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 and driving route information of a vehicle to be followed, wherein the driving information comprises vehicle speed information; determining the route overlap between the target vehicle and the vehicle to be followed based on the driving route information; and controlling the target vehicle to follow the vehicle to be followed for following driving when the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed. The vehicle following control method proposed in the embodiment of the present application obtains the vehicle speed and driving route of the vehicle to be followed, first determines whether the route overlap between the target vehicle and the route of the vehicle to be followed and the vehicle speed meet the following requirements, and promptly excludes vehicles that are not suitable for following, thereby saving computing power and increasing the success rate of following.

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 and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information;

[0006] Determine the degree of route overlap between the target vehicle and the vehicle to be followed based on the driving route information;

[0007] When the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed, the target vehicle is controlled to follow the vehicle to be followed.

[0008] Optionally, the driving information also includes wind speed information and vehicle shape information;

[0009] The above method further includes:

[0010] The driving information is used as an input 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;

[0011] Determining a relative position relationship between the simulated following vehicle position and the vehicle to be followed based on the lane line information;

[0012] The controlling the target vehicle to follow the vehicle to be followed includes:

[0013] Based on the relative position relationship, the target vehicle is controlled to follow the vehicle.

[0014] Optionally, the above-mentioned using the above-mentioned driving information as an input of the wake vortex simulation model to obtain the simulated following position of the target vehicle includes:

[0015] 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;

[0016] 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;

[0017] Determining a vehicle speed parameter in a vehicle speed library of the wake vortex simulation model based on the vehicle speed information;

[0018] 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.

[0019] Optionally, the above method further includes:

[0020] Construct various 3D flow field simulation models based on fluid mechanics simulation method and vehicle shape database;

[0021] 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;

[0022] 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.

[0023] Optionally, the wind speed information includes crosswind intensity;

[0024] The above-mentioned control of the target vehicle to follow the vehicle based on the above-mentioned relative position relationship includes:

[0025] When the crosswind intensity is less than or equal to the first intensity, the to-be-followed vehicle and the target vehicle are controlled to follow the vehicle in a straight line in the same lane and at a distance greater than the safety distance based on the relative position relationship;

[0026] and / or,

[0027] When the crosswind intensity is greater than the first intensity and less than or equal to the second intensity, the to-be-followed vehicle and the target vehicle are controlled to travel in the same lane and at a staggered following distance greater than the safety distance based on the relative position relationship;

[0028] and / or,

[0029] When the crosswind intensity is greater than the second intensity and less than or equal to the third intensity, the to-be-followed vehicle and the target vehicle are controlled to follow each other in adjacent lanes at a staggered following distance greater than the safety distance based on the relative position relationship;

[0030] and / or,

[0031] When the crosswind intensity is greater than the third intensity, the vehicle to be followed and the target vehicle are controlled to follow the target vehicle in the same lane at a safe speed and greater than the safety distance.

[0032] Optionally, the above method further includes:

[0033] Acquiring the driving status of the convoy vehicles, wherein the convoy vehicles include at least one of the to-be-followed vehicle and the target vehicle;

[0034] When there is an abnormal vehicle in the formation, control the abnormal vehicle to exit the formation driving mode;

[0035] Adjust the formation positions of the remaining vehicles so that the remaining vehicles in the formation can fully utilize the wake vortex generated by the leading vehicle.

[0036] Optionally, the above method further includes:

[0037] Obtaining the energy reserve status of the above-mentioned convoy vehicles;

[0038] Based on the above energy reserve status, the front and rear order of the vehicles in the formation is adjusted, and the second simulated following position is recalculated;

[0039] The positions of the vehicles in the formation are adjusted based on the second simulated following vehicle position.

[0040] In a second aspect, the present invention further provides a vehicle following control device, comprising:

[0041] An acquisition unit, used to acquire the driving information and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information;

[0042] A determination unit, used to determine the route overlap between the target vehicle and the vehicle to be followed based on the driving route information;

[0043] The control unit is used to control the target vehicle to follow the vehicle to be followed when the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed.

[0044] 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.

[0045] 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.

