CN114312692A - Automobile AutoHold intelligent starting and stopping method based on parking scene learning - Google Patents
Automobile AutoHold intelligent starting and stopping method based on parking scene learning Download PDFInfo
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- CN114312692A CN114312692A CN202111340864.4A CN202111340864A CN114312692A CN 114312692 A CN114312692 A CN 114312692A CN 202111340864 A CN202111340864 A CN 202111340864A CN 114312692 A CN114312692 A CN 114312692A
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Abstract
The invention provides an automobile AutoHold intelligent starting and stopping method based on parking scene learning, which is suitable for automobile starting or parking scenes and comprises the following steps: s1, starting the vehicle or engaging the R gear during the running of the vehicle; s2, calculating the distance between the vehicle and the peripheral obstacles, and establishing a peripheral environment model; s3, judging the vehicle state and the corresponding scene according to the surrounding environment model; and S4, determining whether to inform the AutoHold executing mechanism to trigger according to the vehicle state and the corresponding scene. The method has the advantages that the parking scene is intelligently identified by utilizing the data of the automobile sensor, the triggering of the AutoHold is suspended under the scene, and the triggering of the AutoHold is recovered when the normal driving state is judged, so that the use experience of the automobile is greatly improved, and the safety and the operation convenience are improved.
Description
Technical Field
The invention relates to the technical field of vehicle control, in particular to an automobile AutoHold intelligent starting and stopping method based on parking scene learning.
Background
The automatic hold (automatic parking) of an automobile refers to an automatic braking function of the automobile, when the automatic braking function is started, for example, when the automobile stops at traffic lights and the like, the situation that the automobile slips and slides can be avoided, and an automobile owner does not need to manually pull up a hand brake. The AutoHold function of the automobile is poor in use experience in a parking scene, because the automobile can move in a small distance and high frequency in the parking scene, under the condition that the AutoHold function is effective, a user needs to frequently release the AutoHold through an accelerator, and particularly, the AutoHold function is very easy to operate by mistake, so that the accelerator output of the automobile is too large, and accidents are caused. When parking, a user manually closes the AutoHold, which is tedious, and especially, many vehicles are controlled by large-screen touch operation under the current large trend of vehicle intellectualization, which is very inconvenient.
The traditional hand brake needs to be started by manually releasing the hand brake or matching a skilled accelerator and a clutch by a driver during the slope starting. The automatic Hold automatic parking function provides accurate parking force through a gradient sensor by a controller, and when the automatic Hold automatic parking control unit is started, the parking control unit automatically releases parking brake when driving force is larger than driving resistance through calculation through information provided by a clutch distance sensor, a clutch kneading speed sensor, an accelerator pedal sensor and the like, so that the automobile can be started stably. Even if the plug running in the urban area stops at ordinary times, the corresponding automatic parking function can be started as long as the AutoHold function is started. When the static state needs to be relieved, the brake can be relieved by only slightly pressing the accelerator. The main function of the automobile reversing radar which is an ultrasonic sensor is to send and receive ultrasonic signals, then the signals are input into the host and displayed through the display device, and when an automobile reverses, the ultrasonic reversing radar detects the distance from the tail of the automobile to an obstacle by adopting an ultrasonic ranging principle, so that the automobile reversing radar is an automobile parking auxiliary device. At present, a main stream vehicle is generally provided with a plurality of (including a vehicle head, a vehicle tail and a vehicle side surface) ultrasonic sensors.
The invention discloses an electronic parking brake system with an AUTOHOLD function and a brake method thereof in Chinese patent literature, wherein the publication number is CN 101934737A. The invention effectively solves the problem that the driver needs to manually operate and park/release frequently when driving on the urban roads. And the temperature of the brake disc is reduced, the parking braking force is reduced, and the brake disc is easy to slide down a slope. But does not involve automatic start-up and shut-down of the AutoHold under different usage scenarios.
Disclosure of Invention
The invention solves the problem that the AutoHold function is more complicated to be turned on or turned off manually through a physical switch or touch setting in the prior art, and provides an automobile AutoHold intelligent starting and stopping method based on parking scene learning.
In order to achieve the purpose, the invention adopts the following technical scheme: an automobile AutoHold intelligent starting and stopping method based on parking scene learning is suitable for a vehicle starting or parking scene and comprises the following steps:
s1, starting the vehicle or engaging the R gear during the running of the vehicle;
s2, calculating the distance between the vehicle and the peripheral obstacles, and establishing a peripheral environment model;
s3, judging the vehicle state and the corresponding scene according to the surrounding environment model;
and S4, determining whether to inform the AutoHold executing mechanism to trigger according to the vehicle state and the corresponding scene.
