Vehicle motion planning method, device, equipment and computer storage medium

Abstract

The present application discloses a vehicle motion planning method, apparatus, device and computer storage medium. The vehicle motion planning method comprises: obtaining initial motion data of preset motion parameters and preset parameter values ​​associated with each of a plurality of preset control parameters in a planning cycle, and determining a safe driving distance, wherein the preset parameter values ​​include preset parameter values ​​for matching an acceleration state; determining candidate driving distances corresponding to each preset parameter value based on the initial motion data and the preset parameter values; and planning the preset motion parameters to obtain target motion data when a first preset condition is satisfied between the candidate driving distance and the safe driving distance, wherein the first preset condition is used to indicate that motion planning can be performed according to an acceleration state. The embodiments of the present application can effectively avoid sudden changes in the planned values ​​of the preset motion parameters.

Description

Technical Field

[0001] The present application belongs to the field of intelligent driving technology, and in particular relates to a vehicle motion planning method, device, equipment and computer storage medium. Background Art

[0002] As we all know, in the field of intelligent driving, it is generally necessary to plan the vehicle's motion parameters to ensure driving safety. The planning of vehicle motion parameters can usually be carried out in multiple planning cycles to ensure real-time planning.

[0003] In existing technologies, vehicle speed is usually used as a motion parameter for planning. However, due to the complex actual road driving environment, the safe driving distance may vary with the changes in various obstacles, which can easily lead to sudden changes in the planned speed, resulting in poor vehicle comfort. Summary of the Invention

[0004] The embodiments of the present application provide a vehicle motion planning method, apparatus, device and computer storage medium to solve the problem that the existing technology is prone to sudden changes in planned speed and poor vehicle comfort.

[0005] In one aspect, an embodiment of the present application provides a vehicle motion planning method, the method comprising:

[0006] In a planning cycle, initial motion data of a preset motion parameter and a preset parameter value associated with each of a plurality of preset control parameters are obtained, and a safe driving distance is determined, wherein the preset parameter value includes a preset parameter value for matching an acceleration state;

[0007] Determining, based on the initial motion data and each of the preset parameter values, candidate driving distances corresponding to each of the preset parameter values;

[0008] When a first preset condition is satisfied between the candidate driving distance and the safe driving distance, the preset motion parameters are planned to obtain target motion data, wherein the first preset condition is used to indicate that motion planning can be performed in an accelerated state.

[0009] On the other hand, an embodiment of the present application provides a vehicle motion planning device, the device comprising:

[0010] an acquisition module, configured to acquire, during a planning cycle, initial motion data of a preset motion parameter and a preset parameter value associated with each of a plurality of preset control parameters, and determine a safe driving distance, wherein the preset parameter value includes a preset parameter value for matching an acceleration state;

[0011] a determination module, configured to determine, based on the initial motion data and each of the preset parameter values, candidate driving distances corresponding to each of the preset parameter values;

[0012] The first planning module is used to plan the preset motion parameters to obtain target motion data when a first preset condition is satisfied between the candidate driving distance and the safe driving distance, wherein the first preset condition is used to indicate that motion planning can be performed in an accelerated state.

[0013] In another aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory storing computer program instructions;

[0014] When the processor executes the computer program instructions, the above-mentioned vehicle motion planning method is implemented.

[0015] On the other hand, an embodiment of the present application provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions implement the above-mentioned vehicle motion planning method when executed by a processor.

[0016] The vehicle motion planning method, apparatus, device and computer storage medium provided in the embodiments of the present application obtain, in a planning cycle, initial motion data of preset motion parameters and preset parameter values ​​associated with different preset control parameters, wherein the preset parameter values ​​include preset parameter values ​​for matching the acceleration state; based on the initial motion data and each preset parameter value, respectively determine the candidate driving distance corresponding to each preset parameter value, and when a first preset condition is satisfied between the candidate driving distance and the determined safe driving distance, plan the preset motion parameters to obtain target motion data, wherein the first preset condition is used to indicate that motion planning can be performed according to the acceleration state, so that the vehicle can try to use the planning logic corresponding to the acceleration state for motion planning in each planning cycle, limit the planning values ​​of the preset motion parameters to a certain extent, and effectively avoid the situation where the planning values ​​of the preset motion parameters suddenly change; at the same time, based on multiple preset control parameters, multiple candidate driving distances can be obtained, which can provide multiple references for the preset motion parameter planning, thereby helping to determine more appropriate target motion data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 Schematic diagram of the vehicle motion planning method provided in the embodiment of the present application;

[0019] Figure 2 This is another flowchart of the vehicle motion planning method provided by an embodiment of the present application;

[0020] Figure 3 is a schematic structural diagram of a vehicle motion planning device provided in an embodiment of the present application;

[0021] Figure 4 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0023] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0024] In order to solve the problems of the prior art, the embodiments of the present application provide a vehicle motion planning method, apparatus, device and computer storage medium. The vehicle motion planning method provided by the embodiments of the present application is first introduced below.

[0025] Figure 1 FIG. 1 shows a flow chart of a vehicle motion planning method provided by an embodiment of the present application. Figure 1 As shown, the vehicle motion planning method includes:

[0026] Step 101, in a planning cycle, obtaining initial motion data of preset motion parameters and preset parameter values ​​associated with each of a plurality of preset control parameters, and determining a safe driving distance, wherein the preset parameter values ​​include preset parameter values ​​for matching an acceleration state;

[0027] Step 102 , determining candidate driving distances corresponding to respective preset parameter values ​​based on the initial motion data and respective preset parameter values;

[0028] Step 103 : When a first preset condition is satisfied between the candidate driving distance and the safe driving distance, preset motion parameters are planned to obtain target motion data, wherein the first preset condition is used to indicate that motion planning can be performed in an accelerated state.

