CN111483460A - Vehicle driving assistance control method, device, equipment and storage medium - Google Patents
Vehicle driving assistance control method, device, equipment and storage medium Download PDFInfo
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- CN111483460A CN111483460A CN201910017822.3A CN201910017822A CN111483460A CN 111483460 A CN111483460 A CN 111483460A CN 201910017822 A CN201910017822 A CN 201910017822A CN 111483460 A CN111483460 A CN 111483460A
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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
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/107—Longitudinal acceleration
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/109—Lateral acceleration
Abstract
The invention provides a vehicle auxiliary driving control method, a device, equipment and a storage medium, wherein the method comprises the steps of obtaining vehicle-related information, wherein the vehicle-related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information; determining a driver type from the vehicle-related information; obtaining target auxiliary driving parameters according to the driver type; and then performing auxiliary driving on the vehicle based on the target auxiliary driving parameter. The invention can provide personalized and anthropomorphic driving experience for the driver; the experience feeling brought to the driver by the auxiliary driving function of the vehicle is effectively improved.
Description
Technical Field
The invention relates to the technical field of vehicle control, in particular to a vehicle driving assistance control method, device, equipment and storage medium.
Background
With the rapid development of highway traffic, particularly expressways, vehicles become important elements in modern road traffic systems, and the wide use of vehicles promotes the civilization and progress of human society. The auxiliary driving function of the vehicle is a function for improving the driving effectiveness and reliability of a driver; the method mainly utilizes intelligent information processing to realize the state of automatic driving without manual intervention; from the realization function of the technical product, the method comprises a plurality of key technical links such as map acquisition, environment perception, decision planning, control execution and the like, and relates to the contents in various aspects such as adaptive cruise control and the like.
However, the current vehicle driving assistance function is too much concerned about the unmanned control of the vehicle, neglects the driving habit of the driver, and further seriously affects the driving experience of the driver.
Therefore, it is desirable to provide a technical solution that can effectively improve the experience of vehicle-assisted driving.
Disclosure of Invention
In order to solve the technical problem, the invention provides a vehicle driving assistance control method, a device, equipment and a storage medium, and specifically comprises the following steps:
one aspect provides a vehicle driving assist control method, including:
acquiring vehicle-related information, wherein the vehicle-related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information;
determining a driver type from the vehicle-related information;
obtaining target auxiliary driving parameters according to the driver type;
and performing auxiliary driving on the vehicle based on the target auxiliary driving parameter.
Another aspect provides a vehicle driving assist control apparatus, including:
the vehicle-related information acquisition module is used for acquiring vehicle-related information, wherein the vehicle-related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information;
a driver type determination module for determining a driver type from the vehicle-related information;
the target auxiliary driving parameter obtaining module is used for obtaining target auxiliary driving parameters according to the type of the driver;
and the driving assistance control module is used for performing driving assistance on the vehicle based on the target driving assistance parameters.
Another aspect provides an apparatus comprising a processor and a memory having stored therein at least one instruction, at least one program, set of codes, or set of instructions that is loaded and executed by the processor to implement a vehicle assisted driving control method as described in the above aspect.
Another aspect provides a computer-readable storage medium having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions, which is loaded and executed by a processor to implement the vehicle driving assistance control method according to the above aspect
The vehicle driving assisting method, the vehicle driving assisting device, the vehicle driving assisting equipment and the storage medium have the advantages that:
the method comprises the steps of obtaining vehicle-related information, wherein the vehicle-related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information; determining a driver type further from the vehicle-related information; obtaining target auxiliary driving parameters according to the driver type; and then performing auxiliary driving on the vehicle based on the target auxiliary driving parameter. The target auxiliary driving parameters obtained by the method can be matched with the type of the driver driving the vehicle at present, so that personalized and anthropomorphic driving experience is provided for the driver; the experience feeling brought to the driver by the auxiliary driving function of the vehicle is effectively improved.
Drawings
Fig. 1 is a flowchart of a vehicle driving assistance control method provided in an embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating steps provided by embodiments of the present disclosure to determine a driver type from the vehicle-related information;
FIG. 3 is a schematic diagram of types of drivers refined from driving style and driving ability levels provided by embodiments of the present description;
FIG. 4 is a flowchart illustrating steps provided by embodiments of the present disclosure for determining a driving style level from the dynamic acceleration information of the vehicle;
FIG. 5 is a flowchart of steps provided by an embodiment of the present specification to obtain a target style parameter for a first monitoring duration;
FIG. 6 is a flowchart of steps provided by embodiments of the present disclosure to determine an initial style parameter for each first time segment;
FIG. 7 is a flowchart illustrating steps for calculating the target style parameters according to all the initial style parameters according to embodiments of the present disclosure;
FIG. 8 is a flowchart illustrating steps provided by embodiments of the present disclosure for determining a drivability level from the dynamic deceleration information of the vehicle;
FIG. 9 is a flowchart of steps provided by embodiments of the present specification to obtain a target capacity parameter for a second monitoring duration;
FIG. 10 is a flowchart of the steps provided by the embodiments of the present disclosure to determine an initial capability parameter for each second time segment;
FIG. 11 is a flowchart illustrating steps provided in an embodiment of the present disclosure to calculate the target performance parameter according to all initial performance parameters;
FIG. 12 is a schematic flow chart illustrating obtaining target style parameters according to an embodiment of the present disclosure;
FIG. 13 is a schematic flow chart of obtaining a target capability parameter according to an embodiment of the present disclosure;
fig. 14 is a schematic configuration diagram of a vehicle driving assistance control device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments in the present description, belong to the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the specification described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Existing vehicles generally have a driving assistance function, such as an adaptive cruise function; however, only one driving style corresponding to the driving assistance function is available, so that when a driver uses an advanced driving assistance system (adas), the driver can only automatically control the vehicle by using the inherent driving style, which is difficult to meet the driving assistance requirements of different drivers.
