An autonomous driving lane-changing decision-making method, device, equipment, and storage medium

Abstract

This invention discloses an autonomous driving lane-changing decision-making method, apparatus, device, and storage medium. The method includes: acquiring first driving data of a target vehicle and corresponding road information within a target area; determining lane-changing information based on the road information and the first driving data; wherein the lane-changing information includes a target lane-changing road; acquiring obstacle information within a sub-area corresponding to the target lane-changing road in the target area; and determining a lane-changing decision for the target vehicle based on the obstacle information; wherein the target lane-changing decision includes executing a lane change or stopping a lane change. Using this method, by combining current road information and obstacle information, the optimal lane-changing timing is determined based on the obstacle information, reducing the occurrence of repeated lane changes.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to an autonomous driving lane-changing decision-making method, apparatus, device and storage medium. Background Technology

[0002] Autonomous driving is an extremely complex systems engineering project, and decision planning is one of its key components, its core being to solve the problem of how the vehicle should move. It first integrates information from multiple sensors, and then makes task decisions based on driving needs. Intelligent vehicles generate the desired path based on various parameters input from sensors and provide the corresponding control quantities to subsequent controllers. Therefore, decision planning and expectation is an important research area, determining whether the vehicle can smoothly and accurately complete various driving behaviors during operation.

[0003] Lane-changing decision-making and planning refers to the process by which a vehicle, in order to gain a speed advantage or due to driving needs, comprehensively considers factors such as its own position, speed, and acceleration as well as those of surrounding vehicles, to calculate its spatiotemporal trajectory within a given future timeframe to ensure the smooth and safe execution of lane-changing actions. Generally, the lane-changing process consists of four stages: information perception, behavioral decision-making, trajectory planning, and control execution. Currently, rule-based lane-changing behavioral decision-making suffers from shortcomings in terms of safety when making lane-changing decisions. Summary of the Invention

[0004] This invention provides an autonomous driving lane-changing decision-making method, device, equipment, and storage medium. By combining current road information and obstacle information, the optimal lane-changing timing is determined based on the obstacle information, thereby reducing the occurrence of repeated lane changes.

[0005] In a first aspect, embodiments of the present invention provide an autonomous driving lane-changing decision-making method, the method comprising:

[0006] Acquire the initial driving data of the target vehicle and the corresponding road information within the target area;

[0007] Lane change information is determined based on the road information and the first driving data; wherein, the lane change information includes the target lane change road;

[0008] Obtain obstacle information within the sub-region corresponding to the target lane change route in the target region;

[0009] The lane-changing decision for the target vehicle is determined based on the obstacle information; wherein, the target lane-changing decision includes executing the lane change or stopping the lane change.

[0010] Secondly, embodiments of the present invention also provide an autonomous driving lane-changing decision-making device, the device comprising:

[0011] The first acquisition module is used to acquire the first driving data of the target vehicle and the corresponding road information within the target area;

[0012] The lane change information determination module is used to determine lane change information based on the road information and the first driving data; wherein, the lane change information includes the target lane change road;

[0013] The second acquisition module is used to acquire obstacle information in the sub-region corresponding to the target lane change road in the target region;

[0014] The lane change decision determination module is used to determine the lane change decision of the target vehicle based on the obstacle information; wherein, the target lane change decision includes executing the lane change or stopping the lane change.

[0015] Thirdly, embodiments of this disclosure also provide an electronic device, the electronic device comprising:

[0016] One or more processors;

[0017] Storage device for storing one or more programs.

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the autonomous driving lane-changing decision method provided in the embodiments of this disclosure.

[0019] Fourthly, embodiments of this disclosure also provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to implement the autonomous driving lane-changing decision-making method provided in embodiments of this disclosure.

