CN115107809A - Automatic driving decision method and device, electronic equipment and storage medium - Google Patents

Automatic driving decision method and device, electronic equipment and storage medium Download PDF

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Publication number
CN115107809A
CN115107809A CN202210897616.8A CN202210897616A CN115107809A CN 115107809 A CN115107809 A CN 115107809A CN 202210897616 A CN202210897616 A CN 202210897616A CN 115107809 A CN115107809 A CN 115107809A
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China
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vehicle
obstacle
determining
transverse
strategy
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魏守洋
田山
张东好
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Beijing Jingxiang Technology Co Ltd
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Beijing Jingxiang Technology Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/402—Type
    • B60W2554/4029—Pedestrians
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4041—Position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/801—Lateral distance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/802—Longitudinal distance

Abstract

The application discloses an automatic driving decision method, an automatic driving decision device, electronic equipment and a storage medium. The method of the present application comprises: acquiring a planned path of a vehicle in a current decision period, and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path; acquiring barrier information in front of a vehicle, determining whether a barrier is in a dangerous area, and if the barrier is in the dangerous area, determining that the vehicle adopts a pre-deceleration strategy in a current decision period; and if the obstacle is not in the dangerous area, determining the static state of the obstacle, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state. This application takes the pre-deceleration strategy to the barrier in front of the vehicle, and at the in-process that the vehicle is close to the barrier, the safety of autopilot is ensured to dynamic adjustment planning speed to compromise travelling comfort and efficiency.

Description

Automatic driving decision method and device, electronic equipment and storage medium
Technical Field
The present application relates to the field of automotive technologies, and in particular, to an automatic driving decision method and apparatus, an electronic device, and a storage medium.
Background
The decision-making subsystem is one of the core subsystems of the automatic driving system, and the safety, comfort and driving efficiency of the automatic driving system are directly influenced by the quality of a decision-making planning algorithm adopted by the decision-making subsystem. Autonomous vehicles are often affected by obstacles during driving, such as scenes in which pedestrians cross or walk along a road, and if the decision planning algorithm is not properly processed, serious traffic accidents may be caused.
The existing automatic emergency braking system is divided into a braking area, an alarming area and a safety area according to the transverse position of a vehicle when an obstacle crosses a road scene. The position and the speed of the obstacle are recognized through a perception prediction system of the self-vehicle, the running track of the obstacle is predicted, and if the obstacle is predicted to collide with the self-vehicle in a braking area, the self-vehicle is controlled to decelerate. Because the longitudinal distance is not considered in the decision making process, when the fact that the obstacle collides with the self-vehicle in a braking area is predicted, the obstacle needs to be decelerated urgently, and the comfort and the safety are poor.
In view of the above problems, the prior art generates a warning signal in the face of an obstacle in a warning area, so that a driver artificially controls a vehicle in accordance with the warning signal to cope with possible actions of the obstacle. However, the movement of obstacles such as pedestrians has high mobility and unpredictability, especially, the prediction of the obstacle trajectory by the sensing subsystem cannot be completely accurate, and if a decision planning algorithm is not appropriate, even if a driver manually controls the system, serious traffic accidents can be caused.
Disclosure of Invention
In order to overcome at least one of the above-mentioned problems, embodiments of the present application provide an automatic driving decision method, an automatic driving decision device, an electronic device, and a storage medium.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides an automatic driving decision method, including:
acquiring a planned path of a vehicle in a current decision period, and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path;
acquiring obstacle information in front of a vehicle and determining whether the obstacle is in the dangerous area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle;
if the obstacle is in the dangerous area, determining that the vehicle adopts a pre-deceleration strategy in the current decision period;
if the obstacle is not in the dangerous area, determining the static state of the obstacle, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state.
Optionally, the determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path includes:
acquiring a vehicle position and preset transverse distance of a near vehicle end, transverse distance of a far vehicle end and a path length reference value, wherein the transverse distance of the near vehicle end is smaller than the transverse distance of the far vehicle end;
determining a near vehicle end transverse reference position according to the vehicle position and the near vehicle end transverse distance, and determining a far vehicle end transverse reference position according to the path length reference value and the far vehicle end transverse distance along the advancing direction of the planned path;
and determining the dangerous area according to the near vehicle end transverse reference position and the far vehicle end transverse reference position.
