A vehicle following control method and related equipment

Abstract

The present invention discloses a vehicle following control method and related equipment. The method comprises: obtaining driving information of a vehicle to be followed; using vehicle speed information and wind speed information as inputs of a wake vortex simulation model to obtain a simulated vehicle following position of a target vehicle; obtaining lane line type information and lane line position information in front of the target vehicle; and controlling the target vehicle to follow the vehicle based on the lane line type information, lane line position information and simulated vehicle following position. The vehicle following control method proposed in the embodiment of the present application not only considers the influence of the front vehicle speed and wind speed on the wake vortex during driving, but also considers the influence of lane line type and lane line position. It can ensure that the target vehicle is controlled as close to the simulated vehicle following position as possible under the premise of complying with traffic rules and ensuring vehicle following safety, so as to make full use of the negative pressure of the wake vortex of the vehicle to be followed, so as to improve the vehicle following fuel economy of the target vehicle.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control, and more specifically, to a vehicle following control method and related equipment. Background Art

[0002] Aerodynamic drag is generally characterized by the drag coefficient. For fuel vehicles, a 10% decrease in the drag coefficient reduces fuel consumption by about 3%. For electric vehicles, a 0.02 decrease in the drag coefficient increases the driving range by about 10 km. Vehicle formation significantly reduces the drag experienced by each vehicle because the total pressure in the tail vortex area is small, so when the vehicle is driving within the tail vortex area of ​​the front vehicle, it will obtain a smaller pressure difference drag. This reduction in drag means less fuel consumption, higher fuel efficiency and less pollution. In some current following schemes, the tail vortex area is usually calculated based on the speed of the vehicle in front, and the following vehicle is controlled to enter the tail vortex area to follow in order to save fuel. However, the current following method cannot make accurate judgments on the tail vortex area based on wind speed and different vehicle models, and the energy-saving effect is greatly reduced. Summary of the invention

[0003] A series of simplified concepts are introduced in the Summary of the Invention, which will be further described in detail in the Detailed Description of the Invention. The Summary of the Invention does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0004] In order to provide a more energy-saving and convenient vehicle following method, in a first aspect, the present invention proposes a vehicle following control method, the method comprising:

[0005] Acquire driving information of the vehicle to be followed, wherein the driving information includes vehicle speed information and wind speed information;

[0006] The vehicle speed information and the wind speed information are used as inputs of a wake vortex simulation model to obtain a simulated following position of the target vehicle;

[0007] Obtain the lane line type information and lane line position information in front of the target vehicle;

[0008] Based on the lane line type information, the lane line position information and the simulated following vehicle position, the target vehicle is controlled to follow the vehicle.

[0009] Optionally, the above-mentioned obtaining of lane line type information and lane line position information includes:

[0010] Acquire road image information in front of the target vehicle;

[0011] Binarizing the image information based on a preset threshold to obtain binary road image information;

[0012] Obtain lane line pixel points according to the above binary road image information;

[0013] Based on the lane line pixel points, the least square method is used to perform fitting to obtain the lane line type and the lane line position.

[0014] Optionally, the driving information also includes vehicle appearance information;

[0015] The wind speed information and the vehicle speed information are used as inputs of the wake vortex simulation model to obtain the simulated following position of the target vehicle, including:

[0016] Determining the shape parameters of the vehicle to be followed in the vehicle shape library of the trailing vortex simulation model based on the vehicle shape information;

[0017] Determine the crosswind speed parameter and the crosswind direction parameter in the wind speed library of the wake vortex simulation model based on the wind speed information;

[0018] Determining a vehicle speed parameter in a vehicle speed library of the wake vortex simulation model based on the vehicle speed information;

[0019] A simulation calculation is performed based on the shape parameters of the vehicle to be followed, the side wind speed parameters, the side wind direction parameters, and the vehicle speed parameters as inputs of the tail vortex simulation model to obtain a simulated following vehicle position.

[0020] Optionally, the above method further includes:

[0021] Construct various 3D flow field simulation models based on fluid mechanics simulation method and vehicle shape database;

[0022] A preset simulated following vehicle position is obtained by simulation based on the vehicle speed database, the wind speed database and the above three-dimensional flow field simulation model;

[0023] The above-mentioned wake vortex simulation model is obtained by iterative training based on the neural network method through the wake vortex measurement data of the following vehicle test and the above-mentioned preset simulation following vehicle position.

[0024] Optionally, the controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position includes:

[0025] When the lane line is a solid line and the simulated following vehicle position is in a lane adjacent to the vehicle to be followed, controlling the vehicle to be followed to travel close to the first side lane line of the current driving lane;

[0026] Controlling the target vehicle to drive close to the second side lane line of the current driving lane;

[0027] The vehicle distance information between the vehicle to be followed and the target vehicle is controlled based on the simulated following vehicle position.

