Conflict processing method and device, equipment and storage medium

Abstract

The invention provides a conflict processing method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence such as automatic driving and intelligent transportation. The method comprises the steps that a target obstacle is determined from obstacles based on track information of a target vehicle and track information of the obstacles, and the track information of the target obstacle conflicts with the track information of the target vehicle; the conflict type of the target vehicle and the target obstacle is determined, and the conflict type comprises a deterministic conflict and an uncertain conflict; and determining a target conflict processing result according to the conflict type and the number of the target obstacles, and adjusting the driving speed of the target vehicle according to the target conflict processing result. According to the method provided by the invention, different processing can be carried out on conflicts in the determined / uncertain conflict scene, and the driving safety of the vehicle is ensured.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence technology, specifically to the field of autonomous driving and intelligent transportation technology, and in particular to a conflict handling method, device, equipment and storage medium. Background Art

[0002] When an autonomous vehicle is driving in some complex scenarios, such as scenarios where interactive vehicles appear in the form of a continuous traffic flow, if a time-space conflict occurs between the autonomous vehicle and other interactive vehicles, the autonomous vehicle should make its own decisions based on the speed, trajectory and other information of all vehicles in the traffic flow, so as to avoid collisions, scratches and other behaviors with other interactive vehicles. Summary of the invention

[0003] The present disclosure provides a conflict handling method, apparatus, device and storage medium.

[0004] According to a first aspect of the present disclosure, a conflict handling method is provided, comprising: determining a target obstacle from obstacles based on trajectory information of a target vehicle and trajectory information of obstacles, wherein the target obstacle is an obstacle whose trajectory information conflicts with the trajectory information of the target vehicle; determining a conflict type between the target vehicle and the target obstacle, wherein the conflict type includes a deterministic conflict and an uncertain conflict; determining a target conflict handling result according to the conflict type and the number of target obstacles, and adjusting a driving speed of the target vehicle according to the target conflict handling result.

[0005] According to a second aspect of the present disclosure, a conflict handling device is provided, comprising: an obstacle determination module, configured to determine a target obstacle from obstacles based on trajectory information of a target vehicle and trajectory information of obstacles, wherein the target obstacle is an obstacle whose trajectory information conflicts with trajectory information of the target vehicle; a conflict determination module, configured to determine a conflict type between the target vehicle and the target obstacle, wherein the conflict type includes a deterministic conflict and an uncertain conflict; and a result determination module, configured to determine a target conflict handling result according to the conflict type and the number of target obstacles, and to adjust a travel speed of the target vehicle according to the target conflict handling result.

[0006] According to a third aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in any implementation manner in the first aspect.

[0007] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, where the computer instructions are used to cause a computer to execute the method described in any implementation manner of the first aspect.

[0008] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program, wherein the computer program, when executed by a processor, performs the method described in any implementation manner of the first aspect.

[0009] According to a sixth aspect of the present disclosure, an autonomous driving vehicle is provided, which includes the electronic device as described in the third aspect.

[0010] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. Figure 1 is a flow chart of a first embodiment of a conflict handling method according to the present disclosure; Figure 2 It is a schematic diagram of the conflict zone; Figure 3 is a flow chart of a second embodiment of a conflict handling method according to the present disclosure; Figure 4 is a flow chart of a third embodiment of a conflict handling method according to the present disclosure; Figure 5 is a flowchart of a fourth embodiment of the conflict handling method according to the present disclosure; Figure 6 It is a schematic diagram of the horizontal overlap relationship; Figure 7 is a flow chart of a fifth embodiment of the conflict handling method according to the present disclosure; Figure 8 is a flow chart of a sixth embodiment of the conflict handling method according to the present disclosure; Fig. 9 is a schematic structural diagram of an embodiment of a conflict handling device according to the present disclosure; Fig.10 It is a block diagram of an electronic device used to implement the conflict handling method of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0012] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0013] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0014] An exemplary system architecture for implementing the conflict handling method provided by the present disclosure may include a terminal device, a network, and a server. The network is used to provide a communication link between the terminal device and the server, and may include various connection types, such as a wired communication link, a wireless communication link, or an optical fiber cable, etc.

[0015] The user can use the terminal device to interact with the server through the network to receive or send information, etc. Various client applications can be installed on the terminal device, for example, map, navigation, entertainment and other client applications.

[0016] The terminal device can be hardware or software. When the terminal device is hardware, it can be various electronic devices, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, etc.; it can also be intelligent devices such as vehicles and intelligent robots, such as self-driving cars, delivery robots, etc. When the terminal device is software, it can be installed in the above electronic devices. It can be implemented as multiple software or software modules, or as a single software or software module. No specific limitation is made here.

[0017] The server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, used to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0018] It should be pointed out that the conflict handling method provided by the present disclosure can be executed by the server in the above system architecture, and can also be implemented by the above terminal device.

[0019] Figure 1 The process 100 of the first embodiment of the conflict handling method according to the present disclosure is shown. The conflict handling method comprises the following steps: Step 101 : determining a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle.

[0020] In this embodiment, the executor of the conflict handling method, such as a server or a terminal device (such as a vehicle-mounted terminal), determines a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle, wherein the target obstacle is an obstacle whose trajectory information conflicts with the trajectory information of the target vehicle.

[0021] The above-mentioned execution subject will first obtain the trajectory information of the vehicle, where the trajectory information can refer to the planned trajectory, and will also obtain the position, speed and other information of the vehicle, where the vehicle is the autonomous driving vehicle and the target vehicle. Then the above-mentioned execution subject will also obtain the trajectory information of other interactive vehicles (i.e. obstacles), where the trajectory information of the obstacles can be the predicted trajectory, and will also obtain the position, speed and other information of the obstacles. There can be one or more obstacles, and this embodiment does not limit the number of obstacles.