[0029] It is easy to understand that during vehicle driving, it is usually necessary to plan the movement of a certain time period in the future in real time. This time period can be considered as a total planning time. In this total planning time, it is generally necessary to divide it into multiple shorter time periods for iterative calculations, and this shorter time period can be considered as a calculation cycle, or the above-mentioned planning cycle. For example, the total planning time can be 1s, and the planning cycle can be 0.02s. Accordingly, 50 iterative calculations can be performed in the total planning time; of course, this is just an example of the relationship between the two times. In actual applications, these time values ​​can be set as needed.

[0030] In this embodiment, the planning of vehicle motion in a certain planning cycle will be mainly described.

[0031] The initial motion data obtained during a planning cycle can be the values ​​of preset motion parameters such as the vehicle's distance, speed, acceleration, jerk, or acceleration at the beginning of the planning cycle. It's easy to understand that jerk can be used to reflect the change in acceleration over time, while jerk can be used to reflect the change in jerk over time.

[0032] Generally speaking, the above-mentioned initial motion data can be obtained through iterative calculations, that is, it can be the motion data obtained based on the planning of vehicle motion in the previous planning cycle; of course, these initial motion data can also be obtained based on vehicle sensors or on-board terminals and other devices.

[0033] Taking the driving distance as an example, the driving distance can be the distance relative to a certain reference position on the driving path of the vehicle; the driving path can be obtained through path planning, and the reference position here can be a starting position point or other preset position points, etc., which are not specifically limited here. As for the driving distance, it can be obtained through iterative calculations during the vehicle motion planning process, or it can be obtained through the positioning function of the vehicle terminal. However, generally speaking, except when the vehicle starts to move, it is necessary to use the above-mentioned positioning function to obtain the driving distance, and the subsequent data can be obtained through iterative calculations. In this embodiment, the initial motion data such as driving distance, speed, and acceleration will be mainly used as an example to illustrate the obtained iterative calculation based on the previous planning cycle.

[0034] The safe driving distance can also refer to the driving distance relative to a reference position. It is easy to understand that when there are obstacles in front of the vehicle during driving, such as other vehicles, pedestrians or roadblocks, when performing motion planning, it should be ensured that the vehicle will not collide with the above obstacles after the current planning cycle; taking the obstacle as another vehicle as an example, at the beginning of the current planning cycle, the obstacle may be at one driving distance, and at the end of the current planning cycle, the vehicle may travel to another driving distance. When performing motion planning for the vehicle, it should be ensured that after the current planning cycle, the vehicle will not collide with the obstacle due to reaching or exceeding the above-mentioned other driving distance; to achieve this effect, a safe driving distance can be determined in the current planning cycle. Of course, when there is no obstacle in front of the vehicle, the safe driving distance can be considered to be infinite.

[0035] In this embodiment, the preset control parameters can be considered as motion parameters that restrict the movement of the vehicle, such as speed, acceleration, jerk, and acceleration-jerk. For example, when a vehicle is traveling on a certain road section, there may be a speed limit, in which case the vehicle speed is usually limited. For another example, to ensure passenger comfort, it may be necessary to limit the value of the vehicle's acceleration or jerk. For another example, due to the limitations of the vehicle's own performance, acceleration may have a maximum value.

[0036] The restriction of the movement of the vehicle by the preset control parameter is specifically achieved by limiting the value. Therefore, the preset control parameter can be associated with a preset parameter value. In this embodiment, the preset parameter value can include a preset parameter value for matching the acceleration state. For example: for the preset control parameter of speed, the preset parameter value for matching the acceleration state can be an optimal speed value, such as the maximum speed limit on a certain path, and the acceleration state can be considered to be that the vehicle can travel at the optimal speed value; for another example, for the preset control parameter of acceleration, the associated preset parameter value for matching the acceleration state can be considered to be a positive acceleration value, and the acceleration state can be considered to be that the vehicle can travel at the positive acceleration value.

[0037] To further understand the definition of the acceleration state, the definition of the deceleration state can be used here for comparison and explanation: for the preset control parameter of speed, the deceleration state can be considered as the vehicle cannot travel at the optimal speed; for the preset control parameter of acceleration, a preset parameter value for matching the deceleration state can be additionally associated, and the preset parameter value can be a negative acceleration value, or a deceleration value, and the deceleration state can be considered as the vehicle can travel at this deceleration.

[0038] From the above description, it can be seen that the acceleration state mentioned in this embodiment can be understood as a planning logic, and matching the acceleration state can be understood as executing the planning logic to try to perform motion planning based on the corresponding preset parameter values, rather than simply controlling the vehicle speed to increase.

[0039] In this embodiment, there are multiple preset control parameters, for example, speed and acceleration, etc. Accordingly, there are multiple preset parameter values. A corresponding candidate driving distance can be determined for each preset parameter value.

[0040] For example, let the above planning cycle be the nth planning cycle, and the duration of each planning cycle, that is, the planning step length, be t step ; n can be a positive integer. When n=1, s(n-1) and v(n-1) can be some actual measured starting values. When n>1, s(n-1) and v(n-1) can be some values ​​obtained through motion planning. The above multiple preset parameter values ​​include the optimal speed v perffered With the optimal acceleration a preffered At the same time, the initial motion data includes the initial travel distance s(n-1) and the initial speed value v(n-1). perffered , the determined candidate driving distance can be expressed as s(n-1)+v perffered *t step ; Based on the initial motion data and a prefferedThe determined candidate driving distance can be expressed as

[0041] Of course, in actual applications, the preset control parameters can be selected according to actual needs, and each preset control parameter can be associated with not only a preset parameter value for matching the acceleration state, but also the above-mentioned preset parameter value for matching the deceleration state, etc.; further, the process of determining the corresponding candidate driving distance based on the preset parameter value can also be implemented in combination with some actual kinematic parameters of the vehicle; the details will be further explained in the following embodiments.

