CN116749965A

CN116749965A - Vehicle speed planning method and device, electronic equipment and storage medium

Info

Publication number: CN116749965A
Application number: CN202310601635.6A
Authority: CN
Inventors: 孟祥哲; 刘斌; 吴杭哲; 李伟男; 于欣彤; 王庚; 于淼
Original assignee: Faw Nanjing Technology Development Co ltd; FAW Group Corp
Current assignee: Faw Nanjing Technology Development Co ltd; FAW Group Corp
Priority date: 2023-05-25
Filing date: 2023-05-25
Publication date: 2023-09-15

Abstract

The embodiment of the invention discloses a vehicle speed planning method, a vehicle speed planning device, electronic equipment and a storage medium. The method comprises the following steps: acquiring state data of a driving vehicle, and sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and a vehicle speed of the driving vehicle at the future time point; generating at least one alternative speed curve data according to the sampling data and the state data; respectively determining acceleration information of the at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information; and determining target speed curve data from the at least one alternative speed curve data, so as to complete the speed planning of the driving vehicle according to the target speed curve data. According to the technical scheme provided by the embodiment of the invention, the calculation force required by vehicle speed planning is reduced, and the driving safety of the driving vehicle is ensured.

Description

Vehicle speed planning method and device, electronic equipment and storage medium

Technical Field

The embodiment of the invention relates to the technical field of vehicles, in particular to a vehicle speed planning method, a vehicle speed planning device, electronic equipment and a storage medium.

Background

The speed planning of a vehicle is an important component in the trajectory planning output of an autopilot system.

However, the existing vehicle speed planning method has high calculation force, so that the speed planning result cannot be calculated in time, potential danger is easily brought to an automatic driving function user, and the vehicle speed planning method is easy to solve.

Disclosure of Invention

The embodiment of the invention provides a vehicle speed planning method, a vehicle speed planning device, electronic equipment and a storage medium, which are used for reducing calculation force required by vehicle speed planning and ensuring driving safety of a driving vehicle.

According to an aspect of the present invention, there is provided a vehicle speed planning method, which may include:

acquiring state data of a driving vehicle, and sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and the vehicle speed of the driving vehicle at the future time point;

generating at least one alternative speed curve data according to the sampling data and the state data;

respectively determining acceleration information of at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information;

And determining target speed curve data from at least one alternative speed curve data, so as to complete the speed planning of the driving vehicle according to the target speed curve data.

According to another aspect of the present invention, there is provided a vehicle speed planning apparatus, which may include:

the system comprises a sampling data obtaining module, a sampling data processing module and a data processing module, wherein the sampling data obtaining module is used for obtaining state data of a driving vehicle and obtaining sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and a vehicle speed of the driving vehicle at the future time point;

the alternative speed curve data generation module is used for generating at least one alternative speed curve data according to the sampling data and the state data;

the first alternative speed curve data updating module is used for respectively determining acceleration information of at least one alternative speed curve data and updating the at least one alternative speed curve data according to the acceleration information;

and the target speed curve data determining module is used for determining target speed curve data from at least one piece of alternative speed curve data so as to complete the speed planning of the driving vehicle according to the target speed curve data.

According to another aspect of the present invention, there is provided an electronic device, which may include:

At least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to cause the at least one processor to implement the vehicle speed planning method provided by any embodiment of the present invention when executed.

According to another aspect of the present invention, there is provided a computer readable storage medium having stored thereon computer instructions for causing a processor to execute a vehicle speed planning method according to any embodiment of the present invention.

According to the technical scheme, the state data of the driving vehicle are obtained, and based on the state data, the preset sampling interval and the preset sampling number, sampling data are obtained, wherein the sampling data comprise a future time point and the vehicle speed of the driving vehicle at the future time point; generating at least one alternative speed curve data according to the sampling data and the state data; respectively determining acceleration information of at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information; and determining target speed curve data from at least one alternative speed curve data, so as to complete the speed planning of the driving vehicle according to the target speed curve data. According to the technical scheme provided by the embodiment of the invention, the alternative speed curve data which do not meet the conditions can be screened out by updating at least one alternative speed curve data according to the acceleration information, so that the calculation force required by vehicle speed planning is reduced, and the driving safety of a driving vehicle is ensured.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention, nor is it intended to be used to limit the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

Fig. 1 is a flowchart of a vehicle speed planning method according to a first embodiment of the present invention;

fig. 2 is a flowchart of a vehicle speed planning method provided in a second embodiment of the present invention;

fig. 3 is a flowchart of a vehicle speed planning method provided in a third embodiment of the present invention;

FIG. 4 is a flowchart of an alternative example of a vehicle speed planning method provided in the third embodiment of the present invention;

fig. 5 is a block diagram showing the structure of a vehicle speed planning apparatus according to a fourth embodiment of the present invention;

fig. 6 is a schematic structural diagram of an electronic device implementing a vehicle speed planning method according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. The cases of "target", "original", etc. are similar and will not be described in detail herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a vehicle speed planning method according to a first embodiment of the present invention. The embodiment is applicable to the situation of planning the vehicle speed. The method can be implemented by the vehicle speed planning device provided by the embodiment of the invention, the device can be implemented by software and/or hardware, and the device can be integrated on electronic equipment, and the electronic equipment can be various user terminals or servers.

Referring to fig. 1, the method of the embodiment of the present invention specifically includes the following steps:

s110, acquiring state data of a driving vehicle, and sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and a vehicle speed of the driving vehicle at the future time point.

The driving vehicle may be an autonomous driving vehicle or an auxiliary driving vehicle, may be a vehicle driven by a driving object, or the like. The state data is data related to a state of driving the vehicle; the status data may be, for example, the speed of the driving vehicle, the lane in which the driving vehicle is located, the lane change status of the driving vehicle, the position of the driving vehicle and/or the yaw angle of the driving vehicle. Etc. The preset sampling interval may be understood as a preset sampling time interval, and may be understood as a time interval for planning a future vehicle speed of the driving vehicle. The preset number of samples may be understood as the number of time points of the preset samples, and may be understood as the number of time points at which the future vehicle speed of the driving vehicle is planned. The sampled data may be understood as sampled data; the sample data may be in the form of key-value pairs.