In the invention, after the vehicle is started and driven out, the distance information is monitored by using the ultrasonic radar, a peripheral environment model is established by using a plurality of groups of ultrasonic radar distance data, the peripheral environment model judges whether obstacles or vehicles exist at the front side and the rear side of the vehicle according to the judgment basis of 0.5 m, four states of a front vehicle and a rear vehicle, a parking state are identified through the distance model, in this state, the vehicle notifies the AutoHold actuator through the host system not to trigger logic, therefore, the user does not need to frequently release the AutoHold through the accelerator, the accident caused by overlarge accelerator output of the vehicle due to misoperation is prevented, the manual switching operation on and off operation on the AutoHold is not needed, the practical experience of the vehicle is greatly improved, and the AutoHold is intelligently controlled to be triggered according to the data detection and analysis of the ultrasonic radar.
Preferably, in step S2, a plurality of ultrasonic radars are respectively disposed on the front side and the rear side of the vehicle, the real-time distance data between the plurality of ultrasonic radars and the peripheral obstacle disposed on the front side and the rear side of the vehicle are acquired, and the real-time distance data between the plurality of ultrasonic radars and the peripheral obstacle is stored in the peripheral environment model for comparison and determination.
In the invention, a plurality of ultrasonic radars monitor the distance information from the peripheral obstacles of the vehicle in various states in real time, the distance information is stored in the peripheral environment model according to the sequence of the timestamps, and the peripheral environment model has deep learning and data error investigation functions and can filter the obviously wrong distance information by referring to the past distance information data so as to better and more accurately judge the step S3.
Preferably, the specific vehicle states in the vehicle starting scenario in step S3 mainly include:
the front and rear vehicle states: the real-time distance between the two or more vehicle front ultrasonic radars and the peripheral obstacles is less than or equal to 0.5 meter, and the real-time distance between the two or more vehicle rear ultrasonic radars and the peripheral obstacles is less than or equal to 0.5 meter;
the state that the front vehicle is in a state of no vehicle: the real-time distances between the two or more vehicle front ultrasonic radars and the peripheral obstacles are less than or equal to 0.5 m, and the real-time distances between the plurality of vehicle rear ultrasonic radars and the peripheral obstacles are all greater than 0.5 m;
the state of no vehicle in front and vehicle in back: the real-time distances between the plurality of vehicle front ultrasonic radars and the peripheral obstacles are all larger than 0.5 meter, and the real-time distances between the two or more vehicle rear ultrasonic radars and the peripheral obstacles are smaller than or equal to 0.5 meter;
the front and rear non-vehicle states: the real-time distances between the plurality of vehicle front ultrasonic radars and the peripheral obstacles are all larger than 0.5 meter, and the real-time distances between the plurality of vehicle rear ultrasonic radars and the peripheral obstacles are all larger than 0.5 meter.
In the invention, four states of a front vehicle and a rear vehicle, a front vehicle and a rear vehicle are identified and judged by the surrounding environment model, wherein the distance of 0.5 m is the judgment basis, and when the obstacle is within 0.5 m, the vehicle presence condition is simulated, so that the safety is higher.
Preferably, the front and rear vehicle-presence state and the front and rear vehicle-absence state are determined as parking scenes; the front-vehicle-free and rear-vehicle-free state is judged to be a parking scene when the vehicle is in an R gear during running, and the front-vehicle-free and rear-vehicle-free state is judged to be a non-parking scene.
In the invention, when the vehicle is started, the parking scene is judged when the real-time distances between the ultrasonic radar on the front side of the vehicle and the peripheral obstacles are within the range of 0.5 m.
Preferably, in the step S3, the specific determination process when the R range is engaged while the vehicle is running is to acquire real-time distance data of a plurality of ultrasonic radars on the rear side of the vehicle and surrounding obstacles, and determine a parking scene when the real-time distances between two or more ultrasonic radars on the rear side of the vehicle and surrounding obstacles are less than or equal to 0.5 m.
In the invention, when the R gear is engaged during the running of the vehicle, only the real-time distance between the ultrasonic radar at the rear side of the vehicle and the peripheral obstacles needs to be judged.
Preferably, in step S4, if the scene corresponding to the vehicle is a parking scene, the vehicle notifies the AutoHold executing mechanism through the host system that the logic is not triggered; and if the scene corresponding to the vehicle is a non-parking scene, the vehicle triggers the AutoHold executing mechanism.
