Vehicle driving queuing method, device and equipment and storage medium

Abstract

The invention relates to a vehicle driving queuing method, device and equipment and a storage medium, and relates to the technical field of vehicle road driving. The method at least solves the technical problems of relatively high energy consumption and relatively high time cost caused by relatively low driving lane selection accuracy of a vehicle in related technologies, and comprises the steps of determining vehicle driving information and road information for a target vehicle passing through a target intersection at a target moment t; on the basis of the vehicle driving information and the road information, determining the driving duration # imgabs0 # of the target vehicle driving to the mth lane in the target intersection, on the basis of the vehicle driving information, the road information, the first parameter and the second parameter, and determining the driving cost of the target vehicle driving to the mth lane in the target intersection. # imgabs1 #, and determining the target lane of the target vehicle driving in the target intersection when the minimum value of the target optimization equation is taken based on the preset control parameters, the vehicle driving information, the road information, # imgabs2 # and # imgabs3 #.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle road driving, and in particular to a vehicle driving queuing method, device, equipment and storage medium. Background Art

[0002] At present, vehicle driving issues play an important role in the autonomous driving industry. More and more novel vehicle services are attracting more people to use them, such as intelligent driving, high-precision map navigation, traffic information systems and other Internet of Vehicles applications. These types of vehicle applications all involve vehicle driving methods, with a wide range of demands and high driving costs. Since the driving of vehicles on the road is restricted by the current traffic conditions of the road section, its driving time may cause a lot of time consumption due to congestion, as well as a large amount of cost waste, such as fuel consumption or energy consumption. Users cannot get a good driving experience, and may even cause safety accidents. Specifically, the shortest path for vehicle driving can be calculated by determining the starting point and the end point to calculate the shortest distance between the two points; or, considering the travel time as the judgment standard, the shortest path is determined based on the road grade, excluding construction or blocked sections on the road.

[0003] However, in the above method, even if the shortest driving distance between two points is found and the destination can be reached quickly, the corresponding cost paid by the user may also increase. Therefore, during the driving process, the current vehicle has a low accuracy in selecting the driving lane, resulting in high energy consumption, high time cost, and poor driving experience for users. Summary of the invention

[0004] The present application provides a vehicle queuing method, device, equipment and storage medium to at least solve the technical problem in the related art that the accuracy of the vehicle's lane selection during driving is low, resulting in high energy consumption, high time cost and poor user driving experience. The technical solution of the present application is as follows:

[0005] According to a first aspect of the present application, a vehicle queuing method is provided, comprising: determining vehicle driving information and road information for a target vehicle passing through a target intersection at a target time t, wherein the vehicle driving information includes: the distance from the target vehicle to the mth lane in the target intersection The current speed of the target vehicle v n , the road information includes: the number of vehicles P allowed to pass in the mth lane of the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), the target intersection includes M lanes, and the target vehicle is the nth vehicle among the N vehicles passing through the target intersection at the target time; based on v n, P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection based on v n , P m (t), Q m (t), the first parameter, and the second parameter determine the driving cost of the target vehicle traveling to the mth lane in the target intersection The first parameter is used to indicate the driving cost of the target vehicle per unit time, and the second parameter is used to indicate the waiting cost of the target vehicle in the queue per unit time; based on the preset control parameters, Q m (t) v n , P m (t) and A target lane for a target vehicle to travel in a target intersection when a target optimization equation takes a minimum value is determined, and a preset control parameter is used to indicate the degree of emphasis on the minimum cost.

[0006] According to the above technical means, the present application can determine the distance from the target vehicle to the mth lane in the target intersection when the target vehicle passes through the target intersection. The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), thus based on v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection And further based on the first parameter and the second parameter, determine the driving cost of the target vehicle traveling to the mth lane in the target intersection Thus, based on the preset control parameters and the data obtained in advance, the target lane in which the target vehicle is traveling in the target intersection is determined when the target optimization equation takes the minimum value. Through the above method, when the target vehicle passes through the target intersection, based on the specific driving information of the vehicle (i.e., the distance from the target vehicle to the mth lane in the target intersection, the current driving speed of the target vehicle) and the road information (i.e., the number of vehicles allowed to pass through the mth lane in the target intersection at the target time, the queue length of the vehicles included in the mth lane in the target intersection), the target lane in which the target vehicle is traveling in the target intersection is accurately determined by taking the minimum value of the target optimization equation, thereby ensuring that the target vehicle can pass through the target intersection in the shortest time with the lowest energy consumption, and improving the accuracy of the vehicle's lane selection and the traffic efficiency.