[0046] In summary, the following vehicle control method of the embodiment of the present application includes: obtaining the driving information and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information; determining the route overlap between the target vehicle and the vehicle to be followed based on the driving route information; and controlling the target vehicle to follow the vehicle to be followed for following driving when the route overlap is greater than or equal to the preset overlap and the vehicle speed information is greater than or equal to the preset following speed. The following vehicle control method proposed in the embodiment of the present application obtains the vehicle speed and driving route of the vehicle to be followed, first determines whether the route overlap between the target vehicle and the route of the vehicle to be followed and the vehicle speed meet the following vehicle requirements, and promptly excludes vehicles that are not suitable for following, thereby saving computing power and increasing the success rate of following vehicles.

[0047] 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

[0048] 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:

[0049] Figure 1 A flow chart of a vehicle following control method provided in an embodiment of the present application;

[0050] Figure 2 A schematic diagram of the measurement principle of vehicle-following driving related parameters provided in an embodiment of the present application;

[0051] Figure 3A schematic diagram of the structure of a wind speed measurement system provided in an embodiment of the present application;

[0052] Figure 4 A schematic diagram of a sensor arrangement for a vehicle following test provided in an embodiment of the present application;

[0053] Figure 5 A schematic diagram of another arrangement of sensors for a vehicle following test provided in an embodiment of the present application;

[0054] Figure 6 A schematic diagram of a simulated vehicle following position provided in an embodiment of the present application;

[0055] Figure 7 A schematic diagram of a vehicle platoon driving provided in an embodiment of the present application;

[0056] Figure 8 Another schematic diagram of vehicle platoon driving provided in an embodiment of the present application

[0057] Fig. 9 A schematic diagram of the structure of a vehicle following control device provided in an embodiment of the present application;

[0058] 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

[0059] The vehicle following control method proposed in the embodiment of the present application obtains the speed and driving route of the vehicle to be followed, first determines the overlap between the route of the target vehicle and the route of the vehicle to be followed and whether the speed meets the vehicle following requirements, and promptly excludes vehicles that are not suitable for following, thereby saving computing power and increasing the success rate of vehicle following.

[0060] 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.

[0061] 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:

[0062] S110, obtaining driving information and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information;

[0063] Exemplarily, the vehicle to be followed is the leading vehicle, and a millimeter-wave radar can be installed on the front of the trailing vehicle (target vehicle) to identify the position and relative speed of the leading vehicle, and the speed of the leading vehicle is calculated based on the current vehicle speed. It is understandable that if the leading vehicle can communicate with the trailing vehicle, the speed of the leading vehicle can also be measured by the ECU (Electronic Control Uni) of the leading vehicle, and the measurement result can be transmitted to the trailing vehicle or the cloud for calculating the following strategy. Wind speed information can also be measured by a roadside wind speed measuring device. The driving route information of the vehicle to be followed can be obtained based on the navigation information corresponding to the vehicle, or by statistically obtaining previous driving routes based on cloud data. S120. Determine the degree of route overlap between the target vehicle and the above-mentioned vehicle to be followed based on the above-mentioned driving route information;

[0064] For example, according to the driving route information of the vehicle to be followed obtained in step S210, if the overlap is high, the most suitable following position can be calculated through the target vehicle and the following vehicle can be driven. If the overlap is low, the following vehicle cannot be driven for a long time, which will cause a waste of computing resources.

[0065] S130: When the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed, control the target vehicle to follow the vehicle to be followed.

[0066] Exemplarily, the preset following speed can be the minimum following speed expected by the target vehicle, or the minimum speed at which the tail vortex generated by the vehicle to be followed can meet the safe following distance. It should be noted that if the speed of the leading vehicle is higher, the point with stronger negative pressure of the tail vortex formed by it will be farther away from the rear of the vehicle. Only when the speed is fast enough, the position of the point with stronger tail vortex can meet the requirement of safe following distance. Only when the line overlap is greater than or equal to the preset overlap and the speed is greater than or equal to the preset following speed can the tail vortex effect be fully utilized to save energy and avoid the waste of computing resources caused by only short-term following or failure to follow.

[0067] In summary, the vehicle following control method proposed in the embodiment of the present application, by obtaining the speed and driving route of the vehicle to be followed, first determines the degree of overlap between the route of the target vehicle and the route of the vehicle to be followed and whether the speed meets the vehicle following requirements, and promptly excludes vehicles that are not suitable for following, thereby saving computing power and increasing the success rate of vehicle following.

