehicle speed currently collected by the wheel speed sensor , calculate the driving speed ratio of the current road area When there is no vehicle in front of the current vehicle, the driving speed ratio is the ratio between the current speed of the current vehicle and the speed limit on the lane; when there is a vehicle in front of the current vehicle, the driving speed ratio is the current speed of the current vehicle and the speed of the vehicle in front. The calculation formula of the driving speed ratio is as follows:

[0064] .

[0065] When determining the distance from the center of the lane (i.e., vehicle neutrality), the deviation of the vehicle's center position in the lane in the current road area The calculation formula is as follows:

[0066] ;

[0067] in, Indicates the current position of the vehicle in the center of the lane, Indicates the location of the lane center.

[0068] Determining the lane change rate includes:

[0069] Obtaining a first distance between the current vehicle and a common lane line before the lane change and a second distance between the current vehicle and the common lane line after the lane change; wherein the common lane line is a common lane line between the lane before the lane change and the lane after the lane change;

[0070] Obtaining a third distance between the first target line and the common lane line and a fourth distance between the second target line and the common lane line; wherein the first target line is located in the lane before the lane change, and the second target line is located in the lane after the lane change; the third distance is less than half of the lane width before the lane change, and the fourth distance is less than half of the lane width after the lane change;

[0071] The lane change rate is determined according to a relationship between the first distance and the third distance, and a relationship between the second distance and the fourth distance.

[0072] Specifically, determining the lane change rate according to the relationship between the first distance and the third distance and the relationship between the second distance and the fourth distance includes:

[0073] FIG3 is a schematic diagram of a first lane-changing scenario provided by an embodiment of the present invention, that is, the first distance is greater than or equal to the third distance, and the second distance is greater than or equal to the fourth distance. In this scenario, the lane-changing rate is determined as the ratio of the sum of the distances to the first duration; wherein the sum of the distances is the sum of the third distance and the fourth distance, the first duration is the sum of the duration of the current vehicle in the first target area and the duration of the current vehicle in the second target area, the two sides of the first target area are the first target line and the common lane line, and the two sides of the second target area are the second target line and the common lane line.

[0074] FIG4 is a schematic diagram of a second lane change scenario provided by an embodiment of the present invention, that is, the first distance is less than the third distance, and the second distance is greater than the fourth distance. In this scenario, the lane change rate is determined as the ratio of the second distance to the second duration; wherein the second duration is the duration that the current vehicle is in the second target area.

[0075] FIG5 is a schematic diagram of a third lane change scenario provided by an embodiment of the present invention, that is, the first distance is greater than or equal to the third distance, and the second distance is less than the fourth distance. In this scenario, the lane change rate is determined as the ratio of the first distance to the third duration; wherein the third duration is the duration that the current vehicle is in the first target area.

[0076] FIG6 is a schematic diagram of the fourth lane change scenario provided by an embodiment of the present invention, that is, the first distance is less than the third distance, and the second distance is less than the fourth distance. In this scenario, the lane change rate is determined as the ratio of the width of the current vehicle to the fourth time length; wherein the fourth time length is the difference between the moment when the first edge of the current vehicle presses on the common lane line and the moment when the second edge of the current vehicle presses on the common lane line. When the vehicle changes lanes from the right lane to the left lane, the first edge of the vehicle refers to the left edge of the vehicle, and the second edge refers to the right edge of the vehicle; when the vehicle changes lanes from the left lane to the right lane, the first edge of the vehicle refers to the right edge of the vehicle, and the second edge refers to the left edge of the vehicle. In FIG6, the first edge of the vehicle refers to the left edge of the vehicle, and the second edge refers to the right edge of the vehicle.

[0077] Lateral speed of the vehicle when crossing the line The calculation formula is as follows:

[0078]

[0079] in, and All are calibrated quantities. Indicates the calibrated distance from the public lane line before the vehicle changes lanes. Indicates the calibrated distance from the public lane line after changing lanes. Indicates the distance to the public lane line before changing lanes. Indicates the distance from the public lane line after changing lanes. Indicates that the vehicle is parked The duration within the range, Indicates that the vehicle is parked Duration within the range. Indicates the vehicle width. It indicates the time from the left edge of the vehicle stepping on the public lane line to the right edge of the vehicle stepping on the public lane line. Usually, due to the use of smart cameras, the distance between the vehicle and the public lane line can be output by the smart camera, so , , and can be calculated.