[0042] After obtaining the above-mentioned candidate driving distances, each candidate driving distance can be combined with the safe driving distance to determine whether the two meet the first preset condition; the first preset condition here can be used to indicate that motion planning can be performed according to the acceleration state, that is, motion planning can be performed based on the preset parameter value used to match the acceleration state.

[0043] For example, when a candidate driving distance that is shorter than a safe driving distance exists among a plurality of candidate driving distances, a target driving distance may be determined from the plurality of candidate driving distances to plan the preset motion parameters.

[0044] Of course, it is worth emphasizing that this is only an example of the first preset condition. In actual applications, the first preset condition can be set in combination with more factors, which will be explained in detail in the embodiments below and will not be repeated here.

[0045] The process of planning the preset motion parameters to obtain target motion data can be explained through the following example:

[0046] Combined with the example of the nth planning cycle above, the target driving distance is recorded as s(n) d , the target driving distance in this planning cycle can be planned as s(n) d , set the target speed value v(n) d Planning is (s(n) d -s(n-1)) / t step Of course, you can also set the target acceleration value a(n) d Planning for (v(n) d -v(n-1)) / t step , or further plan the target acceleration, etc. The above-mentioned target driving distance, target speed value and target acceleration value, etc. can all be considered as the above-mentioned target motion data.

[0047] The vehicle motion planning method provided in an embodiment of the present application obtains initial motion data of preset motion parameters and preset parameter values ​​associated with different preset control parameters in a planning cycle, wherein the preset parameter values ​​include preset parameter values ​​for matching the acceleration state; based on the initial motion data and each preset parameter value, the candidate driving distance corresponding to each preset parameter value is determined respectively, and when a first preset condition is satisfied between the candidate driving distance and the determined safe driving distance, the preset motion parameters are planned to obtain target motion data, wherein the first preset condition is used to indicate that motion planning can be performed according to the acceleration state, so that the vehicle can try to use the planning logic corresponding to the acceleration state for motion planning in each planning cycle, which limits the planning values ​​of the preset motion parameters to a certain extent, and effectively avoids the situation where the planning values ​​of the preset motion parameters suddenly change; at the same time, multiple candidate driving distances can be obtained based on multiple preset control parameters, which can provide multiple references for the preset motion parameter planning, thereby helping to determine more appropriate target motion data.

[0048] In one example, the plurality of preset control parameters include speed and at least one of the following:

[0049] Acceleration, the preset parameter values ​​associated with acceleration include a first acceleration value for matching an acceleration state, and a second acceleration value for matching a deceleration state;

[0050] Jerk, the preset parameter values ​​associated with the jerk include a first jerk value for matching an acceleration state, and a second jerk value for matching a deceleration state;

[0051] Jerk, the preset parameter value associated with the jerk includes a first jerk value for matching an acceleration state, and a second jerk value for matching a deceleration state;

[0052] The speed-associated preset parameter value includes a first speed value for matching the acceleration state.

[0053] As mentioned above, the acceleration state and the deceleration state can be understood as two different planning logics. In the acceleration state, motion planning can be performed using corresponding preset parameter values, which can be understood as the first velocity value, the first acceleration value, the first jerk value, or the first jerk value. Correspondingly, in the deceleration state, motion planning can be performed using the second acceleration value, the second jerk value, or the second jerk value.

[0054] Combined with some practical application scenarios, the first speed value can be an optimal speed value, denoted as v perffered,The optimal speed value here can be considered as the maximum ,limited speed over the driving distance corresponding to the planning period, or ,when there is no speed limit over the driving distance, it can be the maximum ,speed that the vehicle can reach.

[0055] The first acceleration value can be a positive value, which can be considered to correspond to the expression of the acceleration state to a certain extent; accordingly, the second acceleration value can be a negative value, and the negative acceleration value can also be defined using the deceleration value. When explaining the first acceleration value below, it can be recorded as the optimal acceleration a preffered , the second acceleration value can be recorded as the optimal deceleration d perffered It is easy to understand that the optimal value involved here can be a pre-defined parameter value that is more suitable for vehicle motion planning. Specifically, it can be a value obtained based on the vehicle's acceleration or deceleration performance, or an empirical value obtained from the comfort of the passengers, etc. There is no specific restriction at this time.

[0056] Similar to the first acceleration value and the second acceleration value, the first jerk value can be recorded as the optimal jerk a′ perffered The second acceleration value can be recorded as the optimal deceleration value d′ perffered , the first jerk value can be recorded as the optimal jerk a″ perffered The second jerk value can be recorded as the optimal deceleration d″ perffered .

[0057] In this example, preset parameter values ​​for matching the deceleration state are added to some preset control parameters. Corresponding candidate driving distances can also be determined for these preset parameter values ​​for matching the deceleration state. Then, in the above step 103, the safe driving distance can be compared with the candidate driving distances obtained according to different planning logics to determine whether the first preset condition is met, thereby being able to adapt to motion planning in more vehicle driving scenarios.

[0058] For ease of understanding, the following example illustrates the advantages of using the candidate driving distance determined by the preset parameter value for matching the deceleration state for motion planning. For example, in a planning cycle, the value of v(n-1) is much larger than v perffered ; Based on v perffered Determined candidate driving distance s h1 It may be s(n-1)+v perffered *t step , based on d perffered Determined candidate driving distance s h2 may be Since v(n-1) is much larger than v perffered , even if d preffered is a negative value, but the obtained s h2The value may still be greater than s h1 In other words, the planning logic based on the acceleration state may not be applicable to the current vehicle driving scenario, or may not be able to directly determine whether the first preset condition is met. This effectively avoids the situation where the vehicle's actual kinematic performance cannot meet the target motion data, and better adapts motion planning to different vehicle driving scenarios.

[0059] In the above embodiment, in addition to using the preset parameter values ​​associated with the preset control parameters, the safe driving distance and the optimal speed value v are also involved. perffered , the following is for safe driving distance and optimal speed value v perffered An example is given to illustrate how to determine .