[0068] In some examples, the driving information also includes wind speed information and vehicle shape information;

[0069] The above method further includes:

[0070] The driving information is used as an input 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;

[0071] Determining a relative position relationship between the simulated following vehicle position and the vehicle to be followed based on the lane line information;

[0072] The controlling the target vehicle to follow the vehicle to be followed includes:

[0073] Based on the relative position relationship, the target vehicle is controlled to follow the vehicle.

[0074] For example, Figure 2 As shown in the figure, 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. The direction and intensity of the crosswind can be calculated based on the current vehicle speed. The simulated following position output by the flow field simulation model is combined with the tail vortex measurement data obtained from the following test to construct a neural network for iterative training to obtain a trained tail vortex simulation model. In some examples, the following method can also be used. 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.

[0075] (When v≤3m / s)

[0076] R 1 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 is, the greater the speed of the first motor or the second motor is, ensuring the rapid movement of the second slider. 2is the speed of the second motor. The smaller the wind speed v is, the faster R 1 With R 2 The smaller the difference is, the second slider is kept moving in the horizontal or vertical direction; the greater the measured wind speed v is, the greater the difference between R1 and R2 is, the slider moves along the inclined direction.

[0077] (When v>3m / s)

[0078] 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, and the speed of the second motor R 2 The direction follows the first motor speed and direction adaptive adjustment, c is the measured wind direction angle, the horizontal right angle is 0, 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 iR 1 +jR 2 =0, the physical meaning is that the first motor and the second motor have the same rotation 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 along the direction parallel to the wind direction.

[0079] The trained wake vortex simulation model can be loaded on the target vehicle or in the cloud. Before the target vehicle follows the vehicle, the recognized 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. 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, which can achieve a faster and more accurate following strategy. According to the calculated simulated following position and the lane information on the driving road, there may be three situations, namely, the simulated following position is in the same lane as the leading vehicle, the simulated following position is in an adjacent lane with the leading vehicle, and the simulated following position and the leading vehicle are on the lane line of the leading vehicle's driving lane. The target vehicle is controlled to follow the vehicle according to the relative position relationship. For example, when the simulated following position is on the lane line, the rear vehicle is not allowed to occupy the lane line for a long time; 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 an adjacent lane, observe whether the adjacent lane is available. If the adjacent lane is available and there are no other obstructing vehicles in front and behind, the rear vehicle drives in the adjacent lane to the simulated following position.

[0080] In summary, the following vehicle control method proposed in the embodiment of the present application not only takes into account the influence of the speed of the leading vehicle on the wake vortex, but also takes into account the influence of the wind speed on the wake vortex during the process, and the resulting simulated following vehicle position is more accurate; at the same time, the present application utilizes a wake vortex simulation model trained by a neural network, which has a faster calculation speed, and the error between the determined following vehicle position and the actual position with the maximum wake vortex intensity is smaller, which can achieve a faster and more accurate following vehicle strategy.

[0081] In some examples, using the wind speed information and the vehicle speed information as inputs to a wake vortex simulation model to obtain a simulated following position of a target vehicle includes:

[0082] 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;

[0083] 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;

[0084] Determining a vehicle speed parameter in a vehicle speed library of the wake vortex simulation model based on the vehicle speed information;

[0085] 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.

[0086] 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.

[0087] 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.

[0088] In some examples, the method further includes:

[0089] Construct various 3D flow field simulation models based on fluid mechanics simulation method and vehicle shape database;

[0090] 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;

[0091] 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.

[0092] 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.

[0093] The specific steps of constructing a trained wake vortex simulation model may include:

[0094] S210, constructing an initial neural network model;

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] In some examples, the method further includes:

[0101] 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;

[0102] 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.

[0103] For example, Figure 4 and Figure 5 As 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.

[0104] 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.

[0105] In some examples, controlling the target vehicle to follow the vehicle based on the relative position relationship includes:

[0106] When the simulated following vehicle position is in the current driving lane of the vehicle to be followed and the distance between the simulated following vehicle position and the vehicle to be followed is greater than the legal distance, obtaining the road information of the current driving lane behind the vehicle to be followed, wherein the legal distance is the shortest following distance allowed under the current road conditions and the current vehicle speed;

[0107] When there is no other vehicle traveling within a first following distance behind the vehicle to be followed, the target vehicle is controlled to travel to the simulated following position for following driving, wherein the first following distance is determined based on the simulated following position and the outer dimensions of the target vehicle.