It should be noted that the preset sampling interval and/or the preset sampling number may be determined according to at least one of a state of the driving vehicle, a driving stage of the driving vehicle, a vehicle speed planning requirement, a calculation requirement, and the like

In an embodiment of the invention, the sampled data may include a future point in time and a vehicle speed of the driving vehicle at the future point in time; the sampled data may also include a future point in time, a position of the driving vehicle at the future point in time, and a vehicle speed of the driving vehicle at the future point in time; in the embodiment of the present invention, the content of the sampled data is not particularly limited.

It should be noted that the future time point may be understood as a time point at which the future speed and/or distance is planned based on the preset sampling interval and the preset number of samples, for example, the preset sampling interval is 0.5s and the preset number of samples is 6, and then the future time point may be considered as including 0.5s, 1s, 1.5s, 2s, 2.5s and 3s after the current time point with respect to the current time point. The future time point is obtained based on the current time point, the preset sampling interval, and the preset sampling number, for example, the preset sampling interval is 1s, the preset sampling number is 6, and then the future time point can be considered to include 1s, 2s, 3s, 4s, 5s, and 6s based on the current time point.

In the embodiment of the invention, the state data of the driving vehicle can be acquired, the sampling data can be acquired based on the state data, the preset sampling interval and the preset sampling number, the state data of the driving vehicle can be acquired, the driving speed of the driving vehicle at a plurality of time points in the future is planned based on the state data, the preset sampling interval and the preset sampling number, for example, the preset sampling interval is 1s, the preset sampling number is 3, the driving speed of the driving vehicle is planned to be 50km/h relative to the future time point 1s at the current time point based on the state data, the preset sampling interval and the preset sampling number, the driving speed of the driving vehicle is planned to be 51km/h relative to the future time point 2s at the current time point, and the driving speed of the driving vehicle is planned to be 52km/h relative to the future time point 3s at the current time point.

S120, generating at least one alternative speed curve data according to the sampling data and the state data.

The alternative speed profile data may be understood as profile data that is alternative to the target speed profile data. The target speed profile data may be understood as data capable of characterizing a vehicle speed plan for driving the vehicle.

It should be noted that the alternative speed profile data may be, for example, a profile in which the abscissa represents time and the ordinate represents speed; the candidate speed profile data may be, for example, data that can form a correspondence relationship between time and speed of a profile, or may be, for example, data expressed in the form of a functional relation. Correspondingly, the target speed profile data may be, for example, a profile in which the abscissa represents time and the ordinate represents speed; the target speed profile data may be, for example, data that can form a correspondence relationship between time and speed of a profile, or may be, for example, data expressed in the form of a functional relation.

In the embodiment of the present invention, the alternative speed profile data may represent a relationship between an alternative future time point and the planned vehicle speed, and may also represent a relationship between an alternative future time point, the planned vehicle speed, and the planned position of the driving vehicle. Accordingly, the target speed profile data may represent a relationship between a future point in time and the planned vehicle speed, and may also represent a relationship between the future point in time, the planned vehicle speed, and the planned position of the driving vehicle.

In an embodiment of the present invention, the at least one alternative speed profile data may exist in the form of a list of alternative speed profiles.

In an embodiment of the present invention, the state data may include longitudinal state data of the driving vehicle, and the at least one candidate speed profile data is generated from the sampled data and the longitudinal state data. The longitudinal state data may be understood as data of the driving vehicle relating to the direction of a driving lane in which the driving vehicle is traveling; longitudinal state data may be understood, for example, as the speed, acceleration and/or longitudinal position of the driving vehicle; the longitudinal position may be, for example, the position of the driving vehicle on the driving lane, for example, the longitudinal position of the driving vehicle in the world coordinate system, etc.

S130, respectively determining acceleration information of at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information.

The acceleration information may be understood as information relating to the acceleration of the alternative speed profile data, which may comprise, for example, maximum acceleration information and/or minimum acceleration information.

In the embodiment of the invention, the acceleration information of at least one alternative speed curve data can be respectively determined, the at least one alternative speed curve data can be screened according to the acceleration information to screen out the alternative speed curve data which does not meet the requirements, and/or the at least one alternative speed curve data is corrected according to the acceleration information to correct the alternative speed curve data which does not meet the requirements, so that the at least one alternative speed curve data is updated according to the screening result and/or the correction result.

And S140, determining target speed curve data from at least one piece of alternative speed curve data, so as to complete the speed planning of the driving vehicle according to the target speed curve data.

In the embodiment of the invention, the target speed curve data can be determined from at least one piece of candidate speed curve data, for example, the candidate speed curve data with the minimum required cost is determined from the at least one piece of candidate speed curve data and used as the target speed curve data, so that the speed planning of the driving vehicle is completed according to the target speed curve data.

It should be noted that the target speed profile data may include a vehicle speed planning situation for a future driving vehicle, for example, including planning a driving vehicle speed up to 50km/h with respect to a future time point after 1s from the current time point, so that the vehicle speed planning for the driving vehicle may be completed according to the target speed profile data.

It should be noted that, in the embodiment of the present invention, the speed profile corresponding to each of the at least one candidate speed profile data may be different in length of the spanned time interval, for example, the spanned time interval may be 0s-1s based on the data corresponding to the future time point 1s in the sampled data, the spanned time interval may be 0s-2s based on the data corresponding to the future time point 2s in the sampled data, in order to ensure the consistency and integrity of the at least one candidate speed profile data, the at least one candidate speed profile data may be interpolated and complemented before the target speed profile data is determined from the at least one candidate speed profile data, and the at least one candidate speed profile data may be updated according to the interpolation and complement results.

