CN115257815A

CN115257815A - Planning method and device for automatically driving automobile to turn right and terminal equipment

Info

Publication number: CN115257815A
Application number: CN202211027048.2A
Authority: CN
Inventors: 彭炳顺; 何天翼; 阙秋根
Original assignee: BDstar Intelligent and Connected Vehicle Technology Co Ltd
Current assignee: BDstar Intelligent and Connected Vehicle Technology Co Ltd
Priority date: 2022-08-25
Filing date: 2022-08-25
Publication date: 2022-11-01

Abstract

The planning method for the right turn of the automatic driving automobile comprises the steps of obtaining map information of a turning intersection, identifying the states of obstacles on each zebra crossing which need to pass when the automobile runs through the turning intersection according to a preset route, determining the position of the automobile for obtaining related information of surrounding obstacles according to the states of the obstacles, obtaining the related information and each road information at intervals of a first preset period when the automobile is located at the position, predicting the action track of the surrounding obstacles according to each road information, map information and related information, planning the right turn track of the automobile according to each road information, map information and action track, and controlling the automobile to run according to the right turn track. The safety and the stability of the automatic driving vehicle in the complex road condition driving process can be improved, the safety of the vehicle and passengers can be further guaranteed, and the comfort of the passengers is improved.

Description

Planning method and device for automatically driving automobile to turn right and terminal equipment

Technical Field

The invention relates to the field of path planning, in particular to a planning method and device for automatically driving a right turn of an automobile and terminal equipment.

Background

China is wide in territory, traffic development is unbalanced along with rapid development of traffic, the situation that no right-turn indicator lamp exists in many places, the traffic of pedestrians and non-motor vehicles is often accompanied by non-standard behaviors and even behaviors of violating traffic safety laws, and traffic safety accidents easily occur in the process of turning driving of an automatic driving vehicle under the condition of large pedestrian flow and vehicle flow, so that personnel and property loss in the vehicle can be caused.

Disclosure of Invention

The invention aims to provide a planning method, a planning device, a terminal device and a readable storage medium for automatically driving a right turn of an automobile.

In a first aspect, the present invention provides a planning method for automatically driving a right turn of an automobile, which is applied to a vehicle to be turned, and the method includes:

obtaining map information of a turning intersection, identifying the states of obstacles on each zebra crossing which the vehicle needs to pass when the vehicle runs through the turning intersection according to a preset route, and determining the position of the vehicle for obtaining the related information of the surrounding obstacles according to the states of the obstacles on each zebra crossing;

when the vehicle is located at the position, acquiring the related information and each road information every interval of a first preset period, and predicting the action track of the surrounding obstacles based on each road information, the map information and the related information;

planning a right turn track of the vehicle based on the road information, the map information and the action track, and controlling the vehicle to run according to the right turn track.

In an optional embodiment, the determining, according to the state of the obstacle on the zebra crossing, a position where the vehicle starts to acquire information about a surrounding obstacle includes:

when an obstacle exists on any one of the zebra crossings, the position which is away from the zebra crossings where the obstacle exists by a preset interval is used as the position for acquiring the related information;

and when no obstacle exists on each zebra crossing, taking the current position as the position obtained by the related information.

In an alternative embodiment, the respective road information comprises respective traffic light states of respective roads, the method further comprising:

and when an obstacle exists on any one zebra crossing, driving to the position according to the preset route, and detecting the state of the obstacle on each zebra crossing at intervals of a second preset period.

In an alternative embodiment, the respective road information includes a vehicle passing state on respective roads, the respective roads include a lateral road, the right turn trajectory includes a traveling direction of the vehicle, and the method further includes:

when the vehicle passing state of the transverse road is that vehicles pass through, and the passing direction of passing vehicles is the same as the running direction, the passing direction and the passing speed of the passing vehicles are obtained, and the passing track of the passing vehicles is predicted based on the passing direction and the passing speed;

if the passing track is overlapped with the right turning track, stopping running;

and if the passing track is not overlapped with the right turning track, driving according to the right turning track, and executing the step of acquiring the passing direction and the passing speed of the passing vehicle.

