Vehicle driving method, electronic equipment, vehicle and computer program product

Abstract

The invention relates to the technical field of automatic driving, in particular to a vehicle driving method, electronic equipment, a vehicle and a computer program product. In the method, an electronic device can obtain a planned path of a vehicle, the planned path can comprise a plurality of planned path points, and in the process that the vehicle travels along the planned path, when the vehicle passes through the planned path points, the electronic device can travel based on planned speeds corresponding to the planned path points. Wherein the planning speed corresponding to the planning path point can be determined based on planning parameters, the planning speeds corresponding to different planning path points are different, and the planning parameters can comprise a first speed corresponding to the curvature of the planning path point and a second speed at which the vehicle does not collide with the obstacle on the planning path point. Therefore, the safety of automatic driving of the vehicle can be improved, and the speed of the vehicle at each planned path point can be ensured to be within the psychological acceptable range of the user.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a vehicle driving method, electronic equipment, vehicle, and computer program product. Background Technology

[0002] During autonomous driving, if the onboard terminal detects that the distance between the vehicle and an obstacle is less than a pre-set safe distance, the onboard terminal can trigger emergency braking or lane changing. However, before the vehicle brakes or changes lanes, the user may have the illusion that a collision with the obstacle is imminent, causing the user to panic and prematurely and unnecessarily take over the vehicle. This reduces the usability of autonomous driving and the user experience. Summary of the Invention

[0003] To address the issues of low usability and poor user experience in autonomous driving, embodiments of this application provide a vehicle driving method, an electronic device, a vehicle, and a computer program product, including:

[0004] In a first aspect, embodiments of this application provide a vehicle driving method applied to an electronic device, comprising: acquiring a planned path of the vehicle, the planned path including multiple planned path points; during the process of the vehicle driving along the planned path, when passing each planned path point, driving based on the planned speed corresponding to the planned path point, wherein the planned speed corresponding to the planned path point is determined based on planning parameters, and the planning parameters include a first speed corresponding to the curvature of the planned path point and a second speed at which the vehicle does not collide with obstacles at the planned path point.

[0005] It can be understood that the first velocity corresponding to the curvature of the path planning point can be: the highest velocity at which the user will not panic under the curvature of the path planning point. The specific value of this highest velocity can be determined based on the speed at which users of different age groups panic under different curvatures.

[0006] It can be understood that the second speed at which a vehicle does not collide with an obstacle at a planned path point can be: the speed at which the vehicle does not collide with a static first obstacle and does not collide with a dynamic second obstacle at a planned path point.

[0007] Based on the above scheme, by combining the speed at which the user will not panic under the curvature of each planned path point and the speed at which the user will not collide with obstacles at each planned path point, the planned speed corresponding to each planned path point is determined. The vehicle driving is then controlled based on the planned speed corresponding to each planned path point. This can avoid the user having the illusion that "a collision with an obstacle is imminent" at each planned path point, and thus avoid the user taking over the vehicle prematurely and unnecessarily due to panic. This can improve the usability of autonomous driving and enhance the user experience.

[0008] In some implementations of the first aspect, the first velocity is determined by: determining the first velocity corresponding to the curvature of the planned path point based on a preset first mapping relationship between curvature and velocity, and the curvature of the planned path point.

[0009] In this embodiment, by determining the speed at which the user will not panic under the curvature of the planned path point, the planned speed corresponding to the planned path point can be determined subsequently. This can prevent the user from panicking and taking over the vehicle due to the curvature of the planned path point, thereby improving the availability of autonomous driving and the user experience.

[0010] In some implementations of the first aspect, the second speed is determined by: determining multiple candidate speeds at which the vehicle will not collide with any of the surrounding obstacles at the planned path point; and determining the minimum value among the multiple candidate speeds as the second speed.

[0011] In some implementations of the first aspect, the multiple obstacles include a static first obstacle, and multiple candidate speeds are determined so that the vehicle will not collide with each of the multiple surrounding obstacles at the planned path point, including: obtaining a first position of the planned path point and a second position of the first obstacle; determining a first distance between the first position and the second position; and determining a first candidate speed based on the first distance and a preset somatosensory collision time threshold.

[0012] In some implementations, the first candidate speed at which the vehicle will not collide with the static first obstacle at the planned path point S1i can be determined using formula (2):

[0013] V_static(S1i)=Di / TTC_comfort

[0014] Where V_static(S1i) can represent the first candidate speed at which the vehicle will not collide with the first obstacle at the planned path point S1i, Di can represent the first distance between the planned path point S1i and the first obstacle, and TTC_comfort can represent the time threshold for the perceived collision.

[0015] In this embodiment, by determining the speed at which the vehicle will not collide with a static first obstacle at a planned path point, and using this speed to determine the planned speed corresponding to that path point, the user can avoid panic and take over the vehicle due to the possibility of a collision with the first obstacle at the planned path point, thereby improving the usability of autonomous driving and the user experience. Furthermore, in determining the first candidate speed, by determining the candidate speed at each planned path point where the vehicle will not collide with the first obstacle—that is, by progressively limiting the candidate speed at a long distance where the vehicle will not collide with the first obstacle—the vehicle can be guided to smoothly and linearly reduce to a safe speed. This eliminates the abruptness of emergency braking when the distance between the vehicle and the first obstacle is less than a safe distance, making the user's riding experience more comfortable.

