Vehicle speed curve determination method and apparatus, electronic device, and computer medium

Abstract

The present disclosure discloses a vehicle speed curve determination method and device, electronic equipment and computer medium, wherein the method comprises: obtaining driving information of a current vehicle and obstacle information corresponding to the current vehicle; determining a corresponding target reference line according to the driving information; determining a target coordinate system corresponding to the target reference line; and determining a target speed curve corresponding to the current vehicle in the automatic driving process according to the target coordinate system and the obstacle information. The technical solutions provided by the embodiments of the present disclosure can improve the safety of vehicle driving.

Description

Technical Field

[0001] This disclosure pertains to the field of autonomous driving technology, and particularly relates to a method, apparatus, electronic device, and computer medium for determining a vehicle speed curve. Background Technology

[0002] In autonomous driving, a speed curve describes the speed changes of a vehicle along a planned path during path planning. It is typically used to control vehicle acceleration and deceleration to achieve smooth, safe, and efficient driving. However, in related technologies, speed curve planning often only considers the operating states of the vehicle and the target vehicle. The resulting longitudinal decisions may contradict the driver's intentions, potentially leading to speed curves that include acceleration or deceleration processes that do not meet the driver's expectations. This can negatively impact vehicle safety and driver comfort. Summary of the Invention

[0003] This disclosure provides an implementation scheme different from related technologies to solve the technical problems of poor vehicle driving safety and poor driver comfort in related technologies.

[0004] In a first aspect, this disclosure provides a method for determining a vehicle speed curve, including:

[0005] The vehicle obtains driving information of the current vehicle and obstacle information corresponding to the current vehicle. The driving information of the current vehicle includes the first location information of the current vehicle and the operation information of the relevant personnel controlling the current vehicle. The obstacle information corresponding to the current vehicle includes the second location information of each obstacle in at least one obstacle within a first preset geographical range from the current vehicle.

[0006] The target reference line is determined based on the driving information. The target reference line includes at least one of the following: the center line of the lane in which the current vehicle is located, the target lane line that the current vehicle is currently crossing, and the preset planned route corresponding to the current vehicle.

[0007] Determine the target coordinate system corresponding to the target reference line;

[0008] The target speed curve of the current vehicle during autonomous driving is determined based on the target coordinate system and the obstacle information.

[0009] Secondly, this disclosure provides a vehicle speed curve determination device, comprising:

[0010] The acquisition unit is used to acquire the driving information of the current vehicle and the obstacle information corresponding to the current vehicle. The driving information of the current vehicle includes the first location information of the current vehicle and the operation information of the relevant personnel driving the current vehicle. The obstacle information corresponding to the current vehicle includes the second location information of each obstacle among at least one obstacle within a first preset geographical range from the current vehicle.

[0011] The determining unit is configured to determine a corresponding target reference line based on the driving information. The target reference line includes at least one of the following: a center line indicating the lane in which the current vehicle is located, a target lane line currently crossed by the current vehicle, or a preset planned route corresponding to the current vehicle.

[0012] The determining unit is also used to determine the target coordinate system corresponding to the target reference line;

[0013] The determining unit is further configured to determine the target speed curve of the current vehicle during autonomous driving based on the target coordinate system and the obstacle information.

[0014] Thirdly, this disclosure provides an electronic device, including:

[0015] Processor; and

[0016] Memory for storing the executable instructions of the processor;

[0017] The processor is configured to execute the first aspect and any of the methods in each possible implementation of the first aspect by executing the executable instructions.

[0018] Fourthly, embodiments of this disclosure provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the first aspect and any of the methods in the possible implementations of the first aspect.

[0019] This disclosure provides a scheme for obtaining current vehicle driving information and corresponding obstacle information. The current vehicle driving information includes the first position information of the current vehicle and the operation information of the relevant personnel controlling the current vehicle. The obstacle information of the current vehicle includes the second position information of each obstacle among at least one obstacle within a first preset geographical range from the current vehicle. The scheme involves determining a corresponding target reference line based on the driving information. The target reference line includes at least one of the following: a centerline indicating the lane the current vehicle is in, a target lane line currently crossed by the current vehicle, or a preset planned route corresponding to the current vehicle. The scheme also involves determining a target coordinate system corresponding to the target reference line and determining the target speed curve of the current vehicle during autonomous driving based on the target coordinate system and obstacle information. Different target coordinate systems can be constructed based on the first position information of the current vehicle and the operation information of the relevant personnel controlling the current vehicle. The target speed curve is then constructed by combining the obstacle information. This target speed curve is determined based on the current vehicle driving information and the intentions of the relevant personnel, which can avoid situations where the planned target speed curve does not meet the driver's expectations, improving the rationality, accuracy, and reliability of the target speed curve, thereby improving vehicle driving safety and traffic efficiency, as well as driver comfort. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments or related technologies of this disclosure, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0021] Figure 1 A schematic flowchart illustrating a method for determining a vehicle speed curve, provided as an exemplary embodiment of this disclosure;

[0022] Figure 2 This is a schematic diagram of a first scene of the current vehicle and obstacles in the Frenet coordinate system provided in an embodiment of this disclosure;

[0023] Figure 3 This is a schematic diagram of a second scene in the Frenet coordinate system, showing the current vehicle and obstacles, provided in an embodiment of this disclosure.