In an alternative embodiment, the predicting the action trajectory of the peripheral obstacle based on the respective road information, the map information, and the related information includes:

predicting forward information of the surrounding obstacles based on the last relevant information of the surrounding obstacles and the current relevant information;

and determining the action track of the surrounding obstacles according to the forward information, the map information and the road information.

In an optional embodiment, the planning a right turn trajectory of the vehicle by a preset method based on the respective road information, the map information, and the action trajectory includes:

drawing out a movement path of the vehicle by a dynamic planning algorithm based on the respective road information, the map information, and the movement trajectory;

and optimizing the action path through a quadratic programming algorithm to obtain a right turning track of the vehicle.

In an alternative embodiment, the method further comprises:

and when the special vehicles are identified to exist on each road, stopping running according to the right turning track until the special vehicles cannot be identified.

In a second aspect, the present invention provides a planning device for automatically driving a right turn of an automobile, which is applied to a vehicle to be turned, and the device comprises:

the sensing module is used for acquiring map information of a turning intersection, identifying the states of obstacles on each zebra crossing which the vehicle needs to pass when the vehicle runs through the turning intersection according to a preset route, and determining the position of the vehicle for acquiring the related information of the surrounding obstacles according to the states of the obstacles on each zebra crossing;

the prediction module is used for acquiring the related information and each piece of road information every first preset period when the vehicle is positioned at the position, and predicting the action track of the surrounding obstacles based on each piece of road information, the map information and the related information;

and the planning module is used for planning the right turning track of the vehicle based on the road information, the map information and the action track and controlling the vehicle to run according to the right turning track.

In a third aspect, the present invention provides a terminal device comprising a memory and a processor, the memory storing a computer program, the computer program, when executed on the processor, executing the method for planning a right turn of an autonomous vehicle.

In a fourth aspect, the present invention provides a readable storage medium storing a computer program which, when run on a processor, performs the method for planning a right turn in an autonomous vehicle.

The embodiment of the invention has the beneficial effects that:

the embodiment of the application provides a planning method for automatically turning right of an automobile, which is applied to a vehicle, and is used for identifying the states of obstacles on each zebra crossing which the vehicle needs to pass through when the vehicle runs through the turning crossing according to a preset route by obtaining map information of the turning crossing, determining the position of the vehicle for obtaining related information of surrounding obstacles according to the states of the obstacles, obtaining the related information and each road information at intervals of a first preset period when the vehicle is positioned at the position, predicting the action track of the surrounding obstacles according to each road information, the map information and the related information, planning the right turning track of the vehicle according to each road information, the map information and the action track, and controlling the vehicle to run according to the right turning track. The safety and the stability of the automatic driving vehicle in the complex road condition driving process can be improved, the safety of the vehicle and passengers can be further guaranteed, and the comfort of the passengers is improved.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solution of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention. In the various figures of the drawing, like elements are numbered similarly.

Fig. 1 is a schematic diagram illustrating each road in a planning method for automatically driving a right turn of an automobile according to an embodiment of the present application;

FIG. 2 is a schematic flow chart illustrating a method for planning a right turn of an autonomous vehicle according to an embodiment of the present disclosure;

fig. 3 is a schematic diagram illustrating each zebra crossing and obstacle in a planning method for automatically driving a right turn of an automobile according to an embodiment of the present application;

FIG. 4 is a schematic flow chart illustrating the prediction of the action trajectory in a method for planning a right turn of an autonomous vehicle according to an embodiment of the present application;

FIG. 5 is a schematic diagram illustrating a planned right turn trajectory in a planning method for a right turn of an autonomous vehicle according to an embodiment of the present application;

FIG. 6 is a schematic flow chart illustrating planning of a right turn trajectory in a method for planning a right turn of an autonomous vehicle according to an embodiment of the present application;

fig. 7 shows a schematic structural diagram of a planning apparatus for automatically driving a right turn of an automobile according to an embodiment of the present application.

Description of the main element symbols:

10-a planning device for automatically driving the right turn of the automobile; 11-a perception module; 12-a prediction module; 13-planning module.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.

