Vehicle avoidance strategy determination method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of vehicles, and discloses a vehicle avoidance strategy determination method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a target steering intention of a target vehicle based on a historical track of the target vehicle; wherein the target steering intention is the steering intention with the maximum steering probability of the target vehicle; determining a track intersection point according to the predicted track corresponding to the target steering intention and the predicted tracks of other vehicles; according to the current distance between the target vehicle and the track intersection point and the driving parameters of the target vehicle and the other vehicles, the current safety distance between the target vehicle and the other vehicles is calculated; and determining a corresponding avoidance strategy according to a difference value between the current distance and the current safety distance. The method is not limited to collision analysis of single vehicle data, the driving influence of other vehicles is combined, and the corresponding avoidance strategy is determined, so that real-time effective avoidance of the vehicle is ensured, and collision accidents are prevented.

Description

Technical Field

[0001] This application relates to the technical field of vehicles, and particularly to a method, device, electronic device and storage medium for determining a vehicle avoidance strategy. Background Art

[0002] Related vehicle collision avoidance technologies are based on in-vehicle sensors such as in-vehicle cameras and radars to perceive collision risks, and thus determine avoidance strategies to avoid the occurrence of collision accidents.

[0003] However, the actual road conditions are very complex and there are various influencing factors. Based on the data collected by in-vehicle sensors for collision analysis, the analyzed avoidance strategies cannot adapt to complex road conditions, so the vehicle cannot perform effective anti-collision avoidance. Summary of the Invention

[0004] In view of the above problems, this application provides a method, device, electronic device and storage medium for determining a vehicle avoidance strategy to improve the effectiveness of the avoidance strategy.

[0005] According to one aspect of this application, a method for determining a vehicle avoidance strategy is provided. The determination method includes: determining a target steering intention of the target vehicle based on the historical trajectory of the target vehicle; where the target steering intention is the steering intention with the highest steering probability of the target vehicle; determining a trajectory intersection point according to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles; calculating a current safety distance between the target vehicle and the other vehicles according to the current distance between the target vehicle and the trajectory intersection point, and the driving parameters of the target vehicle and the other vehicles; and determining a corresponding avoidance strategy according to the difference between the current distance and the current safety distance.

[0006] In an optional manner, the determining a target steering intention of the target vehicle based on the historical trajectory of the target vehicle includes: determining the motion characteristics, driving behavior characteristics, and environmental characteristics of the target vehicle in the historical trajectory based on the historical trajectory of the target vehicle; calculating the probability of each steering intention according to the probabilities of the motion characteristics, the driving behavior characteristics, and the environmental characteristics respectively affecting the corresponding steering intention, and the probability of the fusion feature affecting the steering intention, so as to determine the target steering intention with the highest probability; where the fusion feature is a feature obtained by fusing the motion characteristics, the driving behavior characteristics, and the environmental characteristics.

[0007] In an alternative manner, calculating the probability of each steering intention according to the probabilities of the motion feature, the driving behavior feature, and the environmental feature respectively affecting the corresponding steering intention, and the probability of the fusion feature affecting the steering intention, includes: traversing each steering intention, multiplying the probabilities of the motion feature, the driving behavior feature, and the environmental feature respectively affecting the currently traversed steering intention by their respective corresponding weight coefficients to obtain a plurality of products; dividing the sum of the plurality of products by the probability of the fusion feature affecting the currently traversed steering intention to obtain the probability of the currently traversed steering intention, so as to obtain the probabilities of each steering intention.

[0008] In an alternative manner, calculating the current safety distance between the target vehicle and the other vehicle according to the current distance between the target vehicle and the intersection of the trajectory, and the driving parameters of the target vehicle and the other vehicle, includes: calculating the collision occurrence duration according to the current distance between the target vehicle and the intersection of the trajectory and the current vehicle speed of the target vehicle; wherein, the collision occurrence duration represents the duration required for the target vehicle to travel from the current position to the intersection of the trajectory at the current vehicle speed in the case where the other vehicle stops moving; calculating the current safety distance between the target vehicle and the other vehicle according to the relative speed between the target vehicle and the other vehicle, the collision occurrence duration, the braking reaction duration of the target vehicle, the road friction coefficient, and the gravitational acceleration.

[0009] In an alternative manner, calculating the current safety distance between the target vehicle and the other vehicle according to the relative speed between the target vehicle and the other vehicle, the collision occurrence duration, the braking reaction duration of the target vehicle, the road friction coefficient, and the gravitational acceleration, includes: multiplying the relative speed between the target vehicle and the other vehicle by the sum of the collision occurrence duration and the current compensation factor to obtain a first value; dividing the square value of the relative speed by the product of the road friction coefficient and the gravitational acceleration to obtain a second value; taking the sum of the first value and the second value as the current safety distance between the target vehicle and the other vehicle.