[0024] Figure 4 This is a schematic diagram of a third scene in the Frenet coordinate system, showing the current vehicle and obstacles, according to an embodiment of this disclosure.

[0025] Figure 5 This is a schematic diagram of a vehicle speed curve determination device provided in an embodiment of the present disclosure;

[0026] Figure 6 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present disclosure. Detailed Implementation

[0027] Embodiments of this disclosure are described in detail below, with examples of these embodiments illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting it.

[0028] The terms "first" and "second," etc., used in the specification, claims, and drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the present disclosure described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] First, some terms used in the embodiments of this disclosure will be explained below to facilitate understanding by those skilled in the art.

[0030] The Lattice algorithm is an algorithm used in computer science and mathematics to search for optimal solutions in a finite discrete dataset.

[0031] The QP algorithm (Quadratic Programming) refers to an optimization problem with a quadratic objective function and constraints.

[0032] Yaw rate: The angular velocity of the car's mass as it rotates around the z-axis (car coordinate system).

[0033] A geographic coordinate system is a coordinate system that uses a three-dimensional sphere to define the location on the Earth's surface, enabling the reference of points on the Earth's surface via latitude and longitude.

[0034] Autonomous driving is a technology that enables driverless operation through computer systems. In autonomous driving, the speed curve describes the speed changes of a vehicle along a planned path during path planning. It is typically used to control the vehicle's acceleration and deceleration to achieve smooth, safe, and efficient driving. In related technologies, when planning speed curves, only the operating states of the vehicle and the target vehicle are usually considered. The longitudinal decisions made may contradict the driver's intentions, potentially resulting in speed curves that include acceleration or deceleration processes that do not meet the driver's expectations. This can lead to poor vehicle safety and driver comfort. Therefore, this disclosure provides a method, apparatus, electronic device, and computer medium for determining a vehicle speed curve to address the technical problems of poor vehicle safety and driver comfort in related technologies.

[0035] The technical solutions of this disclosure and how they solve the aforementioned technical problems will be 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 repeated in some embodiments. The embodiments of this disclosure will now be described with reference to the accompanying drawings.

[0036] Figure 1 This is a flowchart illustrating a method for determining a vehicle speed curve, provided as an exemplary embodiment of the present disclosure. The method is applicable to terminal devices (such as smartphones, personal computers, tablets, servers, etc.), and the terminal device may be equipped with an autonomous driving system for the vehicle. The method includes at least the following steps S1-S4:

[0037] S1. Obtain the driving information of the current vehicle and the obstacle information corresponding to the current vehicle. The driving information of the current vehicle includes the first location information of the current vehicle and the operation information of the relevant personnel controlling the current vehicle. The obstacle information corresponding to the current vehicle includes the second location information of each obstacle in at least one obstacle within a first preset geographical range from the current vehicle.

[0038] In some embodiments, the current vehicle may include, but is not limited to, cars, trucks, buses, trailers, etc.

[0039] In some embodiments, the first position information of the current vehicle can be the coordinate information of the current vehicle in an initial coordinate system. The first position information can include the coordinate range corresponding to the outline of the current vehicle, or it can be the coordinates of the corner points of the current vehicle. The corner points of the vehicle can refer to the corners of the vehicle's shape (such as the front, rear, or four corners of the vehicle). The initial coordinate system can be a geographic coordinate system, a world coordinate system, etc., and the first position information can be collected by a relevant module with GPS functionality in the current vehicle.

[0040] In some embodiments, the person controlling the current vehicle may be the driver of the current vehicle or a technician who remotely controls the current vehicle; the operation information for the current vehicle may include actions such as turning the turn signal on / off, turning the steering wheel counterclockwise / clockwise, and honking the horn.

[0041] In some embodiments, the second position information may be the coordinate information of the obstacle in the initial coordinate system. The second position information may include the coordinate range corresponding to the outline of the obstacle, or it may be the coordinates of the corner point of the obstacle. The corner point of the obstacle may be the corner of the obstacle's shape.

[0042] In some optional embodiments provided in this disclosure, the driving information further includes first speed information, first acceleration information, and first heading information of the current vehicle, and the obstacle information further includes the type of obstacle, second speed information, second acceleration information, and second heading information. The first heading information can be the orientation or direction of travel of the current vehicle, and the second heading information can be the orientation or direction of travel of the obstacle. Specifically, the first heading information and the second heading information can be in the form of angles or direction vectors. Obstacles can include various types such as vehicles, trees, pedestrians, and warning signs. This obstacle information can be acquired by sensors such as cameras or millimeter-wave radar in the current vehicle.

[0043] S2. Determine the corresponding target reference line based on the driving information. The target reference line includes at least one of the following: the center line of the lane in which the current vehicle is located, the target lane line that the current vehicle is currently crossing, and the preset planned route corresponding to the current vehicle.

[0044] In some embodiments, the lane currently occupied by the vehicle may include two lane lines on the left and right sides. When the operation information is to control the steering wheel to turn counterclockwise, the target lane line currently crossed by the vehicle can be the left lane line of the lane currently occupied by the vehicle. When the operation information is to control the steering wheel to turn clockwise, the target lane line currently crossed by the vehicle can be the right lane line of the lane currently occupied by the vehicle.

