CN116923389A - Vehicle control method and device, storage medium and vehicle - Google Patents
Vehicle control method and device, storage medium and vehicle Download PDFInfo
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0953—Predicting travel path or likelihood of collision the prediction being responsive to vehicle dynamic parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/50—Barriers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/80—Spatial relation or speed relative to objects
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Abstract
The invention discloses a vehicle control method and device, a storage medium and a vehicle. The method comprises the following steps: acquiring target image data acquired by a vehicle in a detection area; determining at least one target object in the target image data, and acquiring at least one attribute information of the target object; inputting the attribute information into a Kalman filtering model for filtering processing to obtain a target state value of a target object, wherein the target state value is used for representing a measured value of a sensor of a vehicle; carrying out fusion processing on the target state value to obtain a fusion result, wherein the fusion result is used for representing whether the target object is an obstacle relative to the vehicle in the detection area; and responding to the fusion result meeting a preset threshold value, determining that the vehicle has an obstacle in the detection area, and controlling the vehicle so as to avoid the obstacle. The invention solves the technical problem of lower efficiency of vehicle decision control.
Description
Technical Field
The present invention relates to the field of vehicles, and in particular, to a vehicle control method and apparatus, a storage medium, and a vehicle.
Background
At present, in the current obstacle detection process, a single sensor is adopted to detect the obstacle, the accuracy is lower, while in the current detection process, a plurality of sensors are adopted to detect the obstacle, but for detection under a plurality of complex scenes, decision control on the vehicle is inaccurate, most of documents only aim at active situations, only front obstacles are considered, so that emergency braking is carried out, whether a rear vehicle is influenced by the emergency braking of the front vehicle is not considered, and in passive situations, if the rear vehicle is not controlled, the technical problem of lower efficiency of the decision control of the vehicle is caused.
Aiming at the technical problem that the vehicle decision control efficiency is low, no effective solution is proposed at present.
Disclosure of Invention
The embodiment of the invention provides a vehicle control method and device, a storage medium and a vehicle, which are used for at least solving the technical problem of low vehicle decision control efficiency.
According to an aspect of an embodiment of the present invention, there is provided a control method of a vehicle. The method may include: acquiring target image data acquired by a vehicle in a detection area; determining at least one target object in the target image data, and acquiring at least one attribute information of the target object; inputting the attribute information into a Kalman filtering model for filtering processing to obtain a target state value of a target object, wherein the target state value is used for representing a measured value of a sensor of a vehicle; carrying out fusion processing on the target state value to obtain a fusion result, wherein the fusion result is used for representing whether the target object is an obstacle relative to the vehicle in the detection area; and responding to the fusion result meeting a preset threshold value, determining that the vehicle has an obstacle in the detection area, and controlling the vehicle so as to avoid the obstacle.
Optionally, performing fusion processing on the target state value to obtain a fusion result, including: acquiring a weight value of a target state value; and determining a fusion result based on the product of the weight value and the target state value.
Optionally, in response to the fusion result meeting a preset threshold, determining that the vehicle has an obstacle in the detection area, and controlling the vehicle so that the vehicle avoids the obstacle, including: determining the direction of the obstacle relative to the vehicle, and acquiring the distance between the vehicle and the obstacle; adjusting gear information, acceleration information and throttle information of the vehicle in response to the obstacle being in front of, to the left of or to the right of the vehicle, the distance being less than a first preset distance and the distance being greater than a second preset distance, and transmitting the gear information, the acceleration information and the throttle information to a rear vehicle of the vehicle, wherein the second preset distance is less than the first preset distance; and in response to the obstacle being in front of, to the left of, or to the right of the vehicle and the distance being less than a second preset distance, performing a braking process on the vehicle and transmitting braking information of the vehicle to a rear vehicle.
Optionally, in response to the fusion result meeting the preset threshold, determining that the vehicle has an obstacle in the detection area, and controlling the vehicle so as to avoid the obstacle, and further including: adjusting gear information and throttle information in response to the obstacle being at the rear of the vehicle and the distance being less than a first preset distance and the distance being greater than a second preset distance, and transmitting the gear information and the throttle information to the rear vehicle; and acquiring feedback information sent by the rear vehicle in response to the gear information and the throttle information, wherein the feedback information is used for representing that an automatic driving system of the rear vehicle works normally.
Optionally, in addition to acquiring feedback information sent by the rear vehicle in response to the gear information and the throttle information, the control method of the vehicle further includes: the rear vehicle is subjected to a braking process.
Optionally, the control method of the vehicle further includes: and in response to the fusion result not meeting the preset threshold, determining that the vehicle has no obstacle in the detection area, and maintaining gear information, acceleration information and throttle information of the vehicle.
According to an aspect of an embodiment of the present invention, there is provided a control device of a vehicle. The apparatus may include: the acquisition unit is used for acquiring target image data acquired by the vehicle in the detection area; the determining unit is used for determining at least one target object in the target image data and acquiring at least one attribute information of the target object; the filtering unit is used for inputting the attribute information into the Kalman filtering model for filtering processing to obtain a target state value of a target object, wherein the target state value is used for representing a measured value of a sensor of the vehicle; the fusion unit is used for carrying out fusion processing on the target state value to obtain a fusion result, wherein the fusion result is used for representing whether the target object is an obstacle relative to the vehicle in the detection area; and the control unit is used for responding to the fusion result to meet a preset threshold value, determining that the vehicle has an obstacle in the detection area and controlling the vehicle so as to avoid the obstacle.