[0080] The following threshold is the following distance between the vehicle and the preceding vehicle in the current road area. The calculation formula is as follows:

[0081] ;

[0082] in, Indicates the distance between the vehicle and the vehicle in front.

[0083] The threshold for determining the lateral distance between the current vehicle and the neighboring vehicle (i.e., the lateral threshold) includes:

[0084] Obtain the distance between the current vehicle and the adjacent vehicle at each target moment; wherein the target moment is each moment within the duration when the current vehicle and the adjacent vehicle are traveling side by side;

[0085] The minimum distance among all distances is obtained, and the minimum distance is used as the threshold of the lateral distance between the current vehicle and the neighboring vehicle.

[0086] The calculation formula of the horizontal threshold is as follows:

[0087] ;

[0088] ;

[0089] in, It indicates the time when two vehicles are running parallel to each other. Indicates the unit time of driving (system operation cycle, default 20ms), Indicates Time and lateral distance to neighboring vehicles. Indicates 0 to The average spacing in time, Indicates 0 to Minimum spacing in time.

[0090] The calculation formula of the overtaking rate (i.e. the overtaking trigger speed threshold of the vehicle in the current road area) is as follows:

[0091] ;

[0092] ;

[0093] in, Indicates the maximum allowed speed for the current lane (when there is little traffic, the road speed limit is used; when there is heavy traffic, the maximum traffic speed of each lane is used). Indicates the allowed speed for overtaking. represents the distance to the vehicle in the left lane, Indicates the distance to the vehicle in the right lane, Indicates the calculated headway time between left and right vehicles.

[0094] The calculation formula of intersection passability is as follows:

[0095] ;

[0096] ;

[0097] in, Indicates the minimum allowed red light countdown, Indicates the remaining time of the current traffic light. Indicates the speed ratio when passing through a traffic light; Indicates the average speed when passing through the traffic light.

[0098] The above describes the method of obtaining each driving characteristic parameter. After obtaining each driving characteristic parameter, the reference value calculated by the parameter item corresponding to each road area can be stored.

[0099] When the memory driving function is turned on (driving along the memory route), the map releases the road area at the corresponding location and the above parameter information of the corresponding road area based on the positioning information. During the planning process, the weight value of each parameter will be taken into account so that the planned trajectory is more in line with the above parameter items. There is no limit on the set weight value, which can be determined by the type of road area. Afterwards, an optimization model can be established based on the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter. The optimization model is used to characterize the difference between the actual value of the driving characteristic and the reference value of the driving characteristic. The calculation formula of the optimization model is as follows:

[0100]

[0101] in, ;

[0102] ;

[0103] each They represent weight coefficients respectively, is the distance between the current vehicle and the center line of the lane, It represents half the width of the lane. Indicates half the width of the target lane when changing lanes. Indicates the current headway distance. Indicates the current lateral distance between vehicles. Indicates the current vehicle distance to the target lane, Indicates the current traffic light countdown.

[0104] In order to accurately find the optimization model corresponding to various types of road areas, in practice, the optimization model is established according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter, including:

[0105] determining a target driving characteristic parameter and a weight value of the target driving characteristic parameter according to the type of the road area;

[0106] Obtaining a difference between each target driving characteristic parameter and a driving characteristic reference value corresponding to each target driving characteristic parameter;

[0107] An optimization model is established according to the sum of the products of each difference and the weight value of the corresponding driving characteristic parameter.

[0108] In implementation, determining the target driving characteristic parameters according to the type of the road area includes:

[0109] When it is detected that the type of the road area is a straight road area type, determining the target driving characteristic parameters including the driving speed ratio, the distance between the current vehicle and the center of the lane, the following threshold, and the threshold of the lateral distance between the current vehicle and the adjacent vehicle;

[0110] When it is detected that the type of the road area is a lane change area type, determining the target driving characteristic parameters including the driving speed ratio, the distance between the current vehicle and the center of the lane, the lane change rate, the following vehicle threshold, the threshold of the lateral distance between the current vehicle and the adjacent vehicle, and the overtaking rate;

[0111] When it is detected that the type of the road area is an intersection area type, the target driving characteristic parameters are determined to include the driving speed ratio, the distance between the current vehicle and the center of the lane, the following threshold, the threshold of the lateral distance between the current vehicle and the adjacent vehicle, and the intersection passability.

[0112] That is, different types of road areas, For example, when driving in a straight line, the weight coefficient ; When changing lanes, When crossing an intersection, .

