CN117465394A - Control method and system for emergency braking of electric vehicle - Google Patents
Control method and system for emergency braking of electric vehicle Download PDFInfo
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- CN117465394A CN117465394A CN202311824368.5A CN202311824368A CN117465394A CN 117465394 A CN117465394 A CN 117465394A CN 202311824368 A CN202311824368 A CN 202311824368A CN 117465394 A CN117465394 A CN 117465394A
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/172—Determining control parameters used in the regulation, e.g. by calculations involving measured or detected parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
- B60Q9/008—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling for anti-collision purposes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T17/00—Component parts, details, or accessories of power brake systems not covered by groups B60T8/00, B60T13/00 or B60T15/00, or presenting other characteristic features
- B60T17/18—Safety devices; Monitoring
- B60T17/22—Devices for monitoring or checking brake systems; Signal devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T7/00—Brake-action initiating means
- B60T7/12—Brake-action initiating means for automatic initiation; for initiation not subject to will of driver or passenger
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/171—Detecting parameters used in the regulation; Measuring values used in the regulation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T2201/00—Particular use of vehicle brake systems; Special systems using also the brakes; Special software modules within the brake system controller
- B60T2201/02—Active or adaptive cruise control system; Distance control
- B60T2201/022—Collision avoidance systems
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Transportation (AREA)
- Human Computer Interaction (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a control method and a system for emergency braking of an electric vehicle, which relate to the technical field of automobiles and comprise the following steps: identifying a preceding vehicle, a non-vehicle, a pedestrian, and a fixed obstacle in an image of an environment outside of the driving vehicle; measuring real-time distances from a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle to a driving vehicle by using infrared rays; acquiring a real-time speed of a driving vehicle; real-time speed measurement is carried out on front motor vehicles, non-motor vehicles and pedestrians; establishing a pavement analysis model and a brake track model; generating road surface friction coefficient evaluation data; calculating a braking distance according to the relative speed of the driving vehicle and the front object and the road friction coefficient evaluation data; and judging whether the distance between the driving vehicle and the object in front is larger than the braking distance by a preset distance. By arranging the model building module, the road surface analysis module, the brake prediction module and the distance judgment module, collision or rear-end collision can be avoided under any road surface environment.
Description
Technical Field
The invention relates to the technical field of automobiles, in particular to a control method and a system for emergency braking of an electric vehicle.
Background
Emergency braking refers to the fact that when an automobile encounters an emergency during running, a driver rapidly and correctly uses a brake to stop the automobile within a shortest distance. A method for operating a vehicle with an antilock brake system includes quickly lifting an accelerator pedal, quickly and forcefully stepping on the brake pedal, and simultaneously stepping on a clutch pedal to quickly stop the vehicle.
However, when the emergency braking is actually performed, road surface environments are complex, friction coefficients of different road surfaces are different, braking distances are difficult to judge, the driver directly judges the road surface environments, deviation is easy to occur, and rear-end collision or collision is caused by insufficient vehicle distance or too high vehicle speed.
Disclosure of Invention
In order to solve the technical problems, the technical scheme provides a control method and a system for emergency braking of an electric vehicle, which solve the problems that when the emergency braking is actually carried out in the background technology, the road surface environment is complex, the friction coefficients of different road surfaces are different, the braking distance is difficult to judge, the driver directly judges, deviation is easy to occur, and rear-end collision or collision is caused by insufficient vehicle distance or too fast vehicle speed.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a control method for emergency braking of an electric vehicle comprises the following steps:
at least one driving vehicle driving external environment image is acquired by using a camera at preset time intervals, and a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle are identified in the driving vehicle driving external environment image;
measuring real-time distances from a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle to a driving vehicle by using infrared rays, and eliminating the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle with the real-time distances larger than a given value;
acquiring a real-time speed of a driving vehicle;
real-time speed measurement is carried out on front motor vehicles, non-motor vehicles and pedestrians;
establishing a pavement analysis model and a brake track model;
acquiring the road surface environment in which a driving vehicle runs, and generating road surface friction coefficient evaluation data;
acquiring a front object of a travel route of a driving vehicle, wherein the front object is one of a front motor vehicle, a non-motor vehicle, a pedestrian or a fixed obstacle, acquiring the speed of the front object, calculating to obtain the relative speed of the driving vehicle and the front object, and calculating to obtain the braking distance according to the relative speed of the driving vehicle and the front object and road surface friction coefficient evaluation data;
judging whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance, if so, not performing any processing, if not, giving an early warning to the driver, if the driver does not reduce the vehicle speed to a safe state within a preset time, performing emergency braking, and if the driver reduces the vehicle speed to the safe state within the preset time, not performing any processing.
