Following vehicle control method, electronic equipment and computer readable storage medium

Abstract

The invention provides a following vehicle control method, electronic equipment and a computer readable storage medium, and the following vehicle control method comprises the steps: responding to a received instruction for switching a current vehicle following mode to a target vehicle following mode, obtaining a first parameter of a following vehicle in the current vehicle following mode and a second parameter of the following vehicle in the target vehicle following mode, wherein the first parameter and the second parameter are used for describing different driving styles of the following vehicle in the intelligent queue; adjusting the first parameter to the second parameter within a preset time so as to complete the switching from the current car following mode to the target car following mode; and controlling the following vehicle to run according to the second parameter. Through the method and the device, the problem that the intelligent queue in the related technology cannot maintain relatively high formation probability and good riding experience at the same time is solved, and the technical effects of reducing the probability that the intelligent queue is damaged and improving the riding experience are achieved.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving, and in particular to a following vehicle control method, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of autonomous driving technology, intelligent platooning systems are gaining more and more attention as a key tool to improve road efficiency and safety. Intelligent platooning is a comprehensive system that integrates advanced technologies such as vehicle communication, environmental perception, prediction, positioning, decision-making planning, and automatic control. It aims to optimize vehicle formation integrity and the safety, comfort, and economy of the platooning process. However, there are few studies on intelligent platooning. The parameters related to the target following distance and the cost function weight in the platooning mode are often fixed values, which makes it impossible for intelligent platooning to maintain a high platooning probability and a good riding experience (including safety, comfort, and economy). For this technical problem, no effective solution has been proposed in the relevant technologies. Summary of the invention

[0003] The embodiments of the present application provide a following vehicle control method, an electronic device, and a computer-readable storage medium to solve one or more of the above-mentioned technical problems.

[0004] In a first aspect, an embodiment of the present application provides a following vehicle control method, which is applied to an intelligent queue, comprising: in response to receiving an instruction to switch a current following vehicle mode to a target following vehicle mode, obtaining a first parameter of the following vehicle in the current following vehicle mode and a second parameter of the following vehicle in the target following vehicle mode, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue; within a preset time, adjusting the first parameter to the second parameter to complete the switching of the current following vehicle mode to the target following vehicle mode; and controlling the following vehicle to drive with the second parameter.

[0005] In a second aspect, an embodiment of the present application provides a following vehicle control method, which is applied to a following vehicle decision system or a leading vehicle decision system in an intelligent queue, including: the following vehicle decision system or the leading vehicle decision system determines in real time a target following mode whose performance is better than the current following mode; and sends a following mode switching instruction to the following vehicle, so that the following vehicle uses the above-mentioned control method to adjust parameters to complete the switching of the current following mode to the target following mode.

[0006] In a third aspect, an embodiment of the present application provides a following vehicle control device, which is applied to a following vehicle in an intelligent queue, and includes: an acquisition module, which is used to respond to receiving an instruction to switch a current following vehicle mode to a target following vehicle mode, to acquire a first parameter of the following vehicle in the current following vehicle mode and a second parameter of the following vehicle in the target following vehicle mode, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue; an adjustment module, which is used to adjust the first parameter to the second parameter within a preset time to complete the switching of the current following vehicle mode to the target following vehicle mode; and a control module, which is used to control the following vehicle to drive with the second parameter.

[0007] In a fourth aspect, an embodiment of the present application provides a following vehicle control device, which is applied to a following vehicle decision system or a leading vehicle decision system in an intelligent queue, and includes: a judgment module, which is used to judge in real time a target following vehicle mode whose performance is better than the current following vehicle mode; a sending module, which is used to send a following vehicle mode switching instruction to the following vehicle, so that the following vehicle uses the above-mentioned control method to adjust parameters to complete the switching of the current following vehicle mode to the target following vehicle mode.

[0008] In a fifth aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor implements any of the methods described above when executing the computer program.

[0009] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any of the methods described above is implemented.

[0010] In a seventh aspect, an embodiment of the present application provides a computer program product, including computer instructions, which implement any of the methods described above when executed by a processor.

[0011] Compared with the related art, this application has the following advantages:

[0012] In an embodiment of the present application, in response to receiving an instruction to switch the current following mode to the target following mode, a first parameter of the following vehicle in the current following mode and a second parameter of the following vehicle in the target following mode are obtained, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue; within a preset time, the first parameter is adjusted to the second parameter to complete the switching of the current following mode to the target following mode; and the following vehicle is controlled to travel with the second parameter. The embodiment of the present application can dynamically adjust the intelligent queue following parameters (for example, following distance, weight coefficient related parameters, etc.) according to different driving environments, complete the switching of the following mode, and thus solve the technical problem in the related technology that it is difficult to balance the intelligent queue to maintain the formation state for a long time and improve the overall riding experience, and achieve the overall technical effect of reducing the probability of the intelligent queue being destroyed and improving the riding experience, as well as the technical effect of improving the integrity, safety and comfort of the intelligent queue.

[0013] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments according to the present application and should not be regarded as limiting the scope of the present application.

