Vehicle lane change assist method, system, and medium based on virtual leader follower

Abstract

The application provides a vehicle lane changing assistance method, system and medium based on a virtual leader follower. The method comprises: receiving a lane changing instruction input by a user, acquiring a front road image and vehicle state information of the vehicle; determining a target lane and a lane center line of the target lane according to the lane changing instruction and the front road image; generating a virtual leader according to the vehicle state information and the lane center line of the target lane; and controlling driving of the vehicle according to the virtual leader to change the vehicle from a current lane to the target lane. The method of the application can accurately complete vehicle lane changing and improve the safety of vehicle lane changing.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a vehicle lane change assistance method, system and medium based on a virtual navigator and follower. Background Technology

[0002] With economic development and social progress, vehicles have become increasingly common. Statistics show that a large number of traffic accidents occur every year due to improper lane-changing driving behavior.

[0003] In traditional driving, lane changing relies entirely on the driver's decision-making and execution. Specifically, during a lane change, the driver first uses the left and right rearview mirrors and the interior rearview mirror to obtain information about surrounding vehicles and assess whether the current driving environment is suitable for changing lanes. Once it is determined that a lane change is permissible, the driver selects a speed based on experience to complete the task. However, during lane changes, factors such as potentially limited driver visibility or fatigue can easily lead to inaccurate lane changes, reducing safety and comfort, and increasing the risk of traffic accidents.

[0004] Therefore, a vehicle lane change assistance scheme that can accurately complete safe lane changes for vehicles is needed. Summary of the Invention

[0005] This application provides a vehicle lane-changing assistance method, system, and medium based on a virtual navigator and follower, to solve the technical problem that existing vehicle lane-changing methods are inaccurate, resulting in low safety during vehicle lane changes.

[0006] Firstly, this application provides a vehicle lane-changing assistance method based on a virtual navigator / follower, comprising:

[0007] Receive lane change commands from the user and obtain images of the road ahead and the vehicle's status information;

[0008] Based on the lane change instruction and the image of the road ahead, determine the target lane and the center line of the target lane;

[0009] A virtual navigator is generated based on the vehicle status information and the lane centerline of the target lane;

[0010] The virtual navigator controls the driving of this vehicle to change lanes from the current lane to the target lane.

[0011] In one possible implementation, determining the target lane and its centerline based on the lane-changing instruction and the image of the road ahead specifically includes:

[0012] Using image processing algorithms, the road boundary lines in the image of the road ahead are extracted;

[0013] Determine the current position of the vehicle, and based on the current position of the vehicle and the road boundary line, determine the lane in which the vehicle is currently located;

[0014] Based on the direction in the lane change instruction and the lane the vehicle is currently in, determine the target lane, which is the adjacent lane to the lane the vehicle is currently in;

[0015] Determine the lane line corresponding to the target lane based on the road boundary line;

[0016] Determine the center line of the target lane based on the lane lines corresponding to the target lane;

[0017] Determine the equation of the lane centerline of the target lane in the vehicle coordinate system:

[0018] y = C0 + C1x + C2x 2 +C3x 3

[0019] Wherein, y represents the ordinate of the lane centerline, x represents the abscissa of the lane centerline, C0, C1, C2 and C3 represent lane line coefficients, the positive x-axis of the vehicle coordinate system is the direction the vehicle is facing, and the positive y-axis of the vehicle coordinate system is the direction the vehicle is facing to the left.

[0020] In one possible implementation, generating a virtual navigator based on the vehicle status information and the lane centerline of the target lane specifically includes:

[0021] Determine the curvature of the lane centerline based on the lane centerline of the target lane;

[0022] Determine the lateral target distance between the vehicle's current position and the lane centerline;

[0023] The speed of the virtual navigator is determined based on the curvature of the lane centerline and the vehicle status information.

[0024] The position of the virtual navigator is determined based on the lane centerline curvature, the lateral target distance, and the vehicle status information.

[0025] In one possible implementation, the vehicle status information includes one or more of the following:

[0026] Vehicle position, vehicle speed, yaw rate, lateral acceleration, longitudinal acceleration.

[0027] In one possible implementation, determining the speed of the virtual navigator based on the lane centerline curvature and the vehicle status information specifically includes:

[0028] Calculate the speed of the virtual navigator using the following formula:

[0029]

[0030] Wherein, the v tar The speed of the proposed navigator is represented by v, and the speed of the vehicle itself is represented by a. x This represents the longitudinal acceleration of the vehicle, where a is... y The ρ represents the lateral acceleration of the vehicle. road The k represents the curvature of the lane centerline. ρ k a Indicates calibration parameters.

