CN115042820A

CN115042820A - Autonomous vehicle control method, device, equipment and storage medium

Info

Publication number: CN115042820A
Application number: CN202210810679.5A
Authority: CN
Inventors: 周光学
Original assignee: Beijing Zhuxian Technology Co Ltd
Current assignee: Beijing Zhuxian Technology Co Ltd
Priority date: 2022-07-11
Filing date: 2022-07-11
Publication date: 2022-09-13

Abstract

The embodiment of the application provides a method, a device, equipment and a storage medium for controlling an automatic driving vehicle, which relate to the technical field of automatic driving, and the method comprises the following steps: firstly, acquiring positioning information and map information of a target vehicle; then, planning a path based on the positioning information and the map information to obtain navigation information and track point information; the track point information is used for reflecting the path information of a driving path which drives from the high-speed main road into the ramp; and finally, controlling the target vehicle based on the navigation information and the track point information. According to the method, the high-precision positioning information and the high-precision map information are jointly used as control factors to control the target vehicle, more stable navigation information and path information are obtained through path planning, and the success rate of the target vehicle entering the ramp from the high-speed main road can be improved when the method is applied to the scene that the vehicle enters the ramp from the high-speed main road.

Description

Autonomous vehicle control method, device, equipment and storage medium

Technical Field

The present application relates to the field of autonomous driving technologies, and in particular, to a method, an apparatus, a device, and a storage medium for controlling an autonomous vehicle.

Background

With the development of the automatic driving technology, various automobile host factories and science and technology companies are developing higher-level automatic driving functions such as L2+/L3/L4 of the Society of Automotive Engineers (SAE) at present, and a high-speed scene is a key point of high-level automatic driving research and development as an automatic driving scene which is relatively easy to land on the ground. The auxiliary driving function and the intelligent driving function of the high-speed main road are mature at present, and more commercial mass-production vehicle types exist, and the situation that the high-speed main road enters the ramp is a difficulty in technical research and development at present and an important barrier for realizing high-speed full-road-section intelligent driving.

According to the current technical scheme, when automatic driving under the scene that the high-speed main road enters the ramp is achieved, the lane line of the high-speed main road entering the ramp is identified and vehicles are controlled to change the lane to enter the ramp mainly by means of forward visual perception. However, this method has a problem that the success rate of the vehicle entering the ramp from the high-speed main road is low.

Disclosure of Invention

The application provides a control method, a device, equipment and a storage medium for an automatic driving vehicle, which are used for solving the problem of low success rate of driving the vehicle into a ramp from a high-speed main road.

According to a first aspect of the present application, there is provided an autonomous vehicle control method comprising:

acquiring positioning information and map information of a target vehicle;

performing path planning based on the positioning information and the map information to obtain navigation information and track point information; the track point information is used for reflecting the path information of a driving path which drives from the high-speed main road into the ramp;

and controlling the target vehicle based on the navigation information and the track point information.

According to the automatic driving vehicle control method, high-precision positioning information and high-precision map information are jointly used as control factors to control the target vehicle, more stable navigation information and path information are obtained through path planning, and therefore the success rate of the target vehicle entering the ramp from the high-speed main road can be improved.

In one possible implementation manner, the controlling the target vehicle based on the navigation information and the track point information includes:

determining decision information by using a preset decision algorithm according to the navigation information;

and under the condition that the decision information is in a track point tracking mode, controlling the target vehicle according to the track point information.

The embodiment of the application can accurately determine the decision information through the decision algorithm, and provides a specific vehicle control mode, namely a tracking point mode, because the tracking point information is used for reflecting the path information of the driving path of the ramp driven into the main highway from the high-speed main highway, on the basis that the path information has stability, the tracking point information also has higher stability, and further the success rate of the target vehicle driven into the ramp from the main highway through the tracking point information with high stability can be further improved.

In one possible implementation, the navigation information includes: a next navigation lane change marker and a distance of the target vehicle to a next navigation lane change point; determining decision information by using a preset decision algorithm according to the navigation information comprises the following steps:

judging whether the next navigation lane change mark is a mark for entering a ramp from a high-speed main road to the right or not by using a preset decision algorithm, and whether the distance from the target vehicle to the next navigation lane change point is smaller than or equal to a preset threshold value or not;

and determining the tracking point entering mode as decision information under the condition that the next navigation lane change mark is a mark entering a ramp from the high-speed main road to the right and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold value.