According to another aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium. The computer readable storage medium includes a stored program, wherein the device in which the computer readable storage medium is controlled to execute the control method of the vehicle of the embodiment of the present invention when the program runs.
According to another aspect of an embodiment of the present invention, there is also provided a processor. The processor is used for running a program, wherein the program is executed by the processor to execute the control method of the vehicle according to the embodiment of the invention.
According to another aspect of the embodiment of the present invention, there is also provided a vehicle for executing the control method of the vehicle of the embodiment of the present invention.
In the embodiment of the invention, the target image data acquired by the vehicle in the detection area is acquired, at least one target object can be determined in the target image data, at least one attribute information of the target object is acquired, the acquired attribute information is input into the Kalman filtering model for filtering processing, the target state value of the target object can be obtained, namely, the measured value of the sensor can be obtained, the measured value of the sensor is subjected to fusion processing, the fusion result can be obtained, whether the fusion result meets the preset threshold value or not is judged, if the fusion result meets the preset threshold value, the condition that the vehicle has an obstacle in the detection area is determined, and the vehicle is controlled so as to avoid the obstacle, thereby achieving the aim of accurately detecting the target obstacle, solving the technical problem of lower vehicle decision control efficiency and realizing the technical effect of improving the vehicle decision control efficiency.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
fig. 1 is a flowchart of a control method of a vehicle according to an embodiment of the present application;
FIG. 2 is a flow chart of a vehicle control method based on obstacle detection in accordance with an embodiment of the application;
FIG. 3 is a schematic diagram of a vehicle control system based on obstacle detection in accordance with an embodiment of the application;
fig. 4 is a schematic view of a control device of a vehicle according to an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, shall fall within the scope of the application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present invention, there is provided a control method of a vehicle, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of a control method of a vehicle according to an embodiment of the present invention, which may include the steps of:
step S101, acquiring target image data acquired by a vehicle in a detection area.
In the technical solution provided in the step S101 of the present invention, the detection area may be used to represent an area centered on the vehicle and having a preset distance as a radius, and the target image data may be acquired by an image capturing module of the vehicle, where the preset distance may be taken from 3m to 5m to ensure the sharpness and validity of the acquired target image data, and the image capturing module may include, but is not limited to: video cameras, and the like, are only examples, and are not particularly limited.
Alternatively, target image data acquired by the vehicle in the detection area may be acquired, for example, by the image capturing module, the image data in the detection area may be subjected to noise removal processing, and the noise-removed image data may be determined as target image data.
Step S102, at least one target object is determined in the target image data, and at least one attribute information of the target object is acquired.
In the technical solution provided in the step S102 of the present invention, the target object may include, but is not limited to: the above attribute information may be used to represent characteristics of the target object, such as, but not limited to, persons, vehicles, buildings, obstacles, etc. in the target image data: position information, speed information, etc.
Optionally, after the target image data acquired by the vehicle in the detection area is acquired, at least one target object is determined in the target image data, and at least one attribute information of the target object is acquired, for example, the at least one target object may be identified in the target image data by an image identification technology, and after the at least one target object is identified, the at least one attribute information of the target object, that is, the position information and the speed information of the target object may be acquired by a monitoring module of the vehicle.
Alternatively, the monitoring module of the vehicle may include: at least one radar arranged around the vehicle body, through which attribute information such as a relative distance, an angle, a speed, and the like of the target object and the own vehicle can be acquired.
Step S103, inputting the attribute information into a Kalman filtering model for filtering processing to obtain a target state value of a target object.
In the solution provided in the above step S103 of the present invention, the above target state value may be used to characterize the measured value of the sensor of the vehicle.
Optionally, after determining at least one target object in the target image data and acquiring at least one attribute information of the target object, inputting the attribute information into a kalman filter model for filtering processing to obtain a target state value of the target object, for example, filtering processing is performed on the attribute information according to the following formula, so as to obtain a measured value of a sensor of the vehicle:
X(k+1)＝AX(k)+BM(k)+ω(k)
(1)
Z(k)＝HX(k)+N(k)
(2)
Wherein X (k) can be used to represent the state quantity of the vehicle control system at time k, M (k) can be used to represent the control quantity of the vehicle control system at time k, Z (k) can be used to represent the observed value of the vehicle control system at time k, A can be used to represent the state transition matrix, B can be used to represent the control matrix, H can be used to represent the observed matrix, ω (k) can be used to represent the process noise of the vehicle control system at time k, and N (k) can be used to represent the observed noise of the vehicle control system at time k.
Step S104, fusion processing is carried out on the target state value, and a fusion result is obtained.
In the solution provided in the above step S104 of the present invention, the above fusion result may be used to characterize whether the target object is an obstacle in the detection area relative to the vehicle.
Optionally, after the attribute information is input into the kalman filter model to perform filtering processing to obtain a target state value of the target object, the target state value is subjected to fusion processing to obtain a fusion result, for example, the measured value of the sensor is subjected to fusion processing according to a weight, so that the fusion result can be obtained, wherein the weight can be in one-to-one correspondence with the sensor.
