CN112622924A

CN112622924A - Driving planning method and device and vehicle

Info

Publication number: CN112622924A
Application number: CN201910907005.5A
Authority: CN
Inventors: 于宁
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2019-09-24
Filing date: 2019-09-24
Publication date: 2021-04-09
Anticipated expiration: 2039-09-24
Also published as: CN112622924B

Abstract

The embodiment of the application discloses a driving planning method and device, a vehicle and a non-transitory computer readable storage medium storing computer instructions, and belongs to the field of automatic driving. The driving planning method comprises the following steps: determining a global path of the vehicle on the journey based on parameters of the journey and vehicle parameters; and adjusting the real-time speed of the vehicle and the planned track of the vehicle on the global path in a second time based on the global path and the feedback information of the motion control state of the vehicle in the first time. Thereby making the speed and trajectory planning more consistent with the capabilities of the vehicle and able to accommodate more and more complex scenarios.

Description

Driving planning method and device and vehicle

Technical Field

Embodiments of the present application relate to the field of automatic driving, and in particular, to a driving planning method and apparatus, a vehicle, and a non-transitory computer-readable storage medium storing computer instructions.

Background

The automatic driving vehicle is used as a complex software and hardware combined system, and the safe and reliable operation of the automatic driving vehicle needs the cooperative work of a plurality of modules such as vehicle-mounted hardware, sensor integration, perception prediction, control planning and the like. The automatic driving vehicle core software module comprises the following parts: perception (Perception), Prediction (Prediction), Routing (Routing), Decision Planning (Decision & Planning), Control (Control), and other software modules, wherein the Routing is used for global path Planning, the Decision Planning is used for Planning real-time driving, and data flow between the modules is generally unidirectional. However, in the related art, the problem that the result of the planning does not conform to the capability of the vehicle and the problem that the vehicle cannot adapt to more scenes cannot be avoided in the planning process of the global path and the real-time driving.

Disclosure of Invention

The application provides a driving planning method and device, a vehicle and a non-transitory computer readable storage medium storing computer instructions.

The embodiment of the application provides a driving planning method, which comprises the following steps:

determining a global path of the vehicle on the journey based on parameters of the journey and vehicle parameters;

and adjusting the real-time speed of the vehicle and the planned track of the vehicle on the global path in a second time based on the global path and the feedback information of the motion control state of the vehicle in the first time.

Optionally, the determining a global path of the vehicle on the trip based on the trip parameter and the vehicle parameter includes:

determining an initial path of the trip composed of at least one sub-path based on a start point of the trip, an end point of the trip, and map information;

determining a first sub-path from the at least one sub-path that does not comply with the relevant parameter of the vehicle;

selecting a second sub-path replacing the first sub-path based on the relevant parameters of the vehicle;

and generating the global path based on the second sub-path and other sub-paths except the first sub-path in the initial path.

Optionally, the method further includes:

determining a motion control command for a first time based on a real-time speed of the vehicle and a planned trajectory of the vehicle on the global path over the first time.

Optionally, the method further includes:

and acquiring a control error between the motion control execution state of the vehicle and the motion control command in the first time, and using the control error as feedback information of the motion control state of the vehicle in the first time.

Optionally, the relevant parameters of the vehicle include at least one of:

the vehicle profile parameter, the vehicle power parameter, the vehicle capability level parameter.

The embodiment of the application provides a driving planning device, the device includes:

the routing module is used for determining a global path of the vehicle on the journey based on the parameters of the journey and the parameters of the vehicle;

the decision planning module is used for adjusting the real-time speed of the vehicle and the planned track of the vehicle on the global path in a second time based on the global path and the feedback information of the motion control state of the vehicle in a first time; wherein the first time is earlier than the second time.

Optionally, the routing module is configured to determine an initial route of the trip, which is composed of at least one sub-route, based on the start point of the trip, the end point of the trip, and the map information, and determine a first sub-route, which does not conform to the relevant parameters of the vehicle, from the at least one sub-route; selecting a second sub-path replacing the first sub-path based on the relevant parameters of the vehicle; and generating the global path based on the second sub-path and other sub-paths except the first sub-path in the initial path.

