CN116605228A - Vehicle driving control method and device - Google Patents

Vehicle driving control method and device Download PDF

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Publication number
CN116605228A
CN116605228A CN202210121936.4A CN202210121936A CN116605228A CN 116605228 A CN116605228 A CN 116605228A CN 202210121936 A CN202210121936 A CN 202210121936A CN 116605228 A CN116605228 A CN 116605228A
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China
Prior art keywords
driving
mode
torque
driver
braking
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CN202210121936.4A
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Chinese (zh)
Inventor
谢程宁
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Beijing Didi Infinity Technology and Development Co Ltd
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Shanghai Jusheng Technology Co Ltd
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Priority to CN202210121936.4A priority Critical patent/CN116605228A/en
Publication of CN116605228A publication Critical patent/CN116605228A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18—Propelling the vehicle
    • B60W30/182—Selecting between different operative modes, e.g. comfort and performance modes
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

Abstract

The application discloses a vehicle driving control method and a device, wherein the method comprises the following steps: determining driving control parameters based on the current driving mode fusion parameters of the driver or the characteristic data of the current driving scene; the driving mode fusion parameters are obtained based on driving behavior data of the driver; and performing driving control based on the driving control parameters. By adopting the method and the device, the convenience of driving operation can be enhanced, the matching between driving control and user habit can be improved, and driving experience can be improved.

Description

Vehicle driving control method and device
Technical Field
The present application relates to a vehicle driving control technology, and in particular, to a vehicle driving control method and apparatus.
Background
At present, many manufacturers configure multiple driving modes in automobiles for drivers to select driving control modes so as to meet different driving experience requirements. From the perspective of automobile driving feeling, the automobile driving mode determines different acceleration and deceleration response degrees of the automobile, which are obtained after a driver steps on the same accelerator depth or releases the accelerator in the driving process of the automobile.
There are two main types of driving modes in existence, one is an acceleration mode and the other is an energy recovery mode.
The acceleration mode is a driving mode for controlling the acceleration response speed of a vehicle, and is suitable for various types of automobiles (such as a fuel automobile of conventional fuel, a new energy automobile of unconventional fuel, and the like). For example, the acceleration modes commonly found on pure electric vehicles are "Sport mode/Sport", "Comfort mode/Comfort", and "economy mode/ECO", etc.
The energy recovery mode is used for the driving mode of energy recovery and is applicable to new energy automobiles such as electric vehicles or hybrid electric vehicles. In the energy recovery mode, when the driver releases the accelerator pedal but does not step on the brake pedal, the vehicle is decelerated by motor energy recovery, and the different energy recovery modes affect the magnitude of the vehicle coasting deceleration feeling. The common energy recovery modes include high recovery, medium recovery and low recovery.
Disclosure of Invention
Therefore, a primary object of the present invention is to provide a vehicle driving control method and apparatus, which can enhance the convenience and flexibility of driving operation and control and enhance the driving comfort.
In order to achieve the above purpose, the technical solution provided by the embodiment of the present invention is as follows:
a vehicle driving control method, comprising:
determining driving control parameters based on the current driving mode fusion parameters of the driver or the characteristic data of the current driving scene; the driving mode fusion parameters are obtained based on driving behavior data of the driver;
And performing driving control based on the driving control parameters.
The embodiment of the invention also provides a vehicle driving control device, which comprises:
a driving parameter determining unit, configured to determine a driving control parameter based on a current driving mode fusion parameter of a driver or feature data of a current driving scene; the driving mode fusion parameters are obtained based on driving behavior data of the driver;
and the driving control unit is used for performing driving control based on the driving control parameters.
The embodiment of the invention also provides vehicle driving control equipment which comprises a processor and a memory;
the memory has stored therein an application executable by the processor for causing the processor to execute the vehicle driving control method as described above.
The embodiment of the present invention also proposes a computer-readable storage medium in which computer-readable instructions for executing the vehicle driving control method as described above are stored.
The embodiments of the invention also propose a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the vehicle driving control method as described above.
In summary, in the vehicle driving control scheme provided by the embodiment of the invention, the driving control parameters are determined based on the current driving mode fusion parameters of the driver or the feature data of the current driving scene. Therefore, compared with a simple fixed mode selection scheme, the driving mode fusion parameter can be adjusted more finely according to the driving behavior difference of the driver, so that the driving habit requirements of the user can be met, the driving control flexibility is effectively enhanced, and the driving comfort is improved. In addition, the driving control parameters are determined without depending on the user setting driving modes, so that the convenience of driving control can be effectively enhanced, and meanwhile, the setting of the driving control parameters is not limited by a fixed driving mode set, so that the flexibility of driving control is effectively improved.
In addition, by determining the driving control parameters based on the feature data of the current driving scene, the driving control parameters for performing driving control can be matched with the current driving scene, so that the driving control can be self-adapted to the real-time driving scene without manually changing the driving mode depending on a user, and therefore, the driving comfort is improved, the complexity of driving control is reduced, and the intellectualization of driving control is increased.
Drawings
FIG. 1 is a schematic diagram of a driving control parameter determination method of a conventional driving control scheme;
FIG. 2 is a flow chart of a method according to an embodiment of the invention;
FIG. 3 is a flowchart of a method for determining driving pattern fusion parameters of a driver according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a vehicle driving control in a specific application scenario according to an embodiment of the present invention;
fig. 5 is a schematic view of a device structure according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and the embodiments, in order to make the objects, technical solutions and advantages of the present invention more apparent.
Fig. 1 is a schematic diagram of a driving control parameter determining method in a conventional driving control scheme. As shown in fig. 1, in the existing driving control scheme, when the accelerator request torque needs to be determined, the preset mapping relation between the current driving mode and the accelerator torque is queried based on the current driving mode, the vehicle speed and the accelerator pedal position, the currently adopted accelerator torque (i.e. the accelerator request torque) is determined, then the corresponding acceleration is determined according to the determined accelerator torque, and driving control is performed based on the acceleration; when the recovery torque needs to be determined, a preset mapping relation between the current driving mode and the recovery torque (the mapping relation comprises three dimensions of the accelerator pedal position, the vehicle speed and the driving mode) is queried based on the current driving mode, the vehicle speed and the accelerator pedal position, the recovery torque adopted at present is determined, and driving control is performed according to the determined recovery torque. As shown in the map of each driving pattern and acceleration/recovery torque in fig. 1, the acceleration in the sport pattern is highest, the comfort pattern is next highest, and the economy pattern is lowest at the same accelerator pedal depth and vehicle speed. In the case of throttle release (for convenience of description, the map of the driving mode and the regenerative torque in fig. 1 is a map of the maximum regenerative torque at 0 throttle), the high regenerative mode deceleration is the highest, the medium regenerative mode deceleration is the next highest, and the low regenerative mode deceleration is the smallest.