[0007] In a possible implementation, the method further includes: determining the number of vehicles f arriving at the mth lane of the target intersection at the target time t m (t); Based on P m (t), Q m (t), f m (t), the queue length Q of the vehicles in the mth lane of the target intersection at the next moment after the target moment is determined m (t+1).

[0008] According to the above technical means, the number of vehicles f arriving at the mth lane of the target intersection at the target time t can be further determined: m (t), so that at the next moment after the target moment, the queue length Q of the vehicles included in the mth lane of the target intersection is predetermined m (t+1), so that at the next moment after the target moment, the queue length Q of the vehicles included in the mth lane in the target intersection can be calculated based on m (t+1), determine the lanes that other vehicles are traveling in at the target intersection.

[0009] In a possible implementation, the method based on v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection Includes: Determine With v n The first ratio between m (t) and P m The sum of the first ratio and the second ratio is determined as the driving time of the target vehicle to the mth lane in the target intersection.

[0010] According to the above technical means, the present application can be based on the distance of the target vehicle to the mth lane in the target intersection. The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), accurately determine the driving time of the target vehicle to the mth lane of the target intersection through a specific algorithm Thereby, the accuracy of determining the driving time of the target vehicle to the mth lane in the target intersection can be improved.

[0011] In a possible implementation, the method based on v n , P m (t), Q m (t), the first parameter, and the second parameter determine the driving cost of the target vehicle traveling to the mth lane in the target intersection The method comprises: determining a first product between a first ratio and a first parameter, and determining a first product between a second ratio and a second parameter; and determining the sum of the first product and the second product as a driving cost of the target vehicle traveling to the mth lane in the target intersection.

[0012] According to the above technical means, the present application can be based on the distance of the target vehicle to the mth lane in the target intersection. The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), further combining the preset first parameter and the second parameter, through a specific algorithm, accurately determine the driving cost of the target vehicle traveling to the mth lane in the target intersection Thereby, the accuracy of determining the driving cost of the target vehicle traveling to the mth lane in the target intersection can be improved.

[0013] According to a second aspect of the present application, a vehicle queuing device is provided, comprising a processing module; the processing module is used to determine vehicle driving information and road information for a target vehicle passing through a target intersection at a target time t, wherein the vehicle driving information includes: the distance from the target vehicle to the mth lane in the target intersection The current speed of the target vehicle v n , the road information includes: the number of vehicles P allowed to pass in the mth lane of the target intersection at the target time m(t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), the target intersection includes M lanes, and the target vehicle is the nth vehicle among the N vehicles passing through the target intersection at the target time; the processing module is also used based on v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection Processing module, also used based on v n , P m (t), Q m (t), the first parameter, and the second parameter determine the driving cost of the target vehicle traveling to the mth lane in the target intersection The first parameter is used to indicate the driving cost of the target vehicle per unit time, and the second parameter is used to indicate the waiting cost of the target vehicle in the queue per unit time; the processing module is also used to calculate the target vehicle based on the preset control parameters, Q m (t) v n , P m (t) and A target lane for a target vehicle to travel in a target intersection when a target optimization equation takes a minimum value is determined, and a preset control parameter is used to indicate the degree of emphasis on the minimum cost.

[0014] In a possible implementation, the processing module is further configured to determine the number of vehicles f arriving at the mth lane of the target intersection at the target time t. m (t); processing module, also used based on P m (t), Q m (t), f m (t), the queue length Q of the vehicles in the mth lane of the target intersection at the next moment after the target moment is determined m (t+1).

