Intelligent queuing assisting method and system for vehicle, vehicle and equipment

Abstract

The invention discloses an intelligent queuing assisting method and system for a vehicle, the vehicle and equipment. The intelligent queuing assisting method for the vehicle comprises the steps of obtaining road condition information and obstacle information; according to the state information of the vehicle and the obstacle information, an initial target obstacle influencing the operation of the vehicle is obtained through screening; obtaining a target obstacle according to the initial target obstacle, and generating a driving track of the vehicle according to the type of the target obstacle; and according to the driving track, intelligent queuing control of waiting, following or lane changing is carried out on the own vehicle. By the adoption of the method and device, frequent operation of a driver on the vehicle during queuing can be effectively reduced, highly concentrated monitoring of the driver on the environment is relieved, the driving comfort during queuing is improved, and the problems of traffic crawling and the like caused by slow vehicle response and the like due to the fact that the driver drives too conservatively or responds slowly can be solved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to an intelligent queuing assistance method, system, vehicle and equipment for vehicles. Background Art

[0002] At present, in many truck operation scenarios, trucks sometimes queue up at the factory gate to enter the factory to unload or transport goods for a long time, which may take hours or even days. During this period, the driver needs to pay attention at all times to follow the vehicle in front to move the vehicle forward at any time and prevent other vehicles from cutting in line. Frequent acceleration, braking and other operations during the queuing process increase the driver's operating burden, reduce driving and riding comfort, cause driver fatigue, and long-term operating fatigue also increases driving safety risks. Although the vehicle integrated cruise (ICA, Integrated Cruise Assist) system or traffic jam assist (Traffic Jam Assist, TJA) system can play a certain role, they generally rely on lane lines and have limited application scenarios. Summary of the invention

[0003] Based on this, it is necessary to provide an intelligent queuing assistance method, system, vehicle and equipment for vehicles to address the above technical problems, which can effectively reduce the driver's frequent manipulation of the vehicle when queuing, and alleviate the driver's highly concentrated monitoring of the environment, thereby improving driving comfort when queuing, and avoiding traffic creep caused by slow vehicle response due to overly conservative driving or slow reaction of the driver.

[0004] In a first aspect, a method for intelligent queuing assistance of vehicles is provided, comprising:

[0005] Obtain road condition information and obstacle information;

[0006] According to the state information of the ego vehicle and the obstacle information, an initial target obstacle affecting the operation of the ego vehicle is screened and obtained;

[0007] Obtaining a target obstacle according to the initial target obstacle, and generating a driving trajectory of the vehicle according to the type of the target obstacle;

[0008] According to the driving trajectory, intelligent queuing control is performed on the vehicle such as waiting, following or changing lanes.

[0009] In some examples, the screening of the initial target obstacle affecting the operation of the vehicle according to the vehicle state information and the obstacle information includes:

[0010] According to the state information of the vehicle, the driving trajectory of the vehicle is virtualized to obtain the virtual lane line;

[0011] According to the virtual lane line and obstacle information, initial target obstacles are screened out, wherein the initial target obstacles include the obstacles closest and second closest to the longitudinal distance of the vehicle in the virtual lane line, and the obstacles closest to the left and right of the virtual lane line.

[0012] In some examples, obtaining a target obstacle according to the initial target obstacle, and generating a driving trajectory of the vehicle according to a type of the target obstacle, includes:

[0013] If the obstacle closest to the vehicle in the virtual lane line has the intention to change lanes;

[0014] If yes, determine whether there is the next closest obstacle;

[0015] If the next closest obstacle exists, the next closest obstacle is used as the target obstacle; otherwise, the lane change operation is performed following the preceding vehicle.

[0016] In some examples, this also includes:

[0017] Determining whether the target obstacle is a vehicle;

[0018] If not, a takeover reminder is given and obstacle avoidance operations are performed.

[0019] In some examples, the virtualizing the driving trajectory of the vehicle based on the state information of the vehicle to obtain the virtual lane line includes:

[0020] Perform lateral control of the vehicle based on the location of the target obstacle; or

[0021] The historical trajectory of the target obstacle is recorded, and the ego vehicle is controlled to follow the historical trajectory of the target obstacle.