[0015] Figure 1 A schematic diagram of a scenario of an intelligent queue provided in an embodiment of the present application is shown;

[0016] Figure 2 A flow chart of a following vehicle control method provided in an embodiment of the present application is shown;

[0017] Figure 3 A schematic diagram of a method for designing a following vehicle distance provided in an embodiment of the present application is shown;

[0018] Figure 4a A schematic diagram of a method for adjusting parameters of a following vehicle provided in an embodiment of the present application is shown;

[0019] Figure 4b A schematic diagram of another method for adjusting parameters of a following vehicle provided in an embodiment of the present application is shown;

[0020] Figure 5 A structural block diagram of a follower vehicle control device provided in an embodiment of the present application is shown;

[0021] Figure 6 A flow chart of another following vehicle control method provided in an embodiment of the present application is shown;

[0022] Figure 7 A structural block diagram of another following vehicle control device provided in an embodiment of the present application is shown;

[0023] Figure 8 A block diagram of an electronic device used to implement an embodiment of the present application is shown. DETAILED DESCRIPTION

[0024] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the concept or scope of the present application. Therefore, the drawings and descriptions are considered to be exemplary in nature and not restrictive.

[0025] To facilitate understanding of the technical solutions of the embodiments of the present application, the following describes the related technologies of the embodiments of the present application. The following related technologies can be combined with the technical solutions of the embodiments of the present application as optional solutions, and they all belong to the protection scope of the embodiments of the present application.

[0026] The application scenarios of the smart fleet in the embodiment of the present application include but are not limited to: long-distance freight logistics fleet, urban public transportation fleet, high-speed train formation, etc. Among them, the smart fleet is composed of a pilot vehicle with a driver with no less than L2 level assisted driving and multiple unmanned rear vehicles with L4 level autonomous driving, such as Figure 1 As shown. The queue is equipped with a communication device, which can transmit the historical trajectory information, position and posture and other positioning information of the vehicle to other vehicles in the intelligent queue; vehicle controller area network (CAN) information such as throttle, brake, turn signal, steering wheel; automatic driving instructions and human-computer interaction interface instruction information related to lateral and longitudinal following, etc. In the intelligent queue, except for the leading vehicle at the front, each other vehicle in the formation state follows the nearest front vehicle in the queue. The intelligent queue is equipped with sensors such as cameras, lidars, inertial measurement units (IMUs) and human-computer interaction interfaces, which can be used to obtain and update the surrounding environment information of the queue in real time, including but not limited to sensing road congestion, road slope, road bumps and other information.

[0027] At present, the following distance of intelligent platoons at a certain speed is often a certain value, that is, the time distance (the distance (m) obtained by multiplying the own vehicle speed (m / s) and the time coefficient (s) and the minimum following distance (the target following distance when the own vehicle speed is 0) are fixed. However, on bumpy roads, the vehicle speed fluctuates greatly, and the following distance changes with the vehicle speed, which easily causes unstable control instructions. Therefore, the selection of the following distance and control accuracy requirements of the intelligent platoon should be combined with the traffic environment and road information. In order to ensure the integrity of the intelligent platoon formation, in an environment with dense social vehicles, a relatively small following distance and high control accuracy should be preferred to maintain the stability of the platoon. When the road conditions are poor, the system is usually unable to effectively maintain a high control accuracy, which may lead to unstable driving behaviors such as sudden acceleration and deceleration, affecting driving comfort and economy. Therefore, a design method that can dynamically adjust the following distance and control accuracy of the intelligent platoon according to different driving environments may help to provide the integrity, safety and comfort of the intelligent platoon.

[0028] In view of the above technical problems, the technical solution of the present application and how the technical solution of the present application solves the above technical problems are described in detail with specific embodiments below. The several specific embodiments listed can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

[0029] The present application embodiment provides a following vehicle control method, which is applied to an intelligent queue, such as Figure 2 The flowchart of the following vehicle control method according to an embodiment of the present application is shown. The method may include:

[0030] Step S202, in response to receiving an instruction to switch the current following mode to the target following mode, obtain a first parameter of the following vehicle in the current following mode and a second parameter of the following vehicle in the target following mode, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue.

[0031] It should be noted that the above instructions can be issued by the central control system, the cloud command center, the driver (or passenger), and the vehicle-to-vehicle communication (V2V) system. Among them, the central control system is the core responsible for driving decision-making and strategy implementation. It decides when and how to switch the following mode based on sensor data, map information, and real-time traffic conditions. The cloud command center can remotely monitor and control the vehicle. In situations such as dangerous road conditions, emergencies, or the need for unified traffic scheduling, the cloud command center can issue instructions to switch the following mode. The driver (or passenger) can also adjust the following mode through manual intervention. For example, through a human-computer interaction interface, steering wheel buttons, or other input devices, the driver can select and switch the following mode. Or some advanced autonomous driving systems support voice assistants, and the driver (or passenger) can adjust the following mode in real time through voice commands. The vehicle-to-vehicle communication (V2V) system can be a signal sent by the current vehicle to suggest or request the following vehicle to adjust the following mode when it detects that the following vehicle's following mode is unreasonable (for example, the distance is too close or too far). If a vehicle suddenly brakes, the following vehicle can immediately receive the signal and switch to the appropriate following mode to avoid collision, etc.

