CN111103871A - Automobile auxiliary driving control method based on finger vein recognition - Google Patents
Automobile auxiliary driving control method based on finger vein recognition Download PDFInfo
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Abstract
The invention relates to an automobile assistant driving control method based on finger vein recognition, which comprises the following steps: (1) acquiring image information of a vehicle driver by using a finger vein acquisition device, and establishing a current user information database; (2) initializing system control parameters for the newly added user in a database; (3) recording the driving habits of the current user, and carrying out parameter fine adjustment on the actual operation of the current user according to parameter setting; (4) carrying out feedback rate adjustment guidance according to real-time feedback of a user, actively correcting driving habits of the user and avoiding overshooting of feedback rate parameters; (5) and realizing automatic tracking driving under the condition of vehicle traffic jam, collision early warning and emergency avoidance under the abnormal driving state and control curve optimization under the normal driving state based on the fine-tuned parameters. The method and the device utilize the finger vein recognition technology to assist in recognizing the user information, so that the control process is more adaptive to the personal habits of the user, the intelligence of the control system is improved, and the driving experience of the user is improved.
Description
Technical Field
The invention belongs to the technical field of finger vein recognition, and particularly relates to an automobile driving assistance control method based on finger vein recognition.
Background
The finger vein recognition technology is a new biometric technology for recognizing user information according to finger vein distribution characteristics of a user. Compared with the traditional fingerprint identification technology, the finger vein identification has the advantage of being not reproducible. In the field of military engineering safety, finger vein devices are often used for the preservation of strategic materials of important military equipment such as firearms, bullets and the like. In the civil aspect, the finger vein technology is integrated into an intelligent door lock, and the finger vein technology enters thousands of households. Due to the excellent performance of the finger vein technology, organizations such as banks and schools also utilize the finger vein technology to improve the operation experience of users.
The existing vehicle driving auxiliary system is mostly used for intelligent navigation direction, the navigation mode is single and constant, and the system can not be adapted and adjusted according to the change of a user. For people skilled in driving technology, the intelligent navigation system cannot completely accord with personal operation habits; for people with poor driving skills, the navigation system can only provide voice or route planning, and cannot provide help for the actual driving process of the user. Under the condition that the vehicle encounters a dangerous situation, early warning cannot be issued in advance, and the dangerous situation cannot be avoided through the maneuvering of the vehicle by utilizing the advantage of quick response of the intelligent equipment. For a user who just touches an automobile for driving, the problem of excessive control of an accelerator or a brake is easy to occur due to unfamiliarity with the operation and control of the automobile, so that the experience feeling in the driving process is poor.
Chinese patent CN107215332A discloses a safety assistant driving system and control method, including a camera unit, an alarm unit and a processing unit, the camera device is used for collecting real-time panoramic images outside and inside the vehicle when driving; the processing device acquires the vehicle exterior environment image and the driving position image in the real-time panoramic image, respectively identifies, calculates and judges the vehicle exterior environment image and the driving position image, and sends out alarm reminding according to the judgment result.
Therefore, a driving assistance system that can provide a more moderate power input or brake output based on the control intention of the driver, can give an early warning in an emergency, and can avoid a dangerous situation in time is urgently needed.
Disclosure of Invention
In order to solve the problem that the controlled instruction of the existing automobile control technology is single, and the best instruction feedback cannot be given according to the difference of users, so that the drivers cannot obtain the most comfortable driving experience, the invention provides an automobile safety mode auxiliary driving system based on finger vein recognition and finger vein recognition for analyzing the operation habits of the drivers, which can give different degrees of feedback under the same instruction according to the difference of the drivers, so that the control process is more adaptive to the personal habits of the users, the intelligence of the control system is improved, and the driving experience of the users is improved; early warning can be carried out in advance under the emergency condition, and emergency danger avoidance can be carried out according to the situation. Thereby furthest guaranteeing the safety of drivers.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
the invention relates to an automobile assistant driving control method based on finger vein recognition, which comprises the following steps:
(1) acquiring image information of a vehicle driver by using a finger vein acquisition device, and establishing a current user information database;
(2) initializing system control parameters for newly added users in a database, wherein the system control parameters comprise an automatic tracking driving mode parameter, an anti-collision parameter and a user driving parameter;
(3) recording the driving habits of the current user, and carrying out parameter fine adjustment on the actual operation of the current user according to parameter setting;
(4) carrying out feedback rate adjustment guidance according to real-time feedback of a user, actively correcting driving habits of the user and avoiding overshooting of feedback rate parameters;
(5) and realizing automatic tracking driving under the condition of vehicle traffic jam, collision early warning and emergency avoidance under the abnormal driving state and control curve optimization under the normal driving state based on the fine-tuned parameters.
Preferably, in step (1), the finger vein collection device includes a finger vein collection device for acquiring finger vein image information; a finger vein storage unit for storing the finger vein image features; the finger vein comparison system is used for comparing and classifying according to the finger vein image information; a native database unit for adapting to small batches of users; a remote server processing unit for adapting to large-scale users.
