CN114132344A - Decision-making method, device, equipment and storage medium for automatically driving vehicle - Google Patents

Decision-making method, device, equipment and storage medium for automatically driving vehicle Download PDF

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Publication number
CN114132344A
CN114132344A CN202111570643.6A CN202111570643A CN114132344A CN 114132344 A CN114132344 A CN 114132344A CN 202111570643 A CN202111570643 A CN 202111570643A CN 114132344 A CN114132344 A CN 114132344A
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target vehicle
distance
priority
vehicle
turning
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CN114132344B (en
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章桢
于宁
王星宇
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Apollo Zhixing Information Technology Nanjing Co ltd
Apollo Intelligent Connectivity Beijing Technology Co Ltd
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Apollo Zhixing Information Technology Nanjing Co ltd
Apollo Intelligent Connectivity Beijing 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
    • B60W60/0013—Planning or execution of driving tasks specially adapted for occupant comfort
    • 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
    • B60W60/0016—Planning or execution of driving tasks specially adapted for safety of the vehicle or its occupants
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/06—Direction of travel

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)

Abstract

The present disclosure provides a decision method, an apparatus, a device and a storage medium for automatically driving a vehicle, which relate to the technical field of computers, in particular to the technical fields of automatic driving, intelligent transportation and the like. The specific implementation scheme is as follows: determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior; determining the passing priority of the target vehicle based on the turning behavior and the turning progress; a driving decision is determined based on the traffic priority of the target vehicle.

Description

Decision-making method, device, equipment and storage medium for automatically driving vehicle
Technical Field
The present disclosure relates to the field of computer technology, and more particularly to the field of automatic driving, intelligent transportation, and the like.
Background
When the automatic driving vehicle runs, avoidance or rush-to-walk decision is usually made based on the level of the road right priority. In the case where the setting of the right-of-way priority is not reasonable, the host vehicle may make an unreasonable avoidance decision. Therefore, the efficiency of automatic driving is low, and the riding experience of a user is poor.
Therefore, how to reduce unreasonable avoidance in the automatic driving process and improve the riding experience of the user becomes a problem to be solved.
Disclosure of Invention
The disclosure provides a decision-making method, a decision-making device, equipment and a storage medium for an automatic driving vehicle.
According to an aspect of the present disclosure, there is provided a decision method of automatically driving a vehicle, which may include the steps of:
determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior;
determining the passing priority of the target vehicle based on the turning behavior and the turning progress;
a driving decision is determined based on the traffic priority of the target vehicle.
According to another aspect of the present disclosure, there is provided a decision making apparatus of an autonomous vehicle, the apparatus may include:
the state determination module is used for determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior;
the priority determination module is used for determining the passing priority of the target vehicle based on the turning behavior and the turning progress;
and the decision-making module is used for determining a driving decision based on the passing priority of the target vehicle.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method according to any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform a method in any of the embodiments of the present disclosure.
According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method in any of the embodiments of the present disclosure.
According to the technology disclosed by the invention, the passing priority of the target vehicle is determined based on the turning behavior and the turning progress of the target vehicle, and then the driving decision is made based on the passing priority, so that unreasonable avoidance is reduced on the premise of ensuring the safety, and the passing efficiency and the riding experience of a user are improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a flow chart of a decision method for automatically driving a vehicle according to the present disclosure;
FIG. 2 is a flow chart of a method of determining turn progress according to the present disclosure;
FIG. 3 is a schematic illustration of a target vehicle turning process according to the present disclosure;
FIG. 4 is a flow chart of a traffic priority adjustment method according to the present disclosure;
FIG. 5 is a flow chart of a driving decision adjustment method according to the present disclosure;
FIG. 6 is a flow chart diagram of a predictive trajectory adjustment method according to the present disclosure;
FIG. 7 is a block diagram of a decision-making device for an autonomous vehicle according to the present disclosure;
FIG. 8 is a block diagram of an electronic device for implementing a decision-making method for an autonomous vehicle according to an embodiment of the disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
As shown in fig. 1, the present disclosure relates to a decision method for an autonomous vehicle, which may include the steps of:
s101: determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior;
s102: determining the passing priority of the target vehicle based on the turning behavior and the turning progress;
s103: a driving decision is determined based on the traffic priority of the target vehicle.