[0020] This invention discloses an autonomous driving lane-changing decision-making method, apparatus, device, and storage medium. The method includes: acquiring first driving data of a target vehicle and corresponding road information within a target area; determining lane-changing information based on the road information and the first driving data; wherein the lane-changing information includes a target lane-changing road; acquiring obstacle information within a sub-area corresponding to the target lane-changing road in the target area; and determining a lane-changing decision for the target vehicle based on the obstacle information; wherein the target lane-changing decision includes executing a lane change or stopping a lane change. Using this method, by combining current road information and obstacle information, the optimal lane-changing timing is determined based on the obstacle information, reducing the occurrence of repeated lane changes. Attached Figure Description

[0021] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0022] Figure 1 A flowchart of an autonomous driving lane-changing decision-making method provided in an embodiment of this disclosure;

[0023] Figure 2 A schematic diagram of a vehicle decision-making method for an autonomous driving lane-changing decision-making method provided in an embodiment of this disclosure;

[0024] Figure 3 A schematic diagram of a stationary obstacle decision-making method for an autonomous driving lane-changing decision-making method provided in this embodiment of the present disclosure;

[0025] Figure 4 This is a schematic diagram of the structure of an autonomous driving lane-changing decision-making device provided in an embodiment of the present disclosure;

[0026] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0027] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0028] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0029] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0030] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0031] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0032] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0033] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0034] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0035] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0036] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0037] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0038] Example 1

[0039] Figure 1 This is a flowchart of an autonomous driving lane-changing decision provided in an embodiment of the present disclosure. This embodiment of the present disclosure is applicable to situations where autonomous driving lane-changing decisions are provided to users. The method can be executed by an autonomous driving lane-changing decision device, which can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, such as a mobile terminal, a PC, or a server.

[0040] like Figure 1As shown in the embodiments of this disclosure, an autonomous driving lane-changing decision-making method may specifically include the following steps:

[0041] S110. Obtain the first driving data of the target vehicle and the corresponding road information within the target area.

[0042] In this embodiment, the target vehicle can be a currently autonomous vehicle. The first driving data can be its driving speed and its current location. In practical applications, the driving speed of the target vehicle can be obtained using a speed sensor installed on the target vehicle, and its current location can be obtained using a positioning device on the target vehicle. The target area can be a rectangular area formed by moving from 50m behind the target vehicle to 100m ahead, with the target vehicle as the center, and the width of each lane on the left and right sides as a set multiple. The set multiple can be arbitrarily selected between 2 and 4 times. The road information can include information about each lane in the road, the status of each lane (left turn, right turn, or straight), and areas where lane changes are permitted.

[0043] Specifically, once the target vehicle determines its starting and ending points, an algorithm calculates a globally optimal path as the current vehicle's route. The algorithm also acquires the target vehicle's initial driving data and road information within the target area corresponding to that vehicle.

[0044] S120, Determine lane change information based on road information and initial driving data;

[0045] The lane change information includes the target lane change route.

[0046] In this embodiment, the lane change information can be the specific road that the target vehicle wants to change to and the starting position of the lane change. The lane change information may include the target lane change road.

[0047] Specifically, based on the road information within the target area corresponding to the first driving data of the target vehicle, and according to the path determined by the target vehicle and the lane status (left turn, right turn, and lane change allowed) in the road information within the target area, a route to be traveled in that target area is generated. The travel route may include lane change information for the vehicle.

[0048] Optionally, the lane change information may also include the lane change starting point; before determining the lane change information based on road information and first driving data, it may also include: activating the turn signal at a position at a first set distance from the lane change starting point.

[0049] In this embodiment, the lane-changing starting point can be the starting position where the target vehicle begins to change lanes. The first preset distance can be a pre-set distance threshold between the target vehicle and the lane-changing starting point. For example, 15 meters.

[0050] Specifically, the system determines when the target vehicle will activate its turn signal at a predetermined distance from the lane change starting point.

[0051] In this embodiment, by activating the turn signal in advance, the driver can promptly inform the following vehicle of their intention to change lanes, thus reducing the need for repeated lane changes.

[0052] S130. Obtain obstacle information within the sub-region corresponding to the target lane change road in the target region.