[0045] In some embodiments, the preset planned route corresponding to the current vehicle can be a driving path automatically planned by the autonomous driving system for the current vehicle. For specific planning methods, please refer to relevant technologies, which will not be elaborated here.

[0046] In some optional embodiments provided in this disclosure, in S2, the corresponding target reference line is determined based on the driving information, including S21-S24:

[0047] S21. Obtain the first location information and the operation information included in the driving information;

[0048] S22. When the first location information indicates that the current vehicle has not crossed the lane line, and the operation information indicates that the relevant personnel have not turned on the turn signal and have not controlled the steering wheel to turn, the center line and the preset planned route are both determined as the corresponding target reference lines.

[0049] In some embodiments, the lane lines can be any lane lines.

[0050] S23. When the first location information indicates that the current vehicle has crossed the lane line, and the operation information indicates that the relevant personnel have not turned on the turn signal, the target lane line and the preset planned route are both determined as the corresponding target reference lines.

[0051] In some embodiments, the method for determining whether a vehicle has crossed a lane line further includes S01-S04:

[0052] S01. Obtain lane line position information of candidate lane lines within the second preset geographical range of the current vehicle. The lane line position information can be a fitted polynomial curve or a series of discrete point coordinates in the initial coordinate system.

[0053] S02. Determine the coordinates of the center point of the current vehicle based on the first location information. The center point of the current vehicle may be the geometric center of the current vehicle.

[0054] S03. Calculate the lateral distance between the coordinates of the center point and the candidate lane line. The lateral distance between the coordinates of the center point and the candidate lane line is used to indicate the lateral offset between the current vehicle and the candidate lane line.

[0055] S04. When the lateral distance is greater than a preset distance, the first location information is determined to indicate that the current vehicle has crossed the lane line; when the lateral distance is not greater than the preset distance, the first location information is determined to indicate that the current vehicle has not crossed the lane line.

[0056] In other embodiments, sensors of the current vehicle, such as lidar or cameras, can also be used to detect whether the vehicle is crossing lane lines.

[0057] S24. When the operation information instructs the relevant personnel to turn on the turn signal and control the steering wheel to turn, the preset planned route is determined as the corresponding target reference line.

[0058] In some embodiments, the preset planned route may be determined based on the operation information. For example, when the turn signal is to the left and the person in charge controls the steering wheel to turn counterclockwise, the preset planned route may be a route from the current lane of the vehicle to the adjacent lane on the left.

[0059] S3. Determine the target coordinate system corresponding to the target reference line;

[0060] In some embodiments, there may be one or more target reference lines, and correspondingly, there may be one or more target reference systems.

[0061] In some optional embodiments provided in this disclosure, the origin of the target coordinate system is the reference point position information included in the first position information. The reference point position information can be the coordinates of any coordinate point within the outline range of the current vehicle indicated by the first position information, for example, the coordinates of the geometric center point of the current vehicle.

[0062] In some embodiments, when the target reference line includes the center line, the target coordinate system includes a first coordinate system with the center line as the reference line; when the target reference line includes the target lane line, the target coordinate system includes a second coordinate system with the target lane line as the reference line; and when the target reference line includes the preset planned route, the target coordinate system includes a third coordinate system with the preset planned route as the reference line.

[0063] In some embodiments, the target coordinate system can be a Frenet coordinate system, which is a coordinate system describing points on a curve and used to represent the position of a vehicle or object relative to a road or trajectory. When the target reference line includes the centerline, the S-axis of the corresponding first coordinate system (Frenet coordinate system) is along the curve direction of the centerline; when the target reference line includes the target lane line, the S-axis of the corresponding second coordinate system (Frenet coordinate system) is along the curve direction of the target lane line; when the target reference line includes a preset planned route, the S-axis of the corresponding third coordinate system (Frenet coordinate system) is along the curve direction of the preset planned route.

[0064] S4. Determine the target speed curve of the current vehicle during the autonomous driving process based on the target coordinate system and the obstacle information.

[0065] In some embodiments, the target speed curve can be used to describe the speed change of the current vehicle on a preset planned route, and can represent the expected speed that the current vehicle is to reach along the planned route.

[0066] In some optional embodiments provided in this disclosure, in S4, the target speed curve corresponding to the current vehicle during autonomous driving is determined based on the target coordinate system and the obstacle information, including S41-S42:

[0067] S41. Based on the target coordinate system and the second position information included in the obstacle information, determine whether the at least one obstacle includes a target obstacle that meets the preset conditions;

[0068] In some embodiments, the target obstacle can serve as the following target for the current vehicle during autonomous driving. The following target can refer to the target vehicle that the vehicle is tracking and maintaining in the autonomous driving system. During the following process, the vehicle will adjust its speed and position according to the movement and behavior of the target vehicle in order to maintain a safe distance and driving trajectory from the target vehicle.