[0031] In one possible implementation, determining the position of the virtual navigator based on the lane centerline curvature, the lateral target distance, and the vehicle status information specifically includes:

[0032] Determine a first distance between the center line of the target lane and any lane line of the target lane;

[0033] Determine whether the lateral target distance is less than the first distance;

[0034] If not, the virtual navigator's position is calculated using the following formula:

[0035] s = s0 + k sv v+k sρ ρ road +k sy yawrate

[0036] l=l0+k lv v+k lρ ρ road +k ly yawrate

[0037] If so, the virtual navigator's position can be calculated using the following formula:

[0038] s = s0 + k sv v+k sρ ρ road +k sy yawrate

[0039] l = C0 + C1s + C2s 2 +C3s 3

[0040] Wherein, the k sv k sρ k sy k lv klρ k ly The calibration parameters are defined as follows: s represents the longitudinal distance between the virtual navigator and the vehicle; s0 represents the preset longitudinal distance between the virtual navigator and the vehicle; l represents the lateral distance between the virtual navigator and the vehicle; l0 represents the preset lateral distance between the virtual navigator and the vehicle; and ρ represents the calibration parameters. road The curvature of the lane centerline is represented by yawrate, which represents the yaw rate.

[0041] In one possible implementation, before acquiring the image of the road ahead and the vehicle's status information, the method further includes:

[0042] Using vehicle-mounted cameras and radar, determine the position and speed of vehicles around the vehicle;

[0043] The position and speed of the surrounding vehicles are output to the user;

[0044] If the user inputs a lane-changing command again, the step of obtaining the image of the road ahead and the vehicle's status information is executed.

[0045] Secondly, this application provides a lane change assist system, comprising:

[0046] The receiving module is used to receive lane change commands input by the user, obtain images of the road ahead, and the vehicle's status information.

[0047] The execution module is used to determine the target lane and the center line of the target lane based on the lane change instruction and the image of the road ahead; generate a virtual navigator based on the vehicle status information and the center line of the target lane; and control the driving of the vehicle based on the virtual navigator to change the vehicle from the current lane to the target lane.

[0048] Thirdly, this application provides another lane-changing assistance system, including: a processor, and a memory communicatively connected to the processor;

[0049] The memory stores computer-executed instructions;

[0050] The processor executes computer execution instructions stored in the memory to implement the above-described method.

[0051] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the above-described method.

[0052] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0053] The lane-changing assistance method, system, and medium based on a virtual navigator provided in this application can receive lane-changing commands input by a user, acquire an image of the road ahead and the vehicle's status information; determine the target lane and its center line based on the lane-changing command and the road image ahead; generate a virtual navigator based on the vehicle status information and the target lane's center line; and control the vehicle's driving according to the virtual navigator to change lanes from the current lane to the target lane. In this method, after receiving a lane-changing command input by a user, the lane-changing assistance system can acquire an image of the road ahead and the vehicle's status information, generate a virtual navigator based on this information, and then control the vehicle to change lanes from the current lane to the target lane according to the virtual navigator to complete the lane-changing task. Through this setup, the virtual navigator can be used to control the vehicle to complete lane changes, avoiding inaccuracies caused by manual lane changing, improving the safety and comfort of lane changing, and reducing the risk of traffic accidents. Furthermore, a virtual navigator is generated based on vehicle status information and the center line of the target lane, which improves the accuracy of the virtual navigator and further enhances the accuracy and safety of lane changes. Attached Figure Description

[0054] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0055] Figure 1 This is a system architecture diagram of an embodiment of this application;

[0056] Figure 2 This is a flowchart of a vehicle lane-changing assistance method based on a virtual navigator and follower according to an embodiment of this application;

[0057] Figure 3 This is a flowchart of a vehicle lane-changing assistance method based on a virtual navigator and follower, according to another embodiment of this application.

[0058] Figure 4 This is a schematic diagram of a lane-changing process according to an embodiment of this application;

[0059] Figure 5 This is a schematic diagram of the structure of a lane change assist system according to an embodiment of this application;

[0060] Figure 6 This is a schematic diagram of the structure of a lane change assist system according to another embodiment of this application.

[0061] Reference numerals: 1. Vehicle; 11. Lane change assist system; 12. Onboard camera device; 13. Onboard radar; 14. Sensor.

[0062] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0063] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0064] It should be noted that the vehicle lane change assistance method, system, and medium based on virtual navigator and follower of this application can be used in the field of autonomous driving technology, as well as in any other field besides autonomous driving technology, such as the field of virtual navigator. The application areas of the vehicle lane change assistance method, system, and medium based on virtual navigator and follower of this application are not limited.

[0065] First, let me explain the terms used in this application:

[0066] A virtual navigator refers to the desired position calculated using a virtual navigator-following algorithm. An assumed virtual navigator (with the desired trajectory) can be selected as a reference for the follower (vehicle). The virtual navigator maintains a corresponding distance and angle with the follower. The control algorithm, input to the controller, guides the follower to track the virtual navigator's trajectory and state. When the follower reaches the virtual navigator's position, it means the vehicle is in the desired position and motion state.