Preferably, the identifying of the preceding vehicle, the non-vehicle, the pedestrian and the fixed obstacle in the driving vehicle running external environment image includes the steps of:
extracting a fixed object from at least one driving vehicle driving external environment image as a reference point, wherein the fixed object is a street lamp post, a tree or a sign;
extracting at least one external object contour from the continuous driving vehicle driving external environment images;
judging whether the relative positions of the outline of the external object and the reference point are changed in the continuous driving vehicle running external environment images, and if not, judging that the outline of the external object is a fixed obstacle;
if so, calculating the change rate of the distance between the outline of the external object and the reference point, and if the change rate is smaller than the preset rate, judging that the outline of the external object is a pedestrian;
if not, judging whether the outline area of the external object is larger than the preset area, if so, judging that the external object is a front motor vehicle, and if not, judging that the external object is a non-motor vehicle;
the change rate of the distance between the outline of the external object and the reference point is calculated as follows:
and obtaining shooting time intervals of two driving vehicle driving external environment images, respectively obtaining a first interval and a second interval of an external object outline and a reference point in the two driving vehicle driving external environment images, calculating to obtain a difference value of the first interval and the second interval, and dividing the difference value by the shooting time interval to obtain the change rate.
Preferably, the measuring of the real-time distance of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle to the driving vehicle using the infrared rays includes the steps of:
according to the recognition results of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle, at least one direction relation of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle and the driving vehicle is obtained respectively;
the infrared rays are emitted along the direction presented by the direction relation, and the infrared ray round trip time is obtained;
the real-time distances from the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle to the driving vehicle are calculated.
Preferably, the real-time speed measurement of the front motor vehicle, the non-motor vehicle and the pedestrian comprises the following steps:
acquiring a real-time speed of a driving vehicle;
acquiring real-time distances from a front motor vehicle, a non-motor vehicle and a pedestrian to a driving vehicle;
acquiring the past distances from the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle in the front of 0.1 seconds;
dividing the value obtained by subtracting the past distance from the real-time distance by 0.1 to obtain the relative speeds of the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle;
and superposing the real-time speed and the relative speed to obtain the real-time speeds of the front motor vehicle, the non-motor vehicle and the pedestrians.
Preferably, the building of the pavement analysis model includes the following steps:
acquiring at least one pavement material, and acquiring the intensity condition of ultrasonic waves reflected by the pavement material;
and obtaining abrasion images of the same pavement material at different degrees, and obtaining pavement friction coefficients corresponding to abrasion of the same pavement material at different degrees.
Preferably, the building of the brake track model includes the following steps:
acquiring a tire material used for driving a vehicle and acquiring the weight of the driving vehicle;
taking the tire material and weight as model invariants;
setting model variables as the speed of a driving vehicle and the road friction coefficient;
under the conditions of the speeds of different driving vehicles and road friction, testing the braking distance of the driving vehicles;
the braking distance is paired with the corresponding vehicle speed of the driving vehicle and road surface friction.