The embodiment can be applied to computer equipment, and specifically can include a vehicle-mounted running computer or a server in communication connection with a vehicle.
The target vehicle may be an autonomous vehicle that may make aid decisions based on high-precision maps, on-board cameras, and on-board radar. For example, the automatic driving vehicle can shoot road conditions in front of the vehicle in real time based on the vehicle-mounted camera, and if intersections appear in shooting distance, decision of accelerating traffic or decelerating avoidance can be made based on data captured by equipment such as a vehicle-mounted radar. The intersection may be one of an intersection or a t-junction, and may be a single lane intersection or a multi-lane intersection, which is not limited herein.
After the target vehicle enters the intersection, the target vehicle can carry out running selection such as straight running or turning and the like based on a preset planning route. In the case where the target vehicle enters the intersection to start turning, the turning behavior includes one of left turning, right turning, and turning around.
The manner of determination of the turning behavior may be determined based on the current lane type. The current lane type is used to represent the lane type currently occupied by the target vehicle. For example, the target vehicle may determine the current lane based on lane line detection techniques. The current lane may be a left-turn lane, a right-turn lane, or a u-turn lane, and the like, which is not limited herein. Based on the current lane type, a turning behavior corresponding to the lane type may be determined.
The current turning behavior may also be determined based on the planned trajectory of the target vehicle. Specifically, the automatic driving vehicle may determine the turning behavior of the target vehicle at the next intersection based on the intelligent navigation technology, which is not described herein again.
The turning progress is used to indicate the degree of completion of the corresponding turning behavior, and the turning progress may be expressed by a percentage value, for example, the turning progress is 0, indicating that the target vehicle has not started turning; the turning progress is 50%, which represents that the turning action of the target vehicle is completed by half; the turn progress is 90%, indicating that the target vehicle has approached completion of the turn and the locomotive has been substantially directed toward the target lane.
Based on the turning behavior and the turning progress of the target vehicle, the passing priority of the target vehicle may be determined. For example, when the target vehicle turns left, the turning schedule has reached 90%, at which time the traffic priority of the target vehicle is high. When the target vehicle turns around, the turning progress exceeds 50%, and the passing priority of the target vehicle is high.
A driving decision is determined based on the traffic priority of the target vehicle. For example, when the passing priority is higher, the corresponding driving decision is to accelerate the passing; and when the passing priority is lower, the corresponding driving decision is deceleration and avoidance. Other driving strategies may also be set according to the need of automatic driving, which is not limited herein.
Through the process, the passing priority of the target vehicle is determined based on the turning behavior and the turning progress of the target vehicle, and then the driving decision is made based on the passing priority, so that unreasonable avoidance is reduced on the premise of ensuring safety, and the passing efficiency and the riding experience of a user are improved.
As shown in fig. 2, in one embodiment, the manner of determining the progress of the turn includes the following sub-steps:
s201: acquiring the current orientation of a target vehicle and the predicted driving road of the target vehicle;
s202: and determining the turning progress based on the current orientation and the included angle predicted to enter the road.
The current orientation may be a heading orientation of the target vehicle. For example, it may be the heading of the target vehicle relative to the geodetic coordinate system. The current orientation of the target vehicle may be acquired based on an on-board unit of the target vehicle.
The projected inbound path for the target vehicle may be determined based on a planned trajectory of the target vehicle. For example, the planned trajectory of the target vehicle at the next intersection is determined to be a left turn or a right turn based on the intelligent navigation, and the road after the left turn or the right turn at the next intersection can be taken as the predicted driving-in road.
After the target vehicle enters the intersection and starts turning behavior, an included angle is formed between the current orientation of the target vehicle and the predicted driving road. As the progress of turning of the target vehicle increases, the angle is continuously decreased until the orientation of the target vehicle is parallel to the expected incoming road, that is, the angle becomes 0.
When the turning progress is expressed by a percentage value, the turning progress may be calculated based on a ratio between the included angle and a preset included angle of the road.