[0113] A control method for memory driving provided by an embodiment of the present invention, in the process of memory driving mapping, establishes an optimization model according to a driving characteristic reference value, a driving characteristic parameter and a weight value of the driving characteristic parameter corresponding to the driving characteristic parameter of the current vehicle, and obtains a driving characteristic target value corresponding to the road area when the value of the optimization model corresponding to the road area is the minimum value. After the memory driving function is turned on, the driving of the vehicle is controlled by using the driving characteristic target value corresponding to the current road area, so that the vehicle can simulate the driving behavior of the user, and the driving characteristic target value corresponding to the road area is obtained when the value of the optimization model is the minimum value to control the driving of the vehicle, so that the way of controlling the vehicle is more consistent with the behavior of the user when driving the vehicle, and improves the user's experience when using the vehicle; in addition, when establishing the optimization model, the driving characteristic parameters considered include at least a parameter for characterizing the current vehicle's driving speed, a parameter for characterizing the current vehicle's driving position or a parameter for characterizing the position between the current vehicle and other vehicles, and a weight value is set for the driving characteristic parameter according to the type of the road area, so that the driving characteristic target value determined according to the optimization model is more consistent with the user's driving behavior and the actual situation of the road, and further improves the user's driving experience.

[0114] In the above embodiments, the control method of the memory driving is described in detail, and the present invention also provides the control device of the memory driving and the corresponding embodiments of the control equipment of the memory driving. It should be noted that the present invention describes the embodiments of the device part from two perspectives, one is based on the functional module perspective, and the other is based on the hardware perspective.

[0115] A control device for memory driving provided by an embodiment of the present invention includes, based on the perspective of functional modules:

[0116] A first acquisition module is used to acquire a driving characteristic reference value corresponding to a driving characteristic parameter of the current vehicle during the process of memorizing the driving map; wherein the driving characteristic parameter at least includes a parameter for representing the current vehicle's driving speed, a parameter for representing the current vehicle's driving position, or a parameter for representing the position between the current vehicle and other vehicles;

[0117] An establishment module is used to establish an optimization model according to a driving characteristic reference value, a driving characteristic parameter and a weight value of the driving characteristic parameter; wherein the optimization model is used to characterize the difference between the actual driving characteristic value and the driving characteristic reference value; the weight value is determined by the type of the road area; the type of the road area includes at least one of a straight road area type, a lane change area type, a curve area type and a junction area type;

[0118] The second acquisition module is used to acquire the driving characteristic target value corresponding to the road area when the value of the optimization model corresponding to the road area is a preset value; wherein the preset value is the minimum value of all the values ​​of the optimization model corresponding to the road area; when all the values ​​of the optimization model correspond to different driving characteristic actual values ​​of each driving characteristic parameter, the value of the optimization model;

[0119] The third acquisition module is used to obtain the current road area where the current vehicle is located when detecting that the memory driving function is turned on, and control the vehicle driving by using the driving characteristic target value corresponding to the current road area.

[0120] Since the embodiments of the apparatus part correspond to the embodiments of the method part, please refer to the description of the embodiments of the method part for the embodiments of the apparatus part, which will not be repeated here.

[0121] FIG7 is a structural diagram of a control device for memory driving provided by an embodiment of the present invention. Based on the hardware perspective, as shown in FIG7 , the control of memory driving includes:

[0122] A memory 20, for storing computer programs;

[0123] The processor 21 is used to implement the steps of the method for controlling the memory driving mentioned in the above embodiment when executing the computer program.

[0124] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an artificial intelligence (AI) processor, which is used to process computing operations related to machine learning.

[0125] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein, after the computer program is loaded and executed by the processor 21, it can implement the relevant steps of the memory driving control method disclosed in any of the aforementioned embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, etc., and the storage method may be temporary storage or permanent storage. Among them, the operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include but is not limited to the data involved in the above-mentioned memory driving control method, etc.

[0126] In some embodiments, the memory driving control device may further include a display screen 22 , an input / output interface 23 , a communication interface 24 , a power supply 25 , and a communication bus 26 .

[0127] Those skilled in the art will appreciate that the structure shown in FIG. 7 does not constitute a limitation on the control device for memory driving, and may include more or fewer components than those shown in the figure.

[0128] The memory driving control device provided in the embodiment of the present invention includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the following method: the memory driving control method, the effect is the same as above.