[0022] In some examples, longitudinal control of the ego vehicle includes:

[0023] According to the distance, speed, acceleration of the target obstacle and the lane-changing vehicle foreseen in advance, the acceleration and deceleration of the vehicle are calculated, and the longitudinal control of the vehicle is performed based on the calculated acceleration and deceleration of the vehicle, wherein the longitudinal control at least includes longitudinal following control, follow-stop start control, non-target parking control and wheel-end torque command limitation,

[0024] Among them: In the intelligent queuing mode, EBS is prohibited from distributing torque, and the braking energy distribution module is used to distribute braking energy to achieve efficient deceleration control;

[0025] In the intelligent queuing mode, when the target ahead is lost, the targetless parking control is executed to finally stop the vehicle in place, and then the N gear is engaged and the handbrake is engaged to exit the function;

[0026] In the intelligent queuing mode, the improved IDM model is used to calculate the vehicle following control.

[0027] In some examples, lateral control of the ego vehicle includes:

[0028] Use pure tracking, LQR or MPC methods to control the ego vehicle laterally.

[0029] In a second aspect, a vehicle intelligent queuing assistance system is provided, comprising:

[0030] An acquisition module is used to obtain road condition information and obstacle information;

[0031] A screening module, used for screening and obtaining initial target obstacles that affect the operation of the vehicle according to the state information of the vehicle and the obstacle information;

[0032] A generating module, used to obtain a target obstacle according to the initial target obstacle, and generate a driving trajectory of the ego vehicle according to the type of the target obstacle;

[0033] The control module is used to intelligently control the waiting, following or lane changing of the vehicle according to the driving trajectory.

[0034] In a third aspect, a vehicle is provided, comprising: the intelligent queuing assistance system for the vehicle according to the second aspect.

[0035] In a fourth aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the intelligent queuing assistance method for vehicles of the first aspect and any possible implementation method of the first aspect are implemented.

[0036] In a fifth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the intelligent queuing assistance method for vehicles in the above-mentioned first aspect and any possible implementation method of the first aspect are implemented.

[0037] In a sixth aspect, a computer program product is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the intelligent queuing assistance method for vehicles in the above-mentioned first aspect and any possible implementation method of the first aspect are implemented.

[0038] Using the embodiment of the present application, the intelligent queuing function inputs the perception and fusion of environmental information, performs vehicle auxiliary behavior decision-making, trajectory planning and control, and sends the longitudinal and lateral control commands of the vehicle to the control unit to realize automatic control of the lateral and longitudinal movement of the vehicle in the case of intelligent queuing. It can effectively reduce the driver's frequent manipulation of the vehicle when queuing, and alleviate the driver's highly concentrated monitoring of the environment, improve the driving comfort when queuing, and avoid traffic creep caused by slow vehicle response due to overly conservative driving or slow reaction of the driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0040] Figure 1 A flow chart of an intelligent queuing assistance method for vehicles provided in an embodiment of the present application;

[0041] Figure 2 A control schematic diagram of a vehicle provided in an embodiment of the present application;

[0042] Figure 3 A structural block diagram of an intelligent queuing assistance system for vehicles provided in an embodiment of the present application;

[0043] Figure 4 A structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] The present application is further described in detail below in conjunction with the embodiments and drawings. It is to be understood that the specific embodiments described herein are only used to explain the relevant application, rather than to limit the application. It is also necessary to explain that, for ease of description, only the parts related to the application are shown in the drawings.

[0045] It should be noted that, in the absence of conflict, the embodiments of the present application, that is, the features of the embodiments, can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0046] The following describes in detail the intelligent queuing assistance method, system, vehicle and device for vehicles according to the embodiments of the present application in conjunction with the accompanying drawings.

[0047] Figure 1 FIG. 1 is a flow chart of an intelligent queuing assistance method for vehicles according to an embodiment of the present application. Figure 1 As shown, the intelligent queuing assistance method for vehicles according to an embodiment of the present application includes the following steps:

[0048] S101: Obtain road condition information and obstacle information.