[0010] In an alternative manner, determining the corresponding avoidance strategy according to the difference between the current distance and the current safety distance, includes: if the difference is less than or equal to the first preset difference and greater than the second preset difference, the avoidance strategy represents sending a prompt voice to each vehicle for warning; wherein, the first preset difference is greater than the second preset difference; if the difference is less than or equal to the second preset difference, determining the decelerating vehicle based on the priorities of each vehicle, and the avoidance strategy represents sending a deceleration instruction to the decelerating vehicle and sending a prompt voice to each vehicle for warning.

[0011] In an alternative approach, determining the trajectory intersection point based on the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles includes: unifying the coordinates of the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles to obtain the position coordinates of each point in each predicted trajectory; and taking the points with the same position coordinates in the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles as the trajectory intersection points.

[0012] According to another aspect of the present application, there is provided an apparatus for determining a vehicle avoidance strategy. The determining apparatus includes: a steering intention determination module for determining the target steering intention of the target vehicle based on the historical trajectory of the target vehicle, where the target steering intention is the steering intention with the highest steering probability of the target vehicle; a trajectory intersection point determination module for determining a trajectory intersection point based on the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles; a calculation module for calculating the current safety distance between the target vehicle and the other vehicles based on the current distance between the target vehicle and the trajectory intersection point and the driving parameters of the target vehicle and the other vehicles; and an avoidance strategy determination module for determining a corresponding avoidance strategy based on the difference between the current distance and the current safety distance.

[0013] According to one aspect of the present application, there is provided an electronic device including: a controller; and a memory for storing one or more programs, which when executed by the controller, perform the above-mentioned determination method.

[0014] According to one aspect of the present application, there is also provided a computer-readable storage medium having stored thereon computer-readable instructions, which when executed by a processor of a computer, cause the computer to perform the above-mentioned determination method.

[0015] According to one aspect of the present application, there is also provided a computer program product or a computer program. The computer program product or the computer program includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform the above-mentioned determination method.

[0016] This application takes into account the driving uncertainty among vehicles on the road to predict the driving trajectories of individual vehicles. Based on the historical trajectory of the target vehicle, the target steering intention with the highest steering probability is determined, and the predicted trajectory corresponding to the target steering intention (i.e., the driving trajectory with the highest probability of the target vehicle) and the trajectory intersection points with the predicted trajectories of other vehicles are used as potential collision points, and the current distance between the target vehicle and the trajectory intersection points is calculated. This application is not limited to the collision analysis of single vehicle data. By combining the driving influences of other vehicles, the current distance determined in real time and the driving parameters of the target vehicle and other vehicles are combined to calculate the current safety distance between the target vehicle and other vehicles, and according to the difference between the current distance and the current safety distance, the corresponding avoidance strategy is determined to ensure that relevant vehicles can avoid in real time and effectively and prevent collision accidents.

[0017] The above description is only an overview of the technical solution of this application. In order to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the specific embodiments of this application are specifically given below. Brief Description of the Drawings

[0018] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 is a schematic flowchart of a method for determining a vehicle avoidance strategy shown in an exemplary embodiment of this application.

[0020] Figure 2 is based on Figure 1 shown in the exemplary embodiment is a schematic flowchart of another method for determining a vehicle avoidance strategy.

[0021] Figure 3 is based on Figure 1 shown in the exemplary embodiment is a schematic flowchart of another method for determining a vehicle avoidance strategy.

[0022] Figure 4 is a schematic diagram of the application scenario of the method for determining the vehicle avoidance strategy of this application.

[0023] Figure 5 is a schematic diagram of the data flow direction between the road test unit and related vehicles shown in an exemplary embodiment of this application.

[0024] Figure 6 It is a schematic diagram of the data flow at the vehicle end shown in an exemplary embodiment of the present application.

[0025] Figure 7 It is a schematic structural diagram of a device for determining a vehicle avoidance strategy shown in an exemplary embodiment of the present application.

[0026] Figure 8 It is a schematic structural diagram of a computer system of an electronic device shown in an exemplary embodiment of the present application. Detailed implementation manners

[0027] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0028] The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0029] The flowcharts shown in the drawings are only exemplary descriptions, and do not necessarily include all contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined. Therefore, the actual execution order may change according to the actual situation.

[0030] As used in the present application, "a plurality of" means two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0031] The actual road conditions are very complex and there are various influencing factors. The related technology performs collision analysis based on the data collected by in-vehicle sensors, and the analyzed avoidance strategy cannot adapt to the complex road conditions, so the vehicle cannot perform effective anti-collision avoidance.

