Vehicle control method and related product

Abstract

A vehicle control method and a vehicle control apparatus. On the basis of motion information and perception data of a first vehicle, a plurality of trajectories having different passing regions are planned, and then an optimal trajectory is determined from among the plurality of trajectories. Further, the vehicle control apparatus controls the first vehicle to travel along a passing trajectory of the first vehicle, such that the first vehicle and a target obstacle pass each other in a target passing region. By using this multi-trajectory parallel planning solution, when faced with a passing scenario, an optimal passing trajectory can be determined from among the plurality of trajectories having different passing regions, and thus the safety and comfort of the passing trajectory in the passing scenario, the traffic efficiency and the ride experience of occupants can be improved.

Description

A vehicle control method and related products Technical Field

[0001] This application relates to the field of intelligent vehicle technology, and in particular to a vehicle control method and related products. Background Technology

[0002] With the continuous growth in car ownership and the increasing density of vehicles on the road, the frequency of oncoming traffic encounters is also increasing. In traditional driving, passing other vehicles mainly relies on the driver's experience and judgment, which often leads to scrapes or vehicles falling off the road.

[0003] With the rise of intelligent driving technology, ensuring vehicles safely navigate oncoming traffic has become a challenge in the design of intelligent driving systems. Currently, intelligent driving systems often use rule-based methods to first determine which environmental conditions are met, and then derive a driving strategy for those conditions. However, each condition is tailored to a specific situation, lacking flexibility, and this rule-based driving strategy does not align with human drivers' driving habits. Summary of the Invention

[0004] This application provides a vehicle control method and related products that can improve the safety and comfort of oncoming traffic trajectories in oncoming traffic scenarios, increase traffic efficiency, and make the decision-making process and results more human-like and intelligent.

[0005] Firstly, this application provides a vehicle control method applied to a vehicle control device capable of controlling a vehicle. For example, the vehicle control device can directly generate control commands for components within the vehicle. Furthermore, the vehicle control device can generate information for controlling components within the vehicle, such as one or more of the following: trajectory, information triggering the generation of a user interface, information triggering the generation of a projection, and target quantities for control operations. This information for controlling the vehicle can be provided to a control execution device to achieve vehicle control. Exemplarily, the vehicle control device is a computing device within the vehicle, such as a controller, mobile data center (MDC) (or autonomous driving domain controller), domain controller (DC), electronic control unit (ECU), etc., where the DC includes a motion domain controller (MDC), vehicle domain controller (VDC), etc. Alternatively, the vehicle control device can be a software and / or hardware module within the aforementioned computing device.

[0006] The vehicle control method includes: a vehicle control device planning multiple alternative motion trajectories along a first road based on the motion information and perception data of a first vehicle; determining a target motion trajectory based on the multiple alternative motion trajectories; and using the target motion trajectory to indicate the meeting trajectory of the first vehicle. The vehicle control device controls the first vehicle to travel along the meeting trajectory of the first vehicle, so that the first vehicle meets the target obstacle in the target meeting area.

[0007] The perception data includes road information of the first road and motion information of the target obstacle. The direction of motion of the target obstacle on the first road is opposite to the direction of motion of the first vehicle on the first road. That is, the target obstacle is an obstacle traveling towards the first vehicle, and the vehicle will interact with the target obstacle on the first road.

[0008] Each alternative trajectory corresponds to an alternative meeting area. Multiple alternative trajectories correspond to different alternative meeting areas. Here, the alternative meeting area refers to the range of locations where the first vehicle and the target obstacle may meet. In other words, the vehicle control device plans multiple trajectories with different meeting areas. For example, if the vehicle follows trajectory 1, the first vehicle will meet the target obstacle in area 1. However, if the vehicle follows trajectory 2, the first vehicle will meet the target obstacle in area 2.

[0009] Furthermore, the vehicle control device can use multiple motion trajectories to determine the target intersection trajectory. If the first vehicle travels according to the target intersection area, it will interact with the target obstacle in the alternative intersection area (i.e. the target intersection area) corresponding to the target motion trajectory.

[0010] In the above implementation, when there are oncoming traffic participants (i.e., target obstacles), the vehicle control device plans multiple trajectories with different intersection areas based on the vehicle's motion information and environmental perception data, and then decides on the optimal trajectory. This multi-trajectory parallel planning scheme, when facing oncoming traffic, can determine the optimal return trajectory from multiple trajectories with different intersection areas, improving the safety and comfort of oncoming traffic, increasing traffic efficiency, and enhancing the passenger experience. Furthermore, the vehicle control device observes the environment, estimates multiple oncoming traffic areas, plans trajectories for each of these areas, and then makes a decision; this decision-making process and result are more human-like and intelligent.

[0011] In another possible implementation of the first aspect, the target obstacle is a second vehicle. In the above implementation, the target obstacle can be a vehicle, such as a second vehicle. In this case, the vehicle control device can utilize the vehicle control method of the first aspect to control the safe passing of the first vehicle and the second vehicle.

[0012] In another possible implementation of the first aspect, the target obstacle is an object (including living objects) that meets preset conditions, such as an object that meets preset size conditions, or an object in motion, or an object that meets preset size conditions and has the ability to move (currently possibly in a stationary or moving state), or an object of a preset type.

[0013] For example, the dimensional conditions include related conditions such as length, width, height, volume, and cross-sectional area. For instance, preset dimensional conditions include at least one of the following: length greater than or equal to a first length, width greater than or equal to a first width, or height greater than or equal to a first height. The values ​​of the first length, first width, and first height can be predefined or flexibly determined.

[0014] In one possible implementation of the first aspect, the vehicle control device plans multiple alternative motion trajectories through the first road based on the motion information and perception data of the first vehicle, including the following operations: the vehicle control device samples multiple alternative intersection areas within the encounter area between the first vehicle and the target obstacle on the first road, and obtains multiple alternative motion trajectories based on the motion information of the first vehicle, perception data, and information of the multiple alternative intersection areas.

[0015] In the above implementation, by sampling the meeting area and then performing trajectory planning, the trajectory planning can be guided by the meeting area. The trajectory planning is more purposeful, the computational complexity is relatively low, and the differentiation between different trajectories can be guaranteed, which helps to select a safe, comfortable and efficient meeting trajectory.

[0016] In some possible implementations, the vehicle control device can display multiple alternative intersection areas via an interface. For example, the target trajectory is highlighted, such as by bolding or thickening. Other trajectories that are not the target trajectory are displayed without highlighting, such as by reducing brightness or displaying in grayscale.

[0017] In another possible implementation of the first aspect, the vehicle control device samples multiple candidate intersection areas within the encounter area between the first vehicle and the target obstacle, including the following operation: the vehicle control device samples along the longitudinal direction of the first road at a first sampling interval within the encounter area to obtain multiple candidate intersection areas.

[0018] In this context, longitudinal direction refers to the direction along the centerline of the road. In road engineering and related fields, longitudinal and transverse directions are commonly used terms to describe the different directional characteristics of a road. Longitudinal direction is the length of the road, while transverse direction is the direction perpendicular to the centerline of the road, i.e., the width of the road.

[0019] The above embodiments describe the sampling method, which includes the sampling direction and the sampling interval. The longitudinal sampling considers the scenario where the vehicle and the target obstacle are traveling longitudinally relative to each other along the first road; therefore, the candidate intersection areas are sampled along the longitudinal direction. The sampling interval is a first sampling interval, which can be relative or absolute. For example, a sampling interval of 1 / 3 indicates that four candidate intersection areas are obtained. Similarly, a sampling interval of 2 meters (m) indicates that a candidate intersection area is formed every 2 meters. This interval can be the interval between the edges of the intersection areas or the interval between the centers of the intersection areas.

[0020] The above-described implementation method defines the sampling direction and sampling interval, which can standardize and streamline the sampling process, improve the usability of the intersection area obtained by sampling, ensure the differentiation between different trajectories, and help select safe, comfortable and efficient passing trajectories.

[0021] Of course, in some cases, sampling can be limited only to the sampling direction or only to the sampling interval. For example, random sampling can be performed along the longitudinal direction. Alternatively, intersection regions can be optimized along the longitudinal direction to obtain the k preferred intersection regions, where k is a positive integer.

[0022] In another possible implementation of the first aspect, the vehicle control device obtains multiple candidate motion trajectories based on the motion information of the first vehicle, perception data, and information on multiple candidate intersection areas, including the following operations: The vehicle control device obtains a first longitudinal trajectory using the motion information of the first vehicle, the motion information of the target obstacle, and information on the first candidate intersection area. The vehicle control device optimizes the first candidate motion trajectory using the motion information of the first vehicle, perception data, and the first longitudinal trajectory, and the first candidate motion trajectory belongs to multiple candidate motion trajectories.

[0023] The above scheme provides a trajectory planning method that combines lateral and longitudinal optimization. The vehicle control device adopts lateral and longitudinal joint planning, first pulling the vehicle and the target obstacle to the intersection area in the longitudinal direction, and then optimizing laterally to meet obstacle avoidance constraints, road constraints, etc., which can improve the safety and comfort of each trajectory.

[0024] The perception data also includes information about other obstacles in the environment, which includes obstacles in the surrounding environment other than the target obstacle.

[0025] In another possible implementation of the first aspect, the vehicle control device obtains a first longitudinal trajectory using the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first candidate intersection area. This includes the following operation: the vehicle control device solves a first optimization problem based on the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first candidate intersection area to obtain the first longitudinal trajectory. Exemplarily, the first optimization problem is established based on first trajectory-related parameters, which include one or more of the following: the position of the first candidate area, the velocity and reference velocity of the first vehicle at the i-th trajectory point, the acceleration of the first vehicle at the i-th trajectory point, the jerk (reciprocal of the acceleration) of the first vehicle at the i-th trajectory point, the velocity and reference velocity of the target obstacle at the i-th trajectory point, the acceleration of the target obstacle at the i-th trajectory point, and the jerk of the target obstacle at the i-th trajectory point, where i is a positive integer, for example, 1, 2, 3, ...