Therefore, the present specification proposes a technical solution that can assist driving with respect to the style of the driver; the scheme is mainly applied to an intelligent automobile and used for assisting a driver in driving the automobile in an auxiliary mode; the target auxiliary driving parameters matched with the current driver are obtained through further processing by acquiring vehicle related information such as acceleration, angular speed and the like of the vehicle in real time, so that the driving habits of different drivers are adapted, and personalized and personified driving experience is provided for the drivers.
As shown in fig. 1, an embodiment of the present specification provides a vehicle driving assist control method, including:
s202, obtaining vehicle related information, wherein the vehicle related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information;
the method comprises the steps of collecting vehicle related information in real time through a vehicle controller of a vehicle, and specifically collecting vehicle dynamic acceleration information and vehicle dynamic deceleration information.
S204, determining the type of a driver according to the vehicle related information;
in detail, the vehicle control unit processes and analyzes the collected vehicle-related information; and further determining the type of the driver according to the processing and analyzing result.
S206, obtaining target auxiliary driving parameters according to the driver type;
the step of obtaining the target auxiliary driving parameter corresponding to the driver type may be that the vehicle controller obtains an auxiliary driving comparison table from a vehicle memory, where the auxiliary driving comparison table is used to represent a corresponding relationship between the driver type and the target auxiliary driving parameter; and further comparing the currently determined driver type with the driver type in the assistant driving comparison table, so as to match the target assistant driving parameter corresponding to the currently determined driver type.
And S208, carrying out auxiliary driving on the vehicle based on the target auxiliary driving parameters.
Specifically, after the vehicle controller obtains the target driving assistance parameter and detects confirmation information for starting driving assistance, the current vehicle is automatically driven to be assisted by using the target driving assistance parameter.
In the embodiment, the type of a driver is determined according to the vehicle-related information, a target auxiliary driving parameter is further obtained according to the type of the driver, and then the vehicle is subjected to auxiliary driving based on the target auxiliary driving parameter; the target auxiliary driving parameters can be matched with the type of a driver driving a vehicle at present, so that personalized and personified driving experience is provided for the driver, and the viscosity of a user is improved.
In one possible embodiment, step S204 determines the driver type from the vehicle-related information, which may include, as shown in fig. 2;
s402, determining a driving style grade according to the dynamic acceleration information of the vehicle;
the driving style of the driver can be divided into a plurality of different styles according to the driving severity of the driver in the scene of accelerated driving, and the driving styles are ranked according to different grades. For example: three styles are comfortable, stable and radical; the level given to the comfort driving style is S1, the level of the robust driving style is S2, and the level of the aggressive driving style is S3. And further processing the vehicle dynamic acceleration information, and matching the driving style grade of the driver according to the processed data information.
S404, determining the driving capacity grade according to the dynamic deceleration information of the vehicle;
for example, three abilities of novice, proficiency and professionalism are given, the level of the driving ability given to the novice is L1, the level of the proficiency driving ability is L2, and the level of the professionalism driving ability is L3.
And S406, obtaining the driver type according to the driving style grade and the driving ability grade.
The driving style grade and the driving ability grade are freely combined and correspond to one driver type, so that the driver type is refined into various types; for example, as shown in FIG. 3, the driver type may be comfort novice A, robust proficiency B, aggressive specialty C, and the like. Therefore, after the current driving style level and the driving ability level are determined, the corresponding driver type is obtained.
In the embodiment, the driving style and the driving capability of the driver are comprehensively considered, so that the classification of the driver types is more refined, more accurate target auxiliary driving parameters can be provided for different drivers, and the driving experience of the auxiliary driving function on the driver is further improved.
In practical application, generally, the acquisition of the relevant information of the vehicle is started after the vehicle is started to reach a normal driving stage so as to ensure the accuracy of the acquisition of the relevant information of the vehicle, and the type of the driver is reasonably matched; therefore, correspondingly:
in one specific embodiment, the step S204 of determining the driver type from the vehicle-related information may include:
monitoring a current speed of the vehicle;
and when the current speed is greater than the preset speed, triggering the corresponding vehicle related information to be processed so as to determine the type of the driver.