It should be noted that, after the vehicle speed planning of the driving vehicle is completed according to the target speed curve data, when the driving vehicle runs according to the vehicle speed planning, the driving vehicle does not necessarily run according to the whole vehicle speed planning, for example, the vehicle speed planning time span is 8s, and the driving vehicle may run according to the planning speed in 0s-1s in the vehicle speed planning, and then the driving vehicle may run according to the planning result after the next vehicle speed planning.

It should be noted that after the vehicle speed planning of the driving vehicle is completed according to the target speed curve data, a speed control instruction can be generated according to the vehicle speed planning result so as to send the speed control instruction to the driving vehicle, so that the driving vehicle can drive according to the vehicle speed planning, and the tracking of the vehicle speed planning result is realized.

An optional technical solution, respectively determining acceleration information of at least one candidate speed curve data, and updating the at least one candidate speed curve data according to the acceleration information, includes: determining acceleration information corresponding to the candidate speed curve data for each candidate speed curve data in the at least one candidate speed curve data, wherein the acceleration information comprises maximum acceleration information and minimum acceleration information; judging whether the alternative speed curve data meet the preset vehicle dynamics constraint requirement according to the maximum acceleration information and the minimum acceleration information; and updating the at least one alternative speed curve data according to the alternative speed curve data meeting the vehicle dynamics constraint requirement in the at least one alternative speed curve data.

The vehicle dynamics constraint requirements are understood to be preset requirements for dynamics constraints of the driving vehicle, such as maximum acceleration and/or minimum acceleration of the driving vehicle, etc.; the vehicle dynamics constraint requirement may be preset according to the attribute of the driving vehicle, or may be obtained after calibrating the driving vehicle or a driving system loaded by the driving vehicle.

For example, each of the at least one candidate speed profile data may be represented in the form of a polynomial curve of a plurality of times, for example, the candidate speed profile data may be a polynomial curve of a fourth order of a highest term when the operating condition type of the driving vehicle is a cruise condition type, and the candidate speed profile data may be a polynomial curve of a fifth order of a highest term when the operating condition type of the driving vehicle is a following condition type, to connect the states of the start point and the end point of the vehicle speed planning by the polynomial curve of a plurality of times; for each of the at least one candidate speed profile data, for example, a method of solving an extreme point of an equation may be adopted to solve a maximum acceleration and a minimum acceleration in the candidate speed profile data; judging whether the alternative speed curve data meets the preset vehicle dynamics constraint requirement according to the maximum acceleration and the minimum acceleration; the alternative speed curve data which does not meet the preset vehicle dynamics constraint requirement can be ignored, and the at least one alternative speed curve data is updated according to the alternative speed curve data which meets the vehicle dynamics constraint requirement in the at least one alternative speed curve data. The working condition type can be understood as the driving state type of the driving vehicle; the cruising condition type can be understood as a type in which the driving vehicle is in a running state in which the continuous speed is relatively stable; the following condition type may be understood as a type in which the driving vehicle is in a running state of following the preceding vehicle.

In the embodiment of the invention, acceleration information corresponding to the candidate speed curve data can be determined for each candidate speed curve data in at least one candidate speed curve data, wherein the acceleration information comprises maximum acceleration information and minimum acceleration information; judging whether the alternative speed curve data meet the preset vehicle dynamics constraint requirement according to the maximum acceleration information and the minimum acceleration information; and updating the at least one alternative speed curve data according to the alternative speed curve data meeting the vehicle dynamics constraint requirement in the at least one alternative speed curve data. According to the scheme provided by the embodiment of the invention, at least one alternative speed curve data can be updated more accurately, so that the alternative speed curve data which does not meet the preset vehicle dynamics constraint requirement is screened out, and the subsequent calculation force for processing the alternative speed curve data which does not meet the preset vehicle dynamics constraint requirement is further saved.

In another optional technical solution, before sampling to obtain the sampled data based on the state data, the preset sampling interval and the preset sampling number, the method further includes: acquiring lane vehicle data of a driving lane, wherein the driving lane is a lane where a driving vehicle runs, and the lane vehicle data is data of a lane vehicle positioned on the driving lane; determining the working condition type of the driving vehicle according to the state data and the lane vehicle data; based on the state data, a preset sampling interval and a preset sampling number, sampling to obtain sampling data comprises: under the condition that the working condition type is a cruising working condition type, sampling to obtain sampling data according to a preset cruising speed, a preset dynamic feasible range, state data, a preset sampling interval and a preset sampling number; under the condition that the working condition type is the following vehicle working condition type, sampling data is obtained according to a preset sampling distance interval, lane vehicle data, state data, a preset sampling interval and a preset sampling number.

In an embodiment of the present invention, the lane vehicle may be a vehicle other than a driving vehicle located on a driving lane. The lane vehicle may be a vehicle that is traveling and/or stopped on a driving lane. A lane vehicle may be all vehicles located on a driving lane; it may also be a vehicle located on the driving lane within a first preset range of the driving vehicle, the lane vehicle may be, for example, a front vehicle closest to the driving vehicle and/or a rear vehicle closest to the driving vehicle, and the lane vehicle may be, for example, a front vehicle within a first preset distance from the driving vehicle and/or a rear vehicle within a second preset distance from the driving vehicle.

In an embodiment of the invention, the lane vehicle data may be, for example, the speed, acceleration, position, direction relative to the driving vehicle and/or distance relative to the driving vehicle of the lane vehicle. It should be noted that the position mentioned in the embodiment of the present invention may be a position on the driving lane, a position under the world coordinate system, or the like, and is not particularly limited.