[0049] In one embodiment of the present application, vehicle surrounding environment information such as road condition information and obstacle information can be obtained through an environmental perception module such as an on-board sensor. Specifically, the vehicle surrounding environment, including road conditions and obstacles, is perceived through the on-board sensors, where the sensors include but are not limited to forward-looking cameras, front millimeter-wave radars, fisheye cameras, etc.

[0050] Road condition information includes but is not limited to the curbs and guardrails on both sides of the vehicle (i.e., the vehicle itself), road surface smoothness, etc.;

[0051] Obstacle information includes but is not limited to sensing the target in front through the front-facing camera, sensing the vehicle targets on both sides through the left and right fisheye cameras, and sensing the distance and speed of the target in front through the forward millimeter-wave radar.

[0052] S102: According to the state information of the vehicle and the obstacle information, an initial target obstacle that affects the operation of the vehicle is screened and obtained.

[0053] In one embodiment of the present application, based on the status information of the vehicle and the obstacle information, initial target obstacles that affect the operation of the vehicle are screened, including: based on the status information of the vehicle, a virtual driving trajectory of the vehicle is virtualized to obtain a virtual lane line; based on the virtual lane line and the obstacle information, initial target obstacles are screened, wherein the initial target obstacles include the obstacles closest and second closest to the longitudinal distance of the vehicle within the virtual lane line, and the obstacles closest to the left and right of the virtual lane line.

[0054] S103: Obtain a target obstacle according to the initial target obstacle, and generate a driving trajectory of the vehicle according to the type of the target obstacle.

[0055] In one embodiment of the present application, a target obstacle is obtained according to the initial target obstacle, and a driving trajectory of the ego vehicle is generated according to the type of the target obstacle, including: if the obstacle closest to the ego vehicle in the virtual lane line has an intention to change lanes; if so, determine whether there is the second closest obstacle; if there is the second closest obstacle, use the second closest obstacle as the target obstacle, otherwise follow the leading vehicle to change lanes.

[0056] Furthermore, the intelligent queuing assistance method for vehicles also includes: determining whether the target obstacle is a vehicle; if not, taking over reminders and performing obstacle avoidance operations.

[0057] S104: Based on the driving trajectory, intelligent queuing control is performed on the vehicle such as waiting, following or changing lanes.

[0058] In one embodiment of the present application, based on the status information of the vehicle, the driving trajectory of the vehicle is virtualized to obtain a virtual lane line, including: performing lateral control of the vehicle according to the position of the target obstacle; or recording the historical trajectory of the target obstacle and controlling the vehicle to follow the historical trajectory of the target obstacle.

[0059] Among them, the longitudinal control of the vehicle includes: calculating the acceleration and deceleration of the vehicle according to the distance, speed, acceleration of the target obstacle and the lane-changing vehicle foreseen in advance, and performing longitudinal control of the vehicle based on the calculated acceleration and deceleration of the vehicle, wherein the longitudinal control at least includes longitudinal following control, follow-stop start control, targetless parking control and wheel-end torque command limitation, wherein: in the intelligent queuing mode, EBS is prohibited from performing torque distribution, and braking energy distribution is performed through the braking energy distribution module to achieve efficient deceleration control; in the intelligent queuing mode, when the front target is lost, targetless parking control is performed to finally stop the vehicle in place, and then the N gear is switched to the handbrake exit function; in the intelligent queuing mode, an improved IDM model is used to calculate the following control.

[0060] The lateral control of the vehicle includes: using pure tracking, LQR or MPC method to control the vehicle laterally.

[0061] In a specific application, steps S102-S104 are actually divided into target screening, tracking, trajectory generation, and lateral and longitudinal control processes of the vehicle.

[0062] Specifically, the target screening module obtains obstacle perception information and vehicle status information, analyzes and predicts the motion status of the vehicle and the obstacle, and screens out all target obstacles that affect the operation of the corresponding functions of the vehicle.