[0069] In some optional embodiments provided in this disclosure, in S41, determining whether the at least one obstacle includes a target obstacle that meets preset conditions based on the target coordinate system and the second position information included in the obstacle information includes S411-S413:

[0070] S411. Obtain preset coordinate transformation relationship and preset threshold information, wherein the preset coordinate transformation relationship includes the association between the initial coordinate system where the second position information is located and the target coordinate system;

[0071] In some embodiments, preset threshold information is used to filter at least one obstacle to obtain a target obstacle, specifically including a first threshold, a second threshold, and a third threshold. The first threshold can be a decision threshold in the S-axis direction, and the second and third thresholds can be decision thresholds in the L-axis direction.

[0072] In some embodiments, a first threshold, a second threshold, and a third threshold can be set according to the actual scenario. For example, when the first location information indicates that the current vehicle has not crossed the lane line, and the operation information indicates that the relevant personnel have not activated the turn signal and have not controlled the steering wheel, the first threshold can be 150 meters, and half the width of the current vehicle can be taken as the second threshold. The second threshold and the third threshold can be opposites of each other. When the first location information indicates that the current vehicle has crossed the lane line, and the operation information indicates that the relevant personnel have not activated the turn signal, the second threshold can be the maximum left offset (l_left) of the current vehicle, and the third threshold can be the maximum right offset (l_right) of the current vehicle. The maximum left offset (l_left) represents the maximum offset of the current vehicle's body relative to the left side of the target reference line, and the maximum right offset (l_right) represents the maximum offset of the current vehicle's body relative to the right side of the target reference line. The specific values ​​of the maximum left offset (l_left) and the maximum right offset (l_right) can be determined according to the above-mentioned preset coordinate transformation relationship and the first location information.

[0073] S412. Based on the preset coordinate transformation relationship and the second position information included in the obstacle information, determine the third position information corresponding to the second position information in the target coordinate system;

[0074] In some embodiments, when the target coordinate system is the Frenet coordinate system, the third position information corresponding to the second position information in the target coordinate system is used to represent the position boundary of the corresponding obstacle in the Frenet coordinate system, that is, the boundary position on the longitudinal axis and the transverse axis. The third position information may specifically include the longitudinal end coordinate (end_s) of the obstacle corresponding to the second position information in the direction indicated by the target reference line, and the transverse start coordinate (start_l) and transverse end coordinate (end_l) of the obstacle in the direction perpendicular to the target reference line.

[0075] In some embodiments, the third location information may further include the longitudinal starting coordinates (start_s) of the obstacle corresponding to the second location information in the direction indicated by the target reference line.

[0076] Wherein, the longitudinal start coordinate (start_s) represents the starting longitudinal position of the corresponding obstacle on the target reference line, that is, the longitudinal distance between the obstacle and the origin of the Frenet coordinate system; the longitudinal end coordinate (end_s) represents the ending longitudinal position of the corresponding obstacle on the target reference line, that is, the longitudinal distance between the obstacle and the origin of the Frenet coordinate system; the lateral start coordinate (start_l) represents the starting lateral position of the corresponding obstacle in the target coordinate system, that is, the lateral offset vector of the obstacle in the target coordinate system; the lateral end coordinate (end_l) represents the ending lateral position of the corresponding obstacle in the target coordinate system, that is, the lateral offset vector of the obstacle in the target coordinate system.

[0077] The above solution describes the location and extent of obstacles more accurately by determining the starting and ending longitudinal positions of obstacles on the target reference line and providing the lateral offset of obstacles in the target coordinate system. This is beneficial for avoiding collisions between the current vehicle and obstacles, for path planning, and for making decisions in autonomous driving.

[0078] S413. Based on the third location information and the preset threshold information, determine whether the at least one obstacle includes a target obstacle that meets the preset conditions.

[0079] In some optional embodiments provided in this disclosure, in S413, determining whether the at least one obstacle includes a target obstacle that meets the preset conditions based on the third position information and the preset threshold information includes: determining that the at least one obstacle includes a target obstacle that meets the preset conditions if the longitudinal termination coordinate included in the third position information is less than the first threshold, the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold.

[0080] In some embodiments, when the longitudinal termination coordinate included in the third location information is not less than the first threshold, or the lateral start coordinate is not less than the second threshold, or the lateral termination coordinate is not greater than the third threshold, it is determined that the at least one obstacle does not include a target obstacle that meets the preset conditions.

[0081] In some optional embodiments provided in this disclosure, when the at least one obstacle includes a target obstacle that meets preset conditions, the method further includes S21-S23:

[0082] S21. For each obstacle among the at least one obstacle, if the longitudinal termination coordinate included in the third position information of the obstacle is less than the first threshold, the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold, then the obstacle is determined as a candidate obstacle, and at least one candidate obstacle is obtained.

[0083] S22. For each candidate obstacle among the at least one candidate obstacle, based on the first position information and the second position information of the candidate obstacle, determine the distance between the candidate obstacle and the current vehicle, and obtain at least one distance between the at least one candidate obstacle and the current vehicle;

[0084] S23. Among the at least one candidate obstacle, the one with the smallest distance from the current vehicle is determined as the target obstacle that meets the preset conditions.