For example, the status data may include a cruise speed setting of the driving vehicle, which may characterize whether the driving vehicle is set to a preset cruise speed. Lane vehicle data of a driving lane can be acquired; determining whether a collision target exists in the driving lane according to the lane vehicle data, wherein the collision target can be understood as a lane vehicle which has the possibility of exceeding a first preset collision with the driving vehicle; under the condition that the driving vehicle is set to be at a preset cruising speed and no collision target exists, determining the working condition type of the driving vehicle as the cruising working condition type; and under the condition that the driving vehicle is set to be at the preset cruising speed and a collision target exists, determining the working condition type of the driving vehicle as the following working condition type.

For example, the status data may include cruise speed settings of the driving vehicle, and vehicle data of the driving vehicle, which may include speed, acceleration, and/or position related data of the driving vehicle. Lane vehicle data of a driving lane can be acquired; determining whether a collision target exists in the driving lane according to the vehicle data and the lane vehicle data; under the condition that the driving vehicle is set to be at a preset cruising speed and no collision target exists, determining the working condition type of the driving vehicle as the cruising working condition type; and under the condition that the driving vehicle is set to be at the preset cruising speed and a collision target exists, determining the working condition type of the driving vehicle as the following working condition type.

For example, in the case where the operating condition type is a cruise operating condition type, the planned vehicle speed that can be achieved by driving the vehicle at each future time point may be obtained by uniformly sampling in a preset dynamics feasible range according to the preset cruise speed, the state data, the preset sampling interval, and the preset sampling number, so as to obtain each future time point in each future time point and a direct correspondence relationship between the planned vehicle speed corresponding to the future time point, so that sampling data may be obtained according to the correspondence relationship, and the sampling data may exist in the form of a sampling point list.

For example, where the condition type is a following condition type, the lane vehicle data may include following vehicle data of a following vehicle closest to the driving vehicle in front of the driving vehicle, a travel track of the following vehicle within a future preset time period may be predicted based on the following vehicle data, and a following vehicle track may be obtained, the following vehicle track may include a future time point, a following speed of the following vehicle at the future time point, and/or a following position of the following vehicle at the future time point; the state data may include a lateral planned trajectory of the driving vehicle, the lateral planned trajectory may represent a lateral movement state of the driving vehicle on a trajectory of future driving, the lateral planned trajectory may be obtained based on lane condition data of a lane and/or a pre-planned driving vehicle driving route, the lane condition data may represent a road condition of the lane, for example, may be due to a driving lane having an obstacle in front of the driving vehicle for one hundred meters, the lateral planned trajectory may include changing the lane to avoid the obstacle on the driving lane after the driving vehicle drives for one hundred meters, and the following vehicle trajectory may be projected in a longitudinal direction of the lateral planned trajectory to obtain a position correspondence of the future following vehicle in the driving vehicle driving route; determining a specific time value of each future time point according to a preset sampling interval and a preset sampling number, and respectively determining the position point of the following vehicle in the driving vehicle driving route at each future time point; position sampling is respectively carried out at a preset sampling distance interval behind each position point, so that a position sampling result is obtained; setting the vehicle speed corresponding to each future time point as the speed of the following vehicle at the future time point; and obtaining sampling data according to the obtained vehicle speed, the position sampling result and the specific time value of each future time point.

In the embodiment of the invention, the sampling data can be obtained by sampling according to the preset cruising speed, the preset sampling distance interval, the lane vehicle data, the state data, the preset sampling interval and the preset sampling number.

It should be noted that, in the embodiment of the present invention, in the case where the vehicle speed in the acquired data acquired is greater than the preset cruising speed, the vehicle speed greater than the preset cruising speed may be set as the preset cruising speed.

In the embodiment of the invention, the lane vehicle data of the driving lane can be obtained, wherein the driving lane is the lane where the driving vehicle runs, and the lane vehicle data is the data of the lane vehicle positioned on the driving lane; determining the working condition type of the driving vehicle according to the state data and the lane vehicle data; under the condition that the working condition type is a cruising working condition type, sampling to obtain sampling data according to a preset cruising speed, a preset dynamic feasible range, state data, a preset sampling interval and a preset sampling number; under the condition that the working condition type is the following vehicle working condition type, sampling data is obtained according to a preset sampling distance interval, lane vehicle data, state data, a preset sampling interval and a preset sampling number. According to the technical scheme provided by the embodiment of the invention, the sampled data obtained by sampling can be more in line with the type of the working condition of the driving vehicle.

Example two

Fig. 2 is a flowchart of another vehicle speed planning method according to the second embodiment of the present invention. The present embodiment is optimized based on the above technical solutions. In this embodiment, optionally, determining the target speed profile data from the at least one candidate speed profile data includes: based on the state data and the preset cruising speed, respectively analyzing at least one alternative speed curve data to obtain an analysis result; and determining target speed curve data from at least one alternative speed curve data according to the analysis result. Wherein, the explanation of the same or corresponding terms as the above embodiments is not repeated herein.

Referring to fig. 2, the method of this embodiment may specifically include the following steps:

s210, acquiring state data of a driving vehicle, and sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and a vehicle speed of the driving vehicle at the future time point.

S220, generating at least one alternative speed curve data according to the sampling data and the state data.

S230, respectively determining acceleration information of at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information.

S240, respectively analyzing at least one alternative speed curve data based on the state data and the preset cruising speed to obtain an analysis result.

In the embodiment of the invention, at least one alternative speed curve data can be respectively analyzed according to the state data and the preset cruising speed, for example, cost analysis can be performed, and an analysis result is obtained.

In the embodiment of the invention, at least one alternative speed curve data can be respectively analyzed according to an evaluation function.

S250, determining target speed curve data from at least one alternative speed curve data according to the analysis result, so as to complete the speed planning of the driving vehicle according to the target speed curve data.

In the embodiment of the invention, the target speed curve data can be determined from at least one candidate speed curve data according to the analysis result, for example, the candidate speed curve data with the minimum cost to be paid can be determined from the at least one candidate speed curve data according to the analysis result, so that the vehicle speed planning of the driving vehicle can be completed according to the target speed curve data.