[0060] The safe driving distance may have different values ​​in each planning cycle. Therefore, the following description will mainly focus on the safe driving distance determined in the nth planning cycle.

[0061] It is easy to understand that when there is an obstacle in front of the vehicle, the vehicle usually has a specific maximum driving distance to prevent collision with the obstacle; when there is no obstacle in front of the vehicle, the maximum driving distance can be considered infinite. As shown above, the vehicle driving distance usually refers to the distance from a reference position on the planned path. In each planning cycle, the maximum driving distance value s of the vehicle on the planned path can be calculated. max (n). Combined with the above description, s can be calculated as follows max (n):

[0062]

[0063] Where t(n)=n*t step , s obstacle It can be the distance of the obstacle relative to the reference position on the planned path, v obstacle It can be the speed at which the obstacle is traveling.

[0064] In getting s max (n), the safe driving distance s in the nth planning cycle can be further determined safe (n), for example, it can be calculated as follows safe (n):

[0065]

[0066] Among them, distance obstacle_safe is the preset safety distance, t obstacle_safeThe safety distance is the preset safety time. It's easy to understand that the safety distance is the distance margin set to ensure contact between the vehicle and the obstacle, or to prevent the obstacle from slowing down. The safety time, on the other hand, refers to the additional time consumed by calculation time or the response time of the vehicle's actuators.

[0067] In summary, the process of determining the safe driving distance in the presence of obstacles can be summarized as follows:

[0068] In the presence of an obstacle, obtaining the movement data of the obstacle, and determining the maximum driving distance based on the movement data of the obstacle;

[0069] Determine the safe driving distance based on the maximum driving distance, as well as the preset safe distance and safety time.

[0070] For the optimal speed value v perffered , can be determined according to the following formula:

[0071]

[0072] Among them, the above S limit_start With S limit_end They can respectively represent the starting distance and the ending distance of the speed-limited section relative to the reference position, and the speed-limited path can be located on the planned path; specifically, in this embodiment, the path can be decoupled from the above-mentioned preset motion parameters and the path planning can obtain the optimal speed value at each driving distance.

[0073] Based on the above description, it is easy to understand that when planning a path, the planned path can be divided into multiple sub-segments, v perffered (m) can refer to the optimal speed value in the mth sub-segment. When the speed limit information exists in the mth sub-segment, v perffered (m) is set to the corresponding speed limit value v limit , and when there is no speed limit information on the mth sub-segment, v perffered (m) is defined as the maximum speed that the vehicle can reach.

[0074] Of course, when determining the optimal speed value for the mth sub-segment, there may be some special cases, such as a transition from a speed-limited section to a non-speed-limited section, or the presence of multiple speed limit information. In some possible implementations, for the former, interpolation can be used to smooth the optimal speed values ​​for each sub-segment; for the latter, the minimum speed limit value among the speed limit information can be used as the optimal speed value.

[0075] In addition, in order to adapt to practical applications, there may be a limit on the value range of m and n. For example, combined with the above description of decoupling planning, when planning the preset motion parameters, the total planning time is t total , the planning time step is t step , then t(n) in the above text represents the total time to skip n steps, where 0≤n<(t total +t step ) / t step , and n is an integer; it is easy to understand that when n = 0, it corresponds to the state when the movement starts; and according to t total / t step The obtained value is not necessarily an integer. Therefore, in order to cover the motion planning to the total planning time, it can be total / t step Add 1 to the value, that is, round up.

[0076] Similarly, for path planning, the total distance is s total , the step length of path planning is s step , s(m) represents the total distance of skipping m steps, where: 0≤m<(s total +s step ) / s step .

[0077] Optionally, the candidate driving distance includes at least one of the following:

[0078] a first candidate driving distance, where the first candidate driving distance is a candidate driving distance determined based on a preset parameter value associated with a preset control parameter and used to match an acceleration state;

[0079] a second candidate driving distance, the second candidate driving distance being a candidate driving distance determined based on a preset parameter value associated with a preset control parameter for matching a deceleration state;

[0080] a third candidate driving distance, the third candidate driving distance being a candidate driving distance determined based on a first parameter value of a preset control parameter, wherein the first parameter value is a maximum value between a preset parameter value associated with the preset control parameter for matching an acceleration state and an initial parameter value of the preset control parameter, and the initial motion data includes the initial parameter value of the preset control parameter;

[0081] A fourth candidate driving distance is a candidate driving distance determined based on a second parameter value of a preset control parameter, wherein the second parameter value is a minimum value between a preset parameter value associated with the preset control parameter for matching a deceleration state and an initial parameter value of the preset control parameter, and the initial motion data includes the initial parameter value of the preset control parameter.

[0082] In this embodiment, it can be considered that not only the candidate driving distances are determined by different preset parameter values, but also the determination rules of the candidate driving distances are further limited differently to adapt to the needs of planning vehicle movement using the above-mentioned optimal parameter values ​​or maintaining the initial motion data.

[0083] To facilitate understanding of the above-mentioned determination methods of candidate driving distances, some examples are given below for explanation. In these examples, acceleration is mainly used as a preset control parameter, and its preset parameter values ​​include a preffered with d preffered .

[0084] For the first candidate driving distance, it can be determined as:

[0085]

[0086] The second candidate driving distance can be determined as:

[0087]

[0088] The third candidate driving distance can be determined as:

[0089]

[0090] Among them, a a =max(a preffered , a(n-1)), a(n-1) is the initial acceleration, which can be planned in the n-1th planning cycle;

[0091] The fourth candidate driving distance can be determined as:

[0092]

[0093] Among them, a d =min(d preffered , a(n-1)).