The embodiment of the application specifically describes a specific process of determining the tracking point mode as the decision information, that is, a condition for entering the tracking point mode is set for the navigation information, and the navigation information meeting the condition can reflect that the current scene is suitable for realizing accurate control on the target vehicle in the tracking point mode.

In a possible implementation manner, the controlling the target vehicle according to the track point information includes:

and outputting a corresponding control instruction based on the track point information, and controlling the target vehicle by using the control instruction.

According to the control method and the control device, the control of the target vehicle is realized through the control instruction, and the feasibility of accurately controlling the target vehicle can be increased.

In a possible implementation manner, the performing path planning based on the positioning information and the map information to obtain navigation information and track point information includes:

determining the current position of the target vehicle in the map information according to the positioning information;

determining a driving path for driving from the high-speed main road to the ramp according to the current position of the target vehicle and a preset destination position;

and determining the navigation information according to the driving path and the map information, and determining the track point information according to the driving path.

According to the method and the device, the current position of the target vehicle can be accurately identified according to the high-precision positioning information, the preset target place position can be accurately identified, a feasible and optimal driving path for driving from the high-speed main road to the ramp is generated, stable track point information and accurate navigation information are obtained, and a data basis is provided for the follow-up control of the target vehicle according to the track point information.

In one possible implementation manner, determining a driving path from a high-speed main road to an on-ramp according to the current position of the target vehicle and a preset destination position includes:

determining whether a deceleration lane exists on a ramp according to the map information;

under the condition that a deceleration lane exists on the ramp, determining a driving path entering the deceleration lane from the high-speed main road by using a path planning algorithm according to the current position of the target vehicle and a preset destination position arranged on the deceleration lane;

and under the condition that no deceleration lane exists at the high speed, determining a driving path entering the ramp from the high-speed main road by using a path planning algorithm according to the current position of the target vehicle and a preset destination position arranged on the ramp.

The method and the device can intelligently identify whether the ramp has the deceleration lane or not, set the preset destination position on the deceleration lane under the condition that the deceleration lane exists, and set the preset destination position on the ramp under the condition that the deceleration lane does not exist, so that a reasonable driving path can be planned when a path planning algorithm is adopted for path planning.

In a possible implementation manner, the determining the track point information according to the travel path includes:

selecting track points from the current position of the target vehicle by combining a preset track point interval strategy, and generating track point information; the preset track point interval strategy is to select a first preset number of track points according to a first preset interval and select a second preset number of track points according to a second preset interval.

In this application embodiment, the tracing point is the point of selecting after discretizing the route, has the interval between two adjacent tracing points, and this application embodiment can also avoid carrying out frequent control to the target vehicle when guaranteeing that control target vehicle successfully drives into the ramp from high-speed main road through the setting to interval between two adjacent tracing points.

According to a second aspect of the present application, there is provided an autonomous vehicle control apparatus comprising:

the high-precision positioning module is used for acquiring positioning information of the target vehicle;

the high-precision map module is used for acquiring map information;

the path planning module is used for planning a path based on the positioning information and the map information to obtain navigation information and track point information; the track point information is used for reflecting the path information of a driving path which drives from the high-speed main road into the ramp;

and the control module is used for controlling the target vehicle based on the navigation information and the track point information.

According to a third aspect of the present application, there is provided an electronic device comprising: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executes computer-executable instructions stored by the memory to cause the at least one processor to perform the autonomous vehicle control method as described above in the first aspect.

According to a fourth aspect of the present application, there is provided a computer-readable storage medium having stored therein computer-executable instructions for implementing the autonomous vehicle control method of the first aspect as described above when executed by a processor.

According to a fifth aspect of the present application, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the autonomous vehicle control method of the first aspect.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present application, nor do they limit the scope of the present application. Other features of the present application will become apparent from the following description.

Drawings

Fig. 1 is a schematic diagram of a first application scenario related to an embodiment of the present application;

fig. 2 is a schematic diagram of a second application scenario related to the embodiment of the present application;

FIG. 3 is a schematic flow chart illustrating a method for controlling an autonomous vehicle according to an embodiment of the present disclosure;

FIG. 4 is a schematic flow chart illustrating another method for controlling an autonomous vehicle according to an embodiment of the present disclosure;

FIG. 5 is a schematic flow chart illustrating another method for controlling an autonomous vehicle according to an embodiment of the present disclosure;

FIG. 6 is a schematic structural diagram of a control device of an autonomous vehicle according to an embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application.