Optionally, the determining a near end lateral reference position according to the vehicle position and the near end lateral distance includes:
the vehicle position is taken as a reference point, the transverse distance of the near vehicle end is extended along the advancing direction vertical to the planned path to obtain the transverse reference position of the left side of the near vehicle end, and the transverse distance of the near vehicle end is extended along the advancing direction vertical to the planned path by taking the vehicle position as the reference point to obtain the transverse reference position of the right side of the near vehicle end;
determining a far vehicle end transverse reference position according to the path length reference value and the far vehicle end transverse distance along the advancing direction of the planned path, wherein the method comprises the following steps:
taking the vehicle position as a reference point, and extending the distance of the path length reference value along the advancing direction of the planned path to obtain the position of the far vehicle end;
and taking the position of the far vehicle end as a reference point, extending the transverse distance of the far vehicle end along the advancing direction vertical to the planned path to obtain the transverse reference position of the left side of the far vehicle end, and taking the position of the far vehicle end as a reference point, extending the transverse distance of the far vehicle end against the advancing direction vertical to the planned path to obtain the transverse reference position of the right side of the far vehicle end.
Optionally, the determining the dangerous area according to the near vehicle end lateral reference position and the far vehicle end lateral reference position includes:
and sequentially connecting the near vehicle end left side transverse reference position, the near vehicle end right side transverse reference position, the far vehicle end right side transverse reference position and the far vehicle end left side transverse reference position to obtain the trapezoidal dangerous area.
Optionally, the obstacle information includes an obstacle location, the determining whether the obstacle is within the hazardous area includes:
acquiring the longitudinal distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position;
determining whether a longitudinal distance of the obstacle relative to the vehicle is greater than the path-length reference value, and if so, determining that the obstacle is not within the hazard zone; if the distance is not larger than the path length reference value, acquiring the transverse distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position, and acquiring the transverse boundary distance corresponding to the obstacle according to the obstacle position and the trapezoid waist line boundary of the dangerous area;
determining whether a lateral distance of the obstacle relative to the vehicle is greater than the lateral boundary distance, if so, determining that the obstacle is not within the danger zone, and if not, determining that the obstacle is within the danger zone.
Optionally, the pre-deceleration strategy includes a deceleration parking strategy, and if the obstacle is in the danger area, determining that the vehicle adopts the pre-deceleration strategy in the current decision period includes:
obtaining a parking position according to the position of the obstacle and a preset safe distance;
determining a parking speed curve corresponding to a deceleration parking strategy according to the vehicle position and the parking position;
and executing the deceleration parking strategy according to the speed curve.
Optionally, the obstacle information further includes a movement trajectory of an obstacle, the pre-deceleration strategy includes a deceleration avoidance strategy, and when the obstacle is in a movement state, determining that the vehicle adopts the pre-deceleration strategy in a current decision-making period includes:
acquiring the motion trail of the obstacle and the path overlapping time of the planned path;
determining an avoidance speed curve corresponding to a deceleration avoidance strategy according to the path overlapping time;
and executing the deceleration avoidance strategy according to the avoidance speed curve.
In a second aspect, an embodiment of the present application provides an automatic driving decision apparatus, including:
the first processing unit is used for acquiring a planned path of the vehicle in a current decision period and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path;
the second processing unit is used for acquiring obstacle information in front of a vehicle and determining whether the obstacle is in the dangerous area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle;
the first decision unit is used for determining that the vehicle adopts a pre-deceleration strategy in the current decision period if the obstacle is in the dangerous area;
and the second decision unit is used for determining the static and dynamic state of the obstacle if the obstacle is not in the dangerous area, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state.
In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to perform an automated driving decision method.
In a fourth aspect, embodiments of the present application further provide a computer readable storage medium storing one or more programs that, when executed by an electronic device that includes a plurality of application programs, cause the electronic device to perform an automated driving decision method.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
according to the embodiment of the application, the dangerous area is determined according to the advancing direction and the transverse direction of the planned path, and the advancing direction of the planned path comprises longitudinal position information in the advancing direction of a vehicle, so that enough longitudinal distance can be provided for supporting the vehicle to adopt a pre-deceleration strategy for movable barriers in the dangerous area and outside the dangerous area, the emergency braking or collision risk caused by inaccurate perception subsystem or sudden change of the movement state of the barriers after the vehicle approaches the barriers at a high speed is avoided, and the problem of poor comfort caused by emergency parking or emergency steering after the vehicle approaches the barriers at a high speed can be avoided.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic flow chart illustrating an automatic driving decision method according to an embodiment of the present disclosure;
FIG. 2 is a schematic view of a hazardous area in an embodiment of the present application;
FIG. 3 is a schematic view of a pedestrian outside a danger zone in an embodiment of the present application;
FIG. 4 is a schematic view of a pedestrian crossing a roadway in an embodiment of the present application;
FIG. 5 is a schematic diagram of an automated driving decision process in an embodiment of the present application;
FIG. 6 is a schematic structural diagram of an automatic driving decision device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
An embodiment of the present application provides an automatic driving decision method, and as shown in fig. 1, provides a flow diagram of an automatic driving decision method in an embodiment of the present application, where the method at least includes the following steps S110 to S140:
step S110, a planned path of the vehicle in the current decision cycle is obtained, and a dangerous area in front of the vehicle is determined according to the advancing direction and the transverse direction of the planned path.
