Driving trajectory determination method, device, equipment and storage medium

Abstract

The embodiments of the present application disclose a method, apparatus, device, and storage medium for determining a driving trajectory, which can be applied to fields such as cloud computing, road traffic, and maps. The method includes: determining the driving information of each vehicle when entering a second road area within a first road area during a preset period; based on the driving information of each vehicle when entering the second road area, determining the driving information of each vehicle at each moment, where the driving information of each vehicle at any moment includes the driving speed at the corresponding moment and the first displacement within the second road area up to the corresponding moment; determining the positioning information of at least one first vehicle among the vehicles at each moment during the driving process in the second road area; based on the positioning information of each first vehicle at each moment, the driving speed of each vehicle at each moment, and the first displacement, determining the driving trajectory of each vehicle in the second road area. By adopting the embodiments of the present application, the driving trajectory of a vehicle within a certain road area can be accurately determined.

Description

Technical Field

[0001] The present application relates to the field of road traffic, and particularly to a method, apparatus, device, and storage medium for determining a driving trajectory. Background Art

[0002] Currently, in many fields, it is necessary to determine the driving trajectory of a vehicle. For example, in the field of autonomous driving, it is necessary to accurately know the driving trajectory of the vehicle to accurately analyze the performance of autonomous driving. For example, in the logistics and transportation industry, the logistics trajectory can be determined through the vehicle driving trajectory, and so on.

[0003] In the prior art, the driving trajectory of a vehicle is often directly determined based on the positioning information of the vehicle, or is determined based on the relevant data reported by an inertial sensor. However, for multiple vehicles driving in a certain road area, if there are vehicles that cannot upload positioning information and vehicles not equipped with inertial sensors, the prior art often cannot determine the driving trajectories of such vehicles in the target road area. Summary of the Invention

[0004] The embodiments of the present application provide a method, apparatus, device, and storage medium for determining a driving trajectory, which can accurately determine the driving trajectory of a vehicle in a certain road area and has high applicability.

[0005] On the one hand, the embodiments of the present application provide a method for determining a driving trajectory, and the method includes:

[0006] Determine the driving information of each vehicle when it enters a second road area within a first road area during a preset period;

[0007] Based on the driving information of each of the above vehicles when entering the above second road area, determine the driving information of each of the above vehicles at each moment during the driving process in the above second road area. The driving information of each of the above vehicles at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the above second road area up to the corresponding moment; wherein, the above first road area is connected to the above second road area;

[0008] Determine the positioning information of at least one first vehicle among each of the above vehicles at each moment during the driving process in the above second road area;

[0009] Based on the positioning information of each of the above first vehicles at each moment during the driving process in the above second road area, the driving speed and the first displacement of each of the above vehicles at each moment during the driving process in the above second road area, determine the driving trajectories of each of the above vehicles in the above second road area.

[0010] On the other hand, the embodiments of the present application provide a device for determining a driving trajectory, and the device for determining a driving trajectory includes:

[0011] A driving information determination module, configured to determine the driving information of each vehicle when it enters a second road area within a first road area during a preset time period;

[0012] The above-mentioned driving information determination module is configured to determine the driving information of each vehicle at each moment during the driving process in the second road area based on the driving information of each vehicle when it enters the second road area. The driving information of each vehicle at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the second road area up to the corresponding moment; wherein, the first road area is connected to the second road area;

[0013] A positioning information determination module, configured to determine the positioning information of at least one first vehicle among each vehicle at each moment during the driving process in the second road area;

[0014] A driving trajectory determination module, configured to determine the driving trajectories of each vehicle in the second road area based on the positioning information of each first vehicle at each moment during the driving process in the second road area, the driving speed and the first displacement of each vehicle at each moment during the driving process in the second road area.

[0015] On the other hand, an embodiment of the present application provides an electronic device, including a processor and a memory, and the processor and the memory are connected to each other;

[0016] The above-mentioned memory is used to store a computer program;

[0017] The above-mentioned processor is configured to execute the driving trajectory determination method provided by the embodiment of the present application when calling the above-mentioned computer program.

[0018] On the other hand, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the driving trajectory determination method provided by the embodiment of the present application.

[0019] On the other hand, an embodiment of the present application provides a computer program product, which includes a computer program, and the above-mentioned computer program implements the driving trajectory determination method provided by the embodiment of the present application when executed by a processor.

[0020] In the embodiment of the present application, by determining the driving information of each vehicle when it enters the second road area, the displacement and driving speed corresponding to each moment during the driving process of each vehicle in the second road area can be determined. Thus, by combining the positioning information of some vehicles at each moment during the driving process in the second road and based on the displacement and driving speed corresponding to each moment during the driving process of each vehicle in the second road area, the driving trajectories of all vehicles during the driving process in the second road area can be accurately determined, and the applicability is high. Brief Description of the Drawings

[0021] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0022] Figure 1 is a schematic diagram of a scenario of the driving trajectory determination method provided by an embodiment of the present application;

[0023] Figure 2 is a schematic flowchart of the driving trajectory determination method provided by an embodiment of the present application;

[0024] Figure 3 is a schematic diagram of the principle of the following - vehicle model provided by an embodiment of the present application;

[0025] Figure 4 is a schematic flowchart of determining the driving information of the first vehicle provided by an embodiment of the present application;

[0026] Figure 5 is a schematic flowchart of determining the driving information of the second vehicle provided by an embodiment of the present application;

[0027] Figure 6 is a spatio - temporal diagram of a vehicle trajectory provided by an embodiment of the present application;

[0028] Figure 7 is another spatio - temporal diagram of a vehicle trajectory provided by an embodiment of the present application;

[0029] Figure 8 is a flowchart framework diagram of the driving trajectory determination method provided by an embodiment of the present application;

[0030] Figure 9 is a schematic structural diagram of the driving trajectory determination device provided by an embodiment of the present application;

[0031] Figure 10 is a schematic structural diagram of the electronic device provided by an embodiment of the present application. Detailed Description of the Embodiments

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0033] The driving trajectory determination method provided by the embodiments of this application can be applied to the traffic field or the map field to determine the driving trajectory of a vehicle within a certain road area. For example, the driving trajectory determination method provided by the embodiments of this application can be applied to the Intelligent Traffic System (ITS) or the Intelligent Vehicle Infrastructure Cooperative Systems (IVICS) in the traffic field to determine the driving trajectory of a vehicle within the blind area of the vision of traffic shooting equipment.

[0034] Among them, the intelligent traffic system, also known as the Intelligent Transportation System, effectively integrates advanced scientific and technological means (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operations research, artificial intelligence, etc.) into transportation, service control, and vehicle manufacturing, strengthening the connection among vehicles, roads, and users, thereby forming an integrated transportation system that ensures safety, improves efficiency, improves the environment, and saves energy.

[0035] Among them, the intelligent vehicle-road collaborative system, abbreviated as the vehicle-road collaborative system, is a development direction of the intelligent traffic system (ITS). The vehicle-road collaborative system uses advanced wireless communication and new-generation Internet and other technologies to comprehensively implement dynamic real-time information interaction between vehicles and between vehicles and roads, and on the basis of the acquisition and fusion of full-time and full-space dynamic traffic information, conducts vehicle active safety control and road collaborative management, fully realizing the effective collaboration of people, vehicles, and roads, ensuring traffic safety, improving traffic efficiency, and thus forming a safe, efficient, and environmentally friendly road traffic system.

[0036] See Figure 1 , Figure 1 is a schematic diagram of a scenario of the driving trajectory determination method provided by the embodiments of this application. As Figure 1 shown, Figure 1 the first road area and the third road area in

[0037] Further, based on the driving information of each vehicle when entering the second road area, the driving information of each vehicle at each moment during the driving process in the second road area can be determined. For example, based on the driving information of vehicle A, vehicle B, and vehicle C when entering the second road area, the driving information of vehicle A, vehicle B, and vehicle C at each moment during the driving process in the second road area can be determined. Among them, the driving information of each vehicle at any moment includes the driving speed of the vehicle at the corresponding moment, and also includes the first displacement accumulated within the second road area up to the corresponding moment, that is, the driving displacement of the vehicle compared to the boundary between the first road area and the second road area at the corresponding moment.