Alternatively, if the number of sensors of the vehicle is n (n is a positive integer), n weight values exist, and fusion processing is performed on the measured values of the sensors according to the n weight values, a fusion result may be obtained, so as to determine whether the target object is an obstacle with respect to the vehicle in the detection area.
Step S105, in response to the fusion result satisfying the preset threshold, determining that the vehicle has an obstacle in the detection area, and controlling the vehicle so that the vehicle avoids the obstacle.
In the technical solution provided in the step S105 of the present application, the preset threshold may be used to determine whether the vehicle has an obstacle in the detection area.
Optionally, after the target state value is subjected to fusion processing to obtain a fusion result, determining that an obstacle exists in the detection area in response to the fusion result meeting a preset threshold, and controlling the vehicle to avoid the obstacle, for example, judging whether the obtained fusion result meets the preset threshold, if the fusion result meets the preset threshold, determining that the vehicle exists in the detection area, and controlling the vehicle to avoid the obstacle, and if the fusion result does not meet the preset threshold, determining that the vehicle does not exist in the detection area, and controlling the vehicle without the need of maintaining the current running state of the vehicle.
In the application, the step S101 to the step S105 are performed to obtain the target image data acquired by the vehicle in the detection area, at least one target object can be determined in the target image data, at least one attribute information of the target object is acquired, the acquired attribute information is input into the kalman filter model for filtering processing, the target state value of the target object can be obtained, that is, the measured value of the sensor can be obtained, the fusion processing is performed to the measured value of the sensor, the fusion result can be obtained, whether the fusion result meets the preset threshold value or not is judged, if the fusion result meets the preset threshold value, the existence of the obstacle in the detection area of the vehicle is determined, and the vehicle is controlled, so that the vehicle avoids the obstacle, thereby achieving the aim of accurately detecting the target obstacle, solving the technical problem of lower efficiency of vehicle decision control, and realizing the technical effect of improving the efficiency of vehicle decision control.
The above-described method of this embodiment is further described below.
As an optional embodiment, step S104, performing fusion processing on the target state value to obtain a fusion result, includes: acquiring a weight value of a target state value; and determining a fusion result based on the product of the weight value and the target state value.
In this embodiment, the weights may be in one-to-one correspondence with the sensors, and the sum of the weight values is 1.
Optionally, after the attribute information is input into the kalman filter model to perform filtering processing to obtain a target state value of the target object, if n target state values (n is a positive integer) exist, n weight values exist, product operation is performed on each target state value and the weight value corresponding to the target state value to obtain n products, and the sum of the n products is determined as a fusion result.
Alternatively, the measurement of sensor i at time k may be expressed as x i (k) The measurement of sensor i at time k can be calculated by:
x i (k)＝Z i (k)+ε i (k)
(3)
wherein Z is i (k) Can be used to represent the measured estimate of sensor i at time k, ε i (k) Can be used to represent the noise, ω, of sensor i at time k i (k) May be used to represent the weight value of sensor i and R (k) may be used to represent the fusion result.
As an optional embodiment, step S105, in response to the fusion result satisfying the preset threshold, determines that the vehicle has an obstacle in the detection area, and controls the vehicle so that the vehicle avoids the obstacle, includes: determining the direction of the obstacle relative to the vehicle, and acquiring the distance between the vehicle and the obstacle; adjusting gear information, acceleration information and throttle information of the vehicle in response to the obstacle being in front of, to the left of or to the right of the vehicle, the distance being less than a first preset distance and the distance being greater than a second preset distance, and transmitting the gear information, the acceleration information and the throttle information to a rear vehicle of the vehicle; and in response to the obstacle being in front of, to the left of, or to the right of the vehicle and the distance being less than a second preset distance, performing a braking process on the vehicle and transmitting braking information of the vehicle to a rear vehicle.
In this embodiment, the second preset distance is smaller than the first preset distance, where the first preset distance may be used to determine whether the distance between the vehicle and the obstacle is safe, and the second preset distance may be used to determine whether the vehicle performs braking processing.
Optionally, if it is determined that the vehicle has an obstacle in the detection area, the direction in which the obstacle is located relative to the vehicle may be determined by the azimuth sensor, the distance between the vehicle and the obstacle may be acquired by the radar, a determination is made as to whether the obstacle is in front of, to the left of, or to the right of the vehicle, and a relationship between the distance and a first preset distance and a second preset distance is determined, if the obstacle is in front of, to the left of, or to the right of the vehicle, the distance is smaller than the first preset distance and the distance is greater than the second preset distance, gear information, acceleration information, and accelerator information of the vehicle are adjusted, and the gear information, the acceleration information, and the accelerator information are transmitted to a vehicle behind the vehicle, and if the obstacle is in front of, to the left of, or to the right of the vehicle, and the distance is smaller than the second preset distance, braking processing is performed on the vehicle, and braking information of the vehicle is transmitted to the vehicle behind.
Optionally, if the obstacle is located in front of, to the left of, or to the right of the vehicle and the distance is greater than the first preset distance, the vehicle is not controlled at all, and the normal running state is maintained.