As shown in fig. 3, the target vehicle makes a left turn at the illustrated intersection, where t is t0When the target vehicle does not start turning, the included angle between the current orientation of the target vehicle and the expected driving road is 90 degrees, and the turning progress is 0; at t ═ t1When the vehicle is in a state of turning left, the included angle between the current orientation of the target vehicle and the expected driving road is 45 degrees, namely the left turning of the target vehicle is half, and the turning progress is 50 percent; at t ═ t2The angle between the current orientation of the target vehicle and the expected approach to the road is 81 degrees, i.e., the left turn of the target vehicle is nearly completed, and the turn progress is 90%.
Through the process, the current turning progress of the target vehicle can be determined in real time based on the included angle between the current orientation of the target vehicle and the predicted driving-in reason, and then the passing priority of the target vehicle is determined in real time, so that a more reasonable driving decision is made.
As shown in fig. 4, in one embodiment, step 102 may include the following sub-steps:
s401: determining an initial priority corresponding to the turning behavior based on a preset corresponding relation;
s402: adjusting the initial priority based on the turning progress in the case where the target vehicle is in the first state; the first state is a state when the turning progress is larger than the progress threshold;
s403: and taking the adjustment result as the pass priority.
The preset correspondence may be a correspondence between turning behavior and initial priority. In the current traffic rules, the priority of straight going is 1 level, the left turn is 2 levels, the right turn is 3 levels, and the turn around is 4 levels. That is, the initial prioritization of different turning behaviors is: straight going > left turn > right turn > turn around. The preset correspondence may be reset as needed, which is not limited herein.
For example, when the target vehicle enters the intersection to prepare for turning left, the opposite obstacle vehicle passes through the intersection in a straight-going manner, and the passing priority corresponding to the left turning of the target vehicle is lower than the straight-going passing priority of the obstacle vehicle based on the current traffic rules, at this time, the target vehicle should select a driving strategy for deceleration and avoidance.
Under the conditions that the target vehicle turns right and the obstacle vehicle turns left, or the target vehicle turns around and the obstacle vehicle moves straight, and the like, the target vehicle makes different driving decisions based on the existing traffic rules, and the driving decisions are not exhaustive here.
For example, in the case where the target vehicle has started a left turn at the intersection, when the opposite obstacle vehicle is going straight through the intersection but is far from the intersection, the initial priority should be adjusted based on the turning progress of the target vehicle. In other cases where the initial priority is not reasonable, the initial priority should be adjusted, which is not exhaustive here.
Different turning schedules indicate that the target vehicle is in different turning states, and the turning states can be divided into a starting turning state, a turning-in state, an approaching completion state and the like, which are not exhaustive herein.
In the case where the target vehicle is in the first state, the initial priority is adjusted based on the degree of progress of turning. The first state is a state when the progress of the turn is greater than the progress threshold, for example, the first state may be an approach completion state or a turning state, which is not limited herein. Wherein, the progress threshold value can be correspondingly set according to different turning behaviors.
For example, the turn progress threshold may take 70% when the target vehicle makes a left turn at the intersection. That is, when the turning progress is greater than 70%, it indicates that the first state in which the target vehicle is located is a left-turning approach completion state, and at this time, the initial priority corresponding to the left-turning may be adjusted to the priority corresponding to the straight traveling.
When the target vehicle turns around, the turning progress threshold can be 50%, namely when the turning progress is greater than 50%, the turning action of the target vehicle is half, the head of the target vehicle is explored into a turning lane expected to be driven into, the corresponding first state is a turning approaching completion state, the opposite coming vehicle needs to be decelerated and avoided, the target vehicle can pass with higher speed, and the initial priority corresponding to turning can be adjusted to be the priority corresponding to straight-going.
The turning progress threshold value can also be 80%, 90% and the like according to different turning behaviors, and can be specifically set as required, and the turning progress threshold value is not limited here.
And taking the adjustment result of the initial priority as the passing priority of the target vehicle. For example, when the target vehicle turns left at the intersection, its initial priority is lower than that of the straight-ahead obstacle vehicle that is driving into the intersection on the opposite side. When the turning progress is larger than 70%, the initial priority of the target vehicle is adjusted to the priority corresponding to the straight-going, and the passing priority of the target vehicle and the passing priority of the obstacle vehicle are the same.