[0038] Further, the positioning information of at least one first vehicle among the vehicles at each moment during the driving process in the second road area can be determined, and then based on the positioning information of each first vehicle at each moment, as well as the driving speed and the first displacement of each vehicle at each moment, the driving trajectories of each vehicle in the second road area can be determined. For example, if vehicle A is the first vehicle, the positioning information of vehicle A at each moment during the driving process in the second road area can be determined, and then based on the positioning information of vehicle A at each moment, and the driving information of vehicle A, vehicle B, and vehicle C at each moment, the driving trajectories of vehicle A, vehicle B, and vehicle C in the second road area can be determined, such as Figure 1 the driving trajectory of vehicle A in the second road area shown.

[0039] Among them, the driving trajectory determination method provided in the embodiments of the present application can be implemented by a server or a terminal. The server can be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart voice interaction device (such as a smart speaker), a wearable electronic device (such as a smart watch), a vehicle-mounted terminal, a smart home appliance (such as a smart TV), an AR / VR device, etc., but is not limited thereto.

[0040] See Figure 2 , Figure 2 which is a schematic flowchart of the driving trajectory determination method provided in the embodiments of the present application.

[0041] As Figure 2 shown, the driving trajectory determination method provided in the embodiments of the present application specifically may include the following steps:

[0042] Step S21: Determine the driving information of each vehicle in the first road area when entering the second road area within a preset time period.

[0043] In some feasible embodiments, the first road area and the second road area are connected areas. For example, the first road area is the area captured by a traffic shooting device, and the second road area is the road area corresponding to the shooting blind area of the traffic shooting device. For another example, the first road area and the second road area can be two adjacent areas in any road, which can be specifically determined based on the requirements of the actual application scenario and are not limited herein.

[0044] For the vehicles that appear in the first road area within a preset time period, the driving information of each vehicle when entering the second road area can be determined, that is, the driving information of the vehicles in the first road area when leaving the first road area can be determined.

[0045] Specifically, the driving information of each vehicle when entering the second road area can be determined through the continuous images or traffic videos of each vehicle when driving in the first road area, or the driving information of each vehicle when entering the second road area can be determined and uploaded based on the driving information acquisition device located at the junction of the first road area and the second road area when each vehicle enters the second road area.

[0046] Among them, the above implementation methods for determining the driving information of each vehicle when entering the second road area are only examples, which can be specifically determined based on the requirements of the actual application scenario and are not limited herein.

[0047] Among them, the vehicles in the first road area can be determined by using an image recognition algorithm to recognize vehicles in the traffic video or traffic image corresponding to the first road area, and after recognizing the vehicles in the first road area, each vehicle is marked to distinguish different vehicles in the first road area.

[0048] Among them, the driving information of each vehicle when entering the second road area includes the driving speed of each vehicle when entering the second road area.

[0049] Optionally, the driving information of each vehicle when entering the second road area further includes at least one of the lane where it is located, acceleration, and driving association relationship with other vehicles.

[0050] Optionally, the driving association relationship between each vehicle and any other vehicle includes at least one of a speed association relationship or a vehicle distance association relationship.

[0051] Among them, the speed association relationship includes the speed difference between vehicles, and the vehicle distance association relationship includes the distance between vehicles, including but not limited to the headway, the distance between the rear of the leading vehicle and the head of the following vehicle, or the tail distance, etc.

[0052] Optionally, the driving information of each vehicle when entering the second road area may further include information such as the body length of each vehicle, which can be specifically determined based on the requirements of the actual application scenario and are not limited herein.

[0053] Step S22: Based on the driving information of each vehicle when entering the second road area, determine the driving information of each vehicle at each moment during the driving process in the second road area. The driving information of each vehicle at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the second road area up to the corresponding moment.

[0054] In some feasible implementation manners, when determining the driving information of each vehicle at each moment during the driving process in the second road area based on the driving information of each vehicle when entering the second road area, the driving information of each vehicle at the next moment during the driving process in the second road area can be determined based on the driving information of each vehicle at each moment during the driving process in the second road area. That is to say, the driving information of each vehicle at each moment during the driving process in the second road area is determined based on the driving information of each vehicle at the previous moment during the driving process in the second road area at that moment.

[0055] Among them, the driving information of each vehicle at each moment during the driving process in the second road area includes the driving speed of each vehicle at the corresponding moment and the displacement within the second road area up to each moment, that is, the displacement traveled by each vehicle from the start of entering the second road area to each moment.

[0056] Optionally, the driving information of each vehicle at each moment during the driving process in the second road area further includes at least one of the lane where the vehicle is located, the acceleration, and the driving association relationship with other vehicles at each moment.

[0057] Optionally, the driving association relationship between each vehicle and any other vehicle includes at least one of a speed association relationship or a vehicle distance association relationship.

[0058] Among them, the speed association relationship includes the speed difference between vehicles, and the vehicle distance association relationship includes the vehicle distance, including but not limited to the headway, the distance between the rear of the leading vehicle and the front of the following vehicle, or the tail distance, etc.

[0059] Among them, the driving association relationship between each vehicle and any other vehicle can be determined based on relevant information such as the first displacement, driving speed, and lane where the vehicle is located at the corresponding moment, and no limitation is made here.

[0060] Optionally, the driving information of each vehicle at each moment during the driving process in the second road area may further include information such as the vehicle body length of each vehicle, which can be specifically determined according to the requirements of the actual application scenario, and no limitation is made here.

[0061] As an example, vehicle A, vehicle B, and vehicle C enter the second road area. For vehicle A, the driving information of vehicle A at each moment during the driving process in the second road area includes the driving speed of vehicle A at that moment and the first displacement during the driving process in the second road area up to that moment.

[0062] Among them, the driving information of vehicle A at each moment during the driving process in the second road area may further include at least one or more of the lane where vehicle A is located, the acceleration of vehicle A, the speed difference between vehicle A and vehicle B, the speed difference between vehicle A and vehicle C, the vehicle distance between vehicle A and vehicle B, the vehicle distance between vehicle A and vehicle C, and the body length of vehicle A.

[0063] Based on this, the driving information of each vehicle at each moment during the driving process in the second road area can be analyzed to obtain the driving information of each vehicle at the next moment during the driving process in the second road area.

[0064] In some feasible implementation manners, when determining the driving information of each vehicle at the next moment based on the driving information of each vehicle at each moment during the driving process in the second road area, it is also possible to first determine the driving behavior of each vehicle corresponding to the next moment from that moment based on the driving information of each vehicle at each moment during the driving process in the second road area.

[0065] That is, based on the driving information of each vehicle at each moment during the driving process in the second road area, predict the driving behavior of each vehicle corresponding to the next moment from that moment, and thus determine the driving information of each vehicle at the next moment based on the driving behavior of each vehicle corresponding to the next moment from that moment and the driving information of each vehicle at that moment.

[0066] Among them, the above driving behaviors include at least one of accelerating, decelerating, driving at a constant speed, turning left, stopping, turning right, changing lanes, overtaking, driving when the distance from the vehicle in front in the same lane is greater than or equal to the first threshold, and driving when the distance from the vehicle in front in the same lane is less than the first threshold and greater than the second threshold.

[0067] Among them, the above first threshold is greater than the second threshold. When the distance between a vehicle and the vehicle in front in the same lane is greater than or equal to the first threshold, it indicates that the distance between the vehicle and the vehicle in front in the same lane is relatively large. Furthermore, the vehicle can be in a free driving state, that is, the driving speed is not restricted by the vehicle in front in the same lane. When the distance between the vehicle and the vehicle in front in the same lane is less than the first threshold and greater than the second threshold, it indicates that the distance between the vehicle and the vehicle in front in the same lane is within a certain range. At this time, the vehicle needs to maintain a following driving state behind the vehicle in front in the same lane. When the distance between the vehicle and the vehicle in front in the same lane is less than the second threshold, it indicates that the distance between the vehicle and the vehicle in front in the same lane is relatively small, and the vehicle needs to decelerate or stop to avoid vehicle collisions.

