CN117549903A

CN117549903A - Automobile driving control method, computer device and storage medium

Info

Publication number: CN117549903A
Application number: CN202311806272.6A
Authority: CN
Inventors: 吴秀冰; 陈海旋; 刘小锐; 冯锡泽; 李志涛
Original assignee: GAC Honda Automobile Co Ltd; Guangqi Honda Automobile Research and Development Co Ltd
Current assignee: GAC Honda Automobile Co Ltd; Guangqi Honda Automobile Research and Development Co Ltd
Priority date: 2023-12-26
Filing date: 2023-12-26
Publication date: 2024-02-13

Abstract

The invention discloses an automobile driving control method, a computer device and a storage medium. The invention can realize real-time monitoring of the current driving, quantitatively evaluate the safety risk of the current driving, and timely intervene in the current driving process when the safety risk is overlarge, thereby being beneficial to avoiding the expansion of the safety risk or reducing the safety risk and further ensuring the traffic safety. The invention is widely applied to the technical field of automobiles.

Description

Automobile driving control method, computer device and storage medium

Technical Field

The invention relates to the technical field of automobiles, in particular to an automobile driving control method, a computer device and a storage medium.

Background

Currently, quite a few owners often give their cars to others for use, e.g. multiple people in a family drive the same car at different times. Among a plurality of users of the same automobile, some users may be relatively easy to make irregular or even wrong driving operations due to short driving age, insufficient familiarity with the performance of the automobile and the like, so that a great safety risk is faced. For example, a car owner of a car owned by a family is a long lifetime with rich driving experience and high driving skill, and the car may give to the lifetime driving with the driving license just acquired, and when the car owner does not guide on the car, the lifetime is more likely to be stressed or violent driving due to independent driving, and irregular driving operations such as solid line lane changing, turning without turning lights are performed, and even traffic accidents occur.

Disclosure of Invention

Aiming at the technical problems that partial users possibly do irregular driving operations when driving an automobile in the prior automobile technology so as to face safety risks and the like, the invention aims to provide an automobile driving control method, a computer device and a storage medium.

In one aspect, an embodiment of the present invention includes a method for controlling driving of an automobile, including the steps of:

acquiring a safe driving strategy parameter;

detecting current driving action parameters;

determining current driving risk data by comparing the safe driving strategy parameters with the current driving action parameters;

and when the current driving risk data reaches a risk threshold, intervention in a current driving process is performed according to the safe driving strategy parameters.

Further, the acquiring the safe driving strategy parameter includes:

setting a plurality of driving action types;

and setting corresponding threshold values for the driving action types respectively, so as to obtain the safe driving strategy parameters.

Further, the setting the respective threshold value for each driving action type includes:

and setting a corresponding fixed value for any driving action type as a corresponding threshold value of the driving action type.

Further, the detecting the current driving action parameter includes:

carrying out identity recognition on the current driver;

when the current driver is determined to be a first target person, a sensor is called, otherwise, the current time is detected;

when the current time is determined to belong to the target time period, calling a sensor;

and detecting by using the called sensors and taking the driving action types as detection targets respectively to obtain the current driving action parameters corresponding to the driving action types.

under the driving guidance state, invoking a sensor, and respectively detecting by taking each driving action type as a detection target to obtain each corresponding historical driving action parameter of each driving action type; the driving instruction state is a state that the first target person drives the automobile and the second target person gets on the automobile;

detecting voice information of the second target person;

carrying out semantic analysis on the voice information to obtain driving instruction information;

respectively carrying out correlation detection on each driving action type and the driving instruction information;

For any driving action type, when the driving action type is related to the driving instruction information, adjusting the historical driving action parameters corresponding to the driving action type according to the driving instruction information, so as to obtain a corresponding threshold value of the driving action type; and when the driving action type is not related to the driving instruction information, determining a corresponding threshold value of the driving action type according to the historical driving action parameter corresponding to the driving action type.

Further, the determining the current driving risk data by comparing the safe driving strategy parameter with the current driving action parameter includes:

determining parameter similarity according to all the safe driving strategy parameters corresponding to all the driving action types and all the current driving action parameters corresponding to all the driving action types;

and for any driving action type, determining a difference value between the safe driving strategy parameter corresponding to the driving action type and the current driving action parameter, and adjusting the difference value according to the parameter similarity to obtain the current driving risk data corresponding to the driving action type.

Further, when the current driving risk data reaches a risk threshold, according to the safe driving strategy parameter, the current driving process is intervened, including:

for any driving action type, setting a risk threshold corresponding to the driving action type, and determining the current driving risk data corresponding to the driving action type, wherein the risk excess amount of the current driving risk data is relative to the corresponding risk threshold;

and for any driving action type, according to the corresponding risk excess, performing intervention on the driving action corresponding to the driving action type in the current driving process.

Further, the step of performing intervention on the driving action corresponding to the driving action type in the current driving process according to the corresponding risk excess amount comprises the following steps:

when the risk exceeding amount reaches a first interval, generating a site warning instruction; the on-site warning instruction is used for instructing an automobile part to send out a warning;

when the risk exceeding amount reaches a second interval, generating a feedback control instruction; the feedback control instruction is used for instructing an automobile part corresponding to the driving action type to generate feedback force corresponding to the safe driving strategy parameter;

When the risk excess reaches a third interval, establishing a communication connection line between the local server and the remote server of the automobile;

and when the risk excess reaches a fourth interval, switching the automobile from a field manual driving mode to an automatic driving mode or a remote manual driving mode, wherein the automatic driving mode executes automatic driving according to the safe driving strategy parameters.