Preferably, in the step (2), the initialization of the newly added user information is to give a universal control parameter to the newly registered user in the current database system, so that the whole system can normally operate without detailed parameter setting, thereby ensuring the simplicity and convenience of the user in the using process; and providing initial values for user parameter adjustment to ensure that the parameter self-learning process can be normally carried out. The system control parameters include auto-track driving mode parameters including, but not limited to: and selecting a vehicle accelerator feedback rate control coefficient, a vehicle brake feedback rate control coefficient, a vehicle safe distance coefficient and a vehicle external indicator light control mode. The collision avoidance parameters include, but are not limited to: the system comprises a vehicle pre-collision early warning distance, a vehicle rear-end collision pre-collision early warning distance, a vehicle collision avoidance distance, a vehicle rear-end collision avoidance distance, an alarm light switch mode parameter, a vehicle emergency avoidance grade and a vehicle emergency avoidance feedback parameter. The user driving parameters include, but are not limited to: the method comprises the following steps of user type, feedback rate, the ratio of the highest speed of a user driving a vehicle to the highest speed limit of a running road section, the highest acceleration of the user driving the vehicle, the braking coefficient of the user driving the vehicle and the output control parameters of an oil throttle.
Preferably, in the step (3), the parameter fine tuning refers to reading operation parameters of the control system, including a current user type, a feedback rate used by a current user for operating the vehicle, a current user system operation actual feedback value, and a current vehicle operation state, fine tuning the feedback rate parameters according to a current user instruction, verifying a feedback rate adjustment result, and fine tuning the system control parameters according to the fine tuned feedback rate parameters.
Preferably, the calculation formula for fine adjustment of the system control parameters in step (3) is as follows: the post-fine-tuning parameter is an instantaneous parameter (1+ (actual feedback value/feedback parameter) × feedback rate). The instantaneous parameters refer to various relevant parameters when the current vehicle runs, are real-time change quantities, and the values of the instantaneous parameters are obtained from a vehicle control system when the final parameters are calculated; the feedback parameters are parameters used at corresponding moments when the feedback rate is calculated, are instantaneous quantification, are determined when the feedback rate is calculated, and cannot be changed until the next calculation period; these two quantities are consistent when the user chooses to adjust in real time and may be replaced by a single parameter; if the real-time adjustment is not carried out, the adjustment system is delayed, and the adjustment system is distinguished.
Preferably, in the step (4), the feedback rate adjustment guidance mode specifically includes the steps of: and carrying out speed increasing control in a control mode of taking the target speed curve as a logarithmic curve according to the magnitude relation between the control parameters given by the user when the user operates the automobile currently and the control coefficients for adjusting the normal running speed set by the user currently. The logarithmic curve control mode can ensure the smooth and stable control process and ensure higher acceleration under the condition that the actual running speed is far away from the target speed; a more gradual speed adjustment is ensured when the target speed is approached.
Preferably, the feedback rate parameters include a throttle oil output control coefficient feedback rate parameter for controlling a control process curve in a nonlinear form, a vehicle braking system feedback rate parameter for controlling system braking, a sensor parameter comprehensive feedback control system feedback rate parameter for verifying the current state of the vehicle, and a temperature regulation control feedback rate parameter in a carriage.
Preferably, in the step (5), the step of implementing automatic tracking driving under the vehicle traffic jam condition comprises the following specific steps:
(5.1) before the vehicle starts to run, identifying a user through a finger vein, and loading an automatic tracking driving mode parameter corresponding to the user according to an identification result;
(5.2) monitoring the relative distance between the current vehicle and the vehicles in front and at the back when the vehicle runs, and judging the traffic jam condition;
(5.3) if the relative distance is smaller than the parameter limited by the traffic jam mode, the vehicle enters the traffic jam mode;
(5.4) in the vehicle traffic jam mode, monitoring the distance between the vehicle and the front vehicle and the rear vehicle in real time, and comparing and analyzing the distance with set parameters to prevent rear-end collision and rear-end collision;
and (5.5) the user actively jumps out of the traffic jam mode or automatically jumps out of the traffic jam mode according to the speed of the vehicle.
Preferably, in the step (5), the steps of implementing collision early warning and collision avoidance in the abnormal driving state are:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading anti-collision parameters corresponding to the user according to an identification result;
(5.2) monitoring the relative distance between the current vehicle and the front and rear vehicles when the vehicle runs, and judging whether the relative distance is smaller than the collision early warning distance;
and (5.3) after the relative distance is smaller than the early warning distance, the active control system carries out corresponding collision early warning and emergency avoidance.
Preferably, in the step (5), the step of optimizing the control curve in the normal driving state is:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading user driving parameters corresponding to the user according to an identification result;
(5.2) fitting the control process according to the control input of the user when the vehicle runs;
(5.3) judging whether the vehicle is in a normal running mode or not;
and (5.4) recording the control habits of the user and optimizing the control feedback rate of the user.