[0108] For example, after obtaining the simulated following vehicle position through the wake vortex simulation model, the lane line information is obtained through the front radar of the target vehicle or the rear radar of the vehicle to be followed, and the simulated following vehicle position and the lane line position are judged by the vehicle to be followed, the target vehicle or the cloud. If the simulated following vehicle position is in the current driving lane of the vehicle to be followed, for example Figure 6 The recommended position A in the image is obtained. At this time, the distance between the simulated following position and the vehicle to be followed is obtained, that is, the distance between the recommended position A and the vehicle to be followed. If the distance is greater than the legal distance, then it is obtained whether there are other vehicles within the first following distance behind the vehicle to be followed, that is, it is judged whether the target vehicle can interfere with the vehicle behind if it drives to the recommended position A. If there are no other vehicles within the first following distance, the target vehicle is controlled to follow the vehicle at the recommended position A. It should be noted that the legal distance is the shortest following distance that can be allowed under the premise of ensuring the safety of following the vehicle on the current road. The first distance is determined by the simulated following position and the external dimensions of the target vehicle, that is, the distance that can ensure that the target vehicle will not affect the normal driving of the vehicle behind when following the vehicle to be followed.

[0109] In summary, the embodiments of the present application provide a method for controlling a target vehicle following a target vehicle in which a simulated following position appears on the current driving road of the vehicle to be followed, which can ensure a safe distance from the leading vehicle when following the vehicle and will not affect the normal driving of the rear vehicle.

[0110] In some examples, controlling the target vehicle to follow the vehicle based on the relative position relationship includes:

[0111] When the simulated following vehicle position is in the adjacent lane of the vehicle to be followed, obtaining the adjacent lane road information behind the vehicle to be followed;

[0112] When there is no other vehicle traveling within a second following distance of the adjacent road behind the vehicle to be followed, the target vehicle is controlled to travel to the simulated following position for following driving, wherein the second following distance is determined based on the simulated following position, the outer dimensions of the target vehicle and the lane width.

[0113] For example, if the simulated following vehicle position is in the adjacent lane of the vehicle to be followed, such as Figure 6 The recommended position B in the simulation is used to obtain whether there are other vehicles within the second following distance in the adjacent lane behind the vehicle to be followed, that is, to determine whether the target vehicle can interfere with the vehicle behind it if it drives to the recommended position B. If there are no other vehicles within the second following distance, the target vehicle is controlled to follow the vehicle at the recommended position B. It should be noted that the second distance is determined by the simulated following position, the external dimensions of the target vehicle and the lane width, that is, the distance that can ensure that the target vehicle will not affect the normal driving of the vehicle behind it when following the vehicle to be followed.

[0114] In summary, the embodiments of the present application provide a method for controlling a target vehicle following a target vehicle whose simulated following position appears on a road adjacent to a vehicle to be followed, which can effectively follow the vehicle and prevent vehicles in adjacent lanes from driving normally.

[0115] In some examples, the wind speed information includes crosswind intensity;

[0116] The above-mentioned control of the target vehicle to follow the vehicle based on the above-mentioned relative position relationship includes:

[0117] When the crosswind intensity is less than or equal to the first intensity, the to-be-followed vehicle and the target vehicle are controlled to follow the vehicle in a straight line in the same lane and at a distance greater than the safety distance based on the relative position relationship;

[0118] and / or,

[0119] When the crosswind intensity is greater than the first intensity and less than or equal to the second intensity, the to-be-followed vehicle and the target vehicle are controlled to travel in the same lane and at a staggered following distance greater than the safety distance based on the relative position relationship;

[0120] and / or,

[0121] When the crosswind intensity is greater than the second intensity and less than or equal to the third intensity, the to-be-followed vehicle and the target vehicle are controlled to follow each other in adjacent lanes at a staggered following distance greater than the safety distance based on the relative position relationship;

[0122] and / or,

[0123] When the crosswind intensity is greater than the third intensity, the vehicle to be followed and the target vehicle are controlled to follow the target vehicle in the same lane at a safe speed and greater than the safety distance.

[0124] For example, by monitoring the strength of the crosswind, it is possible to preliminarily determine where the location of the strong tail vortex negative pressure occurs, and the safety distance can be set to 50 meters.

[0125] In one following mode, when the intensity of the crosswind is less than or equal to a first intensity, multiple vehicles travel at the same speed in the same lane and are spaced more than 50 meters apart. Multiple vehicles are allowed to be laterally staggered in the same lane to utilize the negative pressure of the tail vortex of the preceding vehicle and to meet safety distance requirements.