The automatic driving system comprises a decision-making subsystem, a perception subsystem, a navigation subsystem and the like, the automatic driving decision-making method of the embodiment of the application can be executed by the decision-making subsystem of the automatic driving system, and the decision-making subsystem executes the automatic driving decision-making method every decision period.
When the vehicle is in the automatic driving mode, the navigation subsystem plans a planned path of the vehicle in the current decision-making period in advance, the decision-making subsystem acquires the planned path through the navigation subsystem, the planned path of the vehicle in the current decision-making period can be a planned driving track of the vehicle in the current decision-making period, if the vehicle does not encounter any obstacle, the vehicle drives along the planned path, and the acquisition of the planned path of the vehicle in the current decision-making period can be realized in any conventional manner, which is not described herein in detail.
The decision cycle refers to the time when the vehicle determines the decision strategy, and since the environment around the vehicle on the road is instantaneously changeable, the decision strategy needs to be made in real time based on the obstacle information and the current planned path, for example, the decision behavior can be determined once every 100 milliseconds.
Different from the prior art, in the embodiment, when the planned path is obtained, the dangerous area is determined according to the advancing direction and the transverse direction of the planned path, and the advancing direction of the planned path includes the longitudinal position information in the advancing direction of the vehicle, so that whether an obstacle exists in the dangerous area in the advancing direction of the vehicle can be judged in advance based on the longitudinal position information and the transverse position information, when the obstacle exists, pre-deceleration processing can be performed in time, and emergency stop or emergency steering after the vehicle approaches the obstacle at a high speed is avoided.
Step S120, obtaining obstacle information in front of the vehicle, and determining whether the obstacle is in a dangerous area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle.
In an autonomous driving environment, the obstacle may be an object that may obstruct the vehicle from traveling on a road as perceived by the vehicle, and may be a stationary object or a movable object, such as a pedestrian, an animal, or a fixed obstacle.
The obstacle information includes a static and dynamic state of the obstacle, an obstacle position, an obstacle type, an obstacle size, an obstacle speed, a movement trajectory of the obstacle, and the like. The size of the obstacle refers to the length, width and height information of the obstacle, the speed of the obstacle refers to the speed of the movable obstacle, the movement speed can be a vector containing the direction, the movement track can be a movement track predicted based on the movement speed of the obstacle, and the static state and the dynamic state of the obstacle are used for reflecting the static state or the movement state of the obstacle. The obstacle information in front of the vehicle may be obtained in any available manner, which is not described herein.
The decision-making strategy comprises a pre-deceleration strategy, a normal cruise strategy and the like, wherein the pre-deceleration strategy can further comprise a deceleration parking strategy and a deceleration avoidance strategy.
And step S130, if the obstacle is in the dangerous area, determining that the vehicle adopts a pre-deceleration strategy in the current decision period.
Step S140, if the obstacle is not in the danger area, determining the static state and the dynamic state of the obstacle, determining that the vehicle adopts a normal cruise strategy in the current decision-making period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision-making period when the obstacle is in the motion state.
Based on the steps, when the obstacle in front of the vehicle is determined to be in the dangerous area, and when the obstacle in front of the vehicle is determined to be out of the dangerous area but is a movable obstacle, a pre-deceleration strategy is adopted, so that the condition that the vehicle approaches the obstacle at a high speed is avoided, and the safety and the comfort of automatic driving are improved due to the emergency stop or collision risk caused by the fact that a perception subsystem is inaccurate or the obstacle suddenly changes the motion state; after the vehicle of this embodiment adopts the pre-deceleration strategy, when the vehicle is close to the barrier, perception subsystem can output the more accurate position of barrier and motion information, and decision-making subsystem can judge whether the barrier can cause the influence to the going of vehicle more accurately this moment to take more reasonable decision-making strategy based on more accurate recognition result, improve autopilot's decision efficiency and accuracy.