The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.

Hereinafter, the terms "including", "having", and their derivatives, which may be used in various embodiments of the present invention, are only intended to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the existence of, or adding to, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.

Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another, and are not to be construed as indicating or implying relative importance.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present invention belong. The terms (such as terms defined in a commonly used dictionary) will be construed to have the same meaning as the contextual meaning in the related art and will not be construed to have an idealized or overly formal meaning unless expressly so defined in various embodiments of the present invention.

Example 1

When the traffic flow and the pedestrian flow are large, the automatic driving vehicle turns around at the complex intersection, and accidents are easy to happen. Therefore, for the automatically driven vehicle, the decision-making plan for the action path which meets the regulation, can pass smoothly and has no stagnation has important significance for ensuring the running safety of the vehicle and the comfort of passengers. The application provides a planning method for the right turn of an automatic driving automobile applied to a scene without a right turn indicator lamp by combining factors such as the existing traffic safety law, traffic lights, pedestrians and non-motor vehicles at an intersection and the like.

In the present embodiment, as shown in fig. 1, when the vehicle travels to the point a and a right turn is to be made, the transverse road and the longitudinal road in the present embodiment are as shown, that is, the traveling direction of the vehicle is the longitudinal road, and the road perpendicular to the longitudinal road is the transverse road. When the global route planning module of the vehicle carries out route planning, a preset route with a right turn is planned. When the automatic driving vehicle drives to the position near the right turn intersection according to the planned route, the automatic driving vehicle calls the traffic regulation of the right turn intersection through the Internet of things to determine whether the vehicle can turn right or not when the longitudinal road of the intersection is displayed as a red light, namely the longitudinal road is the red light; the sign and the traffic signal lamp of the right turn intersection are identified to determine whether the intersection has the right turn indicator lamp, and whether the vehicle can turn right when the longitudinal road is red is judged again; the vehicle can also call a high-definition map of the intersection to check whether the intersection has a right-turn special lane or not. When it is determined that the running vehicle is allowed to turn right when the longitudinal road of the intersection is displayed as the red light, and the right-turn intersection does not have the right-turn indicator light and does not have the right-turn dedicated lane, the planning method for automatically turning right of the automobile provided by the embodiment of the application is called.

Referring to fig. 2, an embodiment of the present application provides a method for planning a right turn of an autonomous vehicle, which is applied to a vehicle to be turned, and exemplarily includes steps S100 to S300.

Step S100: the method comprises the steps of obtaining map information of a turning intersection, identifying the states of obstacles on each zebra crossing which a vehicle needs to pass when the vehicle runs through the turning intersection according to a preset route, and determining the position of the vehicle for obtaining the related information of surrounding obstacles according to the states of the obstacles on each zebra crossing.

It can be understood that when the vehicle drives to a turning intersection, the vehicle will acquire the map information of the turning intersection, and the map information may be a high-precision map, and the map information includes the relevant information of the turning intersection. The vehicle also identifies the state of the obstacles on each passing zebra crossing when the vehicle passes through the turning intersection according to the preset route through the camera sensor on the vehicle, so that the position of the vehicle for acquiring the related information of the surrounding obstacles is determined according to the state of the obstacles on the zebra crossings.

The obstacle includes but is not limited to any one or more of a pedestrian, a non-motor vehicle, an object, an animal and a vehicle, the obstacle state on the zebra crossing includes an obstacle-free state on the zebra crossing and an obstacle state on the zebra crossing, and the obstacle state on the zebra crossing includes that the obstacle is in a moving state and the obstacle is in a static state, and the like. As shown in fig. 3, the vehicle is point a, the zebra crossings to be passed by when the vehicle drives through the turning intersection according to the preset route are the first zebra crossing a and the second zebra crossing b, and the oval shaded parts in the figure may be obstacles, i.e. pedestrians or non-motorized convergence.