[0022] Afterwards, the execution subject will determine the target obstacle according to the trajectory information of the target vehicle and the trajectory information of the obstacle, that is, determine the obstacle whose trajectory information conflicts with the trajectory information of the target vehicle. Accordingly, the number of target obstacles can also be one or more. Specifically, the execution subject will determine whether the trajectory of the obstacle and the trajectory of the target vehicle will conflict at a certain moment or during a certain period of time, that is, whether there is an overlapping area between the two trajectories, based on the speed, trajectory and other information of the target vehicle and the speed, trajectory and other information of the obstacle. If a conflict occurs, the obstacle will be determined as the target obstacle.

[0023] It should be noted that if there are multiple obstacles, it is determined whether the trajectory of each obstacle conflicts with the trajectory of the target vehicle, so as to determine whether the current obstacle is a target obstacle.

[0024] Step 102: Determine the conflict type between the target vehicle and the target obstacle.

[0025] In this embodiment, the above-mentioned execution entity will determine the conflict type between the target vehicle and the target obstacle, wherein the conflict type includes deterministic conflict and uncertain conflict. Deterministic conflict refers to the existence of a clear collision relationship, and uncertain conflict refers to the existence of a clear collision relationship.

[0026] Specifically, the execution subject will determine whether there is a conflict zone between the target vehicle and the obstacle according to the predicted trajectory of the target vehicle and the predicted trajectory of the obstacle. If there is a conflict zone, it is determined that the conflict type between the target vehicle and the obstacle is a deterministic conflict.

[0027] It should be noted that the boundary of the conflict zone is taken from the projection position of the overlap area of ​​the vehicle path and other obstacle predicted trajectories on their respective paths. Figure 2 A schematic diagram of the conflict zone is shown in Figure 2 As shown, ABCD is the interactive conflict area between the ego vehicle and the other vehicle, A is the front boundary of the ego vehicle arriving at the conflict area, B is the rear boundary of the ego vehicle leaving the conflict area, C is the front boundary of the other vehicle arriving at the conflict area, and D is the rear boundary of the other vehicle leaving the conflict area.

[0028] Uncertainty conflict means that there is no clear collision relationship between the target vehicle and the obstacle, but there is a conflict trend, or a slight change in the driving state of one party will pose a driving threat to the other party. For example, in strong interaction areas such as merging and diverging, there is a merging lane in front of the lane where the obstacle is located, but the obstacle is currently in the straight lane, then it may have a collision risk with the vehicle when it merges into the lane later. In this case, the conflict type between the obstacle and the target vehicle is uncertain conflict.

[0029] Step 103: determining a target conflict processing result according to the conflict type and the number of target obstacles, and adjusting the driving speed of the target vehicle according to the target conflict processing result.

[0030] In this embodiment, the execution subject further determines the number of target obstacles, which can be a specific number or divided into one or more. Then, the target conflict result is determined according to the conflict type and the number of target obstacles. The target conflict result includes yielding and overtaking, that is, for the conflict situation of the target obstacle, the target vehicle chooses to overtake or yield, and the driving speed of the target vehicle is adjusted according to the target conflict result. For example, if the target vehicle chooses to overtake, it will speed up; if it chooses to yield, it will slow down to avoid collision with the target obstacle.

[0031] For example, when the conflict type is a deterministic conflict and there is only one target obstacle, the execution entity will calculate the probability of the ego vehicle cutting in and the probability of the target obstacle cutting in, and then determine whether the ego vehicle cuts in or gives way based on the calculated probabilities.

[0032] For another example, when the conflict type is deterministic and there are multiple target obstacles, the above-mentioned execution entity will reduce the size of the set of interactive agents (i.e., target obstacles) as much as possible to avoid selecting more low-risk obstacles that affect the traffic efficiency of the vehicle.

[0033] For another example, when the conflict type is uncertain and there is only one target obstacle, the vehicle will slow down and respond through a preventive speed reduction strategy to ensure that the vehicle has more sufficient adjustment time when the uncertain risk turns into a certain risk.

[0034] For another example, when the conflict type is uncertain and there are multiple target obstacles, since the specific object to avoid is lost, the goal of the vehicle becomes to continuously deal with the intelligent bodies that catch up with the vehicle one after another, so as to ensure traffic efficiency while taking lateral safety into account.

[0035] The conflict handling method provided by the embodiment of the present disclosure first determines the target obstacle that conflicts with the target vehicle, then determines the target conflict handling result for dealing with the conflict according to the number of target obstacles and the conflict type between the target vehicle and the target obstacle, and finally adjusts the driving speed of the target vehicle according to the target conflict handling result, thereby performing different processing on conflicts in certain / uncertain conflict scenarios, thereby ensuring the driving safety of the vehicle.

[0036] In addition, in the technical solutions involved in this disclosure, the acquisition, storage, use, processing, transportation, provision and disclosure of user personal information (such as the vehicle trajectory information involved in the subsequent disclosure, etc.) are in compliance with the relevant laws and regulations and do not violate public order and good morals.

[0037] Continue to refer Figure 3 , Figure 3 A process 300 of a second embodiment of a conflict handling method according to the present disclosure is shown. The conflict handling method comprises the following steps: Step 301 : determining a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle.

[0038] In this embodiment, the executor of the conflict handling method, such as a server or a terminal device (such as a vehicle-mounted terminal), determines a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle, wherein the target obstacle is an obstacle whose trajectory information conflicts with the trajectory information of the target vehicle.

[0039] Step 301 is basically the same as step 101 of the aforementioned embodiment. The specific implementation method can refer to the aforementioned description of step 101, which will not be repeated here.

[0040] Step 302: Determine the conflict type between the target vehicle and the target obstacle.