The inventors found in the course of implementing the present invention that: the existing scheme for carrying out driving control based on the driving mode has the problems of high driving control requirement, poor flexibility, poor driving comfort and the like, and the main reasons for the problems are found as follows through research and analysis:
in the existing driving control scheme, based on a driving mode manually set or default by a driver, a control parameter currently corresponding to the driving mode is queried from a mapping relation between the preset driving mode and acceleration/recovery torque, and driving control is performed based on the control parameter. Therefore, on one hand, the driver needs to know the characteristics and the applicable scene of each driving mode to select the appropriate driving mode according to the driving requirement, so that the technical requirement on the driver is high; on the other hand, because the preset driving mode range in the automobile is limited and fixed, the corresponding control parameter has thicker value granularity, and the driving habits of different drivers are different and can dynamically change along with the richness of driving experience, the driving mode range is limited in this way, each driver cannot be ensured to select a driving mode which is accurately matched with the current driving habit, the driving control flexibility is poor, the driving habit requirements of the users cannot be accurately met, and the driving comfort is poor.
In addition, in the driving process, along with the change of driving scenes, the requirement on the acceleration and deceleration response degree of the vehicle can also change, so that the driving mode is required to be dynamically switched in the driving process, the driving comfort level of the whole driving process can be ensured, the manual operation workload of a driver is increased, and the driving experience is reduced.
Fig. 2 is a schematic flow chart of a vehicle driving control method according to an embodiment of the present invention, as shown in fig. 2, the embodiment mainly includes steps 201 to 202, specifically as follows:
step 201, determining driving control parameters based on the current driving mode fusion parameters of the driver or the characteristic data of the current driving scene.
The driving mode fusion parameters are obtained based on the driving behavior data of the driver, so that the driving mode fusion parameters can accurately reflect the driving habit of the driver.
The timing of determining the driving control parameter in this step is the same as that of the existing system, that is, when a corresponding request instruction (such as an accelerator torque request or a recovery torque request) is received from the driving control system during driving, the corresponding driving control parameter needs to be determined in real time.
Here, the driving control parameter will be determined based on the driver's current driving pattern fusion parameter or the feature data of the current driving scene. Therefore, the driving mode fusion parameters can be utilized to realize stepless adjustment among different modes, so that the driving habit requirements of different drivers can be better met, or the characteristic data of the actual driving scene can be utilized to realize dynamic adjustment of the driving control parameters, so that the driving control parameters adopted in the driving control process are matched with the actual driving scene, and the driving control and the driving scene are adaptively matched, therefore, the step is beneficial to enhancing the convenience and the flexibility of driving control, and improving the driving comfort.
In one embodiment, the driving control parameter may be determined specifically according to a driving control type (habit adaptive control type or scene adaptive type) currently enabled in the driving control system of the automobile, whether to determine the driving control parameter based on a current driving pattern fusion parameter of the driver or based on feature data of a current driving scene.
Specifically, when the driving type is a habit adaptive control type, determining driving control parameters based on the current driving mode fusion parameters of the driver; and when the driving type is a scene self-adaptive type, determining driving control parameters based on the characteristic data of the current driving scene of the driver.
In one embodiment, for the driving mode fusion parameters of the driver used in step 201, as shown in fig. 3, the following steps 301 to 302 may be specifically used for dynamically determining:
step 301, when a preset parameter updating condition is met, determining a preset driving characteristic of the driver in a first driving mode based on driving behavior data generated by the driver in the first driving mode.
Here, the driving behavior data used for generating the driving mode fusion parameter is driving behavior data of the driver in a certain driving mode (namely, the first driving mode), so that driving characteristics of the driver can be obtained based on the driving behavior data of the driver in the driving mode, and the driving mode fusion parameter of the driver can be obtained based on conventional reference characteristics in the driving mode and driving characteristics of the driver, so that the driving mode fusion parameter can show driving behavior differences of different drivers, and the driving control parameter can be finely set by utilizing the obtained driving mode fusion parameter, thereby being beneficial to realizing stepless adjustment control between different driving modes and better adapting to driving habit requirements of different drivers.
In order to facilitate obtaining the driving mode fusion parameter, the first driving mode may be obtained based on an intermediate mode of the same driving mode supported by the vehicle, for example, two types of modes, that is, an acceleration mode and an energy recovery mode, are supported for the electric vehicle, a comfort mode is selected for the acceleration mode, a middle recovery mode is selected for the energy recovery mode, and a combination of the comfort mode and the energy recovery mode is used as the first driving mode of the electric vehicle.
In one embodiment, the setting the parameter updating condition specifically includes:
when a preset parameter updating period is reached; and/or when an instruction to update a driving mode fusion parameter for the driver is received.
The parameter updating period is used for periodically updating the driving mode fusion parameter, and a person skilled in the art can set a proper time length of the parameter updating period according to actual application needs and in combination with supporting capability of parameter updating operation overhead, which is not described herein.
Specifically, the instruction for updating the driving mode fusion parameters for the driver can be sent by the driver according to the requirement, and also can be sent by the maintainer according to the appointed updating maintenance strategy.
In one embodiment, in order to further improve the reliability of the obtained driving feature, the driving behavior data in step 301 is data filtered based on a preset filtering condition, that is, the driving behavior data is filtered based on the preset filtering condition before the driving feature is obtained based on the driving behavior data, so as to remove the non-conventional data in the driving behavior data, which cannot reflect the driving habit of the user, and thus avoid that the obtained driving feature cannot accurately reflect the driving habit of the driver due to the interference of the non-conventional driving behavior data of the driver.