For example, the speed of the vehicle is monitored at any time after the vehicle is started, and if the preset speed is 30 km/h, the processing of the relevant information of the corresponding vehicle is triggered to be performed when the current vehicle speed is monitored to reach 30 km/h, so as to determine the type of the driver. The triggering process of the vehicle dynamic acceleration information and the triggering process of the vehicle dynamic deceleration information may be under the same triggering condition or different triggering conditions, which is not limited herein.
In one embodiment, the step S206 of obtaining the target driving assistance parameter according to the driver type may include:
acquiring an auxiliary driving parameter table, wherein the auxiliary driving parameter table is used for representing the corresponding relation between the type of a driver and target auxiliary driving parameters;
and matching target auxiliary parameters corresponding to the driver type from the auxiliary driving parameter table.
A possible implementation manner, where the driving assistance of the vehicle according to the target driving assistance parameter may be preceded by:
acquiring original auxiliary driving parameters of a vehicle;
and updating the original assistant driving parameters to the target assistant driving parameters.
Specifically, the original driving assistance parameters are driving assistance parameters obtained by performing information acquisition and driver type identification on the free driving operation of the vehicle at the previous stage; in the embodiment, the target auxiliary driving parameters obtained by acquiring and processing the information of the free driving in the current stage are used for replacing the original auxiliary driving parameters in the previous stage; or correcting the original auxiliary driving parameters; thereby being capable of providing more matched driving assisting functions for the current driver.
It should be noted that the vehicle-assisted driving control scheme in the present specification may be executed according to a preset time, for example, every 5 hours; or, the fire extinguishing is performed according to the period of starting the vehicle to extinguish the fire, for example, once the vehicle is started every time the vehicle is detected, the fire extinguishing is performed once when the vehicle runs and meets other related preset conditions; the method may also be performed in other setting manners, and is not particularly limited.
In specific application, target auxiliary driving parameters can be acquired by a driver driving freely for a period of time; specifically, acquiring vehicle dynamic acceleration information and vehicle dynamic deceleration information within the driving time, determining a driving style grade according to the vehicle dynamic acceleration information, and determining a driving capacity grade according to the vehicle dynamic deceleration information; correspondingly:
in one embodiment, the step S402 of determining the driving style grade from the vehicle dynamic acceleration information may include, as shown in fig. 4:
s602, acquiring a target style parameter of a first monitoring duration; the target style parameters are obtained according to a statistic value that the vehicle dynamic acceleration information in the first monitoring duration is within a first information range;
and S604, obtaining the driving style grade according to the target style parameters.
Specifically, the first monitoring duration is the time for acquiring the vehicle dynamic acceleration information of the vehicle controller, for example, 10 min; and in the 10min, the driver freely drives the vehicle, the vehicle controller compares the collected dynamic acceleration information of the vehicle with the first information range, and counts the times of the dynamic acceleration information of the vehicle within the 10min, which is located in the first information range, so as to obtain the target style parameter.
It should be noted that the first monitoring duration may be set according to a requirement, and is not limited to a certain value.
In the embodiment, the vehicle control unit takes the short free driving time of the driver to the vehicle as a first monitoring duration, and obtains the driving style grade through processing and analyzing the dynamic acceleration information of the vehicle in the first monitoring duration; auxiliary driving parameters for auxiliary driving can be determined efficiently after the driver drives for a short time, and the operation time of the driver is saved.
In a specific embodiment, the step S602 of obtaining the target style parameter of the first monitoring duration may include, as shown in fig. 5
S802, dividing the first monitoring time into a plurality of first time sections;
s804, determining an initial style parameter in each first time section; the initial style parameter is obtained according to a statistic value that the vehicle dynamic acceleration information in the first time section is within the first information range;
for example, if the first monitoring duration is 10min and the first time zone is 2min, 5 time zones are obtained by dividing, which is equivalent to 5 continuous and independent processes. And acquiring and processing the dynamic acceleration information of the vehicle in each first time section to determine the initial style parameters in each time section.
S806, obtaining the target style parameters according to all the initial style parameters;
specifically, the target style parameter may be obtained by performing a weighted averaging on all the initial style parameters. For example, after obtaining the initial style parameters of 5 time segments, taking the average value of the 5 initial style parameters as the final target style parameter; if the initial style parameters of the 5 time segments are 0.5, 0.62, 0.4, 0.3 and 0.78 respectively; the target style parameter derived from all the initial style parameters may be (0.5+0.62+0.4+0.3+ 0.78)/5-0.32
If the range of the target style parameter is [0-1], setting [0-a ] as a comfortable type, [ a-b ] as a steady type and [ b-1] as an aggressive type under the condition of three driving styles; if a is 0.3 and b is 0.6; then [0-0.3] is comfortable type, [0.3-0.6] is steady type, and [0.6-1] is aggressive type; under the condition that the result of the target style parameter is obtained through calculation, the corresponding driving style can be matched, and the grade of the driving style can be further determined.