[0068] In other words, for each vehicle, based on the driving information of each vehicle at each moment during the driving process in the second road area, such as acceleration, driving speed, the lane where it is located, as well as the speed correlation relationship and distance correlation relationship between each vehicle, the next driving behavior of each vehicle can be determined, such as accelerating, decelerating, changing lanes, etc. Furthermore, by analyzing the driving information of each vehicle at each moment and the next driving behavior during the driving process in the second road area, the driving information of each vehicle at the next moment during the driving process in the second road area can be obtained.

[0069] Optionally, the process of determining the driving information of each vehicle at the next moment during the driving process in the second road area based on the driving information of each vehicle at each moment during the driving process in the second road area can be implemented based on a trained following model.

[0070] Among them, the following model models the driving behavior of vehicles from the perspective of traffic engineering, focusing on the expression of microscopic driving behavior and the calibration of microscopic data. Based on the analysis of the influence of various external factors on the following behavior of drivers, a reasonable model structure can conform to the actual observed data microscopically. Among them, according to different modeling ideas, the following models from the perspective of traffic engineering can include but are not limited to stimulus-response models, safe distance models, psycho-physiological models, and artificial intelligence models. The stimulus-response models and safe distance models regard the human-vehicle system as a unified entity and use precise kinematic or dynamic formulas to describe the vehicle operation trajectory, which have wide application value in the fields of traffic simulation and intelligent vehicles. The psycho-physiological models and artificial intelligence models, on the other hand, consider more the description and modeling of the psychological reaction characteristics of drivers, and the human factor in the following behavior is more reflected in the models.

[0071] Among them, the car-following models in the embodiments of the present application include, but are not limited to, the Wiedermann model (Wiedermann74 or Wiedermann99), Pitt model, Gipps model, Fritzsche model, VanAerde model, etc. They can also be related models obtained based on the distributed adaptive control method, deep Q-learning network, or cellular automation method, which can be specifically determined based on the actual application scenario requirements and are not limited herein.

[0072] For example, taking the Wiedermann model as an example, the Wiedermann model is a physiological-psychological car-following decision-making model, also known as the Action Point (AP) model. The Wiedermann model uses a series of thresholds and expected distances to reflect people's sensations and reactions. These boundary values delimit different value ranges, and in different value ranges, there are different influence relationships between the following vehicle and the leading vehicle.

[0073] As Figure 3 shown, Figure 3 is a schematic diagram of the principle of the car-following model provided by the embodiments of the present application. As Figure 3 shown, SDX represents the maximum car-following distance boundary. When the vehicle exceeds this boundary, it is in a free driving state. SDV or CLDV represents the boundary of approaching the leading vehicle, and OPDV represents the boundary of the speed difference when the speed of the vehicle is less than that of the leading vehicle. The boundaries of SDV, SDX, OPDV, and ABX constitute the car-following area, and within this area, the vehicle is in a car-following state.

[0074] Among them, ABX = AX + BX, SDX = AX + EX + BX, CLDV = SDV + EX 2 , OPDV = CLDV * (-OPDV add -OPDV mult * NRND).

[0075] Among them, AX is the expected distance boundary between stationary vehicles. When the distance between the vehicle and the leading vehicle in the same lane is less than AX, it stops. AX = L + AX add + rnd1(0,1)AX mult Third, L is the length of the leading vehicle, AX add and AX mult are calibration parameters, and rnd1(0,1) is a random variable that follows a standard normal distribution. BX is an additional speed term, EX = EX add + EX mult*(NRND - rnd1(0,1), where NRND is the normal distribution coefficient, EX add and EX mult are calibration parameters. CX is a parameter that varies based on NRND and rnd1(0,1). Δv is the speed difference between the vehicle behind and the vehicle in front in the same lane, and Δx is the distance between the front of the vehicle in front and the front of the vehicle behind in the same lane. OPDV add and OPDV mult are calibration parameters.

[0076] Based on Figure 3 the car - following model shown above, based on the driving information of each vehicle at each moment during the driving process in the second road area, the above - mentioned boundaries can be determined, and then based on the above - mentioned boundaries, the driving behavior of each vehicle corresponding to the current moment to the next moment can be determined.

[0077] For example, during the driving process in the second road area, a vehicle can determine various driving behaviors through the car - following model, such as driving at a constant speed, accelerating, decelerating, free driving, car - following, lane - changing, and overtaking, etc. Among them, when the distance between the vehicle and the vehicle in front in the same lane is greater than or equal to the first threshold, the vehicle is in a free - driving state. When the distance between the vehicle and the vehicle in front in the same lane is less than the first threshold and greater than the second threshold, the vehicle is in a car - following state.

[0078] Specifically, at each moment, through the car - following model, based on the driving information of each vehicle in the second road area at that moment, if the distance between each vehicle and the vehicle in front exceeds the distance set by the perception critical line (i.e., the first threshold or SDV), then the vehicle is in a free - driving state from the current moment to the next moment. If the speed of the vehicle at that moment is less than its own desired speed, then the vehicle accelerates until the desired speed from the current moment to the next moment and maintains this speed or oscillates slightly above and below this speed.

[0079] If the distance between the vehicle and the vehicle in front in the same lane is less than the distance set by the perception critical line and greater than the second threshold (ABX), then the vehicle enters the car - following state from the current moment to the next moment. At this time, the vehicle can still accelerate, but the distance between it and the vehicle in front in the same lane is greater than the safety distance. If it is less than the safety distance, then it needs to decelerate to reach the car - following state.

[0080] Among them, for any vehicle, during the process of following a vehicle in the second road area, the cumulative time that the vehicle is in the following state can be determined based on the following model. If the cumulative time does not reach the preset threshold, it indicates that the vehicle exits the following state and clears the cumulative time. If the cumulative time exceeds the threshold, it means that the vehicle will attempt to change lanes at the next moment when the cumulative time exceeds the threshold to get rid of the current following state. Before changing lanes, it is necessary to determine whether the distance between the vehicle and the vehicle in front in the same lane is greater than the safety distance, and whether the distance to the following vehicle after changing lanes meets the requirements of the safety distance. If the above requirements can be met, the vehicle changes lanes and clears the cumulative time.

[0081] Based on the above implementation method, based on the driving information of each vehicle at each moment during the driving process in the second road area and the corresponding driving behavior after that moment, the driving information of each vehicle at the next moment during the driving process in the second road area can be determined.

[0082] Optionally, the process of determining the driving information of each vehicle at the next moment during the driving process in the second road area based on the driving information of each vehicle at each moment during the driving process in the second road area can be implemented based on a pre-trained neural network model.

[0083] Step S23: Determine the positioning information of at least one first vehicle among all vehicles at each moment during the driving process in the second road area.

[0084] In some feasible implementation manners, the first vehicle is a vehicle whose positioning information at each moment during the driving process in the second road area can be determined. The positioning information of the first vehicle can be uploaded by the first vehicle through an in-vehicle terminal or obtained through a positioning device installed on the first vehicle, and can be specifically determined based on the requirements of the actual application scenario, which is not limited here.

[0085] Step S24: Based on the positioning information of each first vehicle at each moment during the driving process in the second road area, the driving speed and the first displacement of each vehicle at each moment during the driving process in the second road area, determine the driving trajectories of all vehicles in the second road area.

[0086] In some feasible implementation manners, when determining the driving trajectories of all vehicles in the second road area based on the positioning information of each first vehicle at each moment, and the first displacement and driving speed of each vehicle at each moment, for each first vehicle, the driving trajectory of the first vehicle in the second road area can be determined based on the driving speed, the first displacement and the positioning information corresponding to each moment during the driving process of the first vehicle in the second road area.

[0087] For each second vehicle, the driving trajectory of the second vehicle in the second road area can be determined based on the first displacements of each vehicle at each moment during driving in the second road area and the driving trajectories of each first vehicle in the second road area.

[0088] Specifically, for each first vehicle, the driving speed and first displacement corresponding to each moment during the driving of the first vehicle in the second road area can be used to update the first displacement corresponding to the first vehicle at that moment, and the second displacement corresponding to the first vehicle at that moment can be obtained. For example, if the first displacement corresponding to each moment of the first vehicle is determined by a car-following model, then due to error reasons, there is a certain difference between the first displacement corresponding to each moment of the first vehicle and its actual displacement. Therefore, the first displacement corresponding to the first vehicle at that moment can be updated to make the obtained second displacement closer to its actual displacement.