The specific filtering conditions may be set by those skilled in the art according to actual application requirements, so long as the non-conventional data that cannot reflect the driving habits of the user can be removed, and for example, may be set as follows: the vehicle speed needs to reach more than a preset threshold (10 km/h), but is not limited thereto.
In an embodiment, when the first driving mode is a comfort mode and/or a medium recovery mode, the driving features may include: a throttle actuation feature and/or a braking feature.
Namely: when the first driving mode includes a comfort mode, the driving feature includes a throttle actuation feature; when the first driving mode includes a medium recovery mode, the driving feature includes a braking feature.
Accordingly, the determining, in step 301, the preset driving characteristics of the driver in the first driving mode specifically includes:
determining a throttle actuation characteristic and/or a braking characteristic of the driver in the first driving mode.
The accelerator pedal driving characteristics can reflect whether the vehicle acceleration operation of the driver belongs to a type of partial excitation or a type of partial softness; the braking characteristics can reflect whether the deceleration braking requirements of the driver are frequent, so that the follow-up steps determine the current driving mode fusion parameters of the driver based on the driving characteristics, and the driving mode fusion parameters capable of reflecting the driving habit requirements of the driver can be obtained.
In one embodiment, the following method may be specifically used to determine the accelerator pedal driving characteristic of the driver in the first driving mode:
and step x1, calculating the average accelerator pedal position and the average accelerator pedal position change rate of the driver based on driving behavior data of the driver in a first driving mode.
In this step, the average accelerator pedal position and the average accelerator pedal position change rate of the driver will be calculated based on the accelerator pedal position data in the historical driving behavior data generated by the driver in the first driving mode. The average accelerator pedal position change rate refers to the average change amount of the accelerator pedal position in unit time, and belongs to an index for reflecting the speed of stepping on the accelerator by a driver.
And step x2, obtaining the accelerator stepping driving characteristic by adopting a weighted calculation mode based on the average accelerator pedal position and the average accelerator pedal position change rate.
In this step, the following formula 1 may be specifically adopted to obtain the driving characteristic of stepping on the accelerator:
equation 1: a_drive=k_ Ped ×pid_pos+ (1-k_ Ped) ×pid_pos_rate; where x represents the multiplication operation.
A_drive is the accelerator pedal driving feature of the driver of the vehicle;
k_ ped is a preset accelerator pedal position weighted value, and the range of the value is more than or equal to 0 and less than or equal to 1, and particularly, the proper value can be set according to the requirements of actual automobile types (or automobile type series);
the ped_pos is the average accelerator pedal position;
the ped_pos_rate is the average accelerator pedal position change rate.
In one embodiment, the following method may be specifically used to determine the braking characteristics of the driver in the first driving mode:
and step y1, calculating the average brake pedal stepping frequency and the average brake pedal position of the driver based on the driving behavior data of the driver in the first driving mode.
And step y2, obtaining the braking characteristic by adopting a weighted calculation mode based on the average brake pedal stepping frequency and the average brake pedal position.
In this step, the braking characteristics can be obtained specifically by using the following formula 2:
equation 2: a_regen=k_brk×brk_rate+ (1-k_brk) ×brk_depth;
wherein, the liquid crystal display device comprises a liquid crystal display device,
a_regen is the braking feature of the driver of the host vehicle;
k_Brk is a preset weighting value of the frequency of stepping on the brake pedal, the range of the weighting value is more than or equal to 0 and less than or equal to 1, and the weighting value can be set appropriately according to the requirements of actual automobile types (or automobile type series);
Brk_Rate is the average brake pedal depression frequency;
brk_depth is the average brake pedal position.
And step 302, adjusting the current driving mode fusion parameters of the driver based on the driving characteristics and the corresponding preset characteristic reference values.
In one embodiment of this step, the current driving characteristics obtained in step 301 are respectively compared with corresponding characteristic reference values, and then the current driving mode fusion parameters of the corresponding driver are adjusted according to a preset adjustment strategy based on the comparison result, so that the adjusted driving mode fusion parameters are more matched with the current driving habits of the driver.
Preferably, when the first driving mode is a comfort mode and/or a medium recovery mode, the adjustment strategy may specifically be:
When the acceleration of the vehicle of the driver is biased, the driving mode fusion parameters are learned towards the direction of the movement mode;
when the acceleration operation of the vehicle of the driver is soft, the driving mode fusion parameters are learned towards the economic mode direction;
when the deceleration braking requirement of the driver is frequent, the driving mode fusion parameters are learned towards the strong recovery direction;
when the deceleration braking requirement of the driver is not frequent, the driving mode fusion parameters are learned towards the weak recovery direction.
Based on the adjustment strategy, the latest driving characteristics of the driver are utilized to self-learn the driving mode fusion parameters, so that the throttle control of the driver and the vehicle sliding deceleration control can enter a relatively comfortable section.
In one embodiment, when the driving feature comprises: when the accelerator is stepped on to drive the characteristic and/or brake the characteristic, correspondingly, the driving mode fusion parameters comprise driving fusion parameters and/or braking fusion parameters. That is, when the driving characteristics include: when the accelerator is stepped on to drive the characteristic, correspondingly, the driving mode fusion parameters comprise driving fusion parameters; when the driving characteristics include: and when the braking characteristic is met, correspondingly, the driving mode fusion parameters comprise braking fusion parameters.
Correspondingly, adjusting the current driving mode fusion parameters of the driver comprises: and adjusting the current driving fusion parameters and/or braking fusion parameters of the driver.
In one embodiment, when the first driving mode is the comfort mode and/or the middle recovery mode, the following method may be adopted to adjust the current driving fusion parameters of the driver based on the adjustment strategy:
adjustment of drive fusion parameters:
and if the difference value between the accelerator pedal driving characteristic and the preset accelerator pedal driving characteristic reference value is larger than a preset forward driving adjustment threshold value and is larger than a preset first time duration, the driving fusion parameter of the driver is increased within a preset first range. Wherein the forward drive adjustment threshold is greater than zero, and the first range is greater than or equal to-1 and less than or equal to 1.