[0016] In some implementations of the first aspect, the multiple obstacles include dynamic second obstacles, and multiple candidate speeds are determined so that the vehicle will not collide with any of the surrounding obstacles at a planned path point. This includes: obtaining a first predicted driving path of the second obstacle, the first predicted driving path including multiple predicted path points; determining, from the multiple predicted path points, a predicted path point corresponding to each planned path point, a third position of the predicted path point corresponding to each planned path point, and a third speed of the second obstacle at the predicted path point corresponding to each planned path point; determining a second distance between the first position of each planned path point and the third position of the predicted path point corresponding to each planned path point; and determining a second candidate speed based on a preset second mapping relationship between distance and speed difference, the third speed, and the second distance.

[0017] In some implementations of the first aspect, determining the predicted path point corresponding to each planned path point from multiple predicted path points includes: determining the predicted path point with the smallest distance from each planned path point among multiple predicted path points as the predicted path point corresponding to each planned path point.

[0018] In some implementations of the first aspect, determining a second candidate speed based on a preset second mapping relationship between distance and speed difference, a third speed, and a second distance includes: determining a target speed difference based on the second mapping relationship and the second distance; the target speed difference being the speed difference between the vehicle and the second obstacle allowed when the distance between the vehicle and the second obstacle is the second distance; and determining the second candidate speed based on the third speed and the target speed difference.

[0019] In some implementations, the target velocity difference can be determined using the following formula:

[0020] ΔV=130 / 3.6*k*max(0,min(1,Dj / 1.5))

[0021] Wherein, ΔV can represent the speed difference between the vehicle and the second obstacle when the distance between the vehicle and the second obstacle is the second distance Dj, and k can represent the hazard factor. The specific value of k can be set according to the type of the second obstacle.

[0022] In some implementations, the second candidate speed can be determined using the following formula:

[0023] V_dynamic(S1i)=V_obstacle(S2j)+ΔV

[0024] Wherein, V_dynamic(S1i) can represent the second candidate speed at which the vehicle will not collide with the second obstacle at the planned path point S1i, V_obstacle(S2j) can represent the third speed of the second obstacle at the predicted path point S2j corresponding to the planned path point S1i, and ΔV can represent the speed difference between the vehicle and the second obstacle when the distance between the vehicle and the second obstacle is the second distance Dj.

[0025] In other implementations, the second candidate speed can also be determined using the following formula:

[0026] V_dynamic(S1i)=V_obstacle(S2j)-ΔV

[0027] Wherein, V_dynamic(S1i) can represent the second candidate speed at which the vehicle will not collide with the second obstacle at the planned path point S1i, V_obstacle(S2j) can represent the third speed of the second obstacle at the predicted path point S2j corresponding to the planned path point S1i, and ΔV can represent the speed difference between the vehicle and the second obstacle when the distance between the vehicle and the second obstacle is the second distance Dj.

[0028] In this embodiment, by determining the speed at which a collision with a dynamic second obstacle is avoided at a planned path point, and using this speed to determine the corresponding planned speed for that path point, the user can avoid panic and take over the vehicle at the planned path point due to the possibility of a collision with the second obstacle. This improves the usability of autonomous driving and the user experience. Furthermore, by determining a second candidate speed that is slightly higher or slightly lower than the obstacle's speed, rather than mechanically setting the second candidate speed to the obstacle's speed, the user's driving habits can be simulated, road space can be intelligently utilized, and unnecessary speed fluctuations can be reduced, thereby improving traffic efficiency and comfort.

[0029] In some implementations of the first aspect, the planned speed corresponding to the planned path point is the minimum of the first speed and the second speed.

[0030] In some implementations of the first aspect, the planning speed varies depending on the planning path point.

[0031] In a second aspect, embodiments of this application provide an electronic device, including: a memory for storing instructions executed by one or more processors of the electronic device, and a processor, which is one of the one or more processors of the electronic device, for executing the first aspect and any possible implementation of the vehicle driving method provided in the first aspect.

[0032] Thirdly, embodiments of this application provide a vehicle, including: electronic equipment provided in the second aspect or any possible implementation of the second aspect.

[0033] Fourthly, embodiments of this application provide a computer program product, which includes computer instructions. When executed by an electronic device, the electronic device performs the vehicle driving method provided in the first aspect and any possible implementation of the first aspect.

[0034] It is understood that the specific implementation methods and beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions of any vehicle driving method in the first aspect or any of the various implementation methods provided by the first aspect, and will not be repeated here. Attached Figure Description

[0035] Figure 1 Some application scenario diagrams are shown according to some embodiments of this application;

[0036] Figure 2 According to some embodiments of this application, a schematic flowchart of a vehicle driving method is shown;

[0037] Figure 3 According to some embodiments of this application, a schematic diagram of a planned path is shown;

[0038] Figure 4 According to some embodiments of this application, a flowchart illustrating a method for determining the planning speed corresponding to a planned path point is shown;

[0039] Figure 5 According to some embodiments of this application, a schematic diagram of a second position of a first obstacle is shown;

[0040] Figure 6 According to some embodiments of this application, a schematic diagram of a second position of another first obstacle is shown;

[0041] Figure 7 According to some embodiments of this application, a schematic diagram of a predicted path is shown;

[0042] Figure 8 A schematic diagram of a vehicle driving system is shown according to some embodiments of this application;

[0043] Figure 9 According to some embodiments of this application, a possible functional framework diagram of a vehicle 100 is shown. Detailed Implementation

[0044] The embodiments of this application include, but are not limited to, vehicle driving methods, electronic devices, vehicles, and computer program products.