[0032] For this reason, one aspect of the present application provides a method for determining a vehicle avoidance strategy. Specifically, please refer to Figure 1 , Figure 1It is a schematic flowchart of a method for determining a vehicle avoidance strategy shown in an exemplary embodiment of the present application. The determination method at least includes S110 to S140, which are introduced in detail as follows:

[0033] S110: Based on the historical trajectory of the target vehicle, determine the target steering intention of the target vehicle; wherein, the target steering intention is the steering intention with the highest steering probability of the target vehicle.

[0034] The target vehicle and other vehicles in the present application are relative concepts. The target vehicle can be understood as the vehicle that the execution subject of the present application focuses on analyzing, and other vehicles are all other vehicles in the current scene road except the target vehicle. For example, in the current scene road, there are vehicles A, B, and C. If vehicle A is taken as the target vehicle, vehicles B and C are other vehicles.

[0035] The historical trajectory represents the driving trajectory of the target vehicle in the historical road scene that is the same as and / or similar to the current road scene. The target steering intention is derived from the predicted driving trajectory of the target vehicle.

[0036] Exemplarily, based on the historical trajectory of the target vehicle, predict the predicted driving trajectory of the target vehicle in the current road scene. Each predicted driving trajectory corresponds to a predicted probability. Take the steering intention of the target vehicle in the predicted driving trajectory with the highest predicted probability as the target steering intention.

[0037] S120: According to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles, determine the trajectory intersection points.

[0038] The predicted trajectory corresponding to the target steering intention is the trajectory with the highest predicted probability, that is, the most likely driving trajectory of the target vehicle. In this embodiment, it is analyzed with the predicted trajectories of other vehicles to determine the trajectory intersection points between the predicted trajectories, that is, the collision points where vehicle collision accidents may occur.

[0039] Exemplarily, unify the coordinates of the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles to obtain the position coordinates of each point in each predicted trajectory; take the points with the same position coordinates in the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles as the trajectory intersection points.

[0040] By unifying the predicted trajectory corresponding to the target steering intention with the predicted trajectories of each other vehicle into the same coordinate system, the target trajectory curve corresponding to the target steering intention and the other trajectory curves corresponding to other vehicles can be obtained, so as to quickly determine the intersection points between the target trajectory curve and the corresponding other trajectory curves, that is, the points with the same position coordinates, to obtain the trajectory intersection points between the corresponding predicted trajectories.

[0041] S130: Calculate the current safety distance between the target vehicle and other vehicles based on the current distance between the target vehicle and the intersection of the trajectory, as well as the driving parameters of the target vehicle and other vehicles.

[0042] The current distance is the distance between the position of the target vehicle at the current moment and the intersection of the trajectory. The current distance is a noun with a dynamic concept, and the value of the current distance changes as the position of the target vehicle at different moments varies.

[0043] The driving parameters include, but are not limited to, parameters characterizing the driving conditions of the corresponding vehicle, such as the vehicle speed, acceleration, motor speed, etc. In some embodiments, the driving parameters also include parameters affecting vehicle driving, such as the driving environment parameters of the corresponding vehicle.

[0044] The current safety distance characterizes the braking distance at which both the target vehicle and the corresponding other vehicle take corresponding braking measures, and no collision or just a collision occurs between the target vehicle and the other vehicle.

[0045] S140: Determine the corresponding avoidance strategy according to the difference between the current distance and the current safety distance.

[0046] If the current distance is greater than the current safety distance, it indicates that the probability of collision between the target vehicle and the corresponding other vehicle is relatively low. That is, the greater the difference between the current distance and the current safety distance, the less likely the target vehicle and the corresponding other vehicle are to collide. If the difference is smaller, the target vehicle and the corresponding other vehicle are more likely to collide.

[0047] Exemplarily, if the difference is less than or equal to the first preset difference and greater than the second preset difference, the avoidance strategy indicates sending a prompt voice to each vehicle for warning; where the first preset difference is greater than the second preset difference. This situation indicates that the probability of collision between the target vehicle and the corresponding other vehicle is not high, that is, there is a medium risk, and it is sufficient to give a voice warning to the relevant vehicles.

[0048] If the difference is less than or equal to the second preset difference, based on the priority of each vehicle, determine the decelerating vehicle, and the avoidance strategy indicates sending a deceleration instruction to the decelerating vehicle and sending a prompt voice to each vehicle for warning. This situation indicates that the probability of collision between the target vehicle and the corresponding other vehicle is relatively high. While giving a voice warning to each vehicle, an avoidance strategy indicating the relevant vehicle to decelerate can be sent to the corresponding vehicle to avoid collision between vehicles.

[0049] If the difference is greater than the first preset difference, it indicates that the probability of collision between the target vehicle and the corresponding other vehicle is almost zero, and no corresponding warning operation is required.