In this embodiment, the first monitoring duration is refined into a plurality of time segments, and corresponding initial style parameters are sequentially obtained, so that more accurate target style parameters are obtained, and more appropriate target driving assistance parameters are matched.
In a specific embodiment, the step S804 determines the initial style parameter in each first time interval, as shown in fig. 6, which may include:
s1002, acquiring a first monitoring period, and determining the total number of times of cyclic monitoring according to the first time section and the first monitoring period;
s1004, counting a first count value in the first time section; the first counting value is the monitoring cycle number of the vehicle dynamic acceleration information within the first information range;
for example, if the first monitoring period is 20ms, 6000 loop monitoring will be performed in a first time period 2min long; and in each monitoring cycle, comparing the collected dynamic acceleration information of the vehicle with the first information range, and counting the times that the dynamic acceleration information of the vehicle is positioned in the first information range.
Specifically, in each monitoring cycle, if the vehicle dynamic acceleration information is within the first information range, the count value is increased by one; if the vehicle dynamic acceleration information is not in the first information range, no record is made; and then counting the monitoring cycle number of the vehicle dynamic acceleration information within the first information range.
S1006, obtaining the initial style parameter according to the first counting value and the total number of the monitoring cycles.
Wherein, the stronger the driving process, the more likely a larger longitudinal acceleration is generated; the lateral acceleration represents a dynamic parameter of the vehicle when the vehicle is controlled laterally, and can represent the driving style of a driver in the process of a curve; and during the process of over-bending driving, the greater the yaw velocity and the lateral acceleration generated by the vehicle, the more aggressive the driving process of the vehicle is indicated. Therefore, the vehicle dynamic acceleration information in this specification may include specific acceleration-related information such as longitudinal acceleration, lateral acceleration, and yaw rate, and the analysis of the driving style of the driver is performed by the longitudinal acceleration, lateral acceleration, yaw rate, and the like.
Correspondingly, counting the first count value, namely comparing the collected specific acceleration related information with corresponding preset information, and independently counting the count value and acquiring the specific style parameter.
In detail, taking the longitudinal acceleration as an example, the currently acquired longitudinal acceleration is compared with a preset longitudinal acceleration range, and the numerical values of all the acquired longitudinal accelerations within the preset longitudinal acceleration range in the first time segment are counted; and further dividing the count value corresponding to the longitudinal acceleration by the total number of monitoring cycles to obtain the specific style parameter corresponding to the longitudinal acceleration.
For example, the preset longitudinal acceleration range is 1.5m/S2-2.3m/S2(ii) a If the current longitudinal acceleration is 2.0m/S2，2.0m/S2At 1.5m/S2-2.3m/S2If so, adding one to the corresponding count value; if the count value corresponding to the longitudinal acceleration is 3000 times, the specific style parameter corresponding to the longitudinal acceleration is 3000/6000 ═ 0.5 when the total number of monitoring cycles is known to be 6000 times.
Likewise, a specific style parameter corresponding to the lateral acceleration and a specific style parameter corresponding to the yaw rate can be obtained. Further, weighting and normalizing the specific style parameter corresponding to the longitudinal acceleration, the specific style parameter corresponding to the lateral acceleration and the specific style parameter corresponding to the yaw rate to obtain the initial style parameter in the first time segment.
In this embodiment, the first time segment is further subdivided into a plurality of monitoring periods, and the initial style parameter is obtained according to the number of times that the dynamic acceleration information of the vehicle is located in the first information range in the first time segment; the accuracy of the target style parameters can be further improved.
In an actual scene, due to different road conditions of actual driving of a driver, style judgment results generated under different road conditions can generate deviation; in order to prevent frequent jump of the pre-judged driving style corresponding to the initial style parameters of the continuous time section, the result of the pre-judged driving style is corrected by introducing a forgetting factor; correspondingly:
in a possible implementation manner, step S806 calculates the target style parameter according to all the initial style parameters, as shown in fig. 7, and includes:
s1202, determining a forgetting factor corresponding to each initial style parameter;
in the case that the vehicle dynamic acceleration information includes specific acceleration-related information such as longitudinal acceleration, lateral acceleration, and yaw rate, the initial style parameter in the present embodiment may include a plurality of specific style parameters. Then, for an initial style parameter, the step of determining a forgetting factor corresponding to the initial style parameter may include:
(1) obtaining specific style parameters corresponding to the initial style parameters;
(2) determining the pre-judged driving style corresponding to each specific style parameter; the pre-judged driving style can be a pre-judged comfortable type, a pre-judged steady type and a pre-judged aggressive type;
(3) and obtaining a forgetting factor corresponding to the initial style parameter according to the pre-judged driving style.