[0094] Optionally, in step 103, when the candidate driving distance and the safe driving distance satisfy a first preset condition, planning the preset motion parameters includes:

[0095] When the first driving distance is greater than the second driving distance and the second driving distance is less than the safe driving distance, the minimum of the first driving distance and the safe driving distance is used as the planned driving distance, and the preset motion parameters are planned based on the planned driving distance; wherein the candidate driving distances include the first candidate driving distance and the second candidate driving distances, the first driving distance is the maximum value of the first candidate driving distances, and the second driving distance is the maximum value of the second candidate driving distances;

[0096] and / or,

[0097] When the first driving distance is less than or equal to the second driving distance, the third driving distance is less than the safe driving distance, and the third driving distance is greater than the fourth driving distance, the candidate driving distance determined based on the first speed value is used as the planned driving distance, and the preset motion parameters are planned based on the planned driving distance; wherein the candidate driving distances include the first candidate driving distance, the second candidate driving distance, the third candidate driving distance, and the fourth candidate driving distance, the third driving distance is the minimum value among the third candidate driving distances, and the fourth driving distance is the maximum value among the fourth candidate driving distances.

[0098] In this embodiment, the first preset condition is limited to adapt to the motion planning of the vehicle in different motion states. For ease of understanding, the specific implementation process of this embodiment is described below with reference to formulas.

[0099] For different preset control parameters, the candidate driving distances can be determined in the following manner:

[0100] The formula for calculating the candidate driving distance s(n) with speed v as the variable is:

[0101] f(v)=s(n)=s(n-1)+v*t step (1)

[0102] The formula for calculating the candidate driving distance s(n) with acceleration a as the variable is:

[0103]

[0104] The formula for calculating the candidate driving distance s(n) with the acceleration a′ as the variable is:

[0105]

[0106] The formula for calculating the candidate driving distance s(n) with the jerk a″ as the variable is:

[0107]

[0108] In the above formulas, some monomials may have coefficients in theoretical calculations. For example, in the formula for g(a), the monomial Theoretically with coefficient 1 / 2, however, t step The actual value may be small, and the coefficient has little impact on the actual calculated candidate driving distance. However, the performance of the division operation is low, and the calculation of the candidate driving distance is relatively frequent. Therefore, in order to balance computing resources, these coefficients can be omitted.

[0109] The first driving distance is recorded as s(n)1, which can be obtained by converting the above v perffered 、a preffered , a′ perffered 、a″ perffered Substitute the minimum value of each first candidate driving distance obtained in formula (1), formula (2), formula (3), and formula (4) respectively;

[0110] The second driving distance is recorded as s(n)2, which can be obtained by converting the above d perffered , d′ perffered , d″ perffered Substitute the maximum value of each second candidate driving distance obtained in formula (2), formula (3), and formula (4) respectively;

[0111] The third driving distance is recorded as s(n)3, which can be max(v preffered ,v(n-1))、max(a preffered ,a(n-1))、a′ perffered 、a″ perffered Substitute the minimum value of each third candidate driving distance obtained in formula (1), formula (2), formula (3), and formula (4) respectively;

[0112] The fourth driving distance is recorded as s(n)4, which can be obtained by converting the above min(d preffered , a(n-1)), d′ perffered , d″ perffered Substitute the maximum value among the fourth candidate driving distances obtained in formula (2), formula (3), and formula (4).

[0113] Based on the above content, the first preset condition may exist in two situations, wherein the first situation may be:

[0114] s(n)1>s(n)2 and s(n)2<s safe (n),

[0115] When the above conditions are met, s(n)1 and s safe The smaller value in (n) is determined as the planned driving distance, and the preset motion parameters are planned based on the planned driving distance. At this time, it can be considered that the preset motion parameters are planned based on the optimal acceleration state.

[0116] The second case could be:

[0117] s(n)1≤s(n)2, however s safe >s(n)3>s(n)4;

[0118] When the above conditions are met, f(v perffered) is determined as the planned driving distance. This time, it can be considered as the planning of preset motion parameters based on the actual acceleration state.

[0119] It is worth emphasizing again that in the embodiment of the present application, the acceleration state is merely used as a planning logic and does not necessarily control the vehicle to increase its speed.

[0120] In combination with a practical application scenario, when s(n)1≤s(n)2, it may be because v(n-1) is much larger than v perffered However, safe >s(n)3, indicating that even if the vehicle continues to travel at v(n-1), it may still be able to meet the limit requirements of the safe driving distance. In order to avoid speeding or to ensure the user's riding experience, the vehicle's speed can be controlled to v perffered In other words, the motion planning result obtained at this time may actually control the vehicle to slow down.

[0121] Of course, the above are merely examples of determining whether the first preset condition is satisfied. The selection of preset control parameters and the selection of the monomial coefficients in the above formula can be adjusted according to actual needs and are not specifically limited in this application. Determining the planned driving distance based on the relationship between the first driving distance, the second driving distance, the third driving distance, the fourth driving distance, and the safe driving distance can effectively meet the needs of vehicle motion planning under various special driving conditions.

[0122] Optionally, in step 103, after determining the candidate driving distance corresponding to each preset control parameter based on the initial motion data and the preset parameter value associated with each preset control parameter, the vehicle motion planning method further includes:

[0123] If the candidate driving distance and the safe driving distance do not satisfy the first preset condition, returning to the previous planning cycle to plan the preset control parameters;

[0124] The initial motion data obtained in a planning cycle is the target motion data obtained by planning the preset control parameters in the previous planning cycle.

[0125] like Figure 2 As shown, in this embodiment, when motion planning cannot be performed based on the planning logic corresponding to the acceleration state in the nth planning cycle, it is possible to fall back to the n-1th planning cycle and re-plan.

[0126] As shown above, for each planning cycle, when motion planning is initially performed, motion planning can be performed according to the planning logic corresponding to the acceleration state, and the same is true for the n-1th planning cycle; and if, based on the planning results of the n-1th planning cycle, motion planning cannot be performed in the n-1th planning cycle through the planning logic corresponding to the acceleration state, the planning method of the n-1th planning cycle may be modified. For example, motion planning can be performed using the planning logic of the deceleration state, and the target motion data obtained by re-planning can be used as the initial motion data of the n-1th planning cycle.