Compared with the prior art, the technical scheme provided by the invention has the following beneficial effects:
1. according to the method, the finger vein recognition technology is utilized to assist in recognizing the user information, and feedback of different degrees under the same instruction can be given according to different drivers, so that the control process is more adaptive to the personal habits of the user, the intelligence of a control system is improved, and the driving experience of the user is improved;
2. the invention can automatically track driving under the condition of traffic jam and assist drivers to pass through a traffic jam area at the highest speed under the condition of ensuring the safety of vehicles;
3. the collision early warning function can be provided, assistance is provided for safe driving of the road of a driver, and the probability of traffic accidents is reduced;
4. the collision avoidance function under emergency can be provided, the advantages of electronic control are fully exerted, and the life and property safety of drivers under emergency conditions is ensured to the maximum extent;
5. the invention can provide control curve optimization under the normal running condition, so that the vehicle control process is better compatible to the newly contacted driver, driving discomfort caused by excessive control is avoided, and the riding experience of a user is ensured.
Drawings
FIG. 1 is a flow chart of finger vein database establishment and user feature comparison in the present invention;
FIG. 2 is a flow chart of the operation of the automatic tracking driving system for a vehicle in a traffic jam condition;
FIG. 3 is a flowchart illustrating the operation of the collision avoidance system during abnormal driving conditions;
fig. 4 is a flowchart of control curve optimization of the vehicle motion system under normal driving conditions.
Detailed Description
For further understanding of the present invention, the present invention will be described in detail with reference to examples, which are provided for illustration of the present invention but are not intended to limit the scope of the present invention.
Example 1
The embodiment relates to an automobile assistant driving control method based on finger vein recognition, which comprises the following steps:
(1) acquiring image information of a vehicle driver by using a finger vein acquisition device, and establishing a current user information database;
(2) initializing system control parameters for newly added users in a database, wherein the system control parameters comprise an automatic tracking driving mode parameter, an anti-collision parameter and a user driving parameter;
(3) recording the driving habits of the current user, and carrying out parameter fine adjustment on the actual operation of the current user according to parameter setting;
(4) carrying out feedback rate adjustment guidance according to real-time feedback of a user, actively correcting driving habits of the user and avoiding overshooting of feedback rate parameters;
(5) and automatically tracking and driving under the condition of vehicle traffic jam based on the fine-tuned parameters.
In the step (1), the finger vein acquisition device comprises finger vein acquisition equipment for acquiring finger vein image information; a finger vein storage unit for storing the finger vein image features; the finger vein comparison system is used for comparing and classifying according to the finger vein image information; a native database unit for adapting to small batches of users; a remote server processing unit for adapting to large-scale users.
In the step (2), the initialization of newly added user information is to give a universal control parameter to a newly registered user in the current database system, so that the whole system can normally run without detailed parameter setting, and the convenience of the user in the using process is ensured; and providing initial values for user parameter adjustment to ensure that the parameter self-learning process can be normally carried out.
In the step (3), the parameter fine tuning refers to reading the operation parameters of the control system, including the current user type, the feedback rate used by the current user to operate the vehicle, the actual feedback value of the current user system operation, and the current vehicle operation state, fine tuning the feedback rate parameters according to the current user instruction, verifying the feedback rate adjustment result, and fine tuning the system control parameters according to the fine tuned feedback rate parameters.
The process of fine tuning the feedback rate in step (3) will now be described in detail by taking the vehicle control feedback rate parameter function δ (t) as an example: setting the driving state of the vehicle to A, AtRepresenting the state of the vehicle at time t. Meanwhile, the intention of the driver to change the vehicle state is set as P, PtRepresenting the change in the mind of the person of the vehicle at time t. Delta0Represents the feedback rate parameter function at time 0, and δ (t) represents the final value of the feedback rate parameter function after t passes. From these parameters, the process of vehicle feedback rate fine tuning can be described in the following form.
When the driving state of the vehicle is a, the state of the vehicle is adjusted according to the subjective intention of the user, and since the control process of the user is nonlinear, the state change of the vehicle can be expressed as follows:
due to the wear of the vehicle itself and the difference of the road condition, the actual state of the vehicle at the time t should be expressed as:
wherein k (t) is a function of attenuation rate of vehicle state change caused by performance reduction of the vehicle or road condition change.
The vehicle is controlled by a driver to realize the change of the vehicle state by the mechanical structure of the vehicle during the driving process. In order to cope with the change of the vehicle state, the feedback rate parameter function needs to be compensated, and the state change of the vehicle at the time t after the system compensation is added should be:
the change of the person's intention to control the vehicle is determined by the change of the state of the vehicle itself, and the following should be satisfied between the state of the vehicle and the intention to control the driver:
Pt-P0 (a)t-A0)
represents the relationship between human control intent on the vehicle and the vehicle state.
Under the set straight road barrier-free state, the vehicle state and the change of the control intention of people should satisfy an approximate linear relation. The value is a gradual amount over time for an individual user, and may be considered constant during a short period of vehicle control, as long as a steady change in vehicle conditions is guaranteed.
Can be derived from the functional relationship as long as (A) is guaranteedt-A0) Is linear so that (P)t-P0) The linearity is maintained, so that good driving experience is achieved.
According to AtThe integral of Δ δ (t) over time is the compensation of the system for changes in the function k (t) to changes in the vehicle state. When the driving state of the vehicle is subjectively controlled by a driver to change, the system takes the sending moment of the control command as a starting point and takes delta t as a step length to carry out k (t) monitoring according to the advantages of electronic calculation. At the end of a very short period Δ t, if the k (t) function changes compared to the starting time, the vehicle control feedback rate parameter function δ (t) is adjusted at that time to ensure the driving experience of the driver.