Preferably, the step of obtaining the road surface environment where the driving vehicle runs and generating the road surface friction coefficient evaluation data includes the steps of:
transmitting ultrasonic waves to the road surface environment where the driving vehicle runs, and analyzing to obtain the road surface material of the road surface environment according to the intensity of ultrasonic wave reflection of the road surface and the road surface analysis model;
analyzing and obtaining the abrasion degree corresponding to the pavement material by using an image recognition technology;
and obtaining a road surface friction coefficient corresponding to the road surface environment where the driving vehicle runs according to the road surface analysis model.
Preferably, the calculating the braking distance includes the steps of:
the relative speed V of the driving vehicle and the front object is obtained, the weight G of the driving vehicle is obtained, and the road surface friction coefficient is obtained；
Calculated that the road surface friction is equal to；
In the braking trajectory model, the relative speed V and the road friction force are calledPaired braking distance.
Preferably, the vehicle speed reduction to the safe state is specifically as follows:
acquiring an actual vehicle speed after the vehicle speed is reduced, calculating to obtain an updated relative speed of the driving vehicle and a front object, and calculating to obtain an updated braking distance according to the updated relative speed of the driving vehicle and the front object and road surface friction coefficient evaluation data;
re-acquiring the updated distance between the driving vehicle and the object in front;
and judging whether the update distance between the driving vehicle and the front object is larger than the update braking distance by a preset distance, if so, judging that the vehicle speed is reduced to a safe state, and if not, judging that the vehicle speed is not reduced to the safe state.
The control system for the emergency braking of the electric vehicle is used for realizing the control method for the emergency braking of the electric vehicle, and comprises the following steps:
a target extraction module that identifies a preceding vehicle, a non-vehicle, a pedestrian, and a fixed obstacle in an image of an environment outside of the driving vehicle;
an infrared ranging module that measures real-time distances of a preceding motor vehicle, a non-motor vehicle, a pedestrian, and a fixed obstacle to a driving vehicle using infrared rays;
the speed measuring module is used for acquiring the real-time speed of a driving vehicle and measuring the speed of a front motor vehicle, a non-motor vehicle and pedestrians in real time;
the model building module is used for building a road surface analysis model and a brake track model;
the road surface analysis module is used for obtaining the road surface environment of the driving vehicle and generating road surface friction coefficient evaluation data;
the brake prediction module calculates a brake distance according to the relative speed of the driving vehicle and the object in front and the road friction coefficient evaluation data;
the distance judging module judges whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance or not;
an emergency braking module that takes emergency braking.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of setting a model building module, a road surface analysis module, a brake prediction module and a distance judgment module, wherein the building module builds a road surface analysis model, builds a brake track model, analyzes a road surface on which a driving vehicle runs according to the built model, obtains a road surface friction coefficient on which the driving vehicle runs, further calculates a brake distance according to a real-time vehicle speed, judges whether the distance between the driving vehicle and a front object is larger than the brake distance by a preset distance, sends out early warning according to a judgment result, adopts emergency braking if the early warning is invalid, and further ensures that enough space can be accurately reserved for emergency braking under any road surface environment to avoid collision or rear-end collision.