Optionally, the apparatus further comprises:

and the motion control module is used for determining a motion control instruction at a first time based on the real-time speed of the vehicle at the first time and the planned track of the vehicle on the global path.

Optionally, the decision planning module is configured to obtain a control error between a motion control execution state of the vehicle and a motion control command at a first time, and use the control error as feedback information of the motion control state of the vehicle at the first time.

Optionally, the relevant parameters of the vehicle include at least one of:

An embodiment of the present application further provides a vehicle, including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of the preceding claims.

The present application also provides a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any of the foregoing.

One embodiment in the above application has the following advantages or benefits: and when global path planning is carried out, relevant parameters of the vehicle are increased, and the speed and track planning is carried out on the second time by considering the feedback information of the motion control state of the first time. Therefore, the generated global path can better accord with the capability of the vehicle by considering the relevant parameters of the vehicle, and the speed and track planning can better accord with the capability of the vehicle by combining the execution situation of the control command when the speed and track planning is carried out, and can adapt to more and more complex scenes.

Other effects of the above-described alternative will be described below with reference to specific embodiments.

Drawings

The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:

FIG. 1 is a first schematic diagram of a driving planning method flow of the present application;

FIG. 2 is a schematic diagram of a high-precision map and a generic electronic navigation map;

FIG. 3 is a schematic diagram of the trajectory planning of the present application;

FIG. 4 is an architectural diagram between the various functions of the present application;

FIG. 5 is a first schematic diagram of the construction of the driving planning device of the present application;

FIG. 6 is a schematic diagram of the second embodiment of the driving planning apparatus of the present application;

fig. 7 is a block diagram of a vehicle for implementing the driving planning method of the embodiment of the present application.

Detailed Description

The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

The application provides a driving planning method, as shown in fig. 1, including:

s101: determining a global path of the vehicle on the journey based on parameters of the journey and vehicle parameters;

s102: adjusting the real-time speed of the vehicle and the planned trajectory of the vehicle on the global path in a second time based on the global path and the feedback information of the motion control state of the vehicle in a first time; wherein the first time is earlier than the second time.

The method provided by the embodiment can be applied to an automatic driving vehicle. First, control of an autonomous vehicle will be described: an autonomous vehicle can also be called an unmanned vehicle, and a software and hardware combined system is arranged in the autonomous vehicle, so that the autonomous vehicle can run safely and reliably by the cooperation of a plurality of modules such as vehicle-mounted hardware, sensor integration, perception prediction, control planning and the like.

The control functions of the autonomous vehicle may include:

and a Perception (Perception) function which is responsible for detecting and calculating the objects and the attributes of the surrounding environment from the sensor data.

And a Prediction (Prediction) function which is responsible for processing the perception data and supplementing the motion trend and motion trail Prediction information of the barrier.

And the Routing function is used for searching a global traffic path on the map according to the starting point and the ending point of the vehicle, and the global traffic path is used as a global path planned by the rear-end decision planning module in real time.

And a Decision Planning (Decision & Planning) function is used for making behavior Decision on the global path by combining road boundaries, sensing obstacles and vehicle kinematics rules to obtain real-time trajectory and speed Planning.

And the Control function is responsible for converting the track and speed plan into Control quantities such as an accelerator, a brake and a steering wheel angle according to the planning result of the response planning module, and transmitting the Control quantities to the vehicle through the CANBus so as to drive the vehicle to run according to the expected track and speed.

The routing function is used for generating a global path and sending a result to a downstream decision planning module, wherein in the related technology, the generation of the global path mainly depends on a vehicle starting point, a vehicle destination point and a map, and a passable line with the shortest path is found out.

In the decision planning function, behavior decision, trajectory planning and speed planning results are generated, and the trajectory planning and the speed planning are transmitted to the motion control function at the rear end in a single direction.

The present embodiment mainly adjusts the routing and the decision planning to better adapt to the requirements of complex scenarios. In particular, the present invention relates to a method for producing,

in the processing of the routing function, relevant parameters of the vehicle are added. Wherein the vehicle-related parameter may comprise at least one of: the vehicle profile parameter, the vehicle power parameter, the vehicle capability level parameter.

The vehicle profile parameters may include the width, height, etc. of the vehicle; accordingly, roads having a width less than the width of the vehicle and a traffic height less than the height of the vehicle may be excluded based on the profile parameters of the vehicle.