[0026] The above method presents a longitudinal trajectory optimization approach. During trajectory planning, the vehicle control device establishes an optimization problem based on the motion information of the first vehicle and the target obstacle, and solves it to obtain the motion trajectory. When establishing the optimization problem, multiple trajectory points during the journey from the starting point to the destination are typically considered. By analyzing global information, the optimal trajectory is solved, ensuring that the trajectory reaches an optimal state at the global level, i.e., it possesses global optimality. Furthermore, the optimization problem can flexibly consider various constraints and objective functions, exhibiting high compatibility and scalability.

[0027] For example, a first optimization problem is as follows: minimize cost=∑{w ego,v (v ego,i -v egoref,i ) 2 +w ego,a (a ego,i ) 2 +w ego,j (j ego,i ) 2 +w obj,v (v obj,i -v obj,i ) 2 +w obj,a (a obj,i ) 2 +w obj,j (j obj,i ) 2} subjectto(S ego , i -conflictsS1)*(S obj , i -conflictsS2)≥0

[0028] Where subjectto refers to the constraints of the optimization problem, and S ego , i Let S be the distance between the i-th trajectory point of the vehicle (denoted as ego) and the initial point, and let conflictsS1 be the distance between the candidate passing areas and the vehicle. Similarly, S... obj , i is the distance between the i-th trajectory point of the target obstacle (denoted as obj) and the initial point, while conflictsS2 is the distance between the alternative passing area and the target obstacle.

[0029] Minimize refers to finding the solution that minimizes the cost. Here, w ego,v As a weight of the vehicle's speed, v ego,i Let v be the velocity of the vehicle at the i-th trajectory point. egoref,i Let w be the reference velocity of the vehicle at the i-th trajectory point. ego,a As the weight of the vehicle's acceleration, a ego,i Let w be the acceleration of the vehicle at the i-th trajectory point. ego,j As the weight of the vehicle's agility (jert), j ego,i Let represent the jerk of the vehicle at the i-th trajectory point. Here, the subscript 'obj' indicates parameters related to the target obstacle; for details, please refer to the previous section on vehicle parameters.

[0030] In another possible implementation of the first aspect, the vehicle control device uses the motion information, perception data and first longitudinal trajectory of the first vehicle to optimize and obtain a first alternative motion trajectory, including the following operation: the vehicle control device solves a second optimization problem based on the motion information, perception data and first longitudinal trajectory of the first vehicle to obtain the first alternative motion trajectory.

[0031] For example, the first optimization problem is established based on the second trajectory-related parameters, which include one or more of the following: the first longitudinal trajectory, the lateral position of the first vehicle at the j-th trajectory point, the longitudinal position of the first vehicle at the j-th trajectory point, the heading angle of the first vehicle at the j-th trajectory point, the curvature of the first vehicle at the j-th trajectory point, the rate of change of curvature of the first vehicle at the j-th trajectory point, the acceleration of the first vehicle at the j-th trajectory point, the lateral position of the target obstacle at the j-th trajectory point, the longitudinal position of the target obstacle at the j-th trajectory point, the heading angle of the target obstacle at the j-th trajectory point, the curvature of the target obstacle at the j-th trajectory point, the rate of change of curvature of the target obstacle at the j-th trajectory point, the acceleration of the target obstacle at the j-th trajectory point, obstacle avoidance constraints of the first vehicle and the target obstacle, and road boundary constraints of the first vehicle and the target obstacle, etc.

[0032] The above method presents a lateral trajectory optimization approach. When the longitudinal movements of the two vehicles are determined, the vehicle control device considers constraints such as surrounding environmental obstacles and road boundaries, as well as the obstacle avoidance half-space constraints between the two vehicles, and solves for the optimal obstacle avoidance trajectory between the two vehicles.

[0033] For example, a second optimization problem is as follows: minimize cost=∑{w ego,x (x ego,j -x egoref,j ) 2 +w ego,y (y ego,j -y egoref,j ) 2 +w ego,θ (θ ego,j -θ egoref,j ) 2 +w ego,k (k ego,j ) 2 +w ego,u (u ego,j ) 2 +w ego,a (a ego,j ) 2 +w obj,x (x obj,j -x objref,j ) 2 +w obj,u (y obj,j -y objref,j ) 2 +w obj,θ (θobj ,j -θobjref ,j ) 2 +w obj,k (k ego,j ) 2 +w obj,u (u obj,j ) 2 +w obj,a (a obj,j ) 2}

[0034] subject to A1*(x ego -x obj )+B1*(y ego -y obj )+C1≤0

[0035] ... A n-1 *xego +B n-1 *y ego +C n-1 ≤0 A n *x obj +B n *y obj +C n ≤0

[0036] Where x represents the position in the x-direction, y represents the position in the y-direction, θ represents the heading angle, k represents the curvature, and u represents the rate of change of curvature. A1*(x ego -x obj )+B1*(y ego -y obj The constraint A + C1 ≤ 0 represents an obstacle avoidance constraint. Optional constraints for obstacle avoidance include half-space constraints on the vehicle's obstacle avoidance area. n -1*x ego +B n-1 *y ego +C n -1≤0 represents the boundary constraint for the vehicle, A n *x obj +B n *y obj +C n ≤0 represents the boundary constraint of the target obstacle, such as the road boundary constraint.

[0037] In another possible implementation of the first aspect, the vehicle control method further includes the following operation: the vehicle control device determines the encounter area between the first vehicle and the target obstacle based on the motion information of the first vehicle and the motion information of the target obstacle. The candidate intersection areas corresponding to multiple candidate motion trajectories are all within the encounter area.

[0038] In the above embodiments, the vehicle control device determines the area where the vehicle and other vehicles may meet based on the movement information of the vehicle and the target obstacle, thereby enabling the acquisition of the meeting area to be carried out within the area where the vehicles may meet, improving the availability of the trajectory and increasing the utilization rate of computing resources.

[0039] In another possible implementation of the first aspect, the encounter area includes a first boundary and a second boundary opposite each other along the longitudinal direction of the first road, the first boundary corresponding to the maximum acceleration of the first vehicle and the maximum deceleration of the target obstacle, and the second boundary corresponding to the maximum deceleration of the first vehicle and the maximum acceleration of the target obstacle.

[0040] In the above embodiment, the vehicle control device considers the maximum acceleration and maximum deceleration of both the vehicle and the target obstacle to find the upper and lower limits of the meeting area. Since both the vehicle and the target obstacle have initial velocities, if the target obstacle uses maximum acceleration and / or the vehicle uses maximum deceleration, the boundary closest to the vehicle can be determined. Similarly, considering the target obstacle using maximum deceleration and / or the vehicle using maximum acceleration, the boundary closest to the target obstacle can be determined. The area within these two boundaries is the region where the vehicle and the target obstacle may meet.

[0041] In another possible implementation of the first aspect, the vehicle control device determines the encounter area between the first vehicle and the target obstacle based on the motion information of the first vehicle and the motion information of the target obstacle, including the following operations: The vehicle control device determines the interaction range between the first vehicle and the target obstacle based on the motion path of the first vehicle and the predicted motion path of the target obstacle. The vehicle control device determines the encounter area between the first vehicle and the target obstacle based on the speed, maximum acceleration, and maximum deceleration of the first vehicle, and the speed, maximum acceleration, and maximum deceleration of the target obstacle. Wherein, the motion path, speed, maximum acceleration, and maximum deceleration of the first vehicle belong to the motion information of the first vehicle, and the predicted motion path, speed, maximum acceleration, and maximum deceleration of the target obstacle belong to the motion information of the target obstacle.

[0042] In another possible implementation of the first aspect, the vehicle control device determines a target motion trajectory based on multiple alternative motion trajectories, including the following operation: the vehicle control device determines the target motion trajectory based on evaluation data of the multiple alternative motion trajectories. Exemplarily, the evaluation data is related to at least one of a safety cost parameter, an efficiency cost parameter, and a comfort cost parameter, wherein the safety cost parameter indicates the safety of the motion trajectory, the efficiency cost parameter indicates the communication efficiency of the motion trajectory, and the comfort cost parameter indicates the comfort of the motion trajectory.

[0043] In this way, the vehicle control device can comprehensively evaluate multiple motion trajectories and select the optimal passing trajectory. In the above implementation, when controlling vehicles to pass each other, not only obstacle avoidance safety but also comfort and efficiency are considered, resulting in a more human-like decision-making process and significantly improving the user experience.

[0044] For example, one method for calculating evaluation data is as follows: cost total =w safe cost safe +w effucient cost efficient +w comfortcost comfort

[0045] Among them, cost total This represents the total cost and is part of the evaluation data. safe This represents the weight of the security cost parameter. safe The safety cost parameter can be calculated from one or more of the following: distance between the vehicle and the target obstacle, speed, relative speed, distance between the vehicle and the road boundary, distance between the target obstacle and the road boundary, distance between the vehicle and other obstacles, or distance between the target obstacle and other obstacles. efficient This represents the weight of the efficiency cost parameter. efficient The efficiency cost parameter can be calculated from one or more of the following: trajectory travel time, whether the vehicle and the target obstacle need to stop and yield. comfort This represents the weight of the comfort cost parameter. comfort The comfort cost parameter can be calculated from one or more of the following during the rendezvous process: acceleration, deceleration, yaw rate, etc.

[0046] In some cases, vehicle control devices can provide information such as driving trajectory, interaction area, vehicle position, and target obstacles through a human-machine interface (HMI) or projection. This allows users to be informed of vehicle-related information, enabling them to better understand their surroundings and make driving decisions, reducing anxiety and improving the user experience.

[0047] In another possible implementation of the first aspect, the vehicle control method further includes: the vehicle control device displays a first interface through an interface, the first interface including one or more of the following prompt information: target obstacle prompt information, first prompt information, second prompt information, third prompt information, fourth prompt information, fifth prompt information, or sixth prompt information, etc. Wherein, the target obstacle prompt information is used to indicate that the target obstacle is a meeting object. The first prompt information is used to indicate the target meeting area. The second prompt information is used to indicate a first area within the target meeting area, the first area indicating the occupied position of the first vehicle when it aligns with the target vehicle. The third prompt information is used to indicate a second area within the target meeting area, the second area indicating the occupied position of the target obstacle when it aligns with the target vehicle. The fourth prompt information is used to indicate the meeting trajectory of the first vehicle. The fifth prompt information is used to indicate the expected movement trajectory of the target obstacle, the expected movement trajectory of the target obstacle being indicated by the target movement trajectory.