If the difference value between the accelerator stepping driving characteristic and the accelerator stepping driving characteristic reference value is smaller than a preset negative driving adjustment threshold value and is smaller than a continuous preset second duration, driving fusion parameters of the driver are reduced in the first range; the negative drive adjustment threshold is less than zero.
Here, based on the above adjustment method, the more aggressive the driving habit of the driver (i.e., the more frequently the accelerator pedal is stepped on), the larger the driving fusion parameter value, and vice versa.
When the difference between the accelerator pedal driving characteristic and the preset accelerator pedal driving characteristic reference value is larger than a preset forward driving adjustment threshold value and is larger than a preset first duration, the accelerator pedal habit of the driver is shown to be biased, namely, the driver tends to pedal the accelerator, in order to reduce the accelerator pedal operation of the driver, the current driving fusion parameters of the driver need to be increased to enable the driving mode fusion parameters to learn in the direction of the movement mode, and therefore the driving fusion parameters can be utilized to automatically enhance accelerator driving control to replace the active accelerator pedal of the driver, and the convenience and the intellectualization of driving can be improved.
When the difference between the accelerator pedal driving characteristic and the accelerator pedal driving characteristic reference value is smaller than a preset negative driving adjustment threshold value and is smaller than a preset second duration, the acceleration control of the driver is soft, at the moment, the current driving fusion parameters of the driver need to be reduced, so that the driving mode fusion parameters learn in the direction of the economic mode, and the driving control can be matched with the habit of the driver that the acceleration control of the vehicle is soft by utilizing the adjustment of the driving fusion parameters.
When the accelerator stepping habit of the driver approaches to the average characteristic value (namely, the accelerator stepping driving characteristic reference value) obtained based on big data, the driving fusion parameters of the driver are not required to be adjusted, namely, the driver is kept unchanged.
Based on the above method, learning of the driving fusion parameter can be realized, the initial value of which is 0, and the value is learned between-1 and 1 along with updating of driving behavior data.
The first duration, the second duration, the positive driving adjustment threshold value, and the negative driving adjustment threshold value are used for limiting the time for adjusting the driving fusion parameter, and specifically, a proper value can be set by a person skilled in the art according to the reliability requirement of actual adjustment.
The specific implementation of increasing or decreasing the driving fusion parameter may be based on a preset adjustment step, i.e. increasing or decreasing one step at a time, but is not limited thereto.
The reference value of the driving feature of the accelerator pedal in the above method may be set by a person skilled in the art based on the average value of the corresponding features of the big data statistics in advance, preferably, in order to make the reference value of the driving feature of the accelerator pedal have the standard characteristic of reference, the average value of the corresponding features of all drivers in the cloud in the first driving mode (i.e. average driving feature of the accelerator pedal) may be set, for example, the reference value of the driving feature of the accelerator pedal may be obtained by using the following formula 3, but is not limited thereto.
Equation 3:
A_Drive_Avg＝k_ped*Ped_pos_avg+(1-k_ped)*Ped_pos_rate_avg；
the A_drive_avg is a weighted average value of accelerator pedal driving of all drivers in the first driving mode, namely average accelerator pedal driving characteristics of all drivers in the first driving mode;
k_ ped is a preset accelerator pedal position weighted value, and is the same as the parameter k_ ped in formula 1;
the ped_pos is the average accelerator pedal position of all drivers in the cloud in the first driving mode;
the ped_pos_rate_avg is the average accelerator pedal position change rate of all drivers in the cloud in the first driving mode.
(II) adjusting brake fusion parameters:
if the difference value between the braking characteristic and the preset braking characteristic reference value is larger than a preset forward braking adjustment threshold value and is larger than a preset third duration, the braking fusion parameter of the driver is increased within a preset second range; the forward braking adjustment threshold is greater than zero, and the second range is greater than or equal to-1 and less than or equal to 1; the brake characteristic reference value is the average brake characteristic of all drivers;
if the difference value between the braking characteristic and the preset braking characteristic reference value is smaller than a preset negative braking adjustment threshold value and is smaller than a continuously preset fourth time length, reducing the braking fusion parameter of the driver in the second range; the negative braking adjustment threshold is less than zero.
Here, based on the above adjustment method, the more aggressive the driving habit of the driver (i.e., the more frequent the braking operation), the larger the value of the braking fusion parameter, and vice versa.
When the difference between the braking characteristic and the preset braking characteristic reference value is larger than a preset forward braking adjustment threshold value and is larger than a preset third duration, the driver is frequently stepped on, the driver tends to step on the brake, and in order to reduce the braking operation of the driver, the current braking fusion parameter of the driver needs to be increased at the moment so as to enable the driving mode fusion parameter to learn towards the strong recovery mode direction, and therefore the braking control can be automatically enhanced by utilizing the braking fusion parameter to replace the active stepping on the brake of the driver, and the driving convenience and the intelligence can be improved.
When the difference between the braking characteristic and the preset braking characteristic reference value is smaller than a preset negative braking adjustment threshold value and is smaller than a continuously preset fourth duration, the driver is required to step on the braking less, and at the moment, the current braking fusion parameter of the driver is required to be reduced so as to learn the weak recovery direction of the driving mode fusion parameter, and therefore the driving control can be matched with the habit of the driver of stepping on the braking less by utilizing the adjustment of the braking fusion parameter.
In the method for adjusting the brake fusion parameters, when the brake habit of the driver approaches to the average characteristic value (namely, the brake characteristic reference value) obtained based on big data, the brake fusion parameters of the driver are not required to be adjusted, namely, the brake fusion parameters of the driver are kept unchanged.
Based on the above method, the learning of the brake fusion parameter can be realized, the initial value of which is 0, and the value is learned between-1 and 1 along with the updating of driving behavior data.
The third duration, the fourth duration, the positive braking adjustment threshold value and the negative braking adjustment threshold value are used for limiting the time for adjusting the braking fusion parameters, and particularly, a proper value can be set by a person skilled in the art according to the reliability requirement of actual adjustment.
The specific implementation of increasing or decreasing the brake fusion parameter may be based on a preset adjustment step, i.e. increasing or decreasing one step per adjustment, but is not limited thereto.