[0053] In this embodiment, the sub-region can be the sub-rectangular region where the target lane-changing road is located within the aforementioned target rectangular region. This sub-region can have a length of 150m and a width equal to the lane width of the target lane-changing road, and is located within the area of ​​the target lane-changing road. The obstacle information includes the obstacle type, the distance between the obstacle and the target vehicle, and their relative speed. The obstacle types include: motor vehicles, non-motor vehicles, pedestrians, and static obstacles. The distance can include both forward and backward distances.

[0054] Specifically, it acquires information on all obstacles within the sub-region corresponding to the target lane change route in the target area, including obstacle type, distance between the obstacle and the target vehicle, and relative speed.

[0055] In practical applications, the cameras and radar installed on this vehicle can be used to obtain information about obstacles. For details, please refer to the mature solutions in the existing technology, which will not be elaborated here.

[0056] S140. Determine the lane-changing decision of the target vehicle based on obstacle information; wherein, the target lane-changing decision includes executing the lane change or stopping the lane change.

[0057] In this embodiment, the lane-changing decision can be a decision on whether the target vehicle should perform a lane change. Specifically, the target lane-changing decision can include performing a lane change or stopping the lane change.

[0058] Specifically, firstly, different priorities are assigned to obstacle types, and the method for determining lane-changing decisions differs for different obstacle types. Based on the priority of obstacle type, at least one target obstacle in the obstacle information is sorted from high to low to form a sequence. For each target obstacle in the sequence, a lane-changing decision is determined sequentially. If the lane-changing decision is to execute a lane change, the process continues to the next target obstacle. If the lane-changing decision is to stop lane changing, the process stops, and the vehicle is controlled to execute a lane-changing stop operation.

[0059] In practical applications, during the autonomous driving process, vehicles use a certain time interval as a judgment cycle. If the lane-changing decision in the previous judgment cycle was to stop lane changing, then the vehicle can continue to make lane-changing decisions in the next cycle until the lane change is completed.

[0060] Optionally, the method for determining the lane-changing decision of the target vehicle based on obstacle information can be as follows: sorting at least one target obstacle contained in the obstacle information according to the priority of obstacle type; traversing at least one target obstacle according to the sorting result; determining the lane-changing decision of the target obstacle based on the traversed target obstacle; if the lane-changing decision is to execute lane changing, then continuing to traverse the next target obstacle; if the lane-changing decision is to stop lane changing, then stopping traversal and controlling the vehicle to execute the stop lane-changing operation.

[0061] In this embodiment, the priority of obstacle types can be preset. For example, in this invention, the priority of obstacle types from high to low can be: motor vehicles, pedestrians, non-motor vehicles and static obstacles.

[0062] Specifically, firstly, the target obstacles in the obstacle information are sorted from high to low according to the priority of the set obstacle types. The obstacle information contains at least one target obstacle. The system then iterates through the target obstacles according to the sorting results, determining a lane-changing decision for each target obstacle encountered. If the lane-changing decision for that target obstacle is to execute a lane change, the system continues to traverse the next target obstacle according to the sorting results. If the lane-changing decision is to stop changing lanes, the traversal stops, and the vehicle is controlled to execute a lane-changing stop operation.

[0063] In this embodiment, by making personalized strategy judgments for different obstacle types, the optimal lane-changing timing is determined, reducing the occurrence of repeated lane-changing situations.

[0064] Optionally, the lane-changing decision based on the traversed target obstacle can be as follows: if the type of the traversed target obstacle is a motor vehicle, then the first collision time is determined based on the first driving data and obstacle information within multiple cycles; if the first collision time is greater than the first threshold in each cycle, then the lane-changing decision is to execute the lane change; if the first collision time is less than or equal to the first threshold in one or more cycles of multiple cycles, then the lane-changing decision is to stop the lane change.