[0063] Prediction of the vehicle's driving trajectory: The vehicle's driving trajectory is simulated through the vehicle's state parameters, such as the vehicle's longitudinal speed, lateral speed, and yaw angular velocity, and the lane exit line is further simulated.

[0064] The required target obstacles are screened out according to the virtual lane line and obstacle ID, fusion status, type, etc. The screened obstacles are the closest obstacle in the longitudinal distance of the lane, the second closest obstacle in the longitudinal distance of the lane, the closest obstacles in the adjacent left and right virtual lanes, etc. If it is determined that the closest obstacle in the lane has the intention to change lanes, whether to switch obstacles is determined based on whether the second closest obstacle exists. If the second closest obstacle exists, the second closest obstacle is re-selected as the closest obstacle, otherwise the vehicle follows the vehicle in front to change lanes.

[0065] Non-vehicle target handling strategy: During the function activation process, if the newly selected target type is a non-vehicle target (pedestrians, two-wheeled vehicles and other obstacles), the system will immediately issue a takeover reminder, and at the same time calculate and issue the deceleration for collision avoidance. After the vehicle stops, the system requests to pull up the EPB, and the vehicle remains stationary. After the target disappears, continue to queue with the vehicle; if the newly selected target type is a vehicle target, the system recalculates the vehicle trajectory and continues to queue with the vehicle.

[0066] In order to control the vehicle laterally, the lateral trajectory generates a lateral trajectory. The lateral trajectory can be one or several trajectory points. The options are as follows:

[0067] Directly follow the vehicle in front: Only one point of the vehicle in front is needed to perform lateral control;

[0068] Front vehicle trajectory plan: record the historical trajectory of the front vehicle and let the self-vehicle follow the historical trajectory of the front vehicle.

[0069] Horizontal and vertical control:

[0070] Configuring lateral and longitudinal functions according to vehicle type: IPC determines whether to activate only longitudinal queuing or both lateral and longitudinal queuing functions according to the vehicle's EHPS type. The lateral control function is only allowed to be activated if the vehicle is equipped with a wire-controlled EHPS. It can be performed using lateral and longitudinal coupling control or lateral and longitudinal separation control strategies. Optionally, lateral and longitudinal separation control is as follows:

[0071] Longitudinal control:

[0072] Longitudinal control includes functions such as longitudinal following control, follow-stop start control, targetless parking control, and wheel-end torque command limitation.

[0073] The IPC function can adjust the following parking distance (button multiplexing time distance + / - button). When the IPC working conditions are met and the driver presses the button to activate IPC, the default following parking distance after activation is set as follows:

[0074] 1. If the driver activates IPC while the vehicle is stationary and the distance to the vehicle ahead is between the minimum safety distance and the maximum set following distance, the actual distance to the vehicle ahead will be set as the current following distance.

[0075] 2. If the driver currently activates IPC while the vehicle is in motion, the system sets Xm as the current default following distance.

[0076] 3. After the IPC function is activated, the driver can increase or decrease the following distance behind the vehicle in front by pressing the button (addition / subtraction increases / decreases the distance by 1m each time).

[0077] Following stop distance memory: During the current power-on cycle, the following stop distance set by the driver when the function was last activated is memorized. After powering on and off again, the following stop distance is restored to the default.

[0078] Longitudinal following: By obtaining the distance, speed, acceleration of the obstacle vehicle in front and the lane-changing vehicle foreseen in advance, the appropriate acceleration and deceleration control is calculated. The improved IDM model is used to calculate the following control. The calculation formula is as follows:

[0079]

[0080]

[0081] The ACH acceleration model is used to integrate the results of IDM.

[0082]

[0083] Stop-and-start control: During the process of approaching stop, stopping, and starting, ensure that the vehicle is parked within the appropriate range and the starting conditions are triggered, and continue to follow the vehicle normally.