The brake characteristic reference value in the above method may be set by a person skilled in the art based on the average value of the corresponding characteristic of the big data statistics in advance, preferably, in order to make the brake characteristic reference value have the standard characteristic of reference, the average value of the corresponding characteristic (i.e. average brake characteristic) of all drivers in the cloud in the first driving mode may be set, for example, the brake characteristic reference value may be obtained by using the following formula 4, but is not limited thereto.
Equation 4:
A_Regen_Avg＝k_Brk*Brk_Rate_avg+(1-k_Brk)*Brk_Depth_avg；
wherein a_regen_avg is a weighted average of braking of all drivers in the first driving mode in the cloud, i.e. an average braking characteristic of all drivers in the first driving mode;
k_brk is a brake pedal frequency weighting value, and is the same as the parameter k_brk in formula 2;
the Brk_Rate_avg is the average brake pedal stepping frequency of all drivers in the cloud in the first driving mode;
brk_depth_avg is the average brake pedal position of all drivers in the cloud in the first driving mode.
The method for adjusting the driving fusion parameters and the braking fusion parameters finely adjusts the driving mode fusion parameters based on the driving habit of the driver. Like this, through utilizing driving pattern to fuse the parameter, learn the driving habit of driver, can make driving pattern fuse the parameter and more match with driver's driving habit, thereby can reflect different drivers' driving behavior difference, and then make in driving process, based on driver's current driving pattern fuses the parameter, confirm assorted driving control parameter and carry out driving control, alright satisfy user's driving habit demand, effectively strengthened the flexibility that drives and controlled, promoted the driving travelling comfort. In addition, the driving control parameters are determined without depending on the user setting driving modes, so that the convenience of driving control can be effectively enhanced, and meanwhile, the setting of the driving control parameters is not limited by a fixed driving mode set, so that the flexibility of driving control is effectively improved.
In practical application, the driving control parameters may be generated by the cloud and then sent to the automobile end.
In one embodiment, when the driving mode fusion parameters in step 201 include driving fusion parameters and/or braking fusion parameters, the corresponding driving control parameters to be determined include throttle request torque and/or recovery torque. That is, when the driving mode fusion parameter includes a driving fusion parameter, the driving control parameter includes a throttle request torque; when the driving mode fusion parameter includes a brake fusion parameter, the driving control parameter includes a recuperation torque. Accordingly, the determining driving control parameters in step 201 specifically includes: determining accelerator request torque based on the driver's current drive fusion parameters; and/or determining a recuperation torque based on the driver's current brake fusion parameter.
In one embodiment, the throttle request torque may be determined specifically by the following method:
if the driving fusion parameter is greater than zero, acquiring corresponding preset movement mode torque and preset comfort mode torque based on the current speed and the accelerator pedal position, and calculating the difference value of the movement mode torque and the comfort mode torque to obtain a first driving mode torque difference value; calculating the product of the torque difference value of the first driving mode and the driving fusion parameter to obtain a first driving torque adjustment value; and calculating the sum of the first driving torque adjustment value and the comfort mode torque to obtain the accelerator request torque. Specifically, the expression can be expressed by the following equation 5:
Equation 5: throttle request torque = comfort mode torque + k Drive (sport mode torque-comfort mode torque).
If the driving fusion parameter is smaller than zero, acquiring the corresponding comfort mode torque and the preset economic mode torque based on the current vehicle speed and the accelerator pedal position, and calculating the difference value of the comfort mode torque and the economic mode torque to obtain a second driving mode torque difference value; calculating the product of the torque difference value of the second driving mode and the driving fusion parameter to obtain a second driving torque adjustment value; and calculating the sum of the second driving torque adjustment value and the comfort mode torque to obtain the accelerator request torque. Specifically, the expression of the following formula 6 can be used:
equation 6: throttle request torque = comfort mode torque + k Drive (comfort mode torque-economy mode torque).
In the above method, since the driving mode fusion parameter is obtained based on the behavior data in the comfort mode and/or the medium recovery mode, when the driving fusion parameter is greater than zero, it is indicated that the adjustment from the comfort mode to the sport mode is required, so the throttle request torque is obtained based on the above formula 5, and when the driving fusion parameter is less than zero, it is indicated that the adjustment from the comfort mode to the economy mode is required, so the throttle request torque is obtained based on the above formula 6.
In one embodiment, the recovery torque may be determined specifically by the following method:
if the brake fusion parameter is greater than zero, acquiring corresponding preset high recovery mode torque and preset medium recovery mode torque based on the current vehicle speed and the accelerator pedal position; calculating the difference value between the high recovery mode torque and the medium recovery mode torque to obtain a first braking mode torque difference value; calculating the product of the first braking mode torque difference value and the braking fusion parameter to obtain a first braking torque adjustment value; and calculating the sum of the first braking torque adjustment value and the medium recovery mode torque to obtain the recovery torque. Specifically, the expression of the following formula 7 can be used:
equation 7: regenerative torque=medium regenerative mode torque+k_regen (high regenerative mode torque-medium regenerative mode torque).
If the brake fusion parameter is smaller than zero, acquiring the corresponding medium recovery mode torque and the corresponding preset low recovery mode torque based on the current vehicle speed and the accelerator pedal position; calculating the medium recovery mode torque and the low recovery mode torque to obtain a second braking mode torque difference value; calculating the product of the second braking mode torque difference value and the braking fusion parameter to obtain a second braking torque adjustment value; and calculating the sum of the second braking torque adjustment value and the medium recovery mode torque to obtain the recovery torque. Specifically, the expression of the following formula 8 can be used:
Equation 8: regenerative torque=medium regenerative mode torque+k_regen (medium regenerative mode torque-low regenerative mode torque).
In the above method, since the driving mode fusion parameter is obtained based on the behavior data in the comfort mode and/or the medium recovery mode, when the braking fusion parameter is greater than zero, it is indicated that the medium recovery mode is required to be adjusted to the high recovery mode, and therefore, the recovery torque is obtained based on the above formula 7, and when the braking fusion parameter is less than zero, it is indicated that the medium recovery mode is required to be adjusted to the low recovery mode, and therefore, the accelerator request torque is obtained based on the above formula 8.