[0028] Optionally, the controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position includes:

[0029] When the lane line is a dotted line and the simulated following vehicle position is on the lane line, controlling the vehicle to be followed to travel in the current driving lane close to the lane line;

[0030] Control the target vehicle to drive in an adjacent lane close to the lane line;

[0031] Controlling the distance information between the vehicle to be followed and the target vehicle based on the simulated following vehicle position;

[0032] Based on the lane lines, a following safety warning is provided for the vehicle to be followed and the target vehicle.

[0033] Optionally, the above method further includes:

[0034] When the vehicle to be followed turns, obtaining a first yaw angle of the vehicle to be followed;

[0035] A second yaw angle of the target vehicle is determined based on the first yaw angle and the tail vortex simulation model, so that the target vehicle approaches a current maximum tail vortex pressure position.

[0036] In a second aspect, the present invention further provides a vehicle following control device, comprising:

[0037] A first acquisition unit, used to acquire the driving information of the vehicle to be followed;

[0038] A second acquisition unit is used to use the vehicle speed information and the wind speed information as inputs of a wake vortex simulation model to obtain a simulated following position of the target vehicle, wherein the wake vortex simulation model is obtained through iterative training based on a fluid mechanics simulation method and a neural network method;

[0039] A determination unit, used to obtain lane line type information and lane line position information in front of the target vehicle;

[0040] A control unit is used to control the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position.

[0041] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to implement the steps of the vehicle following control method of any one of the above-mentioned first aspect when executing the computer program stored in the memory.

[0042] In a fourth aspect, the present invention further proposes a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the vehicle following control method of any one of the above items in the first aspect is implemented.

[0043] In summary, the following vehicle control method of the embodiment of the present application includes: obtaining the driving information of the vehicle to be followed, wherein the driving information includes vehicle speed information and wind speed information; using the vehicle speed information and wind speed information as the input of the wake vortex simulation model to obtain the simulated following vehicle position of the target vehicle; obtaining the lane line type information and lane line position information in front of the target vehicle; and controlling the target vehicle to follow the vehicle based on the lane line type information, lane line position information and simulated following vehicle position. The following vehicle control method proposed in the embodiment of the present application not only considers the influence of the speed of the preceding vehicle on the wake vortex, but also considers the influence of the wind speed on the wake vortex during driving, and the obtained simulated following vehicle position is more accurate. In the present application, the influence of the lane line type and the lane line position are considered at the same time, which can ensure that the target vehicle is controlled as close to the simulated following vehicle position as possible under the premise of complying with traffic rules and ensuring the safety of following the vehicle, so as to make full use of the negative pressure of the wake vortex of the vehicle to be followed, so as to improve the following vehicle fuel economy of the target vehicle.

[0044] The vehicle following control method of the present invention, and other advantages, objectives and features of the present invention will be reflected in part through the following description, and in part will be understood by those skilled in the art through research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present specification. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0046] Figure 1 A flow chart of a vehicle following control method provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of the measurement principle of vehicle-following driving related parameters provided in an embodiment of the present application;

[0048] Figure 3 A schematic diagram of the structure of a wind measurement system provided in an embodiment of the present application;

[0049] Figure 4 A schematic diagram of a sensor arrangement for a vehicle following test provided in an embodiment of the present application;

[0050] Figure 5 A schematic diagram of another arrangement of sensors for a vehicle following test provided in an embodiment of the present application;

[0051] Figure 6 A schematic diagram of a vehicle platoon driving provided in an embodiment of the present application;

[0052] Figure 7 Another schematic diagram of vehicle platoon driving provided in an embodiment of the present application;

[0053] Figure 8 A schematic diagram of a method for following a vehicle while turning provided in an embodiment of the present application;

[0054] Fig. 9 A schematic diagram of the structure of a vehicle following control device provided in an embodiment of the present application;

[0055] Fig.10 A schematic diagram of the structure of a vehicle following control electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The following vehicle control method proposed in the embodiment of the present application not only considers the influence of the speed of the preceding vehicle on the tail vortex, but also considers the influence of the wind speed on the tail vortex during driving, and the obtained simulated following vehicle position is more accurate. The present application considers the influence of the lane line type and the lane line position at the same time, and can ensure that the target vehicle is controlled as close to the simulated following vehicle position as possible under the premise of complying with traffic rules and ensuring the safety of following vehicles, so as to make full use of the negative pressure of the tail vortex of the vehicle to be followed, so as to improve the following vehicle fuel economy of the target vehicle.