In another aspect, an embodiment of the present invention further includes a computer apparatus including a memory for storing at least one program and a processor for loading the at least one program to perform a method of controlling driving of an automobile in the embodiment.

In another aspect, embodiments of the present invention further include a storage medium having stored therein a processor-executable program which, when executed by a processor, is for performing a method of controlling driving of an automobile in the embodiments.

The beneficial effects of the invention are as follows: according to the automobile driving control method, real-time monitoring of current driving can be achieved, safety risks facing the current driving can be quantitatively evaluated, when the safety risks are too large, the current driving process is intervened in time, the safety risks are prevented from being enlarged or reduced, and accordingly traffic safety is guaranteed.

Drawings

FIG. 1 is a schematic diagram of an automotive system to which an automotive driving control method may be applied in an embodiment;

FIG. 2 is a schematic diagram illustrating steps of a method for controlling driving of an automobile according to an embodiment;

fig. 3 is a flow chart of an automobile driving control method in an embodiment.

Detailed Description

In this embodiment, the driving control method may be applied to the automobile system shown in fig. 1. Referring to fig. 1, the system includes components such as a vehicle-mounted controller, a distance sensing module, a speed sensing module, a component sensing module, a person sensing module, a man-machine interaction module, a communication module, a manual driving module, and an automatic driving module. The vehicle-mounted controller can be an electronic control unit ECU or a whole vehicle control unit VCU; the distance sensing module can detect information such as the position of the vehicle, the distance between the vehicle and the front and rear vehicles, the distance between the vehicle and the side vehicle or the distance between the vehicle and the nearby lane based on the principles of ultrasonic detection, laser detection or satellite positioning; the speed sensing module can detect the speed information such as the running speed, the running acceleration and the engine speed of the vehicle; the component sensing module can detect whether automobile components such as a steering wheel, a steering lamp, a vehicle window, a windscreen wiper and the like work or not, and component work information such as a steering angle of the steering wheel, a direction of the steering lamp, opening degrees of the vehicle window and the windscreen wiper and the like; the personnel sensing module can be used for carrying out identity recognition, expression recognition, gesture recognition, drunk state recognition and the like on personnel taking in a driver seat, a passenger seat and the like in an automobile cabin; the man-machine interaction module can provide man-machine interaction interfaces such as a touch screen, keys, a knob, light or sound for personnel on the vehicle, so that the personnel on the vehicle can interact with the vehicle-mounted controller; the communication module is connected with the remote server through wireless communication protocols such as 5G and the like, so that the vehicle can perform data interaction with the remote server; the manual driving module comprises a power system, a transmission system, a braking system and other automobile parts, and an onboard person of the automobile can drive the automobile by operating the manual driving module; the automatic driving module also comprises automobile components such as an automatic driving controller, a power system, a transmission system, a braking system and the like, and the automatic driving controller runs an automatic driving control program and outputs control instructions to the power system, the transmission system, the braking system and the like so as to replace manual driving of the automobile.

In this embodiment, the vehicle-mounted controller has functions of data acquisition, processing, storage, transmission and the like. When the vehicle-mounted controller executes each step in the vehicle driving control method, the vehicle-mounted controller can read data from a storage space of the vehicle-mounted controller or call each module such as a distance sensing module to acquire the data when the data is required to be acquired for processing; the data or instructions obtained after the data processing by the vehicle-mounted controller can be stored in a storage space of the vehicle-mounted controller or sent to each module such as the communication module, the manual driving module and the automatic driving module, so that the data output is realized or the communication module, the manual driving module and the automatic driving module are controlled.

In this embodiment, unless otherwise specified, "cars" referred to in different places all refer to the same car.

In this embodiment, referring to fig. 2, the automobile driving control method includes the steps of:

s1, acquiring a safe driving strategy parameter;

s2, detecting current driving action parameters;

s3, determining current driving risk data by comparing the safe driving strategy parameters with current driving action parameters;

s4, when the current driving risk data reaches a risk threshold value, intervention is performed in the current driving process according to the safe driving strategy parameters.

In step S1, the obtained safe driving strategy parameter may be used as a reference value to perform risk assessment on the current driving action parameter obtained in step S2. When executing step S2, the vehicle-mounted controller may invoke the distance sensing module, the speed sensing module, the component sensing module, and the personnel sensing module, so as to detect the working state of the whole vehicle, the working state of some components on the vehicle, and/or the state of personnel on the vehicle, thereby obtaining the current driving action parameters such as the running speed of the vehicle, the running acceleration of the vehicle, the depth of the accelerator pedal, the rotation speed of the engine, the steering angle of the steering wheel, the distance from the solid line, the using state of the steering lamp, the emotional state of the driver, the drunk state of the driver, and the like.

In this embodiment, when step S1, that is, the step of acquiring the safe driving strategy parameter, the following steps may be specifically performed:

s101, setting a plurality of driving action types;

s102, setting corresponding thresholds for each driving action type respectively, and thus obtaining safe driving strategy parameters.