[0127] This embodiment can try to ensure that motion planning is performed according to the same planning logic in each planning cycle. When the planning logic cannot meet the actual driving needs of the vehicle, it can fall back to the previous planning cycle to re-plan the preset control parameters and re-enter the planning results into the next planning cycle to ensure that the vehicle can drive normally.

[0128] Optionally, returning to the previous planning period to plan the preset control parameters includes:

[0129] In the previous planning cycle, obtain the candidate driving distance;

[0130] When the first driving distance is greater than the second driving distance and the second driving distance is less than the safe driving distance, the second driving distance is used as the planned driving distance, and the preset motion parameters are planned according to the planned driving distance;

[0131] and / or,

[0132] When the first driving distance is less than or equal to the second driving distance and the fourth driving distance is less than the safe driving distance, the candidate driving distance determined based on the second acceleration value is used as the planned driving distance, and the preset motion parameters are planned according to the planned driving distance; wherein the multiple preset control parameters include acceleration.

[0133] In this embodiment, the previous planning cycle may correspond to the n-1th planning cycle mentioned above. This embodiment mainly describes the motion planning process in the n-1th planning cycle.

[0134] It's easy to understand that at the start of the nth planning cycle, the vehicle's preset control parameters have already been planned in the n-1th planning cycle. Accordingly, in the n-1th planning cycle, various candidate driving distances have already been calculated. Based on these previously calculated values, values ​​such as the first driving distance s(n-1)1, the second driving distance s(n-1)2, the third driving distance s(n-1)3, and the fourth driving distance s(n-1)4 can be directly obtained. At this point, the preset control parameters can be replanned according to the planning logic corresponding to the deceleration state.

[0135] Specifically, when s(n-1)1>s(n-1)2 and s(n-1)2<s safe When s(n-1)2 is updated to the planned driving distance in the n-1th planning cycle, the preset control parameters can be replanned accordingly.

[0136] And s(n-1)1≤s(n-1)2, but s safe When (n-1)>s(n-1)4, g(d preffered ) is updated to the planned driving distance for the n-1th planning cycle, and the preset control parameters are replanned accordingly. Specifically, when this condition is met, it indicates that the vehicle was traveling too fast and may have collided with an obstacle. In this case, the optimal deceleration rate can be used to control the vehicle's speed while maintaining a safe driving distance.

[0137] In one example, when the target motion data obtained by re-planning the preset control parameters in the n-1th planning cycle still does not meet the acceleration state planning logic of the nth planning cycle, it is possible to continue to fall back to the n-2th planning cycle to re-plan the preset control parameters, and so on, until the acceleration state planning logic of the nth planning cycle is met, or fall back to the 0th cycle.

[0138] In another example, the planning of preset control parameters based on the planned driving distance can be expressed by the following formula:

[0139]

[0140] The following describes a specific application example of the vehicle motion planning method provided in an embodiment of the present application. In this specific application example, the vehicle may be an automatic driving car (ADC), and the vehicle motion planning method can be roughly described as follows:

[0141] 1) Divide the total planning time (the total planning time can be dynamically configured) into multiple planning cycles according to the accuracy of speed planning.

[0142] 2) Based on the speed and distance of the obstacle and the following distance information, the distance that the autonomous driving vehicle can safely travel in the current planning period can be calculated.

[0143] 3) Calculate the driving distance under acceleration using data of optimal vehicle physical characteristics (which can refer to the optimal riding experience and can be pre-configured).

[0144] 4) Calculate the driving distance under deceleration state using data on optimal vehicle physics characteristics.

[0145] 5) Calculate the travel distance under acceleration using the current vehicle kinematic data (which may include the above-mentioned optimal vehicle physics characteristics and the actual vehicle motion data).

[0146] 6) Use the current vehicle kinematic data to calculate the distance traveled in the deceleration state.

[0147] 7) Based on the driving distances calculated in steps 3), 4), 5), and 6), filter out the driving distance data that does not meet the safe driving distance, and give priority to the data in the acceleration state; if the selected acceleration state data does not meet the specific conditions, fall back to the previous planning cycle and give priority to the deceleration state data until all the data in all planning cycles are calculated.

[0148] Of course, the steps of the vehicle motion planning method here are only a rough description process. The setting of the above-mentioned specific conditions and the specific judgment process can refer to the relevant content of the first preset condition involved in the above embodiment, which will not be repeated here.

[0149] When planning vehicle motion, the input parameters may include the following:

[0150] 1) The current state of the ADC, including the speed and acceleration of the ADC. Specifically, these parameters can be the starting position s of the ADC in the 0th planning cycle. start , initial speed v start , initial acceleration a start and the initial acceleration a′ start wait;

[0151] 2) Speed ​​limit information, i.e., the speed limit value within each driving distance interval relative to the reference position; specifically, it includes: the starting driving distance S of the speed limit; limit_start , the end distance of the speed limit S limit_end And the speed limit value v limit ;

[0152] 3) Obstacle information, including the distance s of the obstacle relative to the reference position obstacle , and the speed of the obstacle, etc.obstacle ; Of course, in actual driving, there may be no obstacles.

[0153] 4) ADC kinematic data, such as maximum velocity v max , optimal acceleration a preffered , maximum jerk a′ max , optimal jerk a′ perffered , maximum jerk a″ max , optimal jerk a″ perffered , minimum deceleration d min , optimal deceleration d perffered , minimum deceleration speed d′ min , optimal deceleration speed d′ perffered , minimum deceleration speed d″ min , optimal deceleration speed d″ perffered Of course, these data can be actually applied to vehicle motion planning, or they may just be used as a reference for values ​​and not directly used in calculations.