[0129] Finally, the present invention also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps recorded in the above method embodiment are implemented.

[0130] It is understandable that if the method in the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc. Various media that can store program codes.

[0131] The computer-readable storage medium provided by the present invention includes the above-mentioned memory driving control method, and the effect is the same as above.

[0132] The above is a detailed introduction to a control method, device, equipment and medium for memory driving provided by the present invention. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referenced to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the present invention.

[0133] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. A memory driving control method, characterized in that: include: In the process of memorizing the driving map, a driving characteristic reference value corresponding to the driving characteristic parameter of the current vehicle is obtained; wherein the driving characteristic parameter at least includes a parameter for representing the current vehicle's driving speed, a parameter for representing the current vehicle's driving position, or a parameter for representing the position between the current vehicle and other vehicles; An optimization model is established according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter; wherein the optimization model is used to characterize the difference between the actual driving characteristic value and the driving characteristic reference value; the weight value is determined by the type of the road area; the type of the road area includes at least one of a straight road area type, a lane change area type, a curve area type and a junction area type; When the value of the optimization model corresponding to the road area is a preset value, obtaining the driving characteristic target value corresponding to the road area; wherein the preset value is the minimum value of all the values ​​of the optimization model corresponding to the road area; when all the values ​​of the optimization model correspond to different actual values ​​of the driving characteristics of each driving characteristic parameter, the value of the optimization model; When the memory driving function is detected to be turned on, the current road area where the vehicle is currently located is obtained, and the driving characteristic target value corresponding to the current road area is used to control the vehicle driving; The step of establishing an optimization model according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter comprises: Determining a target driving characteristic parameter and a weight value of the target driving characteristic parameter according to the type of the road area; Obtaining a difference between the actual driving characteristic value corresponding to each of the target driving characteristic parameters and the reference driving characteristic value corresponding to each of the target driving characteristic parameters; The optimization model is established according to the sum of the products of each difference and the weight value of the corresponding driving characteristic parameter.

2. The memory driving control method according to claim 1, characterized in that: The parameters used to characterize the current vehicle speed at least include a driving speed ratio, a lane change rate or an intersection passability; wherein, when there is no vehicle in front of the current vehicle, the driving speed ratio is the ratio between the current speed of the current vehicle and the speed limit on the lane; when there is a vehicle in front of the current vehicle, the driving speed ratio is the ratio between the current speed of the current vehicle and the speed of the vehicle in front; the parameters used to characterize the intersection passability at least include a speed ratio when passing a traffic light and the indicator light indication; The parameters used to characterize the current driving position of the vehicle at least include the distance between the current vehicle and the center of the lane in which it is located; The parameters used to characterize the position between the current vehicle and other vehicles include at least: a following threshold, a threshold of the lateral distance between the current vehicle and the adjacent vehicle, and an overtaking rate; wherein the parameters characterizing the overtaking rate include at least an allowable overtaking speed and a headway between the current vehicle and other vehicles; the following threshold is the following headway between the vehicle and the preceding vehicle in the current road area.

3. The memory driving control method according to claim 2, characterized in that: Determining the lane change rate includes: Obtaining a first distance between the current vehicle and a common lane line before the lane change and a second distance between the current vehicle and the common lane line after the lane change; wherein the common lane line is a common lane line between the lane before the lane change and the lane after the lane change; Acquire a third distance between the first target line and the common lane line and a fourth distance between the second target line and the common lane line; wherein the first target line is located in the lane before the lane change, and the second target line is located in the lane after the lane change; the third distance is less than half of the lane width before the lane change, and the fourth distance is less than half of the lane width after the lane change; determining the lane change rate according to a relationship between the first distance and the third distance, and a relationship between the second distance and the fourth distance; Wherein, determining the lane change rate according to the relationship between the first distance and the third distance and the relationship between the second distance and the fourth distance includes: When it is detected that the first distance is greater than or equal to the third distance and the second distance is greater than or equal to the fourth distance, the lane change rate is determined to be a ratio of the sum of the distances to a first duration; wherein the sum of the distances is the sum of the third distance and the fourth distance; When it is detected that the first distance is smaller than the third distance and the second distance is larger than the fourth distance, determining the lane change rate as a ratio of the second distance to a second duration; When it is detected that the first distance is greater than or equal to the third distance and the second distance is less than the fourth distance, determining the lane change rate as a ratio of the first distance to a third duration; When it is detected that the first distance is smaller than the third distance and the second distance is smaller than the fourth distance, determining the lane change rate as a ratio of a width of the current vehicle to a fourth time duration; The first duration is the sum of the duration of the current vehicle in the first target area and the duration of the current vehicle in the second target area, the two sides of the first target area are the first target line and the common lane line, and the two sides of the second target area are the second target line and the common lane line; The second duration is the duration that the current vehicle is in the second target area; The third duration is the duration of time the vehicle is currently in the first target area; The fourth duration is the difference between the moment when the first edge of the current vehicle presses on the common lane line and the moment when the second edge of the current vehicle presses on the common lane line.