In one embodiment of the present application, determining a hazard zone ahead of a vehicle from a heading direction and a lateral direction of a planned path includes:
obtaining the position of the vehicle and the preset transverse distance l of the near end of the vehicle 0 Distance l from the vehicle end max And a path length reference value s max The lateral distance l of the near end 0 Less than the transverse distance l of the far vehicle end max (ii) a According to the position of the vehicle and the transverse distance l of the near end 0 Determining the transverse reference position of the near end of the vehicle, and the advancing direction along the planned path according to the path length reference value s max And a transverse distance l from the far end of the vehicle max Determining a transverse reference position of a far vehicle end; and determining a dangerous area according to the transverse reference position of the near vehicle end and the transverse reference position of the far vehicle end.
It is found that, in the transverse direction of the planned path, since the vehicle is in the driving state, the transverse position of the obstacle that can affect the driving of the vehicle exhibits an approximately linear position constraint with the distance from the longitudinal direction of the vehicle, as shown in fig. 2, at the near end, the transverse distance of the obstacle that can affect the driving of the vehicle is smaller than that at the far end, and based on this, the present embodiment sets the transverse distance l at the near end in advance 0 Distance l from the vehicle end max And determining the near vehicle end transverse reference position and the far vehicle end transverse reference position so as to obtain the dangerous area according to the near vehicle end transverse reference position and the far vehicle end transverse reference position.
Wherein, the transverse distance l of the far end of the vehicle max The calibration can be carried out according to the precision of a perception subsystem of the vehicle and the braking performance of the vehicle, and the transverse distance l of the near vehicle end 0 The setting may be made in accordance with the vehicle width, for example, the near-vehicle end lateral distance l may be set based on the following formula (1) 0 ：
Figure BDA0003769682640000081
In the formula (1), width is the vehicle width, l buffer Is a dimension of outward expansion of the vehicle widthThe size of the expansion can be set according to driving safety, and the embodiment of the present application is not particularly limited.
Referring to fig. 2, the present embodiment takes the position of the vehicle as a reference point, and extends a lateral distance l from the vehicle end along the advancing direction perpendicular to the planned path 0 Obtaining the lateral reference position of the left side of the near end of the vehicle, and extending the lateral distance l of the near end of the vehicle against the advancing direction vertical to the planned path by taking the position of the vehicle as a reference point 0 Obtaining a transverse reference position of the right side of the near vehicle end;
and further taking the position of the vehicle as a reference point, and extending a path length reference value s along the advancing direction of the planned path max The distance of the distance is obtained, the position of the far vehicle end is taken as a reference point, and the transverse distance l of the far vehicle end is extended along the advancing direction vertical to the planned path max Obtaining a left lateral reference position of the far vehicle end, and extending a lateral distance l of the far vehicle end against the advancing direction perpendicular to the planned path by taking the position of the far vehicle end as a reference point max And obtaining the transverse reference position of the right side of the far vehicle end. Wherein the path length reference value s max Calibration may be based on the accuracy of the vehicle's sensing subsystem and the braking performance of the vehicle.
The near-vehicle-end left-side lateral reference position of the present embodiment refers to a limit value of the lateral position of the dangerous area at the near-vehicle end in the vehicle left-side direction, and the near-vehicle-end right-side lateral reference position refers to a limit value of the lateral position of the dangerous area at the near-vehicle end in the vehicle right-side direction. Similarly, the far-vehicle-end left-side lateral reference position refers to a limit value of a lateral position of the dangerous area at the far vehicle end in the vehicle left-side direction, and the far-vehicle-end right-side lateral reference position refers to a limit value of a lateral position of the dangerous area at the far vehicle end in the vehicle right-side direction.
After the limit values of the lateral positions of the dangerous area on the left and right sides of the vehicle at the near vehicle end and the far vehicle end are obtained, the near vehicle end left lateral reference position, the near vehicle end right lateral reference position, the far vehicle end right lateral reference position and the far vehicle end left lateral reference position are connected in sequence, and the dangerous area having a trapezoidal shape as shown in fig. 2 is obtained.
Therefore, after the dangerous area in front of the vehicle is obtained, if the sensing subsystem senses that the obstacle exists in front of the vehicle and outputs the obstacle information to the decision subsystem, the decision subsystem can judge whether the obstacle is in the dangerous area or not based on the obstacle information.
In one embodiment of the application, upon determining that the obstacle is within the danger zone, the determining that the vehicle is to adopt a deceleration parking strategy within a current decision period includes:
acquiring the longitudinal distance of the obstacle relative to the vehicle according to the position of the vehicle and the position of the obstacle, and determining whether the longitudinal distance of the obstacle relative to the vehicle is greater than a path length reference value s max If it is greater than the path length reference value s max Then it is determined that the obstacle is not within the hazard zone. If the distance is not greater than the path length reference value, acquiring the transverse distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position, acquiring the transverse boundary distance corresponding to the obstacle according to the obstacle position and the trapezoid waist line boundary of the dangerous area, determining whether the transverse distance of the obstacle relative to the vehicle is greater than the transverse boundary distance, if so, determining that the obstacle is not in the dangerous area, and if not, determining that the obstacle is in the dangerous area.