The power parameter of the vehicle may include a minimum turning radius of the vehicle, etc. Some roads with a turning radius smaller than the minimum turning radius of the vehicle may be excluded based on the power parameters of the vehicle.

The capability level parameter of the vehicle may be a comprehensive index, and may include, for example, a hundred kilometers takeover time or a hundred kilometers collision takeover time of the vehicle. The times of taking over for one hundred kilometers can be understood as the times of converting the vehicle into manual control during running for one hundred kilometers; the number of times of taking over for a hundred kilometers collision can be understood as the number of times of taking over manually performed to avoid a safety collision. Or, the comprehensive indexes of the vehicle can also comprise hundreds of kilometers of times of emergency braking, hundreds of kilometers of times of accident braking, hundreds of kilometers of times of abnormal positioning, processing time delay of an automatic driving system and the like. In this embodiment, the number of times of taking over for a hundred kilometers is mainly concerned, and generally, the higher the capability level of the vehicle is, the higher the number of times of taking over for a hundred kilometers is, and accordingly, the more complex scenes, such as areas with more people flows, can be adapted to. The capability level parameter of the vehicle can be determined according to obstacle sensing technologies such as camera shooting, for example, if the obstacle sensing technology is poor, the corresponding capability level of the vehicle is low; in addition, when the scene type is artificially divided, the area range specified in the scene, the corresponding scene type, the lowest capacity of passing vehicles, and the like may be included in the division of the scene, and at this time, whether the area range of the corresponding scene can be passed or not may be determined according to the capacity of the vehicles.

Based on this, in the foregoing S101, the determining a global path of the vehicle on the trip based on the trip parameter and the vehicle parameter includes the following processing manners:

in a first way,

In this way, a shortest path can be planned from the map information as an initial path according to the start point and the end point set by the user.

Dividing the initial path into a plurality of sub paths; the division may be performed according to the same length, or may be performed at will, and is not limited herein.

Sequentially selecting sub-paths from the plurality of sub-paths, judging whether the width or the passing height of the selected sub-paths is larger than the width of the vehicle and/or higher than the height of the vehicle, and if not, taking the selected sub-paths as first sub-paths; it should be further understood that, at this time, it may also be determined whether the selected sub-route is taken as the first sub-route by judging whether the selected sub-route meets the capability level of the vehicle, for example, the sub-route is within the area range of the artificially divided scene, and the scene specifies the lowest capability level of the passing vehicle, and when the capability of the vehicle is equal to or lower than the lowest capability level of the passing vehicle, the route may be determined as the first sub-route;

then, the starting point and the end point of the first sub-path can be used as the starting point and the end point of the second sub-path, a path which can replace the first sub-path is selected, whether the selected path meets the requirements of the relevant parameters of the vehicle or not is judged, if yes, the path is used as the second sub-path, and the second sub-path replaces the first sub-path.

And repeating the steps until the judgment and the processing of all the sub paths of the initial path are finished, wherein the obtained path is the global path.

The second way,

Based on the relevant parameters of the vehicle, all roads which do not meet the requirements of the relevant parameters of the vehicle in the map information can be removed;

then, a global route is generated from the remaining roads included in the map information based on the start point and the end point.

Similarly, in the present embodiment, a road having a width smaller than the width of the vehicle and a road having a traffic height lower than the height of the vehicle may be deleted from the map information based on the height and/or width of the vehicle. Roads that do not meet the capability level requirements of the vehicle may also be deleted from the map information based on the capability level parameter of the vehicle. Whether the vehicles are deleted can be judged according to the lowest capacity level of the corresponding passing vehicles of certain roads. It is also possible to determine whether the road is able to meet the vehicle's dynamics, such as whether the turning radius of a curve is greater than the minimum turning radius of the vehicle, and if not, the road may be eliminated.

Through the processing, the processing aiming at the global path is completed, and the processing is different from the prior art in that the related parameters of the vehicle are considered in the planning of the global path, so that the problem that the global path planned based on the shortest path principle can not meet the indexes of the vehicle is solved.