In step S101, a driving action type corresponding to the safe driving policy parameter to be collected may be set according to the type of the current driving action parameter to be detected in step S2. For example, when step S2 is executed, the current values of the respective types may be collected according to the types of the vehicle running speed, the vehicle running acceleration, the accelerator pedal depth, the engine speed, the steering angle of the steering wheel, the distance from the solid line, the usage state of the steering lamp, the emotional state of the driver, the drunk state of the driver, and the like, so as to form the current driving operation parameters, so that in step S101, the driving operation types such as "the vehicle running speed", "the vehicle running acceleration", "the accelerator pedal depth", "the engine speed", "the steering angle of the steering wheel", "the distance from the solid line", "the usage state of the steering lamp", "the emotional state of the driver", and the drunk state of the driver, may be set, and in step S102, the corresponding threshold value may be set for each driving operation type, so as to form the safe driving strategy parameters.

By executing steps S101-S102, the obtained safe driving strategy parameters have the format shown in table 1.

Table 1 format of safe driving strategy parameters

Type of driving action	Threshold value
		Speed of travel of automobile	threshold ₁
Acceleration of automobile running	threshold ₂
		Depth of accelerator pedal	threshold ₃
Engine speed	threshold ₄
		Steering angle of steering wheel	threshold ₅
Distance from solid line	threshold ₆
		Steering lamp use state	threshold ₇
Driver emotional state	threshold ₈
		Drunk state of driver	threshold ₉

In step S2, the vehicle-mounted controller uses each driving action type identical to the safe driving strategy parameter as a detection target, and invokes the corresponding sensor to detect, and the obtained actual measurement values of each driving action type form the current driving action parameter. For example, the in-vehicle controller calls the speed sensing module to detect "car running speed", "car running acceleration", and "car running acceleration" with each driving action type shown in table 1 as a detection targetActual measurement value detection of driving operation type such as "engine speed ₁ 、detection ₂ Detection of ₄ Calling a component sensing module to detect actual measurement value detection of driving action types such as accelerator pedal depth, steering angle of steering wheel, use state of steering lamp and the like ₃ 、detection ₅ Detection of ₇ Calling a distance sensing module to detect the actual measurement value detection of the driving action types such as distance from the solid line ₆ Invoking a personnel sensing module to detect actual measurement value detection of driving action types such as ' driver emotion state ' and ' driver drunk state ₈ Detection of ₉ 。

By executing step S2, the obtained current driving action parameters have the format shown in table 2.

Table 2 format of current driving action parameters

In this embodiment, the safe driving strategy parameters shown in table 1 and the current driving action parameters shown in table 2 have the same format, and a comparison of magnitude relation or other relations can be performed. The driving behavior of the driver with the style of safety, stability and the like can be detected under the laboratory condition or the standard safe driving condition, and the value of each driving action type is measured, so that the safe driving strategy parameters are formed, the safe driving strategy parameters shown in the table 1 can be used as the reference data representing the standard safe driving state, and the current driving action parameters shown in the table 2 are the value of each actually measured driving action type in a certain actual driving process and represent the quantification result of the driving action of the driver in the actual driving process.

The driving action of the driver in the actual driving process can be determined by comparing the safe driving strategy parameters shown in table 1 with the current driving action parameters shown in table 2, and the deviation degree between the safe driving state and the standard safe driving state can be quantitatively evaluated, so that the risk of the driving action of the driver in the actual driving process can be quantitatively evaluated. Based on the above principle, in step S3, the safe driving strategy parameters shown in table 1 and the current driving action parameters shown in table 2 are compared and calculated, so as to obtain the current driving risk data. The current driving risk data can represent the safety risk faced by the driving action of the driver in the actual driving process.

And when the vehicle-mounted controller executes the step S4, comparing the current driving risk data with a preset risk threshold, and controlling other modules to intervene in the current driving process according to the safe driving strategy parameters when the vehicle-mounted controller detects that the current driving risk data is larger than the risk threshold.

In this embodiment, steps S1-S4 may be applied to the following scenarios:

1. the driving technology of the car owner of the car is good, the car can be used by a family member of the car owner, and the driving technology level of the family member is inferior to that of the car owner, when the step S1 is executed, the car owner can be used as a second target person, according to the actual driving process of the second target person, the safety driving strategy parameters are set for the vehicle-mounted controller, or the vehicle-mounted controller obtains standard data measured in environments such as a laboratory from a traffic management department and the like, so that the safety driving strategy parameters are set; when a family member of a vehicle owner drives a vehicle, the family member serves as a first target person in the embodiment, the vehicle-mounted controller executes step S2 to detect and obtain current driving action parameters generated by the first target person, namely the family member drives the vehicle, and the vehicle-mounted controller executes steps S3-S4 to intervene in the driving process of the family member under the condition that the driving of the family member is judged to have a large risk, so that the driving safety risk of the family member is prevented from being enlarged or reduced.