In a specific implementation process, the present embodiment may construct a coordinate system according to the forward direction of the planned path (i.e., s direction in fig. 2) and the lateral direction of the planned path (i.e., l direction in fig. 2), and after the vehicle position and the obstacle position acquired by the decision making system are obtained, coordinate system conversion may be performed to obtain a longitudinal coordinate represented by the vehicle position and the obstacle position based on the forward direction and a lateral coordinate represented by the lateral direction. At this time, the longitudinal distance of the obstacle with respect to the vehicle can be quickly calculated based on the difference between the longitudinal coordinate of the obstacle position and the longitudinal coordinate of the vehicle position. With continued reference to fig. 2, if the coordinates of the vehicle position in the coordinate system are (0,0), the coordinates of the obstacle in the coordinate system are(s) p ，l p ) Then the longitudinal distance of the obstacle with respect to the vehicle is | s p If s p |＞s max Then no relay is neededThe transverse distance of the obstacle relative to the vehicle is continuously judged, and the obstacle can be directly determined not to be in the dangerous area, so that the calculation efficiency is improved.
If s p |≤s max If the position of the dangerous area is determined to be horizontal, the linear expression corresponding to the trapezoid waist line boundary of the dangerous area is calculated, and s is calculated according to the following formula (2) p Corresponding lateral boundary distance l(s) p )：
Figure BDA0003769682640000101
If | l is shown in FIG. 2 p |≤|l(s p ) If l, it can be determined that the obstacle is in the danger area, as shown in fig. 3 p |＞|l(s p ) If the current speed of the vehicle is used as the initial speed, a cruise speed curve reaching the target cruise speed in the current decision period is calculated, and the normal cruise strategy is executed according to the cruise speed curve.
The pre-deceleration strategy in the embodiment of the application comprises a deceleration parking strategy and a deceleration avoidance strategy, and when an obstacle is in a dangerous area, the pre-deceleration strategy adopted by a vehicle in a current decision period is determined through the following steps:
according to the position of the obstacle and the preset safe distance s safe The parking position is obtained, and the coordinate of the parking position in the coordinate system is (| s) in the above embodiment p |-|s safe And 0), determining a parking speed curve corresponding to the deceleration parking strategy according to the vehicle position and the parking position, and executing the deceleration parking strategy according to the speed curve. If a polynomial fitting or numerical optimization problem is constructed, the parking speed curve is constructed, and the parking speed curve is in the range of | s p |-|s safe L to decelerate the vehicle to zero within a distance range, where the safety distance s safe The safety distance between the front end of the vehicle and the obstacle in the s direction after the vehicle is stopped stably can be set according to safety requirements.
When the obstacle is in a moving state, determining a deceleration avoidance strategy adopted by the vehicle in the current decision period through the following steps:
obtaining the path overlapping time of the movement track of the obstacle and the planned path, as shown in fig. 4, it can be calculated that the transverse distance on the movement track of the obstacle is equal to l 0 Time t of 1 And t 2 The [ t ] of 1 ,t 2 ]Namely the path overlapping time, an avoidance speed curve corresponding to the deceleration avoidance strategy can be determined according to the path overlapping time, and the deceleration avoidance strategy is executed according to the avoidance speed curve. If a polynomial fitting or numerical optimization problem building method is adopted to build the avoiding speed curve, the avoiding speed curve enables the vehicle not to be in [ t ] 1 ,t 2 ]Collision with an obstacle in time.
In order to facilitate understanding of the above embodiments of the present application, the automatic driving decision method according to the embodiments of the present application will be described in detail below with reference to a flowchart shown in fig. 5 and taking a pedestrian as an example.