[0032] In addition, it should be noted that the driving status of the above-mentioned following vehicle in the intelligent queue includes but is not limited to: normal following state, acceleration state, deceleration state, parking state, lane change state, emergency avoidance state, queue dissolution and reorganization, speed change state, etc.

[0033] It should also be noted that the first parameter and the second parameter at least include parameters for calculating the target following distance and the cost function, such as time interval, minimum following distance, position item weight, speed item weight, etc. Among them, the function curves formed by the vehicle speed and following distance in different following modes are monotonically non-decreasing, the cost function composition and constraints in different following modes are the same, and the weight parameters of each component are not completely the same.

[0034] Optionally, the method of obtaining the first parameter of the following vehicle in the current following mode and the second parameter of the following vehicle in the target following mode includes but is not limited to: through multiple technologies such as radar, laser radar, camera, V2V communication and Global Navigation Satellite System (GNSS), and the integrated application of these technologies, the following distance can be accurately and real-time obtained, thereby achieving safe and efficient autonomous driving. The comprehensive use of different technologies and the application of intelligent algorithms enable vehicles in the intelligent queue to accurately perceive and dynamically adjust the following distance, ensuring the coordinated operation and driving safety of the entire queue.

[0035] Step S204: within a preset time, adjusting the first parameter to the second parameter to complete the switching of the current vehicle following mode to the target vehicle following mode.

[0036] It should be noted that the above-mentioned first parameter and the above-mentioned second parameter can include multiple parameters respectively. For example, assuming that the above-mentioned first parameter includes parameter 1 and parameter 2, and the above-mentioned second parameter includes parameter 3 and parameter 4, parameter 1 corresponds to parameter 3, and parameter 2 corresponds to parameter 4. The time for adjusting parameter 1 to parameter 3 is T1, and the time for adjusting parameter 2 to parameter 4 is T2. Then T1 and T2 can be the same or different, which is not limited in the embodiments of the present application.

[0037] Optionally, the method of adjusting the first parameter to the second parameter may include a smooth transition method. The process of smooth transition from the first parameter to the second parameter can be represented by a continuous monotonic function. The selection of a suitable function depends on the specific application requirements, including but not limited to: linear function, exponential function, sigmoid function, etc.

[0038] Step S206, controlling the following vehicle to travel according to the second parameter.

[0039] Through the above steps S202 to S206, in response to receiving an instruction to switch the current following mode to the target following mode, a first parameter of the following vehicle in the current following mode and a second parameter of the following vehicle in the target following mode are obtained, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue; within a preset time, the first parameter is adjusted to the second parameter to complete the switching of the current following mode to the target following mode; and the following vehicle is controlled to travel with the second parameter. In other words, the embodiment of the present application can dynamically adjust the intelligent queue following parameters (for example, following distance, weight coefficient related parameters, etc.) according to different driving environments, complete the switching of the following mode, and thus solve the technical problem in the related technology that it is difficult to balance the intelligent queue to maintain the formation state for a long time and improve the overall riding experience, and achieve the overall technical effect of reducing the probability of the intelligent queue being destroyed and improving the riding experience, as well as the technical effect of improving the integrity, safety and comfort of the intelligent queue.

[0040] In a possible implementation, the target following mode includes one of the following modes: a first following mode, a second following mode, and a third following mode. The first following mode has a higher requirement for vehicle control accuracy than the target following mode (for example, in a low-speed congestion scenario, to ensure that the formation is not destroyed, the intelligent queue requires a mode that can make the queue action consistent and the target following distance fixed to ensure that the vehicles move consistently and the distance between vehicles is stable, referred to as the tight queue mode). The second following mode has the same requirement for vehicle control accuracy as the first following mode (for example, in an environment with a large number of vehicles at medium and high speeds, the second following mode has a higher requirement for vehicle control accuracy than the first following mode (for example, in an environment with a large number of vehicles at medium and high speeds, the second following mode has a higher requirement for vehicle control accuracy than the first following mode). To prevent social vehicles from being inserted into the queue due to excessive queue spacing, the smart queue requires a mode with a relatively small following distance and relatively high control accuracy to ensure that the formation is not destroyed, referred to as the queue precision mode). The third following mode has lower vehicle control accuracy requirements than the first following mode and the second following mode (for example, in an environment with fewer social vehicles or bumpy roads, in order to improve the safety, comfort and economy of the queue, the smart queue should require a mode with a relatively large following distance and relatively low control accuracy within a reasonable distance to reduce the frequency of sudden acceleration, sudden deceleration and throttle-brake switching, referred to as the queue relief mode). There are certain differences in the following distance and control accuracy requirements of the above three following modes.