[0048] In another possible implementation of the first aspect, the vehicle control method further includes: the vehicle control device projecting a first image through a projection module. The first image includes one or more of the following prompt patterns: a first prompt pattern, a second prompt pattern, a third prompt pattern, a fourth prompt pattern, a fifth prompt pattern, or a sixth prompt pattern, etc. Exemplarily, the first prompt pattern is used to indicate a target meeting area. The second prompt pattern is used to indicate a first area within the target meeting area, the first area indicating the occupancy position of the first vehicle when it meets and aligns with a target vehicle. The third prompt pattern is used to indicate a second area within the target meeting area, the second area indicating the occupancy position of the target obstacle when the first vehicle meets and aligns with a target obstacle. The fourth prompt pattern is used to indicate the meeting trajectory of the first vehicle. The fifth prompt pattern is used to indicate the expected movement trajectory of the target obstacle, the expected movement trajectory of the target obstacle being indicated by the target movement trajectory. The sixth pattern is used to indicate the passage order of the first vehicle and / or the target obstacle, the passage order being related to the target movement trajectory.

[0049] Secondly, this application provides a vehicle control device, including a processing module and a control module. The processing module is used to perform one or more of the aforementioned operations such as planning, determining, sampling, obtaining data, solving, and optimizing. The control module is used to control a vehicle, a display device, or a projection module, etc. The vehicle control device is used to implement the methods described in the first aspect or any possible embodiment of the first aspect.

[0050] Thirdly, this application provides a vehicle control device, including at least one processor and a memory. The memory is used to store a computer program, and the at least one processor is used to invoke the computer program to implement the method described in the first aspect or any possible embodiment of the first aspect.

[0051] Fourthly, this application provides a chip system including at least one processor and a communication interface. The communication interface is used for inputting and / or outputting data, and the at least one processor is used for invoking computer instructions to implement the method described in the first aspect or any possible embodiment of the first aspect.

[0052] Fifthly, this application provides a vehicle control system, including a vehicle control device and a projection system. The vehicle control device is connected to the projection system, which includes a projection module. The vehicle control device is used to implement the method described in the first aspect or any possible embodiment of the first aspect, such that the projection module projects a first image.

[0053] In one possible implementation of the fifth aspect, the projection system may include an interactive control device and a projection module. The vehicle control device may provide projection information to the interactive control device, enabling the interactive control device to generate a first image based on the projection information and project the first image using the projection module. The projection information may include one or more of the following: information on the target's trajectory, information on the target's intersection area, information on the first area, information on the second area, and information on target obstacles.

[0054] Furthermore, the interactive control device and the projection module can be installed separately. Alternatively, the interactive control device and the projection module can be integrated together, for example, integrated into the vehicle's headlights.

[0055] In another possible implementation of the fifth aspect, the vehicle control device is able to control the projection module, in which case the vehicle control device can generate a first image and control the projection module to project the first image.

[0056] In a sixth aspect, this application provides a terminal that includes the vehicle control device described in the second aspect, or the vehicle control device described in the third aspect, or the chip system described in the fourth aspect, or the vehicle control system described in the fifth aspect.

[0057] Optionally, the terminal may include intelligent terminals or transportation vehicles such as vehicles, robots, drones, or ships.

[0058] The beneficial effects of the technical solutions in the second to sixth aspects of this application can be understood by referring to the beneficial effects of the technical solution in the first aspect. Attached Figure Description

[0059] The accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0060] Figure 1 is a schematic diagram of a vehicle architecture;

[0061] Figure 2 is a schematic diagram of the architecture of another type of vehicle;

[0062] Figure 3 is a schematic flowchart of a vehicle control method provided in an embodiment of this application;

[0063] Figure 4 is a schematic diagram of a meeting scenario;

[0064] Figure 5 is a schematic diagram of two alternative motion trajectories provided in the embodiments of this application;

[0065] Figure 6 is a schematic diagram of the sampling of the meeting area provided in an embodiment of this application;

[0066] Figure 7 is a schematic diagram of two longitudinal trajectories provided in the embodiments of this application;

[0067] Figure 8 is a schematic diagram of a method for determining an encounter area provided in an embodiment of this application;

[0068] Figure 9 is a schematic diagram of an interface provided in an embodiment of this application;

[0069] Figure 10 is a schematic diagram of another interface provided in an embodiment of this application;

[0070] Figure 11 is a schematic diagram of two types of projected images provided in the embodiments of this application;

[0071] Figure 12 is a schematic diagram of two more projected images provided in the embodiments of this application;

[0072] Figure 13 is a structural schematic diagram of a vehicle control device provided in an embodiment of this application;

[0073] Figure 14 is a structural schematic diagram of another vehicle control device provided in an embodiment of this application. Detailed Implementation

[0074] Before introducing the embodiments of this application, the terminology that may be used in the embodiments of this application will be introduced first.

[0075] 1. An obstacle is a physical entity that may slow down or impede the progress of a terminal during its journey, such as objects, terrain, or facilities. Objects can include living or inanimate objects. Furthermore, obstacles can be fixed or movable.

[0076] 2. Domain Controller. A domain is a functional area formed by dividing a vehicle's systems according to their functions, such as powertrain domain, chassis domain, body domain, cockpit domain, autonomous driving domain, left domain, right domain, etc. Each domain in the vehicle is centrally controlled by a high-performance computing platform; this device is the domain controller. A domain controller mainly includes, but is not limited to, one or more processors, memory, communication interfaces, power management modules, sensor interfaces, etc. The processor is responsible for running various software algorithms within the domain, processing data, making decisions, and controlling actuators. Memory is used to store the operating system, applications, and data, or for temporarily storing running programs and data. The communication interface is used to communicate with other electronic devices in the vehicle, enabling data transmission and interaction. The power management module is responsible for managing and distributing the power supply to the domain controller, ensuring a stable power supply to the system under different operating conditions. The sensor interface connects to various types of sensors, such as cameras, radar, accelerometers, etc., depending on the domain, allowing the processor to receive, process, and analyze sensor data from the corresponding domain. It should be understood that a domain controller may connect to other domain controllers or other controllers or processors with data processing capabilities to transmit or share information. For example, a domain controller may include an MDC, a cockpit domain controller (CDC), etc.

[0077] MDC, also known as Intelligent Driving Domain Controller, is positioned as the computing platform for intelligent driving and is a key hardware architecture for realizing software-defined vehicles. The hardware architecture of the MDC includes, but is not limited to, a main control chip, sensor interfaces, communication modules, power management modules, and cooling systems. The main control chip provides powerful artificial intelligence computing power to handle the numerous perception and computational tasks in intelligent driving, as well as system control functions. The sensor interfaces can have rich interfaces to connect to various types of sensors. These interfaces ensure that the MDC can quickly and accurately receive information from different sensors, providing data support for intelligent driving decisions. The communication module has high-speed communication capabilities, supporting communication methods such as in-vehicle Ethernet (for example only), ensuring efficient communication with the vehicle ECU and the cloud, and enabling real-time data transmission and interaction.

[0078] The Control Center (CDC) is a core component responsible for managing and controlling various electronic devices and functions within the cockpit. The CDC typically uses a system-on-a-chip (SoC) as its processing unit, and also includes storage and multiple communication interfaces. These interfaces allow the CDC to communicate with one or more of the following: interactive devices (such as displays and projectors), body control systems, powertrain systems, driver assistance systems, and sensor systems.

[0079] The above descriptions of technical terms can be applied to the embodiments described below.

[0080] The system architecture of the vehicle to which this application can be applied is described below. Please refer to Figures 1 and 2. The vehicle 10 includes a sensor system 13 and a vehicle control device 14.

[0081] The sensor system 13 may include several sensors (including detection devices) that measure information and convert the measured information into electrical signals or other desired forms of information output. As shown in Figure 1, the sensor system 13 of the vehicle 10 includes one or more of the following detection devices: image sensor 131, radar 132, lidar 133, positioning system 134, or speed sensor 135, etc. Some of these sensors are described below by example:

[0082] Image sensor 131 (or camera) is used to capture images, including pictures and videos. In some specific implementations, image sensor 131 includes, but is not limited to, dashcams, cameras, or other elements used for taking pictures / photographs. Optionally, some image sensors 131 are configured to capture images of the exterior of the vehicle to obtain information about the vehicle's surrounding environment, such as the distance, position, color, and volume of obstacles, as well as information about road elements. For example, referring to Figure 2, the camera can be installed on the top of the vehicle's cabin. Of course, multiple cameras can be installed in the vehicle, and these cameras can be distributed in different positions to capture images of different fields of view around the vehicle.

[0083] Radar 132 and lidar 133 are devices that detect objects using electromagnetic waves (including light). They can obtain relevant information about targets in the object space by emitting signals and receiving echoes, including one or more of the target's distance (or depth), position, angle, speed, reflectivity, and color. For example, referring to Figure 2, lidar 133 is configured to face outwards from the vehicle to detect information about obstacles around the vehicle.

[0084] Positioning system 134 is a device for acquiring location information, which can be used to achieve real-time vehicle positioning and provide the vehicle's geographical location information. Examples of positioning systems include the Global Positioning System (GPS) or the BeiDou Navigation Satellite System. Speed ​​sensor 135 is used to measure speed, such as wheel speed or vehicle speed.

[0085] The vehicle control device 14 is a computing device capable of controlling the vehicle 10. For example, the vehicle control device 14 can directly generate control commands for components within the vehicle (such as the powertrain, braking system, and interactive devices). Furthermore, the vehicle control device can generate information for controlling vehicle components, such as one or more of the following: trajectory, information triggering the generation of a user interface, information triggering the generation of a projection, and target quantities for control operations. The vehicle control device 14 may include one or more processors, which can be used to execute programs or instructions corresponding to programs to achieve corresponding functions. In one implementation, the processor may include circuitry with instruction read and execute capabilities, such as an arithmetic logic unit (ALU), processor core, central processing unit (CPU), microprocessor, microcontroller unit (MCU), graphics processing unit (GPU), or digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logic of hardware circuits. This hardware circuit logic can be fixed or reconfigurable. For example, the processor can be a hardware circuit implemented as an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as a field-programmable gate array (FPGA). In reconfigurable hardware circuits, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the corresponding function. Furthermore, the processor can also be a hardware circuit designed for artificial intelligence, which can be understood as a type of ASIC, such as a neural network processing unit (NPU), tensor processing unit (TPU), or deep learning processing unit (DPU). In some implementations, the vehicle control device 14 includes at least one processor integrated as a system-on-chip (SOC), commonly referred to as an SOC by those skilled in the art. This SOC can include at least one processor; when the SOC includes multiple processors, the types of processors can be different, such as a CPU, an MCU, and an NPU.