[0041] In this embodiment, the execution subject determines the conflict type between the target vehicle and the target obstacle, wherein the conflict type includes deterministic conflict and uncertain conflict.

[0042] Step 302 is basically the same as step 102 of the aforementioned embodiment. The specific implementation method can refer to the aforementioned description of step 102, which will not be repeated here.

[0043] Step 303, in response to determining that the conflict type is a deterministic conflict and the number of target obstacles is one, the yielding benefit of the target vehicle in the pre-constructed game payoff matrix is ​​improved according to the yielding waiting time of the target vehicle, and the yielding benefit of the target obstacle in the game payoff matrix is ​​improved according to the yielding waiting time of the target obstacle, to obtain an improved game payoff matrix.

[0044] In this embodiment, if the conflict type is determined to be a deterministic conflict and there is only one target obstacle, taking into account that long queues are likely to cause traffic jams, etc., therefore, on the basis of the general game payoff matrix, the concept of waiting time is considered, and the benefit of the target vehicle choosing to give way will decrease as the waiting time increases, thereby obtaining an improved game payoff matrix.

[0045] Table 1 is a general game payoff matrix. In Table 1, car M is the target obstacle, car N is the ego car (i.e., the target vehicle), and each value in the matrix represents the benefit. For example, the value of the first row and the first column in the matrix is ​​the benefit value of the decision of car M grabbing the line & car N grabbing the line. Table 1 is as follows: Table 1 General game payoff matrix

[0046] According to the general game payoff matrix in Table 1 and formula (1), the probability of the self-vehicle (vehicle N) and the target obstacle (vehicle M) to grab the lane can be further calculated. Formula (1) is as follows: , ; (1) in, and are the probabilities of choosing to overtake the ego vehicle and the target obstacle respectively; and are the risk perception utility values ​​of the ego vehicle and the target obstacle, respectively, and , is the time when the vehicle reaches the collision area, and are the time loss utility values ​​of the ego vehicle and the target obstacle, respectively, and their values ​​are equal to the time it takes for each interactive agent to pass through the conflict area; a and c are the time loss utility coefficient and the conflict time loss coefficient, respectively, reflecting the time loss of giving way and the additional time loss when a conflict occurs.

[0047] Then, the above-mentioned execution subject will improve the yielding benefit of the target vehicle in the general game payment matrix in Table 1 according to the yielding waiting time of vehicle N, and improve the yielding benefit of the target obstacle in the general game payment matrix in Table 1 according to the yielding waiting time of vehicle M, and obtain the improved game payment matrix. Table 2 is the improved game payment matrix, which is expressed as follows: Table 2 Improved game payoff matrix

[0048] Step 304 , calculating a first overtaking probability of the target vehicle and a second overtaking probability of the target obstacle according to the improved game payoff matrix.

[0049] In this embodiment, the execution subject further calculates the first line grabbing probability and the second line grabbing probability according to the improved game matrix shown in Table 2 and formula (2), and formula (2) is as follows: , ; (2) in, is the probability of being the first to take over, is the second grab probability; The waiting time for the vehicle to stop. The waiting time for stopping at the target obstacle. and is the waiting time influence coefficient, and .

[0050] Step 305, determining a first processing result according to the first overtaking probability and the second overtaking probability, determining the first processing result as a target conflict processing result, and adjusting the driving speed of the target vehicle according to the target conflict processing result.

[0051] In this embodiment, the execution subject determines the first processing result according to the calculated first overtaking probability and second overtaking probability, and the first processing result is determined as the processing result of the single obstacle deterministic conflict, wherein the first processing result includes overtaking or yielding. Specifically, if the first overtaking probability is greater than the second overtaking probability, the first processing result is overtaking by the vehicle; if the first overtaking probability is not greater than the second overtaking probability, the first processing result is overtaking by the target obstacle, i.e., yielding by the vehicle. Finally, the driving speed of the vehicle is adjusted according to the target conflict processing result to avoid collision with the target obstacle.

[0052] from Figure 3 It can be seen that Figure 1 Compared with the corresponding embodiments, the conflict handling method in this embodiment obtains an improved game payoff matrix based on the target vehicle's yield waiting time when the conflict type is a deterministic conflict and the number of target obstacles is one, and calculates the target vehicle's overtaking probability and the target obstacle's overtaking probability based on the improved game payoff matrix, and determines the final processing result based on the two overtaking probabilities, thereby ensuring the vehicle's driving safety in a single obstacle deterministic conflict scenario.

[0053] Continue to refer Figure 4 , Figure 4 A process 400 of a third embodiment of a conflict handling method according to the present disclosure is shown. The conflict handling method comprises the following steps: Step 401 : determining a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle.

[0054] Step 402: Determine the conflict type between the target vehicle and the target obstacle.

[0055] Step 403, in response to determining that the conflict type is a deterministic conflict and the number of target obstacles is one, the yielding benefit of the target vehicle in the pre-constructed game payoff matrix is ​​improved according to the yielding waiting time of the target vehicle, and the yielding benefit of the target obstacle in the game payoff matrix is ​​improved according to the yielding waiting time of the target obstacle, to obtain an improved game payoff matrix.

[0056] Step 404, calculating a first overtaking probability of the target vehicle and a second overtaking probability of the target obstacle according to the improved game payoff matrix.

[0057] Steps 401-404 are basically consistent with steps 301-304 of the aforementioned embodiment. For specific implementation methods, reference may be made to the aforementioned description of steps 301-304, which will not be repeated here.

[0058] Step 405 , determining a right-of-way correction amount according to the right-of-way information of the target vehicle relative to the target obstacle, and correcting the first overtaking probability according to the right-of-way correction amount to obtain a corrected first overtaking probability.