[0154] Of course, you can further set the following parameters:

[0155] The total speed planning time is t total , the step length of speed planning is t step , t(n) represents the total time to skip n steps, where: 0≤n<(t total +t step ) / t step .

[0156] The total distance of the path planning is s total , the step length of path planning is s step , s(m) represents the total distance of skipping m steps, where: 0≤m<(s total +s step ) / s step .

[0157] The vehicle motion planning process can have the following premise assumptions: ADC is based on s start , v start and a start As the initial state, the movement begins, and the ADC must meet the vehicle's operational constraints and cannot collide with obstacles; the safe distance between the ADC and the obstacle is: distance obstacle_safe , the safety time between ADC and the obstacle is: t obstacle_safe .

[0158] The input of vehicle motion planning can be the planned distance s(n), the planned speed v(n), the planned acceleration a(n), the planned jerk a′(n), and the planned jerk a″(n). As for the specific process of vehicle motion planning, please refer to the description of the above embodiment and will not be repeated here.

[0159] like Figure 3 As shown, the embodiment of the present application further provides a vehicle motion planning device, comprising:

[0160] An acquisition module 301 is configured to acquire, during a planning cycle, initial motion data of a preset motion parameter and a preset parameter value associated with each of a plurality of preset control parameters, and determine a safe driving distance, wherein the preset parameter value includes a preset parameter value for matching an acceleration state;

[0161] A determination module 302 is configured to determine, based on the initial motion data and the various preset parameter values, candidate driving distances corresponding to the various preset parameter values;

[0162] The first planning module 303 is used to plan preset motion parameters to obtain target motion data when a first preset condition is satisfied between the candidate driving distance and the safe driving distance, wherein the first preset condition is used to indicate that motion planning can be performed in an accelerated state.

[0163] Optionally, the plurality of preset control parameters include speed and at least one of the following:

[0164] Acceleration, the preset parameter values ​​associated with acceleration include a first acceleration value for matching an acceleration state, and a second acceleration value for matching a deceleration state;

[0165] Jerk, the preset parameter values ​​associated with the jerk include a first jerk value for matching an acceleration state, and a second jerk value for matching a deceleration state;

[0166] Jerk, the preset parameter value associated with the jerk includes a first jerk value for matching an acceleration state, and a second jerk value for matching a deceleration state;

[0167] The speed-associated preset parameter value includes a first speed value for matching the acceleration state.

[0168] Optionally, the candidate driving distance includes at least one of the following:

[0169] a first candidate driving distance, where the first candidate driving distance is a candidate driving distance determined based on a preset parameter value associated with a preset control parameter and used to match an acceleration state;

[0170] a second candidate driving distance, the second candidate driving distance being a candidate driving distance determined based on a preset parameter value associated with a preset control parameter for matching a deceleration state;

[0171] a third candidate driving distance, the third candidate driving distance being a candidate driving distance determined based on a first parameter value of a preset control parameter, wherein the first parameter value is a maximum value between a preset parameter value associated with the preset control parameter for matching an acceleration state and an initial parameter value of the preset control parameter, and the initial motion data includes the initial parameter value of the preset control parameter;

[0172] A fourth candidate driving distance is a candidate driving distance determined based on a second parameter value of a preset control parameter, wherein the second parameter value is a minimum value between a preset parameter value associated with the preset control parameter for matching a deceleration state and an initial parameter value of the preset control parameter, and the initial motion data includes the initial parameter value of the preset control parameter.

[0173] Optionally, the first planning module 303 may include at least one of the following:

[0174] a first planning unit configured to, when the first driving distance is greater than the second driving distance and the second driving distance is less than the safe driving distance, use the minimum of the first driving distance and the safe driving distance as the planned driving distance, and plan the preset motion parameters based on the planned driving distance; wherein the candidate driving distances include the first candidate driving distance and the second candidate driving distances, the first driving distance being the maximum value among the first candidate driving distances, and the second driving distance being the maximum value among the second candidate driving distances;

[0175] The second planning unit is configured to use a candidate driving distance determined based on the first speed value as a planned driving distance, and plan preset motion parameters based on the planned driving distance, if the first driving distance is less than or equal to the second driving distance, the third driving distance is less than the safe driving distance, and the third driving distance is greater than the fourth driving distance; wherein the candidate driving distances include a first candidate driving distance, a second candidate driving distance, a third candidate driving distance, and a fourth candidate driving distance, the third driving distance being a minimum value among the third candidate driving distances, and the fourth driving distance being a maximum value among the fourth candidate driving distances.

[0176] Optionally, the vehicle motion planning device may further include:

[0177] A second planning module is configured to return to the previous planning cycle to plan the preset control parameters if the candidate driving distance and the safe driving distance do not satisfy the first preset condition;

[0178] The initial motion data obtained in a planning cycle is the target motion data obtained by planning the preset control parameters in the previous planning cycle.

[0179] Optionally, the second planning module may include:

[0180] An acquisition unit, used to acquire candidate driving distances in a previous planning cycle;

[0181] AND at least one of the following:

[0182] a third planning unit, configured to, when the first driving distance is greater than the second driving distance and the second driving distance is less than the safe driving distance, use the second driving distance as the planned driving distance and plan the preset motion parameters according to the planned driving distance;

[0183] and a fourth planning unit configured to, when the first driving distance is less than or equal to the second driving distance and the fourth driving distance is less than the safe driving distance, use a candidate driving distance determined based on the second acceleration value as a planned driving distance, and to plan preset motion parameters based on the planned driving distance; wherein the plurality of preset control parameters include acceleration.

[0184] Optionally, the determining module 302 includes:

[0185] a first determining unit, configured to obtain, when an obstacle exists, movement data of the obstacle, and determine a maximum travel distance based on the movement data of the obstacle;

[0186] The second determining unit is configured to determine a safe driving distance according to the maximum driving distance, and a preset safe distance and safety time.