[0050] In some embodiments, it is also necessary to consider the driving priority of the vehicle. For example, ambulances, fire trucks, etc. have the highest driving priority, and the avoidance strategy can be adaptively adjusted to enable the vehicle with a higher driving priority to drive safely first while avoiding collisions.

[0051] This embodiment considers the driving uncertainty between vehicles on the road to predict the driving trajectories of each vehicle. Based on the historical trajectory of the target vehicle, the target steering intention with the highest steering probability is determined, and the predicted trajectory corresponding to the target steering intention (i.e., the driving trajectory with the highest probability of the target vehicle) and the trajectory intersection points of the predicted trajectories of other vehicles are used as the potential collision points, and the current distance between the target vehicle and the trajectory intersection points is calculated. This embodiment is not limited to the collision analysis of single vehicle data. Combining the driving influences of other vehicles, the currently determined current distance is combined with the driving parameters of the target vehicle and other vehicles respectively to calculate the current safety distance between the target vehicle and other vehicles, and the corresponding avoidance strategy is determined according to the difference between the current distance and the current safety distance to ensure real-time and effective avoidance of relevant vehicles and prevent collision accidents.

[0052] The related technology does not involve how to determine the target steering intention of the target vehicle. Therefore, in another exemplary embodiment of the present application, how to determine the target steering intention of the target vehicle based on the historical trajectory of the target vehicle is introduced in detail. For details, please refer to Figure 2 , Figure 2 is based on Figure 1 FIG. is a schematic flowchart of another method for determining a vehicle avoidance strategy shown in the exemplary embodiment. The determination method includes S210 to S220 in S110 as shown in Figure 1 FIG., which is introduced in detail as follows:

[0053] S210: Based on the historical trajectory of the target vehicle, determine the motion characteristics, driving behavior characteristics, and environmental characteristics of the target vehicle in the historical trajectory.

[0054] The motion characteristics represent the characteristics related to kinematic parameters with time series correlation. The kinematic parameters include but are not limited to parameters such as vehicle speed, acceleration, and heading angle. The motion characteristics in this embodiment represent the characteristics related to the kinematic parameters of the target vehicle at each historical moment in the historical trajectory.

[0055] The driving behavior characteristics represent the characteristics of the driver's driving behavior, which are related to the driver's operations. The driving behavior characteristics in this embodiment represent the characteristics of the driving behavior of the driver of the target vehicle in the historical trajectory.

[0056] Environmental features characterize the features of the surrounding environment of a vehicle during driving. For example, weather features, road features, surrounding vehicle features, etc. Among them, road features include, but are not limited to, lane lines, traffic signs, traffic lights, etc.

[0057] S220: Calculate the probability of each steering intention based on the probabilities of the motion feature, driving behavior feature, and environmental feature affecting the corresponding steering intention respectively, and the probability of the fusion feature affecting the steering intention, so as to determine the target steering intention with the highest probability; among them, the fusion feature is a feature obtained by fusing the motion feature, driving behavior feature, and environmental feature.

[0058] The fusion feature is a multi-dimensional matrix feature obtained by fusing the motion feature, driving behavior feature, and environmental feature, and this fusion feature will also affect the corresponding steering intention.

[0059] By analyzing different features in the historical trajectory to determine the influence of each feature on the steering intention, calculating the probability of each feature on the corresponding steering intention, and combining the probability of the fusion feature revealing the steering intention, the probability of each steering intention that the target vehicle may perform can be quickly calculated, and the steering intention with the highest probability is used as the target steering intention, that is, the steering intention that the target vehicle is most likely to execute in the current road scenario.

[0060] In some scenarios, the influence of each feature varies due to different scenarios. To meet the requirements of different scenarios, another exemplary embodiment of the present application introduces corresponding weight coefficients to adaptively adjust the influence of different features. The above S220 includes: traversing each steering intention, multiplying the probabilities of the motion feature, driving behavior feature, and environmental feature affecting the currently traversed steering intention by their respective corresponding weight coefficients to obtain multiple products; dividing the sum of the multiple products by the probability of the fusion feature affecting the current steering intention to obtain the probability of the current steering intention, so as to obtain the probabilities of each steering intention.

[0061] By traversing, the probability of each steering intention can be calculated without omission. According to the following causal inference probability model of motion-behavior-environment interaction, the probability of each steering intention can be calculated:

[0062] P(I|D,B,C)=(0.5P(D|I)+0.3P(B|I)+0.2(C|I)) / P(D,B,C);

[0063] Among them, P(I|D,B,C) represents the turning intention probability; I represents the turning intention (discrete states: left turn / right turn / keep straight); D represents the motion characteristics; P(D|I) represents the probability that the motion characteristics affect the turning intention; B represents the driving behavior characteristics; P(B|I) represents the probability that the driving behavior characteristics affect the turning intention; C represents the environmental characteristics, and P(C|I) represents the probability that the environmental characteristics affect the turning intention; P(D,B,C) represents the fused characteristics constructed from the motion characteristics, driving behavior characteristics, and environmental characteristics, which are the characteristics affecting the turning probability; 0.5, 0.3, and 0.2 are the weight coefficients corresponding to the motion characteristics, driving behavior characteristics, and environmental characteristics respectively. The specific weight coefficients can be adaptively adjusted according to the scenario requirements, and the present application does not limit their specific values.