According to the invention, after a parking scene is judged, the triggering of the AutoHold is suspended in the scene, the use experience of the vehicle is greatly improved, and the triggering of the AutoHold is recovered when the non-parking state, namely the normal driving state, is judged.
Preferably, after the vehicle informs the AutoHold executing mechanism of not triggering logic through the host system, and the vehicle automatically exits from the parking scene after the vehicle speed is judged to be more than 25 km/h.
In the invention, the threshold is also set while the judgment of the surrounding environment model is satisfied, namely, after the vehicle speed reaches 25km/h, the vehicle is in a non-parking scene, and the AutoHold is triggered.
Preferably, the specific number of the plurality of ultrasonic radars arranged on the front side and the rear side of the vehicle is 8, and the number of the plurality of ultrasonic radars arranged on the front side and the rear side of the vehicle is 4.
In the present invention, the vehicle front ultrasonic radars detect the nearest peripheral obstacle in front of the nearest vehicle, and the vehicle rear ultrasonic radars detect the nearest peripheral obstacle behind the nearest vehicle, thereby ensuring the detection of the nearest object.
The invention has the beneficial effects that: detecting and calculating the distance between a vehicle and a peripheral obstacle by using the data of a sensor of the vehicle, namely ultrasonic radar data, and establishing a peripheral environment model; the parking scene of the vehicle is intelligently judged according to the surrounding environment model, and the triggering of the AutoHold is suspended in the scene, so that the use experience of the vehicle is greatly improved, and the safety and the operation convenience are improved.
Drawings
FIG. 1 is a diagram of a practical application scenario of the present invention;
FIG. 2 is a flow chart of a vehicle launch scenario of the present invention;
FIG. 3 is a flow chart of a vehicle parking scenario of the present invention;
1. ultrasonic radar 2, peripheral obstacles.
Detailed Description
Example (b):
the embodiment provides an automobile AutoHold intelligent start-stop method based on parking scene learning, referring to fig. 1 to 3, the automobile AutoHold intelligent start-stop method based on parking scene learning is applicable to both automobile start or parking scenes, and mainly includes the following four steps: step S1, starting the vehicle or engaging the R gear during the running of the vehicle; the method can be carried out when the vehicle is in a D gear or an R gear.
Step S2, calculating the distance between the vehicle and the peripheral obstacle 2, and establishing a peripheral environment model; in this step, referring to fig. 1, the plurality of ultrasonic radars 1 are respectively disposed on the front side and the rear side of the vehicle, the real-time distance data between the plurality of ultrasonic radars 1 and the peripheral obstacle 2 is obtained through detection and calculation by the ultrasonic radars, and finally, the real-time distance data between the ultrasonic radars 1 and the peripheral obstacle 2 is stored in the peripheral environment model, so that the vehicle state and the vehicle scene can be conveniently determined.
Step S3, judging the vehicle state and the corresponding scene according to the surrounding environment model; in the present embodiment, the real-time distance of the ultrasonic radar 1 from the peripheral obstacle 2 is equivalent to the distance of the vehicle from the peripheral obstacle 2. Judging whether the distance between the peripheral barrier 2 and the vehicle is less than or equal to 0.5 m according to the peripheral environment model; two or more than two ultrasonic radars 1 and peripheral obstacles 2 are arranged on the front side and the rear side of the vehicle, and the front and the rear vehicle states are in a real-time distance within the range of 0.5 m; two or more than two ultrasonic radars 1 and peripheral obstacles 2 are arranged on the front side of the vehicle, the real-time distance is within the range of 0.5 m, and the state that the vehicle is not in a state that the vehicle exists in the front and does not exist behind the vehicle is realized when the real-time distance between all the ultrasonic radars 1 and the peripheral obstacles 2 on the rear side of the vehicle exceeds the range of 0.5 m; when the real-time distances between all the ultrasonic radars 1 and the peripheral obstacles 2 on the front side of the vehicle exceed the range of 0.5 m, and the real-time distances between two or more ultrasonic radars 1 and peripheral obstacles 2 on the rear side of the vehicle are within the range of 0.5 m, the vehicle is in a state that the vehicle is not in front of the vehicle and the vehicle is in back of the vehicle; when the real-time distances between all the ultrasonic radars 1 and the peripheral obstacles 2 on the front and rear sides of the vehicle exceed 0.5 m, the vehicle is in a front-rear non-vehicle state. In a vehicle starting scene, a parking scene comprises a front and rear vehicle state and a rear vehicle state, the two states are judged as the parking scene, the front and rear vehicle state is judged as the parking scene under the condition that the vehicle is in the R gear, and the front and rear vehicle state is a non-parking scene. When the vehicle is in the R gear during running, only the ultrasonic radar 1 at the rear side of the vehicle needs to be judged, and the parking scene is determined when two or more ultrasonic radars 1 and peripheral obstacles 2 at the rear side of the vehicle are within the real-time distance of 0.5 m.