[0085] In some embodiments, when there are multiple target reference lines, i.e., multiple target coordinate systems are constructed, for each of the multiple target coordinate systems, the following steps can be performed: S21, for each obstacle among the at least one obstacle, if the longitudinal termination coordinate included in the third position information of the obstacle is less than the first threshold, and the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold, then the obstacle is determined as a candidate obstacle, and at least one candidate obstacle is obtained. In this way, multiple candidate obstacles can be obtained, and the candidate obstacle with the smallest distance from the current vehicle is selected from the multiple candidate obstacles as the target obstacle that meets the preset conditions.

[0086] In the above scheme, by selecting target obstacles that are close to the current vehicle path as following targets, the decision-making and control process can be simplified. Using the Frenet coordinate system to select following targets can maintain a safe distance from the following targets to avoid potential collisions or dangerous situations. Furthermore, the following targets can be updated in real time according to changes in the dynamic environment to adapt to different traffic conditions, effectively improving the safety of vehicle driving.

[0087] S42. If so, then based on the driving information and the target obstacle information of the target obstacle, determine the target speed curve corresponding to the current vehicle during the autonomous driving process.

[0088] In some optional embodiments provided in this disclosure, in S42, determining the target speed curve corresponding to the current vehicle during autonomous driving based on the driving information and the target obstacle information of the target obstacle includes:

[0089] Based on the first position information, first speed information, and first acceleration information included in the driving information, and the second position information, second speed information, and second acceleration information included in the target obstacle information, a preset algorithm is used to determine the target speed curve corresponding to the current vehicle during the autonomous driving process.

[0090] In some embodiments, the preset algorithm can be a speed planning algorithm commonly used in related technologies, such as the sampling-based Lattice algorithm or the numerical optimization-based QP algorithm.

[0091] This disclosure provides the acquisition of current vehicle driving information and corresponding obstacle information. The current vehicle driving information includes the vehicle's first position information, first speed information, and first acceleration information, as well as the operation information of the personnel controlling the vehicle. The corresponding obstacle information includes the second position information, second speed information, and second acceleration information of each obstacle within a first preset geographical range from the vehicle. Based on the driving information, a corresponding target reference line is determined. The target reference line includes at least one of the following: a centerline indicating the lane the vehicle is currently in, a target lane line currently being crossed by the vehicle, or a preset planned route corresponding to the vehicle. The target reference line is then used to determine the relative positions of the target reference lines. The target coordinate system is used to determine the target speed curve of the vehicle during autonomous driving based on the target coordinate system and obstacle information. Different target coordinate systems can be constructed based on the vehicle's first position information, first speed information, first acceleration information, and the operation information of the relevant personnel controlling the vehicle. Then, the target speed curve of the vehicle is constructed by combining the obstacle information. This target speed curve is determined based on the vehicle's driving information and the intentions of the relevant personnel. This can avoid the situation where the planned target speed curve does not meet the driver's expectations, improve the rationality, accuracy and reliability of the target speed curve, and thus improve the safety and traffic efficiency of vehicle driving, as well as the comfort of the driver.

[0092] Furthermore, the following section provides a detailed explanation of this solution in specific scenarios.

[0093] Based on the above steps S22-S24, driving scenarios can be divided into the following three types:

[0094] Scenario 1: The vehicle has not crossed the lane lines, and the occupants have not activated the turn signal or turned the steering wheel. In this scenario, the vehicle can be considered to be controlled solely by the autonomous driving system.

[0095] Figure 2 This is a schematic diagram of a first scene in the Frenet coordinate system, showing the current vehicle and obstacles, according to an embodiment of this disclosure. Figure 2The current vehicle is in the first lane. Taking the current vehicle's direction of travel as the orientation, the second lane is adjacent to the left of the first lane. Within a first preset geographical area, obstacles A, B, and C are included. Two Frenet coordinate systems are constructed based on the centerline of the current vehicle's lane and the planned driving path (preset planned route) for the current vehicle, respectively. Obstacles are then filtered based on the information of each obstacle. Assuming obstacle B is selected as the candidate obstacle by the Frenet coordinate system based on the centerline, and obstacles A and B are selected as candidate obstacles by the Frenet coordinate system based on the preset planned route, then obstacle A, which is closest to the current vehicle, is selected as the target obstacle from all candidate obstacles (obstacle A and obstacle B) selected by the two coordinate systems. The target speed curve is then determined based on the obstacle information of obstacle A.

[0096] Scenario 2: The vehicle crosses the lane line, and the occupants have not activated their turn signals. In this situation, the vehicle crossing the lane line could be the result of the autonomous driving system or the occupants actively controlling the steering wheel.

[0097] Figure 3 This is a schematic diagram of a second scene in the Frenet coordinate system, showing the current vehicle and obstacles, according to an embodiment of this disclosure. Figure 3 The current vehicle crosses the target lane line between the first and second lanes, within a first preset geographical area, including obstacles D, E, and F. Two Frenet coordinate systems are constructed: one based on the target lane line crossed by the current vehicle, and the other on the planned driving path (preset planned route) for the current vehicle. Obstacles are then filtered based on the information of each obstacle. Assuming obstacle F is the candidate obstacle filtered using the Frenet coordinate system based on the target lane line, and obstacle E is the candidate obstacle filtered using the Frenet coordinate system based on the preset planned route, then from all candidate obstacles (obstacles F and E) filtered by the two coordinate systems, the closest candidate obstacle E to the current vehicle is selected as the target obstacle. The target speed curve is then determined based on the obstacle information of obstacle E.

