CN117519123A

CN117519123A - Vehicle track planning method, device and equipment

Info

Publication number: CN117519123A
Application number: CN202311302460.5A
Authority: CN
Inventors: 邓晨
Original assignee: Yunkong Zhixing Technology Co Ltd
Current assignee: Yunkong Zhixing Technology Co Ltd
Priority date: 2023-10-09
Filing date: 2023-10-09
Publication date: 2024-02-06

Abstract

The embodiment of the specification discloses a vehicle track planning method, device and equipment, comprising the following steps: acquiring vehicle operation sensing data for a target vehicle; the vehicle operation sensing data is used for determining the vehicle position of the target vehicle and the vehicle motion state of the target vehicle; determining a vehicle to-be-driven path in a preset range in front of a vehicle position based on vehicle operation sensing data and preset navigation path information of a target vehicle to obtain a target local path of the target vehicle; determining a target motion mode of a target vehicle at a target local path according to the vehicle operation sensing data; the target motion mode is any one of a jerk motion mode and a jerk motion mode; and determining a vehicle track planning result of the target vehicle at the target local path according to the target motion mode. The scheme of the invention is beneficial to improving the calculation efficiency of vehicle track planning, the smoothness of vehicle running and the comfort level of passengers riding.

Description

Vehicle track planning method, device and equipment

Technical Field

The present disclosure relates to the field of automatic driving trajectory planning, and in particular, to a vehicle trajectory planning method, apparatus and device.

Background

The automatic driving track planning refers to the process of calculating a safe and efficient track through an algorithm based on vehicle dynamics and environment perception information so as to guide the automatic driving automobile to run. The automatic driving track planning needs to take the dynamic characteristics, obstacles, road conditions, speed limit and other factors of the vehicle into consideration, and an optimal track is generated through an intelligent algorithm.

The definition of a trajectory is path information plus time information, that is, a target trajectory refers to an expected state of the autonomous vehicle for a future period of time, for example: every 0.1 second in the future 4 seconds, the target position, target speed and target heading of the automatic driving vehicle, namely the sequence of the target position, the speed and the heading.

In the prior art, when calculating the track of an automatic driving vehicle in a future period, an optimization problem is solved, and the optimal jerkiness corresponding to each frame in the period is obtained, but the calculation amount is too large, the calculation efficiency is low, and the waste of calculation resources is caused; in addition, the jerk thus calculated may be different for each frame, resulting in incontinuous vehicle movement patterns, which not only easily results in untimely vehicle response, but also easily results in discomfort to the occupant, and thus reduces the riding comfort of the occupant.

Disclosure of Invention

In view of this, the embodiments of the present disclosure provide a vehicle track planning method, apparatus and device, which are used to improve the calculation efficiency of vehicle track planning, the smoothness of vehicle driving, and the comfort of passengers riding.

In order to solve the above technical problems, the embodiments of the present specification are implemented as follows:

the embodiment of the specification provides a vehicle track planning method, which comprises the following steps:

acquiring vehicle operation sensing data for a target vehicle; the vehicle operation sensing data is used for determining the vehicle position of the target vehicle and the vehicle motion state of the target vehicle;

determining a vehicle to-be-driven path in a preset range in front of the vehicle position based on the vehicle operation sensing data and preset navigation path information of the target vehicle to obtain a target local path of the target vehicle;

determining a target motion mode of the target vehicle at the target local path according to the vehicle operation sensing data; the target motion mode is any one of a jerk motion mode and a jerk motion mode;

and determining a vehicle track planning result of the target vehicle at the target local path according to the target motion mode.

The embodiment of the specification provides a vehicle track planning device, which comprises:

the sensing data acquisition module is used for acquiring vehicle operation sensing data aiming at a target vehicle; the vehicle operation sensing data is used for determining the vehicle position of the target vehicle and the vehicle motion state of the target vehicle;

the local path determining module is used for determining a vehicle to-be-driven path in a preset range in front of the vehicle position based on the vehicle operation sensing data and preset navigation path information of the target vehicle to obtain a target local path of the target vehicle;

the motion mode determining module is used for determining a target motion mode of the target vehicle at the target local path according to the vehicle operation sensing data; the target motion mode is any one of a jerk motion mode and a jerk motion mode;

and the track result determining module is used for determining a vehicle track planning result of the target vehicle at the target local path according to the target motion mode.

at least one processor; the method comprises the steps of,

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

the memory stores instructions executable by the at least one processor to enable the at least one processor to:

At least one embodiment provided in this specification enables the following benefits:

After the vehicle track planning system obtains vehicle running sensing data for determining the vehicle position and the vehicle running state of the target vehicle, a vehicle to-be-driven path in a preset range in front of the current position of the target vehicle can be determined based on the vehicle running sensing data and preset navigation path information of the target vehicle, a target local path of the target vehicle is obtained, a target movement mode (the target movement mode is any one of a jerk movement mode and an acceleration movement mode) of the target vehicle at the target local path is determined according to the vehicle running sensing data, and finally a vehicle track planning result of the target vehicle at the target local path is determined according to the target movement mode.

In the scheme of the invention, when the motion trail of the target vehicle at the target local path is planned, the motion with uniform jerk or uniform acceleration is adopted for calculation and planning, so that the jerk is a fixed value or 0 when the target vehicle moves at the target local path in the calculation process, the calculation process is greatly simplified, the calculation efficiency of vehicle trail planning is improved, and the calculation resources are saved; in addition, in the scheme of the invention, the movement mode of the target vehicle when moving at the target local path is consistent, and the jerk degree is not suddenly changed, so that the method is beneficial to improving the smoothness of vehicle running and the comfort level of passengers riding, and is beneficial to ensuring the timeliness of vehicle response.