[0065] In this embodiment, Figure 2 This diagram illustrates a vehicle decision-making process according to an embodiment of the autonomous driving lane-changing decision-making method provided in this disclosure. In practical applications, during autonomous driving, the vehicle uses a certain time interval as a judgment cycle. The first threshold can be a set threshold related to the lane-changing duration of the target vehicle; it can be the sum of the lane-changing duration and a set duration. For example, if the lane-changing duration of the target vehicle is 5 seconds, then the first threshold can be set to 7 seconds. Figure 2 As shown, the first collision time can be the time required for two objects to collide. When the target vehicle is behind and the obstacle is in front, the collision time is calculated using the following formula:

[0066] TTC obs_back_to_ego_front =-(S obs_back -S ego_front ) / (V obs -V ego )

[0067] When the target vehicle is in front and the obstacle is behind, the collision time is calculated using the following formula:

[0068] TTC obs_front_to_ego_back =-(S obs_front -S ego_back ) / (V obs -V ego )

[0069] Where TTC is the collision time, obs is the obstacle, ego is the target vehicle, back is the rear of the vehicle, front is the front of the vehicle, S is the value of the object in the Frenet coordinate system, and V is the velocity of the obstacle.

[0070] Specifically, if the target obstacle encountered is a motor vehicle, the collision time can be calculated using a formula across multiple cycles based on the aforementioned first driving data and obstacle information. The formula selection can be based on the positional relationship between the target vehicle and the obstacle to determine the first collision time. If the first collision time is greater than a first threshold in each cycle, the lane-changing decision is to execute a lane change. If the first collision time is less than or equal to the first threshold in one or more cycles across multiple cycles, the lane-changing decision is to stop the lane change. The number of cycles can be set according to actual conditions; for example, two cycles can be selected.

[0071] Optionally, the lane-changing decision based on the traversed target obstacle can be determined as follows: if the type of the traversed target obstacle is a pedestrian, then the lane-changing decision is determined based on the distance between the pedestrian and the target vehicle.

[0072] Specifically, if the target obstacle type encountered is a pedestrian, the lane-changing decision is to execute the lane change if the forward distance between the pedestrian and the target vehicle is greater than a set distance threshold, or if the backward distance is greater than a set threshold. The lane-changing decision is to stop the lane change if the forward distance between the pedestrian and the target vehicle is less than or equal to the set distance threshold and the backward distance is also less than or equal to the set distance threshold. The aforementioned set distance thresholds can be set according to actual conditions; the forward distance threshold can be greater than the backward distance threshold.

[0073] Optionally, the method for determining the lane-changing decision based on the traversed target obstacle can be as follows: If the type of the traversed target obstacle is a non-motorized vehicle, the lane-changing decision is to execute the lane change when the non-motorized vehicle meets any of the following conditions: the forward distance between the non-motorized vehicle and the target vehicle is greater than a second threshold or the backward distance is greater than a third threshold; or, if the non-motorized vehicle is located in the first set edge area of ​​the target lane-changing road; when the forward distance between the non-motorized vehicle and the target vehicle is less than or equal to the second threshold and the backward distance is less than or equal to the third threshold, a second collision time is determined based on the first driving data and obstacle information; wherein, the third threshold is less than the second threshold; if the second collision time is greater than the fourth threshold, the lane-changing decision is to execute the lane change.

[0074] In this embodiment, the second and third thresholds can be pre-set thresholds, and the specific setting rules can be related to vehicle speed, wherein the third threshold is less than the second threshold. For example, the second threshold can be a forward distance to the target vehicle equal to the distance traveled at the current speed for 5 seconds, and the third threshold can be a backward distance to the target vehicle equal to the distance traveled at the current speed for 2 seconds. The first defined edge region can be a rectangular area formed by half the width of the target lane away from the target lane, wherein the first defined edge region is within the aforementioned target area. The fourth threshold can be a set threshold related to the lane-changing time of the target vehicle; it can be the sum of the lane-changing time and a set time, and the fourth threshold can be equal to the first threshold. The second collision time can be the time required for two objects to collide, and the specific calculation formula is the same as the first collision time.