[0015] In a possible implementation, the processing module is specifically configured to determine With v n The first ratio between m (t) and P m (t); a processing module, specifically used to determine the sum of the first ratio and the second ratio as the driving time of the target vehicle to the mth lane in the target intersection

[0016] In a possible implementation, the processing module is specifically used to determine a first product between the first ratio and the first parameter, and to determine a first product between the second ratio and the second parameter; the processing module is specifically used to determine the sum of the first product and the second product as the driving cost of the target vehicle traveling to the mth lane in the target intersection

[0017] According to the third aspect provided by the present application, an electronic device is provided, comprising: a processor; a memory for storing processor executable instructions; wherein the processor is configured to execute instructions to implement the method of the above-mentioned first aspect and any possible implementation manner thereof.

[0018] According to the fourth aspect provided by the present application, a computer-readable storage medium is provided. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method in the above-mentioned first aspect and any possible implementation method thereof.

[0019] According to a fifth aspect provided by the present application, a vehicle is provided, the vehicle comprising a vehicle queuing device as in the second aspect, the vehicle being used to implement a method as in the first aspect.

[0020] According to the sixth aspect provided by the present application, a computer program product is provided, the computer program product comprising computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the method of the above-mentioned first aspect and any possible implementation manner thereof.

[0021] Therefore, the above technical features of the present application have the following beneficial effects:

[0022] (1) When the target vehicle passes through the target intersection, the distance from the target vehicle to the mth lane in the target intersection can be determined. The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), thus based on v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection And further based on the first parameter and the second parameter, determine the driving cost of the target vehicle traveling to the mth lane in the target intersection Thus, based on the preset control parameters and the data obtained in advance, the target lane in which the target vehicle is traveling in the target intersection is determined when the target optimization equation takes the minimum value. Through the above method, when the target vehicle passes through the target intersection, based on the specific driving information of the vehicle (i.e., the distance from the target vehicle to the mth lane in the target intersection, the current driving speed of the target vehicle) and the road information (i.e., the number of vehicles allowed to pass through the mth lane in the target intersection at the target time, the queue length of the vehicles included in the mth lane in the target intersection), the target lane in which the target vehicle is traveling in the target intersection is accurately determined by taking the minimum value of the target optimization equation, thereby ensuring that the target vehicle can pass through the target intersection in the shortest time with the lowest energy consumption, and improving the accuracy of the vehicle's lane selection and the traffic efficiency.

[0023] (2) The number of vehicles f arriving at the target intersection at the target time t can be further determined: m (t), so that at the next moment after the target moment, the queue length Q of the vehicles included in the mth lane of the target intersection is predetermined m (t+1), so that at the next moment after the target moment, the queue length Q of the vehicles included in the mth lane in the target intersection can be calculated based on m (t+1), determine the lanes that other vehicles are traveling in at the target intersection.

[0024] (3) The distance from the target vehicle to the mth lane at the target intersection can be The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), accurately determine the driving time of the target vehicle to the mth lane of the target intersection through a specific algorithm Thereby, the accuracy of determining the driving time of the target vehicle to the mth lane in the target intersection can be improved.

[0025] (4) The distance from the target vehicle to the mth lane at the target intersection can be The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), further combining the preset first parameter and the second parameter, through a specific algorithm, accurately determine the driving cost of the target vehicle traveling to the mth lane in the target intersection Thereby, the accuracy of determining the driving cost of the target vehicle traveling to the mth lane in the target intersection can be improved.

[0026] It should be noted that the technical effects brought about by any implementation method in the second to sixth aspects can refer to the technical effects brought about by the corresponding implementation method in the first aspect, and will not be repeated here.

[0027] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.

[0029] Figure 1 is a structural schematic diagram of a vehicle queuing system according to an exemplary embodiment;

[0030] Figure 2 is a flow chart of a vehicle queuing method according to an exemplary embodiment;

[0031] Figure 3 is a schematic diagram of a vehicle queuing scenario according to an exemplary embodiment;

[0032] Figure 4 is a schematic diagram of another vehicle queuing scenario according to an exemplary embodiment;

[0033] Figure 5 is a schematic diagram of another vehicle queuing scenario according to an exemplary embodiment;

[0034] Figure 6 is a flow chart showing another method for queuing vehicles according to an exemplary embodiment;

[0035] Figure 7 is a flow chart showing another method for queuing vehicles according to an exemplary embodiment;

[0036] Figure 8 is a flow chart showing another method for queuing vehicles according to an exemplary embodiment;