As an optional embodiment, step S105, in response to the fusion result satisfying the preset threshold, determines that the vehicle has an obstacle in the detection area, and controls the vehicle so that the vehicle avoids the obstacle, further includes: adjusting gear information and throttle information in response to the obstacle being in the rear of the vehicle, the distance being less than a first preset distance and the distance being greater than a second preset distance, and transmitting the gear information and the throttle information to the rear vehicle; feedback information sent by the rear vehicle in response to the gear information and the throttle information is acquired.
In this embodiment, the feedback information may be used to characterize that the autopilot system of the rear vehicle is working properly.
Optionally, if it is determined that the vehicle has an obstacle in the detection area, determining whether the obstacle is behind the vehicle, and determining a relationship between the distance and the first preset distance and the second preset distance, and if the obstacle is behind the vehicle, the distance is smaller than the first preset distance and the distance is greater than the second preset distance, adjusting the gear information and the throttle information, and transmitting the gear information and the throttle information to the rear vehicle, and after the rear vehicle receives the gear information and the throttle information, the rear vehicle transmits feedback information to the vehicle.
Optionally, if the obstacle is located behind the vehicle and the distance is smaller than the second preset distance, it is determined that an abnormal condition occurs in an automatic driving system of the rear vehicle, an alarm mode is immediately started, corresponding operation processing is executed, meanwhile, the following vehicle can know the condition of the front road section in real time through information forwarding of each node vehicle, and therefore a reasonable travel route is selected, and travel time is saved.
As an alternative embodiment, in addition to acquiring feedback information sent by the rear vehicle in response to the gear information and the throttle information, the control method of the vehicle further includes: the rear vehicle is subjected to a braking process.
In this embodiment, if the rear vehicle does not transmit the feedback information to the own vehicle, the own vehicle does not acquire the feedback information, and determines that the automatic driving system of the rear vehicle is malfunctioning, and immediately starts the warning mode, which is operated as follows: the information of the fault vehicle is sent to the traffic police center through a fifth generation mobile communication (5G) module, and a background system of the traffic police center can directly and forcedly brake the fault vehicle, so that traffic accidents caused by uncontrolled vehicles are prevented, and personal safety of personnel in the vehicle can be guaranteed.
Alternatively, the information of the faulty vehicle may include, but is not limited to: the position of the fault vehicle, the license plate number of the fault vehicle, the gear of the fault vehicle, the throttle state of the fault vehicle and the like.
As an alternative embodiment, the control method of the vehicle further includes: and in response to the fusion result not meeting the preset threshold, determining that the vehicle has no obstacle in the detection area, and maintaining gear information, acceleration information and throttle information of the vehicle.
In this embodiment, whether the obtained fusion result meets the preset threshold value is determined, if the fusion result does not meet the preset threshold value, it is determined that no obstacle exists in the detection area of the vehicle, and no control is required to be performed on the vehicle, so that gear information, acceleration information and throttle information of the vehicle are maintained.
According to the embodiment, the target image data acquired by the vehicle in the detection area is acquired, at least one target object can be determined in the target image data, at least one attribute information of the target object is acquired, the acquired attribute information is input into the Kalman filtering model for filtering processing, a target state value of the target object can be obtained, namely, a measured value of a sensor can be obtained, the measured value of the sensor is fused, a fusion result can be obtained, whether the fusion result meets a preset threshold value or not is judged, if the fusion result meets the preset threshold value, the existence of an obstacle in the detection area of the vehicle is determined, and the vehicle is controlled, so that the vehicle avoids the obstacle, the aim of accurately detecting the target obstacle is fulfilled, the technical problem that the vehicle decision control efficiency is low is solved, and the technical effect that the vehicle decision control efficiency can be improved is realized.
Example 2
The technical solution of the embodiment of the present invention will be illustrated in the following with reference to a preferred embodiment.
In the current obstacle detection process, a single sensor is adopted to detect the obstacle, the accuracy is lower, while a plurality of sensors are adopted to detect the obstacle, the decision control of the vehicle is inaccurate for detection under many complex scenes, most of documents only aim at active situations, only front obstacles are considered, so that emergency braking is carried out, whether a rear vehicle is influenced by the emergency braking of the front vehicle is not considered, and in passive situations, if the rear vehicle is not controlled, the technical problem of lower efficiency of the decision control of the vehicle is caused.
In a related art, a method for detecting presence of an obstacle based on a multi-data fusion result is disclosed, comprising: determining a first trust function corresponding to a first obstacle in a current detection area of the first sensor according to the current acquired data of the first sensor, wherein each element in the trust function is used for representing the existence reliability, the nonexistence reliability and the unknown reliability of the obstacle; judging whether the total presence reliability value corresponding to the first obstacle is greater than a threshold value according to the value of each element in the history trust function corresponding to the first obstacle and the value of each element in the first trust function; if the detection result is larger than the detection result, determining that a first obstacle exists in the current detection area of the first sensor.
However, the embodiment of the invention provides a vehicle control method and a vehicle control system based on obstacle detection, which detect a target obstacle by adopting a multi-sensor fusion algorithm, so that the aim of accurately detecting the target obstacle is fulfilled, the technical problem of lower vehicle decision control efficiency is solved, and the technical effect of improving the vehicle decision control efficiency is realized.