[0089] In a specific implementation, for each first vehicle, the distance gain coefficient corresponding to each moment of the first vehicle can be determined based on the driving speed of the first vehicle at each moment during driving in the second road area.

[0090] For example, the distance gain coefficient corresponding to each first vehicle at the k-th moment can be determined based on the following method:

[0091]

[0092] where represents the driving speed corresponding to the k-th moment of the first vehicle during driving in the second road area, and C and R are preset coefficients.

[0093] At the same time, based on the positioning information of each first vehicle at each moment during driving in the second road area, the third displacement of the first vehicle in the second road area up to each moment can be determined. That is, at this time, the third displacement of the vehicle in the second road area up to each moment is determined based on the positioning information of the first vehicle at the corresponding moment.

[0094] Further, after determining the distance gain coefficient and the third displacement corresponding to each moment of the first vehicle, the displacement offset can be determined based on the distance gain coefficient, the first displacement, and the third displacement corresponding to that moment. After determining the displacement offset corresponding to each moment of the first vehicle, the second displacement corresponding to each moment of the first vehicle can be determined based on the displacement offset and the first displacement corresponding to each moment of the first vehicle, that is, the second displacement after updating the first displacement corresponding to each moment of the first vehicle is determined.

[0095] For example, the second displacement corresponding to each first vehicle at the k-th moment can be determined based on the following method:

[0096]

[0097] wherein is the first displacement of the first vehicle at time k during driving in the second road area, is the third displacement of the first vehicle in the second road area up to time k, is the displacement offset corresponding to the first vehicle at time k.

[0098] Furthermore, for each first vehicle, after updating the first displacement corresponding to each time during the driving of the first vehicle in the second road area to obtain the second displacement, the road information of the second road area can be determined first. Among them, the road information of the second road area includes lane distribution information, lane direction information, intersection distribution information, etc. of the second road area, which is not limited here.

[0099] For each first vehicle, based on the second displacement and positioning information corresponding to each time during the driving of the first vehicle in the second road area, and the second displacement and positioning information corresponding to the next time of that time, the displacement difference between the driving position of the first vehicle at that time and the driving position at the next time of that time can be determined. Further, in combination with the road information of the second road area and this displacement difference, the stage driving trajectory of the first vehicle in the second road area from that time to the next time of that time can be determined.

[0100] Based on the above method, the stage driving trajectories corresponding to each adjacent time during the driving of the first vehicle in the second road area can be determined, and then based on the corresponding stage driving trajectories during the driving of the first vehicle in the second road area, the driving trajectory of the first vehicle in the second road area can be determined.

[0101] After determining the driving trajectories of each first vehicle in the second road area, for each second vehicle other than the first vehicle, based on the driving trajectories of each first vehicle in the second road area and the first displacement corresponding to each time during the driving of the second vehicle in the second road area, the driving position of the second vehicle at each time during the driving in the second road area can be determined.

[0102] For example, based on the driving positions of each first vehicle at each time and the first displacement of the second vehicle at each time, the positional relationship between the second vehicle and each first vehicle at each time can be determined, and then based on the positional relationship between the second vehicle and each first vehicle at each time, the driving position of the second vehicle at each time during the driving in the second road area can be determined. Based on this, the driving trajectory of the second vehicle in the second road area can be determined according to the driving positions of the second vehicle at each time during the driving in the second road area.

[0103] Alternatively, when the driving information of each vehicle at each moment includes the vehicle distance association relationship between the vehicle and other vehicles at each moment, for each second vehicle, based on the driving trajectories of the first vehicles in the second road area and the vehicle distance association relationship between the second vehicle and the first vehicles at each moment, the driving position of the second vehicle in the second road area can be directly determined. Furthermore, based on the driving positions of the second vehicle at each moment during the driving process in the second road area, the driving trajectory of the second vehicle in the second road area can be determined.

[0104] Optionally, when the driving information of each vehicle at each moment includes the vehicle distance association relationship between the vehicle and other vehicles at each moment, for each second vehicle, first, based on the driving trajectories of the first vehicles in the second road area and the vehicle distance association relationship between the second vehicle and the first vehicles at each moment, the first displacement of the second vehicle in the second road area up to each moment during the driving process in the second road area is updated to obtain a fourth displacement.

[0105] Among them, first, based on the driving trajectories of the first vehicles in the second road area and the vehicle distance association relationship between the second vehicle and the first vehicles at each moment, the fifth displacement of the second vehicle in the second road area up to each moment can be determined. At the same time, based on the driving speed of the second vehicle at each moment during the driving process in the second road area, the distance gain coefficient corresponding to the second vehicle at each moment can be determined. The determination method of the distance gain coefficient corresponding to each second vehicle at each moment is the same as that for determining the distance gain coefficient corresponding to each first vehicle at each moment, which will not be elaborated here.

[0106] Furthermore, after determining the distance gain coefficient and the fifth displacement corresponding to the second vehicle at each moment, the displacement offset can be determined based on the distance gain coefficient, the first displacement, and the fifth displacement corresponding to that moment. After determining the displacement offset corresponding to the second vehicle at each moment, based on the displacement offset and the first displacement corresponding to the second vehicle at each moment, the fourth displacement corresponding to the second vehicle at each moment can be determined, that is, the fourth displacement after updating the first displacement corresponding to the second vehicle at each moment is determined.

[0107] Furthermore, based on the driving trajectories of the first vehicles in the second road area and the fourth displacements corresponding to the second vehicle at each moment during the driving process in the second road area, the driving positions of the second vehicle at each moment during the driving process in the second road area can be determined. The specific determination method will not be elaborated here. Based on this, the driving trajectory of the second vehicle in the second road area can be determined according to the driving positions of the second vehicle at each moment during the driving process in the second road area.

[0108] In the embodiments of the present application, since the driving trajectory of each vehicle in the second road area can describe the driving position of the corresponding vehicle at each moment during the driving process in the second road area, the driving trajectory of each vehicle in the second road area can indicate the lane in which the corresponding vehicle travels and the lane change situation during the driving process in the second road area.

[0109] In some feasible embodiments, when determining the driving information of each vehicle at each moment during the driving process in the second road area based on the driving information of each vehicle when entering the second road area, for each vehicle, the driving information of the vehicle at the next moment during the driving process in the second road area can be determined based on the driving information of the vehicle at each moment during the driving process in the second road area. That is, the driving information of each vehicle at each moment during the driving process in the second road area is determined based on the driving information of the vehicle at the previous moment during the driving process in the second road area.

[0110] Specifically, the control factors for controlling the change of driving information can be determined first, that is, under the influence of these control factors, the driving information of each vehicle changes at different moments during the driving process in the second road area.

[0111] Among them, the control factors for controlling the change of driving information can be specifically determined based on the driving information and the requirements of the actual application scenario, and no limitation is made here. For example, if the driving information of each vehicle at each moment during the driving process in the second road area includes the driving speed of the vehicle at the corresponding moment and the first displacement in the second road area up to the corresponding moment, the control factor for controlling the change of driving information can be the acceleration of the vehicle at the corresponding moment.

[0112] Furthermore, the change relationship between the driving information corresponding to each moment and the driving information corresponding to the next moment of that moment can be determined based on the control factor. Then, for each vehicle, the driving information of the vehicle at the next moment during the driving process in the second road area can be determined based on this change relationship and the driving information of the vehicle at each moment during the driving process in the second road area.

[0113] Optionally, when the driving information of each vehicle at each moment during the driving process in the second road area includes multiple sub-driving information items, the change relationship between the sub-driving information corresponding to each moment and the sub-driving information corresponding to the next moment of that moment can be determined under the participation of the control factor. Then, for each vehicle, each item of sub-driving information corresponding to the next moment of that moment during the driving process in the second road area can be determined based on each item of sub-driving information in the driving information of the vehicle at each moment during the driving process in the second road area and the corresponding change relationship, so as to obtain the driving information of the vehicle at the next moment during the driving process in the second road area.