Step S4, determining whether to notify the AutoHold actuator of triggering according to the vehicle state and the corresponding scenario. Under a parking scene, the master control informs the AutoHold module not to trigger logic; and in the non-parking scene, the AutoHold trigger is recovered. Meanwhile, a vehicle speed limit is set in the surrounding environment model, and if the vehicle speed exceeds 25km/h, the parking scene is recovered to be a non-parking scene.
Referring to fig. 1, a distribution diagram of the vehicle ultrasonic radar and the surrounding obstacles shows an arrangement of four front and four back, and the front side and the rear side of the radar are in one-to-one correspondence. In this embodiment, four ultrasonic radars 1 are installed on the front side of the vehicle, four ultrasonic radars 1 are also installed on the rear side of the vehicle, and eight ultrasonic radars 1 are installed on the front side and the rear side of the vehicle, so that the real-time distance between the vehicle and the surrounding obstacles can be conveniently detected and calculated.
In the invention, after the vehicle is started and driven out, the distance information is monitored by using the ultrasonic radar, a peripheral environment model is established by using a plurality of groups of ultrasonic radar distance data, the peripheral environment model judges whether obstacles or vehicles exist at the front side and the rear side of the vehicle according to the judgment basis of 0.5 m, four states of a front vehicle and a rear vehicle, a parking state are identified through the distance model, in this state, the vehicle notifies the AutoHold actuator through the host system not to trigger logic, therefore, the user does not need to frequently release the AutoHold through the accelerator, the accident caused by overlarge accelerator output of the vehicle due to misoperation is prevented, the manual switching operation on and off operation on the AutoHold is not needed, the practical experience of the vehicle is greatly improved, and the AutoHold is intelligently controlled to be triggered according to the data detection and analysis of the ultrasonic radar.
In the invention, a plurality of ultrasonic radars monitor the distance information from the peripheral obstacles of the vehicle in various states in real time, the distance information is stored in the peripheral environment model according to the sequence of the timestamps, and the peripheral environment model has deep learning and data error investigation functions and can filter the obviously wrong distance information by referring to the past distance information data so as to better and more accurately judge the step S3.
In the invention, four states of a front vehicle and a rear vehicle, a front vehicle and a rear vehicle are identified and judged by the surrounding environment model, wherein the distance of 0.5 m is the judgment basis, and when the obstacle is within 0.5 m, the vehicle presence condition is simulated, so that the safety is higher.
In the invention, when the vehicle is started, the parking scene is judged when the real-time distances between the ultrasonic radar on the front side of the vehicle and the peripheral obstacles are within the range of 0.5 m.
In the invention, when the R gear is engaged during the running of the vehicle, only the real-time distance between the ultrasonic radar at the rear side of the vehicle and the surrounding obstacles needs to be determined, and the data at the front side of the vehicle is not needed.
According to the invention, after a parking scene is judged, the triggering of the AutoHold is suspended in the scene, the use experience of the vehicle is greatly improved, and the triggering of the AutoHold is recovered when the non-parking state, namely the normal driving state, is judged.
In the invention, the threshold is also set while the judgment of the surrounding environment model is satisfied, namely, after the vehicle speed reaches 25km/h, the vehicle is in a non-parking scene, and the AutoHold is triggered.
In the present invention, the vehicle front ultrasonic radars detect the nearest peripheral obstacle in front of the nearest vehicle, and the vehicle rear ultrasonic radars detect the nearest peripheral obstacle behind the nearest vehicle, thereby ensuring the detection of the nearest object.
At present, the auto hold configuration of an automobile triggers an automatic parking state according to the braking action of a user under the condition of normal use of the automobile, an automobile owner can turn on or off the function through a physical switch or touch setting, and the automatic parking function is relatively complicated in an actual use scene, such as parking (if the automatic parking function needs to be turned off before parking and then manually turned on after parking).