2. The second target person, namely the vehicle owner has good driving technology, but the driving technology of the vehicle owner may fluctuate, for example, in the evening or under the condition of fatigue of the vehicle owner, the driving technology of the vehicle owner may be worse than usual, the vehicle owner does not give the vehicle to other family members for use, but the vehicle owner hopes that when the driving technology of the vehicle owner is at a lower level, the vehicle owner can correct the driving operation of the vehicle owner, when the step S1 is executed, the vehicle owner can serve as the second target person, according to the actual driving process of the second target person in the good state of the driving technology of the vehicle owner, thereby setting safe driving strategy parameters to the vehicle-mounted controller, or the vehicle-mounted controller obtains standard data measured in the environment of a laboratory and the like from a traffic management department and the like, thereby setting the safe driving strategy parameters; and when the vehicle owner drives the vehicle later, the vehicle-mounted controller executes the step S2 to detect and obtain the current driving action parameters generated by the vehicle owner driving the vehicle, and the vehicle-mounted controller executes the steps S3-S4 to intervene in the driving process of the vehicle owner under the condition that the driving of the vehicle owner is judged to have a large risk, so that the safety risk of the driving of the vehicle owner is prevented from being enlarged or the safety risk is reduced.

According to the scene, through executing the steps S1-S4, the real-time monitoring of the current driving can be realized, the safety risk faced by the current driving can be quantitatively evaluated, and when the safety risk is overlarge, the current driving process is timely intervened, so that the expansion of the safety risk or the reduction of the safety risk can be avoided, and the traffic safety is guaranteed.

In this embodiment, when step S102 is performed, that is, the step of setting the corresponding threshold value for each driving action type, the following steps may be specifically performed:

and S10201A, setting a corresponding fixed value for any driving action type as a corresponding threshold value of the driving action type.

Step S10201A is a first implementation of step S102.

In the execution of step S10201A, the threshold may be set for each driving operation type such as "vehicle running speed", "vehicle running acceleration", "accelerator pedal depth" … …, etc., referring to table 1 ₁ 、threshold ₂ 、threshold ₃ … …, etc., as the corresponding threshold value.

By executing step S10201A, the safe driving strategy parameters can be set according to the steps such as experimental conditions, thereby being beneficial to standardization of driving style, and guiding the driver with lower driving skill level to improve his driving skill level according to the specifications.

S10201B, calling a sensor in a driving instruction state, and respectively detecting by taking each driving action type as a detection target to obtain historical driving action parameters corresponding to each driving action type; the driving instruction state is a state that a first target person drives an automobile and a second target person gets on the automobile;

S10202B, detecting voice information of a second target person;

S10203B, carrying out semantic analysis on the voice information to obtain driving instruction information;

S10204B, respectively carrying out correlation detection on each driving action type and driving instruction information;

S10205B, for any driving action type, when the driving action type is related to the driving instruction information, adjusting historical driving action parameters corresponding to the driving action type according to the driving instruction information, so as to obtain a corresponding threshold value of the driving action type; when the driving action type is not related to the driving instruction information, determining a corresponding threshold value of the driving action type according to the historical driving action parameters corresponding to the driving action type.

Steps S10201B-S10205B are a second implementation of step S102. The time period for the in-vehicle controller to perform steps S10201B-S10205B may differ from the time period for performing steps S2-S4, etc. by a longer time. For example, the in-vehicle controller may store the respective threshold values in its own storage space after performing steps S10201B-S10205B, and recall the respective threshold values when steps S2-S4 are performed after days, weeks, months, or even years, so as to obtain the safe driving strategy parameters to be used for performing steps S2-S4.

The "driving instruction state" in steps S10201B-S10205B includes the following cases: the first target person with lower driving skill level drives the automobile in the driving seat, the second target person with higher driving skill level rides in the co-driving position and the like, and the second target person accompanies and guides the first target person to drive.

Before executing steps S10201B-S10205B, the first target person or the second target person may operate through the human-computer interaction module to confirm that the first target person is currently driving the vehicle, and that the second target person is already sitting in a co-driver or the like, thereby confirming that the driving instruction state is currently performed.

In step S10201B, in the driving instruction state, the vehicle-mounted controller invokes the sensor to detect each driving action type as a detection target, and obtains the historical driving action parameters corresponding to each driving action type. That is, the detection may be performed with reference to the respective driving action types shown in table 1 or table 2, thereby obtaining the historical driving action parameters shown in table 3.

TABLE 3 format of historical driving maneuver parameters

In step S10202B, the vehicle-mounted controller may invoke the man-machine interaction module, invoke the microphone installed in the cabin after the authorization of the person on the vehicle is obtained, detect the voice in the cabin, and extract the voice information spoken by the second target person (i.e. the person with higher driving skill level) through the features such as voiceprint.

In step S10203B, the vehicle-mounted controller runs a semantic analysis algorithm, performs semantic analysis on the voice information of the second target person obtained in step S10201B, and extracts content related to driving guidance in the voice information, thereby obtaining driving guidance information.

In this embodiment, the driving instruction information may be text information with contents of "accelerate to 50km/h as soon as possible", "brake immediately", "drive without pressing the real line", and the like.