In the above method for determining the accelerator request torque and the recovery torque, the sport mode torque, the comfort mode torque, the economic mode torque, the low recovery torque, the medium recovery torque and the high recovery torque may be obtained by searching a map table of a preset driving mode and an acceleration/recovery torque with a current vehicle speed and an accelerator pedal position as indexes, and based on the table searching results and the driving mode fusion parameter values, the current accelerator request torque and the recovery torque are calculated in real time. The throttle request torque is between the economic mode torque and the sport mode torque, the recovery torque is between the low recovery torque and the high recovery torque, and the self-adaptive adjustment is carried out according to the driving mode fusion parameters of the driver, so that compared with the existing scheme of directly obtaining the driving control parameters based on the table look-up of the current driving mode, the value granularity of the driving control parameters in the embodiment of the application is finer, and the stepless adjustment can be carried out between different modes by utilizing the driving mode fusion parameters, thereby better adapting to the driving habit requirements of different drivers.
In one embodiment, when the current driving type is a scene self-adaptive type, in the running process of the automobile, feature data of the current driving scene is acquired in real time, and according to the feature data of the driving scene acquired in real time, a matched driving control parameter is determined, specifically, the driving control parameter can be determined by adopting the following method:
determining a driving mode matched with the current driving scene according to the mapping relation between the preset driving mode and the characteristic data; based on the determined driving mode, a current driving control parameter is obtained.
Here, since the current driving control parameter is obtained based on the driving mode matched with the current driving scene, that is, the driving control parameter (i.e., accelerator request torque or recovery torque) corresponding to the driving mode matched with the current driving scene is queried with the current vehicle speed and accelerator pedal position as indexes from the mapping relation table of the preset driving mode and the acceleration/recovery torque, the obtained driving control parameter can be matched with the actual driving scene.
In one embodiment, the characteristic data may be set by those skilled in the art according to actual scene adaptive control policy requirements, and may include, but not limited to, road condition data, road type, and/or driving speed, for example.
In one embodiment, a mapping relationship between the driving mode and the feature data may be set as follows:
when the road condition of the driving scene is in a preset congestion state, the driving mode is a combination of an economic mode and a strong recovery mode;
when the road type of the driving scene is a high-speed road section and the road condition is in a preset unobstructed state, the driving mode is a combination of a sport mode and a low recovery mode.
Based on the mapping relation, driving control can be more accurately matched with the current application scene, and a driver can obtain more comfortable driving experience. For example, when the vehicle runs on a traffic jam road section and the current mode is a combination of a sport mode and low recovery, the system can judge through navigation information that the current mode is suggested to the driver to be switched to the combination of an economic mode and high recovery, so that the following experience when the vehicle is jammed is improved to a great extent; when the vehicle enters the high-speed road section and traffic is no longer congested, if the current driving mode is a combination of the economy mode and the strong recovery, the system can recommend the current mode to be switched to the combination of the sport mode and the low recovery to the driver, so that the driving experience of the high-speed road section is improved.
The above-described mapping relation is merely a specific exemplary illustration, and is not limited to this in practical application. For example, a person skilled in the art may set the scene condition matched with the driving mode as a combination of various feature data or distinguish the same kind of features to a fine granularity degree according to actual needs, so as to achieve more accurate matching of the scene and the mode through the condition setting of a finer granularity. For example, different congestion degrees can be distinguished, different phase matching modes can be set, and different combinations of vehicle speed and road types can be utilized to set a plurality of phase matching modes, which are not described herein.
In one embodiment, when it is found that there is another driving mode that can be more matched with the current driving scene than the currently adopted driving mode, the method can firstly notify the driver, and then trigger the switching of the driving modes after receiving the mode switching instruction of the driver, specifically as follows:
and when the determined driving mode is inconsistent with the currently adopted driving mode, notifying the determined driving mode as the current recommended driving mode to a driver, and if an instruction of switching to the current recommended driving mode by the driver is received, switching the current driving mode to the determined driving mode.
In one embodiment, in order to reduce the influence of mode switching on the driver, an automatic switching function may be provided, and when a more matched driving mode is detected after the automatic switching function is turned on, the automatic switching function may automatically switch to another driving mode more matched with the current driving scene without selecting by the driver. Furthermore, before the system performs mode switching, the driver can be prompted by signals such as voice, prompt tone or light to perform mode switching, so that the driver is ensured not to feel frightened due to the mode switching, and driving experience is further improved.
And 202, performing driving control based on the driving control parameters.
The specific implementation of this step is known to those skilled in the art and will not be described in detail herein.
The implementation and technical effects of the above embodiments are further exemplarily described below in conjunction with a specific application scenario and fig. 4.
As shown in fig. 4, in this application scenario, driving behavior data (including information of stepping on an accelerator and a brake) of a driver is stored in a cloud server, so that a driving mode fusion parameter is determined for the driver based on the driving behavior data of the driver by the cloud server. Thus, the driving mode fusion parameters obtained based on the driving behavior data of the driver can accurately reflect the driving habit of the driver. Correspondingly, in the driving process, when the selected driving type is the habit self-adaptive control type (namely 1 is selected in the diagram), the torque of the driving mode matched with the driving mode fusion parameter of the driver is inquired by taking the current speed and the accelerator pedal position as indexes from a mapping relation table of the preset driving mode and the accelerating/recovering torque, and then the current accelerator request torque (namely the accelerating torque in the diagram) and the recovering torque are calculated in real time based on the inquired result and the driving mode fusion parameter. In this way, the acceleration obtained based on the accelerator request torque is in the acceleration interval range corresponding to the economic mode and the motion mode (namely the working interval of the self-adaptive driving mode shown by the shaded area in the figure), and self-adaptive adjustment is carried out according to the driving mode fusion parameters of the driver; the recovery torque is adaptively adjusted according to the driving mode fusion parameters of the driver in the range of the recovery torque interval corresponding to the low recovery mode and the high recovery mode (i.e., the working interval of the adaptive recovery mode shown by the shaded area in the figure). Therefore, compared with the existing simple fixed mode selection scheme, the method can make finer adjustment for the driving behavior difference of the driver, realize stepless adjustment of the driving control parameters among different modes, and enable the setting of the driving control parameters not to be limited by the fixed driving mode set, so that the method can better adapt to the driving habit requirements of different drivers, meet the individualized driving habit requirements of the user, effectively enhance the flexibility of driving control and improve driving comfort. Moreover, since the driving control parameter is determined without depending on the user setting of the driving mode, the convenience of driving manipulation can be effectively enhanced.