[0041] The embodiment of the present application can set a speed threshold for enabling the first following mode (tight queue mode), and set the following distance deviations of the second following mode (precision queue mode) and the third following mode (relaxed mode) as a relaxation interval. Optionally, the following distance of the first following mode is not less than a first specified threshold, wherein the first specified threshold is a critical safety following distance; the following distance of the second following mode is a second specified threshold, wherein the second specified threshold is the following distance of the first following mode and is greater than the critical safety following distance; the following distance of the third following mode is a non-fixed value at a certain vehicle speed, and the following distance can be adaptively adjusted according to the actual intelligent queue following distance, and the adjustment range is between the third specified threshold and the fourth specified threshold, the third specified threshold is the following distance of the second following mode and is greater than the second specified threshold, and is also the lower limit of the following distance of the third following mode, and the fourth specified threshold is greater than the third specified threshold and is the upper limit of the following distance of the third following mode. Figure 3 As shown, f1(v) is the critical safety following distance curve, f2(v) is the second following mode following distance curve, the interval between f2(v) and f3(v) is the third following mode following distance interval, and f4(v) is the first following mode following distance curve.

[0042] Optionally, the method for determining the following distance of the above first following vehicle mode or the above second following vehicle mode includes: S11, determining the following distance of the first following vehicle mode or the second following vehicle mode according to the critical safety following distance curve; the method for determining the following distance of the above third following vehicle mode includes: S12, determining the following distance of the third following vehicle mode according to the second following vehicle mode, wherein the upper bound of the following distance of the third following vehicle mode is a non-decreasing continuous function related to the vehicle speed. That is, in the embodiments of the present application, the following distances of the first following vehicle mode, the second following vehicle mode, and the third following vehicle mode are designed step by step based on the queue safety vehicle distance critical function curve, which can ensure that when the following vehicle mode is switched, the frequency of sudden acceleration, sudden deceleration, and throttle-brake switching is reduced.

[0043] In a possible implementation manner, determining the following distance of the first following vehicle mode according to the critical safety following distance curve further includes: S21, before the critical vehicle speed, setting the following distance of the first following vehicle mode as a fixed value; S22, after being greater than the critical vehicle speed, setting that the first following vehicle mode will automatically switch to the second following vehicle mode or the third following vehicle mode, and using the following distance of the second following vehicle mode or the third following vehicle mode, wherein the critical vehicle speed is the vehicle speed corresponding to the intersection point between the critical safety following distance curve and the following distance of the first following vehicle mode, such as Figure 3 Vc in

[0044] The embodiments of the present application will be described below with specific examples.

[0045] First, introduce the critical safety vehicle distance function curve in the queue mode used in this example. Assume that a safety vehicle distance curve related to the queue vehicle speed is obtained through empirical calibration, data analysis, machine learning, etc., and is approximated as a non-decreasing continuous function f(·) within the effective vehicle speed range. For any v1 < v2 within its definition threshold, f(v1) ≤ f(v2), such as sigmoid, exponential function, polynomial function that partially meets the conditions, or even piecewise function, etc., as shown in Formula 1.

[0046]

[0047] Among them, y is the queue following distance, v is the vehicle speed, v max is the maximum vehicle speed of the queue, f1(·) is the critical safety following distance function, and when the vehicle speed is 0, the minimum value y of the queue critical safety following distance can be obtained min = f1(0). In this example, a linear function will be used for illustration, as shown in Formula 2.

[0048] <![CDATA[y=k1v+y min ;0≤v≤v max ]]> Formula 2

[0049] Such as Figure 3As shown, the design of the critical safety following distance curve is not limited to this, and other monotonically non-decreasing continuous functions are also applicable. An important concept in the following distance is called "time headway", which is represented by k in this example and is usually calculated as shown in Formula 3.

[0050]

[0051] It should be noted that although the critical safety time headway in this example is a constant value k1, the method described in this example is also applicable to a following distance model with a variable time headway.

[0052] Based on the critical safety following distance curve of the queue, the following distance curve in the second following mode (precision mode) of the queue is designed. Since this mode is expected to reduce the probability of the intelligent queue being destroyed, the following distance should be close to the critical safety following distance and is also designed as a monotonically non-decreasing continuous function related to the vehicle speed, as shown in Formula 4.

[0053]

[0054] This example will also use a linear function for illustration, as shown in Formula 5.

[0055] <![CDATA[y=k2v+y2;0≤v≤v max ]]> Formula 5

[0056] To ensure the safety of the following distance, the situation shown in Formula 6 exists.

[0057] <![CDATA[f1(v)<f2(v);0≤v≤v max ]]> Formula 6

[0058] like Figure 3 It should be noted that although the time-distance relationship used in this example is k2>k1, the time-distance relationship of the method shown does not need to meet specific conditions.

[0059] The queue relaxation mode is designed based on the queue precision mode following distance curve. In this mode, the queue formation mode will not be disrupted by other vehicles or on bumpy roads with poor road quality, and more attention is paid to comfort and economy. Therefore, the target following distance at a certain speed is no longer a value, but an interval. At different speeds, the lower limit of the following distance interval is the following distance of the queue precision following mode, and the upper limit of the interval is also designed as a monotonically non-decreasing continuous function related to the vehicle speed, as shown in Formula 7.