In step S10204B, the vehicle-mounted controller runs a semantic analysis algorithm, and detects the correlation between the driving instruction information obtained in step S10203B and each driving action type in table 3. For example, the driving instruction information containing "as soon as possible acceleration to 50km/h" is related to the types of driving actions such as "vehicle running speed", "vehicle running acceleration", and "accelerator pedal depth"; the driving instruction information with the content of 'immediate brake' is related to the types of driving actions such as 'automobile running acceleration'; the driving instruction information, which is "do not press the solid line for driving", is related to the types of driving actions such as "steering angle of the steering wheel", "distance from the solid line", and "state of use of the turn signal lamp".

In step S10205B, for any driving action type, when the driving action type is related to the driving instruction information, the historical driving action parameters corresponding to the driving action type are adjusted according to the driving instruction information, so as to obtain the corresponding threshold value of the driving action type; when the driving action type is not related to the driving instruction information, determining a corresponding threshold value of the driving action type according to the historical driving action parameters corresponding to the driving action type.

For example, for a driving action type of "vehicle running acceleration", the corresponding historical driving action parameter is history ₂ The method comprises the steps of carrying out a first treatment on the surface of the If the driving instruction information of accelerating to 50km/h as soon as possible is detected, the history driving action parameter history can be obtained according to the driving instruction information of accelerating to 50km/h as soon as possible ₂ The adjustment is carried out, specifically, the corresponding acceleration value a of the meaning of accelerating to 50km/h as soon as possible can be searched in a database, and the acceleration value a can be set as the corresponding threshold value of the driving action type of the automobile running accelerationthreshold ₂ Or the acceleration a and the history driving action parameter history ₂ Average value of (2)Threshold value threshold corresponding to the type of driving action "vehicle running acceleration ₂ Or by other forms, history of historical driving action parameters ₂ Adjusting; if no driving instruction information related to the driving instruction information is detected, the history driving action parameter history corresponding to the driving action type of the automobile running acceleration can be directly used ₂ Threshold value threshold corresponding to driving action type determined as "vehicle running acceleration ₂ 。

In this embodiment, the principle of performing steps S10201B-S10205B is as follows: the driving instruction state is a state that a first target person with relatively low driving skill level drives an automobile and a second target person with relatively high driving skill level guides the automobile together, in which, in this state, a historical driving action parameter formed by an actual measurement value corresponding to each driving action type generated by the first target person driving the automobile can be considered as a parameter value capable of enabling the automobile to safely and normally run, so that the historical driving action parameter can be used as a threshold value corresponding to each driving action type, and is used for judging the risk in the future driving process, and in addition, since the historical driving action parameter is generated by the first target person driving the automobile and corresponds to the driving style of the first target person, the safe driving strategy parameter set according to the historical driving action parameter can be adapted to the driving style of the first target person, so that the comfort of the first target person in the future driving the automobile can be maintained; on the other hand, considering that the second target person generally guides or corrects the driving operation of the first target person in the form of spoken language, through semantic analysis on the second target person, the guiding or correcting information of the first target person contained in the spoken language can be determined, the historical driving action parameters generated by driving the automobile by the first target person related to the guiding or correcting information can be adjusted, the driving technology and driving experience of the first target person can be utilized, the historical driving action parameters generated by the actual driving operation of the first target person can be corrected, and the safe driving strategy parameters capable of guiding the safe and standard driving automobile can be obtained.

In this embodiment, when step S2, that is, the step of detecting the current driving action parameter is performed, the following steps may be specifically performed:

s201, carrying out identity recognition on the current driver;

s202, when the current driver is determined to be a first target person, a sensor is called, otherwise, the current time is detected;

s203, when the current time is determined to belong to the target time period, a sensor is called;

s204, detecting by using the called sensors and taking each driving action type as a detection target, and obtaining the current driving action parameters corresponding to each driving action type.

In this embodiment, the vehicle-mounted controller may call the person sensing module to perform steps S201 to S204.

Specifically, when executing step S201, the vehicle-mounted controller may invoke the person sensing module, identify whether the current driver is the first target person based on the technology such as the FACE ID, and if the current driver is the first target person, in step S202, the vehicle-mounted controller may invoke the sensors such as the distance sensing module, the speed sensing module, the component sensing module, and the like, and execute step S204, thereby detecting the current driving action parameters as shown in table 2.

If it is identified that the current driver is not the first target person (e.g., is the second target person or other person) based on the FACE ID or the like, the onboard controller may not invoke the sensor so as not to detect the current driving action parameter; the vehicle-mounted controller may also continue to determine whether the current time is within the target time period, for example, if the current time is within the target time period of 7:00-8:00 (peak to work) or 17:00-19:00 (peak to work) or holidays, etc., the vehicle-mounted controller may also call the sensors of the distance sensor module, the speed sensor module, the component sensor module, etc., and execute step S204, so as to detect the current driving action parameters as shown in table 2.

In this embodiment, the principle of performing steps S201 to S204 is that: by carrying out identity recognition on the current driver, certain steps in the automobile driving control method can be triggered and executed only when the current driver is a specific person such as a first target person, so that the steps in the automobile driving control method are executed only for individual persons (usually the person with lower driving skill level and needs to obtain sufficient safety guarantee and driving guidance), and the influence on other persons is reduced; and each step in the automobile driving control method is executed in a specific time period such as a target time period, so that each step in the automobile driving control method can be executed for any current driver in the specific time period with higher requirements on the driving technical level, and therefore, any current driver can obtain sufficient safety guarantee and driving guidance.