[0098] Scenario 3: When the relevant personnel turn on the turn signal and control the steering wheel, it can be assumed that the relevant personnel intend to change lanes. That is, the current vehicle is in "human-machine co-driving" mode. In the "human-machine co-driving" mode, in scenarios where fully autonomous driving cannot be guaranteed, the task of driving the vehicle will be jointly undertaken by the natural driver and the autonomous driving system.

[0099] Figure 4 This is a schematic diagram of a third scene in the Frenet coordinate system, showing the current vehicle and obstacles, according to an embodiment of this disclosure. Figure 4The current vehicle is in the first lane. Taking the current vehicle's direction of travel as the orientation, the second lane is adjacent to the left of the first lane. Within a first preset geographical area, obstacles G, H, and I are included. A Frenet coordinate system is constructed based on the planned driving path (preset planned route) for the current vehicle, and obstacle filtering is performed based on the obstacle information. Assuming that the candidate obstacles obtained from the Frenet coordinate system constructed based on the preset planned route are obstacles G and I, then among all candidate obstacles (obstacle G and obstacle I), the candidate obstacle G closest to the current vehicle is selected as the target obstacle, and then the target speed curve is determined based on the obstacle information of obstacle G.

[0100] The specific process for selecting target obstacles can be found in the steps described in S21-S23 above, and will not be repeated here.

[0101] Figure 5 A schematic diagram of the structure of a data processing apparatus provided for an exemplary embodiment of this disclosure;

[0102] The device includes:

[0103] The acquisition unit 51 is used to acquire the driving information of the current vehicle and the obstacle information corresponding to the current vehicle. The driving information of the current vehicle includes the first position information of the current vehicle and the operation information of the relevant personnel controlling the current vehicle. The obstacle information corresponding to the current vehicle includes the second position information of each obstacle in at least one obstacle within a first preset geographical range from the current vehicle.

[0104] The determining unit 52 is used to determine the corresponding target reference line based on the driving information. The target reference line includes at least one of the following: the center line of the lane in which the current vehicle is located, the target lane line currently crossed by the current vehicle, and the preset planned route corresponding to the current vehicle.

[0105] The determining unit 52 is also used to determine the target coordinate system corresponding to the target reference line;

[0106] The determining unit 52 is further configured to determine the target speed curve corresponding to the current vehicle during the autonomous driving process based on the target coordinate system and the obstacle information.

[0107] In some optional embodiments provided in this disclosure, when determining the corresponding target reference line based on the driving information, the determining unit 52 is specifically used for:

[0108] Obtain the first location information and the operation information included in the driving information;

[0109] When the first location information indicates that the current vehicle has not crossed the lane line, and the operation information indicates that the relevant personnel have not turned on the turn signal and have not controlled the steering wheel to turn, the center line and the preset planned route are both determined as the corresponding target reference lines;

[0110] When the first location information indicates that the current vehicle has crossed the lane line, and the operation information indicates that the relevant personnel have not turned on the turn signal, the target lane line and the preset planned route are both determined as the corresponding target reference lines;

[0111] When the operation information instructs the relevant personnel to turn on the turn signal and control the steering wheel to turn, the preset planned route is determined as the corresponding target reference line.

[0112] In some optional embodiments provided in this disclosure, the origin of the target coordinate system is the reference point position information included in the first position information. When the target reference line includes the center line, the target coordinate system includes a first coordinate system with the center line as the reference line. When the target reference line includes the target lane line, the target coordinate system includes a second coordinate system with the target lane line as the reference line. When the target reference line includes the preset planned route, the target coordinate system includes a third coordinate system with the preset planned route as the reference line.

[0113] In some optional embodiments provided in this disclosure, when determining the target speed curve corresponding to the current vehicle during autonomous driving based on the target coordinate system and the obstacle information, the determining unit 52 is specifically used for:

[0114] Based on the target coordinate system and the second position information included in the obstacle information, determine whether the at least one obstacle includes a target obstacle that meets the preset conditions;

[0115] If so, the target speed curve corresponding to the current vehicle during autonomous driving is determined based on the driving information and the target obstacle information.

[0116] In some optional embodiments provided in this disclosure, when determining whether the at least one obstacle includes a target obstacle that meets preset conditions based on the target coordinate system and the second position information included in the obstacle information, the determining unit 52 is specifically used for:

[0117] Obtain preset coordinate transformation relationship and preset threshold information, wherein the preset coordinate transformation relationship includes the association between the initial coordinate system where the second position information is located and the target coordinate system;

[0118] Based on the preset coordinate transformation relationship and the second position information included in the obstacle information, the third position information corresponding to the second position information in the target coordinate system is determined;

[0119] Based on the third location information and the preset threshold information, determine whether the at least one obstacle includes a target obstacle that meets the preset conditions.