[0060]

[0061] This example will also use a linear function for illustration, as shown in Formula 8.

[0062] <![CDATA[y=k3v+y3;0≤v≤v max ]]> Formula 8

[0063] The upper limit of the following distance interval satisfies Formula 9.

[0064] <![CDATA[f2(v)<f3(v);0≤v≤v max ]]> Formula 9

[0065] like Figure 3 It should be noted that although the time distance relationship between the upper and lower boundaries of the relaxation mode in this example is k2>k3, the method shown does not require the time distance relationship to meet specific conditions. In addition, assuming that the precise target time distance of the queue at a certain speed is k 2,v , the distance interval of the following vehicle in the soothing mode is k 3,v , the actual queue following distance is y c , then the target duration calculation method of the soothing mode is shown in formula 10.

[0066]

[0067] In the queue relaxation mode, when the queue speed is the same and the actual following distance is different, the time interval used may be different. Based on the queue critical safety following distance function curve, the following distance curve in the queue tight mode is designed, which is also a monotonically non-decreasing continuous function related to the vehicle speed, as shown in Formula 11.

[0068]

[0069] Since this mode is mainly used in low-speed congestion scenarios, the goal is to make the front and rear vehicles move in unison and further reduce the following distance, it needs to be enabled at a certain speed and the following distance should be constant. The following distance should not be less than the critical safety following distance and not greater than the following distance in the platoon precision mode. The critical speed is set to v c In this example, a piecewise function will be used to illustrate the problem. It is also designed as a monotonically non-decreasing continuous function related to the vehicle speed, as shown in Formula 12.

[0070]

[0071] Among them, v c The value of is related to the following distance y4 designed in the tight mode.

[0072] According to the above-mentioned queue following distance design method of this example, the following distance, minimum following distance and time interval in various modes have the relationship shown in formula 13, and the function curve is as follows: Figure 3 shown.

[0073]

[0074] In addition, in this example, the human-computer interaction interface can additionally increase the minimum following distance and equally increase the minimum following distance for different following modes of the matching platoon.

[0075] The selection of the platoon following mode is related to the traffic environment, road quality, human-computer interaction interface parameter configuration, and autonomous driving system scenario judgment. For example, the density of social vehicles and the speed of vehicles can be sensed to determine whether the vehicle is in a traffic jam, and then decide whether to enable the platoon tight mode; the historical trajectory of the front vehicle in the platoon, turn signal information, and the decision results of the front vehicle can be used to determine whether the platoon is easily destroyed, such as changing lanes, and then decide whether to enable the platoon precision mode; the pitch angle fluctuation of the vehicle is monitored by the inertial measurement unit (IMU) sensor to determine the degree of road bumps, and then decide whether to enable the platoon relief mode. It should be noted that in scenarios where the probability of the platoon being destroyed is low, the relief mode should be used as much as possible to improve the overall comfort and economy of the platoon.

[0076] At present, the longitudinal following problem of a platoon can be described as an optimization problem, assuming that its cost function can be described as shown in the following formula 14.

[0077] <![CDATA[g(x)=w s s e +w v v e +w a a e +w j j]]> Formula 14

[0078] Among them, s e 、v e 、a e , j are the longitudinal position, velocity, acceleration error matrix and longitudinal jerk respectively; w s 、w v 、w a 、w j is the weight coefficient matrix of each longitudinal following parameter, which affects the longitudinal control style. In the state of automatic driving, there may be changes in the longitudinal following target, such as the exit of the intelligent queue and the entry into the formation mode due to the entry and exit of social vehicles in the queue; even in the formation state, mode conversion may occur, such as when the speed threshold is exceeded in the tight queue mode, the automatic system needs to actively switch to the queue precision mode to ensure safety. In addition, the control style requirements are different under different longitudinal following targets. The queue relaxation mode should pay more attention to comfort than the queue precision mode, and the queue precision mode should pay more attention to the following distance and control error than the queue relaxation mode. Therefore, the minimum fixed following distance, time interval and weight coefficients in various modes are not exactly the same. Therefore, the embodiment of the present application proposes a smooth transition method during the switching of queue modes.

[0079] In a possible implementation, adjusting the first parameter to the second parameter within a preset time includes: S31, determining a continuous non-decreasing function; S32, using the continuous non-decreasing function to smoothly transition the first parameter to the second parameter within the preset time.

[0080] For example, assuming that a following mode switch occurs at time t0, and there are two different following modes before and after time t0, in order to prevent sudden changes in the following target from causing sudden changes in the queue's throttle and brake commands, the embodiment of the present application proposes a smooth transition interval for following mode switching, which is used to smoothly transition the key parameters before and after the following mode switch. The entire transition duration is set to Δt. During this time period, parameters such as the minimum fixed following distance, time headway, and weight coefficient in the cost function all change continuously to ensure a smooth transition of the cost function for the longitudinal following problem. Each parameter change can be divided into three types. Taking the minimum fixed following distance as an example, assuming that the time headway at the time of switching is k init , the target mode time interval after switching is k end :(1)k init <k1<k end ; (2) k1≤k init ≤k end ; (3) k end <k init .like Figure 4a-4b As shown, it should be noted that the parameter does not have to increase linearly over time, as long as it is a continuous non-decreasing function. The transition time of different parameters does not need to be the same, and can be designed according to the size of the change before and after the mode. For example, if the change amount of a certain parameter is fixed at Δa each time, and the absolute value of the parameter difference before and after the mode change is ΔA, then Δt = ΔA / Δa.