[0086] For example, the vehicle control device 14 includes a controller, a domain controller (DC), an electronic control unit (ECU), etc., where the DC is such as an MDC. In some solutions, the vehicle control device 14 may not be located inside the vehicle, for example, it may be located in the cloud, on roadside equipment, or in a data center. In some cases, the vehicle control device 14 includes multiple modules, such as a trajectory planning module and a control execution module. The trajectory planning module is used to calculate the trajectory, and the control execution module is used to control the vehicle to travel along the trajectory. In this case, the multiple modules can be set up separately in different devices or integrated into one device.

[0087] In some cases, vehicle 10 may also include one or more of the following: powertrain 11, braking system 12, interactive control device 15, interactive equipment 16, etc. These components are described below:

[0088] The drive system 11 provides power to the vehicle 10, enabling the vehicle 10 to move. For example, the drive system 11 includes one or more of the following: an engine, a power battery, etc.

[0089] Braking system 12 can represent a device for slowing down the vehicle 10, and may also be referred to as a braking device. It may include a speed reducer or other structural components used for vehicle deceleration. In some embodiments, braking system 12 may utilize friction to slow the movement of the wheels, thereby reducing the vehicle's speed.

[0090] Interactive device 16 is a device used for human interaction and may include several components, such as one or more of display device 161, projection system 162, and voice system 163. Display device 161 is a device capable of presenting information and enabling human-machine interaction, including but not limited to a vehicle central control screen, passenger-side screen, rear-seat screen, streaming rearview mirror, instrument panel, head-up display (HUD), light field screen, or touchscreen. In some solutions, modules or devices that implement similar functions may also be called human-machine interaction (HMI) devices.

[0091] The projection system 162 includes a projection module, which is a device with projection capabilities capable of projecting images (including video) into an object space. For example, the projection module may include a projection lens, and optionally a processor connected to the projection lens, which acquires the projected image and controls the projection lens to project. In some possible implementations, referring to Figure 2, the projection module may be located at the vehicle's headlight position. Exemplarily, the projection module can be integrated with the headlights; that is, the headlights can function as a projection module to project images. Of course, this application also applies to cases where the projection module is independent of the headlights.

[0092] The voice system 163 is used to acquire and / or output sound. For example, the voice system may include or be connected to a microphone. Furthermore, the voice system may also include a speaker for emitting sound. Further, the voice system can interact with a user, such as receiving voice input from the user (e.g., acquiring voice within the cockpit), and / or providing voice prompts to the user.

[0093] The interactive control device 15 is a computing-capable device capable of presenting information to a user or receiving user input via one or more interactive devices 16. For example, the interactive control device can provide a projected image to the projection system 162, causing the projection module to project the corresponding image. Furthermore, the interactive control device can display information such as vehicle speed, function activation status, obstacles, and movement trajectory via a display device. Additionally, the interactive device can control a voice system to output specific voice prompts.

[0094] In some embodiments, the interactive control device 15 may include one or more processors, which can be used to run programs or instructions corresponding to programs to implement corresponding functions. Please refer to the foregoing description of processors. For example, the interactive control device 15 is a CDC (Controller Center), or it may be a controller in a projection system or a controller in a display device, etc.

[0095] Optionally, referring to Figure 2, the vehicle control device 14 and the interactive control device 15 are connected. The vehicle control device 14 can provide interactive information to the interactive control device, and the interactive control device 15 controls the interactive device 16 to output prompts related to the interactive information. For example, the vehicle control device can calculate the movement trajectory of the vehicle 10 and provide the trajectory information to the interactive control device 15, which then prompts the user about the movement trajectory of the vehicle 10 through interface display, projection, voice output, or other means.

[0096] Alternatively, the vehicle control device 14 can also directly control the interactive device 16 to output prompts related to the interactive information. For example, the vehicle control device can calculate the trajectory of the vehicle 10 and prompt the user about the trajectory of the vehicle 10 through interface display, projection, voice output, etc.

[0097] In some designs, the vehicle also includes a memory to provide storage space. For example, the memory may include volatile memory, such as RAM. Alternatively, the memory may include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD). Combinations of these types of memory are also possible. Optionally, the memory may also store information such as road maps, driving routes, and sensor data.

[0098] It should be noted that Figure 1 above is only a schematic diagram of one possible functional framework for vehicle 10. In practical applications, vehicle 10 may include more or fewer systems or components, which is not limited here. For example, vehicle 10 may also include a power supply or a communication system, etc.

[0099] Vehicles frequently encounter oncoming traffic while driving, and safely navigating these situations is a key challenge in designing intelligent driving systems. Some solutions employ rule-based methods, first determining which environmental conditions are met and then deriving a driving strategy based on those conditions. However, in this approach, each condition is tailored to a specific situation, making it difficult to guarantee that the resulting trajectory is globally optimal. Furthermore, given the numerous dimensions of scenarios during vehicle operation, this solution lacks flexibility and is difficult to upgrade. Other solutions, to allow oncoming vehicles to pass smoothly, first guide the vehicle to the edge of the road. This approach increases the safety risk to the vehicle itself and results in a poor user experience.

[0100] In view of this, embodiments of this application provide a vehicle control method and related products that can improve the safety and comfort of oncoming traffic trajectories in oncoming traffic scenarios, improve traffic efficiency, and make the decision-making process and results more human-like and intelligent.

[0101] The vehicle control method provided in the embodiments of this application will be introduced below. Please refer to Figure 3, which is a schematic flowchart of a vehicle control method provided in the embodiments of this application. Optionally, the method is applied to a vehicle control device, such as the vehicle control device 14 shown in Figures 1 and 2. For ease of description, the following description will take the vehicle control device as the executing entity.

[0102] The vehicle control method shown in Figure 3 includes one or more steps from S301 to S303. It should be understood that, for ease of description, the method is described in the order of S301 to S303, but this embodiment does not limit the order of execution, the execution time, or the number of executions of the above one or more steps. S301 to S303 are as follows:

[0103] S301, the vehicle control device plans multiple alternative motion trajectories based on the motion information and perception data of the first vehicle.

[0104] The vehicle control unit is a computing device, such as an MDC or ECU. The first vehicle represents a mobile terminal, such as the vehicle shown in Figure 1 or Figure 2. Alternatively, the first vehicle can be replaced by a mobile robot, logistics vehicle, etc.

[0105] The motion information of the first vehicle describes information related to its motion. This motion information may include one or more of the following: vehicle speed, trajectory, acceleration, position, heading angle, trajectory point, curvature, radius of curvature, steering angle, or navigation information. Furthermore, the motion information may include data indicating the aforementioned information and / or data used to obtain that information. For example, the vehicle speed can be calculated from its wheel speeds, so the motion information of the first vehicle may include wheel speeds. In some cases, the motion information of the first vehicle includes not only its current motion information (or motion state data) but also its future motion information (or motion prediction data), where the future motion information can be predicted and / or planned.

[0106] Perception data is data used to describe the perception of the environment. For example, perception data includes static environmental data and obstacle information. Static environmental data includes road information, such as information on static road elements, including the position and shape of boundary lines, the position and shape of lane lines, road width, speed limits, and one or more other locations. Obstacle information includes obstacle motion information, such as obstacle speed, trajectory, acceleration, position (e.g., distance from the first vehicle), heading angle, trajectory point, curvature, radius of curvature, turning angle, and one or more other information. Similarly, obstacle motion information may include current motion information (or motion state data) and future motion information (or motion prediction data), such as future trajectory, which can be predicted. Optionally, obstacle information may also include obstacle size, type, and location.

[0107] Optionally, the perception data is acquired by a sensor system, or it is data obtained after processing the data acquired by the sensor system. For example, after the data acquired by the sensors is input into the vehicle control device, the vehicle control device (including, for example, a preprocessing module) preprocesses this information to obtain perception data, which includes motion information of the first vehicle, information on static road elements, and information on obstacles. The aforementioned sensor system may include one or more of radar, cameras, lidar, etc.

[0108] In one possible implementation, the perception data includes road information of a first road and motion information of a target obstacle. Exemplarily, the road information of the first road includes the boundary of the first road. The target obstacle is an obstacle in the environment, and its direction of movement is opposite to the direction of movement of the first vehicle; therefore, the target obstacle and the first vehicle will intersect. Exemplarily, referring to Figure 3, the target obstacle's movement traverses the first road, and the first vehicle's movement also traverses the first road (e.g., the first vehicle's navigation route traverses the first road), and the target obstacle's direction of movement on the first road is opposite to the first vehicle's direction of movement on the first road. That is, the target obstacle is an obstacle traveling towards the first vehicle, and the vehicle will interact with the target obstacle on the first road. Further, the trajectory of the first vehicle and the trajectory of the target obstacle are located within the boundary of the first road, or the movement of the first vehicle and the movement of the target obstacle interact within a closed area of ​​the first road.

[0109] Optionally, the perception data also includes information about other obstacles in the environment, which are obstacles other than the target obstacle.

[0110] In one embodiment, the target obstacle is a vehicle, such as a second vehicle. In another embodiment, the target obstacle is an object that meets preset conditions (including living objects), such as an object that meets preset size conditions, or an object in motion, or an object that meets preset size conditions and has the ability to move (currently possibly stationary or in motion), or an object of a preset type, such as a vehicle or a person. Exemplarily, size conditions include related conditions such as length, width, height, volume, and cross-sectional area. For example, preset size conditions include at least one of a length greater than or equal to a first length, a width greater than or equal to a first width, or a height greater than or equal to a first height. The values ​​of the first length, first width, and first height can be predefined or flexibly determined.