Drawings
FIG. 1 is a schematic flow chart of a control method for emergency braking of an electric vehicle;
FIG. 2 is a schematic flow chart for identifying a front vehicle, a non-vehicle, a pedestrian and a fixed obstacle in an image of the environment outside the driving vehicle of the present invention;
FIG. 3 is a schematic diagram of a flow chart of the present invention for measuring real-time distances of a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle to a driving vehicle using infrared rays;
FIG. 4 is a schematic diagram of the flow of real-time speed measurement of vehicles, non-vehicles and pedestrians in front of the present invention;
FIG. 5 is a schematic diagram of a flow chart for establishing a pavement analysis model according to the present invention;
FIG. 6 is a schematic diagram of a flow chart for creating a brake trajectory model according to the present invention;
FIG. 7 is a schematic flow chart of the method for obtaining the road surface environment of the driving vehicle and generating the road surface friction coefficient evaluation data;
FIG. 8 is a schematic diagram of a calculation of a braking distance according to the present invention;
FIG. 9 is a flow chart of the present invention for reducing the vehicle speed to a safe state.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, a control method for emergency braking of an electric vehicle includes:
at least one driving vehicle driving external environment image is acquired by using a camera at preset time intervals, and a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle are identified in the driving vehicle driving external environment image;
measuring real-time distances from a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle to a driving vehicle by using infrared rays, and eliminating the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle with the real-time distances larger than a given value;
acquiring a real-time speed of a driving vehicle;
real-time speed measurement is carried out on front motor vehicles, non-motor vehicles and pedestrians;
establishing a pavement analysis model and a brake track model;
acquiring the road surface environment in which a driving vehicle runs, and generating road surface friction coefficient evaluation data;
acquiring a front object of a travel route of a driving vehicle, wherein the front object is the object closest to the driving vehicle in the direction opposite to the head of the driving vehicle;
the front object is one of a front motor vehicle, a non-motor vehicle, a pedestrian or a fixed obstacle, the speed of the front object is obtained, the relative speed of the driving vehicle and the front object is calculated, and the braking distance is calculated according to the relative speed of the driving vehicle and the front object and road surface friction coefficient evaluation data;
judging whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance, if so, not performing any processing, if not, giving an early warning to the driver, if the driver does not reduce the vehicle speed to a safe state within a preset time, performing emergency braking, and if the driver reduces the vehicle speed to the safe state within the preset time, not performing any processing.
Referring to fig. 2, the identification of a preceding vehicle, a non-vehicle, a pedestrian, and a fixed obstacle in an image of the driving vehicle running external environment includes the steps of:
extracting a fixed object from at least one driving vehicle driving external environment image as a reference point, wherein the fixed object is a street lamp post, a tree or a sign;
extracting at least one external object contour from the continuous driving vehicle driving external environment images;
judging whether the relative positions of the outline of the external object and the reference point are changed in the continuous driving vehicle running external environment images, and if not, judging that the outline of the external object is a fixed obstacle;
if so, calculating the change rate of the distance between the outline of the external object and the reference point, and if the change rate is smaller than the preset rate, judging that the outline of the external object is a pedestrian;
if not, judging whether the outline area of the external object is larger than the preset area, if so, judging that the external object is a front motor vehicle, and if not, judging that the external object is a non-motor vehicle;
the change rate of the distance between the outline of the external object and the reference point is calculated as follows:
acquiring shooting time intervals of two driving vehicle driving external environment images, respectively acquiring a first interval and a second interval of an external object outline and a reference point in the two driving vehicle driving external environment images, calculating to acquire a difference value of the first interval and the second interval, and dividing the difference value by the shooting time interval to acquire a change rate;
the judgment basis for identifying the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle in the driving vehicle driving external environment image is that the fixed object on the road where the lamp post, the tree or the indication board frequently appears is used as the reference point, the fixed obstacle is necessarily fixed in the continuous driving vehicle driving external environment image, the relative position of the fixed object and the reference point is unchanged, and the moving speed of the person is slower relative to the vehicle, so that the preset speed is set, and the fixed object is used as the pedestrian which is smaller than the preset speed;
when infrared measurement is carried out, the front motor vehicle, the non-motor vehicle, the pedestrians and the fixed obstacles with the real-time distance larger than the given value are eliminated, and the outline of the external object with the longer distance is eliminated, so that the rest front motor vehicle and the rest non-motor vehicle are all within the given value of the distance driving vehicle, the situation that the area of the front motor vehicle is smaller than that of the non-motor vehicle can not occur due to the distance, and the front motor vehicle and the non-motor vehicle can be distinguished by the area of the outline of the external object.
Referring to fig. 3, measuring real-time distances of a front motor vehicle, a non-motor vehicle, a pedestrian, and a fixed obstacle to a driving vehicle using infrared rays includes the steps of:
according to the recognition results of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle, at least one direction relation of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle and the driving vehicle is obtained respectively;
the infrared rays are emitted along the direction presented by the direction relation, and the infrared ray round trip time is obtained;
the real-time distances from the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle to the driving vehicle are calculated.