[0067] In traditional driving, lane changing relies entirely on the driver's decision-making and execution. Specifically, during a lane change, the driver first uses the left and right rearview mirrors and the interior rearview mirror to obtain information about surrounding vehicles and assess whether the current driving environment is suitable for changing lanes. Once it is determined that a lane change is permissible, the driver selects a speed based on experience to complete the task. However, during lane changes, factors such as potentially limited driver visibility or fatigue can easily lead to inaccurate lane changes, reducing safety and comfort, and increasing the risk of traffic accidents.

[0068] According to statistics, traffic accidents caused by lane changing account for about 4%-10% of all traffic accidents. Among them, lane changing accidents caused by human factors account for 75% of all lane changing accidents. In addition, traffic delays caused by lane changing account for 10% of the total traffic delays.

[0069] Existing lane change assist solutions do not meet users' safety requirements for lane changes, for example:

[0070] Chinese patent CN211032357U discloses a vehicle lane change hazard warning function. Although this invention can warn the driver of the danger level of lane changing, it cannot correct the driver's inaccurate or even wrong operation, thus resulting in low safety in actual use.

[0071] Chinese patent CN210133060U provides a technology for predicting and alerting safe lane-changing time for vehicles. Although this technology can predict safe lane-changing time, it has a significant drawback: it cannot help drivers participate in actual lane-changing driving.

[0072] Chinese Patent 201220152857.1 discloses a microcontroller-based vehicle lane-changing assist device, designed to prevent traffic accidents caused by insufficient information about the target lane area during lane changes at high speeds. However, this device only provides a simple reminder function and uses a seat back vibrator for alarm, which may cause unnecessary panic to the driver and could actually create a driving safety hazard.

[0073] Based on this technical problem, the inventive concept of this application is: how to provide a vehicle lane change assistance method based on a virtual navigator and follower that can accurately complete safe lane changes for vehicles.

[0074] Specifically, the system can receive lane-change commands input by the user, acquire an image of the road ahead and the vehicle's status information; determine the target lane and its center line based on the lane-change command and the road image; generate a virtual navigator based on the vehicle status information and the target lane's center line; and control the vehicle's driving according to the virtual navigator to change lanes from the current lane to the target lane. In this method, after receiving a lane-change command input by the user, the lane-change assistance system can acquire an image of the road ahead and the vehicle's status information, and generate a virtual navigator based on this information. The system then controls the vehicle to change lanes from the current lane to the target lane based on the virtual navigator to complete the lane-change task. This setup allows the virtual navigator to control the vehicle's lane change, avoiding inaccuracies caused by manual lane changing, improving lane-change safety and comfort, and reducing the risk of traffic accidents. Furthermore, generating the virtual navigator based on the vehicle status information and the target lane's center line improves the accuracy of the virtual navigator, further enhancing the accuracy and safety of lane changing.

[0075] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0076] Figure 1 This is a system architecture diagram of an embodiment of this application, such as... Figure 1 As shown, 1 represents the vehicle, 11 represents the lane change assist system, 12 represents the onboard camera, 13 represents the onboard radar, and 14 represents the sensor. During a lane change, the user first observes the surrounding road environment and, after determining that vehicle 1 is ready to change lanes, inputs a lane change command to the lane change assist system 11 by moving the steering wheel in the corresponding lane change direction. Upon receiving the user's input, the lane change assist system 11 uses the onboard camera 12 and the onboard radar 13 to determine the positions and speeds of surrounding vehicles and outputs these information to the user. The user then again determines that vehicle 1 is ready to change lanes and inputs another lane change command to the lane change assist system 11 by moving the steering wheel in the corresponding lane change direction. Upon receiving the second input, the lane change assist system 11 uses the onboard camera 12 and the sensor 14 to acquire images of the road ahead and the vehicle's status information. The lane change assist system 11 determines the target lane and the center line of the target lane based on the lane change command and the road image ahead. Based on the vehicle status information and the center line of the target lane, it generates a virtual navigator and controls the driving of vehicle 1 according to the speed and position of the virtual navigator, so as to change the vehicle 1 from the current lane to the target lane.

[0077] Example 1

[0078] Figure 2 This is a flowchart illustrating a vehicle lane change assist method based on a virtual navigator / follower according to an embodiment of this application. This embodiment describes the vehicle lane change assist method based on a virtual navigator / follower as the executing entity. Figure 2 As shown, the vehicle lane-changing assistance method based on a virtual navigator / follower may include the following steps:

[0079] S101: Receives lane change commands input by the user, obtains images of the road ahead and vehicle status information of the vehicle itself.

[0080] In this embodiment, the user can observe the surrounding road environment to determine whether the vehicle is ready to change lanes, and then decide whether to perform a lane change operation (i.e., whether to input a lane change command).