For ease of understanding, an application scenario of the embodiment of the present application is first described.

Fig. 1 is a schematic diagram of a first application scenario related to the embodiment of the present application. As shown in fig. 1, the vehicle in the present embodiment needs to enter the decelerating lane from the high-speed trunk. Fig. 2 is a schematic diagram of a second application scenario related to the embodiment of the present application. As shown in fig. 2, the vehicle in the present embodiment needs to enter the ramp from the high-speed trunk. In any application scenario, in the prior art, lane lines are identified only by forward visual perception, lane lines of a main road and lane lines of a ramp are identified, and vehicles are controlled to change lanes and enter the ramp. However, the current visual perception lane line technology has poor recognition quality for the lane lines at the ramp port, so that the recognition of the lane lines of the main road where the vehicle originally runs is interfered by the appearance of the ramp, and the recognition of the lane lines of the newly added ramp is also unstable, so that the success rate of the vehicle entering the ramp from the high-speed main road is low, and the comfort of passengers in the vehicle is poor.

In order to solve at least one of the above technical problems, embodiments of the present application provide a method, an apparatus, a device, and a storage medium for controlling an autonomous vehicle, which are applied to the field of autonomous driving, and are used to solve the technical problems that the success rate of entering a ramp from a high-speed main road of the vehicle is low, and the comfort of passengers in the vehicle is also poor.

The method and the device have the main idea that the high-precision positioning information and the high-precision map information are jointly used as control factors to control the target vehicle, and more stable navigation information and path information are obtained through path planning, so that the success rate of the target vehicle entering the ramp from the high-speed main road can be improved.

The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 3 is a schematic flowchart of a control method for an autonomous vehicle according to an embodiment of the present disclosure.

As shown in fig. 3, the method of the present embodiment includes:

s301: and acquiring positioning information and map information of the target vehicle. The map information is acquired based on a high-precision map.

In this embodiment of the application, the target vehicle in S301 may refer to any vehicle, and the positioning information and the map information of the target vehicle may be acquired by different acquiring modules, and as can be seen from fig. 5, the high-precision positioning module is configured to update the current positioning position of the target vehicle in real time according to the motion of the target vehicle, and output the positioning information of the target vehicle to the path planning module, where the positioning information includes, but is not limited to: latitude, longitude, heading angle, altitude, speed, etc. The high-precision map module is configured to store high-precision map data and provide map information for the route planning module, where the map information may refer to map information of a certain area including the scene in fig. 1 or the scene in fig. 2, or may refer to map information of an urban area including the scene in fig. 1 or the scene in fig. 2, and therefore, the scope to which the map information belongs is not specifically limited in the embodiments of the present application.

S302: performing path planning based on the positioning information and the map information to obtain navigation information and track point information; and the track point information is used for reflecting the path information of the driving path of the on-ramp driven from the high-speed main road.

The path planning algorithm in the embodiment of the present application is not specifically limited, and may be any one of a genetic algorithm, Dijkstra algorithm, a-algorithm, and the like. The navigation information includes at least one of: the current lane type, the right lane type, the next navigation lane change sign, and the distance from the target vehicle to the next navigation lane change point. The track point information comprises: the track point comprises a course h [ N ] of the track point in a target vehicle coordinate system, an x coordinate x [ N ] of the track point in the target vehicle coordinate system, a y coordinate y [ N ] of the track point in the target vehicle coordinate system, a road longitudinal slope _ x [ N ] of the track point, a road transverse slope _ y [ N ] of the track point, a road curvature LaneCure [ N ] of the track point and a road speed limit spdlmt [ N ] of the track point. N is the quantity of track point, and its specific numerical value can carry out adaptability according to actual demand and adjust to interval, track point total distance between the track point also can carry out adaptability according to actual demand. The application takes N as an example of 40, and the first 25 points are spaced by 2m, the second 15 points are spaced by 20m, and the total distance between the trace points is 350 m. It should be understood that specific implementation of S302 may refer to detailed descriptions of S502 to S504 in fig. 5, which are not described herein again.