[0075] Specifically, if the target obstacle encountered is a non-motorized vehicle, the lane-changing decision is to execute the lane change if the non-motorized vehicle meets any of the following conditions: the forward distance between the non-motorized vehicle and the target vehicle is greater than a second threshold or the backward distance is greater than a third threshold; or, if the non-motorized vehicle expands its width by half towards the target vehicle based on its lateral position information, and this position is still within the first defined edge area of ​​the target lane-changing road; or if the forward distance between the non-motorized vehicle and the target vehicle is less than or equal to the second threshold and the backward distance is less than or equal to the third threshold, a second collision time is determined based on the first driving data and obstacle information. If the second collision time is greater than a fourth threshold, the lane-changing decision is to execute the lane change. If the non-motorized vehicle does not meet any of the above conditions, the lane-changing decision is to stop the lane change.

[0076] Optionally, the method for determining the lane-changing decision based on the traversed target obstacles can be as follows: If the traversed target obstacle type is a stationary obstacle, then if the stationary obstacle is located in the second set edge area of ​​the target lane-changing road or behind the target vehicle, the determined lane-changing decision is to execute a lane change; if the stationary obstacle is not located in the second set edge area of ​​the target lane-changing road but is located in front of the target vehicle, the lengths of the reference line in front of the obstacle and the reference line behind the obstacle are determined based on the obstacle information; if the length of the reference line in front is greater than the length of the reference line behind the obstacle and the length of the reference line in front is greater than the lane-changing distance, or the difference between the planned endpoint position and the head position of the obstacle is less than the lane-changing distance threshold, then the lane-changing method is to execute the lane-changing decision in front of the stationary obstacle; if the length of the reference line in front is less than or equal to the length of the reference line behind the obstacle or the length of the reference line in front is less than or equal to the lane-changing distance, and the difference between the planned endpoint position and the head position of the obstacle is greater than the lane-changing distance threshold, then the lane-changing method is to execute the lane-changing decision behind the stationary obstacle.

[0077] In this embodiment, the length of the forward reference line can be the distance at which the target vehicle can change lanes in front of the obstacle. The forward reference line length is equal to the total length of the set reference lines minus the head position of the stationary obstacle. The total length of the set reference lines can be 150m, or it can be set according to actual conditions. The length of the rear reference line can be the distance at which the target vehicle can change lanes behind the obstacle. The rear reference line length is equal to the tail position of the stationary obstacle minus the head position of the target vehicle. The lane-changing distance threshold can be the minimum distance required for the vehicle to change lanes. This threshold is related to the vehicle speed and can be set to the distance traveled forward for 5 seconds at the current speed. The planned endpoint position can be the set endpoint position of the target vehicle distance. The second set edge region can be set in the same way as the first set edge region described above.

[0078] Specifically, Figure 3 This is a schematic diagram illustrating a stationary obstacle decision-making method for an autonomous driving lane-changing decision-making method provided in an embodiment of this disclosure. Figure 3As shown, ego represents the target vehicle, and obs represents stationary obstacles. If the target obstacle encountered is a stationary obstacle, and the stationary obstacle is located in the second predetermined edge area of ​​the target lane change route or behind the target vehicle, then the stationary obstacle is ignored, and the lane change decision is to execute the lane change. If the stationary obstacle is not located in the second predetermined edge area of ​​the target lane change route but is in front of the target vehicle, the lengths of the front and rear reference lines of the obstacle are determined based on the obstacle information and the calculation method of the lengths of the front and rear reference lines of the obstacle. Then, the lengths of the front and rear reference lines are compared. If the length of the front reference line is greater than the length of the rear reference line and the length of the front reference line is greater than the lane change distance, then the lane change method is to execute the lane change decision in front of the stationary obstacle. Alternatively, if the difference between the planned endpoint position and the head position of the obstacle is less than the lane change distance threshold, then the lane change method is to execute the lane change decision in front of the stationary obstacle. If the length of the forward reference line is less than or equal to the length of the rear reference line, or the length of the forward reference line is less than or equal to the lane change distance, and the difference between the planned endpoint position and the head position of the obstacle is greater than the lane change distance threshold, then the lane change method is to execute the lane change decision behind the stationary obstacle.