[0059] In this embodiment, the execution subject of the conflict handling method, such as a server or a terminal device (such as a vehicle-mounted terminal), further modifies the decision probability according to the right of way. Since the right of way is a relative concept, that is, the right of way attribute of A to B and the right of way attribute of A to C have independent characteristics, the right of way is defined into three categories: advantage, equality and disadvantage. Taking the merging scenario as an example, the right of way information of the target vehicle relative to the target obstacle is calculated by the following steps: Get the lane 1 where the vehicle is located, the lane 2 where the target obstacle is located, and the subsequent lane 3, and define the lane continuity threshold ; Calculate the heading difference between lane 1 and lane 3, recorded as ;Heading is the direction of the lane line in the world coordinate system; Calculate the heading difference between lane 2 and lane 3, recorded as ; contrast , If the numerical relationship between and , then the ego vehicle has an advantage over the target obstacle; if and , then the ego vehicle has equal right of way compared to the target obstacle; if and , then the ego vehicle has a disadvantageous right of way compared to the target obstacle.

[0060] For different road right attributes, the decision probability should be dynamically corrected. Therefore, the road right correction amount corresponding to the superior, equal, and inferior road rights is defined as: superiority correction amount , Equality Correction and Disadvantage Modifier , according to the road right correction amount, the probability of first overtaking After correction, the corrected probability of the first rush is expressed as: ; It should be noted that according to experience, Take 0, and there is > > .

[0061] Step 406, determining a first processing result according to the corrected first overtaking probability and the second overtaking probability, determining the first processing result as a target conflict processing result, and adjusting the driving speed of the target vehicle according to the target conflict processing result.

[0062] In this embodiment, the execution subject determines the first processing result according to the revised first overtaking probability and the second overtaking probability, and determines the first processing result as the target conflict processing result, wherein the first processing result includes overtaking or yielding. Specifically, if the revised first overtaking probability is greater than the second overtaking probability, the first processing result is that the vehicle overtakes the target obstacle; if the revised first overtaking probability is not greater than the second overtaking probability, the first processing result is that the target obstacle overtakes the target obstacle, that is, the vehicle yields the target obstacle. Finally, the driving speed of the vehicle is adjusted according to the target conflict processing result to avoid collision with the target obstacle.

[0063] from Figure 4 It can be seen that Figure 3Compared with the corresponding embodiment, the conflict handling method in this embodiment obtains an improved game payoff matrix according to the yield waiting time of the target vehicle when the conflict type is a deterministic conflict and the number of target obstacles is one, and calculates the target vehicle's overtaking probability and the target obstacle's overtaking probability according to the improved game payoff matrix. On this basis, the ego vehicle's overtaking probability is further corrected according to the road right attribute of the target vehicle compared with the target obstacle, and the final processing result is determined according to the corrected ego vehicle's overtaking probability and the target obstacle's overtaking probability, thereby ensuring the vehicle's driving safety in a single obstacle deterministic conflict scenario.

[0064] Continue to refer Figure 5 , Figure 5 The fourth embodiment of the conflict handling method according to the present disclosure is shown in process 500. The conflict handling method comprises the following steps: Step 501 : determining a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle.

[0065] Step 502: Determine the conflict type between the target vehicle and the target obstacle.

[0066] Steps 501-502 are basically consistent with steps 101-102 of the aforementioned embodiment. For specific implementation methods, reference may be made to the aforementioned description of steps 101-102, which will not be repeated here.

[0067] Step 503 , in response to determining that the conflict type is a deterministic conflict and the number of target obstacles is multiple, the multiple target obstacles are roughly clustered according to the lateral distances between the multiple target obstacles and the road boundary to obtain multiple clustered obstacle queues.

[0068] In this embodiment, if the execution subject of the conflict handling method, such as a server or a terminal device (such as a vehicle-mounted terminal), determines that the conflict type is a deterministic conflict and the number of target obstacles is multiple, the execution subject will roughly cluster the multiple target obstacles according to the lateral distances between the multiple target obstacles and the road boundary, thereby obtaining multiple obstacle queues after clustering. The specific algorithm is as follows: A. Initialization: define the open set, close set, and buffer set, place all obstacles in the open set from front to back, and set the close set and buffer set to empty sets, and define the maximum longitudinal queue gap threshold ; B. Move the first element of the open set to the buffer set; C. The upper layer traverses the open set to check whether the obstacle has a horizontal overlap with any obstacle in the buffer set, and the lower layer traverses the buffer set; c.1. If there is no overlap relationship, continue to traverse the upper layer; c.2. If there is an overlap relationship, calculate the longitudinal distance between the obstacle and the buffer set obstacle, recorded as d. If d< , move the obstacle to the buffer set, otherwise, continue to traverse the lower layer; D. Put the buffer set in the close set and clear the buffer set; E. Repeat B to D until the open set is empty.

[0069] The close set finally obtained by the above algorithm is the coarse clustering result.

[0070] The horizontal overlap relationship is defined as follows: Figure 6 As shown, in Figure 6 In the example, there is no lateral overlap relationship between obstacle 1 and obstacle 2, but there is a lateral overlap relationship between agent 3 (obstacle 3) and agent 1 (obstacle 1) and agent 2 (obstacle 2). Specifically, the lateral positions of obstacle 1, obstacle 2 and obstacle 3 in the SL coordinate system can be obtained first, and then it is determined whether there is a lateral overlap relationship by judging whether there is an overlapping relationship between the lateral coordinates of obstacle 1, obstacle 2 and obstacle 3. If there is an overlapping relationship, there is a lateral overlap relationship. For example, there is an overlap between the lateral coordinates of obstacle 3 and obstacle 1 and obstacle 2, so there is a lateral overlap relationship between obstacle 3 and obstacle 1 and obstacle 2; if there is no overlapping relationship, there is no lateral overlap relationship. For example, there is no overlap between the lateral coordinates of obstacle 1 and obstacle 2, so there is no lateral overlap relationship between obstacle 1 and obstacle 2.