[0045] It is understood that the vehicle driving method mentioned in the embodiments of this application can be applied to electronic devices. These electronic devices can be referred to as terminals, user equipment (UE), mobile stations (MS), or mobile terminals (MT), etc.

[0046] In some implementations, the electronic device can be a smartphone, smart TV, smartwatch, smart bracelet, desktop computer, laptop computer, personal computer (PC), virtual reality (VR) device, augmented reality (AR) device, wireless terminal in self-driving, terminal in transport safety (e.g., vehicle terminal), or other device capable of controlling vehicle movement.

[0047] like Figure 1 The diagram illustrates some application scenarios. During the autonomous driving process of a vehicle, when vehicle A detects a static first obstacle (such as...)... Figure 1 The isolation zone shown in (a) is as follows: Figure 1 (b) the guardrail shown in the middle) or a dynamic second obstacle (such as Figure 1 Vehicle B shown in (c) is as follows: Figure 1 Pedestrian C shown in (d) is as follows: Figure 1 If the distance between vehicles D) shown in (e) is less than a preset safe distance, the electronic device can trigger emergency braking or lane change of the vehicles.

[0048] However, before the vehicle brakes suddenly or changes lanes, users may have the illusion that they are about to collide with an obstacle. This can cause users to panic and take over the vehicle prematurely and unnecessarily, which reduces the usability of autonomous driving and the user experience.

[0049] To address the aforementioned problems, this application provides a vehicle driving method. In this method, an electronic device can acquire a planned path for the vehicle, which may include multiple planned path points. Furthermore, as the vehicle travels along the planned path, upon passing each planned path point, the electronic device can drive at a planned speed corresponding to that path point. The planned speed corresponding to each path point can be determined based on planning parameters; different path points correspond to different planned speeds. These planning parameters may include a first speed corresponding to the curvature of the path point and a second speed at which the vehicle will not collide with obstacles at the planned path point.

[0050] It can be understood that the first velocity corresponding to the curvature of the path planning point can be: the highest velocity at which the user will not panic under the curvature of the path planning point. The specific value of this highest velocity can be determined based on the speed at which users of different age groups panic under different curvatures.

[0051] It can be understood that the second speed at which a vehicle does not collide with an obstacle at a planned path point can be: the speed at which the vehicle does not collide with a static first obstacle and does not collide with a dynamic second obstacle at a planned path point.

[0052] In this way, by combining the speed at which the user will not panic under the curvature of each planned path point and the speed at which the user will not collide with obstacles at each planned path point, the planned speed corresponding to each planned path point can be determined. By controlling the vehicle's driving based on the planned speed corresponding to each planned path point, the user can avoid the illusion that "a collision with an obstacle is imminent" at each planned path point. This can prevent the user from taking over the vehicle prematurely and unnecessarily due to panic, thereby improving the usability of autonomous driving and enhancing the user experience.

[0053] The vehicle driving method mentioned in the embodiments of this application will be described in detail below. For example... Figure 2 The diagram illustrates a process flow chart for a vehicle driving method. This vehicle driving method can be executed by electronic devices, such as the vehicle-mounted terminal mentioned earlier.

[0054] For example, the vehicle driving method may include:

[0055] S201: Obtain the planned route of the vehicle, which includes multiple planned waypoints.

[0056] It is understandable that electronic devices can obtain the vehicle's navigation path and determine the navigation path within a preset distance as the planned path. For example, the navigation path within the next 150 meters, the navigation path within the next 100 meters, or the navigation path within the next 200 meters can be determined as the planned path.

[0057] It is understandable that a planned path can include multiple waypoints. For example... Figure 3 As shown, the planned path can be represented as multiple planned path points in the Frenet coordinate system, such as planned path point S11, planned path point S12, planned path point S13... planned path point S1i... planned path point S1n.

[0058] S202: During the vehicle's journey along the planned path, upon passing each planned path point, the vehicle travels at the planned speed corresponding to that path point. This planned speed is determined based on planning parameters. These planning parameters include a first speed corresponding to the curvature of the planned path point and a second speed at which the vehicle will not collide with obstacles at that path point.

[0059] In some implementations, the electronic device can determine a first velocity corresponding to the curvature of each planned path point, and a second velocity at which the vehicle will not collide with obstacles at each planned path point. Based on the first and second velocities, it determines the planned velocity corresponding to each planned path point. Furthermore, as the vehicle travels along the planned path, the electronic device can drive based on the planned velocity corresponding to each planned path point when passing through them.

[0060] It can be understood that the first velocity corresponding to the curvature of the path planning point can be: the highest velocity at which the user will not panic under the curvature of the path planning point. The specific value of this highest velocity can be determined based on the speed at which users of different age groups panic under different curvatures.

[0061] It can be understood that the second speed at which a vehicle does not collide with an obstacle at a planned path point can be: the speed at which the vehicle does not collide with a static first obstacle and does not collide with a dynamic second obstacle at a planned path point.

[0062] For example, the second speed at which a vehicle will not collide with an obstacle at a planned route point can be the minimum of the first candidate speed and the second candidate speed. The first candidate speed can be the speed at which the vehicle will not collide with a static first obstacle at the planned route point, and the second candidate speed can be the speed at which the vehicle will not collide with a dynamic second obstacle at the planned route point. Static first obstacles can include curbs, traffic cones, water-filled barriers, disabled vehicles, guardrails, medians, lampposts, traffic sign poles, signal poles, green belts, bridge piers, or tunnel walls, etc. Dynamic second obstacles can be traffic participants, such as other vehicles or pedestrians.