Further, in the scheme provided in this embodiment, the method further includes:

determining a motion control instruction at a first time based on the real-time speed of the vehicle at the first time and the planned trajectory of the vehicle on the global path;

wherein the motion control instructions include at least one of: a direction control instruction, an accelerator control instruction and a brake control instruction.

In this embodiment, the first time and the second time may be understood as a control frame for generating a control command in each of the real-time path plans. That is, the generation of the motion control command may be periodic, and each period of generating the motion control command may be understood as the aforementioned one frame. The first time and the second time are two adjacent frames for generating the motion control command.

Wherein the velocity and trajectory planning may include:

determining a length range to be planned based on the global path and the current position of the vehicle in the current frame; the length range can be understood as a length range which takes the current position of the vehicle as a starting point in the global path;

the real-time speed of the vehicle in the length range and the planned trajectory of the vehicle on the global path are then determined.

The current frame may be a first time, that is, when the current frame is at the first time, the real-time speed within the length range is planned in combination with the position of the current vehicle and the global path, and the trajectory is planned.

Wherein the length range may be calculated based on the current speed of the vehicle and a preset time period. The preset duration can be determined according to the actual condition or the current speed; for example, the preset duration may be preset to be a fixed 10 s; alternatively, a plurality of preset time periods may be configured, and if the current speed is higher than the preset speed threshold, a shorter preset time period, such as 5s, may be used, and if the current speed is not higher than the preset speed threshold, a longer preset time period, such as 10s, may be used. In this way, the length of the part of the path currently to be planned can be determined.

Further, the speed of travel in the length range is determined and trajectory planning may also be performed. The method comprises the following steps of planning a track, determining whether obstacles exist in the part of the path or not by combining results of a perception function and a prediction function, wherein if the obstacles exist, the type of the obstacles is static or dynamic, and if the obstacles exist, a specific position needs to be determined; in addition, if the obstacle is a dynamic obstacle, the motion trend and the motion trail of the dynamic obstacle need to be predicted by combining a prediction function.

It should be noted here that the map information in the present embodiment may be a high-precision map, and a complex automatic driving task is completed in an automatic driving vehicle mainly by loading the high-precision map. The difference between the high-precision map and the common navigation electronic map is as follows:

from the perspective of a user, the main differences between a high-precision map and a traditional electronic map are as follows: the user of the high-precision map is an automatic driving system, and the user of the traditional electronic map is a human driver.

Referring to fig. 2, a conventional general navigation electronic map (left side in the figure) depicts roads, some of the roads distinguish lanes, and a high-precision map (right side in the figure) not only depicts roads, but also accurately depicts a plurality of lanes on a road, so as to truly reflect the actual patterns of the lanes.

The traditional electronic map cannot completely show the details of the lane shape, and the high-precision map can show the details of the lane shape in detail and accurately in order to enable an automatic driving system to better identify the traffic condition, so that a driving scheme is made in advance, and the positions of the lane shape become wide and narrow and are completely consistent with the real lane.

As shown in fig. 2, the high-precision map includes a plurality of lanes, for example, lanes (Lane) 1-10. At least one Lane may form a road, for example, lanes (Lane)1, 2, and 3 may form a road, lanes (Lane)4, 5, 6, and 7 may form another road, and other forming manners are similar and will not be described again. It should be understood that fig. 2 is only an example, and more expression elements, such as road shoulders, traffic lights, and the like, may exist in an actual high-precision map, but this embodiment is not exhaustive.

The high-precision map can contain driving reference lines of all lanes; correspondingly, in this embodiment, when generating the trajectory plan, the driving reference line corresponding to the lane capable of avoiding the static obstacle and the dynamic obstacle within the length range may be selected, and the result of the trajectory plan is finally formed.

When performing trajectory planning, one example may be: and constructing a driving reference line based on discrete points of a lane central line in a high-precision map loaded in the automatic driving vehicle, and then carrying out trajectory planning and speed planning based on the driving reference line. Wherein, the result of the trajectory planning may be a trajectory curve. The track curve is composed of a series of track points, wherein information corresponding to each track point can include position coordinates formed by x, y and z, coordinates represented by s and l under a Frenet coordinate system after the position coordinates are converted, and related information such as speed, acceleration, curvature, navigation angle, relative time and the like, and the information is not exhaustive.