Fig. 2 is a flowchart of a vehicle control method based on obstacle detection according to an embodiment of the invention, as shown in fig. 2, the vehicle control method based on obstacle detection may include the steps of:
step S201, it is determined whether the vehicle is traveling in a straight line.
If the vehicle is traveling straight, the process proceeds to step S202, step S203 and step S204, the front and rear cameras and the radar are turned on, the presence of an obstacle in front is detected, and it is determined whether the distance between the obstacle and the vehicle is greater than a first safety distance.
If the distance between the obstacle and the vehicle is not greater than the first safety distance, step S205 is entered, whether the distance between the obstacle and the vehicle is greater than the second safety distance is determined, if the distance between the obstacle and the vehicle is greater than the second safety distance, step S206 is entered, the gear of the vehicle is adjusted, and if the distance between the obstacle and the vehicle is not greater than the second safety distance, step S207 is entered, and the vehicle is braked urgently.
If the distance between the obstacle and the vehicle is greater than the first safe distance, the process proceeds to step S208, where the vehicle is kept running normally.
If the vehicle is not traveling in a straight line, the process proceeds to step S209, step S210, step S211, and step S212, all cameras and radars are turned on, a blind area mode is turned on, an obstacle is detected to exist in the rear, and whether the distance between the obstacle and the vehicle is greater than a first safety distance is determined.
If the distance between the obstacle and the vehicle is not greater than the first safety distance, step S213 is entered, it is determined whether the distance between the obstacle and the vehicle is greater than the second safety distance, and if the distance between the obstacle and the vehicle is not greater than the second safety distance, step S214 and step S215 are entered, the alarm mode is turned on, and the following vehicle is forcibly braked.
If the distance between the obstacle and the vehicle is greater than the second safety distance, the method enters step S216 and step S217, starts an early warning mode, judges whether the vehicle receives feedback information sent by the rear vehicle, enters step S218 and step S219 if the vehicle receives the feedback information sent by the rear vehicle, releases the early warning mode, adjusts the gear of the rear vehicle, enters step S220 and step S221 if the vehicle does not receive the feedback information sent by the rear vehicle, starts an alarm mode, and forcedly brakes the rear vehicle.
If the distance between the obstacle and the vehicle is greater than the first safe distance, the process proceeds to step S222, where the vehicle is kept running normally.
Fig. 3 is a schematic diagram of a vehicle control system based on obstacle detection according to an embodiment of the invention, as shown in fig. 3, the vehicle control system may include: a data acquisition unit 301, a perception fusion unit 302, a data analysis unit 303, a decision unit 304, a communication unit 305 and other vehicles 306, wherein the data acquisition unit 301 may comprise: the radar 3011 and the camera 3012, the communication unit 305 may include: a cloud server 3051 and a Dedicated Short Range Communication (DSRC) transceiver 3052.
Optionally, the radar and the camera can be used for detecting information of surrounding conditions of the vehicle, the data acquired by the camera is processed through an image recognition technology, characteristic information of people, buildings, vehicles, obstacles and the like in the image is extracted, information of relative distance, angle, speed and the like of the target object and the vehicle is acquired through the radar, and the position and the motion state of the target object can be judged according to the information.
Optionally, the data acquisition unit may communicate with the sensing fusion unit, the sensing fusion unit may communicate with the data analysis unit, the data analysis unit may communicate with the decision unit, the decision unit may communicate with the communication unit, and information transmission between vehicles may be achieved through the communication unit.
Optionally, the sensing fusion unit may perform data fusion on the acquired data, so as to perform obstacle determination. Because a large amount of environmental noise exists in a real environment, and a plurality of invalid data possibly exist in the data acquired by the data acquisition unit, the application adopts an improved self-adaptive weighting algorithm to perform data fusion, firstly, kalman filtering is performed on the acquired data, the data filtered by the Kalman filtering algorithm is used as the original data of each sensor, and the self-adaptive weighting algorithm is performed, so that the accuracy of a data fusion result can be ensured.
Alternatively, the Kalman filtering algorithm may represent the input-output relationship by a state method, i.e., the filtering algorithm is formed by a system state equation, an observation equation, and the process noise and observation noise of the system, and is represented by the following formula:
X(k+1)＝AX(k)+BM(k)+ω(k) (1)
Z(k)＝HX(k)+N(k) (2)
wherein X (k) can be used to represent the state quantity of the vehicle control system at time k, M (k) can be used to represent the control quantity of the vehicle control system at time k, Z (k) can be used to represent the observed value of the vehicle control system at time k, A can be used to represent the state transition matrix, B can be used to represent the control matrix, H can be used to represent the observed matrix, ω (k) can be used to represent the process noise of the vehicle control system at time k, and N (k) can be used to represent the observed noise of the vehicle control system at time k.