[0063] The following section uses the example of determining the planning speed corresponding to a planning path point in the planning path to introduce the specific implementation method of determining the planning speed corresponding to each planning path point in the planning path.

[0064] like Figure 4 The diagram illustrates a process for determining the planned speed corresponding to a planned path point. This process can be executed by electronic devices, such as the vehicle-mounted terminal mentioned earlier.

[0065] For example, the method for determining the planning speed corresponding to the planning path point may include:

[0066] S401: Determine the first velocity corresponding to the curvature of the planned path point.

[0067] It can be understood that the curvature (kappa) of a planned path point can represent the degree of curvature of the planned path at that point. Specifically, the greater the curvature of a planned path point, the more curved the planned path is at that point; conversely, the smaller the curvature of a planned path point, the less curved the planned path is at that point.

[0068] In some implementations, the electronic device can acquire the speed at which users of different age groups experience panic at different curvatures, and establish a primary mapping relationship between curvature and speed based on each curvature and its corresponding speed. The electronic device can then store this primary mapping relationship between curvature and speed.

[0069] In other implementations, the electronic device can determine the maximum speed at which the user will not experience panic under different curvatures, based on the vehicle's kinematics model and comfort indicators (such as lateral acceleration). Furthermore, the electronic device can determine a first mapping relationship between curvature and speed based on each curvature and its corresponding maximum speed. The electronic device can then store this first mapping relationship between curvature and speed.

[0070] The vehicle kinematic model can be represented by formula (1):

[0071] Vmax = (a y *R) 1 / 2 (1);

[0072] Where Vmax can represent the maximum speed at which the user will not panic under the curvature kappa of the path planning point, a y It can represent lateral acceleration (typically 0.3g~0.4g, g=9.8m / s²). 2 R can represent the reciprocal of the curvature kappa.

[0073] Thus, after obtaining the planned path of the vehicle, the electronic device can obtain the curvature of the planned path point S1i in the planned path, and determine the first speed V_curve(S1i) corresponding to the curvature of the planned path point S1i based on the first mapping relationship and the curvature of the planned path point S1i.

[0074] In this embodiment, by determining the speed at which the user will not panic under the curvature of the planned path point, the planned speed corresponding to the planned path point can be determined subsequently. This can prevent the user from panicking and taking over the vehicle due to the curvature of the planned path point, thereby improving the availability of autonomous driving and the user experience.

[0075] S402: Determine the first candidate speed at which the vehicle will not collide with the first obstacle at the planned path point.

[0076] In some methods of determining the first candidate velocity, the electronic device can acquire the first position of the planned path point S1i and the second position of the first obstacle, and determine the first distance Di between the first position and the second position. Then, the electronic device can acquire a preset haptic collision time threshold TTC_comfort, and determine the first candidate velocity V_static(S1i) based on the first distance Di and the preset haptic collision time threshold TTC_comfort.

[0077] Among them, the somatosensory collision time threshold can be represented as the minimum remaining time before the vehicle collides with the first obstacle, so that the user will not panic. That is, the minimum remaining time before the user feels psychologically comfortable and does not experience negative emotions such as tension or anxiety, such as 3 to 5 seconds.

[0078] It can be understood that the second position of the first obstacle can refer to the position of the first obstacle in the Frenet coordinate system corresponding to the planned path point S1i. For example, as... Figure 5 As shown, when the first obstacle is a guardrail, the second position can be the starting position of the guardrail shown in P1 in the Frenet coordinate system dos.

[0079] It can be understood that the second position of the first obstacle can also refer to: the position of the collision point in the Frenet coordinate system corresponding to the planned path point S1i when colliding with the first obstacle in the motion-sensing path generated based on the vehicle's heading angle (heading(i)) and curvature (kappa) at the planned path point S1i. Here, the motion-sensing path can be the path the user perceives the vehicle might take in the future, based on the vehicle's heading angle (heading(i)) and curvature at the planned path point S1i. For example, as... Figure 6 As shown, when the first obstacle is a guardrail, the second position can be the position in the Frenet coordinate system dos where the collision point will collide with the guardrail when the vehicle is traveling at that position, as shown in P2.

[0080] In some implementations, the electronic device can obtain the vehicle's orientation angle (heading(i)) and curvature at the planned path point S1i, and determine the vehicle's perceived path at the planned path point S1i (e.g., using a spiral curve algorithm, a Bézier curve algorithm, or a polynomial spiral curve algorithm) based on these parameters. Figure 6 (The path indicated by the dashed arrow).

[0081] In some implementations, the first candidate speed at which the vehicle will not collide with the static first obstacle at the planned path point S1i can be determined using formula (2):

[0082] V_static(S1i)=Di / TTC_comfort(2);

[0083] Where V_static(S1i) can represent the first candidate speed at which the vehicle will not collide with the first obstacle at the planned path point S1i, Di can represent the first distance between the planned path point S1i and the first obstacle, and TTC_comfort can represent the time threshold for the perceived collision.

[0084] For example, continue as Figure 5 As shown, for a planned path point S11 in the planned path of vehicle A, the electronic device can determine the first position of the planned path point S11 in the Frenet coordinate system, and the second position of the starting point P1 of the guardrail in the Frenet coordinate system. Then, the electronic device can determine the first distance D1 from the first position to the second position. Furthermore, the electronic device can determine the first candidate speed V_static(S11) at the planned path point S11 that will not collide with the first obstacle, based on the ratio of the first distance D1 to the perceived collision time threshold.