The calculation formula for fine adjustment of the system control parameters in the step (3) is as follows: the post-fine-tuning parameter is an instantaneous parameter (1+ (actual feedback value/feedback parameter) × feedback rate).
The fine adjustment of the system control parameter will now be described in detail by taking the adjustment of the output control parameter h (t) of the fuel throttle as an example:
1. reading instantaneous throttle oil quantity output control instantaneous parameter h (t)0) Instantaneous speed v, maximum travel speed v allowed for the current road sectionm xAverage value v' of driving speed of driver in recent driving period, vector matrix Vec (v) of change relation between speed and accelerator oil output state and feedback rate parameter function delta (t)0)；
2. If v' > vm xAccording to the parameter fine-tuning calculation formula in the step (3), the fine-tuned fuel quantity accelerator output control parameter h (t) can be expressed as
If v' < vm xThe calculation formula of the parameter fine tuning is adjustableIs integrated into
It should be noted that the running speed of the vehicle and the driving speed average v' of the driver in the latest driving period are both directly read from the vehicle control system and are directly obtained by the measurement of the system sensor.
In the step (4), the feedback rate adjustment guidance mode specifically comprises the following steps: and carrying out speed increasing control in a control mode of taking the target speed curve as a logarithmic curve according to the magnitude relation between the control parameters given by the user when the user operates the automobile currently and the control coefficients for adjusting the normal running speed set by the user currently. The logarithmic curve control mode can ensure the smooth and stable control process and ensure higher acceleration under the condition that the actual running speed is far away from the target speed; a more gradual speed adjustment is ensured when the target speed is approached.
The feedback rate parameters comprise a throttle oil output control coefficient feedback rate parameter for controlling a control process curve in a nonlinear form, a vehicle braking system feedback rate parameter for controlling system braking, a sensor parameter comprehensive feedback control system feedback rate parameter for verifying the current state of the vehicle, and a temperature regulation control feedback rate parameter in a carriage.
Referring to fig. 1, the method for controlling the auxiliary driving of the automobile comprises the following specific steps: the user enters a driving state, and if the user selects the finger vein acquisition device to register, the system can judge whether the user is registered; if the user is registered, reminding the user that the user is registered; if not, registration is carried out: and acquiring image information of a vehicle driver, establishing a current user information database, and initializing driving information for a newly added user in the database. And if the user selects to carry out finger vein verification, carrying out user category screening according to a finger vein identification result, if the current user type cannot be identified, carrying out user identification and authentication again, recording the authentication failure times, locking the automobile if the authentication failure times exceed the set failure times, and starting an alarm program. And if the authentication is successful, the system loads control system control parameters corresponding to the user, monitors the running condition of the automobile in real time after the automobile starts running, updates the running parameters of the control system database in real time along with the running of the driving process of the user, and records non-Boolean quantity control commands in the running process of the automobile according to the corresponding scene mode.
As shown in fig. 2, the control method for automatic tracking driving of a vehicle in a traffic jam condition specifically includes:
and (5.1) before the vehicle starts to run, identifying the user through a finger vein, and loading the corresponding automatic tracking driving mode parameters of the user according to the identification result.
And (5.2) monitoring the relative distance between the current vehicle and the vehicles in front and at the back when the vehicle runs, and judging the traffic jam condition.
The decision factors for judging the traffic jam condition include: relative distance s between front and rear vehicles and current vehicle0(ii) a The time loss t required to traverse the fixed stretch s; the driving speed limit v of the current road section.
The rule for calculating the traffic jam condition is that if the ratio a of the difference between the product of the maximum speed limit v of the current road section and the time t required for the vehicle to pass a distance s from the current path and the distance s is greater than the product of the set value α and the feedback rate parameter, and the average value of the sum of the distances of the vehicles before and after the current vehicle distance is less than 20% of the safe distance under the maximum speed limit v, the vehicle is determined to enter the traffic jam condition.
And (5.3) if the relative distance is less than the parameter defined by the traffic jam mode, the vehicle enters the traffic jam mode.
The method comprises the steps of initializing parameters of a traffic jam mode (namely loading control parameters) according to the user category judged by the finger vein device, and controlling the vehicle to keep advancing at a higher running speed in a safe range by controlling the power output and the movement direction change of the vehicle according to the parameter setting in the traffic jam mode.
The parameters to be initialized in the initialization of the parameters of the automatic tracking driving mode comprise: and selecting a vehicle accelerator feedback rate control coefficient, a vehicle brake feedback rate control coefficient, a vehicle safe distance coefficient and a vehicle external indicator light control mode.