[0111] The alternative trajectory is a trajectory planned by the vehicle control device, indicating the vehicle's meeting trajectory and optionally also indicating the desired trajectory of the target obstacle. The alternative trajectory passes through the first road, and each alternative trajectory corresponds to an alternative meeting area.

[0112] Furthermore, the alternative intersection areas corresponding to the multiple alternative motion trajectories are different. Please refer to Figure 5, which is a schematic diagram of two alternative motion trajectories provided in an embodiment of this application. One alternative motion trajectory (i.e., T1) is shown in Figure 5(a). If the first vehicle travels according to this alternative motion trajectory T1, it may intersect with the target obstacle in the alternative intersection area R1. Similarly, another alternative motion trajectory (i.e., T2) is shown in Figure 5(b). If the first vehicle travels according to this alternative motion trajectory T2, it may intersect with the target obstacle in the alternative intersection area R2.

[0113] Optionally, there are two scenarios where the candidate intersection areas corresponding to multiple candidate motion trajectories are different: Scenario 1: At least one candidate motion trajectory corresponds to a different candidate intersection area than the other candidate motion trajectories. In this case, some candidate motion trajectories may have the same candidate intersection area. Scenario 2: The candidate intersection areas corresponding to multiple candidate motion trajectories are all different. In this case, there are no candidate motion trajectories with the same candidate intersection area among the multiple motion trajectories.

[0114] In some possible implementations, the vehicle control device samples multiple candidate intersection areas within the encounter area between the first vehicle and the target obstacle on the first road. Based on the motion information of the first vehicle, perception data, and information from the multiple candidate intersection areas, it obtains multiple candidate motion trajectories. The candidate intersection areas are the possible intersection areas between the vehicle and the target obstacle, essentially assuming multiple possible intersection areas. Referring to Figure 6, the vehicle control device obtains n candidate intersection areas within the encounter area by sampling, where n is an integer and n≥2.

[0115] Furthermore, based on the motion information and perception data of the first vehicle, the vehicle control device plans a motion trajectory using multiple alternative meeting areas as the intersection areas between the first vehicle and the target obstacle, resulting in multiple alternative motion trajectories. In other words, the vehicle control device plans multiple alternative motion trajectories using the positions of these hypothetical meeting areas, each alternative motion trajectory enabling the first vehicle and the target obstacle to meet within a corresponding alternative meeting area. For example, using alternative intersection area #1 out of n alternative areas as the intersection area, one (or more) alternative motion trajectories are planned. If the first vehicle travels according to this alternative motion trajectory, it may meet the target obstacle in alternative intersection area #1.

[0116] In some possible implementations, when sampling the meeting area, the vehicle control device samples along the longitudinal direction of the first road at a first sampling interval to obtain multiple candidate meeting areas. Here, longitudinal refers to the direction along the road centerline. In road engineering and related fields, longitudinal and lateral are commonly used terms to describe the different directional characteristics of a road. Longitudinal refers to the length direction of the road, and lateral refers to the direction perpendicular to the road centerline, i.e., the width direction of the road. Referring to Figure 4, the y-direction is the longitudinal direction of the road, and the x-direction is the lateral direction. The first sampling interval is used to indicate the interval between the sampled candidate meeting areas. It can be designed as a relative interval or an absolute interval. Here, the interval can be the interval between the edges of the meeting areas or the interval between the centers of the meeting areas. In one case using a relative interval, the number n or the sampling interval can be pre-designed. For example, if n candidate meeting areas are sampled, the interval between the candidate meeting areas is 1 / (n-1) of the maximum spacing. For example, if the sampling interval is 1 / 3, it means that 4 candidate meeting areas are sampled. In one case where an absolute interval is used, the distance between two candidate meeting areas (i.e., Δd as shown in Figure 7) is a fixed length. For example, if the sampling interval is 2 meters (m), then each 2-meter interval forms a candidate meeting area.

[0117] Vehicle control devices can plan trajectories using one or more methods, such as optimization-based algorithms, search-based algorithms, or geometry-based algorithms. Optimization-based algorithms include, for example, the joint optimization algorithm described below. Search-based algorithms include, for example, Dijkstra's algorithm. Geometry-based trajectory planning algorithms include, for example, the velocity obstacles (VO) algorithm.

[0118] In some possible implementations, the vehicle control device performs trajectory planning through a combined lateral and longitudinal optimization approach. As one possible implementation, the vehicle control device employs combined lateral and longitudinal planning, first guiding the vehicle and the target obstacle longitudinally to the intersection area, and then optimizing laterally to satisfy obstacle avoidance constraints, road constraints, etc., to plan the trajectory of the first vehicle and the target obstacle. The following explanation uses the process of planning the trajectory with a first alternative intersection area as the intersection area as an example. The vehicle control device uses the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first alternative intersection area to obtain the first longitudinal trajectory. The vehicle control device then uses the motion information of the first vehicle, perception data, and the first longitudinal trajectory to optimize and obtain the first alternative trajectory.

[0119] As an example of longitudinal planning, the vehicle control device solves a first optimization problem based on the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first candidate intersection area to obtain a first longitudinal trajectory. Exemplarily, the first optimization problem is established based on first trajectory-related parameters, including the position of the first candidate area, the velocity and reference velocity of the first vehicle at the i-th trajectory point, the acceleration of the first vehicle at the i-th trajectory point, the jerk (reciprocal of the acceleration) of the first vehicle at the i-th trajectory point, the velocity and reference velocity of the target obstacle at the i-th trajectory point, the acceleration of the target obstacle at the i-th trajectory point, and the jerk of the target obstacle at the i-th trajectory point, where i is a positive integer. Optimization can yield the trajectory that best meets expectations, such as the trajectory with the lowest cost. An exemplary calculation method can be found in the formula for the aforementioned first optimization problem.

[0120] Please refer to Figure 7, which is a schematic diagram of two longitudinal trajectories provided in the embodiments of this application. As shown in part (a) of Figure 7, the vehicle control device uses the alternative meeting area R1 as the meeting area and performs longitudinal (e.g., y-direction) trajectory planning. The purpose is to first guide the vehicle and the target obstacle to the alternative meeting area R1 in the longitudinal direction. Similarly, as shown in part (b) of Figure 7, the vehicle control device uses the alternative meeting area R2 as the meeting area and performs longitudinal trajectory planning.

[0121] As an example of a lateral planning approach, the vehicle control device solves a second optimization problem based on the motion information, perception data, and first longitudinal trajectory of the first vehicle to obtain a first alternative motion trajectory.

[0122] Exemplarily, the first optimization problem is established based on second trajectory-related parameters, which include a first longitudinal trajectory, the lateral position of the first vehicle at the j-th trajectory point, the longitudinal position of the first vehicle at the j-th trajectory point, the heading angle of the first vehicle at the j-th trajectory point, the curvature of the first vehicle at the j-th trajectory point, the rate of change of curvature of the first vehicle at the j-th trajectory point, the acceleration of the first vehicle at the j-th trajectory point, the lateral position of the target obstacle at the j-th trajectory point, the longitudinal position of the target obstacle at the j-th trajectory point, the heading angle of the target obstacle at the j-th trajectory point, the curvature of the target obstacle at the j-th trajectory point, the rate of change of curvature of the target obstacle at the j-th trajectory point, the acceleration of the target obstacle at the j-th trajectory point, obstacle avoidance constraints for the first vehicle and the target obstacle, and road boundary constraints for the first vehicle and the target obstacle. In some cases, the number of obstacle avoidance constraints is related to the number of other obstacles. When there are multiple other obstacles in the environment, multiple obstacle avoidance constraints may be formed. An exemplary calculation method can be found in the formula of the aforementioned second optimization problem.

[0123] For example, in conjunction with Figures 7 and 5, when the longitudinal movement of the two vehicles (i.e., Figure 7) is determined, the vehicle control device considers the constraints of surrounding environmental obstacles, road boundaries, and the obstacle avoidance half-space constraints between the two vehicles, and solves for the optimal obstacle avoidance trajectory between the two vehicles, forming an alternative motion trajectory (as shown in Figure 5).

[0124] The aforementioned section also mentioned the encounter zone, which refers to the area where the first vehicle and the target obstacle meet. All alternative intersection areas corresponding to multiple alternative trajectories fall within this encounter zone. Below are two possible designs for the encounter zone:

[0125] Design 1: The vehicle control device can take into account the kinematic constraints of the first vehicle and the target obstacle, and determine the encounter boundary from the interaction range of the first vehicle and the target obstacle, thereby obtaining the encounter area.

[0126] For example, referring to Figure 8, the encounter area includes a first boundary (i.e., boundary 1) and a second boundary (i.e., boundary 2) that are opposite each other in the longitudinal direction of the first road. The first boundary corresponds to the maximum acceleration of the first vehicle and the maximum deceleration of the target obstacle, and the second boundary corresponds to the maximum deceleration of the first vehicle and the maximum acceleration of the target obstacle.

[0127] As one possible implementation, the vehicle control device determines the interaction range between the first vehicle and the target obstacle based on the first vehicle's trajectory and the predicted trajectory of the target obstacle. For example, the vehicle control device determines a section of the path where interaction may occur on the vehicle's navigation path and the predicted path of the other vehicle; this path is the interaction range. Further, the vehicle control device determines the encounter area between the first vehicle and the target obstacle based on the speed, maximum acceleration, and maximum deceleration of the first vehicle, and the speed, maximum acceleration, and maximum deceleration of the target obstacle. Here, the first vehicle's trajectory, speed, maximum acceleration, and maximum deceleration are considered the first vehicle's motion information, while the target obstacle's predicted trajectory, speed, maximum acceleration, and maximum deceleration are considered the target obstacle's motion information.

[0128] Design 2: The encounter area can be defined as the area between the first vehicle and the target obstacle, as shown in Figure 6. The area between the part of the first vehicle that is close to the target obstacle and the part of the target obstacle that is close to the first vehicle can be used as the encounter area.

[0129] Of course, other methods and / or other parameters may be used to calculate the encounter area during the specific implementation process, and this application does not impose strict limitations on this.