[0071] Step 504 : for a plurality of obstacle queues, according to the first processing result between the target vehicle and the head obstacle of the obstacle queue, the obstacle queue is divided into a set of grabbing obstacle queues or a set of yielding obstacle queues.

[0072] In this embodiment, the multiple obstacle queues obtained by coarse clustering are further divided into a set of obstacle queues for grabbing and a set of obstacle queues for yielding. The specific algorithm is as follows: A. Initialization: define yield set and rush set, record the set of self-car rushing agents and the set of giving way agents; B. Traverse the close set (coarse clustering result) and determine the single-agent decision between the ego vehicle and the obstacle at the head of the team (i.e. the first processing result); b.1. If the decision result is to rush, the obstacle at the head of the team is placed in the rush set; b.2. If the decision result is to yield, the obstacle at the end of the team is placed in the yield set; Thus, a yield set or a rush set of obstacles is obtained.

[0073] Step 505, performing combined optimization solution on the set of rushing obstacle queues and the set of yielding obstacle queues, determining a second processing result according to the solution result, determining the second processing result as the target conflict processing result, and adjusting the driving speed of the target vehicle according to the target conflict processing result.

[0074] In this embodiment, the above-mentioned execution entity will shrink the scale of decision obstacles to yield set and rush set, and solve the final planning result through combinatorial optimization to obtain the second processing result, which is the processing result of multi-obstacle deterministic conflict, and use the second processing result as the target conflict processing result. Finally, the driving speed of the vehicle is adjusted according to the target conflict processing result to avoid collision with the target obstacle.

[0075] It should be noted that the above decision-making process is based on the strong assumption that an obstacle in the queue cannot pass over the previous obstacle. This assumption is generally valid and universal.

[0076] from Figure 5 It can be seen that Figure 1 Compared with the corresponding embodiments, the conflict handling method in this embodiment, when the conflict type is a deterministic conflict and the number of target obstacles is multiple, first performs coarse clustering on the multiple obstacles to obtain multiple queues, and then divides the multiple queues into a set of overtaking obstacle queues or a set of yielding obstacle queues according to the single obstacle deterministic processing results between the vehicle and the first obstacle of each queue. Finally, the final processing result is obtained through combined optimization solution, thereby ensuring the driving safety of the vehicle in a multi-obstacle deterministic conflict scenario.

[0077] Continue to refer Figure 7 , Figure 7 The fifth embodiment of the conflict handling method according to the present disclosure is shown in process 700. The conflict handling method includes the following steps: Step 701 : determining a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle.

[0078] Step 702: Determine the conflict type between the target vehicle and the target obstacle.

[0079] Steps 701-702 are basically consistent with steps 101-102 of the aforementioned embodiment. For specific implementation methods, reference may be made to the aforementioned description of steps 101-102, which will not be repeated here.

[0080] Step 703 , in response to determining that the conflict type is an uncertain conflict and the number of the target obstacle is one, determining a yield waiting time for the target vehicle according to a lateral distance between the target obstacle and the target vehicle.

[0081] In this embodiment, if the execution subject of the conflict handling method, such as a server or terminal device (such as a vehicle-mounted terminal), determines that the conflict type is an uncertain conflict and there is only one target obstacle, the ego vehicle responds through a preventive speed reduction strategy, thereby ensuring that the ego vehicle has more sufficient adjustment time when the uncertain risk turns into a certain risk. In addition, in order to ensure traffic efficiency, only preventive response disposal is performed on vehicles parallel to the ego vehicle. For parallel avoidance, the response decision amount is defined as the time required for the ego vehicle to avoid the target obstacle first (waiting time for yielding), which should be related to the lateral distance between the target obstacle and the ego vehicle, and can be specifically calculated according to formula (3): ; (3) Where T is the avoidance time, λ is the influence coefficient of distance on the avoidance time, is the lateral distance between the target obstacle and the vehicle, is the maximum horizontal distance considered, is the minimum horizontal tolerance distance, is the time required for the vehicle to avoid an obstacle at the maximum deceleration. It is calculated by the following formula (4): ; (4) in, and are the current speeds of the vehicle and the target obstacle, respectively. is the limit deceleration, is the distance between the rear of the current vehicle and the rear of the obstacle (with the vehicle's travel direction as the positive direction), The captain of your own vehicle.

[0082] Step 704: determine a speed control amount for controlling the travel speed of the target vehicle according to the yield waiting time, use the speed control amount as a target conflict processing result, and adjust the travel speed of the target vehicle according to the target conflict processing result.

[0083] In this embodiment, the execution subject determines the speed control amount according to the waiting time for yielding. , which can be calculated according to formula (5): ; (5) Finally, the speed control amount is used as the target conflict processing result, and the driving speed of the target vehicle is adjusted according to the target conflict processing result to avoid possible conflict with the target obstacle.

[0084] from Figure 7 It can be seen that Figure 1 Compared with the corresponding embodiment, the conflict handling method in this embodiment, when the conflict type is an uncertain conflict and the number of target obstacles is one, the vehicle responds through a preventive speed reduction strategy, thereby ensuring that the vehicle has more sufficient adjustment time when the uncertain risk turns into a certain risk, avoiding possible conflict with the target obstacle.

[0085] Continue to refer Figure 8 , Figure 8 The sixth embodiment of the conflict handling method according to the present disclosure is shown in process 800. The conflict handling method comprises the following steps: Step 801 : determining a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle.