After the vehicle enters the traffic jam mode, the automatic tracking driving mode parameters have the following functions in the running process and the updating process of the corresponding parameter values: and judging the distance between the current position and the front and rear vehicles according to the vehicle distance sensor, evaluating the vehicle safety distance coefficient according to the current weather and road surface conditions, and giving the minimum safety distance in the front and rear vehicle traffic jam mode. In the traffic jam mode state, the final power output of the vehicle is formed by multiplying the sum of the power output actively controlled by a user and the power output compensated by the system by a vehicle accelerator feedback rate control coefficient; the final braking output of the vehicle is equal to the sum of the user-provided braking output and the system-compensated braking output multiplied by a vehicle braking feedback rate control coefficient. As shown in the formula:
final output power (power information input by user + power output compensated by system) vehicle throttle feedback rate control coefficient
Final brake output (user-provided brake output + system compensated brake output) vehicle brake feedback rate control coefficient
In the traffic jam mode, the final power output and the final brake output of the vehicle and the road surface condition jointly determine the minimum safe distance of the vehicle, and the actual distance between the vehicle and the front vehicle and the rear vehicle determines the maximum speed at which the current vehicle can operate. The compensation for the user input power and the compensation for the brake output ensure that the vehicle can pass through the traffic jam area at maximum speed.
And (5.4) in the vehicle traffic jam mode, monitoring the distance between the vehicle and the front vehicle and the rear vehicle in real time, and comparing and analyzing the distance with set parameters to prevent rear-end collision and rear-end collision.
After entering an automatic tracking mode, monitoring the distance between the vehicle and a front vehicle, and increasing a brake feedback rate control coefficient to prevent rear-end collision and perform acceleration reminding when the distance is greater than a safe distance; when the distance is less than the safe distance, the distance is close to remind, when the distance is less than one-half of the safe distance, whether the vehicle continues to operate or not can be judged, and pre-collision reminding and deceleration reminding can be carried out when the vehicle continues to operate until the distance is greater than the safe distance.
After entering an automatic tracking mode, monitoring the distance between the rear vehicle and the accelerator, increasing the accelerator feedback rate to prevent rear-end collision when the distance between the rear vehicle and the accelerator is less than a safe distance, and carrying out light reminding on the rear vehicle according to the relative distance; if the distance between the automobile and the front automobile is smaller than the safety distance, the reminding level of the anti-collision light can be improved, and if the distance between the automobile and the front automobile is larger than the safety distance, acceleration reminding is carried out; when the distance between the automobile and the rear automobile is less than one half of the safety distance, if the distance between the automobile and the front automobile is also less than one half of the safety distance, the reminding level of the anti-collision lamplight can be improved, and if the distance between the automobile and the front automobile is more than one half of the safety distance, the acceleration reminding is carried out.
And (5.5) the user actively jumps out of the traffic jam mode or automatically jumps out of the traffic jam mode according to the speed of the vehicle.
The ratio a of the difference between the product of the time t required by the current vehicle to pass through a certain section of route s and the distance s to the distance s is smaller than the product of the set value α and the feedback rate parameter, and the current vehicle is determined to enter a normal running state when the current vehicle runs at a speed not lower than 70% of the highest speed limit v and exceeds twice the safety distance under the highest speed limit v, and the system automatically jumps out of the traffic jam mode.
Example 2
The embodiment relates to an automobile assistant driving control method based on finger vein recognition, which comprises the following steps:
(1) acquiring image information of a vehicle driver by using a finger vein acquisition device, and establishing a current user information database;
(2) initializing system control parameters for newly added users in a database, wherein the system control parameters comprise an automatic tracking driving mode parameter, an anti-collision parameter and a user driving parameter;
(3) recording the driving habits of the current user, and carrying out parameter fine adjustment on the actual operation of the current user according to parameter setting;
(4) carrying out feedback rate adjustment guidance according to real-time feedback of a user, actively correcting driving habits of the user and avoiding overshooting of feedback rate parameters;
(5) and realizing collision early warning and emergency avoidance under the abnormal driving state of the vehicle based on the fine-tuned parameters.
In the step (1), the finger vein acquisition device comprises finger vein acquisition equipment for acquiring finger vein image information; a finger vein storage unit for storing the finger vein image features; the finger vein comparison system is used for comparing and classifying according to the finger vein image information; a native database unit for adapting to small batches of users; a remote server processing unit for adapting to large-scale users.
In the step (2), the initialization of newly added user information is to give a universal control parameter to a newly registered user in the current database system, so that the whole system can normally run without detailed parameter setting, and the convenience of the user in the using process is ensured; and providing initial values for user parameter adjustment to ensure that the parameter self-learning process can be normally carried out.
In the step (3), the parameter fine tuning refers to reading the operation parameters of the control system, including the current user type, the feedback rate used by the current user to operate the vehicle, the actual feedback value of the current user system operation, and the current vehicle operation state, fine tuning the feedback rate parameters according to the current user instruction, verifying the feedback rate adjustment result, and fine tuning the system control parameters according to the fine tuned feedback rate parameters.
The calculation formula for fine adjustment of the system control parameters in the step (3) is as follows: the post-fine-tuning parameter is an instantaneous parameter (1+ (actual feedback value/feedback parameter) × feedback rate).
For feedback rate parameter tuning and system control parameter tuning in this embodiment, see the example of embodiment 1.
In the step (4), the feedback rate adjustment guidance mode specifically comprises the following steps: and carrying out speed increasing control in a control mode of taking the target speed curve as a logarithmic curve according to the magnitude relation between the control parameters given by the user when the user operates the automobile currently and the control coefficients for adjusting the normal running speed set by the user currently. The logarithmic curve control mode can ensure the smooth and stable control process and ensure higher acceleration under the condition that the actual running speed is far away from the target speed; a more gradual speed adjustment is ensured when the target speed is approached.