[0081] In this embodiment, the lane-change command input by the user can be the user moving the steering lever in the corresponding lane-change direction. For example, if the lane-change assist system detects that the user moves the steering lever to the left or right during vehicle driving, it can be considered that the user has input a lane-change command. Whether the user moves the steering lever in the corresponding lane-change direction can be identified using the vehicle steering system. For details, please refer to the prior art, which will not be elaborated here.

[0082] It should be noted that all lane changes involved in this application refer to changes between adjacent lanes.

[0083] In one possible implementation, before acquiring the image of the road ahead and the vehicle status information of the vehicle in step S101 above, the method may further include: using an onboard camera and onboard radar to determine the position and speed of vehicles around the vehicle; outputting the position and speed of the surrounding vehicles to the user; and if a lane-changing command is received again from the user, then executing the step of acquiring the image of the road ahead and the vehicle status information of the vehicle.

[0084] In this embodiment, an onboard camera and onboard radar can be used to sense the relative position and speed of surrounding vehicles to determine the position and speed of vehicles around the vehicle. Similarly, an onboard camera can be used to sense the distance of the vehicle from the lane centerline to determine the vehicle's current position. For determining the distance from the lane centerline, please refer to step S102.

[0085] In this embodiment, the location and speed of surrounding vehicles can be output to the user using one or more of the following methods: voice, text, and images. No restrictions are imposed on this method.

[0086] In this embodiment, due to factors such as limited visibility or fatigue, the user's input lane-change command may be inaccurate, meaning the actual road conditions are not suitable for changing lanes. Therefore, after receiving the user's input lane-change command but before acquiring the image of the road ahead and the vehicle's status information, the positions and speeds of surrounding vehicles can be determined and output to the user so that the user can decide whether to continue with the lane change. This setting further improves the accuracy and safety of lane changes.

[0087] In one possible implementation, the vehicle status information in step S101 above may include one or more of the following: vehicle position, vehicle speed, yaw rate, lateral acceleration, and longitudinal acceleration.

[0088] In this embodiment, the vehicle's position can be identified using the vehicle's GPS system, and the vehicle's speed, yaw rate, lateral acceleration, and longitudinal acceleration can be obtained using various sensors. Alternatively, the vehicle's speed, yaw rate, lateral acceleration, and longitudinal acceleration can be obtained directly from the vehicle control system.

[0089] In this embodiment, the vehicle's position, speed, yaw rate, lateral acceleration, and longitudinal acceleration can comprehensively and accurately represent the vehicle's status information, so as to accurately generate a virtual navigator based on the above vehicle status information.

[0090] S102: Based on the lane change instruction and the image of the road ahead, determine the target lane and the center line of the target lane.

[0091] In this embodiment, the image of the road ahead can be obtained using a vehicle-mounted camera device such as a camera.

[0092] In one possible implementation, step S102, which determines the target lane and its center line based on the lane change instruction and the image of the road ahead, may include:

[0093] S1021: Use image processing algorithms to extract the road boundary lines from the image of the road ahead.

[0094] S1022: Determine the current position of this vehicle, and based on the current position of this vehicle and the road boundary line, determine the lane in which this vehicle is currently located.

[0095] S1023: Based on the direction in the lane change instruction and the current lane of the vehicle, determine the target lane, which is the adjacent lane of the current lane of the vehicle.

[0096] S1024: Determine the lane line corresponding to the target lane based on the road boundary line.

[0097] S1025: Determine the center line of the target lane based on the lane lines corresponding to the target lane.

[0098] S1026: Determine the equation of the lane centerline of the target lane in the vehicle coordinate system, i.e., formula (1):

[0099] y = C0 + C1x + C2x 2 +C3x 3 (1)

[0100] Where y represents the ordinate of the lane centerline, x represents the abscissa of the lane centerline, C0, C1, C2 and C3 represent lane line coefficients, the positive x-axis of the vehicle coordinate system is the direction the vehicle is facing, and the positive y-axis of the vehicle coordinate system is the direction the vehicle is facing to the left.

[0101] In this embodiment, the vehicle's current position can be determined by using an onboard camera to sense the distance between the vehicle and the center line of the lane.

[0102] In this embodiment, existing image processing algorithms can be used to extract the road boundary lines in the image of the road ahead. The specific image processing algorithm can be flexibly set by those skilled in the art, such as a Kalman filter or a deep learning-based object detection model, and no restrictions are imposed here.

[0103] In this embodiment, when determining the target lane based on the direction in the lane change command and the lane the vehicle is currently in, if the direction in the lane change command is left, the target lane is the lane adjacent to the left of the lane the vehicle is currently in; if the direction in the lane change command is right, the target lane is the lane adjacent to the right of the lane the vehicle is currently in.

[0104] In this embodiment, the lane centerline of the target lane refers to a virtual line at the center of the target lane, which does not exist in reality. The lane centerline of the target lane can be determined based on the two lane lines of the target lane.