[0086] Step 802: Determine the conflict type between the target vehicle and the target obstacle.

[0087] Steps 801-802 are basically consistent with steps 101-102 of the aforementioned embodiment. For specific implementation methods, reference may be made to the aforementioned description of steps 101-102, which will not be repeated here.

[0088] Step 803 : in response to determining that the conflict type is an uncertain conflict and the number of target obstacles is multiple, generating an obstacle trajectory set according to trajectory information of the multiple target obstacles.

[0089] In this embodiment, if the execution subject of the conflict handling method, such as a server or a terminal device (such as a vehicle-mounted terminal), determines that the conflict type is an uncertain conflict and the number of target obstacles is multiple, the execution subject will first generate a target obstacle set, the target obstacle set includes multiple target obstacles, and then traverse the target obstacle set to collect the future driving trajectories of each target obstacle, thereby obtaining an obstacle trajectory set. , where n is the number of target obstacles, is the trajectory of the nth target obstacle.

[0090] Step 804, solving the optimal boundary value according to the starting state and the ending state of the relative trajectory of the target vehicle.

[0091] In this embodiment, the execution subject solves the optimal boundary value according to the starting state and the ending state of the relative trajectory of the target vehicle, wherein the relative trajectory is the relative trajectory between the trajectory information of the target vehicle and the obstacle trajectory in the obstacle trajectory set.

[0092] That is, the execution subject will first generate the relative trajectory between the target vehicle's trajectory information and the obstacle trajectory in the obstacle trajectory set. Specifically, the execution subject will first traverse the obstacle trajectory set. , and then the trajectory Reproject the ego vehicle trajectory to the reference line , get the relative trajectory of the vehicle ,in, is a function that projects the trajectory of the vehicle using the obstacle trajectory as the reference line. That is, the input of the function is the trajectory of the vehicle, and the output is the relative trajectory of the vehicle relative to the obstacle trajectory. Then, the optimal boundary value is solved according to the starting state and the end state of the relative trajectory of the target vehicle.

[0093] In some optional implementations of this embodiment, step 804 further includes: traversing the obstacle trajectory set, taking the current obstacle trajectory as a reference line, projecting the trajectory information of the target vehicle, and obtaining a plurality of relative trajectories of the target vehicle after projection; for each relative trajectory of the target vehicle after projection, determining the starting state and the end state of the relative trajectory, and solving the optimal boundary value according to the starting state and the end state.

[0094] In this implementation, the worst-case assumption is followed when generating the reference trajectory: multiple obstacles (traffic flows) and continuous overtaking without time sequence.

[0095] First, determine the relative position between the obstacle and the ego vehicle, and record the ego vehicle's driving direction vector as , the connection vectors between the geometric center of the vehicle and the corner points of the obstacle (box) are , , , , define the following function:

[0096] If f=4, the obstacle is on the left side of the vehicle, and if f=-4, the obstacle is on the right side of the vehicle. The direction is recorded as .

[0097] Secondly, the boundary points of the obstacle prediction trajectory are collected. The boundary selection direction is opposite to the direction of the obstacle relative to the vehicle position, that is, Direction, the set of driving trajectory points is recorded as: , o∈ ; Perform dense processing on the driving trajectory points and record the cumulative S value set at each point ,in: , ; Let the minimum dense unit be Δs, then the kth dense point for: ; Perform a binary search in the S value set s to obtain the S value interval corresponding to the dense point k , further, the corresponding driving trajectory point interval is , the coordinates of the dense point are: = + ; Record the driving trajectory of agent i for: ; Do the same processing on the vehicle's driving trajectory to obtain the vehicle's driving trajectory for: ; Since the driving direction of the ego vehicle is basically consistent with the driving direction of the obstacle set, in order to speed up the search, the incrementally updated search lower bound index is defined as χ, and the search trajectory point of the ego vehicle is In the reference trajectory The closest projection point on and its index j, denoted as: , ; Searching for trajectory points When , its matching range is [χ, N], repeat the above steps to get Repeat for all Execute, get .right According to the worst assumption, the g function is: ; Afterwards, when selecting the interval, the envelope range between the local extreme points of the projection trajectory of the vehicle is considered. Assuming that there are n extreme points, there are n-1 speed limit intervals, and the extreme points satisfy: ; The speed limit is executed from the current state to the next interval. In the first interval, the starting state is the current state: ; in, The current accumulated S value of the vehicle, usually 0; and are the current speed and acceleration of the vehicle respectively.

[0098] Assume that the projection point at the first extreme point is , then the speed limit at this extreme point is defined as: ; in, For road speed limits, is the lateral distance at time t (lateral distance from the obstacle trajectory), is the maximum considered lateral distance or safety distance, and k is a hyperparameter.

[0099] At the first extreme point: ; in, represents the dense unit distance and t is the time.

[0100] Therefore, the terminal state of the first segment is , A random amount.

[0101] Then the above execution body will solve the optimal boundary value according to the starting state and the end state.

[0102] Step 805, determining the interval speed of the target vehicle in the relative trajectory according to the solution result, taking the interval speed as the target conflict processing result of the relative trajectory, and adjusting the driving speed of the target vehicle according to the target conflict processing result.

[0103] In this embodiment, the execution subject will determine the target vehicle's speed in the relative trajectory according to the solution result. Specifically: The state transition process is connected by a quartic spline curve, defined as: ; in, are the coefficients of a quartic polynomial.

[0104] make: , , ; have ; The transfer time t is: ; According to the minimum time step Δt of the frame, the time interval speed constraint is calculated according to the above process: ; At the next extreme point, the current state is updated to ,in, . Repeat the above process to get: ; in, is the speed of the first interval, For the speed of the second interval... Finally, the speed of each interval is used as the target conflict processing result of the relative trajectory, and the driving speed of the target vehicle is adjusted according to the target conflict processing result to avoid possible conflict with the target obstacle.