[0085] For example, such as Figure 6 As shown, for a planned path point S11 in the planned path of vehicle A, the electronic device can determine the first position of the planned path point S11 in the Frenet coordinate system, and the second position of the collision point P2 where the vehicle collides with the guardrail in the Frenet coordinate system. Then, the electronic device can determine the first distance D1 from the first position to the second position. Furthermore, based on the ratio of the first distance D1 to the perceived collision time threshold, the electronic device can determine the first candidate velocity V_static(S1) at which the vehicle will not collide with the first obstacle at the planned path point S11.

[0086] In this embodiment, by determining the speed at which the vehicle will not collide with a static first obstacle at a planned path point, and using this speed to determine the planned speed corresponding to that path point, the user can avoid panic and take over the vehicle due to the possibility of a collision with the first obstacle at the planned path point, thereby improving the usability of autonomous driving and the user experience. Furthermore, in determining the first candidate speed, by determining the candidate speed at each planned path point where the vehicle will not collide with the first obstacle—that is, by progressively limiting the candidate speed at a long distance where the vehicle will not collide with the first obstacle—the vehicle can be guided to smoothly and linearly reduce to a safe speed. This eliminates the abruptness of emergency braking when the distance between the vehicle and the first obstacle is less than a safe distance, making the user's riding experience more comfortable.

[0087] S403: Determine the second candidate speed at which the vehicle will not collide with the second obstacle at the planned waypoint.

[0088] It is understandable that the second candidate velocity can also be called the maximum penetration velocity.

[0089] In some methods of determining a second candidate speed, the electronic device may acquire a first predicted travel path to the second obstacle, which may include multiple predicted path points. For example... Figure 7 As shown, the predicted path can be represented as multiple predicted path points in the Frenet coordinate system, such as predicted path point S21, predicted path point S22 (not shown), predicted path point S23 (not shown)... predicted path point S2j... predicted path point S2m.

[0090] Next, the electronic device can determine, from multiple predicted path points, the predicted path point S2j corresponding to the planned path point S1i, the third position of the predicted path point S2j corresponding to the planned path point S1i, and the third velocity V_obstacle(S2j) of the second obstacle at the predicted path point S2j corresponding to the planned path point S1i. Here, the predicted path point S2j corresponding to the planned path point S1i can refer to the predicted path point with the smallest lateral distance from the planned path point S1i among the multiple predicted path points.

[0091] Then, the electronic device can determine a second distance Dj between the first position of the planned path point S1i and the third position of the predicted path point S2j corresponding to the planned path point S1i. The second distance Dj can represent the lateral distance between the first position of the planned path point S1i and the third position of the predicted path point S2j corresponding to the planned path point S1i.

[0092] Furthermore, the electronic device can obtain a second mapping relationship between a preset distance and speed difference, as well as a second distance, determine the target speed difference ΔV, and determine the second candidate speed V_dynamic (S1i) based on the third speed V_obstacle (S2j) and the target speed difference ΔV.

[0093] In some implementations, the target velocity difference can be determined using formula (3):

[0094] ΔV=130 / 3.6*k*max (0, min (1, Dj / 1.5)) (3);

[0095] Wherein, ΔV can represent the speed difference between the vehicle and the second obstacle when the distance between the vehicle and the second obstacle is the second distance Dj, and k can represent the hazard factor. The specific value of k can be set according to the type of the second obstacle.

[0096] In some implementations, the second candidate velocity can be determined using formula (4):

[0097] V_dynamic(S1i)=V_obstacle(S2j)+ΔV(4);

[0098] Wherein, V_dynamic(S1i) can represent the second candidate speed at which the vehicle will not collide with the second obstacle at the planned path point S1i, V_obstacle(S2j) can represent the third speed of the second obstacle at the predicted path point S2j corresponding to the planned path point S1i, and ΔV can represent the speed difference between the vehicle and the second obstacle when the distance between the vehicle and the second obstacle is the second distance Dj.

[0099] In this embodiment, by determining the speed at which a collision with a dynamic second obstacle will not occur at a planned path point, and using this speed to subsequently determine the planned speed for that path point, the user can avoid panic and take over the vehicle at the planned path point due to the possibility of a collision with the second obstacle. This improves the usability of autonomous driving and the user experience. Furthermore, by determining a second candidate speed slightly higher than the obstacle's speed, rather than mechanically setting the second candidate speed to the obstacle's speed, the user's driving habits can be simulated, road space can be intelligently utilized, and unnecessary speed fluctuations can be reduced, thereby improving traffic efficiency and comfort.

[0100] In some other implementations, the second candidate velocity can also be determined using formula (5):

[0101] V_dynamic(S1i)=V_obstacle(S2j)-ΔV(5)

[0102] Wherein, V_dynamic(S1i) can represent the second candidate speed at which the vehicle will not collide with the second obstacle at the planned path point S1i, V_obstacle(S2j) can represent the third speed of the second obstacle at the predicted path point S2j corresponding to the planned path point S1i, and ΔV can represent the speed difference between the vehicle and the second obstacle when the distance between the vehicle and the second obstacle is the second distance Dj.

[0103] In this embodiment, by determining the speed at which a collision with a dynamic second obstacle will not occur at a planned path point, and using this speed to subsequently determine the planned speed corresponding to that path point, the user can avoid panic and take over the vehicle at the planned path point due to the possibility of a collision with the second obstacle. This improves the usability of autonomous driving and the user experience. Furthermore, by determining a second candidate speed slightly lower than the speed of the second obstacle, rather than mechanically setting the second candidate speed as the speed of the second obstacle, the user's driving habits can be simulated, road space can be intelligently utilized, and unnecessary speed fluctuations of the vehicle can be reduced, thereby improving traffic efficiency and comfort.