Referring to fig. 4, the real-time speed measurement of the front motor vehicle, the non-motor vehicle and the pedestrian comprises the following steps:
acquiring a real-time speed of a driving vehicle;
acquiring real-time distances from a front motor vehicle, a non-motor vehicle and a pedestrian to a driving vehicle;
acquiring the past distances from the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle in the front of 0.1 seconds;
dividing the value obtained by subtracting the past distance from the real-time distance by 0.1 to obtain the relative speeds of the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle;
here, the average speed in the first 0.1 seconds of the current moment is used as the relative speed from the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle, and the error is small due to the very short time, so the average speed can be used as an approximate value;
and superposing the real-time speed and the relative speed to obtain the real-time speeds of the front motor vehicle, the non-motor vehicle and the pedestrians.
Referring to fig. 5, the construction of the pavement analysis model includes the steps of:
acquiring at least one pavement material, and acquiring the intensity condition of ultrasonic waves reflected by the pavement material;
obtaining abrasion images of the same pavement material at different degrees, and obtaining pavement friction coefficients corresponding to abrasion of the same pavement material at different degrees;
the road surface analysis model is used for classifying various road surface materials existing in practice at present and collecting road surface friction coefficients of the road surface materials with different abrasion degrees so as to analyze the road surface environment of a driving vehicle and obtain the road surface friction coefficients.
Referring to fig. 6, the brake trajectory model is built up by the steps of:
acquiring a tire material used for driving a vehicle and acquiring the weight of the driving vehicle;
taking the tire material and weight as model invariants;
setting model variables as the speed of a driving vehicle and the road friction coefficient;
under the conditions of the speeds of different driving vehicles and road friction, testing the braking distance of the driving vehicles;
pairing the braking distance with the corresponding speed of the driving vehicle and the road surface friction;
the tire material used for driving the vehicle is a fixed material, the weight of the driving vehicle is a fixed value, so the model is invariable, but the speed and the road friction coefficient of the driving vehicle are both variable, so in the experiment, the matching combination of the speed and the road friction coefficient of the driving vehicle which can be actually used is needed to be tested, and the braking distance corresponding to the speed and the road friction coefficient of the driving vehicle is obtained;
the value of the vehicle speed of the driving vehicle is the value of the equal point in the actual range section of the vehicle speed, and the value of the road surface friction coefficient is the value of the equal point in the actual road surface friction coefficient range section.
Referring to fig. 7, the road surface environment in which the driving vehicle runs is acquired, and the generation of the road surface friction coefficient evaluation data includes the steps of:
transmitting ultrasonic waves to the road surface environment where the driving vehicle runs, and analyzing to obtain the road surface material of the road surface environment according to the intensity of ultrasonic wave reflection of the road surface and the road surface analysis model;
analyzing and obtaining the abrasion degree corresponding to the pavement material by using an image recognition technology;
obtaining a road surface friction coefficient corresponding to the road surface environment where the driving vehicle runs according to the road surface analysis model;
according to the pavement analysis model, when the pavement material and the abrasion degree corresponding to the pavement material are determined, the pavement friction coefficient is determined.
Referring to fig. 8, the calculation of the braking distance includes the steps of:
the relative speed V of the driving vehicle and the front object is obtained, the weight G of the driving vehicle is obtained, and the road surface friction coefficient is obtained；
Calculated that the road surface friction is equal to；
In the braking trajectory model, the relative speed V and the road friction force are calledPairing braking distance;
the relative speed is obtained by superposing the reverse direction of the front object on the speed of the driving vehicle, and the relative speed V of the driving vehicle and the front object can be regarded as static at the moment, so that the braking distance can be more conveniently analyzed, and the analysis result is not influenced.