The feedback rate parameters comprise a throttle oil output control coefficient feedback rate parameter for controlling a control process curve in a nonlinear form, a vehicle braking system feedback rate parameter for controlling system braking, a sensor parameter comprehensive feedback control system feedback rate parameter for verifying the current state of the vehicle, and a temperature regulation control feedback rate parameter in a carriage.
Referring to fig. 3, the method for controlling collision early warning and collision avoidance in the abnormal driving state of the vehicle specifically comprises the following steps:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading anti-collision parameters corresponding to the user according to an identification result;
the anti-collision parameters in the safe braking and collision avoidance system under the vehicle running condition comprise: the system comprises a vehicle pre-collision early warning distance, a vehicle rear-end collision pre-collision early warning distance, a vehicle collision avoidance distance, a vehicle rear-end collision avoidance distance, an alarm light switch mode parameter, a vehicle emergency avoidance grade and a vehicle emergency avoidance feedback parameter.
The vehicle rear-end collision pre-warning distance is as follows: when the own vehicle and the target vehicle both keep running at the current speed, the target vehicle can collide with the own vehicle within 3 seconds.
The vehicle collision avoidance distance is as follows: the current vehicle can avoid the minimum avoidance distance of collision occurrence through self emergency maneuver before the collision.
The vehicle rear-end collision avoidance distance is as follows: the minimum avoidance distance of the current vehicle before the rear-end collision can be avoided through the emergency maneuver of the current vehicle.
The alarm light switch mode parameters are as follows: a switch parameter for warning light levels to alert other vehicle drivers to maintain a suitable safe distance from the user's currently driven vehicle.
The vehicle emergency avoidance grade is as follows: and judging the proficiency degree of the current user in the vehicle operation through the finger vein recognition result, so that the given grade parameter of the vehicle in the emergency state can automatically avoid collision. The default value of the parameter is that the emergency avoidance grade of the vehicle is highest, the emergency avoidance grade cannot be automatically modified, the emergency avoidance grade must be set by a specific user, and the emergency avoidance grade cannot be changed among different users.
The vehicle emergency avoidance feedback rate parameter is as follows: an assessment is made based on the user's proficiency in vehicle handling during routine driving. The evaluation result can be used for reference of the vehicle emergency avoidance grade, and the user with a low evaluation result is limited to turn down the vehicle emergency avoidance grade.
The purpose of the initialization of the anti-collision parameters is to set different anti-collision protection distances according to different driving permissions of the current user, so that the driving habits of the user are adapted to the greatest extent under the condition of preferentially ensuring the safety of the user, and the driving process is more humanized.
(5.2) monitoring the relative distance between the current vehicle and the front and rear vehicles when the vehicle runs, and judging whether the relative distance is smaller than the collision early warning distance;
the vehicle and collision early warning distance is as follows: the current safe distance traveled by the vehicle, i.e. the current speed v of the vehicletDistance covered by 3 seconds of travel.
And (5.3) after the relative distance is smaller than the early warning distance, the active control system carries out corresponding collision early warning and emergency avoidance.
The collision early warning method comprises the following specific measures:
(5.3.1) entering an early warning state, starting warning light and reminding a vehicle entering a safe distance;
(5.3.2) after the light reminding, if the distance between the target vehicle and the current vehicle is continuously reduced, reminding the driver in a light mode, wherein the vehicle which can cause collision exists in the safe distance;
(5.3.3) if the target vehicle continuously approaches the user to drive the vehicle and the distance between the target vehicle and the user is less than twice of the collision avoidance distance (rear-end collision avoidance distance) of the vehicle, reminding a driver of emergency avoidance through voice;
and (5.3.4) if the distance between the target vehicle and the current user driving the vehicle is less than 1.2 times of the collision avoidance distance (vehicle rear-end collision avoidance distance) of the emergency vehicle, carrying out forced collision avoidance by the system according to the authority of the current user.
(5.3.5) increasing the level of the current user for the vehicle emergency avoidance, and reducing the control rate parameter of the current user for the highest driving speed on the corresponding road.
The concrete implementation process of the vehicle emergency avoidance comprises the following steps:
(5.3.1) detecting whether the target vehicle enters a region of which the collision avoidance distance (vehicle rear-end collision avoidance distance) of the emergency vehicle is 1.2 times.
And (5.3.2) controlling the user to drive the vehicle to perform forced deceleration (or acceleration) so as to increase the distance between the two parties.
And (5.3.3) forcibly controlling the change of the running direction of the vehicle and carrying out maneuver avoidance to the side front of the moving direction.
And (5.3.4) increasing the relative distance measuring and calculating times between the target vehicle and the own vehicle, and starting the highest-level collision early warning.
(5.3.5) if the relative distance between the target vehicle and the user-driven vehicle is less than 0.5 times of the collision avoidance distance (rear-end collision avoidance distance) of the emergency vehicle, the driving user is reminded to perform collision protection.