In this embodiment, when step S3 is performed, that is, the step of comparing the safe driving strategy parameter with the current driving action parameter to determine the current driving risk data, the following steps may be specifically performed:

s301, determining parameter similarity according to all safe driving strategy parameters corresponding to all driving action types and all current driving action parameters corresponding to all driving action types;

S302, for any driving action type, determining a difference value between a safe driving strategy parameter corresponding to the driving action type and a current driving action parameter, and adjusting the difference value according to the parameter similarity to obtain current driving risk data corresponding to the driving action type.

In step S301, the safe driving maneuver parameters shown in table 1 and the current driving maneuver parameters shown in table 2 are taken as examples, wherein the safe driving maneuver parameters may be expressed as a form (threshold ₁ ，threshold ₂ ……threshold ₉ ) The current driving action parameter may be expressed as a vector of (detection) ₁ ，detection ₂ ……detection ₉ ) Can use the vector of (2)And calculating the similarity between the two vectors by a quantity similarity algorithm to obtain the parameter similarity.

In step S302, taking the driving action type of "vehicle driving speed" as an example, the difference between the corresponding safe driving strategy parameter and the current driving action parameter is the detection ₁ -threshold ₁ Is adjusted according to the parameter similarity to be (detection) ₁ -threshold ₁ ) X similarity, can be determined by (detection ₁ -threshold ₁ ) The value x similarity is the current driving risk data corresponding to the driving action type of "vehicle running speed". Similar processing may also be performed for other types of driving actions.

In this embodiment, the principle of performing steps S301 to S302 is that: for any one driving action type, the difference between the corresponding safe driving strategy parameter and the current driving action parameter can represent the degree of deviation between the operation of the driving action type made by the first target person and the standard operation, but cannot represent the degree of deviation between the overall driving operation and the standard operation; conversely, the parameter similarity may indicate the degree of deviation of the overall driving operation by the first target person from the standard operation, but may not indicate the degree of deviation of the operation of a certain specific driving action type from the standard operation; by adjusting the difference value corresponding to the individual driving action type according to the parameter similarity, risk assessment of the operation of the individual driving action type under the overall driving operation condition can be obtained, and finer current driving risk data can be obtained.

In this embodiment, in executing step S4, that is, when the current driving risk data reaches the risk threshold, the following steps may be specifically executed when the current driving process is involved according to the safe driving policy parameter:

S401, setting a risk threshold corresponding to any driving action type, and determining current driving risk data corresponding to the driving action type and risk excess relative to the corresponding risk threshold;

s402, for any driving action type, intervention is carried out on the driving action corresponding to the driving action type in the current driving process according to the corresponding risk excess.

The principle of steps S401-S402 is to calculate the risk excess of each driving action type, which can quantitatively represent the risk size of the driving action type, and set intervention modes with different degrees according to the risk excess of different sizes. Specifically, the progressive intervention modes of the site warning, the site auxiliary correction, the remote connection, the driving permission take over and the like can be set in sequence according to the sequence of the risk excess from small to large.

In this embodiment, when step S402 is performed, that is, the step of performing intervention on the driving action corresponding to the driving action type in the current driving process according to the magnitude of the corresponding risk excess, the following steps may be specifically performed:

s40201, when the risk excess reaches a first interval, generating a site warning instruction; the on-site warning instruction is used for instructing the automobile part to send out a warning;

S40202, when the risk excess reaches a second interval, generating a feedback control instruction;

s40203, when the risk excess reaches a third interval, establishing a communication connection line between the local server and the remote server of the automobile;

s40204, when the risk excess reaches a fourth interval, switching the automobile from a site manual driving mode to an automatic driving mode or a remote manual driving mode, wherein the automatic driving mode executes automatic driving according to the safe driving strategy parameters.

In steps S40201 to S40204, the first section, the second section, the third section, and the fourth section are sections of sequentially increasing size.

In this embodiment, for any driving action type, the risk excess amounts thereof reach the first section, the second section, the third section, and the fourth section, respectively, so that it can be confirmed that the first target person performs the driving operation of the driving action type, and the security risk is at a level of large, very large, and the like.

In step S40201, when the risk exceeding amount corresponding to a certain driving action type reaches the first interval, which indicates that the first target person makes the driving operation of the driving action type, the safety risk facing the first target person is at a relatively high level, in this case, the vehicle-mounted controller may generate a field warning instruction, send the field warning instruction to the human-computer interaction module, and send a warning to the first target person in a text, sound or light manner, so as to remind the first target person of the risk, and enable the first target person to self-check and correct the irregular driving operation.

In step S40202, when the risk exceeding amount corresponding to a certain driving action type reaches the second interval, which indicates that the first target person performs the driving operation of the driving action type, the facing safety risk is at a great level, in which case the vehicle-mounted controller may generate the feedback control instruction and send the feedback control instruction to the automobile component corresponding to the driving action type. For example, for the driving action type of "car running acceleration", the corresponding car component is an accelerator pedal, when the car running acceleration is too large, so that the risk exceeding amount corresponding to the driving action type of "car running acceleration" reaches the second interval, the on-board controller may generate a feedback control instruction, and send the feedback control instruction to the accelerator pedal, so that the accelerator pedal generates a feedback force, and such feedback force belongs to resistance for the first target person driving the car (such resistance does not affect the first target person to continuously step on the accelerator pedal, so that the first target person can make an emergency action), thereby reminding the first target person to reduce the car running acceleration, and guiding the first target person to correct the irregular driving operation.