In this embodiment, when it is recognized that an obstacle exists on any one of zebra crossings through which a pre-planned route of a vehicle will pass, a position at a preset interval from the zebra crossings where the obstacle exists is taken as a position where relevant information of surrounding obstacles is acquired by a laser radar. When the vehicle runs through the turning intersection according to the preset route, no obstacle exists on each zebra crossing, the current position of the vehicle is used as the position for acquiring the related information, namely the related information of the surrounding obstacles is immediately acquired when the vehicle is at the current position. Wherein the preset interval is set according to the actual condition; the relevant information includes, but is not limited to, the position and attitude of the obstacle, the relative distance of the position of the obstacle from the vehicle.

In the embodiment, the vehicle is also positioned in real time, because the vehicle is positioned at the intersection, multiple traffic lines exist, such as a zebra crossing, a solid line in front of the zebra crossing, a light strip line and the like, and if the vehicle is not positioned accurately, traffic violation is easy to occur, and even traffic safety accidents occur. At present, the satellite Positioning accuracy limit is 2.5m, but an automatic driving vehicle in an urban area is far from meeting the use requirement only by means of satellite Positioning, so that the vehicle in the embodiment can achieve Positioning at the centimeter level by adopting a Positioning technology combining satellite Positioning and Real-time kinematic (RTK), and the satellite Positioning is a Global Positioning System (GPS) or a Beidou satellite navigation System, so that the acquired position information of the vehicle meets the requirement of automatic driving vehicle Positioning. In addition, in order to make the vehicle brake in front of the zebra crossing accurately, positioning technology combining satellite positioning, RTK and camera sensors is also applied.

Step S200: when the vehicle is located at the position, the related information and the respective road information are acquired at intervals of a first preset period, and the movement track of the surrounding obstacle is predicted based on the respective road information, the map information and the related information.

It is understood that, when the vehicle immediately starts acquiring the related information at the current position, the related information of the surrounding obstacles and the respective road information will be acquired once every first preset period. And the action track of the surrounding obstacles is predicted according to the acquired road information, map information and related information.

The road information includes, but is not limited to, traffic light states of roads and states of obstacles on roads, and the traffic light states include green light states and red light states. As shown in fig. 1, the various roads include but are not limited to lateral roads and longitudinal roads, the state of the obstacles on each road includes the states that the obstacles exist on each road, the obstacles do not exist on each road, the obstacles exist on the transverse road and the longitudinal road, the obstacles exist on the longitudinal road and the obstacles do not exist on the transverse road, and the like.

In one embodiment, as shown in fig. 4, the step of predicting the action trajectory of the surrounding obstacle based on the respective road information, map information and related information includes substeps S210 to S220.

Substep S210: and predicting the advancing information of the peripheral obstacles based on the last relevant information and the current relevant information of the peripheral obstacles.

It is understood that the vehicle will acquire the relevant information of the surrounding obstacle once every first preset period, and in this embodiment, the advancement information of the surrounding obstacle will be predicted from the acquired last relevant information and present relevant information of the surrounding obstacle. Wherein the forward traveling information includes a traveling direction and a traveling speed of the surrounding obstacle. Because the environment of the intersection is complex when the automatic driving vehicle drives to the intersection, the speed of the automatic driving vehicle driving through the intersection can be controlled to be less than or equal to the preset intersection speed, and the preset intersection speed can be 30km/h.

In this embodiment, the equation is shown by

t _1 and t \u0 represents time, v _{Line of} Indicates the speed of the obstacle for which the speed prediction is performed, and t0 (x 0, y 0) indicates that the position of a certain obstacle around the time t0 is (x) ₀ ，y ₀ )，t1(x ₁ ，y ₁ ) Represents t ₁ The position of the obstacle at the time is (x) ₁ ，y ₁ ) The coordinate system can be a plane coordinate established by taking the central point of the intersection to be turned as an origin. By the above formula, the velocity of the obstacle to be predicted can be determined, t ₀ To t ₁ The advancing direction of the obstacle can be determined; the obstacle t can be obtained by the method ₁ And t ₂ Speed and direction of, obstacle t ₂ And t ₃ The traveling speed and the traveling direction of, the obstacle t ₃ And t ₄ ……。

Substep S220: and determining the action track of the surrounding obstacles according to the forward information, the map information and the road information.