[0064] This embodiment provides a method for calculating the probability of the turning intention, which fully considers the influence probabilities between the motion characteristics, driving behavior characteristics, environmental characteristics and the turning intention, so as to calculate the probability of each turning intention and determine the target turning intention with the highest probability.

[0065] The related technologies focus on the analysis of the parameters of the target vehicle itself to determine the corresponding safety distance, lacking the consideration of other factors.

[0066] Therefore, in another exemplary embodiment of the present application, how to calculate the current safety distance between the target vehicle and other vehicles according to the current distance between the target vehicle and the intersection of the trajectory, and the driving parameters of the target vehicle and other vehicles is introduced in detail. For specific details, please refer to Figure 3 , Figure 3 is based on Figure 1 FIG. shows a schematic flowchart of another method for determining a vehicle avoidance strategy shown in the exemplary embodiment. The determination method includes S310 to S320 in S130 as shown in Figure 1 FIG., and is introduced in detail as follows:

[0067] S310: Calculate the collision occurrence duration according to the current distance between the target vehicle and the intersection of the trajectory and the current vehicle speed of the target vehicle; wherein, the collision occurrence duration represents the duration required for the target vehicle to travel from the current position to the intersection of the trajectory at the current vehicle speed in the case where other vehicles stop moving.

[0068] The collision occurrence duration is the duration required for the target vehicle to travel to the intersection of the trajectory at the current vehicle speed calculated without considering the movement of other vehicles (that is, by default, other vehicles are in a stationary state from the current moment). Exemplarily, the current distance is 200m and the current vehicle speed is 20km / h, and the collision occurrence duration = 200m ÷ 20km / h = 0.01s.

[0069] S320: Calculate the current safety distance between the target vehicle and other vehicles based on the relative speed between the target vehicle and other vehicles, the collision duration, the braking reaction duration of the target vehicle, the road friction coefficient, and the acceleration due to gravity.

[0070] Relative speed between the target vehicle and other vehicles: If the driving directions of the target vehicle and other vehicles are opposite, the relative speed = V 目标 +V 其它 ; If the driving directions of the target vehicle and other vehicles are the same, the relative speed = V 目标 -V 其它 .

[0071] The braking reaction duration represents the duration from when the vehicle detects danger and starts braking until the braking system fully takes effect, that is, the braking system delay duration.

[0072] The road friction coefficient is the adhesion coefficient between the vehicle tires and the ground in the current road scenario, reflecting the braking efficiency of the vehicle.

[0073] Exemplarily, multiply the relative speed between the target vehicle and other vehicles by the sum of the collision duration and the current compensation factor to obtain a first value; divide the square value of the relative speed by the product of the road friction coefficient and the acceleration due to gravity to obtain a second value; take the sum of the first value and the second value as the current safety distance between the target vehicle and other vehicles.

[0074] The current safety distance is calculated according to the following formula: d safe = v rel ×(TTC + Δt)+ v rel 2 / 2μg; where, d safe represents the current safety distance between the target vehicle and other vehicles; v rel represents the relative speed between the target vehicle and other vehicles; TTC represents the collision duration; Δt represents the braking reaction duration; μ represents the road friction coefficient; g represents the acceleration due to gravity.

[0075] This embodiment provides a method for calculating the current safety distance between the target vehicle and other vehicles, introducing the respective driving parameters of the target vehicle and other vehicles, as well as the road friction coefficient related to the current road scenario, not limited to the single - type analysis of the target vehicle, fully considering the driving states of relevant vehicles and the road state, making the calculated current safety distance more adaptable to the current road scenario.

[0076] In another exemplary embodiment of the present application, an exemplary description of the application scenarios of the above - mentioned multiple determination methods is provided. For details, please refer to Figure 4 , Figure 4It is a schematic diagram of the application scenario of the method for determining the vehicle avoidance strategy of the present application. Among them, it includes a target vehicle 100, other vehicles 200, and a server 300. The three parties can be connected by wireless communication. The present application does not limit the connection method between them.