[0057] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0058] See also Figure 1 , is a flow chart of a vehicle following control method provided in an embodiment of the present application, which may specifically include:

[0059] S110, obtaining driving information of the vehicle to be followed, wherein the driving information includes vehicle speed information and wind speed information;

[0060] For example, the vehicle to be followed is the preceding vehicle. Figure 2 As shown, in some target vehicles that implement the following strategy, a 5-hole probe can be installed on the front of the vehicle to connect to a high-precision ALPHA sensor to identify the yaw angle, and the wind speed facing the front of the vehicle can be measured through a Pitot tube, and the direction and intensity of the crosswind can be calculated based on the current vehicle speed. A millimeter-wave radar is installed on the front of the vehicle to identify the position and relative speed of the front vehicle, and the speed of the front vehicle is calculated based on the current vehicle speed. It is understandable that if the front vehicle can communicate with the rear vehicle, the speed of the front vehicle can also be measured by the ECU (Electronic Control Uni) of the front vehicle, and the measurement results can be transmitted to the rear vehicle or the cloud for calculating the following strategy. Wind speed information can also be measured by a roadside wind speed measuring device, which can be used as follows Figure 3 The wind speed is measured in the manner shown. A base 101 is set on an open ground, including two first sliding devices 102 and a second sliding device 103. The second slide rail 1032 of the second sliding device 103 is installed on the first sliders 1021 of the two first sliding devices 102. A guide device 106 is fixed on both ends of the first slider 1021 and the base 101. The first motor 1051 and the second motor 1052 are installed on the base 101. The transmission belt 107 envelops the output shafts of the first motor 1051 and the second motor 1052, and the guide device 106 installed on the first slider 1021 and the base 101, forming an "I" shape. By controlling the speed of the motor, the moving direction of the wind measuring component 104 fixedly connected to the second slider 1031 can be controlled, thereby controlling the side wind component to measure the wind speed and wind direction at a designated location.

[0061] (When v≤3m / s)

[0062] R1 is the speed of the first motor, v is the measured wind speed, a and b are constants. The smaller the measured wind speed v, the greater the speed of the first motor or the second motor, ensuring the rapid movement of the second slider. R2 is the speed of the second motor. The smaller the measured wind speed v, the smaller the difference between R1 and R2, and the second slider is kept moving horizontally or vertically; the greater the measured wind speed v, the greater the difference between R1 and R2, and the slider moves in the tilt direction.

[0063] (When v>3m / s)

[0064] When v>3m / s, i, j are the rotation directions of the first motor and the second motor, clockwise is the positive direction, n is a constant, the speed R2 and direction of the second motor are adaptively adjusted following the speed and direction of the first motor, c is the measured wind direction angle, the horizontal right angle is 0, and the counterclockwise angle becomes larger (such as when the wind direction points to the right of the horizontal axis, c=0, ntanc=0, the requirement is that the second slider needs to move horizontally to the left or right to be parallel to the wind direction, at this time iR1+jR2=0, the physical meaning is that the first motor and the second motor have the same speed and are in opposite directions), n is the proportional coefficient, through this method, the first motor and the second motor control the second slider to slowly translate in the direction parallel to the wind direction.

[0065] S120, using the vehicle speed information and the wind speed information as inputs of a wake vortex simulation model to obtain a simulated following position of a target vehicle;

[0066] For example, the wake vortex simulation model can be loaded on the target vehicle or in the cloud. Before the target vehicle follows the vehicle, the identified vehicle speed information and wind speed information are used as input, and the wake vortex simulation model is used to obtain the simulated following position. When the intensity of the crosswind is large, the wake vortex will shift to the adjacent lane, and the simulated following position will also shift to the adjacent lane accordingly to achieve close following, and the crosswind is used to avoid the minimum 50m following distance in the same lane of the highway stipulated by regulations.

[0067] S130, obtaining lane line type information and lane line position information in front of the target vehicle;

[0068] For example, the type of lane line can be determined based on the lane line information of the current area transmitted from the cloud to determine whether the current road section is a dotted line or a solid line, or the type and position information of the lane line can be identified by sensors carried by the vehicle to be followed or the target vehicle.

[0069] S140, controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position.

[0070] Exemplarily, the target vehicle is controlled to follow the vehicle according to the lane line type information, lane line position information and simulated following position. When the lane line is a solid line, the vehicle is not allowed to change lanes or cross the line. When the lane line is a dotted line, lane change and short-term cross-line driving can be achieved. For example, when the simulated following position is on the lane line, and the type of the lane line is a solid line, only the vehicle to be followed and the target vehicle are allowed to keep driving in their respective lanes. At this time, the target vehicle can be controlled to be as close to the simulated following position as possible; when the simulated following position and the front vehicle are in the same lane, the rear vehicle follows the front vehicle in the same lane and maintains a certain safe distance to meet safety requirements; when the simulated following position and the front vehicle are in the adjacent lane, and the lane line is a dotted line, observe whether the adjacent lane is available. If the adjacent lane is available and there are no other obstacle vehicles in front and behind, the rear vehicle drives to the simulated following position in the adjacent lane.