Of course, the adjusted passing priority of the target vehicle may also be lower or higher than the passing priority of the obstacle vehicle, and is not limited herein.
Through the process, under the condition that the turning progress of the target vehicle is close to completion, the passing priority of the target vehicle is increased, unreasonable avoidance to obstacle vehicles can be reduced, and therefore riding experience of a user is improved.
In one embodiment, step 102 may further include the sub-steps of:
taking the initial priority as the traffic priority under the condition that the target vehicle is in the second state; the second state is a state when the turning progress is not greater than the progress threshold.
The second state is also one of a plurality of turning states. For example, the second state may be a starting turning state or a turning state, which is not limited herein. Specifically, the second state may be a state when the turning progress is not greater than the progress threshold, and the value of the progress threshold is the same as above, which is not described herein again.
When the target vehicle is in the second state, which indicates that the turning behavior of the target vehicle has not reached a state close to completion, the initial priority is set as the traffic priority.
As shown in fig. 5, in one embodiment, step 103 may include the following sub-steps:
s501: adjusting the predicted trajectory line of the obstacle vehicle based on the traffic priority of the target vehicle;
s502: a driving decision is determined based on the adjustment of the predicted trajectory line.
The predicted trajectory line is a predicted line obtained by predicting the travel trajectory of another vehicle on the road by the target vehicle using a device such as an on-vehicle camera or an on-vehicle radar. The length of the predicted trajectory line may be adjusted as needed, for example, the predicted trajectory line may be shortened, the predicted trajectory line may be lengthened, and the like, which is not limited herein.
The obstacle vehicle may be a vehicle whose predicted trajectory line is likely to intersect the predicted trajectory of the target vehicle. For example, when the target vehicle passes through a road condition and plans to turn left, the predicted trajectory line of the straight-ahead vehicle of the oncoming lane may intersect with the predicted trajectory of the target vehicle, with the straight-ahead vehicle of the oncoming lane as the obstacle vehicle. The obstacle vehicles may be 1, 2, 3, etc., and are not limited thereto. When there are a plurality of obstacle vehicles, the target vehicle recognizes a corresponding predicted trajectory line for each obstacle vehicle, that is, obtains a plurality of predicted trajectory lines.
The target vehicle may make driving decisions based on the predicted trajectory line of the obstacle vehicle, e.g., the target vehicle elects to avoid in the event that the planned trajectory of the target vehicle intersects the predicted trajectory line determination of the obstacle vehicle.
In the present embodiment, the predicted trajectory line of the obstacle vehicle may be adjusted based on the traffic priority of the target vehicle. For example, in the case where the passing priority of the target vehicle with respect to the obstacle vehicle is high, the predicted trajectory line of the obstacle vehicle may be shortened; in the case where the passing priority of the target vehicle with respect to the obstacle vehicle is low, the predicted trajectory line of the obstacle vehicle can be extended.
The driving decision is determined based on the adjustment result of the predicted trajectory line, and the driving decision may be made based on whether the adjustment result of the predicted trajectory line intersects with the planned trajectory of the target vehicle. In the case of intersection, the target vehicle can choose to decelerate and avoid; in the non-intersection situation, the target vehicle may choose to pass normally or to pass at an accelerated speed, which is not limited herein.
Through the above process, the predicted trajectory line of the obstacle vehicle can be adjusted based on the traffic priority, so that the target vehicle makes an optimal driving decision. Therefore, unreasonable avoidance to the obstacle vehicle can be reduced, and riding experience of a user is improved.
As shown in fig. 6, in one embodiment, step 501 may include the following sub-steps:
s601: determining a predicted collision point of the target vehicle and the obstacle vehicle under the condition that the passing priority of the target vehicle is not higher than that of the obstacle vehicle;
s602: determining a first distance and a second distance based on the predicted location of the collision point; the first distance is used for representing the distance between the target vehicle and the predicted collision point; the second distance is used for representing the distance between the obstacle vehicle and the predicted collision point;
s603: based on the first distance and the second distance, a predicted trajectory line of the obstacle vehicle is adjusted.