In the scenario shown in fig. 4, the cloud server provides the feature data (including real-time navigation and road condition information) of the current driving scenario, when the selected driving type is the scenario adaptive type (i.e. selecting 2 in the diagram), the driving control parameter is determined based on the feature data of the current driving scenario, that is, the driving control parameter (i.e. acceleration torque or recovery torque in the diagram) corresponding to the driving mode matched with the current driving scenario is queried with the current vehicle speed and accelerator pedal position as indexes from the mapping relation between the preset driving mode and the acceleration/recovery torque, so that the driving control parameter for driving control can be matched with the current driving scenario, so that the driving control can be self-adaptive to the real-time driving scenario without manually changing the driving mode depending on the user, and therefore, the driving comfort is improved, the complexity of driving control is reduced, and the intelligentization of driving control is increased.
Based on the above-mentioned vehicle driving control method embodiment, the embodiment of the present application further realizes a vehicle driving control device, as shown in fig. 5, including:
a driving parameter determining unit 501, configured to determine a driving control parameter based on a current driving mode fusion parameter of a driver or feature data of a current driving scene; the driving mode fusion parameters are obtained based on driving behavior data of the driver;
And a driving control unit 502 for performing driving control based on the driving control parameter.
The above embodiments of the apparatus and the method are implemented based on the same inventive concept, and because the implementation principles of the two embodiments are similar, the implementation of the apparatus and the method may refer to each other, and the repetition is not repeated.
Based on the embodiment of the abnormal positioning identification method, the embodiment of the application also realizes vehicle driving control equipment, which comprises a processor and a memory; the memory has stored therein an application executable by the processor for causing the processor to execute the vehicle driving control method as described above. Specifically, a system or apparatus provided with a storage medium on which a software program code realizing the functions of any of the above embodiments is stored, and a computer (or CPU or MPU) of the system or apparatus may be caused to read out and execute the program code stored in the storage medium. Further, some or all of the actual operations may be performed by an operating system or the like operating on a computer based on instructions of the program code. The program code read out from the storage medium may also be written into a memory provided in an expansion board inserted into the computer or into a memory provided in an expansion unit connected to the computer, and then, based on instructions of the program code, the CPU or the like mounted on the expansion board or the expansion unit may be caused to perform part or all of actual operations, thereby realizing the functions of any of the embodiments of the vehicle driving control method described above.
The memory may be implemented as various storage media such as an electrically erasable programmable read-only memory (EEPROM), a Flash memory (Flash memory), a programmable read-only memory (PROM), and the like. A processor may be implemented to include one or more central processors or one or more field programmable gate arrays, where the field programmable gate arrays integrate one or more central processor cores. In particular, the central processor or central processor core may be implemented as a CPU or MCU.
An embodiment of the application realizes a computer program product comprising a computer program/instruction, characterized in that the computer program/instruction, when executed by a processor, implements the steps of the vehicle driving control method as described above.
It should be noted that not all the steps and modules in the above processes and the structure diagrams are necessary, and some steps or modules may be omitted according to actual needs. The execution sequence of the steps is not fixed and can be adjusted as required. The division of the modules is merely for convenience of description and the division of functions adopted in the embodiments, and in actual implementation, one module may be implemented by a plurality of modules, and functions of a plurality of modules may be implemented by the same module, and the modules may be located in the same device or different devices.
The hardware modules in the various embodiments may be implemented mechanically or electronically. For example, a hardware module may include specially designed permanent circuits or logic devices (e.g., special purpose processors such as FPGAs or ASICs) for performing certain operations. A hardware module may also include programmable logic devices or circuits (e.g., including a general purpose processor or other programmable processor) temporarily configured by software for performing particular operations. As regards implementation of the hardware modules in a mechanical manner, either by dedicated permanent circuits or by circuits that are temporarily configured (e.g. by software), this may be determined by cost and time considerations.
In this document, "schematic" means "serving as an example, instance, or illustration," and any illustrations, embodiments described herein as "schematic" should not be construed as a more preferred or advantageous solution. For simplicity of the drawing, the parts relevant to the present invention are shown only schematically in the drawings, and do not represent the actual structure thereof as a product. Additionally, in order to simplify the drawing for ease of understanding, components having the same structure or function in some of the drawings are shown schematically with only one of them, or only one of them is labeled. In this document, "a" does not mean to limit the number of relevant portions of the present invention to "only one thereof", and "an" does not mean to exclude the case where the number of relevant portions of the present invention is "more than one". In this document, "upper", "lower", "front", "rear", "left", "right", "inner", "outer", and the like are used merely to indicate relative positional relationships between the relevant portions, and do not limit the absolute positions of the relevant portions.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (13)

1. A vehicle driving control method, characterized by comprising:
determining driving control parameters based on the current driving mode fusion parameters of the driver or the characteristic data of the current driving scene; the driving mode fusion parameters are obtained based on driving behavior data of the driver;
and performing driving control based on the driving control parameters.
2. The method according to claim 1, wherein the method further comprises:
when a preset parameter updating condition is met, determining a preset driving characteristic of the driver in a first driving mode based on driving behavior data generated by the driver in the first driving mode;
and adjusting the current driving mode fusion parameters of the driver based on the driving characteristics and the corresponding preset characteristic reference values.
3. The method of claim 2, wherein the determining the preset driving characteristics of the driver in the first driving mode comprises:
Determining a throttle actuation characteristic and/or a braking characteristic of the driver in the first driving mode.
4. The method of claim 3, wherein determining the driver's accelerator drive feature in the first driving mode comprises:
calculating an average accelerator pedal position and an average accelerator pedal position change rate of the driver based on driving behavior data generated by the driver in a first driving mode;
based on the average accelerator pedal position and the average accelerator pedal position change rate, obtaining the accelerator stepping driving characteristic by adopting a weighted calculation mode;
determining a braking characteristic of the driver in the first driving mode includes:
calculating an average brake pedal depression frequency and an average brake pedal position of the driver based on driving behavior data generated by the driver in a first driving mode;
and obtaining the braking characteristic by adopting a weighted calculation mode based on the average brake pedal stepping frequency and the average brake pedal position.