Alternatively, assume thatCan be used to represent the state prediction value and assume +.>May be used to represent the state best estimate, then the state predictor and state best estimate may be represented by the following formulas:
P'(k+1)＝AP(k)A T +M(k+1) (4)
P(k+1)＝[I-K(k+1)H(k+1)]P'(k+1) (7)
x i (k)＝Z i (k)+ε i (k) (8)
where P' (k+1) can be used to represent the covariance at the next time instant, K (k+1) can be used to represent the Kalman gain, Z, at the next time instant i (k) Can be used to represent the measured estimate of sensor i at time k, ε i (k) Can be used to represent the noise, ω, of sensor i at time k i (k) May be used to represent the weight value of sensor i, R (k) may be used to represent the fusion result,may be used to represent the mean square error of sensor i.
Alternatively, the kalman filtering algorithm can filter out data with larger errors through continuous updating, so that a measured value which is closer to reality can be obtained, and then the adaptive weighted average method is adopted for fusion of the multi-sensor data.
Optionally, the fused data is sent to the data analysis unit through the sensing fusion unit, the data analysis unit can judge whether an obstacle exists in the current environment where the vehicle is located according to the fusion result, if the obstacle exists in the current environment where the vehicle is located, the situation is fed back to the decision unit, and a control instruction of the vehicle is issued through the decision unit, so that the running state of the vehicle is controlled, and prompt information is sent to other vehicles around the vehicle.
Alternatively, controlling the running state of the vehicle may include the following:
in the first case, if the current vehicle keeps running straight, starting the radar and the camera at the front and the rear of the vehicle, and detecting the front and the rear obstacles of the current vehicle. When the obstacle is detected to exist in front, if the distance between the vehicle and the obstacle is larger than the first safety distance, the vehicle is not controlled at all, and the normal running state is maintained. If the obstacle distance is smaller than the first safety distance, determining gear information, acceleration information and throttle information of the vehicle according to the speed, distance, running direction and speed and other information of the target obstacle, and sending the gear information, the acceleration information and the throttle information to a gearbox controller, an electronic stabilizing system and a motor controller of the vehicle, so that reasonable gear throttle adjustment is performed, and safe driving of the vehicle is controlled. Meanwhile, the gear adjusting information of the vehicle is synchronously sent to the rear vehicle, so that the rear vehicle can respond in time and change the reasonable gear speed. The whole traffic flow can be controlled through the message forwarding of each vehicle, and the method has better treatment for various complex situations.
If the distance between the vehicle and the obstacle is smaller than the second safety distance due to special conditions such as a ghost probe, the advanced driving assistance system (Advanced Driver Assistance System, abbreviated as ADAS) immediately sends an instruction to the vehicle braking system so as to carry out emergency braking on the vehicle, and meanwhile, a message of emergency braking on the front vehicle is also sent to the rear vehicle through a vehicle-to-vehicle (Vehicle To Vehicle, abbreviated as V2V) communication technology so as to carry out corresponding gear adjustment, so that the situation that the rear vehicle collides due to untimely deceleration caused by sudden stopping of the front vehicle is avoided.
If the current vehicle is in a turning state, the vehicle automatically starts a blind area mode, monitors the periphery of the vehicle in all directions, and starts all radars and cameras around the vehicle. When the vehicle is in the blind area mode, the vehicle can automatically adjust the gear and the throttle state to perform deceleration processing, so that the running speed of the vehicle is not more than 40km/h until the vehicle is in the straight running state, the blind area mode is released, the normal state is restored, and the left camera, the right camera and the radar are closed. In the turning state, the detection of the obstacle is classified into an active case and a passive case similarly to the decision control when the vehicle is traveling straight. Under the active condition, when the obstacle exists in the left and right directions, if the distance from the obstacle is larger than the safety distance, the vehicle is not controlled, and the normal running state is maintained. If the distance between the obstacles is smaller than the first safety distance, adjusting the gear throttle of the vehicle in real time according to the distance and the speed of the obstacles, decelerating and running, and synchronously transmitting information among vehicles to adjust the traffic flow state. Because the vehicle turns, most probably lead to the visual field blind area, if because appear the blind area, pedestrian or vehicle is driven into suddenly, lead to the barrier distance less than the second safe distance, then monitor the rear vehicle, monitor speed and the distance of rear vehicle, send the signal immediately to the braking system of host computer, carry out emergency braking, synchronous with host computer braking information send the rear vehicle to the rear vehicle in time to the rear vehicle carries out gear adjustment, in order to avoid the rear vehicle to stop suddenly because the front vehicle leads to the speed reduction untimely and the condition that bumps into.
And secondly, under the passive condition, when the situation that the obstacle exists behind and the distance between the obstacle and the vehicle is smaller than the first safety distance is detected, the automatic driving system of the rear vehicle is judged to possibly fail, and then the vehicle automatically starts an early warning mode which is operated as follows: the method comprises the steps of firstly, immediately adjusting a gear throttle of a vehicle according to information such as a target obstacle, the speed and the distance of a front vehicle, preventing the two vehicles from collision, simultaneously sending deceleration information to a rear vehicle, feeding back response information after the rear vehicle receives the information, executing corresponding deceleration operation, and releasing an early warning mode to enable the vehicle to resume normal running.
If the vehicle does not receive the positive response, judging that the automatic driving system of the rear vehicle fails, and immediately starting an alarm mode, wherein the alarm mode correspondingly operates as follows: the information of the fault vehicle is sent to the traffic police center through the 5G module, and the background system of the traffic police center can directly perform forced braking on the fault vehicle, so that traffic accidents caused by uncontrolled vehicles are prevented, and personal safety of personnel in the vehicle can be guaranteed, wherein the information of the fault vehicle can comprise, but is not limited to: the position of the fault vehicle, the license plate number of the fault vehicle, the gear of the fault vehicle, the throttle state of the fault vehicle and the like.