[0105] In this embodiment, the lane centerline equation can be obtained by fitting the coordinates of the lane centerline position in the vehicle coordinate system after determining the position of the lane centerline.

[0106] In this embodiment, image processing algorithms can be used to easily and accurately extract road boundary lines from the image of the road ahead. After determining the road boundary lines, the target lane to which the vehicle will change lanes can be easily and conveniently determined based on the vehicle's current position and the steering direction in the lane-changing command. After determining the target lane, the lane lines and lane center lines corresponding to the target lane can be determined based on the extracted road boundary lines. After determining the position of the lane center line, the coordinates of the lane center line position are fitted in the vehicle's coordinate system to accurately obtain the lane center line equation in the vehicle's coordinate system, which is then used to generate a virtual navigator based on the lane center line equation and the lane center line position.

[0107] S103: Generate a virtual navigator based on vehicle status information and the center line of the target lane.

[0108] In this embodiment, the specific implementation of step S103 above, which generates a virtual navigator based on vehicle status information and the center line of the target lane, is detailed in Embodiment 2.

[0109] S104: Drive the vehicle according to the virtual navigator's control to change lanes from the current lane to the target lane.

[0110] In this embodiment, the vehicle's position relative to the target lane can be determined by the distance vector between the vehicle and the lane centerline, thus determining whether the lane change task has been completed. The direction of the distance vector can be defined as positive if the vehicle is to the left of the lane centerline and negative if it is to the right. When the vehicle (the center point of the vehicle body) coincides with the lane centerline of the target lane (distance vector is 0), the lane change task is considered to be completed.

[0111] In this embodiment, when the vehicle is following the virtual navigator and changing lanes, the tracking control method for the vehicle's speed and position can be one of the proportional-integral-derivative control method, fuzzy control method, or optimization control method. Of course, other control methods can also be used, and no restrictions are placed here.

[0112] For example, when controlling the vehicle's driving based on the virtual navigator, the specific control process can be as follows:

[0113] (1) The speed control adopts the proportional-integral-derivative control method expressed by the following formula (2):

[0114]

[0115] Where Δv is the speed difference between the vehicle and the virtual navigator, kp and T I and T D It is the control parameter, and a(t) is the speed control output.

[0116] (2) Position control employs an optimization control method, wherein,

[0117] The kinematic equation is given by formula (3):

[0118]

[0119] At reference point (s) r , l r At point ), use formula (4) to perform a Taylor expansion:

[0120]

[0121] The evaluation function expressed by design formula (5) is as follows:

[0122]

[0123] The steering wheel angle control amount expressed by formula (6) can be obtained:

[0124] δ steer =-Kχ+arctan (ρ road L) (6)

[0125] in, δ is the vehicle's heading angle, L is the vehicle's length, K, Q, and R are the control parameter matrices, and δ is the vehicle's heading angle. steer To control the output.

[0126] In this embodiment, the system can receive a lane-change command input by the user, acquire an image of the road ahead and the vehicle's status information; determine the target lane and its center line based on the lane-change command and the road image; generate a virtual navigator based on the vehicle status information and the target lane's center line; and control the vehicle's driving according to the virtual navigator to change lanes from the current lane to the target lane. In this method, after receiving a lane-change command input by the user, the lane-change assist system can acquire an image of the road ahead and the vehicle's status information, and generate a virtual navigator based on these information. The system then controls the vehicle to change lanes from the current lane to the target lane based on the virtual navigator to complete the lane-change task. This setup allows the virtual navigator to control the vehicle's lane change, avoiding inaccuracies caused by manual lane changing, improving lane-change safety and comfort, and reducing the risk of traffic accidents. Furthermore, generating the virtual navigator based on the vehicle status information and the target lane's center line improves the accuracy of the virtual navigator, further enhancing the accuracy and safety of lane changes.

[0127] The following detailed description, using a specific embodiment two, elaborates on the implementation method of step S103 in embodiment one above, which generates a virtual navigator based on vehicle status information and the lane center line of the target lane.

[0128] Example 2

[0129] Figure 3 This is a flowchart illustrating another embodiment of a vehicle lane change assist method based on a virtual navigator / follower. This embodiment describes the vehicle lane change assist method based on a virtual navigator / follower as the executing entity. Figure 3 As shown, the vehicle lane-changing assistance method based on a virtual navigator / follower may include the following steps:

[0130] S201: Determine the curvature of the lane centerline based on the lane centerline of the target lane.

[0131] In this embodiment, the curvature of the lane centerline can be determined based on the lane centerline equation. The specific calculation process of the lane centerline curvature can be referred to the existing technology, and will not be elaborated here.

[0132] S202: Determine the lateral target distance between the vehicle's current position and the lane centerline.

[0133] In this embodiment, after determining the lane centerline equation, a perpendicular line segment can be drawn between the current position (center point) of the vehicle and the line segment represented by the lane centerline equation. The length of this perpendicular line segment is the lateral target distance.