[0077] The server 300 serves as the execution subject of the determination method shown in any of the above exemplary embodiments to execute any determination method. The exemplary description is as follows:

[0078] The server 300 determines the target steering intention of the target vehicle 100 based on the historical trajectory of the target vehicle 100. Among them, the target steering intention is the steering intention with the highest steering probability of the target vehicle 100. The server 300 determines the trajectory intersection point according to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles 200. The server 300 calculates the current safety distance between the target vehicle 100 and other vehicles 200 according to the current distance between the target vehicle 100 and the trajectory intersection point, as well as the driving parameters of the target vehicle 100 and other vehicles 200. The server 300 determines the corresponding avoidance strategy according to the difference between the current distance and the current safety distance.

[0079] The server 300 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. Among them, multiple servers can form a blockchain, and the server is a node on the blockchain. The server 300 can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. This is not limited here either.

[0080] The server 300 can be as Figure 5 shown and placed in the roadside unit of a complex road to determine the corresponding avoidance strategy in real time and send it to relevant vehicles for collision warning. In some embodiments, the roadside unit processes multi-vehicle data in real time through a lightweight model (such as MobileNet) to reduce cloud dependence (response latency ≤ 30ms). The target vehicle 100 and other vehicles 200 can send relevant data to the server 300 of the roadside unit to enable the server 300 to dynamically calibrate and train the lightweight model. For example, if the deviation between the actual TTC and the predicted value of the server 300 is greater than 20%, the server 300 retrains the lightweight model. The roadside unit can also be provided with corresponding data acquisition devices. In bad weather such as rain and fog, the millimeter-wave radar point cloud data of the roadside unit is fused to compensate for the camera recognition error.

[0081] Please refer to Figure 6 ,Figure 6 It is a schematic diagram of the data flow at the vehicle end shown in an exemplary embodiment of the present application. The vehicle end controller can transfer data with the in-vehicle terminal through the CAN (Controller Area Network) bus. The in-vehicle terminal can communicate with the roadside unit through V2X (Vehicle to Everything) communication. The roadside unit can conduct 5G communication with the cloud. The server 300 in the roadside unit can analyze based on relevant data to determine corresponding avoidance strategies and send the corresponding avoidance strategies to relevant vehicles.

[0082] On the other hand, the present application also provides a device for determining a vehicle avoidance strategy, such as Figure 7 shown Figure 7 It is a schematic structural diagram of the device for determining a vehicle avoidance strategy shown in an exemplary embodiment of the present application. The determination device 700 includes:

[0083] A steering intention determination module 710, configured to determine the target steering intention of the target vehicle based on the historical trajectory of the target vehicle; wherein, the target steering intention is the steering intention with the highest steering probability of the target vehicle.

[0084] A trajectory intersection determination module 730, configured to determine the trajectory intersection according to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles.

[0085] A calculation module 750, configured to calculate the current safety distance between the target vehicle and other vehicles according to the current distance between the target vehicle and the trajectory intersection, and the driving parameters of the target vehicle and other vehicles.

[0086] An avoidance strategy determination module 770, configured to determine the corresponding avoidance strategy according to the difference between the current distance and the current safety distance.

[0087] In another exemplary embodiment, the steering intention determination module 710 includes:

[0088] A determination unit, configured to determine the motion characteristics, driving behavior characteristics, and environmental characteristics of the target vehicle in the historical trajectory based on the historical trajectory of the target vehicle.

[0089] A calculation and determination unit, configured to calculate the probability of each steering intention according to the probabilities of the motion characteristics, driving behavior characteristics, and environmental characteristics respectively affecting the corresponding steering intention, and the probability of the fused characteristics affecting the steering intention, so as to determine the target steering intention with the highest probability; wherein, the fused characteristics are the characteristics obtained by fusing the motion characteristics, driving behavior characteristics, and environmental characteristics.

[0090] In another exemplary embodiment, the calculation and determination unit includes:

[0091] A traversal module, configured to traverse each steering intention, multiply the probabilities of the motion feature, driving behavior feature, and environmental feature respectively affecting the current traversed steering intention by their respective corresponding weight coefficients to obtain multiple products.

[0092] A calculation module, configured to divide the sum of the multiple products by the probability of the fusion feature affecting the current steering intention to obtain the probability of the current steering intention, so as to obtain the probabilities of each steering intention.

[0093] In another exemplary embodiment, the calculation module 750 includes:

[0094] A collision occurrence duration calculation unit, configured to calculate the collision occurrence duration according to the current distance between the target vehicle and the trajectory intersection point and the current vehicle speed of the target vehicle; wherein, the collision occurrence duration represents the duration required for the target vehicle to travel from the current position to the trajectory intersection point at the current vehicle speed in the case where other vehicles stop moving.

[0095] A current safety distance calculation unit, configured to calculate the current safety distance between the target vehicle and other vehicles according to the relative speed between the target vehicle and other vehicles, the collision occurrence duration, the braking reaction duration of the target vehicle, the road friction coefficient, and the gravitational acceleration.