[0105] from Figure 8 It can be seen that Figure 1 Compared with the corresponding embodiment, the conflict handling method in this embodiment, when the conflict type is uncertain conflict and the number of target obstacles is multiple, since there is no specific avoidance object, the goal of the vehicle becomes the continuous handling of obstacles that catch up with the vehicle one after another. The vehicle trajectory is re-projected with the obstacle trajectory as the reference line to obtain the relative trajectory of the vehicle, and then the start and end states are set to solve the optimal boundary value problem to obtain the interval speed value. The speed of the vehicle is adjusted according to the interval speed, so as to ensure the traffic efficiency while taking into account the lateral safety and avoid possible conflicts with the target obstacles.

[0106] Further references Fig. 9 As an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a conflict handling device. Figure 1 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0107] like Fig. 9As shown, the conflict handling device 900 of this embodiment includes: an obstacle determination module 901, a conflict determination module 902 and a result determination module 903. The obstacle determination module 901 is configured to determine a target obstacle from obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle, wherein the target obstacle is an obstacle whose trajectory information conflicts with the trajectory information of the target vehicle; the conflict determination module 902 is configured to determine the conflict type between the target vehicle and the target obstacle, wherein the conflict type includes a deterministic conflict and an uncertain conflict; the result determination module 903 is configured to determine the target conflict handling result according to the conflict type and the number of target obstacles, and adjust the driving speed of the target vehicle according to the target conflict handling result.

[0108] In this embodiment, in the conflict handling device 900, the specific processing of the obstacle determination module 901, the conflict determination module 902 and the result determination module 903 and the technical effects thereof can be referred to in Figure 1 The relevant descriptions of steps 101 - 103 in the corresponding embodiment are not repeated here.

[0109] In some optional implementations of the present embodiment, the result determination module 903 includes: an improvement submodule, configured to, in response to determining that the conflict type is a deterministic conflict and the number of target obstacles is one, improve the yielding benefit of the target vehicle in a pre-constructed game payment matrix according to the yielding waiting time of the target vehicle, and improve the yielding benefit of the target obstacle in the game payment matrix according to the yielding waiting time of the target obstacle, so as to obtain an improved game payment matrix; a calculation submodule, configured to calculate a first overtaking probability of the target vehicle and a second overtaking probability of the target obstacle according to the improved game payment matrix; a determination submodule, configured to determine a first processing result according to the first overtaking probability and the second overtaking probability, and determine the first processing result as the target conflict processing result, wherein the first processing result includes overtaking or yielding.

[0110] In some optional implementations of the present embodiment, the conflict handling device 900 also includes: a correction module, configured to determine a right of way correction amount based on the right of way information of the target vehicle relative to the target obstacle; correct the first overtaking probability based on the right of way correction amount to obtain a corrected first overtaking probability; and the determination submodule is further configured to: determine a first processing result based on the corrected first overtaking probability and the second overtaking probability.

[0111] In some optional implementations of the present embodiment, the result determination module 903 is further configured to: in response to determining that the conflict type is a deterministic conflict and the number of target obstacles is multiple, coarsely cluster the multiple target obstacles according to the lateral distances between the multiple target obstacles and the road boundary to obtain multiple obstacle queues after clustering; for multiple obstacle queues, divide the obstacle queues into a set of overtaking obstacle queues or a set of yielding obstacle queues according to the first processing result between the target vehicle and the head obstacle of the obstacle queue; perform combined optimization solution on the set of overtaking obstacle queues and the set of yielding obstacle queues, determine a second processing result according to the solution result, and determine the second processing result as the target conflict processing result.

[0112] In some optional implementations of the present embodiment, the result determination module 903 is further configured to: in response to determining that the conflict type is an uncertain conflict and the number of target obstacles is one, determine the yield waiting time of the target vehicle according to the lateral distance between the target obstacle and the target vehicle; determine a speed control amount for controlling the driving speed of the target vehicle according to the yield waiting time, and use the speed control amount as the target conflict processing result.

[0113] In some optional implementations of this embodiment, the result determination module 903 includes: a generation submodule, configured to generate an obstacle trajectory set according to the trajectory information of multiple target obstacles in response to determining that the conflict type is an uncertain conflict and the number of target obstacles is multiple; a solution submodule, configured to solve the optimal boundary value according to the starting state and the end state of the relative trajectory of the target vehicle, wherein the relative trajectory is the relative trajectory between the trajectory information of the target vehicle and the obstacle trajectory in the obstacle trajectory set; a result determination submodule, configured to determine the interval speed of the target vehicle on the relative trajectory according to the solution result, and use the interval speed as the target conflict processing result of the relative trajectory.

[0114] In some optional implementations of the present embodiment, the result determination submodule is further configured to: traverse the obstacle trajectory set, use the current obstacle trajectory as a reference line, project the trajectory information of the target vehicle, and obtain the relative trajectory of the target vehicle after multiple projections; for each relative trajectory of the target vehicle after projection, determine the starting state and the end state of the relative trajectory, and solve the optimal boundary value according to the starting state and the end state.

[0115] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, a computer program product and an autonomous driving vehicle.