[0084] 1. When the following stop time is less than T1, the vehicle will automatically follow the front vehicle when it starts;

[0085] 2. When T1 is less than the follow-stop time and T2s is less than the stop time, the system will issue a warning that the vehicle ahead has left after the vehicle ahead has started, and the driver needs to lightly press the accelerator pedal to start;

[0086] 3. When the follow-up stop time is ≥ T3, request EPB to be pulled up. After EPB is pulled up, the function does not exit and the system remains activated;

[0087] 4. After the EPB is pulled up, if the starting conditions of the vehicle in front are met, the system will issue a reminder for the vehicle in front to leave. At this time, after the driver lightly presses the accelerator pedal to confirm, the system will issue an EPB release request. After the EPB is released, the system will continue to perform the following control.

[0088] No target parking control: When the vehicle is stopped, if the target ahead is lost or there is no target ahead for more than T4, the system will request to shift to N gear and pull EPB, and finally exit the IPC function; when the vehicle is following a vehicle, if the vehicle ahead gradually moves away, wait until the target has driven to the farthest distance or the target is lost, then request the driver to take over, and then gradually brake to a stop. After braking, execute the operation of shifting to N gear and pulling EPB, and then exit the IPC function.

[0089] Wheel-end torque command limit: According to different scenario conditions (different stages such as stationary start, driving and following, different vehicle weights), the target acceleration of the vehicle at different vehicle speeds is limited, and the wheel-end torque output limit is calculated based on the acceleration limit.

[0090] Inverse longitudinal dynamics model: The required target torque is calculated using the inverse longitudinal dynamics model.

[0091] Wheel end torque:

[0092] WheelTorque=F_{drive}*R; R is the radius of the vehicle tire.

[0093] F_{drive}-F_{load}=m*a

[0094] Among them, F_{drive} is the driving force of the vehicle, which is used to calculate the wheel end torque.

[0095] F_{load} is the vehicle's driving resistance, including aerodynamic resistance, rolling resistance, etc.

[0096] Through theoretical calculation or actual vehicle experiment, we can get:

[0097] F_{load}=k1*v^2+K2*v+k3, K1 K2 K3 are the coefficients obtained by calibration.

[0098] m is the vehicle weight and a is the expected acceleration.

[0099] Because when new energy heavy trucks brake, they can use motor negative torque braking or EBS braking, and execute the switching strategy of motor negative torque and EBS. When the longitudinal control calculates a negative deceleration, the longitudinal control is responsible for the distribution of braking energy. EBS is prohibited from performing torque distribution:

[0100] In the automatic driving mode, EBS is prohibited from distributing torque. The brake energy distribution module is used to distribute the brake energy, achieving more efficient deceleration control. The specific strategies are as follows:

[0101] The negative torque required for braking is calculated based on the calculated braking deceleration; the maximum negative torque capacity of the motor is obtained from the motor control module. If the maximum negative torque capacity of the motor is greater than the required automatic negative torque, the motor is used for braking. Otherwise, the difference between the two is supplemented by the EBS module.

[0102] Lateral Control:

[0103] The lateral control can adopt pure tracking, LQR, MPC and other methods. Optionally, the pure tracking method is as follows:

[0104] like Figure 2As shown in the figure, pure tracking is essentially a proportional controller, which is proportional to the lateral position deviation and inversely proportional to the square of the forward distance. The curvature of the road is not taken into account; the robustness is good; even if the road is discontinuous, its robustness is still good. The idea of ​​the algorithm is to match a preview point at a distance ld forward on the reference path based on the current center position of the rear wheel of the vehicle. It is assumed that the center point of the rear wheel of the vehicle can reach the preview point according to a certain turning radius R, and then determine the front wheel turning angle based on the geometric relationship between the preview distance ld, the turning radius R, and the orientation angle α of the preview point in the vehicle coordinate system.

[0105] Lateral hand torque takeover: When the IPC function is activated, after the driver applies hand torque takeover on the steering wheel, the function is downgraded to longitudinal following queue mode and the lateral control does not self-recover. At the same time, a prompt sound and a pop-up window request are sent to the instrument, and the pop-up window prompts "The driver has taken over the steering wheel and is currently in longitudinal following queue."