S303: and controlling the target vehicle based on the navigation information and the track point information.

It should be understood that specific implementation of S303 may refer to detailed descriptions of S403 to S404 in fig. 4, which are not described herein again.

It can be known from the descriptions of S301 to S303 that the embodiment of the present application uses the high-precision positioning information and the high-precision map information together as the control factor to control the target vehicle, and obtains more stable navigation information and path information through path planning, thereby improving the success rate of the target vehicle entering the ramp from the high-speed main road.

On the basis of the above embodiments, the technical solution of the present application will be described in more detail with reference to several specific embodiments.

Fig. 4 is a schematic flowchart of another control method for an autonomous vehicle according to an embodiment of the present disclosure. On the basis of the embodiment shown in fig. 3, the present embodiment focuses on refining S303 in fig. 3. As shown in fig. 4, the method of this embodiment includes:

s401: acquiring positioning information and map information of a target vehicle; it should be understood that, a specific implementation manner of S401 may refer to a detailed description of S301 in fig. 3, which is not described herein again.

S402: performing path planning based on the positioning information and the map information to obtain navigation information and track point information; the track point information is used for reflecting the path information of a driving path which drives from the high-speed main road into the ramp; it should be understood that specific implementation of S302 may refer to detailed descriptions of S502 to S504 in fig. 5, which are not described herein again.

S403: determining decision information by using a preset decision algorithm according to the navigation information;

the decision information is whether to enter tracking mode (0/1). A decision algorithm is arranged in the decision submodule for executing the above S403, specifically, according to the navigation information, a preset decision algorithm is used to determine whether to enter the tracking point mode (0/1), and the decision information whether to enter the tracking point mode (0/1) is sent to the control submodule, and the specific process is as the following S4031 to S4032, which is not described herein again.

S404: and under the condition that the decision information is in a track point tracking mode, controlling the target vehicle according to the track point information.

By executing the operations of S403 to S404, a specific process of controlling the target vehicle can be determined, and the target vehicle enters a tracking point mode, so that the target vehicle can be effectively controlled to keep running along the tracking point transversely according to stable path information, and the success rate of the vehicle running into the ramp from the high-speed main track can be improved.

In one possible implementation, the navigation information includes: a next navigation lane change marker and a distance of the target vehicle to a next navigation lane change point; the step S403: determining decision information by using a preset decision algorithm according to the navigation information, wherein the decision information comprises the following steps:

s4031: judging whether the next navigation lane change mark is a mark for entering a ramp from a high-speed main road to the right or not by using a preset decision algorithm, and whether the distance from the target vehicle to the next navigation lane change point is smaller than or equal to a preset threshold value or not;

s4032: and determining the tracking point entering mode as decision information under the condition that the next navigation lane change mark is a mark entering a ramp from the high-speed main road to the right and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold value. The preset threshold may be 100, or may be other values, which is not limited in this embodiment of the application. And when the decision submodule judges that the next navigation lane change mark is a mark entering a ramp from the high-speed main road to the right and the distance from the target vehicle to the next navigation lane change point is less than or equal to 100, outputting decision information as entering a tracking point mode.

In a possible implementation manner, the S404: controlling the target vehicle according to the track point information, comprising: and outputting a corresponding control instruction based on the track point information, and controlling the target vehicle by using the control instruction.

The control instruction may include a transverse control instruction and a longitudinal control instruction, a planning algorithm is provided in the control sub-module, and is configured to execute the S404, specifically, plan and control the motion of the target vehicle according to the decision information and the track point information, and output the transverse control information and the longitudinal control information in the form of the control instruction to further control the motion of the target vehicle (vehicle Ego in fig. 6). The lateral control information includes a steering wheel angle request, and the longitudinal control information includes an acceleration torque request and a deceleration request.

According to the method and the device, forward visual perception of a related scheme is replaced by high-precision positioning and a high-precision map, and under the scene that the high-speed main road enters the ramp, the corresponding path planning algorithm, the decision algorithm and the rule control algorithm are matched, so that more stable path information can be obtained, and further, the target vehicle enters the ramp from the high-speed main road according to the path information.