After at least one set of forward information of the surrounding obstacles is determined, the action track of the surrounding obstacles is determined by combining the traffic indicator lamp state of each road in each road information acquired by the camera sensor and the map information, wherein the action track comprises the traveling intention of the obstacles such as pedestrians or vehicles, namely information such as the direction and the speed of the obstacles to act.

For example, if the obstacle is a pedestrian, the pedestrian is at t ₀ To t ₁ 、t ₁ To t ₂ … … is along the zebra crossing direction, that is, when a pedestrian travels on a transverse road, the pedestrian travels along the zebra crossing direction on the transverse road, and the travel speeds in the multiple sets of travel information obtained through the formula are all greater than the preset speed, or most of the travel speeds are greater than the preset speed, it can be determined that the pedestrian is likely to pass through the zebra crossing, and at this time, the identified traffic light information is used to predict the action track of the pedestrian, so as to avoid the obstacle from suddenly breaking into the travel path of the vehicle.

For example, the traffic light state at the zebra crossing where the pedestrian is going to pass is a green light state, so that the pedestrian can be judged to want to pass through the zebra crossing, and the pedestrian track can be predicted according to the relevant information of the zebra crossing, such as the position and width information, and the traveling direction information of the pedestrian; if the traffic light state at the zebra crossing is the red light state, the pedestrian can be judged not to cross the zebra crossing, and the preset speed can be set as the speed of the ordinary person in normal walking according to the condition.

Step S300: and planning a right turn track of the vehicle based on the road information, the map information and the action track, and controlling the vehicle to run according to the right turn track.

It can be understood that after the action path of the obstacle around the vehicle is determined, the right turn track of the vehicle is planned by a preset method according to the road information, the map information and the action track, so that the driving safety and the driving stability of the vehicle are improved.

As shown in fig. 5, the right turning trajectory includes a first turning trajectory and a second turning trajectory, where point a is a center of mass of the vehicle, point B is an intersection of the right longitudinal zebra crossing and a center line of the right lane, point C is an intersection of the right longitudinal zebra crossing and a center line of the left lane, a is a first zebra crossing, which is a lower transverse zebra crossing, and B is a second zebra crossing, which is a right longitudinal zebra crossing. A first turning track can be planned by combining the points A and C, and a second turning track can be planned by combining the points A and B.

In this embodiment, each piece of road information includes a vehicle passing state on each road, and when the vehicle passing state on the lateral road in each road is no vehicle passing, the first turning track corresponding to the vehicle is planned based on the acquired map information, each piece of road information acquired in real time and the predicted action track, that is, the large turning radius track is planned, so that the vehicle is far away from the waiting area of the right-side pedestrian and the non-motor vehicle.

In one embodiment, each of the road information includes a vehicle passing state on each of roads, each of the roads includes a lateral road and a longitudinal road, and the right turn trajectory includes a traveling direction of the vehicle. When the vehicle passing state on the transverse road in each road is that the vehicle passes through, and the passing direction of the passing vehicle is the same as the running direction of the vehicle, the planned right turning track is a second turning track, namely a small turning track, the passing direction and the passing speed of the passing vehicle are obtained, the passing track of the passing vehicle is predicted according to the passing direction and the passing speed, and when the predicted passing track is coincident with the right turning track, the vehicle gives up the passing, namely stops running; and when the passing track is not overlapped with the right turning track, the vehicle runs according to the right turning track of the vehicle, the step of acquiring the passing direction and the passing speed of the passing vehicle is executed to predict the track movement direction of the passing vehicle in real time, if the vehicle track changes and is overlapped with the right turning track of the vehicle in the passing process, the vehicle stops running and waits for the passing of the passing vehicle, and the vehicle continues to run according to the planned right turning track.

When the vehicle recognizes that special vehicles exist on each road through the camera sensor, namely, for example, when a warning light is arranged on the vehicle and the vehicle rushes a red light on a transverse road, the vehicle is determined to be the special vehicle executing the task, the vehicle stops running according to the planned right turning track until the special vehicle cannot be recognized, and then the vehicle continues running according to the right turning track. Special vehicles include ambulances, fire trucks or other special case vehicles.