In step S40203, when the risk exceeding amount corresponding to a certain driving action type reaches the third interval, it indicates that the first target person makes driving operation of the driving action type, and the facing safety risk is at a very high level, in this case, the vehicle-mounted controller may establish a communication connection between the vehicle local and the remote server through the communication module, and the remote server may establish a connection with a terminal such as a mobile phone of the second target person with a higher driving level, so that the first target person driving the vehicle and the second target person outside the vehicle may establish a call in a voice or video form, so that the second target person may learn about the situation on the vehicle in time, on one hand, may provide driving guidance for the first target person, and on the other hand, may accompany the first target person, and may positively affect the mind of the first target person, thereby guaranteeing traffic safety.

In step S40204, when the risk exceeding amount corresponding to a certain driving action type reaches the fourth interval, which indicates that the first target person performs the driving operation of the driving action type, the security risk faced is at a very high level, in this case, the vehicle-mounted controller may invoke the autopilot module to switch the driving and control authority of the whole vehicle from the manual driving module to the autopilot module, and the vehicle-mounted controller may invoke the communication module to obtain the driving instruction (such as the depth of the accelerator pedal, the rotation angle of the steering wheel, etc.) of the automobile component from the terminal such as the mobile phone of the first target person, etc., and shield the use of the accelerator pedal, the steering wheel, etc. on the automobile.

The following is a more specific execution flow when the in-vehicle controller executes steps S40201 to S40204:

1. and distinguishing urban roads, suburban roads and expressways according to the high-precision map data, obtaining driving speed data, and when the speed is greater than the specified speed, giving a prompt by the system, displaying that the speed exceeds the specified speed of the driver, and not responding to an accelerator pedal, so that the vehicle does not exceed the maximum driving speed.

2. According to the high-precision map, the curvature of the curve is searched in advance, the maximum running speed allowed by the front curve is searched from the configuration table, the system smoothly decelerates according to the appointed deceleration before entering the curve, and a prompt is given: the excessive bending speed is excessive, namely, the gentle deceleration is realized. The system calculates the distance between the vehicle and the curve and the speed of the vehicle in the curve in advance according to the high-precision map data. Assuming that the curve should travel at a speed v_target, the current vehicle speed v_current, and the deceleration of the vehicle at smooth deceleration a, the distance the host vehicle should decelerate in advance is set as:

distance＝(V_current^2-V_target^2)/(2*a)

if the current road does not have a high-precision map, and reaches a curve, the speed is larger than the designated speed, the vehicle is slowly decelerated, the maximum deceleration is a_max, and the vehicle cannot be rapidly decelerated to the target speed. If the target over-bend speed cannot be reduced, over-bending is allowed beyond the specified speed, but the system records a risk event and initiates an alarm to the administrator. Meanwhile, the driver is prompted to pay attention to safe driving when the over-bending speed is too high.

3. According to lane line information, when lane change is initiated without turning on a steering lamp, the system prompts a driver to turn with very slight torque through steering wheel shake, the driver can finish lane change, and the system records lane change risk.

4. According to workshop line information, the distance between the vehicle and a lane line on one side is calculated, if the distance is smaller than a threshold value K, the vehicle is considered as a line pressing line, the system steering wheel automatically provides a slight swing car for central driving, if a driver does not interfere, central driving is realized, and if the driver interferes, the line pressing driving can be continued.

5. According to lane line information, the solid line will not allow lane change, if the driver forces lane change, the system will slightly prevent the solid line from changing lane torsion through the steering wheel, if not interfere, will stop lane change, if interfere, will complete lane change as the driver intends.

6. At 0.1 second recording speed intervals, the acceleration is calculated in real time by a=v_t-v_t-1/0.1, and if the acceleration exceeds a, the system will not increase the output power any more.

7. And measuring the speed of the front vehicle, searching the following distance set in the configuration table according to the speed, and if the current following distance is smaller than the set distance, slowly decelerating and pulling the system for a distance. Until the distance between vehicles reaches a set distance

8. When the front is red light, calculating the distance of the intersection of the red light, assuming that the current speed is V, and calculating the predicted deceleration when the distance passes through the intersection to be L: a= (v_final 2-v_current 2)/(2 x distance).

In order to prevent rear-end collision caused by sudden deceleration, the maximum deceleration allowed by the system is a_max, if a > a_max is calculated, the system performs deceleration according to a_max, and simultaneously prompts: the front red light is about to slow down, but is expected to stop, please take over the vehicle, detect whether the driver takes over, take over the condition includes: actively steering and actively stepping on the acceleration and deceleration pedals. If a < a_max is calculated, the deceleration is started at deceleration of a, the system prompts: the front red light, i.e. decelerating.

The front is green light, but the vehicle is about to enter a reverse plan, the countdown time is calculated, whether the vehicle can pass or not is judged according to the current vehicle speed and the distance between the vehicle and the road junction, if the vehicle can pass, and if the vehicle can not pass, a braking deceleration flow is entered, and the braking logic refers to flow 8.