Drawings

In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.

Fig. 1 is a schematic flow chart of a vehicle track planning method according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a vehicle track planning apparatus corresponding to FIG. 1 according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a vehicle track planning apparatus corresponding to fig. 1 according to an embodiment of the present disclosure.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of one or more embodiments of the present specification more clear, the technical solutions of one or more embodiments of the present specification will be clearly and completely described below in connection with specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present specification. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without undue burden, are intended to be within the scope of one or more embodiments herein.

The following describes in detail the technical solutions provided by the embodiments of the present specification with reference to the accompanying drawings.

Fig. 1 is a flow chart of a vehicle track planning method according to an embodiment of the present disclosure. From the program perspective, the execution subject of the process may be a vehicle track planning system, or a vehicle track planning program carried at the cloud server. As shown in fig. 1, the process may include the steps of:

step 102: acquiring vehicle operation sensing data for a target vehicle; the vehicle operation sensing data is used for determining a vehicle position of the target vehicle and a vehicle motion state of the target vehicle.

In the embodiment of the present disclosure, the target vehicle may be a vehicle that needs to perform track planning, and the target vehicle may be an automatic driving vehicle or not, which is not limited specifically. In general, a vehicle needs to be subjected to track planning according to a traffic environment around a target vehicle, so that before track planning is performed, the traffic environment around the target vehicle needs to be sensed in real time by using sensing equipment, and sensing data are collected to obtain vehicle operation sensing data for the target vehicle.

In the embodiment of the present disclosure, the vehicle operation sensing data may be collected by a sensing device at a road side or may be collected by a sensing device at a vehicle end, which is not limited specifically. Vehicle operation awareness data for a target vehicle may include, but is not limited to: perception data for obstacles around the target vehicle, perception data for traffic lights in front of the target vehicle, perception data for a running course angle of the target vehicle, perception data for a running speed of the target vehicle, perception data for a running acceleration of the target vehicle, perception data for a position of the target vehicle, and the like.

Step 104: and determining a vehicle to-be-driven path in a preset range in front of the vehicle position based on the vehicle operation sensing data and the preset navigation path information of the target vehicle to obtain a target local path of the target vehicle.

In the embodiment of the present disclosure, the preset navigation path information of the target vehicle may be a target global path determined based on the starting position, the destination position, and the high-precision map data of the target vehicle. The preset navigation path information may be derived from a control system of the target vehicle, may be derived from a cloud control system, and may be derived from an electronic map provider, which is not limited in particular.

In the embodiment of the present disclosure, the target local path of the target vehicle may be a partial path of the preset navigation path information. Since the preset navigation path information of the target vehicle is only a whole path, dynamic obstacles and various traffic conditions on the path are not considered, and the target vehicle is not refined to a specific lane. Therefore, for a target vehicle that needs to perform track planning and automatically drives according to the planning result, only the preset navigation path information cannot perform accurate track planning. It is also necessary to determine a section of target local path which considers dynamic obstacles and traffic conditions and refines to a specific lane on the whole path based on the vehicle operation sensing data of the target vehicle acquired in real time.

In the embodiment of the present disclosure, in order to ensure that the determined target local path may be suitable for traffic road conditions that change in real time, the target local path may be updated once every first time interval, where the first time interval may be a shorter time interval, and may be 0.1 seconds or 0.2 seconds, which is not limited specifically. In practical application, after determining a speed sequence, a position sequence and a course angle sequence of a target vehicle at a target local path, the vehicle track planning results are input into a control system of the target vehicle, and the control system controls the target vehicle according to the vehicle track planning results. Therefore, in order to ensure that the control system can accurately control the target vehicle, the vehicle track planning result of the control system input into the target vehicle cannot be too small. Thus, even if the target local path is planned again at intervals of the first time interval, the planned target local path is the path length of the maximum possible travel of the target vehicle within a second time interval, wherein the second time interval is far greater than the first time interval; in view of the parameter requirements of the control system, the second time interval may typically take 4 seconds. If the second time interval is taken to be 4 seconds, the path length of the target local path may be the maximum distance that the target vehicle may travel in 4 seconds on the current road. For example: if the speed limit of the road where the target vehicle is currently located is 28m/s, the path length of the target local path calculated by the target vehicle is 112 meters.

Step 106: determining a target motion mode of the target vehicle at the target local path according to the vehicle operation sensing data; the target motion mode is any one of a jerk motion mode and a jerk motion mode.

In the embodiment of the present specification, the jerk is also referred to as jerk, or as jerk, and the jerk may reflect the amount of change in acceleration per second, that is: jerk may reflect the speed of the acceleration change. The vehicle will cause passengers to experience discomfort during acceleration, which is not only from acceleration, but also in relation to jerk. The larger jerk will cause the human body to generate a considerable uncomfortable feeling, so that the value of the jerk can be limited to ensure the riding comfort of the passengers, and the riding comfort of the passengers is prevented from being reduced due to the overlarge jerk. Since the limitation of jerk will be explained in detail in the following embodiments of the present embodiment, the description thereof will be omitted.