[0114] For example, when the driving information of each vehicle at each moment during driving in the second road area includes the driving speed of the vehicle at the corresponding moment and the first displacement within the second road area up to the corresponding moment, the displacement change relationship corresponding to each vehicle at the k-th moment during driving in the second road area is expressed as The driving speed change relationship corresponding to the k-th moment can be expressed as

[0115] where A is the transition matrix, used to represent the transition relationship between and k u is the control factor (such as acceleration) of the vehicle at the k-th moment, B is the control matrix corresponding to the control factor, used to represent the control mode of the control factor, and Q is the noise matrix.

[0116] where is the second displacement after updating the first displacement of the vehicle at the (k - 1)-th moment during driving in the second road area. The specific update method can refer to the implementation method for determining the second displacement corresponding to the first vehicle at any moment described above, which will not be elaborated here.

[0117] where P k-1 is the updated driving speed after updating the driving speed of the vehicle at the (k - 1)-th moment during driving in the second road area, and its specific update method is I, C, and R are preset coefficients.

[0118] For example, referring to Figure 4 , Figure 4 is a schematic flow chart for determining the driving information of the first vehicle provided by an embodiment of the present application. For each first vehicle, the following can be performed: based on the control factor (such as acceleration) corresponding to each moment during driving of the first vehicle in the second road area, input it into the car-following model, and the car-following model can determine the displacement change relationship and the driving speed change relationship The car-following model further updates the driving speed at the (k - 1)-th moment to obtain the updated driving speed, and then based on the updated driving speed corresponding to the (k - 1)-th moment, determines the driving speed corresponding to the k-th moment through the driving speed change relationship.

[0119] Further, the car-following model determines the corresponding distance gain coefficient based on the driving speed of the first vehicle at the (k - 1)th moment, determines the third displacement corresponding to the first vehicle at the (k - 1)th moment based on the positioning information of the first vehicle at the (k - 1)th moment, and updates the first displacement at the (k - 1)th moment through the distance gain coefficient and the third displacement to obtain the second displacement at the (k - 1)th moment. Thus, based on the second displacement of the first vehicle at the (k - 1)th moment, the first displacement of the first vehicle at the kth moment can be determined through the displacement change relationship.

[0120] Optionally, for the second vehicle among the vehicles, the first displacement of the second vehicle at the kth moment can be directly determined based on the first displacement of the second vehicle at the (k - 1)th moment and the displacement change relationship during the driving process of the second vehicle in the second road area, and the driving speed of the second vehicle at the kth moment can be determined based on the driving speed of the second vehicle at the (k - 1)th moment and the driving speed change relationship during the driving process of the second vehicle in the second road area.

[0121] For example, referring to Figure 5 , Figure 5 is a schematic flow chart for determining the driving information of the second vehicle provided by an embodiment of the present application. For each second vehicle, control factors (such as acceleration) corresponding to each moment during the driving process of the second vehicle in the second road area can be input into the car-following model, and the car-following model can determine the displacement change relationship and the driving speed change relationship based on the control factors. Furthermore, the car-following model can directly determine the first displacement of the second vehicle at the kth moment based on the first displacement of the second vehicle at the (k - 1)th moment and the displacement change relationship during the driving process of the second vehicle in the second road area, and determine the driving speed of the second vehicle at the kth moment based on the driving speed of the second vehicle at the (k - 1)th moment and the driving speed change relationship during the driving process of the second vehicle in the second road area.

[0122] Among them, interference noise can also be added to the displacement change relationship corresponding to each vehicle at the kth moment during the driving process in the second road area to obtain w k indicating the interference factor for the first displacement of the vehicle during the driving process of the vehicle, such as road surface unevenness, roadblock influence factors, etc., which are not limited here.

[0123] Further, as Figure 6 shown, Figure 6 is a spatio-temporal diagram of the trajectory of a vehicle provided by an embodiment of the present application. In Figure 6 shown is the change relationship between the driving mileage and time when the vehicle is driving on the highway under low traffic density conditions. As can be seen from Figure 6 , the relationship between the driving mileage and time when the vehicle is driving on the highway is approximately a linear relationship. Thus, it can be known that for the road area where the vehicle is driving normally, the displacement change relationship and the driving speed change relationship in this road area basically conform to the linear relationship.

[0124] As shown in Figure 7 the figure Figure 7 is another vehicle trajectory spatio-temporal diagram provided by an embodiment of the present application. Figure 7 As shown in the figure, under high traffic density conditions and under the mutual influence between vehicles, the relationship between mileage and time gradually deviates from the linear relationship when the vehicle is driving on the highway. It can be seen from this that as the traffic flow increases and the mutual influence between vehicles gradually intensifies, the above displacement change relationship and driving speed change relationship deviate from the linear relationship under high traffic density conditions.

[0125] Based on this, the displacement change relationship and the driving speed change relationship can be preprocessed to obtain the linear processed displacement change relationship and the processed driving speed change relationship. For example, the partial derivatives of and u k can be obtained to get Based on the processed displacement change relationship and the second displacement at the k-1 moment, the initial displacement is obtained and then is restored to obtain the first displacement at the k moment

[0126] Similarly, the partial derivative of P k-1 in the driving speed change relationship can be obtained to get P′ k = g(P k-1 ). Based on the processed driving speed change relationship and the driving speed at the k-1 moment, the initial driving speed displacement P′ k is obtained, and then P′ k is restored to obtain the driving speed at the k moment.

[0127] Next, in combination with Figure 8 the driving trajectory determination method provided by the embodiment of the present application will be further described. Figure 8 is the flow framework diagram of the driving trajectory determination method provided by the embodiment of the present application. As shown in Figure 8 the figure, when the distance between vehicles is far, there is basically no influence on each other's driving behaviors or driving information. Therefore, the first vehicle and the second vehicle in the first road area within a preset time period can be identified first, where the first vehicle is the vehicle for which positioning information can be obtained, and the second vehicle is other vehicles except the first vehicle.

[0128] For the first vehicle and the second vehicle, the driving information at each moment when each vehicle enters the second road area can be determined, such as driving speed, lane where the vehicle is located, acceleration, vehicle distance correlation relationship between vehicles, etc. For the first vehicle, it is also necessary to determine its positioning information at each moment during the driving process in the second road area.

[0129] The car-following model can continuously update the driving information of each vehicle at each moment during the driving process on the second road based on the driving information of each vehicle when entering the second road area, and correct the driving information of the second vehicle based on the driving information of the first vehicle, such as updating the driving speed and displacement of the first vehicle at each moment during the driving process in the second road area. And during this process, the car-following model can finally determine the driving trajectories of each vehicle during the driving process in the second road area based on the driving information of each vehicle at each moment during the driving process in the second road area and the positioning information of the first vehicle.

[0130] Among them, for the car-following model, the processes of determining the driving information of each vehicle at each moment during the driving process on the second road by the car-following model and determining the vehicle driving association relationship, etc. can be realized based on cloud computing technology. Cloud computing is the product of the development and integration of traditional computer and network technologies such as Grid Computing, Distributed Computing, Parallel Computing, Utility Computing, Network Storage Technologies, Virtualization, and Load Balance.

[0131] Among them, for the car-following model, sample data including the driving information of each sample vehicle when entering the sample road area and the positioning information of the first sample vehicle in the sample road area among the sample vehicles can be determined, and then based on the sample data, the predicted driving trajectories of each sample vehicle in the sample road area can be determined through the car-following model. And based on the actual driving trajectories and the corresponding predicted driving trajectories of each sample vehicle during the driving process in the sample road area, the relevant parameters of the car-following model are adjusted to obtain a car-following model that can finally be used to determine the vehicle driving trajectory.

[0132] Among them, adjusting the relevant parameters of the car-following model, that is, the training process of the car-following model, can be realized based on artificial intelligence technology. Artificial intelligence is the theory, method, technology and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology of computer science. It attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a way similar to human intelligence. Artificial intelligence is also to study the design principles and implementation methods of various intelligent machines to make the machines have the functions of perception, reasoning and decision-making.