In an embodiment of the present invention, determining target speed profile data from at least one candidate speed profile data according to an analysis result may include: sequencing at least one alternative speed curve data according to the analysis result; and determining target speed curve data from at least one alternative speed curve data according to the sequencing result. Specifically, at least one candidate speed curve data may be ranked according to the required cost according to the analysis result, and the candidate speed curve data with the minimum required cost is determined from the at least one candidate speed curve data according to the ranking result, so as to complete the vehicle speed planning of the driving vehicle according to the target speed curve data.

According to the technical scheme, at least one alternative speed curve data is respectively analyzed based on the state data and the preset cruising speed to obtain an analysis result; and determining target speed curve data from at least one alternative speed curve data according to the analysis result. In the embodiment of the invention, the optimal target speed curve data can be determined from at least one alternative speed curve data.

Example III

Fig. 3 is a flowchart of another vehicle speed planning method provided in the third embodiment of the present invention. The present embodiment is optimized based on the above technical solutions. In this embodiment, optionally, before analyzing the at least one candidate speed profile data based on the state data and the preset cruising speed, respectively, before obtaining an analysis result, the method further includes: acquiring surrounding vehicle data of surrounding vehicles, wherein the surrounding vehicles are located in a preset range of a driving vehicle; according to the surrounding vehicle data and the state data, determining a collision vehicle which is possibly collided with a driving vehicle from the surrounding vehicles; based on the state data and the preset cruising speed, at least one candidate speed curve data is respectively analyzed to obtain an analysis result, wherein the analysis result comprises: and respectively analyzing at least one alternative speed curve data based on surrounding vehicle data, state data and preset cruising speed of the collision vehicle to obtain an analysis result. Wherein, the explanation of the same or corresponding terms as the above embodiments is not repeated herein.

Referring to fig. 3, the method of this embodiment may specifically include the following steps:

s310, acquiring state data of a driving vehicle, and sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and a vehicle speed of the driving vehicle at the future time point.

S320, generating at least one alternative speed curve data according to the sampling data and the state data.

S330, respectively determining acceleration information of at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information.

S340, acquiring surrounding vehicle data of surrounding vehicles, wherein the surrounding vehicles are located in a preset range of the driving vehicle.

Wherein the surrounding vehicle data is data of surrounding vehicles located around the driving vehicle.

In an embodiment of the invention, the surrounding vehicle may be a vehicle that runs and/or stops around the driving vehicle. The surrounding vehicles may be vehicles within a second preset range of the driving vehicle, for example, may be vehicles within a circular range of 10 meters radius with the driving vehicle as a center; the surrounding vehicles may also be a front vehicle nearest to the driving vehicle, a rear vehicle nearest to the driving vehicle, a left vehicle nearest to the driving vehicle, and/or a right vehicle nearest to the driving vehicle; the surrounding vehicles may also be a front vehicle within a third predetermined distance from the driving vehicle, a rear vehicle within a fourth predetermined distance from the driving vehicle, a left vehicle within a fifth predetermined distance from the driving vehicle, and/or a right vehicle within a sixth predetermined distance from the driving vehicle.

In an embodiment of the invention, the surrounding vehicle data may be, for example, the speed, acceleration, position, direction relative to the driving vehicle and/or distance relative to the driving vehicle of the surrounding vehicle.

S350, according to the surrounding vehicle data and the state data, determining a collision vehicle which is possibly collided with the driving vehicle from the surrounding vehicles.

In the embodiment of the invention, the collision vehicle which is possibly collided with the driving vehicle can be determined from the surrounding vehicles according to the surrounding vehicle data and the state data, for example, the collision vehicle which is possibly collided with the driving vehicle and is possibly collided with the driving vehicle beyond a second preset collision can be determined from the surrounding vehicles. It is noted that the first predetermined collision may be greater than the second predetermined collision.

S360, respectively analyzing at least one alternative speed curve data based on surrounding vehicle data, state data and preset cruising speed of the collision vehicle to obtain an analysis result.

In the embodiment of the invention, the state data may include a transverse planned track of the driving vehicle, and the at least one alternative speed curve data may be respectively analyzed based on surrounding vehicle data of the collision vehicle, the state data and the preset cruising speed to obtain an analysis result.

And S370, determining target speed curve data from at least one alternative speed curve data according to the analysis result, so as to complete the speed planning of the driving vehicle according to the target speed curve data.

According to the technical scheme, at least one alternative speed curve data is analyzed respectively based on the state data and the preset cruising speed, and surrounding vehicle data of surrounding vehicles are obtained before an analysis result is obtained, wherein the surrounding vehicles are located in a preset range of a driving vehicle; according to the surrounding vehicle data and the state data, determining a collision vehicle which is possibly collided with a driving vehicle from the surrounding vehicles; and respectively analyzing at least one alternative speed curve data based on surrounding vehicle data, state data and preset cruising speed of the collision vehicle to obtain an analysis result. In the embodiment of the invention, the analysis result with higher accuracy can be obtained.

An optional technical solution, based on surrounding vehicle data, state data and preset cruising speed of the collision vehicle, respectively analyzing at least one candidate speed curve data to obtain an analysis result, includes: for each of the at least one candidate speed profile data, performing a multi-dimensional cost analysis on the candidate speed profile data based on surrounding vehicle data, status data, and a preset cruise speed of the collision vehicle; weighting and summing initial analysis values respectively corresponding to the multidimensional cost analysis to obtain target analysis values of the alternative speed curve data; and obtaining an analysis result according to the target analysis value of each candidate speed curve data.

It should be noted that the multi-dimensional cost analysis may be understood as cost analysis performed in at least one dimension; the multi-dimensional cost analysis may include a comfort cost analysis, a desired speed cost analysis, a distance travelled cost analysis, and/or a lateral acceleration cost analysis.