As shown in fig. 5, the decision-making subsystem obtains the obstacle information from the sensing subsystem, determines whether the obstacle in front of the vehicle is a pedestrian or not based on the obstacle type, and performs decision-making control based on a preset decision-making method if the obstacle is not a pedestrian, calculates the longitudinal distance and the transverse distance of the pedestrian relative to the vehicle if the obstacle is a pedestrian, determines whether the pedestrian is in a dangerous area or not based on the comparison result of the longitudinal distance and the path length reference value and the comparison result of the transverse distance and the transverse boundary distance, and if the pedestrian is determined to be in the dangerous area, the vehicle adopts a pre-deceleration strategy, specifically, plans a parking speed curve, and executes a deceleration parking strategy according to the parking speed curve. And if the pedestrian is judged not to be in the dangerous area, further determining the static state and the dynamic state of the pedestrian, and if the pedestrian is in the static state, adopting a normal cruise strategy, specifically planning a cruise speed curve, and executing the normal cruise strategy based on the cruise speed curve. When the pedestrian is in a moving state, calculating the path overlapping time of the moving track of the pedestrian and the planned path, planning an avoidance speed curve based on the path overlapping time, and executing a deceleration avoidance strategy based on the avoidance speed curve.
Therefore, the automatic driving decision method provided by the application fully considers the relative transverse position, the relative longitudinal position and the relative speed of the planned path of the barrier and the vehicle, and adopts different pre-deceleration strategies for the movable barrier and the static barrier in the dangerous area and outside the dangerous area by reasonably setting the dangerous area in front of the vehicle. Aiming at the obstacle with collision risk, a deceleration parking strategy is adopted in advance, so that the emergency braking or collision risk caused by inaccurate perception subsystem or sudden change of the motion state of the target after the vehicle approaches the obstacle at a high speed is avoided; when the vehicle approaches the obstacle, the sensing subsystem can output more accurate obstacle position and movement information, and at the moment, a corresponding decision strategy can be more accurately determined and executed, so that the decision efficiency of automatic driving is improved.
According to the embodiment of the application, a reasonable pre-deceleration strategy can be adopted according to a specific scene, the collision risk in the automatic driving process is reduced, and the comfort and the efficiency in the automatic driving process can be considered.
The same technical concept as the automatic driving decision method in the foregoing embodiment is also included, and an embodiment of the present application further provides an automatic driving decision device 600, as shown in fig. 6, which provides a schematic structural diagram of an automatic driving decision device in an embodiment of the present application, where the automatic driving decision device 600 includes: a first processing unit 610, a second processing unit 620, a first decision unit 630 and a second decision unit 640, wherein:
the first processing unit 610 is configured to obtain a planned path of a vehicle in a current decision cycle, and determine a dangerous area in front of the vehicle according to a forward direction and a transverse direction of the planned path;
a second processing unit 620, configured to acquire obstacle information in front of a vehicle, and determine whether the obstacle is within the dangerous area, where the obstacle information includes a static state and a dynamic state of the obstacle;
a first decision unit 630, configured to determine that the vehicle adopts a pre-deceleration strategy in a current decision period if the obstacle is in the dangerous area;
a second decision unit 640, configured to determine a static state of the obstacle if the obstacle is not located in the dangerous area, determine that the vehicle adopts a normal cruise strategy in a current decision period when the obstacle is located in the static state, and determine that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is located in a moving state.
In an embodiment of the present application, the first processing unit 610 is configured to obtain a vehicle position and preset near vehicle end lateral distance, far vehicle end lateral distance and path length reference value, where the near vehicle end lateral distance is smaller than the far vehicle end lateral distance; determining a near vehicle end transverse reference position according to the vehicle position and the near vehicle end transverse distance, and determining a far vehicle end transverse reference position according to the path length reference value and the far vehicle end transverse distance along the advancing direction of the planned path; and determining the dangerous area according to the transverse reference position of the near vehicle end and the transverse reference position of the far vehicle end.
In an embodiment of the present application, the first processing unit 610 is further configured to obtain a lateral reference position of a left side of the proximal end by extending the lateral distance of the proximal end along a forward direction perpendicular to the planned path with the vehicle position as a reference point, and obtain a lateral reference position of a right side of the proximal end by extending the lateral distance of the proximal end against the forward direction perpendicular to the planned path with the vehicle position as a reference point; taking the vehicle position as a reference point, and extending the distance of the path length reference value along the advancing direction of the planned path to obtain the position of the far vehicle end; and taking the position of the far vehicle end as a reference point, extending the transverse distance of the far vehicle end along the advancing direction vertical to the planned path to obtain the transverse reference position of the left side of the far vehicle end, and taking the position of the far vehicle end as a reference point, extending the transverse distance of the far vehicle end against the advancing direction vertical to the planned path to obtain the transverse reference position of the right side of the far vehicle end.
In an embodiment of the present application, the first processing unit 610 is further configured to sequentially connect the near vehicle end left side transverse reference position, the near vehicle end right side transverse reference position, the far vehicle end right side transverse reference position, and the far vehicle end left side transverse reference position, so as to obtain that the danger zone is trapezoidal.