[0104] S404: Determine the planned speed corresponding to the planned path point based on the first speed, the first candidate speed, and the second candidate speed.

[0105] In some implementations, the electronic device can determine the second speed as the minimum of the first candidate speed and the second candidate speed. The second speed can represent the speed at which the vehicle will not collide with an obstacle at the planned path point S1i. Furthermore, the electronic device can determine the planned speed corresponding to the planned path point S1i as the minimum of the first speed and the second speed.

[0106] For example, the electronic device can determine the first speed, the first candidate speed, and the second candidate speed corresponding to each planned path point based on S401, S402, and S403. Furthermore, the electronic device can determine the curvature speed limit curve V_curve (S1) based on the first speed corresponding to each planned path point, the static speed limit curve V_static (S1) based on the first candidate speed corresponding to each planned path point, and the dynamic speed limit curve V_dynamic (S1) based on the second candidate speed corresponding to each planned path point.

[0107] Then, the electronic device can fuse the curvature speed limit curve V_curve(S1), the static speed limit curve V_static(S1), and the dynamic speed limit curve V_dynamic(S1). The specific fusion rule is to take the minimum of the three speed limit values ​​for the same planned path point, thereby generating the final comprehensive speed limit curve V_limit(S1). Furthermore, the electronic device can fit a speed-position curve vs based on the planned path S1 and the comprehensive speed limit curve V_limit(S1) to control vehicle movement based on the speed-position curve; that is, to control vehicle movement based on the first position of each planned path point and the corresponding planned speed.

[0108] Thus, by proactively processing and minimizing the three speed-limiting factors of different origins and characteristics—curvature, dynamic obstacles, and static obstacles—under the speed-position curve vs., smooth, safe, and reassuring vehicle speed control commands can be generated.

[0109] In this embodiment, by introducing two constraints closely integrated with the user's psychological model—the perceived collision time threshold and the maximum penetration speed—the planned speed determined by the electronic device is no longer a cold, hard physical safety boundary, but rather a more predictive and smooth guidance that aligns with the user's driving style. This allows the vehicle to decelerate earlier, more smoothly, and more predictably when encountering dynamic obstacles cutting into or approaching static obstacles, fundamentally avoiding user panic caused by unreasonable control strategies and improving user experience and trust in autonomous driving.

[0110] Understandable, Figure 4 This paper describes a method for determining the planned speed corresponding to a planned path point based on a first speed, a first candidate speed, and a second candidate speed. In practical applications, electronic devices can also determine the planned speed corresponding to a planned path point based on any one or any two of the first speed, the first candidate speed, and the second candidate speed; this application does not impose specific limitations on this method.

[0111] For example, an electronic device can determine the planned speed corresponding to a planned path point from a first speed, a first candidate speed, or a second candidate speed. As another example, the electronic device can determine the minimum value of any two of the first speed, the first candidate speed, and the second candidate speed as the planned speed corresponding to a planned path point.

[0112] It is understood that the vehicle driving method mentioned in the embodiments of this application can be applied to vehicle driving systems, such as the vehicle-mounted terminal mentioned above. The following is in conjunction with... Figure 8 The structure of the vehicle driving system mentioned in the embodiments of this application will be described.

[0113] like Figure 8 As shown, the vehicle driving system 800 may include a path planning module 810, a speed limiting module 820, and a speed planning module 830. Among them, the speed limiting module 820 may include a static speed limiting submodule 821, a dynamic speed limiting submodule 822, a curvature speed limiting submodule 833, and a speed limiting fusion submodule 824.

[0114] The route planning module 810 can be used to obtain the planned route of the vehicle.

[0115] The static speed limit submodule 821 can be used to determine the first candidate speed at which the vehicle will not collide with the first obstacle at each planned path point.

[0116] The dynamic speed limit submodule 822 can be used to determine a second candidate speed at which the vehicle will not collide with the second obstacle at each planned path point.

[0117] The curvature speed limiting submodule 823 can be used to determine the first velocity corresponding to the curvature of each planned path point.

[0118] The speed limit fusion submodule 824 can be used to determine the curvature speed limit curve based on the first speed corresponding to each planned path point, determine the static speed limit curve based on the first candidate speed corresponding to each planned path point, and determine the dynamic speed limit curve based on the second candidate speed corresponding to each planned path point, and perform fusion processing on the curvature speed limit curve, static speed limit curve and dynamic speed limit curve of each planned path point.

[0119] The speed planning module 830 can be used to determine the planned speed corresponding to each planned path point based on the first speed, the first candidate speed, and the second candidate speed.

[0120] Understandable. Figure 8 For the specific implementation details of each module and submodule, please refer to [link / reference]. Figure 3 and Figure 4 To avoid repetition, I will not go into details here.

[0121] It is understood that the vehicle driving method mentioned in the embodiments of this application is intended to be applied to electronic devices in vehicle 100. Figure 9 This is a schematic diagram of a possible functional framework of a vehicle 100 provided in an embodiment of this application.

[0122] like Figure 9 As shown, the functional framework of vehicle 100 may include various subsystems, such as Figure 9The sensor system 110, control system 120, one or more peripheral devices 130 (one is shown as an example), power supply 140, and computer system 150 are shown. Optionally, the vehicle 100 may also include other functional systems, such as an engine system that provides power to the vehicle 100, etc., which are not limited herein.