[0133] For example, based on machine learning (ML) technology in the field of artificial intelligence, a following model for determining the driving trajectory of a vehicle can be trained through methods such as artificial neural networks, belief networks, reinforcement learning, transfer learning, and inductive learning.

[0134] In the embodiments of the present application, after determining the driving trajectories of the vehicles in the second road area, the driving trajectories corresponding to the vehicles can be stored in a specified storage space for subsequent invocation of the driving trajectories of the vehicles. For example, the driving trajectory of an autonomous vehicle can be invoked to analyze and adjust the parameters related to the driving performance of the autonomous vehicle to make it more in line with the driving habits of the driver and improve the stability of autonomous driving.

[0135] Among them, the above-mentioned specified storage space can be a server, a database, a cloud storage space, or a blockchain, which can be specifically determined based on the requirements of the actual application scenario and is not limited here. Briefly speaking, a database can be regarded as an electronic filing cabinet - a place for storing electronic files, and can be used to store the driving trajectories corresponding to the vehicles in the present application. A blockchain is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithms. Essentially, a blockchain is a decentralized database and is a string of data blocks generated by using cryptographic methods. In the present application, each data block in the blockchain can store the driving trajectories corresponding to the vehicles. Cloud storage is a new concept extended and developed from the concept of cloud computing, which refers to the function of clustering applications, grid technology, and distributed storage file systems, etc., to collect a large number of different types of storage devices (storage devices are also called storage nodes) in the network through application software or application interfaces to work together to store the driving trajectories corresponding to the vehicles.

[0136] In the embodiments of the present application, by determining the driving information of the vehicles when they enter the second road area, the displacements and driving speeds corresponding to each moment during the driving process of the vehicles in the second road area can be determined. Then, by combining the positioning information of some vehicles at each moment during the driving process in the second road and based on the displacements and driving speeds corresponding to each moment during the driving process of the vehicles in the second road area, the driving trajectories of all vehicles during the driving process in the second road area can be accurately determined, with high applicability. At the same time, during the process of determining the driving trajectory, the driving behaviors of the vehicles during the driving process in the second road area are fully considered, thereby further improving the accuracy of the determined driving trajectory and having high applicability.

[0137] See Figure 9 , Figure 9 which is a schematic structural diagram of the driving trajectory determination device provided by the embodiments of the present application. The driving trajectory determination device provided by the embodiments of the present application includes:

[0138] A driving information determination module 91, configured to determine the driving information of each vehicle when entering a second road area within a first road area during a preset time period;

[0139] The above-mentioned driving information determination module 91 is configured to determine the driving information of each vehicle at each moment during the driving process of each vehicle in the second road area based on the driving information of each vehicle when entering the second road area; the driving information of each vehicle at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the second road area up to the corresponding moment; wherein, the first road area is connected to the second road area;

[0140] A positioning information determination module 92, configured to determine the positioning information of at least one first vehicle among each vehicle at each moment during the driving process of the first vehicle in the second road area;

[0141] A driving trajectory determination module 93, configured to determine the driving trajectories of each vehicle in the second road area based on the positioning information of each first vehicle at each moment during the driving process of each first vehicle in the second road area, the driving speed and the first displacement of each vehicle at each moment during the driving process of each vehicle in the second road area.

[0142] In some feasible embodiments, the above-mentioned driving information determination module 91 is configured to:

[0143] Based on the driving information of each vehicle at each moment during the driving process of each vehicle in the second road area, determine the driving information of each vehicle at the next moment during the driving process of each vehicle in the second road area;

[0144] For each vehicle, based on the driving information of the vehicle at each moment during the driving process of the vehicle in the second road area, determine the driving information of the vehicle at the next moment during the driving process of the vehicle in the second road area.

[0145] In some feasible embodiments, the above-mentioned driving information determination module 91 is configured to:

[0146] Based on the driving information of each vehicle at each moment during the driving process of each vehicle in the second road area, determine the driving behavior of each vehicle corresponding to the next moment from this moment to this moment;

[0147] Based on the driving behavior of each vehicle corresponding to the next moment from this moment to this moment and the driving information of each vehicle at this moment, determine the driving information of each vehicle at the next moment at this moment;

[0148] Wherein, the above driving behaviors include at least one of accelerating, decelerating, driving at a constant speed, turning left, stopping, turning right, changing lanes, overtaking, driving when the distance from the vehicle in front in the same lane is greater than or equal to the first threshold, and driving when the distance from the vehicle in front in the same lane is less than the first threshold and greater than the second threshold.

[0149] In some feasible embodiments, the above driving trajectory determination module 93 is configured to:

[0150] For each of the above first vehicles, based on the driving speed, first displacement, and positioning information corresponding to each moment during the driving process of the first vehicle in the above second road area, determine the driving trajectory of the first vehicle in the above second road area;

[0151] For each second vehicle, based on the driving trajectories of the above first vehicles in the above second road area and the first displacement corresponding to each moment during the driving process of the second vehicle in the above second road area, determine the driving trajectory of the second vehicle in the above second road area, where each of the above second vehicles is another vehicle other than the above first vehicles among the above vehicles.

[0152] In some feasible embodiments, for each of the above first vehicles, the above driving trajectory determination module 93 is configured to:

[0153] Based on the driving speed and first displacement corresponding to each moment during the driving process of the first vehicle in the above second road area, update the first displacement corresponding to the first vehicle at that moment to obtain the second displacement corresponding to the first vehicle at that moment;

[0154] Based on the second displacements and positioning information corresponding to each moment during the driving process of the first vehicle in the above second road area, determine the driving trajectory of the first vehicle in the above second road area.

[0155] In some feasible embodiments, for each of the above first vehicles, the above driving trajectory determination module 93 is configured to:

[0156] Based on the driving speed of the first vehicle corresponding to each moment during the driving process of the first vehicle in the above second road area, determine the distance gain coefficient corresponding to the first vehicle at each moment;

[0157] Based on the positioning information of the first vehicle corresponding to each moment during the driving process of the first vehicle in the above second road area, determine the third displacement of the first vehicle within the above second road area up to each moment;

[0158] Based on the distance gain coefficient, first displacement, and third displacement corresponding to the first vehicle at each moment, determine the displacement offset;

[0159] Determine the second displacement corresponding to the first vehicle at each moment based on the displacement offset and the first displacement corresponding to the first vehicle at each moment.

[0160] In some feasible implementation manners, for each of the above-mentioned first vehicles, the driving trajectory determination module 93 is configured to:

[0161] Determine the road information of the second road area;

[0162] Based on the above road information, the second displacement and positioning information corresponding to the first vehicle at each moment during the driving process of the first vehicle in the second road area, and the second displacement and positioning information corresponding to the first vehicle at the next moment of this moment, determine the stage driving trajectory of the first vehicle in the second road area from this moment to the next moment of this moment;

[0163] Based on the stage driving trajectories of the first vehicle in the second road area, determine the driving trajectory of the first vehicle in the second road area.

[0164] In some feasible implementation manners, for each of the above-mentioned second vehicles, the driving trajectory determination module 93 is configured to:

[0165] Based on the driving trajectories of the first vehicles in the second road area and the first displacements corresponding to the second vehicle at each moment during the driving process of the second vehicle in the second road area, determine the driving positions of the second vehicle at each moment during the driving process in the second road area;

[0166] Based on the driving positions of the second vehicle at each moment during the driving process in the second road area, determine the driving trajectory of the second vehicle in the second road area.

[0167] In some feasible implementation manners, the driving information of each of the above-mentioned vehicles at any moment during the driving process in the second road area further includes the acceleration of the vehicle at this moment, the lane where it is located, and the driving association relationship with other vehicles. The driving association relationship between each of the above-mentioned vehicles and any other vehicle includes at least one of a speed association relationship or a vehicle distance association relationship.

[0168] In some feasible implementation manners, for each of the above-mentioned vehicles, the driving information determination module 91 is configured to:

[0169] Determine the control factors for controlling the change of driving information;

[0170] Based on the above control factors, determine the change relationship between the driving information corresponding to each moment and the driving information corresponding to the next moment of this moment;

[0171] For each of the above vehicles, based on the above variation relationship and the driving information of the vehicle at that moment during driving in the above second road area, determine the driving information of the vehicle at the next moment during driving in the above second road area.