[0126] In another type of following, such as Figure 7 As shown, when the intensity of the crosswind is greater than the first intensity and less than or equal to the second intensity, multiple vehicles are traveling at the same speed in the same lane and are spaced more than 50 meters apart, and multiple vehicles are allowed to be laterally staggered in the same lane, or multiple vehicles are traveling at the same speed in adjacent lanes, and multiple vehicles are allowed to be laterally staggered in adjacent lanes to utilize the negative pressure of the tail vortex of the preceding vehicle and to meet relevant laws and regulations.

[0127] In another following method, Figure 8 As shown, when the intensity of the crosswind is greater than the second intensity and less than or equal to the third intensity, multiple vehicles travel at the same speed in adjacent lanes, and multiple vehicles are allowed to be laterally staggered in adjacent lanes to utilize the negative pressure of the tail vortex of the preceding vehicle.

[0128] In another following method, when the intensity of the side wind is greater than the third intensity, the vehicle speed is reduced to a safe speed, and multiple vehicles travel at the same speed in the same lane and at a distance of more than 50 meters to prevent vehicles in the formation from being blown over in extreme weather.

[0129] In summary, the vehicle following control method provided in the embodiment of the present application first estimates the lane that the target vehicle should be in through the crosswind intensity, and determines the specific position of the target vehicle based on the relative position relationship, making full use of the wake vortex generated by the leading vehicle.

[0130] In some examples, the method further includes:

[0131] Acquiring the driving status of the convoy vehicles, wherein the convoy vehicles include at least one of the to-be-followed vehicle and the target vehicle;

[0132] When there is an abnormal vehicle in the formation, control the abnormal vehicle to exit the formation driving mode;

[0133] Adjust the formation positions of the remaining vehicles so that the remaining vehicles in the formation can fully utilize the wake vortex generated by the leading vehicle.

[0134] Exemplarily, for vehicles in a formation, the position, speed, and steering information of multiple vehicles in the formation are obtained in real time. At the same time, joint threshold limits are imposed based on the speed and steering information of the vehicles, and abnormality detection is performed on the feedback data. When an abnormality occurs, the faulty vehicle is removed from the formation, and the rear vehicle first drives to Hugo's position according to a preset distance, and then the simulated following position is recalculated based on the speed information, shape information, and wind speed information of the front vehicle, and the following position of the rear vehicle is adjusted to make full use of the wake vortex generated by the front vehicle and save energy consumption.

[0135] In summary, the vehicle following control method provided in the embodiment of the present application can promptly kick abnormally driving vehicles out of the platoon, and calculate a new vehicle following position based on the new formation, thereby saving energy consumption.

[0136] In some examples, the method further includes:

[0137] Obtaining the energy reserve status of the above-mentioned convoy vehicles;

[0138] Based on the above energy reserve status, the front and rear order of the vehicles in the formation is adjusted, and the second simulated following position is recalculated;

[0139] The positions of the vehicles in the formation are adjusted based on the second simulated following vehicle position.

[0140] Exemplarily, the energy reserve status can be the remaining power of the vehicle, the remaining fuel information, and the vehicle with more energy is adjusted to the front to lead the way. After the order is adjusted, the new simulated following position (i.e., the second simulated following position) of each vehicle is recalculated and determined based on the new vehicle arrangement order, and the position of the vehicles in the formation is adjusted so that the rear vehicle falls as close as possible to the position where the wake formed by the front vehicle is stronger.

[0141] In summary, the vehicle following control method proposed in the embodiment of the present application can comprehensively consider the energy reserve status of vehicles in the formation when multiple vehicles are traveling in a platoon, coordinate the energy reserves of different vehicles to adjust the front and rear order of vehicles in the formation, and effectively improve the overall mileage of vehicles in the platoon.

[0142] See also Fig. 9 , an embodiment of the vehicle following control device in the embodiment of the present application may include:

[0143] An acquisition unit 21 is used to acquire the driving information and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information;

[0144] A determination unit 22, configured to determine a degree of overlap between the target vehicle and the vehicle to be followed based on the driving route information;

[0145] The control unit 23 is used to control the target vehicle to follow the vehicle to be followed when the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed.

[0146] like Fig.10 As 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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 comprising 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.