[0071] In summary, the following vehicle control method proposed in the embodiment of the present application not only considers the influence of the front vehicle speed on the tail vortex, but also considers the influence of the wind speed on the tail vortex during driving, and the obtained simulated following vehicle position is more accurate. In the present application, the influence of the lane line type and the lane line position are considered at the same time, which can ensure that the target vehicle is controlled as close to the simulated following vehicle position as possible under the premise of complying with traffic rules and ensuring the safety of following vehicles, so as to make full use of the tail vortex negative pressure of the vehicle to be followed, so as to improve the following vehicle fuel economy of the target vehicle.

[0072] In some examples, the obtaining of lane line type information and lane line position information includes:

[0073] Acquire road image information in front of the target vehicle;

[0074] Binarizing the image information based on a preset threshold to obtain binary road image information;

[0075] Acquire lane line pixel points according to the binary road image information;

[0076] The lane line type and the lane line position are obtained by fitting the lane line pixel points using the least square method.

[0077] Exemplarily, when performing lane line recognition, the road image in front of the car can be obtained through the front camera installed on the car; the obtained image is pre-processed by binarization; possible pixel points of the lane line are searched, and possible pixel points of the lane line are simulated; a lane line search area is generated, and lane points are found in the search zone, and the lane line is fitted by the least square method. The lane line may include a turning lane line, and may also include a non-turning lane line. The non-turning lane line also includes the situation on the highway, because when the highway turns, the radius of the turn is relatively large and can be treated as a straight line; the result of the pixel point continuity of the binary image is counted to identify the dashed lane line and the solid lane line; the fitted curve is displayed on a predetermined user interface, and the curve is a solid line or a dashed line. When the lane line is identified as a solid line, the vehicle is only allowed to drive in the current lane; when the lane line is identified as a dashed line, the vehicle is allowed to change lanes or temporarily occupy the dashed lane.

[0078] In summary, the following vehicle control method proposed in the embodiment of the present application calculates the simulated following vehicle position through the wake vortex simulation model, and distinguishes the types of lane lines based on the image recognition method. Under the premise of ensuring compliance with traffic regulations, the target vehicle is controlled to follow the vehicle at the relatively maximum wake vortex negative pressure, thereby improving the fuel economy of the target vehicle following the vehicle.

[0079] In some examples, the driving information also includes vehicle appearance information;

[0080] The wind speed information and the vehicle speed information are used as inputs of a wake vortex simulation model to obtain a simulated following position of a target vehicle, including:

[0081] Determining the shape parameters of the vehicle to be followed in the vehicle shape library of the wake vortex simulation model based on the vehicle shape information;

[0082] Determining a crosswind speed parameter and a crosswind direction parameter in a wind speed library of the wake vortex simulation model based on the wind speed information;

[0083] Determining a vehicle speed parameter in a vehicle speed library of the wake vortex simulation model based on the vehicle speed information;

[0084] A simulation calculation is performed based on the shape parameters of the vehicle to be followed, the side wind speed parameters, the side wind direction parameters, and the vehicle speed parameters as inputs of a tail vortex simulation model to obtain a simulated following vehicle position.

[0085] For example, due to the different appearances of vehicles, i.e., length, style, height or appearance shape, which will affect the flow field formed by the air flowing through the front vehicle when the vehicle is driving, the tail vortex areas formed by vehicles with different appearances under the same driving conditions are not the same. The influence of the vehicle appearance on the formation of the tail vortex can be considered in the construction of the tail vortex model and during the driving process. The tail vortex simulation model is a model trained with a large amount of data. The trained tail vortex model provides the vehicle with a vehicle appearance library, a wind speed library, and a vehicle speed library. After the target vehicle obtains the appearance information, vehicle speed information and wind speed information of the vehicle to be followed, it selects the appearance parameters, crosswind speed parameters, crosswind direction parameters and vehicle speed parameters of the vehicle to be followed corresponding to its information in the corresponding database as the input of the tail vortex simulation model for simulation calculation to obtain the simulated following position.

[0086] In summary, the following vehicle control method proposed in the present application obtains the vehicle shape information, wind speed information and vehicle speed information, selects the corresponding vehicle shape parameters, crosswind speed parameters, crosswind direction parameters and vehicle speed parameters to be followed in the database corresponding to the wake vortex simulation model, and uses the above parameters as the input of the wake vortex simulation model, which can quickly simulate and calculate the accurate simulated following vehicle position.

[0087] In some examples, the method further includes:

[0088] Construct various 3D flow field simulation models based on fluid mechanics simulation method and vehicle shape database;

[0089] A preset simulated following vehicle position is obtained by simulation based on the vehicle speed database, the wind speed database and the above three-dimensional flow field simulation model;

[0090] The above-mentioned wake vortex simulation model is obtained by iterative training based on the neural network method through the wake vortex measurement data of the following vehicle test and the above-mentioned preset simulation following vehicle position.