[0134] S203: Determine the speed of the virtual navigator based on the curvature of the lane centerline and vehicle status information.

[0135] In this embodiment, vehicle status information may include vehicle speed, lateral acceleration, and longitudinal acceleration.

[0136] In one possible implementation, step S203, which determines the speed of the virtual navigator based on the lane centerline curvature and vehicle status information, may include:

[0137] The speed of the virtual navigator can be calculated using the following formula (7):

[0138]

[0139] Among them, v tar The speed of the proposed navigator is represented by v, and the speed of the vehicle itself is represented by a. x a represents the longitudinal acceleration of the vehicle. y ρ represents the lateral acceleration of the vehicle. road k represents the curvature of the lane centerline. ρ k a Indicates calibration parameters.

[0140] In this embodiment, k ρ k a The calibration parameters indicated can be flexibly set by those skilled in the art according to actual conditions, and no restrictions are imposed here.

[0141] In this embodiment, after determining the vehicle speed, longitudinal acceleration, lateral acceleration, and lane centerline curvature, the speed of the virtual navigator can be obtained simply and accurately using formula (7).

[0142] S204: Determine the position of the virtual navigator based on the lane centerline curvature, lateral target distance, and vehicle status information.

[0143] In this embodiment, vehicle status information may include vehicle speed and yaw rate.

[0144] In one possible implementation, step S204, which determines the position of the virtual navigator based on the lane centerline curvature, lateral target distance, and vehicle status information, may include:

[0145] S2041: Determine the first distance between the center line of the target lane and any lane line of the target lane.

[0146] S2042: Determine if the lateral target distance is less than the first distance.

[0147] S2043: If not, the position of the virtual navigator is calculated using the following formulas (8) and (9):

[0148] s = s0 + k sv v+k sρ ρ road +k sy yawrate (8)

[0149] l=l0+k lv v+k lρ ρ road +k ly yawrate (9)

[0150] S2044: If so, the position of the virtual navigator is calculated using the following formulas (10) and (11):

[0151] s = s0 + k sv v+k sρ ρ road +k sy yawrate (10)

[0152] l = C0 + C1s + C2s 2 +C3s 3 (11)

[0153] Where, k sv k sρ k sy k lv k lρ k ly These represent calibration parameters: s represents the longitudinal distance between the virtual navigator and the vehicle; s0 represents the preset longitudinal distance between the virtual navigator and the vehicle; l represents the lateral distance between the virtual navigator and the vehicle; l0 represents the preset lateral distance between the virtual navigator and the vehicle; ρ road This represents the curvature of the lane centerline, and yawrate represents the yaw rate.

[0154] In this embodiment, k sv k sρ k sy k lv k lρ k ly The calibration parameters indicated can be flexibly set by those skilled in the art according to actual conditions, and no restrictions are imposed here.

[0155] In this embodiment, the preset longitudinal distance s0 between the virtual navigator and the vehicle, and the preset lateral distance l0 between the virtual navigator and the vehicle can be flexibly set by those skilled in the art based on experience and factors such as lane width and vehicle length, and no restrictions are imposed here.

[0156] In this embodiment, the first distance between the center line of the target lane and any lane line of the target lane represents the width of half a lane. When the lateral target distance is not less than the first distance, it indicates that the vehicle has not changed lanes. When the lateral target distance is less than the first distance, it indicates that the vehicle has changed lanes to the target lane.

[0157] In this embodiment, during lane changing, to further improve the accuracy and safety of lane changing and achieve lane transitions, different calculation formulas can be used to determine the position of the virtual navigator when the vehicle is in different lanes. Furthermore, by utilizing the relationship between the lateral target distance and the first distance, the lane the vehicle is in can be easily and conveniently determined, thereby accurately determining the specific calculation formula for the virtual navigator's position and further improving the accuracy of the virtual navigator's position calculation.

[0158] For example, Figure 4 This is a schematic diagram of a lane-changing process according to an embodiment of this application, as shown below. Figure 4 As shown, the lane where this vehicle is located is the current lane, the lane where virtual navigator 2 is located is the target lane, and virtual navigator 1 is located on the shared lane line between the current lane and the target lane. The position of virtual navigator 2 is the desired position that this vehicle will reach after changing lanes. The lane-changing trajectory from this vehicle to virtual navigator 2 is the trajectory of this vehicle changing lanes under the guidance of the virtual navigator. The position points of multiple virtual navigators constitute this lane-changing trajectory. The trajectory between this vehicle and virtual navigator 1 is the trajectory of the vehicle traveling in the lane before changing lanes. At this time, the lateral target distance is not less than the first distance, and the position of the virtual navigator can be calculated using the above formulas (8) and (9). The trajectory between virtual navigator 1 and virtual navigator 2 is the trajectory of the vehicle traveling in the lane after changing lanes. At this time, the lateral target distance is less than the first distance, and the position of the virtual navigator can be calculated using the above formulas (10) and (11).