[0096] In another exemplary embodiment, the current safety distance calculation unit includes:

[0097] A first calculation module, configured to multiply the relative speed between the target vehicle and other vehicles by the sum of the collision occurrence duration and the current compensation factor to obtain a first value.

[0098] A second calculation module, configured to divide the square value of the relative speed by the product of the road friction coefficient and the gravitational acceleration; to obtain a second value.

[0099] A third calculation module, configured to use the sum of the first value and the second value as the current safety distance between the target vehicle and other vehicles.

[0100] In another exemplary embodiment, the avoidance strategy determination module 770 includes:

[0101] A first avoidance strategy unit, configured to, if the difference is less than or equal to a first preset difference and greater than a second preset difference, the avoidance strategy represents sending a prompt voice to each vehicle for warning; wherein, the first preset difference is greater than the second preset difference.

[0102] A second avoidance strategy unit, which is configured to, if the difference is less than or equal to a second preset difference, determine decelerating vehicles based on the priorities of the respective vehicles. The avoidance strategy is to send a deceleration instruction to the decelerating vehicles and send a prompt voice to each vehicle for warning.

[0103] In another exemplary embodiment, the trajectory intersection determination module 730 includes:

[0104] A unification unit, which is configured to unify the coordinate systems of the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles, so as to obtain the position coordinates of each point in each predicted trajectory.

[0105] A trajectory intersection determination unit, which is configured to use the points with the same position coordinates in the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles as trajectory intersections.

[0106] The determination device of the present application takes into account the driving uncertainty between vehicles on the road to predict the driving trajectories of the respective vehicles. Based on the historical trajectory of the target vehicle, the target steering intention with the highest steering probability is determined, and the predicted trajectory corresponding to the target steering intention (i.e., the most probable driving trajectory of the target vehicle) and the trajectory intersections in the predicted trajectories of other vehicles are determined as the potential collision points where collisions may occur, and the current distance between the target vehicle and the trajectory intersections is calculated. The determination device of the present application is not limited to the collision analysis of single vehicle data. By combining the driving influence of other vehicles, the current distance determined in real time and dynamically is combined with the driving parameters of the target vehicle and other vehicles to calculate the current safety distance between the target vehicle and other vehicles, and corresponding avoidance strategies are determined according to the difference between the current distance and the current safety distance, so as to ensure that the vehicle can make real-time and effective avoidance and prevent collision accidents.

[0107] It should be noted that the determination device provided in the above embodiment and the determination method provided in the foregoing embodiment belong to the same concept. The specific manners in which each module and unit perform operations have been described in detail in the method embodiment and will not be elaborated here.

[0108] On the other hand, the present application also provides an electronic device, including: a controller; a memory for storing one or more programs, which, when executed by the controller, are configured to execute the above determination method.

[0109] Please refer to Figure 8 , Figure 8 which is a schematic structural diagram of a computer system of an electronic device shown in an exemplary embodiment of the present application, showing a schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiment of the present application.

[0110] It should be noted that Figure 8The computer system 800 of the illustrated electronic device is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.

[0111] As Figure 8 shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to the programs stored in the read-only memory (ROM) 802 or the programs loaded from the storage section 808 into the random access memory (RAM) 803, such as executing the methods in the above embodiments. In the RAM 803, various programs and data required for system operation are also stored. The CPU 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0112] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as required. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as required so that the computer program read from it can be installed into the storage section 808 as required.

[0113] Specifically, according to the embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments of the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, various functions defined in the system of the present application are executed.

[0114] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0116] The units involved in the embodiments of the present application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the units themselves.

[0117] Another aspect of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned determination method is implemented. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist alone without being assembled into the electronic device.

[0118] Another aspect of the present application further provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the determination method provided in the above various embodiments.

[0119] According to one aspect of the embodiments of the present application, a computer system is further provided, including a central processing unit (CPU), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage part into a random access memory (RAM), such as executing the method in the above embodiments. In the RAM, various programs and data required for system operation are also stored. The CPU, ROM, and RAM are connected to each other through a bus. An input / output (I / O) interface is also connected to the bus.

[0120] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication part performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as required. A removable medium, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive as required, so that a computer program read from it can be installed into the storage part as required.

[0121] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation of the present application. Those of ordinary skill in the art can make corresponding adaptations or modifications very conveniently according to the main concept and spirit of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope required by the claims.

Claims

1. A method for determining a vehicle avoidance strategy, characterized in that The determination method includes: Based on the historical trajectory of the target vehicle, determining the target steering intention of the target vehicle; wherein, the target steering intention is the steering intention with the highest steering probability of the target vehicle; Determining a trajectory intersection point according to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles; Calculating the current safety distance between the target vehicle and the other vehicle according to the current distance between the target vehicle and the trajectory intersection point, and the driving parameters of the target vehicle and the other vehicle; Determining a corresponding avoidance strategy according to the difference between the current distance and the current safety distance.