9. The vehicle-mounted controller marks drunk driving data and normal driving data according to parameters such as a braking acceleration value, a distance from a vehicle in front of the vehicle, a distance between the vehicle and left and right lane lines, lane curvature, steering angular speed and the like, identifies drunk driving through a machine learning model, automatically triggers the system to stop by side when the drunk driving is identified, opens double flashing, and sends alarm information to an administrator.

In this embodiment, the vehicle-mounted controller may automatically record the video and the speed of the first target person driving the automobile no matter which intervention mode in steps S40201-S40204 is executed, and give a specific statistical report, where the report content includes: time of occurrence, number of times, location, type, severity level, video several seconds before and after the event, improvement advice, etc.

In this embodiment, by executing steps S40201-S40204, as shown in fig. 3, according to the magnitude of the corresponding risk excess corresponding to various driving action types, that is, the magnitude of the safety risk caused by the nonstandard degree of the driving operation corresponding to various driving action types, an appropriate intervention mode is selected to intervene in the current driving process, so that the driving process of the automobile accords with the standard of determining the parameters of the safety driving strategy, and the traffic safety is ensured.

The same technical effects as those of the automobile driving control method in the embodiment can be achieved by writing a computer program for executing the automobile driving control method in the embodiment, writing the computer program into a computer device or a storage medium, and executing the automobile driving control method in the embodiment when the computer program is read out to run.

It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly or indirectly fixed or connected to the other feature. Further, the descriptions of the upper, lower, left, right, etc. used in this disclosure are merely with respect to the mutual positional relationship of the various components of this disclosure in the drawings. As used in this disclosure, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. In addition, unless defined otherwise, all technical and scientific terms used in this example have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in the description of the embodiments is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used in this embodiment includes any combination of one or more of the associated listed items.

It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element of the same type from another. For example, a first element could also be termed a second element, and, similarly, a second element could also be termed a first element, without departing from the scope of the present disclosure. The use of any and all examples, or exemplary language (e.g., "such as") provided herein, is intended merely to better illuminate embodiments of the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.

It should be appreciated that embodiments of the invention may be implemented or realized by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer readable storage medium configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, in accordance with the methods and drawings described in the specific embodiments. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.

Furthermore, the operations of the processes described in the present embodiments may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes (or variations and/or combinations thereof) described in this embodiment may be performed under control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications), by hardware, or combinations thereof, that collectively execute on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.

Further, the method may be implemented in any type of computing platform operatively connected to a suitable computing platform, including, but not limited to, a personal computer, mini-computer, mainframe, workstation, network or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and so forth. Aspects of the invention may be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optical read and/or write storage medium, RAM, ROM, etc., such that it is readable by a programmable computer, which when read by a computer, is operable to configure and operate the computer to perform the processes described herein. Further, the machine readable code, or portions thereof, may be transmitted over a wired or wireless network. When such media includes instructions or programs that, in conjunction with a microprocessor or other data processor, implement the above steps, the invention of this embodiment includes these and other different types of non-transitory computer-readable storage media. The invention also includes the computer itself when programmed according to the methods and techniques of the invention.

The computer program can be applied to the input data to perform the functions of the present embodiment, thereby converting the input data to generate output data that is stored to the non-volatile memory. The output information may also be applied to one or more output devices such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including specific visual depictions of physical and tangible objects produced on a display.

The present invention is not limited to the above embodiments, but can be modified, equivalent, improved, etc. by the same means to achieve the technical effects of the present invention without departing from the spirit and principle of the present invention. Various modifications and variations are possible in the technical solution and/or in the embodiments within the scope of the invention.

Claims

1. An automobile driving control method, characterized in that the automobile driving control method comprises:

acquiring a safe driving strategy parameter;

detecting current driving action parameters;

2. The automobile driving control method according to claim 1, wherein the acquiring the safe driving strategy parameter includes:

setting a plurality of driving action types;

3. The automobile driving control method according to claim 2, wherein the setting of the respective threshold value for each of the driving action types, respectively, includes:

4. The automobile driving control method according to claim 2, wherein the detecting of the current driving action parameter includes:

carrying out identity recognition on the current driver;

5. The automobile driving control method according to claim 4, wherein the setting of the respective threshold value for each of the driving action types, respectively, includes:

detecting voice information of the second target person;

6. The automobile driving control method according to any one of claims 2-5, wherein said determining current driving risk data by comparing said safe driving maneuver parameters with said current driving maneuver parameters comprises:

7. The method according to claim 6, wherein the intervening in the current driving process according to the safe driving strategy parameter when the current driving risk data reaches a risk threshold value includes:

8. The automobile driving control method according to claim 7, wherein the intervening driving actions corresponding to the driving action type during the current driving according to the magnitude of the corresponding risk excess amount includes:

9. A computer device comprising a memory for storing at least one program and a processor for loading the at least one program to perform the method of controlling driving of a motor vehicle as claimed in any one of claims 1-8.

10. A computer-readable storage medium in which a processor-executable program is stored, characterized in that the processor-executable program is for performing the automobile driving control method according to any one of claims 1 to 8 when being executed by a processor.