After determining the pre-judged driving style corresponding to each specific style parameter, obtaining the forgetting factor corresponding to the initial style parameter according to the pre-judged driving style, which may include:
(31) acquiring a comparison table of pre-judged driving style and pre-judged style grade; determining a pre-judging style grade corresponding to the pre-judging driving style according to the comparison table; for example, the pre-judgment style grades corresponding to the pre-judgment comfort type, the pre-judgment robust type and the pre-judgment aggressive type are 1, 2 and 3 respectively.
(32) Performing normalization processing on the obtained pre-judging style grade to obtain an intermediate style parameter;
for example, if the pre-judgment style level corresponding to the longitudinal acceleration is 3, the pre-judgment style level corresponding to the lateral acceleration is 2, and the pre-judgment style level corresponding to the pre-judgment aggressive type is 3, the intermediate style parameter is further obtained through normalization processing:
(33) and acquiring a comparison table of the intermediate style parameter and the forgetting factor, and determining the forgetting factor corresponding to the intermediate style parameter, namely the forgetting factor corresponding to the initial style parameter according to the comparison table.
In this embodiment, there are three corresponding forgetting factors, such as λ 1, λ 2, and λ 3, and the range of the forgetting factor is [0-1 ].
If the first preset style parameter is 0.3 and the second preset style parameter is 0.6, when the intermediate style parameter a1 is [0-0.3], the pre-judged driving style is a pre-judged comfortable type, and the corresponding forgetting factor is lambda 1 after further matching; when the intermediate style parameter a2 is located at [0.3-0.6], the pre-judged driving style is a pre-judged robust type, and a corresponding forgetting factor is obtained through further matching and is lambda 2; when the intermediate style parameter a3 is greater than 0.6, the pre-judged driving style is a pre-judged aggressive type, and a corresponding forgetting factor is further obtained by matching and is lambda 3.
In detail, determining the pre-judged driving style corresponding to each specific style parameter includes:
(21) comparing each specific style parameter with a first preset style parameter q1 and a second preset style parameter q 2;
(22) when the specific style parameter is smaller than a first preset style parameter q1, the pre-judged driving style is a pre-judged comfortable type; when the specific style parameter is greater than a first preset style parameter q1 and less than a second preset style parameter q2, the pre-judged driving style is a pre-judged robust type; and when the specific style parameter is greater than a second preset style parameter q2, the pre-judged driving style is a pre-judged aggressive type. For example, if q1 is 0.005 and q2 is 0.013 and the obtained specific style parameter is 0.011, it is possible to obtain that the predicted driving style is the predicted robust type.
It should be noted that the parameters mentioned in the present specification are not limited to a certain numerical value in the example, and may be set as needed.
S1204, calculating to obtain the target style parameters according to each initial style parameter and the corresponding forgetting factor.
Specifically, in the case that 5 first time segments are obtained by dividing, corresponding to 5 initial style parameters (such as a1, a2, a3, a4, a5), each initial style parameter is multiplied by a corresponding forgetting factor (such as λ 1, λ 2, λ 3, λ 2, λ 1), and all the products are summed; further averaging the summed results to obtainThe target style parameter Des(ii) a As shown in equation one:
Des＝(a1*λ1+a2*λ2+a3*λ3+a4*λ2+a5*λ1)/5
in this embodiment, each initial style parameter is corrected by introducing a forgetting factor, so as to avoid the problem that the deviation of adjacent initial style parameters is too large due to different road conditions, and further improve the accuracy of the target style parameter and the robustness and stability of the auxiliary driving control function.
In one embodiment, the step S404 of determining the driving ability level from the vehicle dynamic deceleration information may include, as shown in fig. 8:
s1402, acquiring a target capacity parameter of a second monitoring duration; the target capacity parameter is obtained according to a statistical value of the dynamic vehicle deceleration information in the second monitoring duration within a second information range;
s1404, obtaining the driving ability grade according to the target ability parameters.
Specifically, the second monitoring time is the time for acquiring the vehicle dynamic deceleration information of the vehicle controller; and the vehicle controller compares the collected dynamic vehicle deceleration information with a second information range, counts the times that the dynamic vehicle deceleration information in the second monitoring duration is in the second information range, and further obtains the target capacity parameter.
It should be noted that the second monitoring duration may be set according to a requirement, and is not limited to a certain value; in addition, the second monitoring duration may be the same as the first monitoring duration, for example, both the second monitoring duration and the first monitoring duration are 10min, and the driver can simultaneously acquire the vehicle dynamic acceleration information and the vehicle dynamic deceleration information within 10min of free driving, so as to save the time required for obtaining the target driving assistance parameter.
In a specific embodiment, the step S1402 obtains the target capability parameter of the second monitoring duration, as shown in fig. 9, which may include:
s1602, dividing the second monitoring time into a plurality of second time sections;
s1604, determining initial capacity parameters in each second time zone; the initial capacity parameter is obtained according to a statistic value that the vehicle dynamic deceleration information in the second time section is within the second information range;
and S1606, obtaining the target capability parameter according to all the initial capability parameters.