[0091] Exemplarily, by means of computational fluid dynamics, a wake vortex simulation model of the preceding vehicle is obtained. The simulation model includes a database of the shape of the vehicle to be followed, a database of the speed of the vehicle, and a database of the wind speed. The input of the wake vortex simulation model includes simulation parameters of the crosswind speed and the crosswind direction, simulation parameters of the speed of the preceding vehicle, and the shape parameters of the preceding vehicle. The output of the wake vortex simulation model is the coordinate simulation parameters of the position where the negative pressure of the wake vortex of the preceding vehicle is relatively strong, i.e., the simulated following position. The trained wake vortex simulation model can be obtained by iteratively training the simulated following position output by the flow field simulation model in combination with the wake vortex measurement data obtained from the following test. The trained wake vortex simulation model can be loaded on the target vehicle and used to determine the simulated following position according to the identified shape information, speed information, and wind speed information of the preceding vehicle. The wake vortex simulation model trained by the neural network has a faster calculation speed, and the error between the determined following position and the actual position with the maximum wake vortex intensity is smaller, so that a faster and more accurate following strategy can be achieved.

[0092] Specifically constructing a trained wake vortex simulation model may include the following steps:

[0093] S210, constructing an initial neural network model;

[0094] With the goal of minimizing the error between the measured value of the position where the negative pressure of the front vehicle's tail vortex is stronger and the actual position where the negative pressure of the front vehicle's tail vortex is stronger output by the initial neural network model, the crosswind speed and direction simulation parameters, the vehicle speed simulation parameters of the front vehicle and the front vehicle appearance parameters are input into the initial neural network model for iterative training to obtain a target neural network model for obtaining the measured value of the position where the negative pressure of the front vehicle's tail vortex is stronger (simulated following position). The type of the initial neural network model can be a feedback neural network model, a deep learning neural network model, a convolutional neural network model, etc., which are not limited here. According to the type of the initial neural network model, the step training operation can be completed. Specifically, the initial neural network model can be understood as an untrained target neural network model, which can input the crosswind speed and direction simulation parameters and the vehicle speed simulation parameters of the front vehicle, and output the measured value of the position where the negative pressure of the initial front vehicle's tail vortex is stronger through neural network calculation. Normally, the initial neural network model may include an input layer, a hidden layer and an output layer, wherein the hidden layer is responsible for the relevant calculations of the neural network. Through iterative training, the weight parameters and other relevant transfer function parameters in the hidden layer may be gradually adjusted so that the initial wheel center vertical displacement measurement signal output by the initial neural network model meets the established training objectives. At this time, the initial neural network model may be considered as the target neural network model, and the measurement value of the position where the initial leading vehicle tail vortex negative pressure is stronger output by it may be identified as the measurement value of the position where the leading vehicle tail vortex negative pressure is stronger.

[0095] S220, obtaining the initial simulation model of the tail vortex of the preceding vehicle, including: obtaining the initial simulation model of the initial tail vortex of the preceding vehicle, inputting the crosswind speed parameter, the crosswind direction parameter, the speed parameter of the vehicle to be followed and the shape parameter of the vehicle to be followed into the initial simulation model of the tail vortex for simulation, and obtaining the coordinate simulation parameters of the position where the negative pressure of the tail vortex of the preceding vehicle is strong output by the initial tail vortex simulation model. The tail vortex simulation model of the preceding vehicle is obtained by the method of computational fluid dynamics; wherein the preceding vehicle selects a specific vehicle model with known shape dimension parameters in the database, i.e., the target type vehicle (also referred to as the preceding vehicle), the input of the tail vortex simulation model includes the simulation parameters of the crosswind speed and direction, the speed simulation parameters of the preceding vehicle, and the output of the tail vortex simulation model is the coordinate simulation value of the position where the negative pressure of the tail vortex of the preceding vehicle is strong, i.e., the preset simulation following vehicle position.

[0096] S230, obtaining the tail vortex measurement data of the following vehicle test, based on the actual crosswind speed and direction and vehicle speed of the target type vehicle, and obtaining the test sensor signal through the whole vehicle sensor group on the vehicle behind the target type vehicle; wherein the whole vehicle sensor group includes: one or more of ALPHA sensor, pitot tube, pressure sensor, millimeter wave radar, camera. Based on the test sensor signal and the simulation output value, the initial tail vortex simulation model of the leading vehicle is optimized to the tail vortex simulation model of the leading vehicle.