[0130] S302, the vehicle control device determines the target motion trajectory based on multiple alternative motion trajectories.

[0131] The target trajectory is used to indicate the passing trajectory of the first vehicle. For example, referring to Figure 5, if the alternative trajectory T1 is used as the target trajectory, the passing trajectory of the first vehicle is shown in part (a) of Figure 5. If the alternative trajectory T1 is used as the target trajectory, the passing trajectory of the first vehicle is shown in part (b) of Figure 5. Furthermore, the target trajectory also includes the expected trajectory of the target obstacle.

[0132] In some cases, the target trajectory is one of several alternative trajectories. In this situation, the vehicle control unit can select one trajectory from the multiple alternatives as the target trajectory. For example, the vehicle control unit selects the optimal trajectory as the target trajectory based on factors such as safety, comfort, and traffic efficiency.

[0133] In one possible implementation, the vehicle control device determines the target trajectory based on evaluation data from multiple alternative trajectories. Exemplarily, the evaluation data is associated with at least one of a safety cost parameter, an efficiency cost parameter, and a comfort cost parameter, where the safety cost parameter indicates the safety of the trajectory, the efficiency cost parameter indicates the communication efficiency of the trajectory, and the comfort cost parameter indicates the comfort of the trajectory.

[0134] For example, one method for calculating evaluation data is as follows: cost total =w safe cost safe +w efficient cost efficient +w comfort cost comfort

[0135] Among them, cost total This represents the total cost and is part of the evaluation data. safe This represents the weight of the security cost parameter. safe The safety cost parameter can be calculated from one or more of the following: distance between the vehicle and the target obstacle, speed, relative speed, distance between the vehicle and the road boundary, distance between the target obstacle and the road boundary, distance between the vehicle and other obstacles, or distance between the target obstacle and other obstacles. efficient This represents the weight of the efficiency cost parameter. efficient The efficiency cost parameter can be calculated from one or more of the following: trajectory travel time, whether the vehicle and the target obstacle need to stop and yield. comfort This represents the weight of the comfort cost parameter. comfortThe comfort cost parameter can be calculated from one or more of the following during the rendezvous process: acceleration, deceleration, yaw rate, etc.

[0136] In some cases, the target trajectory may not belong to multiple trajectories. For example, when the total cost of multiple trajectories fails to meet the preset cost condition, a new trajectory may be obtained through optimization. Alternatively, the target trajectory can be further optimized using one or more existing trajectories to obtain the final trajectory.

[0137] In some possible implementations, the target motion trajectory is used to prompt the human driver, i.e., displayed on an interface (such as a HUD or a large screen), indicating what kind of motion trajectory the human driver can use to pass through oncoming traffic.

[0138] In some other possible implementations, the first vehicle is currently in a state where the intelligent driving system is activated, at which time the vehicle control device can control the vehicle to drive along the trajectory indicated by the target motion trajectory.

[0139] Optionally, the vehicle control method also includes S303, as follows:

[0140] S303, the vehicle control device controls the first vehicle to travel along the passing trajectory of the first vehicle.

[0141] In the above scenario, the vehicle control device has the ability to control the vehicle, specifically to control the first vehicle to travel along the indicated meeting trajectory in the target motion path. For example, the vehicle control device can issue control commands to the power system, steering system, etc., to control the first vehicle to travel along the planned route.

[0142] Furthermore, the alternative intersection area corresponding to the target trajectory is the target intersection area. If the first vehicle travels according to the target intersection area, the first vehicle may interact with the target obstacle within the target intersection area. Of course, the target intersection area here is planned and under ideal conditions. In actual implementation, since the trajectory of the target obstacle is not controlled by the vehicle control device, the final intersection area may not be exactly the same as the target intersection area.

[0143] In some possible implementations, the vehicle is equipped with an intelligent driving system, and this system is activated. In this case, the vehicle control unit can control the vehicle's movement according to a planned trajectory.

[0144] In some cases, vehicle control devices can provide information such as driving trajectory, interaction area, vehicle position, and target obstacles through a human-machine interface (HMI) or projection. This allows users to be informed of vehicle-related information, enabling them to understand their surroundings and / or make driving decisions in a timely manner, reducing user anxiety and improving the user experience. Two possible interaction designs are described below:

[0145] Interaction Design 1: Interact through the user interface, display the user interface through a display device, and present interactive information on the user interface.

[0146] In one possible implementation, the vehicle control device displays a first interface. The first interface includes prompts indicating one or more of the following: driving trajectory, interaction area, vehicle position, target obstacles, etc.

[0147] For example, please refer to part (a) of Figure 9, where the display screen in the vehicle can display interface 90. As shown in part (b) of Figure 9, interface 90 includes one or more of the following prompts: target obstacle prompt 901, first prompt 902, second prompt 903, third prompt 904, fourth prompt 905, fifth prompt 906, or sixth prompt 907, etc. Among them, target obstacle prompt 901 is used to indicate that the target obstacle is a meeting object; for example, the obstacle can be selected by drawing a box, or the obstacle can be displayed using a special color, or the target obstacle can be marked with text or symbols. First prompt 902 is used to indicate the target meeting area; first prompt 902 may include an image, and optionally also text, symbols, etc. Second prompt 903 is used to indicate a first area within the target meeting area; the first area indicates the position occupied by the first vehicle when the first vehicle and the target vehicle are aligned. Second prompt 903 may include an image, and optionally also text, symbols, etc. The third prompt 904 indicates the second area within the target intersection zone, which indicates the position of the target obstacle when the first vehicle aligns with it. The fourth prompt 905 indicates the passing trajectory of the first vehicle, which can be represented by driving lines, arrows, or other directional graphics. The fifth prompt 906 indicates the expected trajectory of the target obstacle, indicated by the target obstacle's trajectory, which can also be represented by driving lines, arrows, or other directional graphics.

[0148] In some other possible implementations, the vehicle control device displays a second interface via a physical interface. The second interface includes information on multiple alternative motion trajectories. Please refer to Figure 10, which is a schematic diagram of an interface provided in an embodiment of this application. The second interface 100 includes multiple display areas, wherein display area 1001 is used to display one alternative motion trajectory, and display area 1002 is used to display another alternative motion trajectory. Of course, the second interface can have more display areas to display more alternative motion trajectories.

[0149] In some cases, the target motion trajectory and other alternative motion trajectories can be displayed using different display styles. For example, referring to Figure 10, the target motion trajectory, i.e., the trajectory in display area 1001, is highlighted, such as by highlighting, bolding, or displaying a large area. Other motion trajectories that are not the target motion trajectory, such as the trajectory in display area 1002, are not highlighted, such as by reducing brightness, displaying in grayscale, or displaying in a small area.

[0150] In some solutions, the vehicle control device also supports trajectory switching. For example, the user can select one trajectory from multiple alternative trajectories for driving. In this case, a selection control 1003 can be set in the second interface to receive the user's selection operation for a certain alternative trajectory. Accordingly, the vehicle control device receives the user's selection operation and uses the selected alternative trajectory as the target trajectory.

[0151] Interaction Design 2: Interaction is achieved through projected images. An image is projected using a projection module, and interactive information is presented in the projected image.

[0152] In one possible implementation, the vehicle control device projects a first image via a projection module. The first interface includes prompts indicating one or more of the following: driving trajectory, interactive area, vehicle position, target obstacle, etc.

[0153] For example, the first image includes one or more of the following cue patterns: a first cue pattern, a second cue pattern, a third cue pattern, a fourth cue pattern, a fifth cue pattern, or a sixth cue pattern, etc. The first cue pattern is used to indicate the target intersection area. The second cue pattern is used to indicate a first area within the target intersection area, which indicates the position occupied by the first vehicle when it aligns with the target vehicle. The third cue pattern is used to indicate a second area within the target intersection area, which indicates the position occupied by the target obstacle when it aligns with the first vehicle. The fourth cue pattern is used to indicate the passing trajectory of the first vehicle. The fifth cue pattern is used to indicate the expected movement trajectory of the target obstacle, which is indicated by the target movement trajectory. The sixth cue pattern is used to indicate the passage order of the first vehicle and / or the target obstacle, the passage order being related to the target movement trajectory.

[0154] In some cases, when projecting the first image, the projection area of ​​the first image is the path area traveled by the vehicle (i.e., the vehicle's lane). As shown in part (a) or (b) of Figure 11, the first image includes one or more of a first warning pattern, a second warning pattern, a fourth warning pattern, and a sixth warning pattern. The first warning pattern indicates the vehicle's lane portion of the target intersection area. Similarly, the other warning patterns are also compressed into the path area traveled by the vehicle.

[0155] In some other cases, when projecting the first pattern, the projection area of ​​the first image may include the path area traveled by the vehicle and the path area traveled by the target obstacle. As shown in part (a) or part (b) of Figure 12, the first image includes one or more of the following: a first prompt pattern, a second prompt pattern, a third prompt pattern, a fourth prompt pattern, a fifth prompt pattern, or a sixth prompt pattern.

[0156] It should be understood that the collection, use, storage, and display of information (or data) in this application are all designed to comply with the scope permitted by the laws and regulations of the region where the vehicle control device is located.

[0157] Optionally, the vehicle also includes a projection system, which can generate a first image and provide it to a projection module in the projection system for projection.

[0158] Alternatively, the projection system includes a controller. The vehicle control device can provide projection information to the controller in the projection system, enabling the controller to generate a first image based on the projection information and project the first image using a projection module. The projection information may include one or more of the following: information about the target's motion trajectory, information about the target's intersection area, information about a first area, information about a second area, information about target obstacles, etc. For example, referring to Figure 1, the controller can be an interactive control device in the vehicle. More exemplarily, the controller can be integrated with the projection module, for example, by being installed in the vehicle's headlights.

[0159] In the embodiment shown in Figure 3, when there are oncoming traffic participants (i.e., target obstacles), the vehicle control device plans multiple trajectories with different intersection areas based on the vehicle's motion information and environmental perception data, and then decides on the optimal trajectory. This multi-trajectory parallel planning scheme, when facing oncoming traffic, can determine the optimal return trajectory from multiple trajectories with different intersection areas, improving the safety and comfort of oncoming traffic, increasing traffic efficiency, and enhancing the passenger experience. Furthermore, the vehicle control device observes key points, estimates multiple oncoming traffic areas, plans trajectories for each of these areas, and then makes a decision; this decision-making process and result are more human-like and intelligent.