In the embodiment of the invention, multi-dimensional cost analysis can be performed on the candidate speed curve data based on surrounding vehicle data, state data and preset cruising speed of the collision vehicle, so as to obtain initial analysis values respectively corresponding to cost analysis of at least one dimension, wherein the initial analysis values can be understood as analysis values obtained by performing cost analysis of one dimension on the candidate speed curve data; weighting and summing initial analysis values respectively corresponding to the cost analysis of at least one dimension to obtain target analysis values of the alternative speed curve data, wherein the target analysis values can be understood as analysis values obtained by analyzing the alternative speed curve data; and obtaining an analysis result according to the target analysis value of each candidate speed curve data.

In the embodiment of the present invention, at least one candidate speed curve data may be ranked according to the target analysis value of each candidate speed curve data, for example, the at least one candidate speed curve data may be ranked according to the order of the analysis values from small to large, and the analysis result may be obtained according to the target analysis value of each ranked candidate speed curve data and/or the ranked at least one candidate speed curve data.

In the embodiment of the invention, multi-dimensional cost analysis can be performed on the alternative speed curve data aiming at each alternative speed curve data in at least one alternative speed curve data; weighting and summing initial analysis values respectively corresponding to the multidimensional cost analysis to obtain target analysis values of the alternative speed curve data; and obtaining an analysis result according to the target analysis value of each candidate speed curve data. According to the technical scheme, the analysis result with higher accuracy can be obtained.

Another optional solution, after updating at least one candidate speed profile data according to the acceleration information, further includes: for each of the at least one candidate speed profile data, performing collision detection on the candidate speed profile data based on surrounding vehicle data, status data, and candidate speed profile data of the collision vehicle; and updating the at least one alternative speed curve data according to collision detection results respectively corresponding to the at least one alternative speed curve data.

In the embodiment of the invention, the surrounding vehicle data of the collision vehicle can comprise data such as the position and/or the speed of the collision vehicle, the running track of the collision vehicle in a future preset time period can be predicted based on the surrounding vehicle data of the collision vehicle, and the collision vehicle track can be obtained and can comprise a future time point, the speed of the collision vehicle in the future time point and/or the position of the collision vehicle in the future time point; the state data can comprise a transverse planning track, and the states of the driving vehicle and the collision vehicle at various moments in the future can be recursively calculated based on surrounding vehicle data, collision vehicle track, transverse planning track and alternative speed curve data of the collision vehicle to obtain recursion results, wherein the recursion results can comprise position states, yaw angle states and/or driving vehicle circumscribed rectangular frame states and the like of the driving vehicle and the collision vehicle at various moments in the future according to vehicle attributes such as driving size and the like; according to the recurrence result, collision detection is carried out on the driving vehicle and the collision vehicle every moment, for example, a rapid rejection-straddling test method is adopted to carry out collision detection on the external rectangular frame of the driving vehicle and the external rectangular frame of the collision vehicle every moment, the method can fully utilize the yaw angle information of the vehicle, and the accurate collision detection result can be still obtained under the complex driving scene of the vehicle; updating the at least one candidate speed profile data according to the collision detection results respectively corresponding to the at least one candidate speed profile data, for example, whether the driving vehicle collides with the collision vehicle or not can be determined according to the collision detection results, the candidate speed profile data with the collision is screened out, and the at least one candidate speed profile data is updated according to the screening results. According to the technical scheme, at least one alternative speed curve data can be further screened and updated, so that calculation force required by vehicle speed planning is further reduced, and driving safety of a driving vehicle is guaranteed.

For better understanding of the technical solution of the embodiment of the present invention described above, an alternative example is provided herein. For example, referring to fig. 4, in an embodiment of the present invention, a target vehicle track may be obtained by predicting a vehicle track of a following vehicle, a surrounding vehicle, and/or a lane vehicle by using a target track prediction module, and the target vehicle track may be sent to a target screening module; determining a transverse planning track of the driving vehicle through a transverse track determining module, and sending the transverse planning track to a target screening module; acquiring target vehicle data of a following vehicle, surrounding vehicles and/or lane vehicles through a target information acquisition module, and sending the target vehicle data to a speed planning state management module and a target screening module, wherein the target vehicle data can comprise speed, acceleration and/or position and the like; the lane change state of the driving vehicle is obtained through the lane change state obtaining module, and is sent to the speed planning state management module and the target screening module, wherein the lane change state can be a straight running state or a lane change state; and acquiring state data of the driving vehicle through a driving vehicle state acquisition module, and sending the state data to a speed planning state management module and a target screening module.

The speed planning state management module can determine the working condition type of the driving vehicle according to the received state data, the lane change state and the target vehicle data, and send the working condition type to the target screening module, wherein the working condition type comprises a cruising working condition type and a following working condition type.

The target screening module comprises a following target screening module and a collision target screening module, and can determine following vehicle data of a following vehicle which is required to be followed by a driving vehicle at the current moment according to the state data, the target vehicle data and the target vehicle track under the condition that the working condition type is the following working condition type by the following target screening module, and send the following vehicle data to the following speed schedule generating module; the collision vehicle which needs to be subjected to collision detection can be determined through the collision target screening module according to the state data, the target vehicle data and the target vehicle track, the collision vehicle is uniformly output, and the target vehicle data of the collision vehicle and the data received by the target screening module are sent to the following speed planning generation module or the cruising speed track generation module according to the working condition type.