In the embodiment of the specification, before calculating the speed sequence, the position sequence and the course angle sequence of the target vehicle at the target local path, the target motion mode of the target vehicle at the target local path should be determined, and the uniform jerk motion mode or the uniform acceleration motion mode is selected to ensure that the jerk is a fixed value or 0, so that the calculation process can be greatly simplified, the calculation efficiency of vehicle track planning is improved, and the calculation resources are saved. In addition, the abrupt change of the jerk of the vehicle in the running process can be guaranteed, so that the smoothness of running of the vehicle and the comfort level of riding of passengers are improved, and the timeliness of vehicle response is guaranteed.

Step 108: and determining a vehicle track planning result of the target vehicle at the target local path according to the target motion mode.

In the embodiment of the specification, after the target motion mode of the target vehicle at the target local path is determined, the speed sequence of the target vehicle at the target local path can be calculated according to the target motion mode and part of vehicle operation sensing data; after the speed sequence is determined, the position sequence of the target vehicle at the target local path can be determined in an integral mode; after the position sequence is determined, the course angle sequence of the target vehicle at the target local path can be further determined; finally, after the speed sequence, the position sequence and the course angle sequence of the target vehicle at the target local path are determined, the vehicle track planning result of the target vehicle at the target local path is obtained.

In the method in fig. 1, when the motion trail of the target vehicle at the target local path is planned, the motion with uniform jerk or uniform acceleration is adopted for calculation and planning, so that the jerk is a fixed value or 0 when the target vehicle moves at the target local path in the calculation process, the calculation process is greatly simplified, the calculation efficiency of vehicle trail planning is improved, and the calculation resources are saved; in addition, in the scheme of the invention, the movement mode of the target vehicle when moving at the target local path is consistent, and the jerk degree is not suddenly changed, so that the method is beneficial to improving the smoothness of vehicle running and the comfort level of passengers riding, and is beneficial to ensuring the timeliness of vehicle response.

Based on the method in fig. 1, the examples of the present specification also provide some specific embodiments of the method, as described below.

In the embodiment of the present disclosure, the target local path of the target vehicle is to be determined based on the preset navigation path information of the target vehicle, so that the preset navigation path information of the target vehicle is acquired before the target local path of the target vehicle is determined.

Based on this, the method in fig. 1, step 104: based on the vehicle operation sensing data and the preset navigation path information of the target vehicle, determining a vehicle to-be-driven path within a preset range in front of the vehicle position, before obtaining the target local path of the target vehicle, may further include:

acquiring preset navigation path information of the target vehicle; the preset navigation path information is a preset navigation path obtained by performing global path planning based on the starting position, the destination position and the high-precision map data of the target vehicle.

Correspondingly, the method in fig. 1, step 104: determining a vehicle to-be-driven path within a preset range in front of the vehicle position based on the vehicle operation sensing data and the preset navigation path information of the target vehicle to obtain a target local path of the target vehicle specifically may include:

Determining a lane which does not have an obstacle in the preset distance in front of the vehicle position on the preset navigation path based on the vehicle operation sensing data and the preset navigation path information of the target vehicle, so as to obtain a drivable lane of the target vehicle; the preset distance is a maximum distance that the target vehicle can travel on the preset navigation path within a preset time period in the future.

And determining a vehicle to-be-driven path of the preset distance in front of the vehicle position from the drivable lane of the target vehicle to obtain a target local path of the target vehicle.

In the embodiment of the present disclosure, global path planning may be performed by using a global path planning algorithm based on the starting position, the destination position and the high-precision map data of the target vehicle to obtain preset navigation path information of the target vehicle. The global path planning algorithm may include, but is not limited to: an A-Star algorithm, a Dijkstra algorithm, an artificial potential field method, a graph searching method, a rapid expansion random tree method and the like. The provider of the preset navigation path information may be a cloud platform, a path planning system carried by the target vehicle, or other third party platforms, which is not limited in particular.

In this embodiment of the present disclosure, the preset distance is a maximum distance that the target vehicle can travel on the preset navigation path in a preset time period in the future, and corresponds to a path length of a target local path of the target vehicle. Wherein the future preset time period corresponds to the second time interval of the foregoing, and may take 4 seconds in general.

In the embodiment of the present disclosure, after the preset navigation path information of the target vehicle is obtained, the lane where no static obstacle and no dynamic obstacle exist in the preset distance in front of the vehicle may be determined by combining the vehicle operation sensing data. Because the more obvious static obstacle on the path can be avoided when the preset navigation path of the target vehicle is determined, but the static obstacle and the dynamic obstacle with smaller volumes can be ignored, the more refined target local path considering to avoid the static obstacle and the dynamic obstacle with smaller volumes can be determined from the preset navigation path by combining the vehicle operation sensing data acquired in real time around the vehicle. In practical application, a lane without an obstacle within a preset distance in front of the target vehicle may be selected from multiple lanes as a drivable lane, and if none of the multiple lanes is provided with an obstacle, one drivable lane may be selected as a vehicle to-be-driven path, or a drivable lane may be selected as a vehicle to-be-driven path by comprehensively considering factors such as a driving direction of the lane, and the like, which is not particularly limited.

In the embodiment of the present disclosure, the target motion mode of the target vehicle at the target local path is determined according to the vehicle operation sensing data of the target vehicle, and the main basis is to determine whether the target vehicle needs to be parked at the current moment, and if so, whether the jerk value can be calculated.

Based on this, the method in fig. 1, step 106: according to the vehicle operation sensing data, determining a target motion mode of the target vehicle at the target local path specifically may include:

and judging whether the target vehicle needs to be parked at the current moment according to the vehicle operation sensing data, and obtaining a first judgment result.