It should be noted that, in this embodiment, the process of dividing the time segment and obtaining the target capability parameter may refer to the related content of the target style parameter.
In a specific embodiment, the step S1604 determines the initial capability parameter in each second time zone, as shown in fig. 10, which may include:
s1802, acquiring a second monitoring period, and determining the total number of monitoring cycles according to the second time section and the second monitoring period;
s1804, counting a second count value in the second time section; the second counting value is the monitoring cycle number of the vehicle dynamic deceleration information in the second information range;
s1806, obtaining the initial capacity parameter according to the second count value and the total number of monitoring cycles.
Among them, inexperienced drivers often have inexperienced driving experience, are not skilled in vehicle operation, are not in place, and often generate braking force exceeding the expectation or large longitudinal deceleration during braking, so that the longitudinal deceleration can be taken as a factor for considering the driving ability; in addition, when a driver operates the vehicle longitudinally, the vehicle generates different longitudinal impact degrees due to different capabilities; and the driver can make the vehicle have different steering wheel rotating speeds due to different capabilities when the driver controls the vehicle in the transverse direction. Among them, the more powerful the driver is, the smoother the differential of the deceleration corresponding to the longitudinal jerk at the time of the longitudinal operation is, and the relatively linear differential of the steering wheel angular velocity at the time of the lateral control is. Therefore, the vehicle dynamic deceleration information in the present specification may include specific deceleration-related information such as a longitudinal deceleration, a lateral impact, and a steering wheel angular velocity, and the driving ability of the driver is analyzed by the longitudinal deceleration, the lateral impact, and the steering wheel angular velocity.
Correspondingly, counting the second counting value, namely comparing the collected specific deceleration related information with corresponding preset information, and independently counting the counting value and acquiring specific capability parameters.
It should be noted that, in this embodiment, the content of the monitoring period and the process of obtaining the initial capability parameter may refer to the content related to the initial style parameter.
In an actual scene, due to the fact that the road conditions of actual driving of a driver are different, the capacity judgment results generated under different road conditions can generate deviation; in order to prevent frequent jump of the pre-judged driving capacity corresponding to the initial capacity parameter of the continuous time section, the result of the pre-judged driving capacity is corrected by introducing a forgetting factor; therefore, correspondingly:
in a possible implementation manner, the step S1806 calculates the target performance parameter according to all the initial performance parameters, as shown in fig. 11, and may include:
s2002, determining a forgetting factor corresponding to each initial capacity parameter;
and S2004, calculating to obtain the target capability parameters according to each initial capability parameter and the corresponding forgetting factor.
It should be noted that, in this embodiment, a forgetting factor corresponding to each initial capability parameter is determined, and processing may also be performed according to a manner of determining a forgetting factor corresponding to an initial style parameter; specifically, the forgetting factor corresponding to the initial capability parameter is obtained by obtaining a specific capability parameter, a pre-judged driving capability, a pre-judged capability grade and an intermediate capability parameter.
For example, in the case that there are 5 initial capability parameters (such as b1, b2, b3, b4, b5) corresponding to 5 second time zones obtained by dividing, each initial capability parameter is multiplied by a corresponding forgetting factor (such as μ 1, μ 2, μ 3, μ 1), and the multiplied initial capability parameters are multiplied by the forgetting factorSumming the products of some; further averaging the summation result to obtain the target capability parameter Del(ii) a As shown in equation two:
Del＝(b1*μ1+b2*μ2+b3*μ3+b4*μ3+b5*μ1)/5
in this embodiment, each initial capability parameter is corrected by introducing a forgetting factor, so as to avoid the problem that the deviation of adjacent initial capability parameters is too large due to different road conditions, and further improve the accuracy of the target capability parameter and the robustness and stability of the auxiliary driving control function.
As shown in fig. 12, a schematic flow chart of obtaining the target style parameter is given under the conditions that the first monitoring duration is 10min and the first time zone is 2 min; as shown in fig. 13, a schematic flow chart of obtaining the target capacity parameter is given under the condition that the second monitoring time period is 10min and the second time zone is 2 min.
It should be noted that the vehicle dynamic acceleration information and the vehicle dynamic deceleration information in the embodiments of the present specification are not limited to the specific information mentioned in the present specification, and may be other information that can be used for sensitively sensing and characterizing the driving style and driving ability of the driver.
As shown in fig. 14, the present specification provides a vehicle driving assist control apparatus, including:
a vehicle-related information obtaining module 202, configured to obtain vehicle-related information, where the vehicle-related information includes vehicle dynamic acceleration information and vehicle dynamic deceleration information;
a driver type determination module 204 for determining a driver type from the vehicle-related information;
a target assistant driving parameter obtaining module 206, configured to obtain a target assistant driving parameter according to the driver type;
and the driving assistance control module 208 is used for performing driving assistance on the vehicle based on the target driving assistance parameter.