The condition that the passing priority of the target vehicle is not higher than the passing priority of the obstacle vehicle may include that the obstacle vehicle moves straight and the target vehicle turns left when the target vehicle and the obstacle vehicle move in opposite directions and enter the intersection, or that the obstacle vehicle moves straight and the target vehicle turns around, the obstacle vehicle turns left and the target vehicle turns right, and the like, which are not exhaustive herein.
The predicted collision point may be a collision point between the planned trajectory of the target vehicle and the predicted trajectory line of the obstacle vehicle, which is predicted in a case where the target vehicle and the obstacle vehicle keep the current vehicle speed, and no acceleration pass or deceleration avoidance is performed.
Based on the predicted location of the collision point, a first distance and a second distance are determined. The first distance may be a distance between the current position of the target vehicle and the position of the predicted collision point, and the second distance may be a distance between the current position of the obstacle vehicle and the position of the predicted collision point.
The adjusting of the predicted trajectory line of the obstacle vehicle based on the first distance and the second distance may be adjusting the predicted trajectory line of the obstacle vehicle when the first distance and the second distance satisfy a preset condition.
The preset condition may be set based on consideration of security priority or traffic efficiency priority. In one embodiment, the preset condition may be that a difference value obtained by subtracting the first distance from the second distance is greater than a preset distance threshold, where the preset distance threshold may be 3 meters, 5 meters, 10 meters, and the like, where a larger value of the preset distance threshold is more prone to a safety-priority driving decision; otherwise, driving decisions with traffic efficiency priority tend to be favored. Preferably, the preset distance threshold is 5 meters, and when the first distance is 10 meters and the second distance is 20 meters, a difference obtained by subtracting the first distance from the second distance satisfies a preset condition, it may be determined that the target vehicle is closer to the predicted collision point than the obstacle vehicle, and thus the predicted trajectory of the obstacle vehicle may be adjusted.
The preset condition may also be that a ratio between the first distance and the second distance is smaller than a preset ratio threshold, where the preset ratio threshold may be 0.5, 0.6, 0.7, and the like, and is not limited herein. The smaller the value of the preset proportion threshold value is, the more the driving decision of safety priority is favored; otherwise, driving decisions with traffic efficiency priority tend to be favored. Preferably, the value of the preset proportion threshold may be 0.6, and under the condition that the first distance is 10 meters and the second distance is 20 meters, the ratio of the first distance to the second distance satisfies the preset condition, and at this time, it may also be determined that the target vehicle is closer to the predicted collision point relative to the obstacle vehicle, which is not described herein again.
In one embodiment, the predicted trajectory line of the obstacle vehicle is shortened in a case where the first distance and the second distance satisfy a preset condition. The predicted trajectory line of the obstacle vehicle may be shortened by a certain ratio or by a certain length, and may be specifically set as required, which is not limited herein. For example, the predicted trajectory line is shortened to 60%, 50%, 40%, etc., and the value of the shortening ratio is not limited. Or the predicted trajectory may be shortened by 20 meters, 15 meters, 10 meters, etc., which are not exhaustive here.
In the case where the first distance and the second distance do not satisfy the preset condition, the predicted trajectory line of the obstacle vehicle is maintained.
Through the above process, the first distance and the second distance can be determined based on the position of the predicted collision point in the case where the target vehicle is not higher than the passage priority of the obstacle vehicle, and the predicted trajectory line can be adjusted based on the relationship between the first distance and the second distance. Thus, the target vehicle may make driving decisions based on the predicted trajectory of the obstacle vehicle.
In one embodiment, the target vehicle accelerates through in the event that the traffic priority of the target vehicle is higher than the traffic priority of the obstacle vehicle.
As shown in fig. 7, the present disclosure relates to a decision making device of an autonomous vehicle, which may include:
a state determination module 701 for determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior;
a priority determination module 702 for determining a traffic priority of the target vehicle based on the turning behavior and the turning schedule;
a decision module 703 for determining a driving decision based on the traffic priority of the target vehicle.
In one embodiment, the determination of the progress of the turn includes:
acquiring the current orientation of a target vehicle and the predicted driving road of the target vehicle;
and determining the turning progress based on the current orientation and the included angle predicted to enter the road.