At least one alternative speed curve data for completing the speed planning of the vehicle driven at the future moment can be calculated by a vehicle speed planning generation module or a cruising speed track generation module based on a sampling method, an alternative planning result is determined according to the at least one alternative speed curve data, and the alternative planning result is sent to a result analysis and processing module, and the overall architecture of the alternative speed curve data is kept consistent with that of a submodule in the vehicle speed planning generation module or the cruising speed track generation module, and the alternative speed curve data comprises a longitudinal sampling module, a speed track generation module, a speed track analysis module and a collision detection module, but the alternative speed curve data is different due to different functions; the candidate planning results output by the vehicle speed planning generation module or the cruise speed track generation module can comprise candidate planning result success zone bits and at least one candidate speed curve data, and the candidate planning result success zone bits can represent whether each candidate vehicle speed planning is successful or not. Specifically, the longitudinal sampling module can sample based on a sampling method to obtain sampling data; the speed track generation module can generate at least one alternative speed curve data according to the sampling data and the state data; the speed track analysis module can analyze the at least one alternative speed curve data and sort the at least one alternative speed curve data according to an analysis result; the collision detection module can adopt a rapid repulsion-hurdle test method to carry out side-by-side collision detection on the collision rectangle of the driving vehicle and the collision rectangle of the collision vehicle, and update at least one alternative speed curve data according to the collision detection result.

The result analysis and processing module can select an optimal result from at least one alternative speed curve data in the alternative planning results as target speed curve data and send the optimal result to the speed tracking control module as a vehicle speed planning result.

The speed tracking control module can generate a speed control instruction according to the received vehicle speed planning result and send the speed control instruction to the driving vehicle so as to enable the driving vehicle to run according to the vehicle speed planning.

Example IV

Fig. 5 is a block diagram of a vehicle speed planning apparatus according to a fourth embodiment of the present invention, which is configured to execute the vehicle speed planning method according to any of the above embodiments. The device and the vehicle speed planning method of each embodiment belong to the same invention conception, and the details of the device for vehicle speed planning, which are not described in detail in the embodiments of the device for vehicle speed planning, can be referred to the embodiments of the method for vehicle speed planning. Referring to fig. 5, the apparatus may specifically include: the sample data obtaining module 410, the alternative speed profile data generating module 420, the first alternative speed profile data updating module 430 and the target speed profile data determining module 440.

The sampling data obtaining module 410 is configured to obtain status data of a driving vehicle, and sample to obtain sampling data based on the status data, a preset sampling interval, and a preset sampling number, where the sampling data includes a future time point and a vehicle speed of the driving vehicle at the future time point;

An alternative speed profile data generating module 420, configured to generate at least one alternative speed profile data according to the sampled data and the status data;

a first alternative speed profile data updating module 430, configured to determine acceleration information of at least one alternative speed profile data, and update the at least one alternative speed profile data according to the acceleration information;

the target speed profile data determining module 440 is configured to determine target speed profile data from at least one candidate speed profile data, so as to complete the vehicle speed planning of the driving vehicle according to the target speed profile data.

Optionally, the first alternative speed profile data update module 430 may include:

an acceleration information determining unit, configured to determine, for each of at least one candidate speed profile data, acceleration information corresponding to the candidate speed profile data, where the acceleration information includes maximum acceleration information and minimum acceleration information;

the alternative speed curve data judging unit is used for judging whether the alternative speed curve data meets the preset vehicle dynamics constraint requirement according to the maximum acceleration information and the minimum acceleration information;

And the alternative speed curve data updating unit is used for updating at least one alternative speed curve data according to the alternative speed curve data meeting the vehicle dynamics constraint requirement in the at least one alternative speed curve data.

Optionally, the vehicle speed planning device may further include:

the lane vehicle data acquisition module is used for acquiring lane vehicle data of a driving lane before sampling based on the state data, a preset sampling interval and a preset sampling number to obtain sampling data, wherein the driving lane is a lane on which the driving vehicle runs, and the lane vehicle data is data of a lane vehicle positioned on the driving lane;

the working condition type determining module is used for determining the working condition type of the driving vehicle according to the state data and the lane vehicle data;

the sample data obtaining module 410 may include:

the first sampling data obtaining unit is used for obtaining sampling data according to preset cruising speed, preset dynamic feasible range, state data, preset sampling interval and preset sampling number under the condition that the working condition type is the cruising working condition type;

the second sampling data obtaining unit is used for obtaining sampling data according to a preset sampling distance interval, lane vehicle data, state data, a preset sampling interval and a preset sampling number under the condition that the working condition type is the following working condition type.

Optionally, the target speed profile data determination module 440 may include:

the analysis result obtaining unit is used for respectively analyzing at least one alternative speed curve data based on the state data and the preset cruising speed to obtain an analysis result;

and the target speed curve data determining unit is used for determining target speed curve data from at least one alternative speed curve data according to the analysis result.

On the basis of the above scheme, optionally, the vehicle speed planning device may further include:

the system comprises a surrounding vehicle data acquisition module, a vehicle control module and a vehicle control module, wherein the surrounding vehicle data acquisition module is used for respectively analyzing at least one alternative speed curve data based on state data and preset cruising speed to acquire surrounding vehicle data of surrounding vehicles before an analysis result is obtained, wherein the surrounding vehicles are positioned in a preset range of a driving vehicle;

the collision vehicle determining module is used for determining collision vehicles which possibly collide with the driving vehicle from the surrounding vehicles according to the surrounding vehicle data and the state data;

the analysis result obtaining unit may include:

and the analysis result obtaining subunit is used for respectively analyzing at least one alternative speed curve data based on surrounding vehicle data, state data and preset cruising speed of the collision vehicle to obtain an analysis result.

Based on the above scheme, optionally, the analysis result is obtained as a subunit, which is specifically used for:

for each of the at least one candidate speed profile data, performing a multi-dimensional cost analysis on the candidate speed profile data based on surrounding vehicle data, status data, and a preset cruise speed of the collision vehicle;

weighting and summing initial analysis values respectively corresponding to the multidimensional cost analysis to obtain target analysis values of the alternative speed curve data;

and obtaining an analysis result according to the target analysis value of each candidate speed curve data.

a collision detection module for performing collision detection on the candidate speed profile data based on surrounding vehicle data, state data, and candidate speed profile data of the collision vehicle for each of the at least one candidate speed profile data;

and the second alternative speed curve data updating module is used for updating at least one alternative speed curve data according to collision detection results respectively corresponding to the at least one alternative speed curve data.