[0123] The sensor system 110 may include several detection devices that can sense the measured information and convert the sensed information into electrical signals or other desired forms of information output according to a certain rule. Figure 9 As shown, these detection devices may include a global positioning system (GPS), a vehicle speed sensor (112), an inertial measurement unit (IMU), etc., and this application does not limit them.

[0124] The Global Positioning System (GPS) 111 is a system that uses GPS positioning satellites to perform real-time positioning and navigation globally. In this application, the GPS 111 can be used to achieve real-time positioning of vehicle 100, providing the geographical location information of vehicle 100. The vehicle speed sensor 112 is used to detect the vehicle speed of vehicle 100. The inertial measurement unit 113 may include a combination of an accelerometer and a gyroscope, and is a device for measuring the angular rate and acceleration of vehicle 100. For example, during the movement of vehicle 100, the inertial measurement unit can measure the changes in the vehicle's position and angle based on the inertial acceleration of vehicle 100, such as measuring the acceleration and angular rate of vehicle 100.

[0125] The control system 120 may include a steering unit 121 and a braking unit 122, etc.

[0126] Steering unit 121 can represent a system for adjusting the direction of travel of vehicle 100, and may include, but is not limited to, a steering wheel or other structural device for adjusting or controlling the direction of travel of vehicle 100. Braking unit 122 can represent a system for slowing down the speed of vehicle 100, and may also be referred to as the vehicle 100 braking system. It may include, but is not limited to, a brake controller, a reducer, or other structural device for slowing down vehicle 100. In practical applications, braking unit 122 can use friction to slow down the tires of vehicle 100, thereby slowing down the speed of vehicle 100.

[0127] Peripheral device 130 may include several components, such as Figure 9 The diagram shows a communication system 131, a touchscreen 132, a user interface 133, etc. The communication system 131 is used to enable network communication between the vehicle 100 and other devices besides the vehicle 100.

[0128] In practical applications, the communication system 131 can use wireless communication technology or wired communication technology to realize network communication between the vehicle 100 and other devices. The wired communication technology can refer to communication between the vehicle 100 and other devices via network cables or optical fibers. The wireless communication technology includes, but is not limited to, Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Wireless Local Area Networks (WLAN) (such as Wireless Fidelity (Wi-Fi) networks), Bluetooth (BT), Global Navigation Satellite System (GNSS), Frequency Modulation (FM), Near Field Communication (NFC), and Infrared (IR) technology, etc.

[0129] The touchscreen 132 can be used to detect operation commands on the touchscreen 132. For example, the user can perform touch operations on the content data displayed on the touchscreen 132 according to actual needs to achieve the corresponding function, such as playing music, video, or other multimedia files. The user interface 133 can specifically be a touch panel for detecting operation commands on the touch panel. The user interface 133 can also be a physical button or a mouse. The user interface 133 can also be a display screen for outputting data and displaying images or data. Optionally, the user interface 133 can also be at least one device belonging to the category of peripheral devices, such as a touchscreen, microphone, and speaker.

[0130] Several functions of vehicle 100 are controlled and implemented by computer system 150. Computer system 150 may include multiple processors such as processor 151, chassis domain controller (CDC) 152, automated driving domain controller (MDC) 153, telematics box (T-BOX) 154, as well as memory 155 (also referred to as storage device) and gateway 156. In practical applications, memory 155 may be located inside computer system 150 or outside computer system 150, for example, as a cache in vehicle 100, etc., and this application does not limit this.

[0131] Among them, processors 151, CDC152, MDC153, and T-BOX154 can be used to run relevant programs or instructions corresponding to programs stored in memory 155 to realize the corresponding functions of vehicle 100, such as the function of calling vehicle camera.

[0132] In some implementations, the processor 151 can acquire a planned path for the vehicle, which may include multiple planned path points. As the vehicle travels along the planned path, upon passing each planned path point, the electronic device can travel at a planned speed corresponding to that path point. The planned speed corresponding to each path point can be determined based on planning parameters, with different planned speeds for different path points. These planning parameters may include a first speed corresponding to the curvature of the path point and a second speed at which the vehicle avoids colliding with obstacles at each path point.

[0133] In this way, by combining the speed at which the user will not panic under the curvature of each planned path point and the speed at which the user will not collide with obstacles at each planned path point, the planned speed corresponding to each planned path point can be determined. By controlling the vehicle's driving based on the planned speed corresponding to each planned path point, the user can avoid the illusion that "a collision with an obstacle is imminent" at each planned path point. This can prevent the user from taking over the vehicle prematurely and unnecessarily due to panic, thereby improving the usability of autonomous driving and enhancing the user experience.

[0134] Memory 155 may include volatile memory, such as RAM; it may also include non-volatile memory, such as ROM, flash memory, HDD, or SSD; or it may include a combination of the above types of memory. Memory 155 can be used to store a set of program code or instructions corresponding to program code, so that processor 151 can call the program code or instructions stored in memory 155 to implement the corresponding functions of vehicle 100. This function includes, but is not limited to, […]. Figure 9 The schematic diagram of the functional framework of vehicle 100 shown includes some or all of the functions. In this application, memory 155 can store a set of program code for controlling vehicle 100. Processor 151, CDC 152, MDC 153, and T-BOX 154 can call this program code to control vehicle 100 to perform the vehicle driving method described in this application.

[0135] Optionally, in addition to storing program code or instructions, the memory 155 may also store information such as road maps, driving routes, and sensor data. The computer system 150 can be combined with other components in the functional framework diagram of the vehicle 100, such as sensors in the sensor system and GPS, to realize the relevant functions of the vehicle 100. For example, the computer system 150 can control the driving direction or speed of the vehicle 100 based on data input from the sensor system 110; this application does not impose limitations on this.