5. The method of claim 2, wherein the adjusting the driver's current driving pattern fusion parameters comprises: adjusting the current driving fusion parameters and/or braking fusion parameters of the driver;
Wherein, the adjusting the current driving fusion parameter of the driver comprises:
if the difference value between the accelerator stepping driving characteristic and the preset accelerator stepping driving characteristic reference value is larger than a preset forward driving adjustment threshold value and is larger than a continuous preset first time length, driving fusion parameters of the driver are increased within a preset first range; the forward driving adjustment threshold is greater than zero, and the first range is greater than or equal to-1 and less than or equal to 1; the accelerator pedal driving characteristic reference value is an average accelerator pedal driving characteristic of all drivers;
if the difference value between the accelerator stepping driving characteristic and the accelerator stepping driving characteristic reference value is smaller than a preset negative driving adjustment threshold value and is smaller than a continuous preset second duration, driving fusion parameters of the driver are reduced in the first range; the negative drive adjustment threshold is less than zero;
the adjusting of the current brake fusion parameters of the driver comprises the following steps:
if the difference value between the braking characteristic and the preset braking characteristic reference value is larger than a preset forward braking adjustment threshold value and is larger than a preset third duration, the braking fusion parameter of the driver is increased within a preset second range; the forward braking adjustment threshold is greater than zero, and the second range is greater than or equal to-1 and less than or equal to 1; the brake characteristic reference value is the average brake characteristic of all drivers;
If the difference value between the braking characteristic and the preset braking characteristic reference value is smaller than a preset negative braking adjustment threshold value and is smaller than a continuously preset fourth time length, reducing the braking fusion parameter of the driver in the second range; the negative braking adjustment threshold is less than zero.
6. The method of claim 2, wherein the step of determining the position of the substrate comprises,
the first driving mode includes a comfort mode;
the driving mode fusion parameters comprise driving fusion parameters;
the driving control parameters include throttle request torque;
determining the driving control parameter based on the driver's current driving pattern fusion parameter includes:
determining accelerator request torque based on the driver's current drive fusion parameters;
the determining the throttle request torque includes:
if the driving fusion parameter is greater than zero, acquiring corresponding preset movement mode torque and preset comfort mode torque based on the current speed and the accelerator pedal position, and calculating the difference value of the movement mode torque and the comfort mode torque to obtain a first driving mode torque difference value; calculating the product of the torque difference value of the first driving mode and the driving fusion parameter to obtain a first driving torque adjustment value; calculating the sum of the first driving torque adjustment value and the comfort mode torque to obtain the accelerator request torque;
If the driving fusion parameter is smaller than zero, acquiring the corresponding comfort mode torque and the preset economic mode torque based on the current vehicle speed and the accelerator pedal position, and calculating the difference value of the comfort mode torque and the economic mode torque to obtain a second driving mode torque difference value; calculating the product of the torque difference value of the second driving mode and the driving fusion parameter to obtain a second driving torque adjustment value; and calculating the sum of the second driving torque adjustment value and the comfort mode torque to obtain the accelerator request torque.
7. The method of claim 2, wherein the step of determining the position of the substrate comprises,
the first driving mode includes a medium recovery mode;
the driving mode fusion parameters comprise braking fusion parameters;
the driving control parameters include a recuperation torque;
determining the driving control parameter based on the driver's current driving pattern fusion parameter includes:
determining a recovery torque based on the driver's current brake fusion parameters;
the determining the recovery torque includes:
if the brake fusion parameter is greater than zero, acquiring corresponding preset high recovery mode torque and preset medium recovery mode torque based on the current vehicle speed and the accelerator pedal position; calculating the difference value between the high recovery mode torque and the medium recovery mode torque to obtain a first braking mode torque difference value; calculating the product of the first braking mode torque difference value and the braking fusion parameter to obtain a first braking torque adjustment value; calculating the sum of the first braking torque adjustment value and the medium recovery mode torque to obtain the recovery torque;
If the brake fusion parameter is smaller than zero, acquiring the corresponding medium recovery mode torque and the corresponding preset low recovery mode torque based on the current vehicle speed and the accelerator pedal position; calculating the medium recovery mode torque and the low recovery mode torque to obtain a second braking mode torque difference value; calculating the product of the second braking mode torque difference value and the braking fusion parameter to obtain a second braking torque adjustment value; and calculating the sum of the second braking torque adjustment value and the medium recovery mode torque to obtain the recovery torque.
8. The method according to claim 1, wherein the method further comprises:
acquiring the characteristic data of the current driving scene in real time;
based on the current characteristic data, determining driving control parameters includes:
determining a driving mode matched with the current driving scene according to the mapping relation between the preset driving mode and the characteristic data; based on the determined driving mode, a current driving control parameter is obtained.
9. The method of claim 8, wherein the mapping of the driving pattern to the characteristic data comprises:
when the road condition of the driving scene is in a preset congestion state, the driving mode is a combination of an economic mode and a strong recovery mode;
When the road type of the driving scene is a high-speed road section and the road condition is in a preset unobstructed state, the driving mode is a combination of a sport mode and a low recovery mode.
10. A vehicle driving control apparatus, characterized by comprising:
a driving parameter determining unit, configured to determine a driving control parameter based on a current driving mode fusion parameter of a driver or feature data of a current driving scene; the driving mode fusion parameters are obtained based on driving behavior data of the driver;
and the driving control unit is used for performing driving control based on the driving control parameters.
11. A vehicle driving control apparatus, characterized by comprising a processor and a memory;
the memory has stored therein an application executable by the processor for causing the processor to execute the vehicle driving control method according to any one of claims 1 to 9.
12. A computer-readable storage medium having stored therein computer-readable instructions for executing the vehicle driving control method according to any one of claims 1 to 9.
13. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the vehicle driving control method of any one of claims 1 to 9.
CN202210121936.4A 2022-02-09 2022-02-09 Vehicle driving control method and device Pending CN116605228A (en)

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Application Number Priority Date Filing Date Title
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