In a specific embodiment, the driver type determination module may include:
the style grade determining submodule is used for determining the driving style grade according to the dynamic acceleration information of the vehicle;
the capability level determining submodule is used for determining the driving capability level according to the dynamic deceleration information of the vehicle;
and the driver type obtaining submodule is used for obtaining the driver type according to the driving style grade and the driving ability grade.
In one embodiment, the style level determination submodule may include:
the target style parameter acquisition unit is used for acquiring a target style parameter of the first monitoring duration; the target style parameters are obtained according to a statistic value that the vehicle dynamic acceleration information in the first monitoring duration is within a first information range;
and the style grade determining unit is used for obtaining the driving style grade according to the target style parameter.
In one embodiment, the target style parameter obtaining unit may include:
a first time zone dividing subunit, configured to divide the first monitoring duration into a plurality of first time zones;
an initial style parameter determining subunit, configured to determine an initial style parameter in each first time segment; the initial style parameter is obtained according to a statistic value that the vehicle dynamic acceleration information in the first time section is within the first information range;
and the target style parameter obtaining subunit is used for obtaining the target style parameters according to all the initial style parameters.
In one embodiment, the initial style parameter determining subunit may include:
the first total number acquiring subunit is used for acquiring a first monitoring period and determining the total number of cyclic monitoring according to the first time section and the first monitoring period;
a first count counting subunit, configured to count a first count value in the first time segment; the first counting value is the monitoring cycle number of the vehicle dynamic acceleration information within the first information range;
and the initial style parameter obtaining subunit is configured to obtain the initial style parameter according to the first count value and the total number of monitoring cycles.
In one embodiment, the target style parameter deriving subunit may include:
the first forgetting factor determining subunit is used for determining a forgetting factor corresponding to each initial style parameter;
and the target style parameter calculating subunit is used for calculating to obtain the target style parameters according to each initial style parameter and the corresponding forgetting factor.
In a possible implementation, the capability level determination sub-module may include:
the target capacity parameter acquiring unit is used for acquiring a target capacity parameter of the second monitoring duration; the target capacity parameter is obtained according to a statistical value of the dynamic vehicle deceleration information in the second monitoring duration within a second information range;
and the driving ability grade obtaining unit is used for obtaining the driving ability grade according to the target ability parameter.
In a specific embodiment, the target capability parameter obtaining unit may include:
a second time zone dividing subunit, configured to divide the second monitoring duration into a plurality of second time zones;
an initial capacity parameter determining subunit, configured to determine an initial capacity parameter in each second time segment; the initial capacity parameter is obtained according to a statistic value that the vehicle dynamic deceleration information in the second time section is within the second information range;
and the target capability parameter obtaining subunit is used for obtaining the target capability parameters according to all the initial capability parameters.
In one embodiment, the initial capability parameter determining subunit may include:
a second total number obtaining subunit, configured to obtain a second monitoring period, and determine a total number of monitoring cycles according to the second time segment and the second monitoring period;
the second secondary counting subunit is used for counting a second counting value in the second time section; the second counting value is the monitoring cycle number of the vehicle dynamic deceleration information in the second information range;
and the initial capacity parameter obtaining subunit is configured to obtain the initial capacity parameter according to the second count value and the total number of monitoring cycles.
In one embodiment, the target capability parameter obtaining subunit may include:
the second forgetting factor determining subunit is used for determining a forgetting factor corresponding to each initial capability parameter;
and the target capability parameter calculating subunit is used for calculating to obtain the target capability parameters according to each initial capability parameter and the corresponding forgetting factor.
In detail, the vehicle dynamic acceleration information includes a longitudinal acceleration, a lateral acceleration, and a yaw rate; the vehicle dynamic deceleration information includes a longitudinal deceleration, a lateral impact, and a steering wheel angular velocity.
It is to be noted that the embodiments of the apparatus presented in this description have the same inventive concept as the corresponding embodiments of the method described above.
The present specification embodiments provide an apparatus, which may be an entire controller of a vehicle, including a processor and a memory, where at least one instruction, at least one program, a set of codes, or a set of instructions is stored in the memory, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by the processor to implement the vehicle driving assistance control method according to the above method embodiments.
The present specification further provides a computer storage medium, which may be disposed in an apparatus to store at least one instruction, at least one program, a code set, or a set of instructions related to implementing a vehicle assistant driving control method in the method embodiments, where the at least one instruction, the at least one program, the code set, or the set of instructions is loaded and executed by the processor to implement the vehicle assistant driving control method provided by the above method embodiments.
Optionally, in this embodiment, the storage medium may be located in at least one network device of a plurality of network devices of a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, which can store program codes.