The forced control includes forced acceleration, forced deceleration and forced control of vehicle driving direction change, and is an emergency processing mode on the premise of ensuring the safety of a driving user in an emergency situation. The vehicle control system takes over the vehicle control to ensure the personal safety of the driver under the dangerous condition. The forced control is automatically released after the hazardous condition is released.
Example 3
The embodiment relates to an automobile assistant driving control method based on finger vein recognition, which comprises the following steps:
(1) acquiring image information of a vehicle driver by using a finger vein acquisition device, and establishing a current user information database;
(2) initializing system control parameters for newly added users in a database, wherein the system control parameters comprise an automatic tracking driving mode parameter, an anti-collision parameter and a user driving parameter;
(3) recording the driving habits of the current user, and carrying out parameter fine adjustment on the actual operation of the current user according to parameter setting;
(4) carrying out feedback rate adjustment guidance according to real-time feedback of a user, actively correcting driving habits of the user and avoiding overshooting of feedback rate parameters;
(5) and optimizing a control curve under the normal driving state of the vehicle based on the fine-tuned parameters.
In the step (1), the finger vein acquisition device comprises finger vein acquisition equipment for acquiring finger vein image information; a finger vein storage unit for storing the finger vein image features; the finger vein comparison system is used for comparing and classifying according to the finger vein image information; a native database unit for adapting to small batches of users; a remote server processing unit for adapting to large-scale users.
In the step (2), the initialization of newly added user information is to give a universal control parameter to a newly registered user in the current database system, so that the whole system can normally run without detailed parameter setting, and the convenience of the user in the using process is ensured; and providing initial values for user parameter adjustment to ensure that the parameter self-learning process can be normally carried out.
In the step (3), the parameter fine tuning refers to reading the operation parameters of the control system, including the current user type, the feedback rate used by the current user to operate the vehicle, the actual feedback value of the current user system operation, and the current vehicle operation state, fine tuning the feedback rate parameters according to the current user instruction, verifying the feedback rate adjustment result, and fine tuning the system control parameters according to the fine tuned feedback rate parameters.
The calculation formula for fine adjustment of the system control parameters in the step (3) is as follows: the post-fine-tuning parameter is an instantaneous parameter (1+ (actual feedback value/feedback parameter) × feedback rate).
For feedback rate parameter tuning and system control parameter tuning in this embodiment, see the example of embodiment 1.
In the step (4), the feedback rate adjustment guidance mode specifically comprises the following steps: and carrying out speed increasing control in a control mode of taking the target speed curve as a logarithmic curve according to the magnitude relation between the control parameters given by the user when the user operates the automobile currently and the control coefficients for adjusting the normal running speed set by the user currently. The logarithmic curve control mode can ensure the smooth and stable control process and ensure higher acceleration under the condition that the actual running speed is far away from the target speed; a more gradual speed adjustment is ensured when the target speed is approached.
The feedback rate parameters comprise a throttle oil output control coefficient feedback rate parameter for controlling a control process curve in a nonlinear form, a vehicle braking system feedback rate parameter for controlling system braking, a sensor parameter comprehensive feedback control system feedback rate parameter for verifying the current state of the vehicle, and a temperature regulation control feedback rate parameter in a carriage.
As shown in fig. 4, the control curve is optimized for normal operating conditions with the purpose of: the vehicle driven by the user is prevented from jolting due to too fast acceleration, and riding experience of the user is guaranteed.
The control curve optimization in the step (5) under the normal operation condition is realized by the following specific steps:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading user driving parameters corresponding to the user according to an identification result;
the user driving parameters of the current user comprise: the ratio of the highest speed of the user driving the vehicle to the highest speed limit of the road section to be driven, the highest acceleration of the user driving the vehicle and the braking coefficient of the user driving the vehicle.
The braking coefficient when the user drives the vehicle is as follows: the user decreases the value of the ratio of the vehicle speed to the time taken to stop entering the braking command by entering the braking command.
(5.2) fitting the control process according to the control input of the user when the vehicle runs;
the fitting of the control process means: and fitting a control curve of a user, and reducing the change rate of power input or brake output under a non-emergency condition so as to ensure that the control curve of the vehicle does not change violently.
(5.3) judging whether the vehicle is in a normal running mode or not;
the control curve optimization is only suitable for normal operation conditions, and cannot be started in a collision early warning mode and a traffic jam mode.
And (5.4) recording the control habits of the user and optimizing the control feedback rate of the user.
Starting from an actual control mode of a user, if the vehicle power input parameter changes too violently in a normal operation mode, fitting a vehicle control curve according to a control scheme in a mode of giving priority to the control intention of the user, and performing control reminding and control mode guidance on the user so as to reduce the change rate of power control of the user. It is important to emphasize that for braking control of the vehicle, if a large braking output is detected, the system will first perform vehicle state confirmation and will not perform brake control curve fitting until it is determined that the vehicle is currently in a normal operating state. So as to improve the driving experience of the user under the condition of ensuring the safety of the user to the maximum extent. The fitting of the control process means: and fitting a control curve of a user, and reducing the change rate of power input or brake output under a non-emergency condition so as to ensure that the control curve of the vehicle does not change violently.