4. The memory driving control method according to claim 2, characterized in that: The thresholds for determining the lateral distance between the current vehicle and the neighboring vehicle include: Obtain the distance between the current vehicle and the neighboring vehicle at each target moment; wherein the target moment is each moment within the duration when the current vehicle and the neighboring vehicle are traveling side by side; The minimum distance among all distances is obtained, and the minimum distance is used as a threshold of a lateral distance between the current vehicle and an adjacent vehicle.

5. The memory driving control method according to claim 2, characterized in that: Determining the overtaking allowed vehicle pressing speed includes: The overtaking allowable speed is determined according to the difference between the maximum allowable speed of the current lane and the actual speed of the vehicle; wherein the maximum allowable speed of the current lane is the road speed limit or the maximum traffic speed of each lane.

6. The memory driving control method according to claim 2, characterized in that: Determining the headway time between the current vehicle and other vehicles includes: The headway time between the current vehicle and other vehicles is determined according to the ratio of the distance value between the current vehicle and the vehicle in the adjacent lane and the actual speed of the current vehicle.

7. The memory driving control method according to claim 1, characterized in that: Determining target driving characteristic parameters according to the type of road area includes: When it is detected that the type of the road area is a straight road area type, determining the target driving characteristic parameters including a driving speed ratio, a distance between the current vehicle and the center of the lane, a following threshold, and a threshold of a lateral distance between the current vehicle and an adjacent vehicle; When it is detected that the type of the road area is a lane change area type, determining the target driving characteristic parameters including a driving speed ratio, a distance between the current vehicle and the center of the lane, a lane change rate, a following threshold, a threshold of a lateral distance between the current vehicle and an adjacent vehicle, and an overtaking rate; When it is detected that the type of the road area is an intersection area type, the target driving characteristic parameters are determined to include a driving speed ratio, a distance between the current vehicle and the center of the lane, a following threshold, a threshold for the lateral distance between the current vehicle and an adjacent vehicle, and intersection passability.

8. A memory driving control device, characterized in that: include: A first acquisition module is used to acquire a driving characteristic reference value corresponding to a driving characteristic parameter of the current vehicle during the process of memorizing the driving map; wherein the driving characteristic parameter at least includes a parameter for representing the current vehicle's driving speed, a parameter for representing the current vehicle's driving position, or a parameter for representing the position between the current vehicle and other vehicles; An establishment module is used to establish an optimization model according to the driving characteristic reference value, the driving characteristic parameter and the weight value of the driving characteristic parameter; wherein the optimization model is used to characterize the difference between the actual driving characteristic value and the driving characteristic reference value; the weight value is determined by the type of road area; the type of road area includes at least one of a straight road area type, a lane change area type, a curve area type and a junction area type; A second acquisition module is used to acquire a driving characteristic target value corresponding to the road area when the value of the optimization model corresponding to the road area is a preset value; wherein the preset value is the minimum value of all values ​​of the optimization model corresponding to the road area; and when all values ​​of the optimization model correspond to different actual values ​​of the driving characteristics of each driving characteristic parameter, the value of the optimization model; A third acquisition module is used to acquire the current road area where the current vehicle is located when detecting that the memory driving function is turned on, and control the vehicle driving by using the driving characteristic target value corresponding to the current road area; The establishment module is specifically used for: Determining a target driving characteristic parameter and a weight value of the target driving characteristic parameter according to the type of the road area; Obtaining a difference between the actual driving characteristic value corresponding to each of the target driving characteristic parameters and the reference driving characteristic value corresponding to each of the target driving characteristic parameters; The optimization model is established according to the sum of the products of each difference and the weight value of the corresponding driving characteristic parameter.

9. A memory driving control device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the memory driving control method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the memory driving control method according to any one of claims 1 to 7 are implemented.

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