And if the first judgment result indicates that the target vehicle does not need to stop at the current moment, determining a target motion mode of the target vehicle at the target local path as a uniform acceleration motion mode.

If the first judgment result indicates that the target vehicle needs to be parked at the current moment, judging whether a preset equation is solved or not based on the target acceleration of the target vehicle at the current moment, the speed of the target vehicle at the current moment and the target parking distance, and obtaining a second judgment result; the target acceleration is an acceleration which is obtained by taking the acceleration which the target vehicle should execute at the current moment and the jerk limit into consideration and can enable the target vehicle to realize stable acceleration transition.

The preset equation is:

wherein t is _end The unit is s for parking time; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the s is a target parking distance, and the unit is m; jerk is jerk in m/s ³ 。

And if the second judging result shows that the solution is not available, determining the target motion mode of the target vehicle at the target local path as a uniform acceleration motion mode.

And if the second judging result shows that the solution exists, determining the target motion mode of the target vehicle at the target local path as a jerky motion mode.

In the embodiment of the present disclosure, the control system or the path planning system of the target vehicle may analyze whether the target vehicle needs to be parked at the current moment according to the acquired vehicle operation sensing data. Of course, the cloud platform may analyze whether the target vehicle needs to be parked at the current moment according to the vehicle operation sensing data, and then issue the analysis result to the target vehicle, which is not limited in detail.

In the embodiment of the present disclosure, if the target vehicle needs to stop at the current time, the stopping time and the jerk may be calculated according to the formula (1) and the formula (2) based on the target acceleration of the target vehicle at the current time, the speed of the target vehicle at the current time and the target stopping distance, and if the target vehicle does not exist, the target motion mode of the target vehicle at the target local path is determined as the jerk motion mode; and if the solution is not found, determining the target motion mode of the target vehicle at the target local path as a uniform acceleration motion mode. The speed of the target vehicle at the current moment can be obtained from vehicle operation sensing data, and the target parking distance can be determined according to the vehicle operation sensing data. For example: the sensing device at the vehicle end or the road side senses that the position 50 meters in front of the target vehicle is a red light, and judges that the target vehicle needs to stop, and the corresponding target stopping distance is 50 meters.

In the embodiment of the present disclosure, the target acceleration is an acceleration that is obtained by considering an acceleration that should be executed by the target vehicle at the current time and a jerk limit and that can enable the target vehicle to implement a smooth transition of the acceleration, so before calculating the target acceleration, it is first necessary to calculate an input acceleration that should be executed by the target vehicle at the current time, and determine a preset jerk limit range.

Based on this, the method in fig. 1, step 106: before determining the target motion pattern of the target vehicle at the target local path according to the vehicle operation sensing data, the method may further include:

determining an input acceleration according to the vehicle operation sensing data; the input acceleration is the calculated acceleration that should be performed by the target vehicle at the present time.

And determining a preset jerk limit range according to the value of the input acceleration.

And determining the target acceleration of the target vehicle at the current moment based on the input acceleration, the jerk limit range and the measured acceleration of the target vehicle at one frame.

Wherein, the determining the input acceleration according to the vehicle operation sensing data may specifically include:

Determining a target task to be executed by the target vehicle according to the vehicle operation sensing data; the target task is any one of a deceleration task, a following task and an acceleration task.

And calculating the input acceleration according to the target task.

If the target task is a deceleration task, the calculation formula of the input acceleration is:

wherein v is ₁ The unit is m/s for the target vehicle speed after the target vehicle is decelerated; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; s is the target deceleration distance, and the unit is m; a, a ₀ For input acceleration, the unit is m/s ² 。

If the target task is a following task, the calculation formula of the input acceleration is:

wherein v is _rel The unit is m/s for the difference between the front vehicle speed of the target vehicle at the current moment and the target vehicle speed; d is the distance between the front vehicle of the target vehicle at the current moment and the target vehicle, and the unit is m; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; t is t _re For the driver reaction time constant, 2 seconds may be set; τ _v Calculating a constant for the first following acceleration, which may be set to 2 seconds; τ _d Calculating a constant for the second following acceleration, which may be set to 5 seconds; a, a ₀ For input acceleration, the unit is m/s ² 。

If the target task is an acceleration task, the calculation formula of the input acceleration is:

wherein v is _max The unit is m/s for the target vehicle speed after the target vehicle is accelerated; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a ₀ For input acceleration, the unit is m/s ² 。

In the embodiment of the specification, according to the current vehicle operation sensing data of the target vehicle, the task which needs to be executed by the target vehicle at present can be analyzed, and whether the target vehicle needs to execute the deceleration task, the following task or the acceleration task at present is determined. After determining the target task that the target vehicle needs to execute currently, selecting formulas (3) to (5) according to different task types to calculate the acceleration that the target vehicle should execute at the current moment, namely: and inputting acceleration.

In the embodiment of the present disclosure, after determining the input acceleration, if the difference between the measured acceleration of the target vehicle at one frame time and the input acceleration is large, the acceleration of the target vehicle may change too fast, and the comfort of the passenger may be affected. Therefore, in determining the target acceleration that should be performed by the target vehicle at the present time, it is also considered to ensure that the target vehicle acceleration does not change too fast, that is: limiting jerk.

Based on this, the determining a preset jerk limit range according to the value of the input acceleration may specifically include:

judging whether the value of the input acceleration is smaller than-2 m/s ² And obtaining a third judgment result.