[0136] This application provides a computer program product that, when run on a device, causes the device to execute the technical solutions described in the above embodiments. Its implementation principle and technical effects are similar to those of the related embodiments described above, and will not be repeated here.

[0137] It is understood that the various embodiments of the mechanisms disclosed in this application can be implemented in hardware, software, firmware, or a combination of these implementation methods. Embodiments of this application can be implemented as computer programs or program code executable on a programmable system, the programmable system including at least one processor, a storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device.

[0138] Program code can be applied to input instructions to execute the functions described in this application and generate output information. The output information can be applied to one or more output devices in a known manner. For the purposes of this application, the processing system includes any system having a processor such as, for example, a digital signal processor (DSP), a microcontroller, an application-specific integrated circuit (ASIC), or a microprocessor.

[0139] The program code can be implemented using a high-level procedural language or an object-oriented programming language to communicate with the processing system. Assembly language or machine language can also be used when needed. The mechanisms described in this application are not limited to any particular programming language. In either case, the language can be a compiled language or an interpreted language.

[0140] The above describes the possible hardware structures of electronic devices. It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the electronic device. In other embodiments of this application, the electronic device may include more or fewer components than illustrated, or combine certain components, or split certain components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of both.

[0141] In the accompanying drawings, some structural or methodological features may be shown in a specific arrangement and / or order. However, it should be understood that such a specific arrangement and / or order may not be necessary. Rather, in some embodiments, these features may be arranged in a manner and / or order different from that shown in the illustrative drawings. Furthermore, the inclusion of structural or methodological features in a particular figure does not imply that such features are required in all embodiments, and in some embodiments, these features may be omitted or may be combined with other features.

[0142] It should be noted that in the examples and description of this patent, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the aforementioned element.

[0143] Although this application has been illustrated and described with reference to certain embodiments thereof, those skilled in the art will understand that various changes in form and detail may be made thereto without departing from the scope of this application.

Claims

1. A method for driving a vehicle, characterized in that, include: Obtain the planned route of the vehicle, wherein the planned route includes multiple planned waypoints; As the vehicle travels along the planned path, it travels at each planned path point based on the planned speed corresponding to that path point. This planned speed is determined based on planning parameters. The planning parameters include a first speed corresponding to the curvature of the planned path point and a second speed at which the vehicle will not collide with obstacles at the planned path point.

2. The vehicle driving method according to claim 1, characterized in that, The first velocity is determined in the following manner: Based on the preset first mapping relationship between curvature and velocity, and the curvature of the planned path point, the first velocity corresponding to the curvature of the planned path point is determined.

3. The vehicle driving method according to claim 1, characterized in that, The second velocity is determined in the following manner: Determine multiple candidate speeds at which the vehicle will not collide with any of the surrounding obstacles at the planned path point; The minimum value among the plurality of candidate velocities is determined as the second velocity.

4. The vehicle driving method according to claim 3, characterized in that, The plurality of obstacles includes a static first obstacle, and The determination of multiple candidate speeds at which the vehicle will not collide with any of the surrounding obstacles at the planned path point includes: Obtain the first position of the planned path point and the second position of the first obstacle; Determine a first distance between the first position and the second position; The first candidate speed is determined based on the first distance and the preset somatosensory collision time threshold.

5. The vehicle driving method according to claim 3, characterized in that, The plurality of obstacles includes a dynamic second obstacle, and The determination of multiple candidate speeds at which the vehicle will not collide with any of the surrounding obstacles at the planned path point includes: Obtain a first predicted driving path for the second obstacle, wherein the first predicted driving path includes multiple predicted path points; Determine the predicted path point corresponding to each of the multiple predicted path points, the third position of the predicted path point corresponding to each of the planned path points, and the third velocity of the second obstacle at each of the predicted path points corresponding to the planned path points from the plurality of predicted path points; Determine the second distance between the first position of each planned path point and the third position of the predicted path point corresponding to each planned path point; A second candidate speed is determined based on a preset second mapping relationship between distance and speed difference, the third speed, and the second distance.

6. The vehicle driving method according to claim 5, characterized in that, Determining the predicted path point corresponding to each of the planned path points from the plurality of predicted path points includes: The predicted path point with the smallest distance to each of the planned path points among the multiple predicted path points is determined as the predicted path point corresponding to each of the planned path points.

7. The vehicle driving method according to claim 5, characterized in that, The step of determining the second candidate speed based on a preset second mapping relationship between distance and speed difference, the third speed, and the second distance includes: The target speed difference is determined based on the second mapping relationship and the second distance; the target speed difference is the speed difference between the vehicle and the second obstacle that is allowed when the distance between the vehicle and the second obstacle is the second distance. The second candidate speed is determined based on the difference between the third speed and the target speed.

8. The vehicle driving method according to any one of claims 1 to 7, characterized in that, The planned speed corresponding to the planned path point is the minimum value between the first speed and the second speed.

9. The vehicle driving method according to claim 8, characterized in that, Different planning path points correspond to different planning speeds.

10. An electronic device, characterized in that, Includes: a memory for storing instructions executed by one or more processors of the electronic device. And a processor, which is one or more processors of the electronic device, for performing the vehicle driving method according to any one of claims 1 to 9.

11. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 10.

12. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed by an electronic device, enable the electronic device to perform the vehicle driving method as described in any one of claims 1 to 9.

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