[0160] The foregoing has described the application scenarios and methods provided by the embodiments of this application. The apparatus of the embodiments of this application is provided below. It is understood that the various apparatuses provided in the embodiments of this application, such as interactive devices, computing devices, chips, etc., include hardware structures, software units, or combinations of hardware and software structures to perform the functions described in the above method embodiments. Those skilled in the art should readily recognize that the apparatus and modules within it can be implemented in hardware or a combination of hardware and computer software in conjunction with the various functions described in the embodiments disclosed herein. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different apparatus implementations in different application scenarios to implement the aforementioned method embodiments, and different implementations of the apparatus should not be considered beyond the scope of the embodiments of this application.

[0161] Several possible devices are listed below.

[0162] Please refer to Figure 13, which is a schematic diagram of a vehicle control device provided in an embodiment of this application. The vehicle control device 140 includes a processing unit 1401, and optionally also includes a control unit 1402. The vehicle control device 140 can be an independent device, or it can be a software module and / or hardware module in an independent device, such as a chip or a computer program.

[0163] The vehicle control device 140 is used to implement the aforementioned vehicle control method, such as the method executed by the vehicle control device in the embodiment shown in FIG3 and its possible implementations. The processing unit 1401 is used to process data and perform operations, such as implementing one or more of the aforementioned operations such as planning, determining, sampling, obtaining data, and solving. The control unit 1402 is used to control the vehicle, for example, outputting control information, such as a trajectory, or outputting control commands, such as outputting commands to control the powertrain and steering system based on the trajectory.

[0164] In one possible implementation, the processing unit 1401 is configured to plan multiple alternative motion trajectories along the first road based on the motion information and perception data of the first vehicle, and determine a target motion trajectory based on the multiple alternative motion trajectories. This target motion trajectory is used to indicate the passing trajectory of the first vehicle.

[0165] Furthermore, when the vehicle control device 140 includes a control unit 1402, the control unit 1402 is used to control the first vehicle to travel along the first vehicle's meeting trajectory, so that the first vehicle and the target obstacle meet in the target meeting area.

[0166] In another possible implementation, the processing unit 1401 is further configured to sample multiple candidate intersection areas within the encounter area between the first vehicle and the target obstacle on the first road, and obtain multiple candidate motion trajectories based on the motion information of the first vehicle, the perception data and the information of the multiple candidate intersection areas.

[0167] In another possible implementation, the processing unit 1401 is further configured to sample along the longitudinal direction of the first road at a first sampling interval within the encounter area to obtain a plurality of candidate intersection areas.

[0168] In another possible implementation, the processing unit 1401 is further configured to obtain a first longitudinal trajectory using the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first alternative intersection area, and to optimize and obtain a first alternative motion trajectory using the motion information of the first vehicle, the perception data, and the first longitudinal trajectory, wherein the first alternative motion trajectory belongs to multiple alternative motion trajectories.

[0169] In another possible implementation, the processing unit 1401 is further configured to solve a first optimization problem based on the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first alternative intersection area, to obtain a first longitudinal trajectory.

[0170] In another possible implementation, the processing unit 1401 is further configured to solve a second optimization problem based on the motion information of the first vehicle, the perception data, and the first longitudinal trajectory, to obtain a first alternative motion trajectory.

[0171] In another possible implementation, the processing unit 1401 is further configured to determine the encounter area between the first vehicle and the target obstacle based on the motion information of the first vehicle and the motion information of the target obstacle.

[0172] In another possible implementation, the processing unit 1401 is further configured to determine the interaction range between the first vehicle and the target obstacle based on the movement path of the first vehicle and the predicted movement path of the target obstacle, and to determine the encounter area between the first vehicle and the target obstacle based on the speed of the first vehicle, the maximum acceleration and the maximum deceleration of the first vehicle, and the speed of the target obstacle, the maximum acceleration and the maximum deceleration of the target obstacle.

[0173] In another possible implementation, the processing unit 1401 is further configured to determine the target motion trajectory based on evaluation data of multiple alternative motion trajectories.

[0174] In another possible implementation, the control unit 1402 is also used to display a first interface through an interface, the first interface including one or more of the following prompt information: prompt information of the target obstacle, first prompt information, second prompt information, third prompt information, fourth prompt information, fifth prompt information, or sixth prompt information, etc.

[0175] In another possible implementation, the control unit 1402 is further configured to project a first image via a projection module. The first image includes one or more of the following prompt patterns: a first prompt pattern, a second prompt pattern, a third prompt pattern, a fourth prompt pattern, a fifth prompt pattern, or a sixth prompt pattern, etc.

[0176] The specific operations performed by the vehicle control operation can be found in the descriptions of the foregoing embodiments, such as the description in the method embodiment shown in FIG3.

[0177] Figure 14 shows a schematic diagram of a vehicle control device provided in an embodiment of this application. The vehicle control device 14 is a device with computing capabilities; this device can be a physical device, such as an embedded device. Optionally, the vehicle control device 14 can be included in a vehicle, for example, as an on-board component in the vehicle 10 shown in Figure 2.

[0178] As shown in Figure 14, the vehicle control device 14 includes a processor 141 and a memory 142. Optionally, the vehicle control device 14 may also include one or more of a connection line 144, a communication interface 143, etc., for example, the processor 141 and the memory 142 communicate with each other via the connection line 144. It should be understood that this application does not limit the number of processors and memories in the vehicle control device 14.

[0179] Memory 142 provides storage space for computer programs or data. Memory 142 may include volatile memory, such as random access memory (RAM). Memory 142 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0180] Processor 141 is a module for performing calculations and may include any one or more of the following: controller, central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), digital signal processor (DSP), coprocessor (to assist the central processing unit in completing corresponding processing and applications), application-specific integrated circuit (ASIC), microcontroller unit (MCU), virtual machine, container, etc.

[0181] The communication interface 143 is used to provide information input or output to at least one processor, such as an in-line interface, an out-of-line interface, etc. And / or, the communication interface 143 can be used to receive externally transmitted data and / or transmit data externally. The communication interface 143 can be a wired link interface, including an Ethernet cable, or a wireless link interface (Wi-Fi, Bluetooth, general wireless transmission, and other wireless communication technologies, etc.). Optionally, the communication interface 143 may also include a transmitter (such as a radio frequency transmitter, antenna, etc.) or a receiver coupled to the interface.

[0182] The connection line 144 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one line is used in Figure 14, but this does not imply that there is only one bus or one type of bus. The connection line 144 can include pathways for transmitting information between various components of the vehicle control unit 14 (e.g., memory 142, processor 141, communication interface 143).

[0183] In one possible implementation, memory 142 stores executable instructions, and processor 141 executes the executable instructions to implement the aforementioned vehicle control method, such as the method executed by the vehicle control device in the embodiment shown in FIG3 and its possible implementation methods.

[0184] This application also provides a chip, including a processor and a communication interface. The communication interface is used for outputting and / or outputting data (including instructions), and / or for receiving and / or sending data. When the processor executes program instructions in memory, it performs the aforementioned vehicle control method, for example, implementing the method in the embodiment shown in FIG3.

[0185] This application also provides a vehicle control system, including a vehicle control device and a projection system. The vehicle control device is connected to the projection system, which includes a projection module. The vehicle control device is used to implement the method described in the first aspect or any possible implementation of the first aspect, so that the projection module projects a first image.

[0186] Optionally, the projection system may include an interactive control device and a projection module. The vehicle control device may provide projection information to the interactive control device, enabling the interactive control device to generate a first image based on the projection information and project the first image using the projection module. The projection information may include one or more of the following: information on the target's motion trajectory, information on the target's intersection area, information on the first area, information on the second area, and information on target obstacles.

[0187] Furthermore, the interactive control device and the projection module can be installed separately. Alternatively, the interactive control device and the projection module can be integrated together, for example, integrated into the vehicle's headlights.

[0188] Alternatively, the vehicle control unit can control the projection module, in which case the vehicle control unit can generate a first image and control the projection module to project the first image.

[0189] This application also provides a computer-readable storage medium storing instructions that, when executed by at least one processor, implement the aforementioned vehicle control method, such as the method in the embodiment shown in FIG3. The computer-readable storage medium can be any available medium capable of being stored by a computing device, or a data storage device such as a data center containing one or more available media. The computer-readable storage medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive).

[0190] This application provides a computer program product including computer instructions that, when executed on at least one processor, implement the aforementioned vehicle control method, such as the method in the embodiment shown in FIG3. Optionally, the computer program product may be a software installation package or an image package. When the aforementioned method is required, the computer program product can be downloaded and executed on a computing device.

[0191] This application provides a vehicle that includes the aforementioned vehicle control device 14, or the vehicle includes the aforementioned vehicle control system, or the vehicle includes the aforementioned chip, or the vehicle includes the aforementioned computer storage medium, or the vehicle is equipped with the aforementioned computer program product.

[0192] In addition, a few additional points need to be made regarding this application:

[0193] 1. Unless otherwise stated, “multiple” means two or more.

[0194] 2. Unless otherwise specified or in case of logical conflict, the terms and / or descriptions in different embodiments of this application are consistent and can be referenced in each other. The technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0195] III. The various numerical designations used in this application are merely for descriptive convenience and are not intended to limit the scope of protection of this application. The magnitude of the serial numbers used in this application does not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic. For example, the terms "first," "second," "third," "fourth," and other various terminology (if present) in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein.

[0196] Furthermore, any embodiment or design described in this application as "exemplary" or "for example" should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0197] IV. The terms “comprising” and “having” and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are expressly listed, but may include other steps or units that are not expressly listed or that are inherent to such process, method, product or device.

[0198] V. In this application, "for indicating" can be understood as "enabling". "Enabling" can include direct enabling and indirect enabling. When describing information for enabling A, it can include whether the information directly enables A or indirectly enables A, but it does not mean that the information necessarily carries A.