[0172] In a specific implementation, the above driving trajectory determination device can execute the implementation methods provided in each of the above Figure 2 steps through its built-in functional modules. Specifically, reference can be made to the implementation methods provided in each of the above steps, which will not be elaborated here.

[0173] See Figure 10 , Figure 10 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 10 shown, the electronic device 1000 in this embodiment may include: a processor 1001, a network interface 1004, and a memory 1005. In addition, the above electronic device 1000 may further include: an object interface 1003 and at least one communication bus 1002. Among them, the communication bus 1002 is used to implement connection communication between these components. Among them, the object interface 1003 may include a display screen (Display) and a keyboard (Keyboard). Optionally, the object interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1004 may be a high-speed RAM memory or a non-volatile memory (NVM), such as at least one disk memory. The memory 1005 may optionally be at least one storage device located far from the aforementioned processor 1001. As Figure 10 shown, the memory 1005, as a computer-readable storage medium, may include an operating system, a network communication module, an object interface module, and a device control application program.

[0174] In Figure 10 the electronic device 1000 shown, the network interface 1004 can provide network communication functions; while the object interface 1003 is mainly used to provide an input interface for an object; and the processor 1001 can be used to call the device control application program stored in the memory 1005 to implement:

[0175] Determine the driving information of each vehicle in the first road area when entering the second road area within a preset time period;

[0176] Based on the driving information of each of the above vehicles when entering the above second road area, determine the driving information of each of the above vehicles at each moment during the driving process in the above second road area. The driving information of each of the above vehicles at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the above second road area up to the corresponding moment; wherein, the above first road area is connected to the above second road area;

[0177] Determine the positioning information of at least one first vehicle among each of the above vehicles at each moment during the driving process in the above second road area;

[0178] Based on the positioning information of each of the above first vehicles at each moment during the driving process in the above second road area, the driving speed and the first displacement of each of the above vehicles at each moment during the driving process in the above second road area, determine the driving trajectories of each of the above vehicles in the above second road area.

[0179] In some feasible implementation manners, the above processor 1001 is configured to:

[0180] Based on the driving information of each of the above vehicles at each moment during the driving process in the above second road area, determine the driving information of each of the above vehicles at the next moment during the driving process in the above second road area;

[0181] For each of the above vehicles, based on the driving information of the vehicle at each moment during the driving process in the above second road area, determine the driving information of the vehicle at the next moment during the driving process in the above second road area.

[0182] In some feasible implementation manners, the above processor 1001 is configured to:

[0183] Based on the driving information of each of the above vehicles at each moment during the driving process in the above second road area, determine the driving behavior of each of the above vehicles corresponding to the next moment from this moment to this moment;

[0184] Based on the driving behavior of each of the above vehicles corresponding to the next moment from this moment to this moment and the driving information of each of the above vehicles at this moment, determine the driving information of each of the above vehicles at the next moment of this moment;

[0185] Wherein, the above driving behavior includes at least one of accelerating, decelerating, driving at a constant speed, turning left, stopping, turning right, changing lanes, overtaking, driving when the distance from the vehicle in front in the same lane is greater than or equal to the first threshold, and driving when the distance from the vehicle in front in the same lane is less than the first threshold and greater than the second threshold.

[0186] In some feasible implementation manners, the above processor 1001 is configured to:

[0187] For each of the above-mentioned first vehicles, based on the driving speed, first displacement, and positioning information corresponding to each moment during the driving of the first vehicle in the above-mentioned second road area, determine the driving trajectory of the first vehicle in the above-mentioned second road area;

[0188] For each second vehicle, based on the driving trajectories of the above-mentioned first vehicles in the above-mentioned second road area and the first displacements corresponding to each moment during the driving of the second vehicle in the above-mentioned second road area, determine the driving trajectory of the second vehicle in the above-mentioned second road area. Each of the above-mentioned second vehicles is another vehicle other than the above-mentioned first vehicles among the above-mentioned vehicles.

[0189] In some feasible embodiments, for each of the above-mentioned first vehicles, the processor 1001 is configured to:

[0190] Based on the driving speed and first displacement corresponding to each moment during the driving of the first vehicle in the above-mentioned second road area, update the first displacement corresponding to the first vehicle at that moment to obtain the second displacement corresponding to the first vehicle at that moment;

[0191] Based on the second displacements and positioning information corresponding to each moment during the driving of the first vehicle in the above-mentioned second road area, determine the driving trajectory of the first vehicle in the above-mentioned second road area.

[0192] In some feasible embodiments, for each of the above-mentioned first vehicles, the processor 1001 is configured to:

[0193] Based on the driving speed of the first vehicle corresponding to each moment during the driving of the first vehicle in the above-mentioned second road area, determine the distance gain coefficient corresponding to the first vehicle at each moment;

[0194] Based on the positioning information of the first vehicle corresponding to each moment during the driving of the first vehicle in the above-mentioned second road area, determine the third displacement of the first vehicle within the above-mentioned second road area up to each moment;

[0195] Based on the distance gain coefficient, first displacement, and third displacement corresponding to the first vehicle at each moment, determine the displacement offset;

[0196] Based on the displacement offset and first displacement corresponding to the first vehicle at each moment, determine the second displacement corresponding to the first vehicle at each moment.

[0197] In some feasible embodiments, for each of the above-mentioned first vehicles, the processor 1001 is configured to:

[0198] Determine the road information of the above-mentioned second road area;

[0199] Based on the above road information, the second displacement and positioning information corresponding to each moment during the driving process of the first vehicle in the above second road area, and the second displacement and positioning information corresponding to the next moment of the first vehicle at this moment, determine the stage driving trajectory of the first vehicle in the above second road area from this moment to the next moment of this moment;

[0200] Based on the stage driving trajectories of the first vehicle in the above second road area, determine the driving trajectory of the first vehicle in the above second road area.

[0201] In some feasible implementation manners, for each of the above second vehicles, the processor 1001 is configured to:

[0202] Based on the driving trajectories of the first vehicles in the above second road area and the first displacements corresponding to each moment during the driving process of the second vehicle in the above second road area, determine the driving positions of the second vehicle at each moment during the driving process in the above second road area;

[0203] Based on the driving positions of the second vehicle at each moment during the driving process in the above second road area, determine the driving trajectory of the second vehicle in the above second road area.

[0204] In some feasible implementation manners, the driving information of each of the above vehicles at any moment during the driving process in the above second road area further includes the acceleration of the vehicle at this moment, the lane where it is located, and the driving association relationship with other vehicles. The driving association relationship between each of the above vehicles and any other vehicle includes at least one of a speed association relationship or a vehicle distance association relationship.

[0205] In some feasible implementation manners, for each of the above vehicles, the processor 1001 is configured to:

[0206] Determine the control factors for controlling the change of driving information;

[0207] Based on the above control factors, determine the change relationship between the driving information corresponding to each moment and the driving information corresponding to the next moment of this moment;

[0208] For each of the above vehicles, based on the above change relationship and the driving information of the vehicle at this moment during the driving process in the above second road area, determine the driving information of the vehicle at the next moment during the driving process in the above second road area.

[0209] It should be understood that in some feasible embodiments, the above-mentioned processor 1001 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0210] In specific implementation, the above-mentioned electronic device 1000 may execute the implementation manners provided in each of the steps as described above through its built-in functional modules. Figure 2 For the specific implementation manners, reference may be made to the implementation manners provided in each of the above steps, which will not be elaborated herein.

[0211] The embodiment of the present application also provides a computer-readable storage medium, which stores a computer program that is executed by a processor to implement Figure 2 the methods provided in each of the steps as described above. For the specific implementation manners, reference may be made to the implementation manners provided in each of the above steps, which will not be elaborated herein.

[0212] The above-mentioned computer-readable storage medium may be an internal storage unit of the driving trajectory determination device or the electronic device provided in any of the foregoing embodiments, such as the hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device. The above-mentioned computer-readable storage medium may also include magnetic disks, optical disks, read-only memory (ROM), or random access memory (RAM), etc. Further, the computer-readable storage medium may include both the internal storage unit and the external storage device of the electronic device. The computer-readable storage medium is used to store the computer program and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store the data that has been output or will be output.