[0097] S240, training a neural network model based on the initial simulation data of the tail vortex and the tail vortex measurement data of the following vehicle test to obtain a tail vortex simulation model. The goal is to minimize the error between the initial simulation data and the tail vortex measurement data of the following vehicle test, input the crosswind speed and direction simulation parameters, and the vehicle speed simulation parameters of the front vehicle into the initial neural network model for iterative training, and obtain a target neural network model for the measurement value of the position where the front vehicle tail vortex negative pressure is strong. Specifically, using the tail vortex simulation model of the front vehicle obtained in step S220, multiple groups of crosswind speed and direction simulation parameters that meet the test accuracy, the vehicle speed simulation parameters of the front vehicle, and the coordinate simulation values ​​of the position where the front vehicle tail vortex negative pressure is strong (preset simulation following vehicle position) and the tail vortex measurement data of the following vehicle test can be obtained, so as to construct a training set of the initial neural network model, complete the iterative training of the initial neural network model, and obtain the target neural network model for the measurement value of the position where the front vehicle tail vortex negative pressure is strong, that is, the tail vortex simulation model.

[0098] In summary, the following vehicle control method proposed in the embodiment of the present application uses a trained wake vortex simulation model to determine the simulated following vehicle position based on the identified leading vehicle shape information, vehicle speed information and wind speed information. The calculation speed is faster, and the error between the determined following vehicle position and the actual position with the maximum wake vortex intensity is smaller. It can achieve a faster and more accurate following strategy and can effectively save the energy consumption of the following vehicle.

[0099] In some examples, the method further includes:

[0100] Acquiring front pressure data and rear pressure data of the target vehicle at different positions in the tail vortex area corresponding to the vehicle to be followed;

[0101] The tail vortex measurement data of the following vehicle test is obtained based on the vehicle head pressure data and the parking space pressure data.

[0102] For example, Figure 4 and Figure 5As shown, in some vehicles, 4 patch pressure sensors are installed in the head area of ​​the vehicle and 8 patch pressure sensors are installed in the rear area of ​​the vehicle. Simulate following the vehicle and measure the absolute pressure value of the front of the vehicle and the front and rear pressure difference at the position where the negative pressure of the tail vortex of the leading vehicle is strong. During the test, multiple measurements are made within a preset range near and at the position where the negative pressure of the tail vortex of the leading vehicle is strong to test whether the area with strong negative pressure of the tail vortex of the leading vehicle is accurate, and the measurement results are summarized to form the tail vortex measurement data of the following vehicle test, which is used to train the tail vortex simulation model. It can be understood that the following vehicle test can change the shape of the leading vehicle, the speed of the leading vehicle and the wind speed to obtain more comprehensive tail vortex measurement data of the following vehicle test under different following vehicle conditions.

[0103] In summary, the following control method provided in the embodiment of the present application, by adding pressure sensors at the front and rear ends of the target vehicle, obtains the following test tail vortex measurement data through the following test, and optimizes the tail vortex simulation model based on the neural network according to the following test tail vortex measurement data, so as to obtain a more accurate tail vortex simulation model, and can provide the target vehicle with a more accurate simulated following position in the actual following of the target vehicle, so as to make fuller use of the position with stronger tail vortex negative pressure to achieve the purpose of energy-saving following.

[0104] In some examples, the controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position includes:

[0105] When the lane line is a solid line and the simulated following vehicle position is in a lane adjacent to the vehicle to be followed, controlling the vehicle to be followed to travel close to the first side lane line of the current driving lane;

[0106] Controlling the target vehicle to drive close to the second side lane line of the current driving lane;

[0107] The vehicle distance information between the vehicle to be followed and the target vehicle is controlled based on the simulated following vehicle position.

[0108] For example, Figure 6 As shown in the figure, when the lane line is a solid line and the vehicle to be followed and the target vehicle are traveling in the same lane, and due to the influence of the crosswind, the simulated following position is not in the current lane but in the adjacent lane, in order to make the best use of the tail vortex of the leading vehicle, the vehicle to be followed is controlled to drive close to the first side lane line of the current lane, and the first side lane line is the direction of the incoming wind. The target vehicle is controlled to drive close to the second side lane line of the current lane to minimize the influence of the crosswind on the strong position deviation of the tail vortex, and the leading and following vehicles are controlled to drive as close as possible to the two sides of the current lane, so that the following position of the vehicle is as close as possible to the position with strong negative pressure of the tail vortex.

[0109] In summary, the vehicle following control method provided in the embodiment of the present application is:

[0110] In some examples, the controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position includes:

[0111] When the lane line is a dotted line and the simulated following vehicle position is on the lane line, controlling the vehicle to be followed to travel in the current driving lane close to the lane line;

[0112] Control the target vehicle to drive in an adjacent lane close to the lane line;

[0113] Controlling the distance information between the vehicle to be followed and the target vehicle based on the simulated following vehicle position;

[0114] Based on the lane lines, a following safety warning is provided for the vehicle to be followed and the target vehicle.