[0037] Fig. 9 is a block diagram of a vehicle queuing device according to an exemplary embodiment;

[0038] Fig.10 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0039] In order to enable ordinary persons in the art to better understand the technical solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0041] Currently, the shortest distance between two points is calculated by calculating the shortest path for vehicle travel by determining the starting point and the end point; or, the travel time is used as the judgment standard to determine the shortest path based on the road grade, excluding the construction or blocked sections of the road. The travel cost issue is not considered. Even if the shortest travel distance between two points is found and the destination can be reached quickly, the corresponding cost paid by the user may also increase. Therefore, the vehicle travel time must be reduced as much as possible to meet the user experience requirements and minimize the user's use cost. Therefore, the tense relationship between the optimal vehicle travel and the user's use cost has brought a huge challenge to the development of the vehicle application platform.

[0042] This application proposes a vehicle queuing method, which determines which lane the vehicle should drive to based on the driving cost while meeting the time requirements of the vehicle user. The selection method is flexible and will dynamically change according to the current vehicle driving parameters. It will select the appropriate lane while meeting the user's time requirements. The ultimate goal is to find an optimal driving decision to minimize the cost of vehicle driving. This driving decision-making scheme that has the function of reducing costs and meeting time requirements has far-reaching significance for improving the economic benefits of users.

[0043] The vehicle queuing method provided in the embodiment of the present application can be applied to a vehicle queuing system. Figure 1 FIG. 1 shows a structural schematic diagram of the vehicle queuing system. Figure 1 As shown, the vehicle queuing system 10 includes: a plurality of vehicle terminals 11 and a cloud server 12 .

[0044] The vehicle terminal 11 can be used in the Internet of Things, and may include hardware such as multiple central processing units (CPUs), multiple memories, and storage devices storing multiple operating systems.

[0045] The cloud server 12 can be used in the Internet of Things and can be a server corresponding to the vehicle-mounted terminal 11 , used to exchange information with multiple vehicle-mounted terminals 11 and provide vehicle driving queuing services for the vehicle-mounted terminals 11 .

[0046] For ease of understanding, the vehicle queuing method provided by the present application is specifically introduced below with reference to the accompanying drawings.

[0047] Figure 2 is a flow chart of a vehicle queuing method according to an exemplary embodiment. Figure 2 As shown, the vehicle queuing method includes the following S201-S204:

[0048] S201. Determine vehicle driving information and road information for a target vehicle passing through a target intersection at a target time t.

[0049] The vehicle driving information includes: the distance from the target vehicle to the mth lane at the target intersection The current speed of the target vehicle v n , the road information includes: the number of vehicles P allowed to pass in the mth lane of the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), the target intersection includes M lanes, and the target vehicle is the nth vehicle among the N vehicles passing through the target intersection at the target time.

[0050] In the embodiment of the present application, on a road at a certain intersection (i.e., the target intersection), a certain number of vehicles will pass through at each time interval, that is, the vehicles traveling on this road and passing through this intersection are all decision makers for lane selection. The time of lane selection is discretized, and the target time t is used to represent the time when the vehicle selects the lane. Then, at each time, the vehicle needs to make a decision to select which lane to drive in to pass the target intersection.

[0051] For example, Figure 3 As shown, the lanes are numbered from top to bottom. Assuming that at the target time t, a total of N vehicles drive to the target intersection, the target intersection includes M lanes. The lanes are numbered from top to bottom, with the first lane at the top being numbered 1 and the last lane at the bottom being numbered M.

[0052] Optionally, the present application can study the queuing of vehicles through the Lyapunov optimization theory. For the nth vehicle (i.e., the target vehicle) among the N vehicles passing the target intersection at the target time, first determine the distance from the target vehicle to the mth lane in the target intersection. And determine the current speed v of the target vehicle n , that is, the speed v of the target vehicle traveling to the mth lane n , where n=1, 2,…N.

[0053] Furthermore, the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time is determined m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), that is, the queue length Q that the target vehicle needs to queue in the mth lane m (t), so it can be obtained by Q(t)={Q1(t),Q2(t),...,Q M (t)}, represents the queue length of vehicles queuing in all lanes at the target intersection.