[0159] In this embodiment, since the vehicle is constantly moving during the lane change process, and the vehicle's position and speed are changing, as is the road image ahead, the lane change assist system can obtain the latest road and vehicle information through real-time image processing and vehicle tracking control to update the speed and position of the virtual navigator.

[0160] In this embodiment, to achieve vehicle driving control based on a virtual navigator, the virtual navigator typically needs to be represented by both speed and position. Therefore, generating a virtual navigator involves determining its speed and position. Since the virtual navigator is used to guide the vehicle in lane changes, in addition to vehicle status information, the speed and position of the virtual navigator also need to be determined based on the lane centerline curvature. Furthermore, because the calculation formula for determining the virtual navigator's position differs depending on the vehicle's lane position, in addition to vehicle status information and lane centerline curvature, the position of the virtual navigator also needs to be determined based on the lateral target distance. Using lane centerline curvature, lateral target distance, and vehicle status information, a virtual navigator can be generated simply and accurately.

[0161] The following is a specific embodiment illustrating the vehicle lane-changing assistance method based on virtual navigator and follower of this application.

[0162] Example 3

[0163] In one specific embodiment, a driver is driving on a highway and needs to change lanes to the left to make a left turn. The vehicle's lane change assist system will assist the driver in completing the lane change task. The specific lane change assist process is as follows:

[0164] The first step is for the driver to observe the surrounding road environment. If there are no vehicles in the left lane, the driver determines that the vehicle is ready to change lanes and inputs a lane change command to the lane change assist system by turning the steering lever to the left.

[0165] The second step is that after receiving the lane change command input by the user, the lane change assist system uses the onboard camera and onboard radar to determine the position and speed of the vehicles around the vehicle, and outputs the position and speed of the surrounding vehicles to the driver.

[0166] The third step is for the driver to confirm again that there are no vehicles around the vehicle and that it is safe to change lanes. The driver then inputs the lane change command into the lane change assist system by turning the steering wheel to the left.

[0167] Fourth, after receiving the lane change command from the user again, the lane change assist system acquires the image of the road ahead and the vehicle's status information.

[0168] Fifth, the lane change assist system determines the target lane and its center line based on the lane change command and the image of the road ahead.

[0169] The sixth step involves the lane change assist system determining the curvature of the lane centerline based on the target lane's centerline, determining the lateral target distance between the vehicle's current position and the lane centerline, determining the speed of the virtual navigator based on the lane centerline curvature and vehicle status information, and determining the position of the virtual navigator based on the lane centerline curvature, lateral target distance, and vehicle status information.

[0170] Step 7: The lane change assist system controls the vehicle's driving based on the speed and position of the virtual navigator to change the vehicle from its current lane to the target lane.

[0171] Figure 5 This is a schematic diagram of the structure of a lane change assist system according to an embodiment of this application, as shown below. Figure 5 As shown, the lane change assist system includes: a receiving module 51, used to receive a lane change command input by a user, acquire an image of the road ahead, and obtain vehicle status information of the vehicle; an execution module 52, used to determine the target lane and the lane center line of the target lane based on the lane change command and the image of the road ahead; generate a virtual navigator based on the vehicle status information and the lane center line of the target lane; and control the driving of the vehicle according to the virtual navigator to change the vehicle from the current lane to the target lane. In one embodiment, a description of the specific functions implemented by the lane change assist system can be found in steps S101-S104 of Embodiment 1 and steps S201-S204 of Embodiment 2, and will not be repeated here.

[0172] Figure 6 This is a schematic diagram of the structure of a lane change assist system according to another embodiment of this application, as shown below. Figure 6 As shown, the lane change assist system includes: a processor 101 and a memory 102 communicatively connected to the processor 101; the memory 102 stores computer execution instructions; the processor 101 executes the computer execution instructions stored in the memory 102 to implement the steps of the vehicle lane change assist method based on virtual navigator follower in the above method embodiments.

[0173] The lane change assist system can be standalone or part of the vehicle control system, and the processor 101 and memory 102 can utilize existing hardware of the vehicle control system.

[0174] In the aforementioned lane-changing auxiliary system, the memory 102 and the processor 101 are electrically connected directly or indirectly to enable data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines, such as a bus connection. The memory 102 stores computer-executable instructions that implement data access control methods, including at least one software functional module that can be stored in the memory 102 in the form of software or firmware. The processor 101 executes various functional applications and data processing by running the software programs and modules stored in the memory 102.

[0175] The memory 102 may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 102 stores programs, which are executed by the processor 101 upon receiving execution instructions. Furthermore, the software programs and modules within the memory 102 may include an operating system, which may include various software components and / or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.) and can communicate with various hardware or software components to provide an operating environment for other software components.