Fig. 5 is a schematic flowchart of another control method for an autonomous vehicle according to an embodiment of the present disclosure. On the basis of the embodiment shown in fig. 3, the present embodiment focuses on refining S302 in fig. 3. As shown in fig. 5, the method of the present embodiment includes:

s501: acquiring positioning information and map information of a target vehicle; it should be understood that a specific implementation manner of S501 may refer to a detailed description of S301 in fig. 3, or refer to a detailed description of S401 in fig. 4, which is not described herein again.

S502: determining the current position of the target vehicle in the map information according to the positioning information;

s503: determining a driving path for driving from the high-speed main road to the ramp according to the current position of the target vehicle and a preset destination position; it should be understood that specific implementation of S503 can refer to the following detailed descriptions of S5031 to S5033, which are not described herein again.

S504: determining the navigation information according to the driving path and the map information, and determining the track point information according to the driving path;

s505: and controlling the target vehicle based on the navigation information and the track point information.

It should be understood that specific implementation of S505 may refer to detailed descriptions of S403 to S404 in fig. 4, which are not described herein again. By performing the operations of S502 to S504 described above, a specific process of determining the navigation information and the track point information can be described in detail.

In one possible implementation, S503: determining a driving path for driving from the high-speed main road to the ramp according to the current position of the target vehicle and the preset destination position, wherein the method comprises the following steps:

s5031: determining whether a deceleration lane exists on a ramp according to the map information;

s5032: under the condition that a deceleration lane exists on the ramp, determining a driving path entering the deceleration lane from the high-speed main road by using a path planning algorithm according to the current position of the target vehicle and a preset destination position arranged on the deceleration lane;

s5033: and under the condition that no deceleration lane exists at the high speed, determining a driving path entering the ramp from the high-speed main road by using a path planning algorithm according to the current position of the target vehicle and a preset destination position arranged on the ramp.

By executing the operations of the above S5031 to S5033, whether a deceleration lane exists on the ramp can be determined, so that the scene in fig. 1 and the scene in fig. 2 can be intelligently distinguished, and the application can determine the driving path entering the ramp from the high-speed main road by using a path planning algorithm in different scenes, thereby effectively controlling the target vehicle. Further, in both the scenario in fig. 1 and the scenario in fig. 2, the travel path for entering the ramp from the expressway is determined by the operations of S5031 to S5033 described above.

Specifically, in the scenario in fig. 1, the path planning module fits a trajectory line that is transformed from the center line of the highway to the center line of the deceleration lane at a position where the width of the deceleration lane is gradually increased to be larger than the width of the target vehicle according to the lane line of the current highway and the lane line of the ramp in the indexed high-precision map, and outputs trajectory point information of the trajectory line in the vehicle coordinate system (with the center of the front bumper of the target vehicle as the origin, the forward direction as the x-axis positive direction, the rightward direction as the y-axis positive direction, and the upward direction as the z-axis positive direction).

Under the scene in fig. 2, the path planning module fits a trajectory line transformed from the lane center line of the highway to the lane center line of the ramp according to the lane line of the current highway and the lane line of the ramp in the indexed high-precision map on the premise of meeting the minimum turning radius of the target vehicle (the minimum turning radius of the target vehicle is a known value, for example, the minimum turning radius of a certain heavy truck vehicle is 30m, and the minimum turning radius is a parameter of the fitted trajectory line), and outputs trajectory point information of the trajectory line in the vehicle coordinate system (the center of a front bumper of the heavy truck vehicle is taken as the origin, the forward direction is the positive direction of the x axis, the rightward direction is the positive direction of the y axis, and the upward direction is the positive direction of the z axis).

In an alternative embodiment, the navigation information includes at least one of: the current lane type, the right lane type, the next navigation lane change mark, and the distance from the target vehicle to the next navigation lane change point, and thus the following determination processes of the respective navigation information may be introduced, wherein (1) the current lane type is determined in the following manner: and reading a road topological structure in the map information, determining the road where the current position of the vehicle is located and the type of the lane where the vehicle is located, and determining the type of the lane where the vehicle is located as the type of the current lane. The current lane type is a high-speed main road, a ramp or an emergency lane. (2) The right lane type is determined as follows: and reading a road topological structure in the map information, determining the type of the road where the current position of the vehicle is located and the type of the right lane, and determining the type of the right lane as the type of the right lane, wherein the type of the right lane is a main road, a ramp or an emergency lane. (3) The next navigation lane change marker is determined as follows: calculating a point of change of a road ID (Identity document) in the process of planning a path connecting the current position of the vehicle to the destination position, and calculating the types of lanes before and after the point, wherein if the point is a ramp before the point and a high-speed main lane after the point, the next navigation lane change mark is 'the ramp enters a high-speed driving lane leftwards', and if the point is the high-speed main lane before the point and the ramp after the point, the next navigation lane change mark is 'the high-speed main lane enters the ramp rightwards'. (4) The distance of the target vehicle to the next navigation lane change point is determined as follows: calculating a point with a changed road ID in the process of planning a path from the current position of the vehicle to the destination position, calculating the arc length distance from the current position to the point in a Frenet coordinate system, wherein if the arc length distance > is 5000m, the distance of the next navigation lane change point is 5000m, and if the arc length distance is less than 5000m, the distance of the next navigation lane change point is the arc length distance.