Referring to fig. 9, the vehicle speed is reduced to a safe state as follows:
acquiring an actual vehicle speed after the vehicle speed is reduced, calculating to obtain an updated relative speed of the driving vehicle and a front object, and calculating to obtain an updated braking distance according to the updated relative speed of the driving vehicle and the front object and road surface friction coefficient evaluation data;
re-acquiring the updated distance between the driving vehicle and the object in front;
judging whether the update distance between the driving vehicle and the front object is larger than the update braking distance by a preset distance, if so, judging that the vehicle speed is reduced to a safe state, and if not, judging that the vehicle speed is not reduced to the safe state;
the purpose of reducing the vehicle speed to the safe state is to determine whether the vehicle speed after the reaction of the driver is reduced enough, namely, whether the distance between the driving vehicle and a front object is larger than the braking distance by a preset distance, so that the condition of reducing the vehicle speed to the safe state is met, and enough space is provided to ensure that no collision or rear-end collision can occur after the electric vehicle is braked emergently.
The control system for the emergency braking of the electric vehicle is used for realizing the control method for the emergency braking of the electric vehicle, and comprises the following steps:
a target extraction module that identifies a preceding vehicle, a non-vehicle, a pedestrian, and a fixed obstacle in an image of an environment outside of the driving vehicle;
an infrared ranging module that measures real-time distances of a preceding motor vehicle, a non-motor vehicle, a pedestrian, and a fixed obstacle to a driving vehicle using infrared rays;
the speed measuring module is used for acquiring the real-time speed of a driving vehicle and measuring the speed of a front motor vehicle, a non-motor vehicle and pedestrians in real time;
the model building module is used for building a road surface analysis model and a brake track model;
the road surface analysis module is used for obtaining the road surface environment of the driving vehicle and generating road surface friction coefficient evaluation data;
the brake prediction module calculates a brake distance according to the relative speed of the driving vehicle and the object in front and the road friction coefficient evaluation data;
the distance judging module judges whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance or not;
an emergency braking module that takes emergency braking.
The working process of the control system for the emergency braking of the electric vehicle is as follows:
step one: the target extraction module uses a camera to acquire at least one driving vehicle driving external environment image at intervals of preset time, and identifies a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle in the driving vehicle driving external environment image;
step two: the infrared ranging module measures real-time distances from a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle to a driving vehicle by using infrared rays, and excludes the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle with the real-time distances larger than a given value;
step three: the speed measuring module obtains the real-time speed of the driving vehicle and measures the speed of the front motor vehicle, the non-motor vehicle and the pedestrians in real time;
step four: the model building module builds a pavement analysis model and a brake track model;
step five: the road surface analysis module acquires the road surface environment of the driving vehicle and generates road surface friction coefficient evaluation data;
step six: the brake prediction module acquires a front object of a travelling route of the driving vehicle, acquires the speed of the front object, calculates the relative speed of the driving vehicle and the front object, and calculates the brake distance according to the relative speed of the driving vehicle and the front object and the road surface friction coefficient evaluation data;
step seven: the distance judging module judges whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance, if so, no processing is performed, if not, the driver is warned, if the driver does not reduce the vehicle speed to a safe state within a preset time, the emergency braking module adopts emergency braking, and if the driver reduces the vehicle speed to the safe state within the preset time, no processing is performed.
Still further, the present disclosure also provides a storage medium having a computer readable program stored thereon, where the computer readable program executes the control method for emergency braking of an electric vehicle described above when called.
It is understood that the storage medium may be a magnetic medium, e.g., floppy disk, hard disk, magnetic tape; optical media such as DVD; or a semiconductor medium such as a solid state disk SolidStateDisk, SSD, etc.