[0079] This invention discloses an autonomous driving lane-changing decision-making method. The method includes: acquiring first driving data of a target vehicle and corresponding road information within a target area; determining lane-changing information based on the road information and the first driving data; wherein the lane-changing information includes a target lane-changing road; acquiring obstacle information within a sub-area corresponding to the target lane-changing road in the target area; and determining a lane-changing decision for the target vehicle based on the obstacle information; wherein the target lane-changing decision includes executing a lane change or stopping a lane change. Using this method, by combining current road information and obstacle information, the optimal lane-changing timing is determined based on the obstacle information, reducing the occurrence of repeated lane changes.

[0080] Example 2

[0081] Figure 4 The present invention also provides a schematic diagram of an autonomous driving lane-changing decision-making device, as shown in the embodiment of the invention. Figure 4 As shown, the device includes: a first acquisition module 210, a lane change information determination module 220, a second acquisition module 230, and a lane change decision determination module 240.

[0082] The first acquisition module 210 is used to acquire the first driving data of the target vehicle and the corresponding road information within the target area;

[0083] Lane change information determination module 220 is used to determine lane change information based on the road information and the first driving data; wherein, the lane change information includes the target lane change road;

[0084] The second acquisition module 230 is used to acquire obstacle information in the sub-region corresponding to the target lane change road in the target region;

[0085] The lane change decision determination module 240 is used to determine the lane change decision of the target vehicle based on the obstacle information; wherein, the target lane change decision includes executing the lane change or stopping the lane change.

[0086] The technical solution provided in this disclosure uses this method to combine current road information and obstacle information, and determines the optimal lane-changing time based on the obstacle information, thereby reducing the occurrence of repeated lane-changing situations.

[0087] Furthermore, the device also includes a turn signal activation module.

[0088] Turn signal activation module: used to activate the turn signal at a first predetermined distance from the lane change starting point.

[0089] Furthermore, the second acquisition module 230 can be used for:

[0090] The obstacle information includes the obstacle type, the distance between the obstacle and the target vehicle, and the relative speed; wherein, the obstacle type includes: motor vehicles, non-motor vehicles, pedestrians, and static obstacles.

[0091] Furthermore, the lane change decision determination module 240 can also be used for:

[0092] The obstacle information is sorted based on the priority of the obstacle type; at least one target obstacle is included in the obstacle information.

[0093] Traverse the at least one target obstacle according to the sorting result;

[0094] Determine the lane-changing decision for the target obstacle based on the traversed target obstacles;

[0095] If the lane-changing decision is to execute a lane change, then continue traversing the next target obstacle;

[0096] If the lane-changing decision is to stop lane changing, then stop traversing and control the vehicle to perform the stop lane-changing operation.

[0097] Furthermore, the lane change decision determination module 240 can be used for:

[0098] If the type of target obstacle encountered is a motor vehicle, the first collision time is determined based on the first driving data and the obstacle information within multiple cycles.

[0099] If the first collision time is greater than the first threshold in each cycle, the lane-changing decision is to execute a lane change.

[0100] If the first collision time is less than or equal to the first threshold in one or more of the plurality of cycles, the lane-changing decision is to stop the lane change.

[0101] Furthermore, the lane change decision determination module 240 can also be used for:

[0102] If the target obstacle encountered is a pedestrian, a lane-changing decision is determined based on the distance between the pedestrian and the target vehicle.

[0103] Furthermore, the lane change decision determination module 240 can also be used for:

[0104] If the target obstacle encountered is a non-motorized vehicle, the lane-changing decision is to execute the lane change if the non-motorized vehicle meets any of the following conditions:

[0105] The forward distance between the non-motorized vehicle and the target vehicle is greater than a second threshold or the backward distance is greater than a third threshold; or, if the non-motorized vehicle is located in the first defined edge area of ​​the target lane-changing road;

[0106] If the forward distance between the non-motorized vehicle and the target vehicle is less than or equal to a second threshold and the backward distance is less than or equal to a third threshold, a second collision time is determined based on the first driving data and the obstacle information; wherein the third threshold is less than the second threshold.