According to the vehicle speed planning device provided by the fourth embodiment of the invention, the state data of the driving vehicle is obtained through the sampling data obtaining module, and sampling data is obtained based on the state data, the preset sampling interval and the preset sampling number, wherein the sampling data comprises a future time point and the vehicle speed of the driving vehicle at the future time point; generating at least one alternative speed curve data according to the sampling data and the state data by an alternative speed curve data generating module; respectively determining acceleration information of at least one alternative speed curve data through an alternative speed curve data updating module, and updating the at least one alternative speed curve data according to the acceleration information; and determining target speed curve data from at least one alternative speed curve data by a target speed curve data determining module so as to complete the speed planning of the driving vehicle according to the target speed curve data. According to the device, the at least one alternative speed curve data is updated according to the acceleration information, and the alternative speed curve data which does not meet the conditions can be screened out, so that the calculation force required by vehicle speed planning is reduced, and the driving safety of a driving vehicle is ensured.

The vehicle speed planning device provided by the embodiment of the invention can execute the vehicle speed planning method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

It should be noted that, in the embodiment of the vehicle speed planning device, each unit and module included are only divided according to the functional logic, but are not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.

Example five

Fig. 6 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 6, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as a vehicle speed planning method.

In some embodiments, the vehicle speed planning method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle speed planning method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the vehicle speed planning method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims

1. A vehicle speed planning method, comprising:

acquiring state data of a driving vehicle, and sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number, wherein the sampling data comprises a future time point and a vehicle speed of the driving vehicle at the future time point;

Respectively determining acceleration information of the at least one alternative speed curve data, and updating the at least one alternative speed curve data according to the acceleration information;

and determining target speed curve data from the at least one alternative speed curve data, so as to complete the speed planning of the driving vehicle according to the target speed curve data.

2. The method of claim 1, wherein the determining acceleration information of the at least one candidate speed profile data, respectively, and updating the at least one candidate speed profile data based on the acceleration information, comprises:

determining acceleration information corresponding to the alternative speed curve data for each alternative speed curve data in the at least one alternative speed curve data, wherein the acceleration information comprises maximum acceleration information and minimum acceleration information;

judging whether the alternative speed curve data meets the preset vehicle dynamics constraint requirement according to the maximum acceleration information and the minimum acceleration information;

and updating the at least one alternative speed curve data according to the alternative speed curve data meeting the vehicle dynamics constraint requirements in the at least one alternative speed curve data.

3. The method of claim 1, further comprising, prior to sampling the sampled data based on the status data, a preset sampling interval, and a preset number of samples:

acquiring lane vehicle data of a driving lane, wherein the driving lane is a lane on which the driving vehicle runs, and the lane vehicle data is data of a lane vehicle positioned on the driving lane;

determining the working condition type of the driving vehicle according to the state data and the lane vehicle data;

the sampling to obtain sampling data based on the state data, a preset sampling interval and a preset sampling number includes:

under the condition that the working condition type is a cruising working condition type, sampling to obtain sampling data according to a preset cruising speed, a preset dynamic feasible range, the state data, a preset sampling interval and a preset sampling number;

and under the condition that the working condition type is a following vehicle working condition type, sampling to obtain sampling data according to a preset sampling distance interval, the lane vehicle data, the state data, a preset sampling interval and a preset sampling number.

4. The method of claim 1, wherein said determining target speed profile data from said at least one alternative speed profile data comprises:

Based on the state data and a preset cruising speed, respectively analyzing the at least one alternative speed curve data to obtain an analysis result;

and determining target speed curve data from the at least one alternative speed curve data according to the analysis result.

5. The method of claim 4, further comprising, prior to analyzing the at least one alternative speed profile data based on the status data and a preset cruise speed, respectively:

acquiring surrounding vehicle data of surrounding vehicles, wherein the surrounding vehicles are located in a preset range of the driving vehicle;

determining a collision vehicle which is possibly collided with the driving vehicle from the surrounding vehicles according to the surrounding vehicle data and the state data;

the step of respectively analyzing the at least one alternative speed curve data based on the state data and the preset cruising speed to obtain an analysis result comprises the following steps:

and respectively analyzing the at least one alternative speed curve data based on surrounding vehicle data of the collision vehicle, the state data and the preset cruising speed to obtain an analysis result.

6. The method according to claim 5, wherein the analyzing the at least one candidate speed profile data based on surrounding vehicle data of the collision vehicle, the state data, and the preset cruise speed, respectively, includes:

for each of the at least one candidate speed profile data, performing a multi-dimensional cost analysis on the candidate speed profile data based on surrounding vehicle data of the collision vehicle, the state data, and the preset cruise speed;

carrying out weighted summation on initial analysis values respectively corresponding to the multi-dimensional cost analysis to obtain target analysis values of the alternative speed curve data;

7. The method of claim 5, further comprising, after said updating said at least one alternative speed profile data based on said acceleration information:

for each of the at least one candidate speed profile data, performing collision detection on the candidate speed profile data based on surrounding vehicle data of the collision vehicle, the state data, and the candidate speed profile data;

And updating the at least one alternative speed curve data according to collision detection results respectively corresponding to the at least one alternative speed curve data.

8. A vehicle speed planning apparatus, comprising:

the first alternative speed curve data updating module is used for respectively determining acceleration information of the at least one alternative speed curve data and updating the at least one alternative speed curve data according to the acceleration information;

and the target speed curve data determining module is used for determining target speed curve data from the at least one alternative speed curve data so as to complete the speed planning of the driving vehicle according to the target speed curve data.

9. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores a computer program executable by the at least one processor to cause the at least one processor to perform the vehicle speed planning method according to any one of claims 1-7.

10. A computer readable storage medium storing computer instructions for causing a processor to implement the vehicle speed planning method according to any one of claims 1-7 when executed.