In one embodiment, as shown in fig. 6, the planning of the right turn trajectory of the vehicle by a preset method based on the respective road information, map information, and action trajectory includes substeps S310 to S320.

Substep S310: and drawing out a movement path of the vehicle by a dynamic planning rule based on the respective road information, map information and movement trajectory.

In the present embodiment, it will be determined whether the vehicle is about to turn right, i.e., the traveling direction of the vehicle, by traffic decision based on the respective road information, map information, and action trajectory. After the driving direction is determined, a plurality of selectable driving paths are planned through DP (Dynamic Programming), an optimal path is selected through DP path decision, DP speed planning is carried out, multi-section speed is planned, an optimal speed curve is selected through DP speed decision, and the action path of the vehicle is determined.

Substep S320: and optimizing the action path through a quadratic programming algorithm to obtain the right turning track of the vehicle.

Since the planned movement path of the vehicle is mostly uniform points, interpolation processing is required, and dense points are required at a turn to track the path of the vehicle. Because each path point on the planned action path has a corresponding speed, the trajectory and speed of the action path are optimized through a Quadratic Programming (QP), so that the right turn trajectory of the vehicle is obtained. The dynamic planning algorithm and the quadratic planning algorithm are not the key points of the present application, and are not described herein in detail.

In one embodiment, the method further comprises step S400.

Step S400: when an obstacle exists on any zebra crossing, the vehicle runs to the position according to a preset route, and the state of the obstacle on each zebra crossing is detected at intervals of a second preset period.

It can be understood that when an obstacle exists on any one zebra crossing, namely, when an obstacle exists on the zebra crossing which the vehicle will pass through when the vehicle travels through the crossing according to a preset path, the vehicle will travel to a position away from the zebra crossing where the obstacle exists by a preset interval according to a preset route, and the state of the obstacle on each zebra crossing will be detected every second preset period, so as to determine whether the obstacle exists on each zebra crossing and determine whether the obstacle is in a stationary state or in a moving state. Wherein the preset distance and the second preset period are set according to actual conditions.

And detecting the state of the obstacles on each zebra crossing every second preset period, and when the obstacle exists on any zebra crossing and is in a static state, starting to acquire the related information of the surrounding obstacles at the position away from the zebra crossing with the obstacle by a preset interval. For example, when an obstacle does not move on a certain zebra crossing, such as a pedestrian or a non-motor vehicle waiting to cross a road, a scene standing at the head end of the zebra crossing is not moved. At this time, relevant information of the pedestrian or the non-motor vehicle is detected, so that the movement of the pedestrian or the non-motor vehicle is predicted.

When an obstacle exists on any zebra crossing and the obstacle is in a moving state, the vehicle stops running at a position away from the zebra crossing with the obstacle by a preset interval, and the state of the obstacle on each zebra crossing is detected every second preset period until no obstacle exists on each zebra crossing. For example, when the transverse road is in a green light state, the longitudinal road is in a red light state, and an obstacle exists on a certain zebra crossing and the pedestrian is in a moving state.

In one embodiment, when the vehicle travels on the longitudinal road according to the preset route, when the vehicle travels to a position away from the zebra crossing by a preset interval, if the state of the traffic light of the identified longitudinal road is a yellow light state, the vehicle stops traveling, and the step of continuously identifying the state of the obstacle on each zebra crossing through which the vehicle at the turning intersection will travel according to the preset route is continuously performed.

In this application, not only can improve security and the stability of autopilot vehicle when complicated road conditions travel, can also further ensure vehicle and passenger's safety, improve passenger's travelling comfort.

Based on the planning method for automatically driving a right turn of an automobile in the foregoing embodiment, fig. 7 shows a schematic structural diagram of a planning apparatus 10 for automatically driving a right turn of an automobile provided in the embodiment of the present application, which is applied to a vehicle to be turned, and the planning apparatus 10 for automatically driving a right turn of an automobile includes:

the sensing module 11 is configured to acquire map information of a turning intersection, identify states of obstacles on each zebra crossing that the vehicle needs to pass through when driving through the turning intersection according to a preset route, and determine a position where the vehicle acquires information related to surrounding obstacles according to the states of the obstacles on each zebra crossing.