If the third judgment result indicates that the value of the input acceleration is not less than-2 m/s ² Determining a preset jerk limit of [ -2,2]m/s ³ 。

If the third determination result indicates that the value of the input acceleration is smaller than-2m/s ² Determining a preset jerk limit of [ -5,2]m/s ³ 。

Correspondingly, the determining the target acceleration of the target vehicle at the current moment based on the input acceleration, the jerk limit range and the vehicle measured acceleration of the target vehicle in one frame may specifically include:

if the third judgment result indicates that the value of the input acceleration is not less than-2 m/s ² The calculation formula of the target acceleration is:

a _soll ＝median([a _sollpre +2*STime,a ₀ ,a _sollpre -2*STime]) (6)

wherein a is _sollpre Measured acceleration of the vehicle for one frame on the target vehicle in m/s ² ；a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the STime is the time interval between two frames, in s; median is a median function; a, a ₀ For input acceleration, the unit is m/s ² 。

If the third judgment result shows that the value of the input acceleration is smaller than-2 m/s ² The calculation formula of the target acceleration is:

a _soll ＝median([a _sollpre +2*Stime,a ₀ ,a _sollpre -5*STime]) (7)

In the embodiment of the present disclosure, the STime is a time interval between two frames, and may generally take 0.1 seconds; a, a _sollpre The acceleration measured for one frame of the vehicle on the target vehicle can be measured by an acceleration measuring instrument mounted on the target vehicle. Calculating the input acceleration a by using the formulas (3) to (5) ₀ Then, according to the input accelerationAnd (3) determining and selecting the formula (6) or the formula (7) to calculate the value of the target acceleration.

In the embodiment of the present specification, the preset jerk limit range is an empirical range calculated according to actual measurement, and when the input acceleration value is smaller than-2 m/s according to the actual vehicle test ² When the preset jerk limit range is [ -5,2]m/s ³ The influence on the riding comfort of passengers is small; when the value of the input acceleration is not less than-2 m/s ² When the preset jerk limit range is [ -2,2]m/s ³ The influence on the riding comfort of passengers is small. Thereby being beneficial to ensuring the smoothness of the running of the vehicle and the comfort level of riding of passengers.

In this embodiment of the present disclosure, after determining the target motion pattern of the target vehicle at the target local path, the speed sequence of the target vehicle at the target local path may be calculated first according to the target motion pattern, where the calculation methods of the corresponding speed sequences are different for different target motion patterns.

Based on this, the method in fig. 1, step 108: according to the target movement mode, determining a vehicle track planning result of the target vehicle at the target local path specifically may include:

if the target movement mode is a uniform jerk movement mode, calculating a speed sequence of the target vehicle at the target local path based on the jerk, the parking time, the target acceleration of the target vehicle at the current moment and the speed of the target vehicle at the current moment; the calculation formula of the speed sequence of the target vehicle at the target local path is as follows:

V _c ＝v ₀ +a _soll *t _c +0.5*jerk*t _c ² (t _c <t _end time) (8)

V _c ＝0(t _c ≥t _end Time) (9)

Wherein V is _c For a speed sequence of the target vehicle at the target local path, the unit is m/s; t is t _end The unit is s for parking time; t is t _c For the target vehicleTime series at the target local path, in s, t _c The sequence interval in (a) is the time interval between each frame; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the jerk is jerk in m/s ³ 。

If the target motion mode is a uniform acceleration motion mode, a calculation formula of a speed sequence of the target vehicle at the target local path is as follows:

V _end ＝0(a _soll < 0) (10)

V _end ＝v ₀ (a _soll When=0) (11)

V _end ＝V _max (a _soll At > 0) (12)

V _c ＝v ₀ +a _soll *t _c (t _c <t _e Time) (14)

V _c ＝V _end (t _c ≥t _e Time) (15)

Wherein V is _end For a final speed of the target vehicle at the target local path in m/s; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² ；V _max The speed limit is the road speed limit, and the unit is m/s; t is t _e For the time required for the target vehicle to reach the final speed from the current speed at the target local path, in s; v (V) _c For a speed sequence of the target vehicle at the target local path, the unit is m/s; t is t _c For the time sequence of the target vehicle at the target local path, the unit is s, t _c The sequence interval in (a) is the time interval between each frame.

And determining a position sequence and a course angle sequence of the target vehicle at the target local path according to the speed sequence of the target vehicle at the target local path to obtain a vehicle track planning result of the target vehicle at the target local path.

In the embodiment of the present disclosure, if the target motion mode is a jerk motion mode, the speed sequence of the target vehicle at the target local path may be calculated based on the formula (8) and the formula (9); if the target motion pattern is a uniform acceleration motion pattern, a speed sequence of the target vehicle at the target local path can be calculated based on the formulas (10) to (15).

In the embodiment of the present disclosure, after determining the speed sequence of the target vehicle on the target local path, the sequence of the journey corresponding to each time sequence point may be determined by integrating, so that the position corresponding to each time sequence point may be determined on the target local path according to the sequence of journey, and the position sequence of the target vehicle on the target local path may be obtained.

In the embodiment of the specification, after the position sequence of the target vehicle at the target local path is determined, the tangent line of the path trend at each position can be made according to the path trend of the target local path, and the included angle between the tangent line and the north direction is the course angle, so that the course angle sequence of the target vehicle at the target local path can be determined.

In the present embodiment, when calculating the speed sequence of the target vehicle at the target local path using the equation (8) and the equation (9), it is necessary to determine the parking time t in advance _end Jerk.