[0176] Processor 101 can be an integrated circuit chip with signal processing capabilities. The aforementioned processor 101 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor.

[0177] An embodiment of this application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the steps of the various method embodiments of this application.

[0178] An embodiment of this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the various method embodiments of this application.

[0179] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the appended claims.

[0180] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A vehicle lane-changing assistance method based on a virtual navigator and follower, characterized in that, include: Receive lane change commands from the user and obtain images of the road ahead and the vehicle's status information; Based on the lane change instruction and the image of the road ahead, determine the target lane and the center line of the target lane; A virtual navigator is generated based on the vehicle status information and the lane centerline of the target lane; The virtual navigator controls the driving of this vehicle to change lanes from the current lane to the target lane; The step of generating a virtual navigator based on the vehicle status information and the lane centerline of the target lane specifically includes: Determine the curvature of the lane centerline based on the lane centerline of the target lane; Determine the lateral target distance between the vehicle's current position and the lane centerline; The speed of the virtual navigator is determined based on the curvature of the lane centerline and the vehicle status information. The position of the virtual navigator is determined based on the lane centerline curvature, the lateral target distance, and the vehicle status information.

2. The method according to claim 1, characterized in that, The step of determining the target lane and its centerline based on the lane-changing instruction and the image of the road ahead specifically includes: Using image processing algorithms, the road boundary lines in the image of the road ahead are extracted; Determine the current position of the vehicle, and based on the current position of the vehicle and the road boundary line, determine the lane in which the vehicle is currently located; Based on the direction in the lane change instruction and the lane the vehicle is currently in, determine the target lane, which is the adjacent lane to the lane the vehicle is currently in; Determine the lane line corresponding to the target lane based on the road boundary line; Determine the center line of the target lane based on the lane lines corresponding to the target lane; Determine the equation of the lane centerline of the target lane in the vehicle coordinate system: Among them, the The ordinate of the lane centerline is represented by the following: The x-coordinate of the lane centerline, the , , and The lane line coefficient is represented by the positive x-axis of the vehicle coordinate system, which represents the direction the vehicle is facing, and the positive y-axis of the vehicle coordinate system represents the direction the vehicle is facing to the left.

3. The method according to claim 1, characterized in that, The vehicle status information includes one or more of the following: Vehicle position, vehicle speed, yaw rate, lateral acceleration, longitudinal acceleration.

4. The method according to claim 3, characterized in that, The step of determining the speed of the virtual navigator based on the lane centerline curvature and the vehicle status information specifically includes: Calculate the speed of the virtual navigator using the following formula: Among them, the Indicating the speed of the proposed leader, the stated This indicates the speed of the vehicle. This indicates the longitudinal acceleration of the vehicle. This indicates the lateral acceleration of the vehicle. Indicates the curvature of the lane centerline, the , Indicates calibration parameters.

5. The method according to claim 4, characterized in that, The step of determining the virtual navigator's position based on the lane centerline curvature, the lateral target distance, and the vehicle status information specifically includes: Determine a first distance between the center line of the target lane and any lane line of the target lane; Determine whether the lateral target distance is less than the first distance; If not, the virtual navigator's position is calculated using the following formula: If so, the virtual navigator's position can be calculated using the following formula: Among them, the , , , , , Indicates the calibration parameters, the This indicates the longitudinal distance between the virtual navigator and the vehicle. This indicates the preset longitudinal distance between the virtual navigator and the vehicle. This indicates the lateral distance between the virtual navigator and the vehicle. This indicates the preset lateral distance between the virtual navigator and the vehicle. Indicates the curvature of the lane centerline, the This represents the yaw rate.

6. The method according to any one of claims 1-5, characterized in that, Before acquiring the image of the road ahead and the vehicle's status information, the process also includes: Using vehicle-mounted cameras and radar, determine the position and speed of vehicles around the vehicle; The position and speed of the surrounding vehicles are output to the user; If the user inputs a lane-changing command again, the step of obtaining the image of the road ahead and the vehicle's status information is executed.

7. A lane-changing assist system, characterized in that, include: The receiving module is used to receive lane change commands input by the user, obtain images of the road ahead, and the vehicle's status information. The execution module is used to determine the target lane and the lane centerline of the target lane based on the lane change instruction and the image of the road ahead; A virtual navigator is generated based on the vehicle status information and the lane centerline of the target lane; The virtual navigator controls the driving of this vehicle to change lanes from the current lane to the target lane; The step of generating a virtual navigator based on the vehicle status information and the lane centerline of the target lane specifically includes: determining the lane centerline curvature based on the lane centerline of the target lane; determining the lateral target distance between the current position of the vehicle and the lane centerline; determining the speed of the virtual navigator based on the lane centerline curvature and the vehicle status information; and determining the position of the virtual navigator based on the lane centerline curvature, the lateral target distance, and the vehicle status information.

8. A lane-changing assist system, characterized in that, Includes a processor and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 6.

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