[0106] Upgrade to lateral queuing: When the IPC function is downgraded to longitudinal following queuing mode due to the driver taking over laterally, the driver needs to upgrade to lateral and longitudinal following queuing mode by clicking the IPC activation button again (press and hold the ICA button for more than 1000ms).

[0107] The steering wheel angle value (for example, ±500°) is commanded according to the maximum lateral controllability limit. When the calculated steering wheel angle value is continuously greater than the maximum limit for more than the set time, it is considered that the lateral control capability is insufficient, and the driver is reminded to take over the lateral control.

[0108] Hands-off detection and reminder:

[0109] When the vehicle is in a controlled state laterally, the system continuously detects the driver's hands-off state; if it detects that the driver has kept hands-off, the system will remind the driver to keep hands on the steering wheel through voice. The hands-off reminder can be divided into N levels, and each level corresponds to a different duration of hands-off state (such as 10s, 20s, 30s, etc.). If the driver keeps hands-off and meets the N-level reminder that the driver still does not have hands on the steering wheel, the system will slowly brake the vehicle to stop and exit the function.

[0110] Human-computer interaction interface:

[0111] The human-computer interaction of the intelligent queuing function is mainly reflected through the dashboard, central control screen and steering wheel buttons. The reminders mainly include voice reminders, instrument interface pop-up reminders, and text reminders.

[0112] The intelligent queuing assistance method for vehicles in the embodiment of the present application does not rely on lane lines, and compared with ICA and TJA, it improves the scope of application of the function and avoids the risks caused by misdetection of lane lines; the applicable scenarios are structured roads or unstructured roads inside and outside the factory area, with potholes, no pavement, no lane lines, but there may be grid lines, parking space lines and other ground surfaces; special working condition safety parking mechanism: for example, in working conditions such as the sudden disappearance of obstacles, the driver will be reminded to take over before the system exits the function. If the driver has not taken over, the system will execute a safe parking strategy, slowly brake to a stop, switch to N gear and pull the handbrake, and then exit the function to ensure safety; the designed operating speed is within the queuing scene range (0~30kph); within this speed, the driver is provided with lateral and longitudinal assistance. During the process, the driver can take over the lateral function through the steering wheel, so that the entire function only remains longitudinal; when the conditions are met, the lateral and longitudinal control functions can be entered from lateral control only. For some curves with a relatively large turning radius, the driver can pass by just taking over the steering wheel, which improves the availability of the entire function. The target type of the queue is a vehicle. If the screened target is a non-vehicle such as a pedestrian or a bicycle, the driver will be reminded to take over the vehicle. If the driver does not take over, a safe parking strategy will be implemented. When the queue function is activated, there must be an obstacle within a certain range in front of the vehicle, otherwise the function cannot be activated. When the queue function is activated, if the lateral activation conditions are not met, only the longitudinal function can be activated. Intelligent queue scene reminder: Through the intelligent queue scene working condition judgment module, the driver is reminded that he can enter the automatic queue function, and the function is activated after the driver presses the button to confirm.

[0113] According to the intelligent queuing assistance method for vehicles in the embodiment of the present application, the intelligent queuing function inputs the perception and fusion of environmental information, performs vehicle auxiliary behavior decision-making, trajectory planning and control, and sends the longitudinal and lateral control commands of the vehicle to the control unit to realize automatic control of the lateral and longitudinal movement of the vehicle in the case of intelligent queuing. It can effectively reduce the driver's frequent manipulation of the vehicle when queuing, and alleviate the driver's highly concentrated monitoring of the environment, improve the driving comfort when queuing, and avoid traffic creep caused by slow vehicle response due to overly conservative driving or slow reaction of the driver.

[0114] Figure 3 FIG. 1 is a structural block diagram of an intelligent queuing assistance system for vehicles according to an embodiment of the present application. Figure 3 As shown, the intelligent queuing assistance system for vehicles according to an embodiment of the present application includes: an acquisition module 310, a screening module 320, a generation module 330 and a control module 340, wherein:

[0115] An acquisition module 310 is used to obtain road condition information and obstacle information;

[0116] A screening module 320, configured to screen and obtain an initial target obstacle that affects the operation of the vehicle according to the vehicle status information and the obstacle information;

[0117] A generating module 330, configured to obtain a target obstacle according to the initial target obstacle, and generate a driving trajectory of the ego vehicle according to the type of the target obstacle;

[0118] The control module 340 is used to perform intelligent queuing control of the vehicle such as waiting, following or changing lanes according to the driving trajectory.