Based on this, before calculating the speed sequence of the target vehicle at the target local path based on the jerk, the parking time, the target acceleration at the target vehicle current time, and the speed at the target vehicle current time, the method may further include:

if the target acceleration of the target vehicle at the current moment is greater than zero, the calculation formulas of the parking time and the jerk are as follows:

If the target acceleration of the target vehicle at the current moment is equal to zero, the calculation formulas of the parking time and the jerk are as follows:

wherein t is _end The unit is s for parking time; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; s is a target parking distance, and the unit is m; jerk is jerk in m/s ³ 。

If the target acceleration of the target vehicle at the current moment is smaller than zero, the calculation formulas of the parking time and the jerk are as follows:

wherein t is _end For stopping time, singlyThe bit is s; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the s is a target parking distance, and the unit is m; jerk is jerk in m/s ³ 。

In the embodiment of the present specification, if the calculated target acceleration of the target vehicle at the current time is greater than zero, the parking time t may be calculated using the formulas (16) and (17) _end Jerk; if the calculated target acceleration of the target vehicle at the current time is equal to zero, the parking time t can be calculated by using the formula (18) and the formula (19) _end Jerk; if the calculated target acceleration of the target vehicle at the current time is less than zero, the parking time t can be calculated by using the formula (20) and the formula (21) _end Jerk.

Based on the same thought, the embodiment of the specification also provides a device corresponding to the method. Fig. 2 is a schematic structural diagram of a vehicle track planning apparatus corresponding to fig. 1 according to an embodiment of the present disclosure. As shown in fig. 2, the apparatus may include:

a sensing data acquisition module 202 for acquiring vehicle operation sensing data for a target vehicle; the vehicle operation sensing data is used for determining the vehicle position of the target vehicle and the vehicle motion state of the target vehicle;

the local path determining module 204 is configured to determine a path to be driven by the vehicle within a preset range in front of the vehicle position based on the vehicle operation sensing data and preset navigation path information of the target vehicle, so as to obtain a target local path of the target vehicle;

a movement pattern determining module 206, configured to determine a target movement pattern of the target vehicle at the target local path according to the vehicle operation sensing data; the target motion mode is any one of a jerk motion mode and a jerk motion mode;

The track result determining module 208 is configured to determine a vehicle track planning result of the target vehicle at the target local path according to the target motion mode.

The present description example also provides some specific embodiments of the device based on the device of fig. 2, which is described below.

Optionally, the apparatus may further include:

the preset navigation path information acquisition module is used for acquiring preset navigation path information of the target vehicle; the preset navigation path information is a preset navigation path obtained by performing global path planning based on the starting position, the destination position and the high-precision map data of the target vehicle.

Correspondingly, the local path determining module 204 may specifically include:

the drivable lane determining submodule is used for determining a lane which does not have an obstacle in the preset distance in front of the vehicle position on the preset navigation path based on the vehicle operation sensing data and the preset navigation path information of the target vehicle to obtain a drivable lane of the target vehicle; the preset distance is a maximum distance that the target vehicle can travel on the preset navigation path within a preset time period in the future.

And the target local path determining sub-module is used for determining a vehicle to-be-driven path of the preset distance in front of the vehicle position from the drivable lane of the target vehicle to obtain the target local path of the target vehicle.

Optionally, the motion mode determining module 206 may specifically include:

and the first judging sub-module is used for judging whether the target vehicle needs to be parked at the current moment according to the vehicle operation sensing data to obtain a first judging result.

And the target movement mode determining sub-module is used for determining the target movement mode of the target vehicle at the target local path as a uniform acceleration movement mode if the first judging result indicates that the target vehicle does not need to stop at the current moment.

The second judging sub-module is used for judging whether a preset equation is solved or not based on the target acceleration of the target vehicle at the current moment, the speed of the target vehicle at the current moment and the target parking distance if the first judging result indicates that the target vehicle needs to park at the current moment, so as to obtain a second judging result; the target acceleration is an acceleration which is obtained by taking the acceleration which the target vehicle should execute at the current moment and the jerk limit into consideration and can enable the target vehicle to realize stable acceleration transition.

The preset equation is:

And the target motion mode determining sub-module is further used for determining the target motion mode of the target vehicle at the target local path as a uniform acceleration motion mode if the second judging result shows that the solution is not available.

And the target motion mode determining sub-module is further used for determining the target motion mode of the target vehicle at the target local path as a jerky motion mode if the second judging result shows that the solution exists.

Optionally, the apparatus may further include:

the input acceleration determining module is used for determining input acceleration according to the vehicle operation sensing data; the input acceleration is the calculated acceleration that should be performed by the target vehicle at the present time.

And the jerk limit range determining module is used for determining a preset jerk limit range according to the value of the input acceleration.

And the target acceleration determining module is used for determining the target acceleration of the target vehicle at the current moment based on the input acceleration, the jerk limit range and the vehicle measured acceleration of a frame on the target vehicle.

The input acceleration determining module may specifically include:

the target task determining submodule is used for determining target tasks which the target vehicle needs to execute according to the vehicle operation sensing data; the target task is any one of a deceleration task, a following task and an acceleration task.

And the input acceleration determining submodule is used for calculating the input acceleration according to the target task.

The jerk limitation range determining module may specifically include:

a judging sub-module for judging whether the value of the input acceleration is smaller than-2 m/s ² And obtaining a third judgment result.