In one embodiment, the priority determination module includes:
the initial priority determining submodule is used for determining an initial priority corresponding to the turning behavior based on the preset corresponding relation;
the priority adjusting submodule is used for adjusting the initial priority based on the turning progress under the condition that the target vehicle is in the first state to obtain an adjusting result; the first state is a state when the turning progress is larger than the progress threshold;
and the first execution submodule of the pass priority is used for taking the adjustment result as the pass priority.
In one embodiment, the second execution submodule of the traffic priority is used for taking the initial priority as the traffic priority when the target vehicle is in the second state; the second state is a state when the turning progress is not greater than the progress threshold.
In one embodiment, a decision module comprises:
the predicted trajectory line adjusting submodule is used for adjusting the predicted trajectory line of the obstacle vehicle based on the passing priority of the target vehicle to obtain an adjusting result of the predicted trajectory line;
a first decision making sub-module for determining a driving decision based on the adjustment of the predicted trajectory line in one embodiment, the predicted trajectory line adjustment sub-module includes:
a collision point prediction submodule for determining a predicted collision point of the target vehicle and the obstacle vehicle, in a case where the passage priority of the target vehicle is not higher than the passage priority of the obstacle vehicle;
a distance prediction sub-module for determining a first distance and a second distance based on the predicted location of the collision point; the first distance is used for representing the distance between the target vehicle and the predicted collision point; the second distance is used for representing the distance between the obstacle vehicle and the predicted collision point;
a predicted trajectory line adjustment submodule for adjusting the predicted trajectory line of the obstacle vehicle based on the first distance and the second distance.
In one embodiment, the predicted trajectory line adjustment submodule is further configured to shorten the predicted trajectory line of the obstacle vehicle if the first distance is less than the second distance.
In one embodiment, the predicted trajectory line adjustment submodule is further operable to maintain the predicted trajectory line of the obstacle vehicle if the first distance is not less than the second distance.
In one embodiment, the decision-making device for an autonomous vehicle further comprises:
and the second decision execution submodule is used for accelerating the target vehicle to pass through under the condition that the passing priority of the target vehicle is higher than that of the obstacle vehicle.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 8 illustrates a schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 8, the apparatus 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
A number of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
Computing unit 801 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and the like. The computing unit 801 performs the various methods and processes described above, such as decision-making methods for autonomous driving of a vehicle. For example, in some embodiments, the decision-making method of autonomous driving a vehicle may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto device 800 via ROM 802 and/or communications unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the above described decision method of autonomous driving a vehicle may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured by any other suitable means (e.g., by means of firmware) to perform the method of decision making of an autonomous vehicle.
Various implementations of the systems and techniques described here above may be implemented 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 disclosure 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 server.
In the context of this disclosure, 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 machine-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 server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
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 detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims (21)

1. A decision-making method for automatically driving a vehicle, comprising:
determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior;
determining a traffic priority of the target vehicle based on the turning behavior and the turning progress;
determining a driving decision based on the traffic priority of the target vehicle.
2. The method of claim 1, wherein the determination of the progress of the turn comprises:
acquiring the current orientation of the target vehicle and the predicted driving road of the target vehicle;
and determining the turning progress based on the included angle between the current orientation and the predicted entering road.
3. The method of claim 1, wherein the determining a traffic priority of the target vehicle based on the turning behavior and the turning progress comprises:
determining an initial priority corresponding to the turning behavior based on a preset corresponding relation;
under the condition that the target vehicle is in a first state, adjusting the initial priority based on the turning progress to obtain an adjustment result; the first state is a state when the turning progress is greater than a progress threshold;
and taking the adjustment result as the pass priority.
4. The method of claim 3, further comprising:
taking the initial priority as the traffic priority if the target vehicle is in a second state; the second state is a state when the turning progress is not greater than the progress threshold.
5. The method of claim 1, wherein the determining a driving decision based on the traffic priority of the target vehicle comprises:
adjusting the predicted track line of the obstacle vehicle based on the passing priority of the target vehicle to obtain an adjustment result of the predicted track line;
determining a driving decision based on the adjustment of the predicted trajectory line.