[0081] During the smooth transition of parameters, it may happen that the parameters in the current intelligent platoon following mode are less than the critical safety following parameters, such as Figure 4a-4b As shown by the dotted line, based on this, using the continuous non-decreasing function to smoothly transition the first parameter to the second parameter may include: S321, judging whether the parameter in the current intelligent queue following mode is less than the critical safety following parameter; S322, when judging that the parameter in the current intelligent queue following mode is less than the parameter in the critical safety following distance curve, setting the corresponding parameter in the critical safety following distance curve to the critical safety following parameter. Through the above steps S321 to S332, when judging that the parameter in the current intelligent queue following mode is less than the parameter in the critical safety following distance curve, setting the corresponding parameter in the critical safety following distance curve to the critical safety following parameter ensures that the following vehicle is always in a safe state during the smooth transition of the parameters.

[0082] In summary, the embodiments of the present application disclose a following vehicle control method, which involves a following vehicle distance design method and a following vehicle mode design method for intelligent queues. The embodiments of the present application divide and define three following vehicle modes of "tight", "precise" and "soothing" according to scenario requirements, and specifically design queue following vehicle distances in different modes according to the following vehicle modes, and propose a smooth switching method between different modes. Following vehicle mode judgment relies on the sharing of information such as the positioning, chassis, road environment, automatic driving instructions and human-computer interaction interface of each vehicle between intelligent queues. The following vehicle distance and vehicle control emphasis are different in different following vehicle modes. The method provided in the embodiments of the present application can reduce the probability of intelligent formations being destroyed and improve the safety, comfort and economy of intelligent queues.

[0083] Corresponding to the application scenario and method of the method provided in the embodiment of the present application, the embodiment of the present application also provides a following vehicle control device, which is applied to the following vehicle in the intelligent queue. Figure 5 The following is a block diagram of a follower vehicle control device according to an embodiment of the present application. The device may include:

[0084] an acquisition module 52, configured to acquire, in response to receiving an instruction to switch a current following mode to a target following mode, a first parameter of a following vehicle in the current following mode and a second parameter of a following vehicle in the target following mode, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue;

[0085] An adjustment module 54, configured to adjust the first parameter to the second parameter within a preset time to complete the switching of the current vehicle following mode to the target vehicle following mode;

[0086] The control module 56 is used to control the following vehicle to travel according to the second parameter.

[0087] pass Figure 5The device shown, in response to receiving an instruction to switch the current following mode to the target following mode, obtains a first parameter of the following vehicle in the current following mode and a second parameter of the following vehicle in the target following mode, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in the intelligent queue; within a preset time, the first parameter is adjusted to the second parameter to complete the switching of the current following mode to the target following mode; and the following vehicle is controlled to travel with the second parameter. In other words, the embodiment of the present application can dynamically adjust the intelligent queue following parameters (for example, following distance, weight coefficient related parameters, etc.) according to different driving environments to complete the switching of the following mode, thereby solving the technical problem in the related art that it is difficult to balance the intelligent queue to maintain the formation state for a long time and improve the overall riding experience, and achieves the overall technical effect of reducing the probability of the intelligent queue being destroyed and improving the riding experience, as well as the technical effect of improving the integrity, safety and comfort of the intelligent queue.

[0088] In one possible implementation, the first parameter and the second parameter include at least parameters for calculating the target following distance and the cost function, wherein the function curve formed by the vehicle speed and the following distance under different following modes is a monotonic non-decreasing relationship, the cost function composition and constraints under different following modes are the same, and the weight parameters of the various components are not completely the same.

[0089] Optionally, the target following mode includes one of the following modes: a first following mode, a second following mode, and a third following mode, wherein the first following mode has a higher requirement for vehicle control accuracy than the target following mode, the second following mode has the same requirement for vehicle control accuracy as the first following mode, and the third following mode has a lower requirement for vehicle control accuracy than the first following mode and the second following mode;

[0090] The following distance of the above-mentioned first following mode is not less than the first specified threshold, wherein the first specified threshold is the critical safety following distance; the following distance of the second following mode is the second specified threshold, wherein the second specified threshold is the following distance of the first following mode and is greater than the critical safety following distance; the following distance of the third following mode is a non-fixed value at a certain vehicle speed, and the following distance can be adaptively adjusted according to the actual intelligent queue following distance, and the adjustment range is between the third specified threshold and the fourth specified threshold, the third specified threshold is the following distance of the second following mode and is greater than the second specified threshold, and is also the lower limit of the following distance of the third following mode, and the fourth specified threshold is greater than the third specified threshold and is the upper limit of the following distance of the third following mode.