[0107] If the second collision time is greater than the fourth threshold, the determined lane-changing decision is to execute the lane change.

[0108] Furthermore, the lane change decision determination module 240 can also be used for:

[0109] If the target obstacle encountered is a stationary obstacle, then if the stationary obstacle is located in the second defined edge area of ​​the target lane change road or behind the target vehicle, the determined lane change decision is to execute the lane change.

[0110] When the static obstacle is not located in the second defined edge area of ​​the target lane change road but is located in front of the target vehicle, the length of the reference line in front of the obstacle and the length of the reference line behind the obstacle are determined based on the obstacle information;

[0111] If the length of the forward reference line is greater than the length of the rear reference line and the length of the forward reference line is greater than the lane change distance, or if the difference between the planned endpoint position and the head position of the obstacle is less than the lane change distance threshold, then the lane change method is to make a lane change decision in front of the stationary obstacle.

[0112] If the length of the forward reference line is less than or equal to the length of the rear reference line, or the length of the forward reference line is less than or equal to the lane change distance, and the difference between the planned endpoint position and the head position of the obstacle is greater than the lane change distance threshold, then the lane change method is to execute the lane change decision behind the stationary obstacle.

[0113] The above-described apparatus can execute the methods provided in all the foregoing embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the above methods. Technical details not described in detail in this embodiment can be found in the methods provided in all the foregoing embodiments of the present invention.

[0114] Example 3

[0115] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement embodiments of the present invention is provided. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0116] like Figure 5 The electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0117] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0118] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as autonomous driving lane-changing decision-making methods.

[0119] In some embodiments, the autonomous driving lane-changing decision-making method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the autonomous driving lane-changing decision-making method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the autonomous driving lane-changing decision-making method by any other suitable means (e.g., by means of firmware).

[0120] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0121] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0122] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0123] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the 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 can be received in any form (including sound input, voice input, or tactile input).

[0124] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0125] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0126] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0127] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An autonomous driving lane-changing decision-making method, characterized in that, include: Acquire the initial driving data of the target vehicle and the corresponding road information within the target area; Lane change information is determined based on the road information and the first driving data; wherein, the lane change information includes the target lane change road; Obtain obstacle information within the sub-region corresponding to the target lane change route in the target region; The lane-changing decision for the target vehicle is determined based on the obstacle information; wherein, the target lane-changing decision includes executing the lane change or stopping the lane change; the obstacle information includes the obstacle type, the distance between the obstacle and the target vehicle, and the relative speed; wherein, the obstacle type includes: motor vehicles, non-motor vehicles, pedestrians, and static obstacles; The step of determining the lane-changing decision of the target vehicle based on the obstacle information includes: The obstacle information is sorted based on the priority of the obstacle type; at least one target obstacle is included in the obstacle information. Traverse the at least one target obstacle according to the sorting result; Determine the lane-changing decision for the target obstacle based on the traversed target obstacles; If the lane-changing decision is to execute a lane change, then continue traversing the next target obstacle; If the lane-changing decision is to stop lane changing, then stop traversing and control the vehicle to perform the stop lane-changing operation; The step of determining the lane-changing decision for the target obstacle based on the traversed target obstacles includes: If the target obstacle encountered is a non-motorized vehicle, the lane-changing decision is to execute the lane change if the non-motorized vehicle meets any of the following conditions: The forward distance between the non-motorized vehicle and the target vehicle is greater than a second threshold or the backward distance is greater than a third threshold; or, if the non-motorized vehicle is located in the first defined edge area of ​​the target lane-changing road; If the forward distance between the non-motorized vehicle and the target vehicle is less than or equal to a second threshold and the backward distance is less than or equal to a third threshold, a second collision time is determined based on the first driving data and the obstacle information; wherein the third threshold is less than the second threshold. If the second collision time is greater than the fourth threshold, the determined lane-changing decision is to execute the lane change.