In one possible implementation, S504: determining the track point information according to the driving path, wherein the determining comprises the following steps: selecting track points from the current position of the target vehicle by combining a preset track point interval strategy, and generating track point information; the preset track point interval strategy is to select a first preset number of track points according to a first preset interval and select a second preset number of track points according to a second preset interval. For example, the first preset interval is 2m, the first preset number is 25, the second preset interval is 20m, and the second preset number is 15. The embodiment of the application does not specifically limit the specific numerical values of the first preset interval, the first preset number, the second preset interval and the second preset number.

The method for determining the track point information in the embodiment of the application is as follows: according to the planned driving path which is connected from the current position of the vehicle to the destination position, the coordinates of 40 track points are calculated from the position of the vehicle to the front, and the interval between the first 25 track points is set to be 2m, and the interval between the second 15 track points is set to be 20 m. The coordinates of the track points are the coordinates of the track points in the vehicle coordinate system (with the center of the front bumper of the target vehicle as the origin, the forward direction of the x axis, the forward direction of the y axis to the right, and the upward direction of the z axis).

According to the technical scheme, for two scenes of entering the ramp from the high-speed main road, a proper running path entering the ramp from the high-speed main road is fitted by a certain specific path planning algorithm without depending on a visually perceived lane line but depending on high-precision positioning and a high-precision map, navigation information and track point information 350m (adjustable) ahead are generated, then whether a decision submodule enters a track point tracking mode or not is judged by adopting a decision algorithm, a target vehicle is controlled to keep running along the track point by adopting a rule control algorithm according to the track point information in the track point tracking mode,

in summary, in the scenario that the high-speed main road enters the ramp, the recognition rate of the traditional method for the lane line at the ramp port is lower than 50%, and the lateral deviation of the lane line parameter is greater than 0.5 m. According to the experimental data collected by the real vehicle in fig. 6 (the own vehicle Ego in fig. 6), the success rate of fitting the track points at the ramp mouth is greater than 99.9% and the transverse deviation of the track points is less than 0.2m by adopting the technical scheme of high-precision positioning and high-precision maps. The actual vehicle test result shows that the success rate of automatically driving and controlling the target vehicle to enter the ramp from the high-speed main road is less than 70% in the traditional method, and the success rate of the method of the embodiment of the application is more than 95%, so that the success rate of the target vehicle entering the ramp from the high-speed main road is improved.

Fig. 6 is a schematic structural diagram of an automatic driving vehicle control device according to an embodiment of the present application. The apparatus of the present embodiment may be in the form of software and/or hardware. As shown in fig. 6, the present embodiment provides an automatic driving vehicle control apparatus including: a high precision positioning module 61, a high precision map module 62, a path planning module 63 and a control module 64. Wherein,

the high-precision positioning module 61 is used for acquiring positioning information of the target vehicle;

a high-precision map module 62 for obtaining map information;

a path planning module 63, configured to perform path planning based on the positioning information and the map information to obtain navigation information and track point information; the track point information is used for reflecting the path information of a driving path which drives from the high-speed main road into the ramp;

and the control module 64 is used for controlling the target vehicle based on the navigation information and the track point information.

In one possible implementation, the control module 64 includes a decision sub-module and a regulation sub-module, wherein:

the decision sub-module 641 is configured to determine decision information according to the navigation information by using a preset decision algorithm;

and the regulation and control sub-module 642 is used for controlling the target vehicle according to the track point information under the condition that the decision information is in the track point tracking mode.