[0115] For example, Figure 7 As shown in the figure, when the yaw angle is small, the simulated following position may fall on the lane line. In order to make full use of the crosswind and not occupy the lane line, the vehicle to be followed and the target vehicle are controlled to drive in two lanes close to the lane line, such as the front vehicle driving along the left side of a lane line and the rear vehicle driving along the right side of the same lane line, so that the rear vehicle falls into the negative pressure area of ​​the tail vortex of the front vehicle and is as close as possible to the position where the negative pressure of the tail vortex is strong. When the left side of the vehicle is close to the lane line, the position of the fitting curve of the lane line on the user interface is recorded as the threshold position. When the user does not turn left, that is, there is no intention to change lanes to the left, the lane line crosses the threshold position, and an image reminder message is displayed. If the threshold position is crossed for more than 5 seconds, an alarm message is displayed (to avoid misjudging the user turning right along the lane line), or when the fitting curve on the user interface slowly crosses the threshold position at a speed exceeding the judgment threshold, an alarm message is displayed (to avoid the user quickly intruding into the adjacent lane when there is no intention to change lanes). When the right side of the vehicle approaches the lane line, the position of the fitting curve of the lane line on the user interface is recorded as the threshold position. When the user does not make a right turn, that is, has no intention to change lanes to the right, the lane line slowly crosses the threshold position, and an image reminder message is displayed. If it crosses the threshold position for more than 5 seconds, an alarm message is displayed (to avoid misjudging the user turning left along the lane line); or when the speed at which the fitting curve on the user interface crosses the threshold position exceeds the judgment threshold, an alarm message is displayed (to avoid the user quickly intruding into the adjacent lane when there is no intention to change lanes).

[0116] In summary, the vehicle following method proposed in the present application controls the vehicles to be followed to travel in two lanes close to the lane lines when the simulated following position falls within a certain range of the lane lines, and uses the lane lines as the basis for safety warnings, thereby ensuring the safety of following the vehicle while making full use of the tail vortex for following.

[0117] In some examples, the method further includes:

[0118] When the vehicle to be followed turns, obtaining a first yaw angle of the vehicle to be followed;

[0119] A second yaw angle of the target vehicle is determined based on the first yaw angle and the tail vortex simulation model, so that the target vehicle approaches a current maximum tail vortex pressure position.

[0120] For example, Figure 8 As shown, when turning along the lane line, when the size and direction of the crosswind remain unchanged, the yaw angle of the leading vehicle may gradually increase or decrease as the turning process progresses. According to the wake vortex simulation model obtained in the above embodiment, the wind speed input information is corrected according to the first yaw angle, the current simulated following position is determined according to the corrected input information, and the driving direction of the target vehicle is controlled according to the current simulated following position, and the second yaw angle of the target vehicle is determined. As the yaw angle of the leading vehicle continues to change, the rear vehicle gradually adjusts its position and drives in the adjacent lane to a position where the negative pressure of the wake vortex of the leading vehicle is strong.

[0121] In summary, the vehicle following method proposed in the present application corrects the input of the tail vortex simulation model according to the first turning yaw angle of the vehicle to be followed, calculates a more reasonable current simulated following position, and provides an energy-saving following strategy when turning.

[0122] See also Fig. 9 , an embodiment of the vehicle following control device in the embodiment of the present application may include:

[0123] A first acquisition unit 21 is used to acquire driving information of the vehicle to be followed, wherein the driving information includes vehicle speed information and wind speed information;

[0124] A second acquisition unit 22, used for taking the vehicle speed information and the wind speed information as inputs of a wake vortex simulation model to acquire a simulated following position of a target vehicle;

[0125] A determination unit 23, used to obtain lane line type information and lane line position information in front of the target vehicle;

[0126] The control unit 24 is used to control the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position.

[0127] like Fig.10As shown, an embodiment of the present application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 320 and executable on the processor, and when the processor 320 executes the computer program 311, the steps of any of the above-mentioned vehicle following control methods are implemented.

[0128] Since the electronic device introduced in this embodiment is a device used to implement a vehicle following control device in the embodiment of the present application, based on the method introduced in the embodiment of the present application, the technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by the technical personnel in this field to implement the method in the embodiment of the present application falls within the scope of protection of this application.

[0129] In the specific implementation process, when the computer program 311 is executed by the processor, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0130] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0131] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0132] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0134] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0135] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 The process of following vehicle control in the corresponding embodiment.