2. The determination method according to claim 1, characterized in that The determining the target steering intention of the target vehicle based on the historical trajectory of the target vehicle includes: Based on the historical trajectory of the target vehicle, determining the motion characteristics, driving behavior characteristics, and environmental characteristics of the target vehicle in the historical trajectory; Calculating the probability of each steering intention according to the probabilities of the motion characteristics, the driving behavior characteristics, and the environmental characteristics respectively affecting the corresponding steering intentions, and the probability of the fusion feature affecting the steering intention, so as to determine the target steering intention with the highest probability; wherein, the fusion feature is a feature obtained by fusing the motion characteristics, the driving behavior characteristics, and the environmental characteristics.

3. The determination method according to claim 2, characterized in that, The calculating the probability of each steering intention according to the probabilities of the motion characteristics, the driving behavior characteristics, and the environmental characteristics respectively affecting the corresponding steering intentions, and the probability of the fusion feature affecting the steering intention includes: Traversing each steering intention, multiplying the probabilities of the motion characteristics, the driving behavior characteristics, and the environmental characteristics respectively affecting the currently traversed steering intention by their respective corresponding weight coefficients to obtain a plurality of products; Dividing the sum of the plurality of products by the probability of the fusion feature affecting the current steering intention to obtain the probability of the current steering intention, so as to obtain the probabilities of each steering intention.

4. The determination method according to claim 1, characterized in that The calculating the current safety distance between the target vehicle and the other vehicle according to the current distance between the target vehicle and the trajectory intersection point, and the driving parameters of the target vehicle and the other vehicle includes: Calculating the collision occurrence duration according to the current distance between the target vehicle and the trajectory intersection point and the current vehicle speed of the target vehicle; wherein, the collision occurrence duration represents the duration required for the target vehicle to travel from the current position to the trajectory intersection point at the current vehicle speed in the case where the other vehicle stops moving; Calculating the current safety distance between the target vehicle and the other vehicle according to the relative speed between the target vehicle and the other vehicle, the collision occurrence duration, the braking reaction duration of the target vehicle, the road friction coefficient, and the gravitational acceleration.

5. The determination method according to claim 4, wherein The calculating the current safety distance between the target vehicle and the other vehicle according to the relative speed between the target vehicle and the other vehicle, the collision occurrence duration, the braking reaction duration of the target vehicle, the road friction coefficient, and the gravitational acceleration includes: Multiply the relative speed between the target vehicle and the other vehicle by the sum of the collision occurrence duration and the current compensation factor to obtain a first value; Divide the square value of the relative speed by the product of the road friction coefficient and the acceleration due to gravity to obtain a second value; Take the sum of the first value and the second value as the current safety distance between the target vehicle and the other vehicle.

6. The determination method according to any one of claims 1 to 5, characterized in that, Determine a corresponding avoidance strategy according to the difference between the current distance and the current safety distance, including: If the difference is less than or equal to the first preset difference and greater than the second preset difference, the avoidance strategy indicates sending a prompt voice to each vehicle for warning; wherein, the first preset difference is greater than the second preset difference; If the difference is less than or equal to the second preset difference, determine a decelerating vehicle based on the priorities of each vehicle, and the avoidance strategy indicates sending a deceleration instruction to the decelerating vehicle and sending a prompt voice to each vehicle for warning.

7. The determination method according to any one of claims 1 to 5, characterized in that, Determine a trajectory intersection point according to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles, including: Unify the coordinates of the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles to obtain the position coordinates of each point in each predicted trajectory; Take the points with the same position coordinates in the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles as the trajectory intersection points.

8. An apparatus for determining a vehicle avoidance strategy, characterized in that, The determining device includes: A steering intention determining module, configured to determine the target steering intention of the target vehicle based on the historical trajectory of the target vehicle; wherein, the target steering intention is the steering intention with the highest steering probability of the target vehicle; A trajectory intersection point determining module, configured to determine a trajectory intersection point according to the predicted trajectory corresponding to the target steering intention and the predicted trajectories of other vehicles; A calculation module, configured to calculate the current safety distance between the target vehicle and the other vehicle according to the current distance between the target vehicle and the trajectory intersection point and the driving parameters of the target vehicle and the other vehicle; An avoidance strategy determining module, configured to determine a corresponding avoidance strategy according to the difference between the current distance and the current safety distance.

9. An electronic device, characterized in that, Including: A controller; A memory, configured to store one or more programs, and when the one or more programs are executed by the controller, enable the controller to implement the determining method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, enable the computer to execute the determining method according to any one of claims 1 to 7.

Images