In summary, the invention has the advantages that: the method comprises the steps of setting a model building module, a road surface analysis module, a brake prediction module and a distance judgment module, wherein the building module builds a road surface analysis model, builds a brake track model, analyzes a road surface on which a driving vehicle runs according to the built model, obtains a road surface friction coefficient on which the driving vehicle runs, further calculates a brake distance according to a real-time vehicle speed, judges whether the distance between the driving vehicle and a front object is larger than the brake distance by a preset distance, sends out early warning according to a judgment result, adopts emergency braking if the early warning is invalid, and further ensures that enough space can be accurately reserved for emergency braking under any road surface environment to avoid collision or rear-end collision.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. A control method for emergency braking of an electric vehicle, comprising:
at least one driving vehicle driving external environment image is acquired by using a camera at preset time intervals, and a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle are identified in the driving vehicle driving external environment image;
measuring real-time distances from a front motor vehicle, a non-motor vehicle, a pedestrian and a fixed obstacle to a driving vehicle by using infrared rays, and eliminating the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle with the real-time distances larger than a given value;
acquiring a real-time speed of a driving vehicle;
real-time speed measurement is carried out on front motor vehicles, non-motor vehicles and pedestrians;
establishing a pavement analysis model and a brake track model;
acquiring the road surface environment in which a driving vehicle runs, and generating road surface friction coefficient evaluation data;
acquiring a front object of a travel route of a driving vehicle, wherein the front object is one of a front motor vehicle, a non-motor vehicle, a pedestrian or a fixed obstacle, acquiring the speed of the front object, calculating to obtain the relative speed of the driving vehicle and the front object, and calculating to obtain the braking distance according to the relative speed of the driving vehicle and the front object and road surface friction coefficient evaluation data;
judging whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance, if so, not performing any processing, if not, giving an early warning to the driver, if the driver does not reduce the vehicle speed to a safe state within a preset time, performing emergency braking, and if the driver reduces the vehicle speed to the safe state within the preset time, not performing any processing.
2. The control method of emergency braking of an electric vehicle according to claim 1, wherein the identification of a preceding vehicle, a non-vehicle, a pedestrian, and a fixed obstacle in an image of the driving environment of the driving vehicle comprises the steps of:
extracting a fixed object from at least one driving vehicle driving external environment image as a reference point, wherein the fixed object is a street lamp post, a tree or a sign;
extracting at least one external object contour from the continuous driving vehicle driving external environment images;
judging whether the relative positions of the outline of the external object and the reference point are changed in the continuous driving vehicle running external environment images, and if not, judging that the outline of the external object is a fixed obstacle;
if so, calculating the change rate of the distance between the outline of the external object and the reference point, and if the change rate is smaller than the preset rate, judging that the outline of the external object is a pedestrian;
if not, judging whether the outline area of the external object is larger than the preset area, if so, judging that the external object is a front motor vehicle, and if not, judging that the external object is a non-motor vehicle;
the change rate of the distance between the outline of the external object and the reference point is calculated as follows:
and obtaining shooting time intervals of two driving vehicle driving external environment images, respectively obtaining a first interval and a second interval of an external object outline and a reference point in the two driving vehicle driving external environment images, calculating to obtain a difference value of the first interval and the second interval, and dividing the difference value by the shooting time interval to obtain the change rate.
3. The control method for emergency braking of an electric vehicle according to claim 2, wherein the measuring of the real-time distances of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle to the driving vehicle using infrared rays comprises the steps of:
according to the recognition results of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle, at least one direction relation of the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle and the driving vehicle is obtained respectively;
the infrared rays are emitted along the direction presented by the direction relation, and the infrared ray round trip time is obtained;
the real-time distances from the front motor vehicle, the non-motor vehicle, the pedestrian and the fixed obstacle to the driving vehicle are calculated.
4. A control method for emergency braking of an electric vehicle according to claim 3, wherein the real-time speed measurement of the front vehicles, the non-vehicles and the pedestrians comprises the steps of:
acquiring a real-time speed of a driving vehicle;
acquiring real-time distances from a front motor vehicle, a non-motor vehicle and a pedestrian to a driving vehicle;
acquiring the past distances from the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle in the front of 0.1 seconds;
dividing the value obtained by subtracting the past distance from the real-time distance by 0.1 to obtain the relative speeds of the front motor vehicle, the non-motor vehicle and the pedestrian to the driving vehicle;
and superposing the real-time speed and the relative speed to obtain the real-time speeds of the front motor vehicle, the non-motor vehicle and the pedestrians.