[0213] An embodiment of the present application provides a computer program product, which includes a computer program or computer instructions, and the above computer program or computer instructions are executed by a processor Figure 2 in the methods provided by each step.

[0214] The terms "first", "second", etc. in the claims, the description and the drawings of the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or electronic device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or electronic devices. The mention of "embodiment" in this article means that the specific features, structures or characteristics described in connection with the embodiment can be included in at least one embodiment of the present application. The display of this phrase at various positions in the description does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments. The term "and / or" used in the description and claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0215] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to functions in the above description. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0216] The above-disclosed are only the preferred embodiments of the present application, and the scope of the rights of the present application cannot be limited thereby. Therefore, equivalent changes made according to the claims of the present application still fall within the scope covered by the present application.

Claims

1. A method for determining a driving trajectory, characterized in that, The method includes: Determining the driving information of each vehicle when it enters a second road area within a preset time period in a first road area; Based on the driving information of each vehicle when entering the second road area, determining the driving information of each vehicle at each moment during the driving process in the second road area, where the driving information of each vehicle at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the second road area up to the corresponding moment; wherein, the first road area is connected to the second road area; Determining the positioning information of at least one first vehicle among each vehicle at each moment during the driving process in the second road area; Based on the positioning information of each first vehicle at each moment during the driving process in the second road area, the driving speed and the first displacement of each vehicle at each moment during the driving process in the second road area, determining the driving trajectories of each vehicle in the second road area.

2. The method according to claim 1, wherein The determining the driving information of each vehicle at each moment during the driving process in the second road area based on the driving information of each vehicle when entering the second road area includes at least one of the following: Based on the driving information of each vehicle at each moment during the driving process in the second road area, determining the driving information of each vehicle at the next moment during the driving process in the second road area; For each vehicle, based on the driving information of the vehicle at each moment during the driving process in the second road area, determining the driving information of the vehicle at the next moment during the driving process in the second road area.

3. The method according to claim 2, wherein The determining the driving information of each vehicle at the next moment based on the driving information of each vehicle at each moment during the driving process in the second road area includes: Based on the driving information of each vehicle at each moment during the driving process in the second road area, determining the driving behavior of each vehicle corresponding to from this moment to the next moment; Based on the driving behavior of each vehicle corresponding to from this moment to the next moment and the driving information of each vehicle at this moment, determining the driving information of each vehicle at the next moment; Wherein, the driving behavior includes at least one of accelerating, decelerating, driving at a constant speed, turning left, stopping, turning right, changing lanes, overtaking, driving when the distance from the vehicle in the same lane in front is greater than or equal to a first threshold, and driving when the distance from the vehicle in the same lane in front is less than the first threshold and greater than a second threshold.

4. The method according to claim 1, wherein The determining the driving trajectories of each vehicle in the second road area based on the positioning information of each first vehicle at each moment during the driving process in the second road area, the driving speed and the first displacement of each vehicle at each moment during the driving process in the second road area includes: For each first vehicle, based on the driving speed, the first displacement and the positioning information corresponding to each moment during the driving process of the first vehicle in the second road area, determining the driving trajectory of the first vehicle in the second road area. For each second vehicle, based on the driving trajectories of the first vehicles in the second road area and the first displacements corresponding to each moment during the driving of the second vehicle in the second road area, determine the driving trajectory of the second vehicle in the second road area, where each second vehicle is another vehicle other than the first vehicles among the vehicles.

5. The method according to claim 4, characterized in that For each first vehicle, determining the driving trajectory of the first vehicle in the second road area based on the driving speed, first displacement, and positioning information corresponding to each moment during the driving of the first vehicle in the second road area includes: Based on the driving speed and first displacement corresponding to each moment during the driving of the first vehicle in the second road area, update the first displacement corresponding to the first vehicle at that moment to obtain the second displacement corresponding to the first vehicle at that moment; Based on the second displacements and positioning information corresponding to each moment during the driving of the first vehicle in the second road area, determine the driving trajectory of the first vehicle in the second road area.

6. The method according to claim 5, characterized in that For each first vehicle, updating the first displacement corresponding to the first vehicle at that moment based on the driving speed and first displacement corresponding to each moment during the driving of the first vehicle in the second road area to obtain the second displacement corresponding to the first vehicle at that moment includes: Determine the distance gain coefficient corresponding to each moment of the first vehicle based on the driving speed of the first vehicle during the driving in the second road area; Based on the positioning information of the first vehicle during the driving in the second road area at each moment, determine the third displacement of the first vehicle in the second road area up to each moment; Determine the displacement offset based on the distance gain coefficient, first displacement, and third displacement corresponding to each moment of the first vehicle; Based on the displacement offset and first displacement corresponding to each moment of the first vehicle, determine the second displacement corresponding to the first vehicle at each moment.

7. The method according to claim 5, wherein For each first vehicle, determining the driving trajectory of the first vehicle in the second road area based on the second displacements and positioning information corresponding to each moment during the driving of the first vehicle in the second road area includes: Determine the road information of the second road area; Based on the road information, the second displacements and positioning information corresponding to each moment during the driving of the first vehicle in the second road area, and the second displacements and positioning information corresponding to the next moment of the first vehicle at that moment, determine the stage driving trajectory of the first vehicle in the second road area from that moment to the next moment; Based on the stage driving trajectories of the first vehicle in the second road area, determine the driving trajectory of the first vehicle in the second road area.

8. The method according to claim 4, characterized in that For each second vehicle, determining the driving trajectory of the second vehicle in the second road area based on the driving trajectories of the first vehicles in the second road area and the first displacements corresponding to each moment during the driving of the second vehicle in the second road area includes: Determine the driving position of the second vehicle at each moment during the driving process in the second road area based on the driving trajectories of the first vehicles in the second road area and the first displacements corresponding to each moment during the driving process of the second vehicle in the second road area; Determine the driving trajectory of the second vehicle in the second road area based on the driving positions of the second vehicle at each moment during the driving process in the second road area.

9. The method according to claim 1, characterized in that The driving information of each vehicle at any moment during the driving process in the second road area further includes the acceleration of the vehicle at that moment, the lane where it is located, and the driving association relationship with other vehicles. The driving association relationship between each vehicle and any other vehicle includes at least one of a speed association relationship or a vehicle distance association relationship.

10. The method according to claim 2, characterized in that, For each vehicle, the determining, based on the driving information of the vehicle at each moment during the driving process in the second road area, of the driving information of the vehicle at the next moment during the driving process in the second road area includes: Determine the control factors for controlling the change of driving information; Based on the control factors, determine the change relationship between the driving information corresponding to each moment and the driving information corresponding to the next moment of that moment; For each vehicle, based on the change relationship and the driving information of the vehicle at that moment during the driving process in the second road area, determine the driving information of the vehicle at the next moment during the driving process in the second road area.

11. A driving trajectory determination device, characterized in that, The device includes: A driving information determination module, configured to determine the driving information of each vehicle when entering the second road area within a preset time period in the first road area; The driving information determination module is configured to determine the driving information of each vehicle at each moment during the driving process in the second road area based on the driving information of each vehicle when entering the second road area. The driving information of each vehicle at any moment includes the driving speed of the vehicle at the corresponding moment and the first displacement within the second road area up to the corresponding moment; wherein, the first road area is connected to the second road area; A positioning information determination module, configured to determine the positioning information of at least one first vehicle among the vehicles at each moment during the driving process in the second road area; A driving trajectory determination module, configured to determine the driving trajectories of the vehicles in the second road area based on the positioning information of the first vehicles at each moment during the driving process in the second road area, the driving speeds and the first displacements of the vehicles at each moment during the driving process in the second road area; 12. An electronic device, characterized in that, Comprising a processor and a memory, the processor and the memory are interconnected; The memory is used to store a computer program; The processor is configured to execute the method according to any one of claims 1 to 10 when calling the computer program.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 10.

14. A computer program product, characterized in that, The computer program product includes a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 10.

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