[0119] According to the intelligent queuing assistance system of the vehicle in the embodiment of the present application, the intelligent queuing function inputs the perception and fusion of environmental information, performs vehicle auxiliary behavior decision-making, trajectory planning and control, and sends the longitudinal and lateral control commands of the vehicle to the control unit to realize automatic control of the lateral and longitudinal movement of the vehicle in the case of intelligent queuing. It can effectively reduce the driver's frequent manipulation of the vehicle when queuing, and alleviate the driver's highly concentrated monitoring of the environment, improve the driving comfort when queuing, and avoid traffic creep caused by slow vehicle response due to overly conservative driving or slow reaction of the driver.

[0120] For the specific definition of the intelligent queuing assistance system for vehicles, please refer to the definition of the intelligent queuing assistance method for vehicles mentioned above, which will not be repeated here. The various modules of the intelligent queuing assistance system for vehicles mentioned above can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0121] In one embodiment, a vehicle is provided, comprising: an intelligent queuing assistance system for a vehicle according to the above embodiment, wherein the intelligent queuing function of the vehicle inputs the perception fusion environmental information, performs vehicle auxiliary behavior decision-making, trajectory planning and control, and sends the longitudinal and lateral control commands of the vehicle to the control unit to realize automatic control of the lateral and longitudinal movement of the vehicle under intelligent queuing conditions. It can effectively reduce the driver's frequent manipulation of the vehicle when queuing, and alleviate the driver's highly concentrated monitoring of the environment, improve the driving comfort when queuing, and avoid traffic creep caused by slow vehicle response due to overly conservative driving or slow reaction of the driver.

[0122] The vehicle is, for example, a truck.

[0123] In addition, other structures and functions of the vehicle according to the embodiment of the present application are known to ordinary technicians in the field and will not be elaborated herein.

[0124] In one embodiment, a computer device is provided. Figure 4 This is a block diagram of the computer device provided in the embodiment of the present application, refer to Figure 4 The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the above-mentioned vehicle intelligent queuing assistance method embodiment is implemented. For example, the following is performed: obtaining road condition information and obstacle information;

[0125] According to the state information of the ego vehicle and the obstacle information, an initial target obstacle affecting the operation of the ego vehicle is screened and obtained;

[0126] Obtaining a target obstacle according to the initial target obstacle, and generating a driving trajectory of the vehicle according to the type of the target obstacle;

[0127] According to the driving trajectory, intelligent queuing control is performed on the vehicle such as waiting, following or changing lanes.

[0128] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and the processor implements the above-mentioned vehicle intelligent queuing assistance method embodiment when executing the computer program. For example, the following steps are performed: obtaining road condition information and obstacle information;

[0129] According to the state information of the ego vehicle and the obstacle information, an initial target obstacle affecting the operation of the ego vehicle is screened and obtained;

[0130] Obtaining a target obstacle according to the initial target obstacle, and generating a driving trajectory of the vehicle according to the type of the target obstacle;

[0131] According to the driving trajectory, intelligent queuing control is performed on the vehicle such as waiting, following or changing lanes.

[0132] The present application embodiment provides a computer program product, which includes instructions. When the instructions are executed, the method described in the embodiment of the present application is executed. For example, it can be executed Figure 1 The various steps of the vehicle intelligent queuing assistance method shown, for example, are performed: obtaining road condition information and obstacle information;

[0133] According to the state information of the ego vehicle and the obstacle information, an initial target obstacle affecting the operation of the ego vehicle is screened and obtained;

[0134] Obtaining a target obstacle according to the initial target obstacle, and generating a driving trajectory of the vehicle according to the type of the target obstacle;

[0135] According to the driving trajectory, intelligent queuing control is performed on the vehicle such as waiting, following or changing lanes.