[0136] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0137] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0138] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0139] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0141] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0142] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle following control method, characterized in that: include: Acquire driving information of the vehicle to be followed, wherein the driving information includes vehicle speed information, wind direction information, and wind speed information, A measuring device is provided, through which the wind speed information and the wind direction information are determined, and the measuring device includes a first motor and a second motor; The expressions of the wind speed information and the wind direction information include: ； (when v≤3m / s); (when v>3m / s); Wherein, R1 is the speed of the first motor, v is the measured wind speed, a and b are constants, R2 is the speed of the second motor, when v>3m / s, i and j are the rotation directions of the first motor and the second motor, n is a constant, and c is the measured wind direction angle; Using the vehicle speed information, the wind direction information and the wind speed information as inputs of a wake vortex simulation model to obtain a simulated following position of a target vehicle; Obtain the lane line type information and lane line position information in front of the target vehicle; Controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position; Wherein, when the lane line type information is a solid line, the target vehicle is prohibited from changing lanes and crossing the line; When the lane line type information is a dotted line, the target vehicle is allowed to change lanes and cross the lane.

2. The method according to claim 1, characterized in that The obtaining of lane line type information and lane line position information includes: Acquire road image information in front of the target vehicle; Binarizing the image information based on a preset threshold to obtain binary road image information; Acquire lane line pixel points according to the binary road image information; The lane line type and the lane line position are obtained by fitting the lane line pixel points using the least square method.

3. The method according to claim 1, characterized in that The driving information also includes vehicle appearance information; The wind speed information and the vehicle speed information are used as inputs of a wake vortex simulation model to obtain a simulated following position of a target vehicle, including: Determining the shape parameters of the vehicle to be followed in the vehicle shape library of the wake vortex simulation model based on the vehicle shape information; Determining a crosswind speed parameter and a crosswind direction parameter in a wind speed library of the wake vortex simulation model based on the wind speed information; Determining a vehicle speed parameter in a vehicle speed library of the wake vortex simulation model based on the vehicle speed information; A simulation calculation is performed based on the shape parameters of the vehicle to be followed, the side wind speed parameters, the side wind direction parameters, and the vehicle speed parameters as inputs of a tail vortex simulation model to obtain a simulated following vehicle position.

4. The method according to claim 3, characterized in that Also includes: Construct various 3D flow field simulation models based on fluid mechanics simulation method and vehicle shape database; Perform simulation based on the vehicle speed database, the wind speed database and the three-dimensional flow field simulation model to obtain a preset simulation following vehicle position; The wake vortex simulation model is obtained by iterative training based on the neural network method using the wake vortex measurement data of the vehicle following test and the preset simulated vehicle following position.

5. The method according to claim 1, wherein the step of controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position comprises: When the lane line is a solid line and the simulated following vehicle position is in a lane adjacent to the vehicle to be followed, controlling the vehicle to be followed to travel close to a first side lane line of the current driving lane; Controlling the target vehicle to travel close to the second side lane line of the current driving lane; The vehicle distance information between the vehicle to be followed and the target vehicle is controlled based on the simulated following vehicle position.

6. The method according to claim 1, wherein the step of controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position comprises: When the lane line is a dotted line and the simulated following vehicle position is on the lane line, controlling the vehicle to be followed to travel in the current driving lane close to the lane line; Controlling the target vehicle to travel in an adjacent lane close to the lane line; Controlling the distance information between the vehicle to be followed and the target vehicle based on the simulated following vehicle position; Based on the lane line, a vehicle following safety warning is provided to the vehicle to be followed and the target vehicle.

7. The method according to claim 1, wherein the step of controlling the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position comprises: When the vehicle to be followed turns, obtaining a first yaw angle of the vehicle to be followed; A second yaw angle of the target vehicle is determined based on the first yaw angle and the tail vortex simulation model, so that the target vehicle approaches a current maximum tail vortex pressure position.

8. A vehicle following control device, characterized in that: include: a first acquisition unit, configured to acquire driving information of a vehicle to be followed, wherein the driving information includes vehicle speed information, wind direction information, and wind speed information, and a measuring device is provided, and the wind speed information and the wind direction information are determined by the measuring device, and the measuring device includes a first motor and a second motor; The expressions of the wind speed information and the wind direction information include: ； (when v≤3m / s); (when v>3m / s); Wherein, R1 is the speed of the first motor, v is the measured wind speed, a and b are constants, R2 is the speed of the second motor, when v>3m / s, i and j are the rotation directions of the first motor and the second motor, n is a constant, and c is the measured wind direction angle; A second acquisition unit is used to use the vehicle speed information, the wind direction information and the wind speed information as inputs of a wake vortex simulation model to acquire a simulated following position of a target vehicle; A determination unit, used to obtain lane line type information and lane line position information in front of the target vehicle; A control unit, configured to control the target vehicle to follow the vehicle based on the lane line type information, the lane line position information and the simulated following vehicle position; Wherein, when the lane line type information is a solid line, the target vehicle is prohibited from changing lanes and crossing the line; When the lane line type information is a dotted line, the target vehicle is allowed to change lanes and cross the lane.

9. An electronic device, comprising: A memory and a processor, wherein the processor is used to implement the steps of the vehicle following control method as described in any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the following vehicle control method as described in any one of claims 1 to 7 is implemented.

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