And the predicting module 12 is configured to, when the vehicle is located at the position, obtain the relevant information and each piece of road information at intervals of a first preset period, and predict a movement track of the peripheral obstacle based on each piece of road information, the map information, and the relevant information.

And the planning module 13 is configured to plan a right turn track of the vehicle based on the road information, the map information, and the action track, and control the vehicle to travel according to the right turn track.

The planning apparatus 10 for automatically driving a right turn of a vehicle in this embodiment is used to execute the planning method for automatically driving a right turn of a vehicle in the foregoing embodiment, and the implementation and beneficial effects related to the foregoing embodiment are also applicable in this embodiment, and are not described again here.

The embodiment of the application also provides terminal equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the computer program executes the planning method for the right turn of the automatic automobile when running on the processor.

The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed on a processor, the method for planning a right turn of an autonomous vehicle is implemented.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part of the technical solution that contributes to the prior art in essence can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present invention, and shall cover the scope of the present invention.

Claims

1. A planning method for automatically driving a right turn of an automobile is characterized by being applied to a vehicle to be turned, and the method comprises the following steps:

when the vehicle is located at the position, acquiring the related information and each piece of road information at intervals of a first preset period, and predicting the action track of the surrounding obstacles based on each piece of road information, the map information and the related information;

2. The method for planning a right turn of an autonomous vehicle of claim 1, wherein the determining the position of the vehicle to start acquiring the relevant information of the surrounding obstacles according to the state of the obstacles on the zebra crossing comprises:

3. The method of claim 2, wherein the respective road information includes a respective traffic light status for the respective road, the method further comprising:

and when an obstacle exists on any one zebra crossing, driving to the position according to the preset route, and detecting the state of the obstacle on each zebra crossing every other second preset period.

4. The method of claim 1, wherein the respective road information includes a vehicle passing status on respective roads, the respective roads include lateral roads, the right turn trajectory includes a driving direction of the vehicle, the method further comprising:

when the vehicle passing state of the transverse road is that a vehicle passes through, and the passing direction of the passing vehicle is the same as the running direction, acquiring the passing direction and the passing speed of the passing vehicle, and predicting the passing track of the passing vehicle on the basis of the passing direction and the passing speed;

and if the passing track does not coincide with the right turning track, driving according to the right turning track, and executing the step of acquiring the passing direction and the passing speed of the passing vehicle.

5. The method for planning a right turn of an autonomous vehicle as claimed in claim 1, wherein the predicting of the action trajectory of the surrounding obstacle based on the respective road information, the map information and the related information comprises:

predicting the advancing information of the surrounding obstacles based on the last relevant information of the surrounding obstacles and the current relevant information;

and determining the action track of the surrounding obstacles according to the advancing information, the map information and the road information.

6. The method for planning a right turn of an autonomous vehicle according to claim 1, wherein the planning a right turn trajectory of the vehicle by a preset method based on the respective road information, the map information and the action trajectory comprises:

drawing a movement path of the vehicle by a dynamic programming rule based on the respective road information, the map information, and the movement trajectory;

7. The method for planning a right turn of an autonomous vehicle as claimed in claim 1, characterized in that the method further comprises:

8. A planning device for automatically driving a right turn of a car, applied to a car to be turned, the device comprising:

the prediction module is used for acquiring the related information and each road information every interval of a first preset period when the vehicle is positioned at the position, and predicting the action track of the surrounding obstacles based on each road information, the map information and the related information;

and the planning module is used for planning a right turning track of the vehicle based on the road information, the map information and the action track and controlling the vehicle to run according to the right turning track.

9. A terminal device, characterized in that it comprises a memory and a processor, the memory storing a computer program which, when run on the processor, executes the method for planning a right turn of an autonomous vehicle as claimed in any of claims 1 to 7.

10. A readable storage medium, characterized in that it stores a computer program which, when run on a processor, performs the method of planning a right turn of an autonomous vehicle as claimed in any of claims 1 to 7.