A jerk limit determination submodule for determining that if the third determination result indicates that the value of the input acceleration is not less than-2 m/s ² Determining a preset jerk limit of [ -2,2]m/s ³ 。

The jerk limit determination submodule is further used for determining that if the third judgment result shows that the value of the input acceleration is smaller than-2 m/s ² Determining a preset jerk limit of [ -5,2]m/s ³ 。

Correspondingly, the target acceleration determining module may specifically include:

a _soll ＝median([a _sollpre +2*STime,a ₀ ,a _sollpre -2*STime])

a _soll ＝median([a _sollpre +2*STime,a ₀ ,a _sollpre -5*STime])

Optionally, the track result determining module 208 may specifically include:

the speed sequence determining submodule is used for calculating the speed sequence of the target vehicle at the target local path based on the jerk, the parking time, the target acceleration of the target vehicle at the current moment and the speed of the target vehicle at the current moment if the target motion mode is a uniform jerk motion mode; the calculation formula of the speed sequence of the target vehicle at the target local path is as follows:

V _c ＝v ₀ +a _soll *t _c +0.5*jerk*t _c ² (t _c <t _end Time of day)

V _c ＝0(t _c ≥t _end Time of day)

Wherein V is _c For a speed sequence of the target vehicle at the target local path, the unit is m/s; t is t _end The unit is s for parking time; t is t _c For the time sequence of the target vehicle at the target local path, the unit is s, t _c The sequence interval in (a) is the time interval between each frame; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the jerk is jerk in m/s ³ 。

The speed sequence determining submodule is used for determining a calculation formula of the speed sequence of the target vehicle at the target local path if the target motion mode is a uniform acceleration motion mode, wherein the calculation formula is as follows:

V _end ＝0(a _soll when < 0)

V _end ＝v ₀ (a _soll When=0)

V _end ＝V _max (a _soll When > 0)

V _c ＝v ₀ +a _soll *t _c (t _c <t _e Time of day)

V _c ＝V _end (t _c ≥t _e Time of day)

And the track planning result determining submodule is used for determining a position sequence and a course angle sequence of the target vehicle at the target local path according to the speed sequence of the target vehicle at the target local path to obtain a vehicle track planning result of the target vehicle at the target local path.

Optionally, the apparatus may further include:

the jerk determining module is configured to, if the target acceleration of the target vehicle at the current moment is greater than zero, calculate the parking time and the jerk according to the following formula:

The jerk determining module is configured to, if the target acceleration of the target vehicle at the current moment is equal to zero, calculate the parking time and the jerk according to the following formula:

The jerk determining module is configured to, if the target acceleration of the target vehicle at the current moment is less than zero, calculate the parking time and the jerk according to the following formula:

Fig. 3 is a schematic structural diagram of a vehicle track planning apparatus corresponding to fig. 1 according to an embodiment of the present disclosure. As shown in fig. 3, the apparatus 300 may include:

at least one processor 310; the method comprises the steps of,

a memory 330 communicatively coupled to the at least one processor; wherein,

the memory 330 stores instructions 320 executable by the at least one processor 310, the instructions being executable by the at least one processor 310 to enable the at least one processor 310 to:

acquiring vehicle operation sensing data for a target vehicle; the vehicle operation sensing data is used for determining a vehicle position of the target vehicle and a vehicle motion state of the target vehicle.

And determining a vehicle to-be-driven path in a preset range in front of the vehicle position based on the vehicle operation sensing data and the preset navigation path information of the target vehicle to obtain a target local path of the target vehicle.

Determining a target motion mode of the target vehicle at the target local path according to the vehicle operation sensing data; the target motion mode is any one of a jerk motion mode and a jerk motion mode.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the apparatus shown in fig. 3, the description is relatively simple, as it is substantially similar to the method embodiment, with reference to the partial description of the method embodiment.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., a field programmable gate array (Field Programmable gate array, FPGA)) is an integrated circuit whose logic function is determined by the user programming the device. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmelAT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The foregoing is merely exemplary of the present disclosure and is not intended to limit the disclosure. Various modifications and alterations to this specification will become apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of the present description, are intended to be included within the scope of the claims of the present description.

Claims

1. A vehicle trajectory planning method, the method comprising:

2. The method according to claim 1, wherein determining a vehicle to-be-driven path within a preset range in front of the vehicle position based on the vehicle operation sensing data and preset navigation path information of the target vehicle, before obtaining a target local path of the target vehicle, further comprises:

acquiring preset navigation path information of the target vehicle; the preset navigation path information is a preset navigation path obtained by performing global path planning based on the starting position, the destination position and the high-precision map data of the target vehicle;

the determining a vehicle to-be-driven path within a preset range in front of the vehicle position based on the vehicle operation sensing data and the preset navigation path information of the target vehicle to obtain a target local path of the target vehicle specifically includes:

determining a lane which does not have an obstacle in the preset distance in front of the vehicle position on the preset navigation path based on the vehicle operation sensing data and the preset navigation path information of the target vehicle, so as to obtain a drivable lane of the target vehicle; the preset distance is the maximum distance that the target vehicle can travel on the preset navigation path in a preset time period in the future;

3. The method according to claim 1, wherein said determining a target movement pattern of said target vehicle at said target local path based on said vehicle operation awareness data, in particular comprises:

judging whether the target vehicle needs to be parked at the current moment according to the vehicle operation sensing data to obtain a first judgment result;

if the first judgment result indicates that the target vehicle does not need to stop at the current moment, determining a target motion mode of the target vehicle at the target local path as a uniform acceleration motion mode;

if the first judgment result indicates that the target vehicle needs to be parked at the current moment, judging whether a preset equation is solved or not based on the target acceleration of the target vehicle at the current moment, the speed of the target vehicle at the current moment and the target parking distance, and obtaining a second judgment result; the target acceleration is obtained by considering the acceleration which the target vehicle should execute at the current moment and the jerk limit, and can enable the target vehicle to realize stable acceleration transition;