It should be noted that: the sequence of the embodiments in this specification is merely for description, and does not represent the advantages or disadvantages of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the acts or steps loaded in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the device and server embodiments, since they are substantially similar to the method embodiments, the description is simple, and the relevant points can be referred to the partial description of the method embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc. Also, modules in the device in the embodiment may be adaptively changed and set in one or more devices different from the embodiment; the modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (14)
1. A vehicle driving assist control method, characterized by comprising:
acquiring vehicle-related information, wherein the vehicle-related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information;
determining a driver type from the vehicle-related information;
obtaining target auxiliary driving parameters according to the driver type;
and performing auxiliary driving on the vehicle based on the target auxiliary driving parameter.
2. The vehicle-driving assistance control method according to claim 1, wherein the determining a driver type from the vehicle-related information includes:
determining a driving style grade according to the vehicle dynamic acceleration information;
determining the driving capacity grade according to the dynamic vehicle deceleration information;
and obtaining the driver type according to the driving style grade and the driving ability grade.
3. The vehicle-driving assistance control method according to claim 2, wherein the determining a driving style level from the vehicle dynamic acceleration information includes:
acquiring a target style parameter of a first monitoring duration; the target style parameters are obtained according to a statistic value that the vehicle dynamic acceleration information in the first monitoring duration is within a first information range;
and obtaining the driving style grade according to the target style parameter of the first monitoring duration.
4. The vehicle driving assist control method according to claim 3, wherein the acquiring the target style parameter for the first monitored duration includes:
dividing the first monitoring duration into a plurality of first time sections;
determining an initial style parameter in each first time section; the initial style parameter is obtained according to a statistic value that the vehicle dynamic acceleration information in the first time section is within the first information range;
and obtaining the target style parameters of the first monitoring duration according to all the initial style parameters.
5. The vehicle-assisted driving control method according to claim 4, wherein the determining of the initial style parameter in each first time segment comprises:
acquiring a first monitoring period, and determining the total number of cyclic monitoring according to the first time section and the first monitoring period;
counting a first count value in the first time section; the first counting value is the monitoring cycle number of the vehicle dynamic acceleration information within the first information range;
and obtaining the initial style parameter according to the first counting value and the total number of the monitoring cycles.
6. The vehicle driving assist control method according to claim 4, wherein the calculating the target style parameter from all the initial style parameters includes:
determining a forgetting factor corresponding to each initial style parameter;
and calculating to obtain the target style parameters according to each initial style parameter and the corresponding forgetting factor.
7. The vehicle-driving-assist control method according to claim 2, wherein the determining a driving ability level from the vehicle dynamic deceleration information includes:
acquiring a target capacity parameter of a second monitoring duration; the target capacity parameter is obtained according to a statistical value of the dynamic vehicle deceleration information in the second monitoring duration within a second information range;
and obtaining the driving capacity grade according to the target capacity parameter of the second monitoring time length.
8. The vehicle driving assist control method according to claim 7, wherein the acquiring the target capability parameter for the second monitoring period includes:
dividing the second monitoring duration into a plurality of second time sections;
determining an initial capacity parameter in each second time segment; the initial capacity parameter is obtained according to a statistic value that the vehicle dynamic deceleration information in the second time section is within the second information range;
and obtaining the target capacity parameter of the second monitoring duration according to all the initial capacity parameters.
9. The vehicle driving assist control method according to claim 8, wherein the determining an initial capability parameter in each second time zone includes:
acquiring a second monitoring period, and determining the total number of monitoring cycles according to the second time section and the second monitoring period;
counting a second count value in the second time section; the second counting value is the monitoring cycle number of the vehicle dynamic deceleration information in the second information range;
and obtaining the initial capacity parameter according to the second counting value and the total number of the monitoring cycles.
10. The vehicle driving assist control method according to claim 8, wherein the calculating the target ability parameter from all the initial ability parameters includes:
determining a forgetting factor corresponding to each initial capacity parameter;
and calculating to obtain the target capability parameter according to each initial capability parameter and the corresponding forgetting factor.
11. The vehicle driving assist control method according to any one of claims 1 to 10,
the vehicle dynamic acceleration information comprises longitudinal acceleration, lateral acceleration and yaw rate;
the vehicle dynamic deceleration information includes a longitudinal deceleration, a lateral impact, and a steering wheel angular velocity.
12. A vehicle driving assist control apparatus, characterized by comprising:
the vehicle-related information acquisition module is used for acquiring vehicle-related information, wherein the vehicle-related information comprises vehicle dynamic acceleration information and vehicle dynamic deceleration information;
a driver type determination module for determining a driver type from the vehicle-related information;
the target auxiliary driving parameter obtaining module is used for obtaining target auxiliary driving parameters according to the type of the driver;
and the driving assistance control module is used for performing driving assistance on the vehicle based on the target driving assistance parameters.
13. An apparatus comprising a processor and a memory having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions that is loaded and executed by the processor to implement the vehicle assisted driving control method of any of claims 1-11.
14. A computer readable storage medium having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions, which is loaded and executed by a processor to implement a vehicle assisted driving control method as claimed in any one of claims 1 to 11.
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