For example, the resulting speed plan may include the speed to be achieved at the specified location; the trajectory planning can be shown in fig. 3, which illustrates a result of trajectory planning within a certain length, and it can be seen that the trajectory is planned to pass through lane 2-lane 5-lane 8.

Determining the motion control command can be that the position of the length range needing to control the brake and the accelerator is determined according to the result of the speed plan, and the brake quantity or the accelerator quantity is determined at the corresponding position; and according to the result of the trajectory planning, determining the position of the length range where the steering wheel needs to be controlled to turn, and the steering wheel turning and the angle at the corresponding position, thus generating control instructions for the brake, the accelerator and the steering wheel.

Furthermore, in this embodiment S102, the feedback information of the motion control state of the vehicle may be obtained by: acquiring a control error between a motion control state of the vehicle and a motion control command in a first time, and using the control error as feedback information of the motion control state of the vehicle in the first time;

wherein the feedback information of the motion control state comprises at least one of:

direction control error, throttle control error, and brake control error.

Further, when the vehicle is controlled, whether a PID or MPC algorithm is adopted, there may be more or less control errors, which may cause the vehicle to enter an unexpected position or vehicle state, and further cause failure of subsequent planning; or the control function cannot be normally executed according to the planning result given by the decision-making plan, or even if the control function transmits the planning solution to the vehicle controller, the vehicle cannot be completely executed according to the planning result due to the vehicle dynamics limitation. The scheme needs to be adjusted correspondingly based on the control error.

Specifically, when the vehicle executes the control command at the first time, the downstream control function determines that the corresponding control cannot be performed or the corresponding planning result cannot be performed, for example, at a certain speed, the steering and the angle of the steering wheel cannot be matched or only the steering with a smaller angle can be performed, so that the control error of the direction between the motion control execution state and the control command at the first time can be obtained. Accordingly, feedback information for the motion control state is determined from the control error at the first time, then the speed and trajectory plan for the corresponding length range at the second time is adjusted based on the control error in the direction of the first time, at which point the start of the length range may be advanced to the current position of the vehicle at the second time, then the corresponding trajectory plan at the second time may be determined based on the control error in the direction of the first time, and the speed at a different position may be determined based on the re-determined trajectory plan at the second time to re-determine the speed plan at the second time. The manner of re-determining the trajectory plan and the speed plan is the same as the above, and is not repeated here.

For example, at a certain steering angle, the accelerator cannot execute a corresponding control command, but only can steer at a small accelerator amount, and at this time, a control error of the accelerator between the motion control execution state and the control command in the first time can be obtained. Correspondingly, after the control error is obtained, the speed and trajectory plan of the length range are adjusted again in the second time based on the control error of the accelerator, at this time, the starting point of the length range can be advanced to the current position of the vehicle in the second time, and then the speed plan can be adjusted again based on the control error of the accelerator, for example, the corresponding speeds at different positions can be reduced, so that the adjusted speed can meet the control requirement of the accelerator in the second time; when the trajectory plan at the second time is determined, the new trajectory can be determined to be reselected by combining the control error of the throttle, so that the result of the new trajectory plan at the second time can meet the capacity of the throttle. The control error of braking and the corresponding adjustment mode in the second time can also be processed in the same way, and the braking amount corresponding to the reduced speed can be adjusted by combining the control error of braking only when the position needing to reduce the speed is determined.

It should also be understood that, the following adjustment modes for the three control errors are described above, and in practical applications, the three control errors can be used in combination to make adjustments for speed and path planning.

In another case, after the control instruction is issued in the first time, because the vehicle cannot execute according to the control instruction, the vehicle cannot execute some plans at a predetermined time, for example, the speed cannot reach a preset speed plan, or the position has an error from a preset position, at this time, it can be further determined that the vehicle enters an unexpected position or a vehicle state due to at least one of a control error of a direction, a control error of an accelerator, and a control error of a brake when the vehicle is actually executed; and then the speed and the track planning adjustment at the second time are carried out by combining the adjustment mode.

It should be noted that the adjustment process of the speed and trajectory planning may be performed in real time, or may be performed periodically, for example, once every 1 s; that is, the first time may be the 1 st time, and the second time may be the 2 nd time.