The preset equation is:

wherein t is _end The unit is s for parking time; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the s is a target parking distance, and the unit is m; ierk is jerk in m/s ³ ；

If the second judging result shows that the solution is not available, determining a target motion mode of the target vehicle at the target local path as a uniform acceleration motion mode;

4. The method of claim 3, wherein the determining the target vehicle's target movement pattern at the target local path based on the vehicle operation awareness data further comprises:

determining an input acceleration according to the vehicle operation sensing data; the input acceleration is the calculated acceleration which should be executed by the target vehicle at the current moment;

determining a preset jerk limit range according to the value of the input acceleration;

5. The method according to claim 4, wherein said determining an input acceleration from said vehicle operation awareness data, in particular comprises:

determining a target task to be executed by the target vehicle according to the vehicle operation sensing data; the target task is any one of a deceleration task, a following task and an acceleration task;

according to the target task, calculating to obtain the input acceleration;

wherein v is ₁ The unit is m/s for the target vehicle speed after the target vehicle is decelerated; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; s is the target deceleration distance, and the unit is m; a, a ₀ For input acceleration, the unit is m/s ² ；

wherein v is _rel The unit is m/s for the difference between the front vehicle speed of the target vehicle at the current moment and the target vehicle speed; d is the distance between the front vehicle of the target vehicle at the current moment and the target vehicle, and the unit is m; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; t is t _re For the driver reaction time constant, 2 seconds may be set; τ _v Calculating a constant for the first following acceleration, which may be set to 2 seconds; τ _d Calculating a constant for the second following acceleration, which may be set to 5 seconds; a, a ₀ For input acceleration, the unit is m/s ² ；

6. The method according to claim 4, wherein determining a preset jerk limit according to the value of the input acceleration comprises:

judging whether the value of the input acceleration is smaller than-2 m/s ² Obtaining a third judgment result;

if the third judgment result indicates that the value of the input acceleration is not less than-2 m/s ² Determining a preset jerk limit of [ -2,2]m/s ³ ；

If the third judgment result shows that the value of the input acceleration is smaller than-2 m/s ² Determining a preset jerk limit of [ -5,2]m/s ³ ；

The determining the target acceleration of the target vehicle at the current moment based on the input acceleration, the jerk limit range and the measured acceleration of the target vehicle at one frame of the target vehicle specifically includes:

a _soll ＝median([a _sollpre +2*STime，a ₀ ，a _sollpre -2*STime])

wherein a is _sollpre Measured acceleration of the vehicle for one frame on the target vehicle in m/s ² ；a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the STime is the time interval between two frames, in s; median is a median function; a, a ₀ For input acceleration, the unit is m/s ² ；

a _soll ＝median([a _sollpre +2*STime，a ₀ ，a _sollpre -5*STime])

7. A method according to claim 3, wherein said determining a vehicle trajectory planning result of said target vehicle at said target local path according to said target movement pattern, in particular comprises:

V _c ＝v ₀ +a _soll *t _c +0.5*jerk*t _c ² (t _c ＜t _end Time of day)

V _c ＝0(t _c ≥t _end Time of day)

Wherein V is _c For a speed sequence of the target vehicle at the target local path, the unit is m/s; t is t _end The unit is s for parking time; t is t _c For the time sequence of the target vehicle at the target local path, the unit is s, t _c The sequence interval in (a) is the time interval between each frame; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the jerk is jerk in m/s ³ ；

V _end ＝0(a _soll when < 0)

V _end ＝v ₀ (a _soll When=0)

V _end ＝V _max (a _soll >0 time)

V _c ＝v ₀ +a _soll *t _c (t _c ＜t _e Time of day)

V _c ＝V _end (t _c ≥t _e Time of day)

Wherein V is _end For a final speed of the target vehicle at the target local path in m/s; v ₀ For the current moment of the target vehicleSpeed in m/s; a, a _soll The unit is n/s for the target acceleration of the target vehicle at the current moment ² ；V _max The speed limit is the road speed limit, and the unit is m/s; t is t _e For the time required for the target vehicle to reach the final speed from the current speed at the target local path, in s; v (V) _c For a speed sequence of the target vehicle at the target local path, the unit is m/s; t is t _c For the time sequence of the target vehicle at the target local path, the unit is s, t _c The sequence interval in (a) is the time interval between each frame;

8. The method of claim 7, wherein the calculating a sequence of speeds of the target vehicle at the target local path based on the jerk, the parking time, a target acceleration of the target vehicle at a current time, and a speed of the target vehicle at the current time, further comprises:

wherein t is _end The unit is s for parking time; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; a, a _soll The unit is m/s for the target acceleration of the target vehicle at the current moment ² The method comprises the steps of carrying out a first treatment on the surface of the s is the target stopVehicle distance, the unit is m; jerk is jerk in m/s ³ ；

wherein t is _end The unit is s for parking time; v ₀ The unit is m/s for the speed of the target vehicle at the current moment; s is a target parking distance, and the unit is m; jerk is jerk in m/s ³ ；

9. A vehicle trajectory planning device, the device comprising:

10. A vehicle trajectory planning device, the device comprising:

at least one processor; the method comprises the steps of,

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