In one possible implementation, the navigation information includes: a next navigation lane change marker and a distance of the target vehicle to a next navigation lane change point; the decision sub-module comprises: a judging unit and a first determining unit, wherein:

the judging unit is used for judging whether the next navigation lane change mark is a mark for entering a ramp from a high-speed main road to the right by using a preset decision algorithm, and whether the distance from the target vehicle to the next navigation lane change point is smaller than or equal to a preset threshold value;

and the first determining unit is used for determining the tracking trace point entering mode as decision information under the condition that the next navigation lane change mark is a mark for entering a ramp from a high-speed main road to the right and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold value.

In a possible implementation manner, the regulation and control sub-module is further configured to:

In a possible implementation manner, the path planning module 63 includes a first determining sub-module, a second determining sub-module, and a third determining sub-module, where:

the first determining submodule is used for determining the current position of the target vehicle in the map information according to the positioning information;

the second determining submodule is used for determining a driving path for driving from the high-speed main road to the ramp according to the current position of the target vehicle and the preset destination position;

and the third determining submodule is used for determining the navigation information according to the running path and the map information and determining the track point information according to the running path.

In one possible implementation, the second determining sub-module includes: a second determination unit, a third determination unit, and a fourth determination unit, wherein:

the second determining unit is used for determining whether a deceleration lane exists on the ramp according to the map information;

a third determining unit, configured to determine, by using a path planning algorithm, a driving path entering the deceleration lane from the high-speed main road according to a current position of the target vehicle and a preset destination position set on the deceleration lane, when the deceleration lane exists on the ramp;

and the fourth determining unit is used for determining a driving path entering the ramp from the high-speed main road by using a path planning algorithm according to the current position of the target vehicle and a preset destination position arranged on the ramp under the condition that the deceleration lane does not exist at the high speed.

A third determination submodule, further configured to:

The autonomous vehicle control apparatus provided in this embodiment may be configured to execute the autonomous vehicle control method provided in any of the method embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.

In the technical scheme of the application, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good custom of the public order.

According to an embodiment of the present application, an electronic device and a computer-readable storage medium are also provided.

Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device includes a receiver 70, a transmitter 71, a processor 72 and a memory 73, and the electronic device formed by the above components can be used to implement several specific embodiments of the present application, which are not described herein again.

The embodiment of the present application further provides a computer-readable storage medium, in which computer instructions are stored, and when the processor executes the computer instructions, the steps in the method in the foregoing embodiment are implemented.

Embodiments of the present application further provide a computer program product, which includes computer instructions, and when the computer instructions are executed by a processor, the computer instructions implement the steps of the method in the above embodiments.

Various implementations of the systems and techniques described here above may be realized in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs 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.

Program code for implementing the methods of the present application may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or electronic device.

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

To provide for interaction with a user, the systems and techniques described here can be implemented on 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 electronic device), or that includes a middleware component (e.g., an application electronic device), 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.

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 disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

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 principle of the present application shall be included in the protection scope of the present application.

Claims

1. An autonomous vehicle control method, comprising:

acquiring positioning information and map information of a target vehicle;

2. The method of claim 1, wherein the controlling the target vehicle based on the navigation information and the track point information comprises:

3. The method of claim 2, wherein the navigation information comprises: a next navigation lane change marker and a distance of the target vehicle to a next navigation lane change point; determining decision information by using a preset decision algorithm according to the navigation information comprises the following steps:

and determining the mode of entering the tracking trace point as decision information under the condition that the next navigation lane change mark is a mark entering a ramp from the high-speed main road to the right and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold value.

4. The method of claim 2, wherein the controlling the target vehicle according to the trajectory point information comprises:

5. The method of claim 1, wherein performing path planning based on the positioning information and the map information to obtain navigation information and track point information comprises:

6. The method according to claim 5, wherein determining a driving path from a high-speed main road to a ramp according to the current position of the target vehicle and a preset destination position comprises:

7. The method of claim 5, wherein determining the trajectory point information from the travel path comprises:

8. An autonomous vehicle control apparatus, characterized by comprising:

the high-precision map module is used for acquiring map information;

9. An electronic device, comprising: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the autonomous vehicle control method of any of claims 1 to 7.

10. A computer-readable storage medium having computer-executable instructions stored thereon for implementing the autonomous vehicle control method of any of claims 1 to 7 when executed by a processor.