The working principle of the invention is as follows: detecting and calculating the distance between a vehicle and a peripheral obstacle by using the data of a sensor of the vehicle, namely ultrasonic radar data, and establishing a peripheral environment model; the method comprises the steps of judging the vehicle and the corresponding vehicle scene according to the surrounding environment model, mainly comprising a parking scene and a non-parking scene, and suspending the triggering of the AutoHold in the parking scene, so that the use experience of the vehicle is greatly improved, and the safety and the operation convenience are improved.
The above embodiments are further illustrated and described in order to facilitate understanding of the invention, and no unnecessary limitations are to be understood therefrom, and any modifications, equivalents, and improvements made within the spirit and principle of the invention should be included therein.
Claims (8)
1. An automobile AutoHold intelligent starting and stopping method based on parking scene learning is suitable for a vehicle starting or parking scene and is characterized by comprising the following steps:
s1, starting the vehicle or engaging the R gear during the running of the vehicle;
s2, calculating the distance between the vehicle and the peripheral obstacles, and establishing a peripheral environment model;
s3, judging the vehicle state and the corresponding scene according to the surrounding environment model;
and S4, determining whether to inform the AutoHold executing mechanism to trigger according to the vehicle state and the corresponding scene.
2. The automobile AutoHold intelligent start-stop method based on parking scene learning as claimed in claim 1, wherein in step S2, a plurality of ultrasonic radars are respectively arranged on the front side and the rear side of the automobile, real-time distance data between the plurality of ultrasonic radars and peripheral obstacles arranged on the front side and the rear side of the automobile are obtained, and the real-time distance data between the plurality of ultrasonic radars and the peripheral obstacles are stored in a peripheral environment model for comparison and judgment.
3. The automobile AutoHold intelligent start-stop method based on parking scene learning as claimed in claim 1, wherein the specific vehicle states in the vehicle start scene in step S3 mainly include:
the front and rear vehicle states: the real-time distance between the two or more vehicle front ultrasonic radars and the peripheral obstacles is less than or equal to 0.5 meter, and the real-time distance between the two or more vehicle rear ultrasonic radars and the peripheral obstacles is less than or equal to 0.5 meter;
the state that the front vehicle is in a state of no vehicle: the real-time distances between the two or more vehicle front ultrasonic radars and the peripheral obstacles are less than or equal to 0.5 m, and the real-time distances between the plurality of vehicle rear ultrasonic radars and the peripheral obstacles are all greater than 0.5 m;
the state of no vehicle in front and vehicle in back: the real-time distances between the plurality of vehicle front ultrasonic radars and the peripheral obstacles are all larger than 0.5 meter, and the real-time distances between the two or more vehicle rear ultrasonic radars and the peripheral obstacles are smaller than or equal to 0.5 meter;
the front and rear non-vehicle states: the real-time distances between the plurality of vehicle front ultrasonic radars and the peripheral obstacles are all larger than 0.5 meter, and the real-time distances between the plurality of vehicle rear ultrasonic radars and the peripheral obstacles are all larger than 0.5 meter.
4. The automobile AutoHold intelligent start-stop method based on parking scene learning as claimed in claim 3, wherein the front and rear vehicle-presence state and the front and rear vehicle-absence state are determined as parking scenes; the front-vehicle-free and rear-vehicle-free state is judged to be a parking scene when the vehicle is in an R gear during running, and the front-vehicle-free and rear-vehicle-free state is judged to be a non-parking scene.
5. The method as claimed in claim 1, wherein the step S3 is performed in a specific judgment process when the vehicle is in the R-range during driving, wherein the method comprises obtaining real-time distance data between a plurality of ultrasonic radars and surrounding obstacles on the rear side of the vehicle, and determining a parking scene when the real-time distances between two or more ultrasonic radars and surrounding obstacles on the rear side of the vehicle are less than or equal to 0.5 m.
6. The automobile AutoHold intelligent start-stop method based on parking scene learning as claimed in claim 1, wherein in step S4, if the scene corresponding to the automobile is a parking scene, the automobile informs the AutoHold executing mechanism not to trigger logic through the host system; and if the scene corresponding to the vehicle is a non-parking scene, the vehicle triggers the AutoHold executing mechanism.
7. The automobile AutoHold intelligent start-stop method based on parking scene learning as claimed in claim 6, wherein the automobile automatically exits from the parking scene after the host system notifies the AutoHold executing mechanism not to trigger logic and the speed is judged to be greater than 25 km/h.
8. The automobile AutoHold intelligent start-stop method based on parking scene learning as claimed in claim 2, wherein the specific number of the plurality of ultrasonic radars arranged on the front side and the rear side of the automobile is 8, and the number of the ultrasonic radars arranged on the front side and the rear side of the automobile is 4 respectively.
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