In an example, the system framework of fig. 4 is illustrated, and the positioning, mapping, sensing, and predicting functions in fig. 4 are the same as those described above and are not repeated herein; the routing and decision planning in fig. 4 is explained in detail as follows: when the routing function generates a global path, relevant parameters of the vehicle are added; and when the decision planning is carried out on the current frame, the feedback information (namely the control error) of the motion control state of the previous frame is added, then the speed and the trajectory planning of the current frame are adjusted based on the feedback information of the previous frame, and the adjusted speed and the adjusted trajectory planning result of the current frame are sent to the motion control function.

Therefore, the scheme provided by the application can increase relevant parameters of the vehicle when global path planning is carried out, and the feedback information of the motion control state at the first time is considered to carry out speed and track planning adjustment at the second time. Therefore, the generated global path can better accord with the capability of the vehicle by considering the relevant parameters of the vehicle, and the speed and track planning can better accord with the capability of the vehicle by combining the execution situation of the control command when the speed and track planning is carried out, and can adapt to more and more complex scenes.

As shown in fig. 5, the present application provides a driving planning apparatus comprising:

a routing module 301, configured to determine a global path of the vehicle on a trip based on parameters of the trip and vehicle parameters;

a decision planning module 302, configured to adjust a real-time speed of the vehicle and a planned trajectory of the vehicle on the global path at a second time based on the global path and feedback information of a motion control state of the vehicle at a first time; wherein the first time is earlier than the second time.

The device provided by the embodiment can be arranged in an automatic driving vehicle. First, control of an autonomous vehicle will be described: an autonomous vehicle can also be called an unmanned vehicle, and a software and hardware combined system is arranged in the autonomous vehicle, so that the autonomous vehicle can run safely and reliably by the cooperation of a plurality of modules such as vehicle-mounted hardware, sensor integration, perception prediction, control planning and the like.

As shown in fig. 6, the driving planning apparatus of the autonomous vehicle may specifically include:

and the Perception (Perception) module is responsible for detecting and calculating the objects and the attributes of the surrounding environment from the sensor data.

And the Prediction (Prediction) module is responsible for processing the perception data and supplementing the motion trend and motion trail Prediction information of the barrier.

The Routing module 301 is configured to search a global traffic path on a map according to a start point and an end point of a vehicle, and use the global traffic path as a global path planned in real time by the back-end decision planning module.

A Decision Planning (Decision & Planning) module 302 is used for making behavior decisions on the global path by combining road boundaries, sensing obstacles and vehicle kinematics rules to obtain real-time trajectory and speed Planning.

And the Control module 303 is responsible for converting the trajectory and speed plan into Control quantities such as an accelerator, a brake and a steering wheel angle according to the planning result of the response planning module, and transmitting the Control quantities to the vehicle through the CANBus to drive the vehicle to run according to the expected trajectory and speed.

The present embodiment mainly processes the routing module 301 and the decision planning module 302 to adapt to the requirements of complex scenarios. In particular, the present invention relates to a method for producing,

the relevant parameters of the vehicle are added in the processing of the routing module 301. Wherein the vehicle-related parameter may comprise at least one of: the vehicle profile parameter, the vehicle power parameter, the vehicle capability level parameter. Relevant parameters of the vehicle may be preset in the routing module.

The capability level parameter of the vehicle may be a comprehensive index, for example, the capability level parameter may include the number of times of taking over the vehicle for one hundred kilometers, that is, the number of times of the vehicle being converted into manual control during one hundred kilometers of driving. Generally, the higher the capability grade of the vehicle is, the higher the number of times of taking over for one hundred kilometers is, and accordingly, the more complex scenes, such as regions with more people flows, and the like, can be adapted. The capability level parameter of the vehicle can be determined according to obstacle sensing technologies such as camera shooting, for example, if the obstacle sensing technology is poor, the corresponding capability level of the vehicle is low; in addition, when the scene type is artificially divided, the area range specified in the scene, the corresponding scene type, the lowest capacity of passing vehicles, and the like may be included in the division of the scene, and at this time, whether the area range of the corresponding scene can be passed or not may be determined according to the capacity of the vehicles.