[0136] Those of ordinary skill in the art can understand that all or part of the processes in the methods for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0137] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A vehicle intelligent queuing assistance method, characterized in that: include: Obtain road condition information and obstacle information; According to the state information of the ego vehicle and the obstacle information, an initial target obstacle affecting the operation of the ego vehicle is screened and obtained; Obtaining a target obstacle according to the initial target obstacle, and generating a driving trajectory of the vehicle according to the type of the target obstacle; According to the driving trajectory, intelligent queuing control is performed on the vehicle such as waiting, following or changing lanes.

2. The intelligent queuing assistance method for vehicles according to claim 1, characterized in that: The initial target obstacle affecting the operation of the vehicle is screened based on the vehicle state information and the obstacle information, including: According to the state information of the vehicle, the driving trajectory of the vehicle is virtualized to obtain the virtual lane line; According to the virtual lane line and obstacle information, initial target obstacles are screened out, wherein the initial target obstacles include the obstacles closest and second closest to the longitudinal distance of the vehicle in the virtual lane line, and the obstacles closest to the left and right of the virtual lane line.

3. The intelligent queuing assistance method for vehicles according to claim 2, characterized in that: The step of obtaining a target obstacle according to the initial target obstacle and generating a driving trajectory of the vehicle according to the type of the target obstacle includes: If the obstacle closest to the vehicle in the virtual lane line has the intention to change lanes; If yes, determine whether there is the next closest obstacle; If the next closest obstacle exists, the next closest obstacle is used as the target obstacle; otherwise, the lane change operation is performed following the preceding vehicle.

4. The intelligent queuing assistance method for vehicles according to claim 3, characterized in that: Also includes: Determining whether the target obstacle is a vehicle; If not, a takeover reminder is given and obstacle avoidance operations are performed.

5. The intelligent queuing assistance method for vehicles according to claim 3, characterized in that: The virtualizing the driving trajectory of the vehicle according to the state information of the vehicle to obtain the virtual lane line includes: Perform lateral control of the vehicle based on the location of the target obstacle; or The historical trajectory of the target obstacle is recorded, and the ego vehicle is controlled to follow the historical trajectory of the target obstacle.

6. The intelligent queuing assistance method for vehicles according to claim 5, characterized in that: Longitudinal control of the ego vehicle includes: According to the distance, speed, acceleration of the target obstacle and the lane-changing vehicle foreseen in advance, the acceleration and deceleration of the vehicle are calculated, and the longitudinal control of the vehicle is performed based on the calculated acceleration and deceleration of the vehicle, wherein the longitudinal control at least includes longitudinal following control, follow-stop start control, non-target parking control and wheel-end torque command limitation, Among them: In the intelligent queuing mode, EBS is prohibited from distributing torque, and the braking energy distribution module is used to distribute braking energy to achieve efficient deceleration control; In the intelligent queuing mode, when the target ahead is lost, the targetless parking control is executed to finally stop the vehicle in place, and then the N gear is engaged and the handbrake is engaged to exit the function; In the intelligent queuing mode, the improved IDM model is used to calculate the vehicle following control.

7. The intelligent queuing assistance method for vehicles according to claim 5, characterized in that: Lateral control of the vehicle includes: Use pure tracking, LQR or MPC methods to control the ego vehicle laterally.

8. An intelligent queuing assistance system for vehicles, characterized in that: include: An acquisition module is used to obtain road condition information and obstacle information; A screening module, used for screening and obtaining initial target obstacles that affect the operation of the vehicle according to the state information of the vehicle and the obstacle information; A generating module, used to obtain a target obstacle according to the initial target obstacle, and generate a driving trajectory of the ego vehicle according to the type of the target obstacle; The control module is used to intelligently control the waiting, following or lane changing of the vehicle according to the driving trajectory.

9. A vehicle, characterized in that: include: An intelligent queuing assistance system for vehicles according to claim 8.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the intelligent queuing assistance method for vehicles according to any one of claims 1 to 7 is implemented.

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