[0091] The method for determining the following distance of the first following mode or the second following mode includes: determining the following distance of the first following mode or the second following mode according to the critical safety following distance curve;

[0092] The method for determining the following distance of the third following mode includes: determining the following distance of the third following mode according to the second following mode, wherein the upper bound of the following distance of the third following mode is a monotonically non-decreasing continuous function related to the vehicle speed.

[0093] Determining the following distance of the first following mode according to the critical safety following distance curve also includes: before a critical vehicle speed, setting the following distance of the first following mode to a fixed value; after the vehicle speed exceeds the critical vehicle speed, setting the first following mode to automatically switch to the second following mode or the third following mode, and using the following distance of the second following mode or the third following mode, wherein the critical vehicle speed is the vehicle speed corresponding to the intersection between the critical safety following distance curve and the following distance of the first following mode.

[0094] In a possible implementation, the adjustment module 54 includes: a determination unit, configured to determine a continuous non-decreasing function; and a transition unit, configured to use the continuous non-decreasing function to smoothly transition the first parameter to the second parameter within a preset time.

[0095] The above-mentioned transition unit includes: a judgment subunit, used to judge whether the parameters in the current intelligent queue following mode are less than the critical safety following parameters; a setting subunit, used to set the corresponding parameters in the critical safety following distance curve as the critical safety following parameters when it is judged that the parameters in the current intelligent queue following mode are less than the parameters in the critical safety following distance curve.

[0096] The functions of each module in each device in the embodiments of the present application can be found in the corresponding description in the above method, and have corresponding beneficial effects, which will not be repeated here.

[0097] Corresponding to the application scenario and method of the method provided in the embodiment of the present application, the embodiment of the present application also provides a following vehicle control method, which is applied to the following vehicle decision system or the pilot vehicle decision system in the intelligent platoon. Figure 7 The flowchart of the following vehicle control method according to an embodiment of the present application is shown, including:

[0098] S602, the following vehicle decision system or the pilot vehicle decision system determines in real time a target following vehicle mode with better performance than the current following vehicle mode;

[0099] S604: Send a following vehicle mode switching instruction to the following vehicle, so that the following vehicle uses the following vehicle control method to adjust parameters to complete the switching of the current following vehicle mode to the target following vehicle mode.

[0100] Through the above steps S602 to S604, the intelligent queue following parameters (for example, following distance, weight coefficient related parameters, etc.) can be dynamically adjusted according to different driving environments to complete the switching of the following mode, thereby solving the technical problem in the related technology that it is difficult to balance the intelligent queue's long-term maintenance of the formation state and the improvement of the overall riding experience, achieving the technical effect of reducing the overall probability of the intelligent queue being destroyed and improving the riding experience, as well as the technical effect of improving the integrity, safety and comfort of the intelligent queue.

[0101] Corresponding to the application scenario and method of the method provided in the embodiment of the present application, the embodiment of the present application also provides a following vehicle control device, which is applied to the following vehicle decision system or the pilot vehicle decision system in the intelligent queue. Figure 7 The following is a block diagram of a follower vehicle control device according to an embodiment of the present application. The device may include:

[0102] A judgment module 72, used for judging in real time a target vehicle following mode having better performance than the current vehicle following mode;

[0103] The sending module 74 is used to send a following vehicle mode switching instruction to the following vehicle, so that the following vehicle uses the following vehicle control method to adjust parameters to complete the switching of the current following vehicle mode to the target following vehicle mode.

[0104] pass Figure 7 The device can dynamically adjust the intelligent queue following parameters (for example, following distance, weight coefficient related parameters, etc.) according to different driving environments, complete the switching of the following mode, and thus solve the technical problem in the related technology that it is difficult to balance the intelligent queue to maintain the formation state for a long time and improve the overall riding experience, and achieve the technical effect of reducing the probability of the intelligent queue being destroyed and improving the riding experience as a whole, as well as the technical effect of improving the integrity, safety and comfort of the intelligent queue.

[0105] The functions of each module in each device in the embodiments of the present application can be found in the corresponding description in the above method, and have corresponding beneficial effects, which will not be repeated here.

[0106] The functions of each module in the system of the embodiment of the present application can be found in the corresponding description in the above method, and have corresponding beneficial effects, which will not be repeated here.

[0107] Figure 8 FIG. 1 is a block diagram of an electronic device used to implement an embodiment of the present application. Figure 8 As shown, the electronic device includes: a memory 801 and a processor 802. The memory 801 stores a computer program that can be run on the processor 802. When the processor 802 executes the computer program, the method in the above embodiment is implemented. The number of the memory 801 and the processor 802 can be one or more.

[0108] The electronic device also includes:

[0109] The communication interface 803 is used to communicate with external devices and perform data exchange transmission.

[0110] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the memory 801, the processor 802 and the communication interface 803 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0111] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0112] An embodiment of the present application provides a computer-readable storage medium storing a computer program, which implements the method provided in the embodiment of the present application when the program is executed by a processor.