6. The method of claim 5, wherein said adjusting a predicted trajectory line of an obstacle vehicle based on a traffic priority of the target vehicle comprises:
determining a predicted collision point of the target vehicle with an obstacle vehicle if the traffic priority of the target vehicle is not higher than the traffic priority of the obstacle vehicle;
determining a first distance and a second distance based on the location of the predicted collision point; the first distance is used to represent the distance of the target vehicle from the predicted collision point; the second distance is used to represent a distance of the obstacle vehicle from the predicted collision point;
adjusting a predicted trajectory line of the obstacle vehicle based on the first distance and the second distance.
7. The method of claim 6, the adjusting the predicted trajectory line of the obstacle vehicle based on the first distance and the second distance, comprising:
shortening the predicted trajectory line of the obstacle vehicle if the first distance is less than the second distance.
8. The method of claim 6, the adjusting the predicted trajectory line of the obstacle vehicle based on the first distance and the second distance, comprising:
maintaining a predicted trajectory line of the obstacle vehicle if the first distance is not less than the second distance.
9. The method of any of claims 1-8, further comprising:
in the case where the passage priority of the target vehicle is higher than that of the obstacle vehicle, the target vehicle accelerates to pass.
10. A decision-making device for an autonomous vehicle, comprising:
the state determination module is used for determining the turning behavior and the turning progress of the target vehicle; the turning progress is used for representing the completion degree of the turning behavior;
a priority determination module for determining a traffic priority of the target vehicle based on the turning behavior and the turning progress;
a decision module to determine a driving decision based on the traffic priority of the target vehicle.
11. The apparatus of claim 10, wherein the determination of the progress of the turn comprises:
acquiring the current orientation of the target vehicle and the predicted driving road of the target vehicle;
and determining the turning progress based on the included angle between the current orientation and the predicted entering road.
12. The apparatus of claim 11, wherein the priority determination module comprises:
the initial priority determining submodule is used for determining the initial priority corresponding to the turning behavior based on a preset corresponding relation;
the priority adjusting submodule is used for adjusting the initial priority based on the turning progress under the condition that the target vehicle is in a first state to obtain an adjusting result; the first state is a state when the turning progress is greater than a progress threshold;
and the first execution submodule of the pass priority is used for taking the adjustment result as the pass priority.
13. The apparatus of claim 12, further comprising:
a second execution submodule of the passage priority, which is used for taking the initial priority as the passage priority under the condition that the target vehicle is in a second state; the second state is a state when the turning progress is not greater than the progress threshold.
14. The apparatus of claim 10, wherein the decision module comprises:
the predicted trajectory line adjusting submodule is used for adjusting the predicted trajectory line of the obstacle vehicle based on the passing priority of the target vehicle to obtain an adjusting result of the predicted trajectory line;
a first decision execution sub-module for determining a driving decision based on the adjustment of the predicted trajectory line.
15. The apparatus of claim 14, wherein the predicted trajectory adjustment sub-module comprises:
a collision point prediction sub-module for determining a predicted collision point of the target vehicle with the obstacle vehicle, in a case where a passage priority of the target vehicle is not higher than a passage priority of the obstacle vehicle;
a distance prediction sub-module for determining a first distance and a second distance based on the location of the predicted collision point; the first distance is used to represent the distance of the target vehicle from the predicted collision point; the second distance is used to represent a distance of the obstacle vehicle from the predicted collision point;
a predicted trajectory line adjustment submodule for adjusting a predicted trajectory line of the obstacle vehicle based on the first distance and the second distance.
16. The apparatus of claim 15, the predicted trajectory line adjustment sub-module further to shorten the predicted trajectory line of the obstacle vehicle if the first distance is less than the second distance.
17. The apparatus of claim 15, the predicted trajectory line adjustment sub-module further to maintain the predicted trajectory line of the obstacle vehicle if the first distance is not less than the second distance.
18. The apparatus of any of claims 10-17, further comprising:
and the second decision execution submodule is used for accelerating the target vehicle to pass through under the condition that the passing priority of the target vehicle is higher than that of the obstacle vehicle.
19. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.
20. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-9.
21. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-9.
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