[0116] Fig.10A schematic block diagram of an example electronic device 1000 that can be used to implement an embodiment of the present disclosure is shown. 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 can 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 merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0117] like Fig.10 As shown, the device 1000 includes a computing unit 1001, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for the operation of the device 1000 can also be stored. The computing unit 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0118] A number of components in the device 1000 are connected to the I / O interface 1005, including: an input unit 1006, such as a keyboard, a mouse, etc.; an output unit 1007, such as various types of displays, speakers, etc.; a storage unit 1008, such as a disk, an optical disk, etc.; and a communication unit 1009, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1009 allows the device 1000 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0119] The computing unit 1001 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1001 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1001 performs the various methods and processes described above, such as the conflict handling method. For example, in some embodiments, the conflict handling method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1008. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 1000 via the ROM 1002 and / or the communication unit 1009. When the computer program is loaded into the RAM 1003 and executed by the computing unit 1001, one or more steps of the conflict handling method described above may be performed. Alternatively, in other embodiments, the computing unit 1001 may be configured to perform the conflict handling method in any other appropriate manner (e.g., by means of firmware).

[0120] The autonomous driving vehicle provided by the present disclosure may include: Fig.10 The electronic device shown above can implement the conflict handling method described in any of the above embodiments when executed by its processor.

[0121] Various implementations 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 chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0122] The program code for implementing the method 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, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0123] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A 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, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0124] To provide interaction with a user, the systems and techniques described herein 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 the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the 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 acoustic input, voice input, or tactile input).

[0125] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0126] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0127] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0128] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A conflict handling method, comprising: Based on the trajectory information of the target vehicle and the trajectory information of the obstacle, determining a target obstacle from the obstacles, wherein the target obstacle is an obstacle whose trajectory information conflicts with the trajectory information of the target vehicle; Determining a conflict type between the target vehicle and the target obstacle, wherein the conflict type includes a deterministic conflict and an uncertain conflict; A target conflict processing result is determined according to the conflict type and the number of the target obstacles, and a travel speed of the target vehicle is adjusted according to the target conflict processing result.

2. The method according to claim 1, wherein: The determining the target conflict processing result according to the conflict type and the number of the target obstacles includes: In response to determining that the conflict type is the deterministic conflict and the number of the target obstacle is one, improving the yielding benefit of the target vehicle in a pre-constructed game payoff matrix according to the yielding waiting time of the target vehicle, and improving the yielding benefit of the target obstacle in the game payoff matrix according to the yielding waiting time of the target obstacle, to obtain an improved game payoff matrix; Calculate a first overtaking probability of the target vehicle and a second overtaking probability of the target obstacle according to the improved game payoff matrix; A first processing result is determined according to the first overtaking probability and the second overtaking probability, and the first processing result is determined as the target conflict processing result, wherein the first processing result includes overtaking or giving way.

3. The method according to claim 2, wherein: Also includes: Determining a right-of-way correction amount according to the right-of-way information of the target vehicle relative to the target obstacle; Correcting the first overtaking probability according to the road right correction amount to obtain a corrected first overtaking probability; as well as The determining the first processing result according to the first preemption probability and the second preemption probability includes: The first processing result is determined according to the corrected first rush-to-go probability and the second rush-to-go probability.

4. The method according to claim 2 or 3, wherein: The determining of the target conflict processing result according to the conflict type and the number of the target obstacles further includes: In response to determining that the conflict type is the deterministic conflict and the number of the target obstacles is multiple, coarsely clustering the multiple target obstacles according to lateral distances between the multiple target obstacles and the road boundary to obtain multiple clustered obstacle queues; For the plurality of obstacle queues, according to a first processing result between the target vehicle and the head obstacle of the obstacle queue, the obstacle queue is divided into a set of grabbing obstacle queues or a set of yielding obstacle queues; A combined optimization solution is performed on the set of rushing obstacle queues and the set of yielding obstacle queues, a second processing result is determined according to the solution result, and the second processing result is determined as the target conflict processing result.

5. The method according to claim 1, wherein: The determining the target conflict processing result according to the conflict type and the number of the target obstacles includes: In response to determining that the conflict type is the uncertain conflict and the number of the target obstacle is one, determining a yield waiting time for the target vehicle according to a lateral distance between the target obstacle and the target vehicle; A speed control amount for controlling the travel speed of the target vehicle is determined according to the yield waiting time, and the speed control amount is used as the target conflict processing result.

6. The method according to claim 1, wherein: The determining the target conflict processing result according to the conflict type and the number of the target obstacles includes: In response to determining that the conflict type is the uncertain conflict and the number of the target obstacles is multiple, generating an obstacle trajectory set according to trajectory information of the multiple target obstacles; Solving the optimal boundary value according to the starting state and the ending state of the relative trajectory of the target vehicle, wherein the relative trajectory is the relative trajectory between the trajectory information of the target vehicle and the obstacle trajectory in the obstacle trajectory set; The interval speed of the target vehicle in the relative trajectory is determined according to the solution result, and the interval speed is used as the target conflict processing result of the relative trajectory.

7. The method according to claim 6, wherein: The step of solving the optimal boundary value according to the starting state and the ending state of the relative trajectory of the target vehicle includes: Traversing the obstacle trajectory set, taking the current obstacle trajectory as a reference line, respectively, projecting the trajectory information of the target vehicle, and obtaining a relative trajectory of the target vehicle after multiple projections; For each relative track of the target vehicle after projection, a starting state and an end state of the relative track are determined, and an optimal boundary value is solved according to the starting state and the end state.

8. A conflict handling device, comprising: An obstacle determination module is configured to determine a target obstacle from the obstacles based on the trajectory information of the target vehicle and the trajectory information of the obstacle, wherein the target obstacle is an obstacle whose trajectory information conflicts with the trajectory information of the target vehicle; A conflict determination module, configured to determine a conflict type between the target vehicle and the target obstacle, wherein the conflict type includes a deterministic conflict and an uncertain conflict; The result determination module is configured to determine a target conflict processing result according to the conflict type and the number of the target obstacles, and adjust the driving speed of the target vehicle according to the target conflict processing result.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

11. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 7.

12. An autonomous driving vehicle comprising the electronic device as claimed in claim 9.

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