[0120] In some optional embodiments provided in this disclosure, the third location information includes the longitudinal termination coordinates of the corresponding obstacle in the direction indicated by the target reference line, and the lateral start coordinates and lateral termination coordinates of the obstacle in the direction perpendicular to the target reference line; the preset threshold information includes a first threshold, a second threshold, and a third threshold;

[0121] When determining whether the at least one obstacle includes a target obstacle that meets preset conditions based on the third location information and the preset threshold information, the determining unit 52 is specifically used for:

[0122] If the longitudinal termination coordinate included in the third location information is less than the first threshold, the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold, then it is determined that the at least one obstacle includes a target obstacle that meets the preset conditions.

[0123] In some optional embodiments provided in this disclosure, when the at least one obstacle includes a target obstacle that meets preset conditions, the device is further configured to:

[0124] For each obstacle among the at least one obstacle, if the longitudinal termination coordinate included in the third position information of the obstacle is less than the first threshold, the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold, then the obstacle is determined as a candidate obstacle, and at least one candidate obstacle is obtained.

[0125] For each of the at least one candidate obstacle, based on the first location information and the second location information of the candidate obstacle, the distance between the candidate obstacle and the current vehicle is determined, thereby obtaining at least one distance between the at least one candidate obstacle and the current vehicle;

[0126] The candidate obstacle with the smallest distance from the current vehicle among the at least one candidate obstacles is determined as the target obstacle that meets the preset conditions.

[0127] In some optional embodiments provided in this disclosure, the driving information further includes first speed information and first acceleration information of the current vehicle, and the target obstacle information further includes second speed information and second acceleration information of the target obstacle. When determining the target speed curve corresponding to the current vehicle during autonomous driving based on the driving information and the target obstacle information, the determining unit 52 is specifically used for:

[0128] Based on the first position information, first speed information, and first acceleration information included in the driving information, and the second position information, second speed information, and second acceleration information included in the target obstacle information, a preset algorithm is used to determine the target speed curve corresponding to the current vehicle during the autonomous driving process.

[0129] It should be understood that the device embodiments and method embodiments can correspond to each other, and similar descriptions can be referred to the method embodiments. To avoid repetition, they will not be repeated here. Specifically, the device can execute the above method embodiments, and the foregoing and other operations and / or functions of each module in the device correspond to the corresponding processes in the various methods in the above method embodiments, which will not be repeated here for the sake of brevity.

[0130] The apparatus of this disclosure embodiment has been described above from the perspective of functional modules in conjunction with the accompanying drawings. It should be understood that this functional module can be implemented in hardware, in software instructions, or in a combination of hardware and software modules. Specifically, the steps of the method embodiments in this disclosure can be completed by integrated logic circuits in the processor's hardware and / or by software instructions. The steps of the method disclosed in this disclosure embodiment can be directly embodied as being executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. Optionally, the software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps in the above method embodiments.

[0131] Figure 6 This is a schematic block diagram of an electronic device provided in an embodiment of this disclosure. The electronic device may include:

[0132] The system includes a memory 701 and a processor 702. The memory 701 stores computer programs and transfers the program code to the processor 702. In other words, the processor 702 can retrieve and run the computer programs from the memory 701 to implement the methods described in this embodiment.

[0133] For example, the processor 702 can be used to execute the above-described method embodiments according to instructions in the computer program.

[0134] In some embodiments of this disclosure, the processor 702 may include, but is not limited to:

[0135] General-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0136] In some embodiments of this disclosure, the memory 701 includes, but is not limited to:

[0137] Volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0138] In some embodiments of this disclosure, the computer program may be divided into one or more modules, which are stored in the memory 701 and executed by the processor 702 to perform the method provided in this disclosure. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0139] like Figure 6 As shown, the electronic device may further include:

[0140] Transceiver 703, which can be connected to processor 702 or memory 701.

[0141] The processor 702 can control the transceiver 703 to communicate with other devices; specifically, it can send information or data to other devices or receive information or data sent by other devices. The transceiver 703 may include a transmitter and a receiver. The transceiver 703 may further include antennas, and the number of antennas may be one or more.

[0142] It should be understood that the various components in the electronic device are connected through a bus system, which includes a data bus, a power bus, a control bus, and a status signal bus.

[0143] This disclosure also provides a computer storage medium storing a computer program thereon, which, when executed by a computer, enables the computer to perform the methods of the above-described method embodiments. Alternatively, embodiments of this disclosure also provide a computer program product containing instructions that, when executed by a computer, cause the computer to perform the methods of the above-described method embodiments.

[0144] When implemented using software, it can be implemented wholly or partially as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this disclosure are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0145] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0146] In the embodiments provided in this disclosure, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0147] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. For example, the functional modules in the various embodiments of this disclosure may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0148] The above are merely specific embodiments of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for determining a vehicle speed curve, characterized in that, include: The vehicle obtains driving information of the current vehicle and obstacle information corresponding to the current vehicle. The driving information of the current vehicle includes the first location information of the current vehicle and the operation information of the relevant personnel controlling the current vehicle. The obstacle information corresponding to the current vehicle includes the second location information of each obstacle in at least one obstacle within a first preset geographical range from the current vehicle. The target reference line is determined based on the driving information. The target reference line includes at least one of the following: the center line of the lane in which the current vehicle is located, the target lane line that the current vehicle is currently crossing, and the preset planned route corresponding to the current vehicle. Determine the target coordinate system corresponding to the target reference line; The target speed curve of the current vehicle during autonomous driving is determined based on the target coordinate system and the obstacle information. Determining the corresponding target reference line based on the driving information includes: Obtain the first location information and the operation information included in the driving information; When the first location information indicates that the current vehicle has not crossed the lane line, and the operation information indicates that the relevant personnel have not turned on the turn signal and have not controlled the steering wheel to turn, the center line and the preset planned route are both determined as the corresponding target reference lines; When the first location information indicates that the current vehicle has crossed the lane line, and the operation information indicates that the relevant personnel have not turned on the turn signal, the target lane line and the preset planned route are both determined as the corresponding target reference lines; When the operation information instructs the relevant personnel to turn on the turn signal and control the steering wheel to turn, the preset planned route is determined as the corresponding target reference line.