[0153] 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. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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 and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information; Determining the degree of route overlap between the target vehicle and the vehicle to be followed based on the driving route information; When the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed, controlling the target vehicle to follow the vehicle to be followed for following driving; The driving information also includes wind speed information and vehicle shape information; The method further comprises: The driving information is used as an input of a wake vortex simulation model to obtain a simulated following position of a 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; Determining a relative position relationship between the simulated following vehicle position and the vehicle to be followed based on lane line information; The controlling the target vehicle to follow the vehicle to be followed to perform following driving includes: Controlling the target vehicle to follow the vehicle based on the relative position relationship; The wind speed information includes crosswind intensity; The controlling the target vehicle to follow the vehicle based on the relative position relationship includes: When the crosswind intensity is less than or equal to the first intensity, the to-be-followed vehicle and the target vehicle are controlled to follow the vehicle in a straight line in the same lane and at a greater than a safety distance based on the relative position relationship; and, When the crosswind intensity is greater than the first intensity and less than or equal to the second intensity, the to-be-followed vehicle and the target vehicle are controlled to travel in a staggered manner in the same lane and at a distance greater than the safety distance based on the relative position relationship; and, When the crosswind intensity is greater than the second intensity and less than or equal to the third intensity, the to-be-followed vehicle and the target vehicle are controlled to follow each other in adjacent lanes at a staggered following distance greater than the safety distance based on the relative position relationship; and, When the crosswind intensity is greater than the third intensity, the vehicle to be followed and the target vehicle are controlled to follow each other in the same lane at a safe speed and greater than the safe distance.

2. The method according to claim 1, characterized in that The step of using the driving information as an input of a wake vortex simulation model to obtain a simulated following position of a target vehicle includes: 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.

3. The method according to claim 1, 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.

4. The method according to claim 1, characterized in that Also includes: Acquire the driving status of the platoon vehicles, wherein the platoon vehicles include at least one of the to-be-followed vehicles and the target vehicle; When there is an abnormal vehicle in the formation, controlling the abnormal vehicle to exit the formation driving mode; Adjust the formation positions of the remaining vehicles so that the remaining vehicles in the formation can fully utilize the wake vortex generated by the leading vehicle.

5. The method according to claim 4, characterized in that Also includes: Obtaining the energy reserve status of the vehicles in the formation; Adjusting the front and rear order of vehicles in the formation based on the energy reserve state, and recalculating to obtain a second simulated following vehicle position; The positions of the vehicles in the formation are adjusted based on the second simulated following vehicle position.

6. A vehicle following control device, characterized in that: include: An acquisition unit, used to acquire driving information and driving route information of the vehicle to be followed, wherein the driving information includes vehicle speed information; A determination unit, configured to determine a degree of route overlap between a target vehicle and the vehicle to be followed based on the driving route information; A control unit, configured to control the target vehicle to follow the vehicle to be followed for following driving when the route overlap is greater than or equal to a preset overlap and the vehicle speed information is greater than or equal to a preset following speed; The driving information also includes wind speed information and vehicle shape information; The driving information is used as an input of a wake vortex simulation model to obtain a simulated following position of a 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; Determining a relative position relationship between the simulated following vehicle position and the vehicle to be followed based on lane line information; The controlling the target vehicle to follow the vehicle to be followed to perform following driving includes: Controlling the target vehicle to follow the vehicle based on the relative position relationship; The wind speed information includes crosswind intensity; The controlling the target vehicle to follow the vehicle based on the relative position relationship includes: When the crosswind intensity is less than or equal to the first intensity, the to-be-followed vehicle and the target vehicle are controlled to follow the vehicle in a straight line in the same lane and at a greater than a safety distance based on the relative position relationship; and, When the crosswind intensity is greater than the first intensity and less than or equal to the second intensity, the to-be-followed vehicle and the target vehicle are controlled to travel in a staggered manner in the same lane and at a distance greater than the safety distance based on the relative position relationship; and, When the crosswind intensity is greater than the second intensity and less than or equal to the third intensity, the to-be-followed vehicle and the target vehicle are controlled to follow each other in adjacent lanes at a staggered following distance greater than the safety distance based on the relative position relationship; and, When the crosswind intensity is greater than the third intensity, the vehicle to be followed and the target vehicle are controlled to follow each other in the same lane at a safe speed and greater than the safe distance.

7. 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 5 when executing the computer program stored in the memory.

8. 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 5 is implemented.

Images