Based on this, the routing module 301 may include various processes:

in a first way,

The map information processing device is used for determining an initial path of the journey composed of at least one sub-path based on the starting point of the journey, the end point of the journey and the map information, and determining a first sub-path which does not accord with relevant parameters of the vehicle from the at least one sub-path; selecting a second sub-path replacing the first sub-path based on the relevant parameters of the vehicle; and generating the global path based on the second sub-path and other sub-paths except the first sub-path in the initial path.

The second way,

and the motion control module 303 is configured to determine a motion control command at a first time based on the real-time speed of the vehicle at the first time and the planned trajectory of the vehicle on the global path.

The speed and trajectory planning with respect to the decision planning module 302 may include:

determining a length range to be planned based on the global path and the current position of the vehicle; wherein the length range can be understood as a length range in the global path starting from the current position of the vehicle; the speed of the vehicle travelling in real time in the partial path and the trajectory plan are then determined.

Furthermore, the decision planning module 302 obtains a control error between the motion control execution state of the vehicle and the motion control instruction at a first time, and uses the control error as feedback information of the motion control state of the vehicle at the first time;

direction control error, throttle control error, and brake control error.

Specifically, when the control command of the first time is executed in the first time, the downstream control function determines that the corresponding control cannot be performed or the corresponding planning result cannot be performed, for example, at a certain speed, the steering and the angle of the steering wheel cannot be matched or only the steering of a smaller angle can be performed, so that the control error of the motion control execution state and the direction between the control commands can be obtained at this time. Accordingly, the decision plan module 302, after acquiring the control error, readjusts the speed and trajectory plan of the length range corresponding to the second time based on the control error in the direction, at which point the starting point of the length range may be advanced to the current position of the vehicle, then determines the trajectory plan corresponding to the second time based on the control error in the direction, and determines the speed at a different position based on the determined trajectory plan to determine the speed plan again. The manner of re-determining the trajectory plan and the speed plan is the same as the above, and is not repeated here.

For example, at a certain steering angle, the accelerator cannot execute a corresponding control command, but only can steer at a small accelerator amount, and at this time, a control error of the accelerator between the motion control execution state and the control command can be obtained. Correspondingly, after the control error of the first time is obtained, the decision planning module 302 readjusts the speed and trajectory plan of the length range in the second time based on the control error of the accelerator, at this time, the starting point of the length range may be advanced to the position corresponding to the vehicle in the second time, and then readjusts the speed plan of the second time based on the control error of the accelerator, for example, the speeds corresponding to different positions may be reduced, so that the adjusted speed can meet the control requirement of the accelerator; when the trajectory plan is determined, the new trajectory at the second time can be determined to be reselected by combining the control error of the accelerator, so that the result of the new trajectory plan can meet the capability of the accelerator. The control error of the brake and the corresponding adjustment mode can be processed in the same way, and the brake amount corresponding to the reduced speed can be adjusted by combining the control error of the brake only when the position needing to reduce the speed is determined.

In another case, after the control instruction is issued at the first time, because the vehicle cannot execute according to the control instruction, the vehicle cannot execute some plans at a predetermined time, for example, the speed cannot reach a preset speed plan, or the position has an error from a preset position, at this time, it can be further determined that the vehicle enters an unexpected position or a vehicle state due to at least one of a control error of a direction, a control error of an accelerator, and a control error of a brake when the vehicle is actually executed; and then combining the adjustment mode to carry out subsequent speed and track planning adjustment on the second time.

It should be noted that the adjustment process of the speed and trajectory planning may be performed in real time, or may be performed periodically, for example, every 1 s.

Therefore, the scheme provided by the application can increase relevant parameters of the vehicle when global path planning is carried out, and the feedback information of the motion control state at the first time is considered to carry out speed and track planning adjustment at the second time. Therefore, the generated global path can better accord with the capability of the vehicle by considering the relevant parameters of the vehicle, and the speed and trajectory planning can better accord with the capability of the vehicle by combining the execution condition of the control instruction of the previous frame when the speed and trajectory planning is carried out, and can adapt to more and more complex scenes.

The present application further provides a vehicle and a readable storage medium according to embodiments of the present application.

As shown in fig. 7, is a block diagram of a vehicle according to the driving planning method of the embodiment of the present application. The vehicle is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The vehicle may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.