5. The method for controlling emergency braking of an electric vehicle according to claim 4, wherein the step of establishing the road surface analysis model comprises the steps of:
acquiring at least one pavement material, and acquiring the intensity condition of ultrasonic waves reflected by the pavement material;
and obtaining abrasion images of the same pavement material at different degrees, and obtaining pavement friction coefficients corresponding to abrasion of the same pavement material at different degrees.
6. The method for controlling emergency braking of an electric vehicle according to claim 5, wherein the step of establishing a braking trajectory model comprises the steps of:
acquiring a tire material used for driving a vehicle and acquiring the weight of the driving vehicle;
taking the tire material and weight as model invariants;
setting model variables as the speed of a driving vehicle and the road friction coefficient;
under the conditions of the speeds of different driving vehicles and road friction, testing the braking distance of the driving vehicles;
the braking distance is paired with the corresponding vehicle speed of the driving vehicle and road surface friction.
7. The method for controlling emergency braking of an electric vehicle according to claim 6, wherein the step of acquiring the road surface environment in which the driving vehicle is traveling and generating the road surface friction coefficient evaluation data includes the steps of:
transmitting ultrasonic waves to the road surface environment where the driving vehicle runs, and analyzing to obtain the road surface material of the road surface environment according to the intensity of ultrasonic wave reflection of the road surface and the road surface analysis model;
analyzing and obtaining the abrasion degree corresponding to the pavement material by using an image recognition technology;
and obtaining a road surface friction coefficient corresponding to the road surface environment where the driving vehicle runs according to the road surface analysis model.
8. The method for controlling emergency braking of an electric vehicle according to claim 7, wherein the calculating the braking distance comprises the steps of:
the relative speed V of the driving vehicle and a front object is obtained, the weight G of the driving vehicle is obtained, and the road surface friction coefficient is obtained;
calculating to obtain that the road surface friction is equal to;
in the braking trajectory model, a braking distance paired with the relative velocity V and the road surface friction is called.
9. The control method for emergency braking of an electric vehicle according to claim 8, wherein the step of reducing the vehicle speed to a safe state is specifically as follows:
acquiring an actual vehicle speed after the vehicle speed is reduced, calculating to obtain an updated relative speed of the driving vehicle and a front object, and calculating to obtain an updated braking distance according to the updated relative speed of the driving vehicle and the front object and road surface friction coefficient evaluation data;
re-acquiring the updated distance between the driving vehicle and the object in front;
and judging whether the update distance between the driving vehicle and the front object is larger than the update braking distance by a preset distance, if so, judging that the vehicle speed is reduced to a safe state, and if not, judging that the vehicle speed is not reduced to the safe state.
10. A control system for emergency braking of an electric vehicle, for implementing the control method for emergency braking of an electric vehicle according to any one of claims 1 to 9, characterized by comprising:
a target extraction module that identifies a preceding vehicle, a non-vehicle, a pedestrian, and a fixed obstacle in an image of an environment outside of the driving vehicle;
an infrared ranging module that measures real-time distances of a preceding motor vehicle, a non-motor vehicle, a pedestrian, and a fixed obstacle to a driving vehicle using infrared rays;
the speed measuring module is used for acquiring the real-time speed of a driving vehicle and measuring the speed of a front motor vehicle, a non-motor vehicle and pedestrians in real time;
the model building module is used for building a road surface analysis model and a brake track model;
the road surface analysis module is used for obtaining the road surface environment of the driving vehicle and generating road surface friction coefficient evaluation data;
the brake prediction module calculates a brake distance according to the relative speed of the driving vehicle and the object in front and the road friction coefficient evaluation data;
the distance judging module judges whether the distance between the driving vehicle and the front object is larger than the braking distance by a preset distance or not;
an emergency braking module that takes emergency braking.
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