2. The method according to claim 1, characterized in that, The lane-change information also includes the lane-change starting point; before determining the lane-change information based on the road information and the first driving data, it also includes: Turn on the turn signal at a position at a first predetermined distance from the starting point of the lane change.

3. The method according to claim 1, characterized in that, Determining the lane-changing decision for the target obstacle based on the traversed target obstacles further includes: If the type of target obstacle encountered is a motor vehicle, the first collision time is determined based on the first driving data and the obstacle information within multiple cycles. If the first collision time is greater than the first threshold in each cycle, the lane-changing decision is to execute a lane change. If the first collision time is less than or equal to the first threshold in one or more of the plurality of cycles, the lane-changing decision is to stop the lane change.

4. The method according to claim 1, characterized in that, Determining the lane-changing decision for the target obstacle based on the traversed target obstacles further includes: If the target obstacle encountered is a pedestrian, a lane-changing decision is determined based on the distance between the pedestrian and the target vehicle.

5. The method according to claim 1, characterized in that, Determining the lane-changing decision for the target obstacle based on the traversed target obstacles further includes: If the target obstacle encountered is a stationary obstacle, then if the stationary obstacle is located in the second defined edge area of ​​the target lane change road or behind the target vehicle, the determined lane change decision is to execute the lane change. When the static obstacle is not located in the second defined edge area of ​​the target lane change road but is located in front of the target vehicle, the length of the reference line in front of the obstacle and the length of the reference line behind the obstacle are determined based on the obstacle information; If the length of the forward reference line is greater than the length of the rear reference line and the length of the forward reference line is greater than the lane change distance, or if the difference between the planned endpoint position and the head position of the obstacle is less than the lane change distance threshold, then the lane change method is to make a lane change decision in front of the stationary obstacle. If the length of the forward reference line is less than or equal to the length of the rear reference line, or the length of the forward reference line is less than or equal to the lane change distance, and the difference between the planned endpoint position and the head position of the obstacle is greater than the lane change distance threshold, then the lane change method is to execute the lane change decision behind the stationary obstacle.

6. An autonomous driving lane-changing decision-making device, characterized in that, include: The first acquisition module is used to acquire the first driving data of the target vehicle and the corresponding road information within the target area; The lane change information determination module is used to determine lane change information based on the road information and the first driving data; wherein, the lane change information includes the target lane change road; The second acquisition module is used to acquire obstacle information in the sub-region corresponding to the target lane change road in the target region; The lane-change decision determination module is used to determine the lane-change decision of the target vehicle based on the obstacle information; wherein, the target lane-change decision includes executing the lane change or stopping the lane change; the obstacle information includes obstacle type, distance and relative speed between the obstacle and the target vehicle; wherein, the obstacle type includes: motor vehicles, non-motor vehicles, pedestrians and static obstacles; The lane-change decision determination module is further configured to: sort at least one target obstacle contained in the obstacle information based on the priority of obstacle type; traverse the at least one target obstacle according to the sorting result; determine the lane-change decision of the target obstacle based on the traversed target obstacle; if the lane-change decision is to execute a lane change, then continue traversing the next target obstacle; if the lane-change decision is to stop lane change, then stop traversing and control the vehicle to execute a stop lane-change operation; The lane-changing decision determination module is further configured to: if the target obstacle type encountered is a non-motorized vehicle, and the non-motorized vehicle meets any of the following conditions, determine the lane-changing decision as executing a lane change: the forward distance between the non-motorized vehicle and the target vehicle is greater than a second threshold or the backward distance is greater than a third threshold; or, if the non-motorized vehicle is located in the first defined edge area of ​​the target lane-changing road; if the forward distance between the non-motorized vehicle and the target vehicle is less than or equal to the second threshold and the backward distance is less than or equal to the third threshold, determine a second collision time based on the first driving data and the obstacle information; wherein the third threshold is less than the second threshold; if the second collision time is greater than a fourth threshold, then determine the lane-changing decision as executing a lane change.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the autonomous driving lane-changing decision method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the autonomous driving lane-changing decision method according to any one of claims 1-5.

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