The present invention and its embodiments have been described above schematically, without limitation, and the embodiments of the present invention are shown in the drawings, and the actual structures are not limited thereto. Therefore, those skilled in the art should understand that they can easily and effectively design and modify the structure and embodiments of the present invention without departing from the spirit and scope of the present invention.
Claims (10)
1. A car assistant driving control method based on finger vein recognition is characterized by comprising the following steps:
(1) acquiring image information of a vehicle driver by using a finger vein acquisition device, and establishing a current user information database;
(2) initializing system control parameters for newly added users in a database, wherein the system control parameters comprise an automatic tracking driving mode parameter, an anti-collision parameter and a user driving parameter;
(3) recording the driving habits of the current user, and carrying out parameter fine adjustment on the actual operation of the current user according to parameter setting;
(4) carrying out feedback rate adjustment guidance according to real-time feedback of a user, actively correcting driving habits of the user and avoiding overshooting of feedback rate parameters;
(5) and realizing automatic tracking driving under the condition of vehicle traffic jam, collision early warning and emergency avoidance under the abnormal driving state and control curve optimization under the normal driving state based on the fine-tuned parameters.
2. The automobile assistant driving control method based on finger vein recognition as claimed in claim 1, wherein in step (1), the finger vein collection device comprises a finger vein collection device for obtaining finger vein image information; a finger vein storage unit for storing the finger vein image features; the finger vein comparison system is used for comparing and classifying according to the finger vein image information; a native database unit for adapting to small batches of users; a remote server processing unit for adapting to large-scale users.
3. The finger vein recognition-based automobile driving assistance control method according to claim 1, wherein in the step (2), the initialization of the newly added user information is to give a general-purpose control parameter to a newly registered user in the current database system and to provide an initial value for user parameter adjustment.
4. The automobile driving assistance control method based on finger vein recognition according to claim 1, wherein in the step (3), the parameter fine tuning means reading control system operation parameters, including a current user type, a feedback rate used by a current user for operating an automobile, a current user system operation actual feedback value, and a current automobile operation state, fine tuning the feedback rate parameters according to a current user instruction, verifying a feedback rate adjustment result, and fine tuning the system control parameters according to the fine tuned feedback rate parameters.
5. The automobile assistant driving control method based on finger vein recognition as claimed in claim 4, wherein the calculation formula of the system control parameter fine adjustment in step (3) is as follows:
the post-fine-tuning parameter is an instantaneous parameter (1+ (actual feedback value/feedback parameter) × feedback rate).
6. The automobile driving assistance control method based on the finger vein recognition according to claim 1, wherein in the step (4), the specific steps of the feedback rate adjustment guidance mode are as follows: and carrying out speed increasing control in a control mode of taking the target speed curve as a logarithmic curve according to the magnitude relation between the control parameters given by the user when the user operates the automobile currently and the control coefficients for adjusting the normal running speed set by the user currently.
7. The automobile driving assistance control method based on the finger vein recognition of claim 4, wherein the feedback rate parameters comprise an accelerator oil output control coefficient feedback rate parameter for controlling a process curve in a nonlinear form, a vehicle braking system feedback rate parameter for controlling a system brake, a sensor parameter comprehensive feedback control system feedback rate parameter for verifying a current state of a vehicle, and a temperature regulation control feedback rate parameter in a vehicle cabin.
8. The automobile assistant driving control method based on finger vein recognition according to claim 1, wherein in the step (5), the specific steps of realizing automatic tracking driving under the condition of vehicle traffic jam are as follows:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading the automatic tracking driving mode parameters corresponding to the user according to the identification result;
(5.2) monitoring the relative distance between the current vehicle and the vehicles in front and at the back when the vehicle runs, and judging the traffic jam condition;
(5.3) if the relative distance is smaller than the parameter limited by the traffic jam mode, the vehicle enters the traffic jam mode;
(5.4) in the vehicle traffic jam mode, monitoring the distance between the vehicle and the front vehicle and the rear vehicle in real time, and comparing and analyzing the distance with set parameters to prevent rear-end collision and rear-end collision;
and (5.5) the user actively jumps out of the traffic jam mode or automatically jumps out of the traffic jam mode according to the speed of the vehicle.
9. The automobile driving assistance control method based on the finger vein recognition as claimed in claim 1, wherein in the step (5), the steps of implementing the collision early warning and the collision avoidance in the abnormal driving state are as follows:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading anti-collision parameters corresponding to the user according to an identification result;
(5.2) monitoring the relative distance between the current vehicle and the front and rear vehicles when the vehicle runs, and judging whether the relative distance is smaller than the collision early warning distance;
and (5.3) after the relative distance is smaller than the early warning distance, the active control system carries out corresponding collision early warning and emergency avoidance.
10. The automobile driving assistance control method based on the finger vein recognition according to claim 1, wherein in the step (5), the step of optimizing the control curve in the normal driving state is:
(5.1) before the vehicle starts to run, identifying the current user through a finger vein acquisition device, and loading user driving parameters corresponding to the user according to an identification result;
(5.2) fitting the control process according to the control input of the user when the vehicle runs;
(5.3) judging whether the vehicle is in a normal running mode or not;
and (5.4) recording the control habits of the user and optimizing the control feedback rate of the user.
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