As shown in fig. 7, the vehicle includes: one or more processors 401, memory 402, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the vehicle, including instructions stored in or on the memory to display Graphical information of a Graphical User Interface (GUI) on an external input/output device, such as a display device coupled to the Interface. In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple vehicles may be connected, with each device providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 7, a processor 401 is taken as an example, and further, the processor in fig. 7 may be provided with various functional modules of the driving planning apparatus.

Memory 402 is a non-transitory computer readable storage medium as provided herein. Wherein the memory stores instructions executable by at least one processor to cause the at least one processor to perform the driving planning method provided herein. A non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to perform the driving planning method provided herein.

The memory 402, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the driving planning methods in the embodiments of the present application. The processor 401 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 402, that is, implements the driving planning method in the above method embodiment.

The memory 402 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from the use of the vehicle according to the driving plan, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 402 optionally includes memory located remotely from the processor 401, which may be connected to the vehicle driving the plan over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The vehicle for executing the driving planning method according to the embodiment may further include: an input device 403 and an output device 404. The processor 401, the memory 402, the input device 403 and the output device 404 may be connected by a bus or other means, and fig. 7 illustrates an example of a connection by a bus.

The input device 403 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the vehicle for driving planning, such as a touch screen, keypad, mouse, track pad, touch pad, pointer stick, one or more mouse buttons, track ball, joystick, or other input device. The output devices 404 may include a display device, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibrating motors), among others. The Display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) Display, and a plasma Display. In some implementations, the display device can be a touch screen.

Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, Integrated circuitry, Application Specific Integrated Circuits (ASICs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer 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) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can 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, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end 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 back-end, 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), and the internet.

The computer system may include clients and servers. A client and server are generally 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.

According to the technical scheme of the embodiment of the application, a part of images with larger similarity are filtered when the images are stored, so that redundant images are filtered when the images are stored, the storage and transmission pressure is reduced, and the workload of subsequent sorting is also saved.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.

The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A driving planning method, comprising:

determining a global path of the vehicle on the journey based on the acquired parameters of the journey and the parameters of the vehicle;

adjusting the real-time speed of the vehicle and the planned trajectory of the vehicle on the global path in a second time based on the global path and the feedback information of the motion control state of the vehicle in a first time; wherein the first time is earlier than the second time.

2. The method of claim 1, wherein determining the global path of the vehicle over the trip based on the parameters of the trip and related parameters of the vehicle comprises:

determining a first sub-path from the at least one sub-path that does not comply with the vehicle parameters;

selecting a second sub-path replacing the first sub-path based on the vehicle parameters;

3. The method of claim 1, further comprising:

4. The method of claim 1, further comprising:

and acquiring a control error between the motion control state of the vehicle and the motion control command in the first time, and using the control error as feedback information of the motion control state of the vehicle in the first time.

5. The method of claim 1, wherein the vehicle-related parameters include at least one of:

a profile parameter of the vehicle, a power parameter of the vehicle, or a capability rating parameter of the vehicle.

6. A driving planning apparatus, characterized in that the apparatus comprises:

the routing module is used for determining a global path of the vehicle on the journey based on the acquired parameters of the journey and the parameters of the vehicle;

the decision planning module is used for adjusting the real-time speed of the vehicle and the planned track of the vehicle on the global path in the second time based on the global path and the feedback information of the motion control state of the vehicle in the first time; wherein the first time is earlier than the second time.

7. The apparatus of claim 6, wherein the routing module is configured to determine an initial route of the trip based on a start point of the trip, an end point of the trip, and map information, the initial route being composed of at least one sub-route, a first sub-route from the at least one sub-route not meeting relevant parameters of the vehicle being determined; selecting a second sub-path replacing the first sub-path based on the relevant parameters of the vehicle; and generating the global path based on the second sub-path and other sub-paths except the first sub-path in the initial path.

8. The apparatus of claim 6, further comprising:

9. The apparatus of claim 6, wherein the decision-making module is configured to obtain a control error between the motion control execution state of the vehicle and the motion control command at a first time, and use the control error as the feedback information of the motion control state of the vehicle at the first time.

10. The apparatus of claim 6, wherein the vehicle-related parameters include at least one of:

11. A vehicle, characterized by comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.