In an embodiment of the application, the obstacle information includes an obstacle position, and the second processing unit 620 is further configured to obtain a longitudinal distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position; determining whether a longitudinal distance of the obstacle relative to the vehicle is greater than the path-length reference value, and if so, determining that the obstacle is not within the hazard zone; if the distance is not larger than the path length reference value, acquiring the transverse distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position, and acquiring the transverse boundary distance corresponding to the obstacle according to the obstacle position and the trapezoid waist line boundary of the dangerous area; determining whether a lateral distance of the obstacle relative to the vehicle is greater than the lateral boundary distance, if so, determining that the obstacle is not within the danger zone, and if not, determining that the obstacle is within the danger zone.
In an embodiment of the present application, the pre-deceleration strategy includes a deceleration parking strategy, and the first decision unit 630 is specifically configured to obtain a parking position according to the obstacle position and a preset safe distance; determining a parking speed curve corresponding to a deceleration parking strategy according to the vehicle position and the parking position; and executing the deceleration parking strategy according to the speed curve.
In an embodiment of the present application, the obstacle information further includes a motion trajectory of the obstacle, the pre-deceleration strategy includes a deceleration avoidance strategy, and the second decision unit 640 is specifically configured to, when the obstacle is in a motion state, obtain a path overlapping time between the motion trajectory of the obstacle and the planned path; determining an avoidance speed curve corresponding to a deceleration avoidance strategy according to the path overlapping time; and executing the deceleration avoidance strategy according to the avoidance speed curve.
It can be understood that the automatic driving decision device 600 can implement the steps of the automatic driving decision method provided in the foregoing embodiments, and the related explanations regarding the automatic driving decision method are applicable to the automatic driving decision device 600, and are not described herein again.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 7, at the hardware level, the electronic device includes a processor and a memory, and optionally further includes an internal bus and a network interface. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 6, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory to the memory and then runs the computer program to form the automatic driving decision device on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring a planned path of a vehicle in a current decision period, and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path;
acquiring obstacle information in front of a vehicle and determining whether the obstacle is in the dangerous area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle;
if the obstacle is in the danger area, determining that the vehicle adopts a pre-deceleration strategy in the current decision period;
if the obstacle is not in the dangerous area, determining the static state of the obstacle, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state.
The method performed by the automatic driving decision device disclosed in the embodiment of fig. 1 of the present application may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is positioned in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the automatic driving decision-making method.
The electronic device may also execute the method executed by the automatic driving decision-making device in fig. 1, and implement the function of the automatic driving decision-making device in the embodiment shown in fig. 1, which is not described herein again.
Embodiments of the present application further provide a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by an electronic device including a plurality of application programs, enable the electronic device to perform the method performed by the automatic driving decision apparatus in the embodiment shown in fig. 1, and are specifically configured to perform:
acquiring a planned path of a vehicle in a current decision period, and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path;
acquiring obstacle information in front of a vehicle, and determining whether the obstacle is in the danger area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle;
if the obstacle is in the dangerous area, determining that the vehicle adopts a pre-deceleration strategy in the current decision period;
if the obstacle is not in the dangerous area, determining the static state of the obstacle, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (10)

1. An automated driving decision method, comprising:
acquiring a planned path of a vehicle in a current decision period, and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path;
acquiring obstacle information in front of a vehicle and determining whether the obstacle is in the dangerous area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle;
if the obstacle is in the dangerous area, determining that the vehicle adopts a pre-deceleration strategy in the current decision period;
if the obstacle is not in the dangerous area, determining the static state of the obstacle, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state.
2. The method of claim 1, wherein determining the hazard zone ahead of the vehicle based on the heading and the lateral direction of the planned path comprises:
acquiring a vehicle position and preset transverse distance of a near vehicle end, transverse distance of a far vehicle end and a path length reference value, wherein the transverse distance of the near vehicle end is smaller than the transverse distance of the far vehicle end;
determining a near vehicle end transverse reference position according to the vehicle position and the near vehicle end transverse distance, and determining a far vehicle end transverse reference position according to the path length reference value and the far vehicle end transverse distance along the advancing direction of the planned path;
and determining the dangerous area according to the transverse reference position of the near vehicle end and the transverse reference position of the far vehicle end.