[0199] The information that enables the information is called the information to be enabled. In the specific implementation process, there are many ways to enable the information to be enabled, such as, but not limited to, directly enabling the information to be enabled, such as the information to be enabled itself or its index. It can also be indirectly enabled by enabling other information, where there is a relationship between the other information and the information to be enabled. It can also enable only a part of the information to be enabled, while the other parts are known or pre-agreed upon. For example, enabling specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing enabling overhead to some extent. Simultaneously, common parts of various pieces of information can be identified and enabled uniformly to reduce the enabling overhead caused by individually enabling the same information.

[0200] VI. In this application, "predefined" may include preconfiguration. For example, predefining certain information means that the information is calculated or received in advance before performing an action that uses the information. The "predefined" can be implemented by pre-storing corresponding codes, tables, or other means that can be used to indicate relevant information in the device (e.g., in a controller or vehicle). This application does not limit the specific implementation method.

[0201] VII. The term "storage" or "preservation" in this application can refer to storage in one or more memory devices. These memory devices can be separately configured or integrated into an encoder, decoder, processor, or communication device. Alternatively, some memory devices can be separately configured, while others can be integrated into a decoder, processor, or communication device. The type of memory can be any form of storage medium, and this is not limited.

[0202] 8. In the schematic diagrams in the accompanying drawings of this application, the dashed arrows or boxes indicate optional steps or optional modules.

[0203] 9. Unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can mean A or B. In this application, "and / or" is merely a description of the relationship between the related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. A and B can be singular or plural.

[0204] 10. The names of devices, equipment, modules, information, and parameters in this application are merely examples. In actual implementation, the names of the above-mentioned things may be designed in other ways. For example, a vehicle control device may be replaced with a control device, etc.

Claims

1. A vehicle control method, characterized in that, The method includes: Based on the motion information and perception data of the first vehicle, multiple alternative motion trajectories are planned along the first road. The perception data includes road information of the first road and motion information of the target obstacle. The motion direction of the target obstacle on the first road is opposite to the motion direction of the first vehicle on the first road. Each alternative motion trajectory corresponds to an alternative intersection area. The alternative intersection areas corresponding to the multiple alternative motion trajectories are different. Based on the multiple alternative motion trajectories, a target motion trajectory is determined, which is used to indicate the passing trajectory of the first vehicle; The first vehicle is controlled to travel along its oncoming trajectory so that it meets the target obstacle in the target intersection area, which is a candidate intersection area corresponding to the target trajectory.

2. The method according to claim 1, characterized in that, The target obstacle is the second vehicle.

3. The method according to claim 1 or 2, characterized in that, The step of planning multiple alternative movement trajectories along the first road based on the motion information and perception data of the first vehicle includes: Multiple candidate intersection areas were sampled within the area where the first vehicle and the target obstacle met on the first road; Based on the motion information of the first vehicle, the perception data, and the information of the multiple candidate intersection areas, the multiple candidate motion trajectories are obtained.

4. The method according to claim 3, characterized in that, Within the encounter area between the first vehicle and the target obstacle, multiple candidate intersection areas are sampled, including: Within the meeting area, samples are taken along the longitudinal direction of the first road at a first sampling interval to obtain the plurality of candidate meeting areas.

5. The method according to claim 3 or 4, characterized in that, The process of obtaining the multiple candidate motion trajectories based on the motion information of the first vehicle, perception data, and information from the multiple candidate meeting areas includes: Using the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first alternative intersection area, a first longitudinal trajectory is obtained; Using the motion information of the first vehicle, the perception data, and the first longitudinal trajectory, a first alternative motion trajectory is obtained through optimization. The first alternative motion trajectory belongs to the plurality of alternative motion trajectories.

6. The method according to claim 5, characterized in that, The step of obtaining the first longitudinal trajectory using the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first candidate intersection area includes: Based on the motion information of the first vehicle, the motion information of the target obstacle, and the information of the first candidate intersection area, the first optimization problem is solved to obtain the first longitudinal trajectory. The first optimization problem is established based on the first trajectory-related parameters, which include the position of the first candidate area, the speed and reference speed of the first vehicle at the i-th trajectory point, the acceleration of the first vehicle at the i-th trajectory point, the jerk of the first vehicle at the i-th trajectory point, the speed and reference speed of the target obstacle at the i-th trajectory point, the acceleration of the target obstacle at the i-th trajectory point, and the jerk of the target obstacle at the i-th trajectory point, where i is a positive integer.

7. The method according to claim 5 or 6, characterized in that, The step of optimizing the first candidate motion trajectory using the motion information of the first vehicle, the sensing data, and the first longitudinal trajectory includes: Based on the motion information of the first vehicle, the perception data, and the first longitudinal trajectory, a second optimization problem is solved to obtain the first candidate motion trajectory. The first optimization problem is established based on the second trajectory-related parameters, which include the first longitudinal trajectory, the lateral position of the first vehicle at the j-th trajectory point, the longitudinal position of the first vehicle at the j-th trajectory point, the heading angle of the first vehicle at the j-th trajectory point, the curvature of the first vehicle at the j-th trajectory point, the rate of change of curvature of the first vehicle at the j-th trajectory point, the acceleration of the first vehicle at the j-th trajectory point, the lateral position of the target obstacle at the j-th trajectory point, the longitudinal position of the target obstacle at the j-th trajectory point, the heading angle of the target obstacle at the j-th trajectory point, the curvature of the target obstacle at the j-th trajectory point, the rate of change of curvature of the target obstacle at the j-th trajectory point, the acceleration of the target obstacle at the j-th trajectory point, the obstacle avoidance constraints of the first vehicle and the target obstacle, and the road boundary constraints of the first vehicle and the target obstacle.

8. The method according to any one of claims 1-7, characterized in that, Before planning multiple alternative trajectories along the first road based on the motion information and perception data of the first vehicle, the method further includes: Based on the motion information of the first vehicle and the motion information of the target obstacle, the encounter area between the first vehicle and the target obstacle is determined. The candidate intersection areas corresponding to the multiple candidate motion trajectories are all within the meeting area.

9. The method according to claim 8, characterized in that, The meeting area includes a first boundary and a second boundary that are opposite each other along the longitudinal direction of the first road. The first boundary corresponds to the maximum acceleration of the first vehicle and the maximum deceleration of the target obstacle. The second boundary corresponds to the maximum deceleration of the first vehicle and the maximum acceleration of the target obstacle.

10. The method according to any one of claims 1 to 9, characterized in that, The process of determining the target motion trajectory based on the multiple candidate motion trajectories includes: Based on the evaluation data of the multiple candidate motion trajectories, a target motion trajectory is determined. The evaluation data is related to at least one of a safety cost parameter, an efficiency cost parameter, and a comfort cost parameter. The safety metric parameter is used to indicate the safety of the motion trajectory; The efficiency cost parameter is used to indicate the communication efficiency of the motion trajectory; The comfort cost parameter is used to indicate the comfort of the motion trajectory.

11. The method according to any one of claims 1 to 10, characterized in that, The method further includes: A first interface is displayed through a user interface, and the first interface includes one or more of the following prompts: The target obstacle's warning information, first warning information, second warning information, third warning information, fourth warning information, fifth warning information, and sixth warning information, The warning information for the target obstacle is used to indicate that the target obstacle is a meeting object; The first prompt message is used to indicate the target intersection area; The second prompt information is used to prompt the first area in the target intersection area, and the first area is used to indicate the occupied position of the first vehicle when the first vehicle aligns with the target vehicle. The third prompt information is used to prompt the second area in the target intersection area, and the second area is used to indicate the occupied position of the target obstacle when the first vehicle and the target obstacle are aligned and intersecting. The fourth prompt information is used to indicate the passing trajectory of the first vehicle; The fifth prompt information is used to indicate the expected movement trajectory of the target obstacle, and the expected movement trajectory of the target obstacle is indicated by the target movement trajectory.

12. The method according to any one of claims 1 to 11, characterized in that, The method further includes: A first image is projected through a projection module, the first image including one or more of the following prompt patterns: a first prompt pattern, a second prompt pattern, a third prompt pattern, a fourth prompt pattern, a fifth prompt pattern, or a sixth prompt pattern. The first prompt pattern is used to indicate the target intersection area; The second prompt pattern is used to indicate a first area within the target intersection area, the first area being used to indicate the occupied position of the first vehicle when it aligns with the target vehicle. The third prompt pattern is used to prompt a second area in the target intersection area, and the second area is used to indicate the occupied position of the target obstacle when the first vehicle and the target obstacle intersect and align. The fourth prompt pattern is used to indicate the passing trajectory of the first vehicle; The fifth prompt pattern is used to indicate the expected movement trajectory of the target obstacle, and the expected movement trajectory of the target obstacle is indicated by the target movement trajectory; The sixth pattern is used to indicate the passage order of the first vehicle and / or the target obstacle, and the passage order is related to the target's movement trajectory.

13. A vehicle control device characterized by comprising: The vehicle control device includes a processing module and a control module, wherein the vehicle control module is used to implement the method described in any one of claims 1-12.

14. A vehicle control device characterized by comprising: It includes at least one processor and a memory, the memory being used to store a computer program, and the at least one processor being used to invoke the computer program to cause the vehicle control device to implement the method according to any one of claims 1-12.

15. A chip system, characterized by The chip system includes at least one processor and a communication interface, the communication interface being used for inputting and / or outputting data, and the at least one processor being used to invoke computer instructions to cause the chip system to implement the method according to any one of claims 1-12.

16. A vehicle control system characterized by comprising: The vehicle control system includes a vehicle control device and a projection system. The vehicle control device is connected to the projection system. The projection system includes a projection module. The vehicle control device is used to implement the method according to any one of claims 1-12, so that the projection module projects a first image.

17. A vehicle characterized by comprising: The vehicle is described in claim 13 or 14 as a vehicle control device. Alternatively, the vehicle may include the chip system of claim 15. Alternatively, the vehicle may include the vehicle control system of claim 16.

18. A computer-readable storage medium, characterized in that, comprising computer program instructions to be executed by at least one processor to implement the method according to any one of claims 1-12.

19. A computer program product comprising instructions, characterized in that, comprising computer program instructions to be executed by at least one processor to implement the method according to any one of claims 1-12.

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