2. The method according to claim 1, characterized in that, The origin of the target coordinate system is the reference point position information included in the first position information. When the target reference line includes the center line, the target coordinate system includes a first coordinate system with the center line as the reference line. When the target reference line includes the target lane line, the target coordinate system includes a second coordinate system with the target lane line as the reference line. When the target reference line includes the preset planned route, the target coordinate system includes a third coordinate system with the preset planned route as the reference line.

3. The method according to claim 1, characterized in that, Determining the target speed curve of the current vehicle during autonomous driving based on the target coordinate system and the obstacle information includes: Based on the target coordinate system and the second position information included in the obstacle information, determine whether the at least one obstacle includes a target obstacle that meets the preset conditions; If so, the target speed curve corresponding to the current vehicle during autonomous driving is determined based on the driving information and the target obstacle information.

4. The method according to claim 3, characterized in that, Determining whether the at least one obstacle includes a target obstacle that meets preset conditions, based on the target coordinate system and the second position information included in the obstacle information, includes: Obtain preset coordinate transformation relationship and preset threshold information, wherein the preset coordinate transformation relationship includes the association between the initial coordinate system where the second position information is located and the target coordinate system; Based on the preset coordinate transformation relationship and the second position information included in the obstacle information, the third position information corresponding to the second position information in the target coordinate system is determined; Based on the third location information and the preset threshold information, determine whether the at least one obstacle includes a target obstacle that meets the preset conditions.

5. The method according to claim 4, characterized in that, The third location information includes the longitudinal termination coordinates of the corresponding obstacle in the direction indicated by the target reference line, and the lateral start coordinates and lateral termination coordinates of the obstacle in the direction perpendicular to the target reference line; the preset threshold information includes a first threshold, a second threshold, and a third threshold; Determining whether the at least one obstacle includes a target obstacle that meets preset conditions based on the third location information and the preset threshold information includes: If the longitudinal termination coordinate included in the third location information is less than the first threshold, the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold, then it is determined that the at least one obstacle includes a target obstacle that meets the preset conditions.

6. The method according to claim 5, characterized in that, When the at least one obstacle includes a target obstacle that meets preset conditions, the method further includes: For each obstacle among the at least one obstacle, if the longitudinal termination coordinate included in the third position information of the obstacle is less than the first threshold, the lateral start coordinate is less than the second threshold, and the lateral termination coordinate is greater than the third threshold, then the obstacle is determined as a candidate obstacle, and at least one candidate obstacle is obtained. For each of the at least one candidate obstacle, based on the first location information and the second location information of the candidate obstacle, the distance between the candidate obstacle and the current vehicle is determined, thereby obtaining at least one distance between the at least one candidate obstacle and the current vehicle; The candidate obstacle with the smallest distance from the current vehicle among the at least one candidate obstacles is determined as the target obstacle that meets the preset conditions.

7. The method according to claim 3, characterized in that, The driving information also includes the first speed information and first acceleration information of the current vehicle, and the target obstacle information also includes the second speed information and second acceleration information of the target obstacle. Based on the driving information and the target obstacle information, the target speed curve corresponding to the current vehicle during autonomous driving is determined, including: Based on the first position information, first speed information, and first acceleration information included in the driving information, and the second position information, second speed information, and second acceleration information included in the target obstacle information, a preset algorithm is used to determine the target speed curve corresponding to the current vehicle during the autonomous driving process.

8. A vehicle speed curve determination apparatus, suitable for performing the vehicle speed curve determination method according to any one of claims 1-7, characterized in that, include: The acquisition unit is used to acquire the driving information of the current vehicle and the obstacle information corresponding to the current vehicle. The driving information of the current vehicle includes the first location information of the current vehicle and the operation information of the relevant personnel driving the current vehicle. The obstacle information corresponding to the current vehicle includes the second location information of each obstacle among at least one obstacle within a first preset geographical range from the current vehicle. The determining unit is configured to determine a corresponding target reference line based on the driving information. The target reference line includes at least one of the following: a center line indicating the lane in which the current vehicle is located, a target lane line currently crossed by the current vehicle, or a preset planned route corresponding to the current vehicle. The determining unit is also used to determine the target coordinate system corresponding to the target reference line; The determining unit is further configured to determine the target speed curve of the current vehicle during autonomous driving based on the target coordinate system and the obstacle information.

9. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the method of any one of claims 1-7 by executing the executable instructions.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-7.

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