Alternatively, the alarm mode can reduce traffic accidents due to direct control of the vehicle. When the distance between the obstacle existing behind and the vehicle is detected to be smaller than the second safety distance, the abnormal condition of the automatic driving system of the vehicle behind is judged, the alarm mode is immediately started, and corresponding operation processing is executed. Meanwhile, through information forwarding of each node vehicle, the following vehicles can know the conditions of the road sections ahead in real time, so that a reasonable travel route is selected, and travel time is saved.
Optionally, through a fourth generation mobile communication (4G)/5G technology, the vehicle information may be uploaded to a cloud server to store data, so as to generate a long-term monitoring curve of the vehicle autopilot state, so that traffic conditions of different periods may be checked and analyzed.
Optionally, for vehicles with abnormal automatic driving functions, the background of the traffic police system can also perform forced braking treatment on the faulty vehicle so as to avoid traffic accidents caused by uncontrolled vehicle.
Optionally, each vehicle can communicate between vehicles through DSRC technology, information such as the gear, the accelerator and the emergency brake of the current vehicle is sent to the rear vehicle, and after the rear vehicle receives the information, the gear and the accelerator of the vehicle are adjusted according to the state of the front vehicle. When an abnormal condition occurs in a certain node vehicle, the abnormal condition can be immediately sent to surrounding vehicles so that the surrounding vehicles start an early warning/alarming mode to perform corresponding processing.
In this embodiment, whether the vehicle is in straight line running is determined, if the vehicle is in straight line running, the front and rear cameras and the radar are turned on, an obstacle is detected to exist in front, and the relationship between the distance between the obstacle and the vehicle and the first and second safety distances is determined, if the vehicle is not in straight line running, all the cameras and the radar are turned on, the blind area mode is turned on, an obstacle exists in rear is detected, and the relationship between the distance between the obstacle and the vehicle and the first and second safety distances is determined, so that the running state of the vehicle is controlled, so that the vehicle can avoid the obstacle in time, the technical problem that the vehicle decision control efficiency is low is solved, and the technical effect that the vehicle decision control efficiency can be improved is achieved.
Example 3
According to the embodiment of the invention, a control device of the vehicle is also provided. The control device of the vehicle may be used to execute a control method of the vehicle in embodiment 1.
Fig. 4 is a schematic view of a control device of a vehicle according to an embodiment of the present invention. As shown in fig. 4, the control device 400 of the vehicle may include: an acquisition unit 401, a determination unit 402, a filtering unit 403, a fusion unit 404, and a control unit 405.
An acquisition unit 401 for acquiring target image data acquired by the vehicle in the detection area.
A determining unit 402, configured to determine at least one target object in the target image data, and obtain at least one attribute information of the target object.
The filtering unit 403 is configured to input the attribute information into a kalman filtering model for filtering processing, so as to obtain a target state value of the target object, where the target state value is used to represent a measured value of a sensor of the vehicle.
And a fusion unit 404, configured to perform fusion processing on the target state value to obtain a fusion result, where the fusion result is used to characterize whether the target object is an obstacle in the detection area relative to the vehicle.
And the control unit 405 is configured to determine that an obstacle exists in the detection area in response to the fusion result meeting a preset threshold, and control the vehicle so that the vehicle avoids the obstacle.
Alternatively, the fusing unit 404 may include: the first acquisition module is used for acquiring a weight value of the target state value; and the first determining module is used for determining a fusion result based on the product of the weight value and the target state value.
Alternatively, the control unit 405 may include: the second determining module is used for determining the direction of the obstacle relative to the vehicle and acquiring the distance between the vehicle and the obstacle; the first adjusting module is used for adjusting gear information, acceleration information and throttle information of the vehicle and sending the gear information, the acceleration information and the throttle information to a rear vehicle of the vehicle in response to the obstacle being in front of, left of or right of the vehicle, wherein the distance is smaller than a first preset distance and the distance is larger than a second preset distance; and the braking module is used for responding to the situation that the obstacle is in front of, left of or right of the vehicle and the distance is smaller than a second preset distance, performing braking processing on the vehicle and sending braking information of the vehicle to a rear vehicle.
Optionally, the control unit 405 may further include: the second adjusting module is used for adjusting gear information and throttle information and sending the gear information and the throttle information to a rear vehicle in response to the obstacle being positioned behind the vehicle, wherein the distance is smaller than the first preset distance and the distance is larger than the second preset distance; the second acquisition module is used for acquiring feedback information sent by the rear vehicle in response to the gear information and the accelerator information, wherein the feedback information is used for representing that an automatic driving system of the rear vehicle works normally.
Optionally, the control device 400 of the vehicle may further include: and the braking unit is used for braking the rear vehicle.
Optionally, the control device 400 of the vehicle may further include: and the holding unit is used for determining that the vehicle does not have an obstacle in the detection area and holding gear information, acceleration information and throttle information of the vehicle in response to the fusion result not meeting the preset threshold value.