[0113] An embodiment of the present application also provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the method provided by the embodiment of the present application.

[0114] An embodiment of the present application also provides a chip, including: an input interface, an output interface, a processor and a memory, wherein the input interface, the output interface, the processor and the memory are connected via an internal connection path, and the processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the method provided in the embodiment of the application.

[0115] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the Advanced RISC Machines (ARM) architecture.

[0116] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of exemplary but not limiting description, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (DR RAM).

[0117] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to 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 device. 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.

[0118] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0119] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0120] Any process or method described in the flow chart or otherwise described herein can be understood as a module, fragment or portion of a code representing one or more executable instructions for implementing the steps of a specific logical function or process. And the scope of the preferred embodiment of the present application includes other implementations, in which the functions may not be performed in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved.

[0121] The logic and / or steps described in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or used in combination with these instruction execution systems, devices or apparatuses.

[0122] It should be understood that the various parts of the present application can be implemented with hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium, and when the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0123] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0124] The above is only an exemplary embodiment of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope recorded in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A following vehicle control method, applied to an intelligent platoon, comprising: In response to receiving an instruction to switch a current following mode to a target following mode, obtaining a first parameter of a following vehicle in the current following mode and a second parameter of a following vehicle in the target following mode, wherein the first parameter and the second parameter are used to describe different driving styles of the following vehicle in a smart queue; Within a preset time, adjusting the first parameter to the second parameter to complete the switching of the current vehicle following mode to the target vehicle following mode; The following vehicle is controlled to travel according to the second parameter.

2. The method according to claim 1, wherein: The first parameter and the second parameter at least include parameters for calculating a target following distance and a cost function, wherein a function curve formed by vehicle speed and following distance under different following modes is a monotonic non-decreasing relationship, the cost function composition and constraints under different following modes are the same, and the weight parameters of each component are not completely the same.

3. The method according to claim 2, wherein: The target following mode includes one of the following modes: a first following mode, a second following mode, and a third following mode. The first following mode has a higher vehicle control accuracy requirement than the target following mode. The second following mode has the same vehicle control accuracy requirement as the first following mode. The third following mode has a lower vehicle control accuracy requirement than the first following mode and the second following mode. The following distance of the first following mode is not less than a first specified threshold, wherein the first specified threshold is a critical safety following distance; The following distance of the second following mode is a second specified threshold, wherein the second specified threshold is the following distance of the first following mode and is greater than the critical safety following distance; The following distance of the third following mode is a non-fixed value at a certain vehicle speed, and the following distance can be adaptively adjusted according to the actual intelligent queue following distance, and the adjustment range is between the third specified threshold and the fourth specified threshold. The third specified threshold is the following distance of the second following mode and is greater than the second specified threshold, and is also the lower limit of the following distance of the third following mode. The fourth specified threshold is greater than the third specified threshold and is the upper limit of the following distance of the third following mode.

4. The method according to claim 3, wherein: The method for determining the following distance of the first following mode or the second following mode includes: determining the following distance of the first following mode or the second following mode according to the critical safety following distance curve; The method for determining the following distance of the third following mode includes: determining the following distance of the third following mode according to the second following mode, wherein the upper bound of the following distance of the third following mode is a monotonically non-decreasing continuous function related to the vehicle speed.

5. The method according to claim 4, wherein: Determining the following distance of the first following mode according to the critical safety following distance curve also includes: Before reaching a critical vehicle speed, setting the following distance of the first following mode to a fixed value; After the vehicle speed exceeds the critical vehicle speed, the first following mode is set to automatically switch to the second following mode or the third following mode, and the following distance of the second following mode or the third following mode is used, wherein the critical vehicle speed is the vehicle speed corresponding to the intersection between the critical safety following distance curve and the following distance of the first following mode.

6. The method according to claim 1, wherein: Adjusting the first parameter to the second parameter within a preset time includes: Determine continuous non-decreasing functions; Within a preset time, the first parameter is smoothly transitioned to the second parameter using the continuous non-decreasing function.

7. The method according to claim 6, wherein: Using the continuous non-decreasing function to smoothly transition the first parameter to the second parameter comprises: Determine whether the parameters in the current intelligent platoon following mode are less than the critical safety following parameters; When it is determined that the parameter in the current intelligent platoon following mode is less than the parameter in the critical safety following distance curve, the corresponding parameter in the critical safety following distance curve is set as the critical safety following parameter.

8. A following vehicle control method, applied to a following vehicle decision system or a pilot vehicle decision system in an intelligent platoon, comprising: The following vehicle decision system or the pilot vehicle decision system determines in real time a target following vehicle mode with a performance better than the current following vehicle mode; A following mode switching instruction is sent to the following vehicle, so that the following vehicle uses the method described in any one of claims 1 to 7 to adjust parameters to complete the switching of the current following mode to the target following mode.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, wherein the processor implements the method of any one of claims 1 to 7 or claim 8 when executing the computer program.

10. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 or claim 8 is implemented.

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