3. The method of claim 2, wherein said determining a near end lateral reference position based on said vehicle position and said near end lateral distance comprises:
the vehicle position is taken as a reference point, the transverse distance of the near vehicle end is extended along the advancing direction vertical to the planned path to obtain the transverse reference position of the left side of the near vehicle end, and the transverse distance of the near vehicle end is extended along the advancing direction vertical to the planned path by taking the vehicle position as the reference point to obtain the transverse reference position of the right side of the near vehicle end;
determining a far vehicle end transverse reference position according to the path length reference value and the far vehicle end transverse distance along the advancing direction of the planned path, wherein the method comprises the following steps:
taking the vehicle position as a reference point, and extending the distance of the path length reference value along the advancing direction of the planned path to obtain the position of the far vehicle end;
and taking the position of the far vehicle end as a reference point, extending the transverse distance of the far vehicle end along the advancing direction vertical to the planned path to obtain the transverse reference position of the left side of the far vehicle end, and taking the position of the far vehicle end as a reference point, extending the transverse distance of the far vehicle end against the advancing direction vertical to the planned path to obtain the transverse reference position of the right side of the far vehicle end.
4. The method of claim 3, wherein said determining the hazard zone from the near vehicle end lateral reference position and the far vehicle end lateral reference position comprises:
and sequentially connecting the near vehicle end left side transverse reference position, the near vehicle end right side transverse reference position, the far vehicle end right side transverse reference position and the far vehicle end left side transverse reference position to obtain the trapezoidal dangerous area.
5. The method of claim 4, wherein the obstacle information includes an obstacle location, the determining whether the obstacle is within the hazardous area comprising:
acquiring the longitudinal distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position;
determining whether a longitudinal distance of the obstacle relative to the vehicle is greater than the path-length reference value, and if so, determining that the obstacle is not within the hazard zone; if the distance is not larger than the path length reference value, acquiring the transverse distance of the obstacle relative to the vehicle according to the vehicle position and the obstacle position, and acquiring the transverse boundary distance corresponding to the obstacle according to the obstacle position and the trapezoid waist line boundary of the dangerous area;
determining whether a lateral distance of the obstacle relative to the vehicle is greater than the lateral boundary distance, if so, determining that the obstacle is not within the danger zone, and if not, determining that the obstacle is within the danger zone.
6. The method of claim 5, wherein the pre-deceleration strategy comprises a deceleration parking strategy, and wherein determining that the vehicle is to assume the pre-deceleration strategy within a current decision period if the obstacle is within the hazardous area comprises:
obtaining a parking position according to the position of the obstacle and a preset safe distance;
determining a parking speed curve corresponding to a deceleration parking strategy according to the vehicle position and the parking position;
and executing the deceleration parking strategy according to the speed curve.
7. The method of claim 1, wherein the obstacle information further includes a trajectory of movement of an obstacle, the pre-deceleration strategy includes a deceleration avoidance strategy, and the determining that the vehicle is to adopt the pre-deceleration strategy in a current decision period when the obstacle is in motion comprises:
acquiring the motion trail of the obstacle and the path overlapping time of the planned path;
determining an avoidance speed curve corresponding to a deceleration avoidance strategy according to the path overlapping time;
and executing the deceleration avoidance strategy according to the avoidance speed curve.
8. An automated driving decision device, comprising:
the first processing unit is used for acquiring a planned path of the vehicle in a current decision period and determining a dangerous area in front of the vehicle according to the advancing direction and the transverse direction of the planned path;
the second processing unit is used for acquiring obstacle information in front of a vehicle and determining whether the obstacle is in the dangerous area, wherein the obstacle information comprises a static state and a dynamic state of the obstacle;
the first decision unit is used for determining that the vehicle adopts a pre-deceleration strategy in the current decision period if the obstacle is in the dangerous area;
and the second decision unit is used for determining the static and dynamic state of the obstacle if the obstacle is not in the dangerous area, determining that the vehicle adopts a normal cruise strategy in the current decision period when the obstacle is in the static state, and determining that the vehicle adopts a pre-deceleration strategy in the current decision period when the obstacle is in the motion state.
9. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform an automated driving decision method according to any one of claims 1 to 7.
10. A computer readable storage medium storing one or more programs which, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform an automatic driving decision method according to any one of claims 1-7.
CN202210897616.8A 2022-07-28 2022-07-28 Automatic driving decision method and device, electronic equipment and storage medium Pending CN115107809A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116572996A (en) * 2023-07-12 2023-08-11 北京易控智驾科技有限公司 Vehicle control method and device and unmanned vehicle

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116572996A (en) * 2023-07-12 2023-08-11 北京易控智驾科技有限公司 Vehicle control method and device and unmanned vehicle
CN116572996B (en) * 2023-07-12 2023-09-12 北京易控智驾科技有限公司 Vehicle control method and device and unmanned vehicle

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