[0187] It should be noted that the vehicle motion planning device is a device corresponding to the above-mentioned vehicle motion planning method. All implementation methods in the above-mentioned method embodiments are applicable to the embodiments of the device and can achieve the same technical effects.

[0188] Figure 4 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0189] The electronic device may include a processor 401 and a memory 402 storing computer program instructions.

[0190] Specifically, the processor 401 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0191] Memory 402 may include a large capacity memory for data or instructions. By way of example and not limitation, memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 402 may include removable or non-removable (or fixed) media. Where appropriate, memory 402 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, memory 402 is a non-volatile solid-state memory.

[0192] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0193] The processor 401 implements any one of the vehicle motion planning methods in the above embodiments by reading and executing computer program instructions stored in the memory 402 .

[0194] In one example, the electronic device may further include a communication interface 403 and a bus 310. Figure 4 As shown, the processor 401 , the memory 402 , and the communication interface 403 are connected via the bus 310 and communicate with each other.

[0195] The communication interface 403 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0196] Bus 404 includes hardware, software or both, and the parts of online data flow metering equipment are coupled to each other. For example, but not limitation, bus can include accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 404 can include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0197] In addition, in conjunction with the vehicle motion planning method in the above embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the vehicle motion planning methods in the above embodiments is implemented.

[0198] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0199] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0200] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0201] Aspects of the present disclosure have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It is also understood that each box in the block diagram and / or flowchart and the combination of the boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0202] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A vehicle motion planning method, characterized in that: include: In a planning cycle, initial motion data of a preset motion parameter and a preset parameter value associated with each of a plurality of preset control parameters are obtained, and a safe driving distance is determined, wherein the preset parameter value includes a preset parameter value for matching an acceleration state; Determining, based on the initial motion data and each of the preset parameter values, candidate driving distances corresponding to each of the preset parameter values; When a first preset condition is satisfied between the candidate driving distance and the safe driving distance, planning the preset motion parameters to obtain target motion data, wherein the first preset condition is used to indicate that motion planning can be performed in an accelerated state; The first preset condition between the candidate driving distances and the safe driving distances includes: there is a candidate driving distance shorter than the safe driving distance among the candidate driving distances.

2. The method according to claim 1, characterized in that The plurality of preset control parameters include speed and at least one of the following: acceleration, wherein the preset parameter values ​​associated with the acceleration include a first acceleration value for matching an acceleration state and a second acceleration value for matching a deceleration state; Jerk, wherein the preset parameter values ​​associated with the jerk include a first jerk value for matching an acceleration state and a second jerk value for matching a deceleration state; jerk, wherein the preset parameter value associated with the jerk includes a first jerk value for matching an acceleration state, and a second jerk value for matching a deceleration state; The speed-associated preset parameter value includes a first speed value for matching an acceleration state.

3. The method according to claim 2, characterized in that The candidate driving distance includes at least one of the following: a first candidate driving distance, wherein the first candidate driving distance is a candidate driving distance determined based on a preset parameter value associated with the preset control parameter and used to match an acceleration state; a second candidate driving distance, the second candidate driving distance being a candidate driving distance determined based on a preset parameter value associated with the preset control parameter and used to match a deceleration state; a third candidate driving distance, the third candidate driving distance being a candidate driving distance determined based on a first parameter value of the preset control parameter, wherein the first parameter value is a maximum value between a preset parameter value associated with the preset control parameter for matching an acceleration state and an initial parameter value of the preset control parameter, and the initial motion data includes the initial parameter value of the preset control parameter; A fourth candidate driving distance, the fourth candidate driving distance being a candidate driving distance determined based on a second parameter value of the preset control parameter, wherein the second parameter value is a minimum value between a preset parameter value associated with the preset control parameter for matching a deceleration state and an initial parameter value of the preset control parameter, and the initial motion data includes the initial parameter value of the preset control parameter.

4. The method according to claim 3, characterized in that When a first preset condition is satisfied between the candidate driving distance and the safe driving distance, planning the preset motion parameters includes: When the first driving distance is greater than the second driving distance and the second driving distance is less than the safe driving distance, the minimum value between the first driving distance and the safe driving distance is used as the planned driving distance, and the preset motion parameters are planned based on the planned driving distance; wherein the candidate driving distances include the first candidate driving distance and the second candidate driving distances, the first driving distance is the minimum value among the first candidate driving distances, and the second driving distance is the maximum value among the second candidate driving distances.

5. The method according to claim 1, wherein Determining the safe driving distance includes: In the case where an obstacle exists, obtaining motion data of the obstacle, and determining a maximum driving distance based on the motion data of the obstacle; The safe driving distance is determined based on the maximum driving distance, and a preset safe distance and safety time.

6. A vehicle motion planning device, characterized in that: The device comprises: an acquisition module, configured to acquire, during a planning cycle, initial motion data of a preset motion parameter and a preset parameter value associated with each of a plurality of preset control parameters, and determine a safe driving distance, wherein the preset parameter value includes a preset parameter value for matching an acceleration state; a determination module, configured to determine, based on the initial motion data and each of the preset parameter values, candidate driving distances corresponding to each of the preset parameter values; a first planning module configured to plan the preset motion parameters to obtain target motion data when a first preset condition is satisfied between the candidate driving distance and the safe driving distance, wherein the first preset condition indicates that motion planning can be performed in an accelerated state; The first preset condition between the candidate driving distances and the safe driving distances includes: there is a candidate driving distance shorter than the safe driving distance among the candidate driving distances.

7. An electronic device, characterized in that: The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the vehicle motion planning method according to any one of claims 1 to 5 is implemented.

8. A computer storage medium, characterized in that The computer storage medium stores computer program instructions, which, when executed by a processor, implement the vehicle motion planning method according to any one of claims 1 to 5.

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