In this embodiment, an acquisition unit for acquiring target image data acquired by a vehicle in a detection area; the determining unit is used for determining at least one target object in the target image data and acquiring at least one attribute information of the target object; the filtering unit is used for inputting the attribute information into the Kalman filtering model for filtering processing to obtain a target state value of a target object, wherein the target state value is used for representing a measured value of a sensor of the vehicle; the fusion unit is used for carrying out fusion processing on the target state value to obtain a fusion result, wherein the fusion result is used for representing whether the target object is an obstacle relative to the vehicle in the detection area; the control unit is used for responding to the fusion result to meet the preset threshold value, determining that the vehicle has an obstacle in the detection area and controlling the vehicle so as to enable the vehicle to avoid the obstacle, solving the technical problem of lower efficiency of vehicle decision control and achieving the technical effect of improving the efficiency of vehicle decision control.
Example 4
According to an embodiment of the present application, there is also provided a computer-readable storage medium including a stored program, wherein the program executes the control method of the vehicle in embodiment 1.
Example 5
According to an embodiment of the present application, there is also provided a processor for running a program, wherein the program when run by the processor performs the control method of the vehicle in embodiment 1.
Example 6
According to an embodiment of the present application, there is also provided a vehicle for executing the control method of any one of the vehicles of embodiment 1.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of units may be a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-only memory (ROM), a random access memory (RAM, randomAccessMemory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (10)
1. A control method of a vehicle, characterized by comprising:
acquiring target image data acquired by the vehicle in a detection area;
determining at least one target object in the target image data, and acquiring at least one attribute information of the target object;
inputting the attribute information into a Kalman filtering model for filtering processing to obtain a target state value of the target object, wherein the target state value is used for representing a measured value of a sensor of the vehicle;
carrying out fusion processing on the target state value to obtain a fusion result, wherein the fusion result is used for representing whether the target object is an obstacle relative to the vehicle in the detection area;
and responding to the fusion result to meet a preset threshold value, determining that the vehicle has the obstacle in the detection area, and controlling the vehicle so as to enable the vehicle to avoid the obstacle.
2. The method of claim 1, wherein fusing the target state values to obtain the fused result comprises:
acquiring a weight value of the target state value;
and determining the fusion result based on the product of the weight value and the target state value.
3. The method of claim 1, wherein determining that the vehicle is present in the detection zone and controlling the vehicle in response to the fusion result being greater than a preset threshold comprises:
determining the direction of the obstacle relative to the vehicle, and acquiring the distance between the vehicle and the obstacle;
adjusting gear information, acceleration information, and throttle information of the vehicle and transmitting the gear information, the acceleration information, and the throttle information to a vehicle behind the vehicle in response to the obstacle being in front of, to the left of, or to the right of the vehicle, the distance being less than a first preset distance, and the distance being greater than a second preset distance, wherein the second preset distance is less than the first preset distance;
and in response to the obstacle being in front of, to the left of, or to the right of the vehicle, and the distance being less than the second preset distance, performing a braking process on the vehicle, and transmitting braking information of the vehicle to the rear vehicle.
4. The method of claim 3, wherein determining that the vehicle is present in the detection zone and controlling the vehicle in response to the fusion result being greater than a preset threshold, further comprises:
adjusting the gear information and the throttle information and transmitting the gear information and the throttle information to the rear vehicle in response to the obstacle being in the rear of the vehicle, the distance being less than the first preset distance and the distance being greater than the second preset distance;
and acquiring feedback information sent by the rear vehicle in response to the gear information and the throttle information, wherein the feedback information is used for representing normal operation of an automatic driving system of the rear vehicle.
5. The method of claim 4, wherein in addition to obtaining feedback information sent by the rear vehicle in response to the gear information and the throttle information, the method further comprises:
and performing braking treatment on the rear vehicle.
6. The method according to claim 1, wherein the method further comprises:
and in response to the fusion result not meeting the preset threshold, determining that the obstacle does not exist in the detection area of the vehicle, and maintaining gear information, acceleration information and throttle information of the vehicle.
7. A control device for a vehicle, comprising:
the acquisition unit is used for acquiring target image data acquired by the vehicle in the detection area;
the determining unit is used for determining at least one target object in the target image data and acquiring at least one attribute information of the target object;
the filtering unit is used for inputting the attribute information into a Kalman filtering model to carry out filtering processing to obtain a target state value of the target object, wherein the target state value is used for representing a measured value of a sensor of the vehicle;
the fusion unit is used for carrying out fusion processing on the target state value to obtain a fusion result, wherein the fusion result is used for representing whether the target object is an obstacle relative to the vehicle in the detection area;
and the control unit is used for responding to the fusion result to meet a preset threshold value, determining that the vehicle has the obstacle in the detection area and controlling the vehicle so as to enable the vehicle to avoid the obstacle.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored program, wherein the program, when run, controls a device in which the computer-readable storage medium is located to execute the control method of the vehicle according to any one of claims 1 to 6.
9. A processor for running a program, wherein the program when run by the processor performs the control method of the vehicle according to any one of claims 1 to 6.
10. A vehicle for performing the control method of the vehicle according to any one of claims 1 to 6.
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