[0054] Optionally, the number of vehicles arriving at the mth lane at the target intersection at each moment can also be determined as C m (t), can be obtained by C(t) = {C1(t), C2(t), ..., C M (t)}, represents the number of vehicles arriving at all lanes at the target intersection, and C m (t) has a mean value of λ m Poisson distribution, and satisfy independent and identical distribution, that is, we can get E{C m (t)}=λ m , and all vehicles arriving at the lane at the moment satisfy C m (t)≥0, from which we can get the total number of vehicles that need to choose a lane at time t is N=C1(t)+C2(t)+…+C M (t).

[0055] S202, based on v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection

[0056] Optionally, the driving time of the target vehicle in each lane at the target intersection can be determined as

[0057] It should be noted that the target vehicle is at the target time t, and is about to reach the target intersection. At this time, there is still a certain distance from the target intersection. Therefore, before reaching the target intersection, it is necessary to select a lane to pass the target intersection. Therefore, the driving time for the target vehicle to travel to the mth lane in the target intersection is Includes: the time it takes for the target vehicle to travel to the mth lane in the target intersection, and the time it takes to pass through the mth lane.

[0058] For example, Figure 4 As shown, assuming that the target vehicle is about to enter the lane, is the driving time required for the target vehicle to drive to the first lane. is the driving time required for the target vehicle to drive to the second lane. It is the driving time required for the target vehicle to travel to the mth lane.

[0059] Specifically, determine the driving time of the target vehicle to the mth lane at the target intersection Please refer to the following description, which will not be described in detail here.

[0060] S203, based on v n , P m (t), Q m (t), the first parameter, and the second parameter determine the driving cost of the target vehicle traveling to the mth lane in the target intersection

[0061] The first parameter is used to indicate the driving cost of the target vehicle per unit time, and the second parameter is used to indicate the waiting cost of the target vehicle queuing in the queue per unit time.

[0062] Optionally, the number of vehicles in each of the M lanes in the target intersection is updated in real time as time changes. A certain number of vehicles arrive in each lane at each moment, and then each vehicle drives to the corresponding lane and queues up to exit based on the driving decision strategy. Each vehicle drives to a different lane, and the driving time and driving cost are different.

[0063] Specifically, determine the driving cost of the target vehicle traveling to the mth lane at the target intersection Please refer to the following description, which will not be described in detail here.

[0064] S204, based on the preset control parameters, Q m (t) v n , P m (t) and Determine the target lane in which the target vehicle travels in the target intersection when the target optimization equation takes a minimum value.

[0065] The preset control parameter is used to indicate the emphasis on the minimum cost.

[0066] Optionally, you can use a n (t) indicates the target lane in which the target vehicle is traveling at the target intersection, a n (t) = 1 means the target vehicle will drive to the first lane, a n (t) = m means that the target vehicle will drive to the mth lane. Therefore, the lane selection decision vector of the target vehicle can be obtained as a(t) = [a n (t)|n∈{1,2,...,N},a n (t)∈{1,2,...,M}].

[0067] Optionally, you can also represents the driving decision of the target vehicle whether to drive to the mth lane at time t, Indicates that the target vehicle drives to the mth lane. Indicates that the target vehicle does not drive to the mth lane, so or 0. Therefore, assuming a n (t) = m, then we can get Therefore, the driving decision of the target vehicle to drive to the mth lane can be expressed by formula 1:

[0068]

[0069] in, This is to ensure that a vehicle can only travel in one lane.

[0070] It can be understood that the ultimate goal of this application is to find the optimal lane decision vector a n (t), so that the cost of the target vehicle is minimized during driving and the queue of vehicles in each lane is stable.

[0071] Then, based on the optimized vehicle waiting time and cost, as well as the system optimization goal, the following target optimization equation (Formula 2) is obtained:

[0072]

[0073] Optionally, the preset control parameter is V in Formula 2, and the target lane of the target vehicle in the target intersection can also be calculated by three constraints when the target optimization equation takes the minimum value. The three constraints are the following Formula 3, where the first constraint is to ensure that the vehicle passes through within the specified time, including the vehicle driving time and the waiting time of the vehicle in the lane; the second constraint represents the driving lane of the vehicle, and a vehicle can only drive in one lane; the third constraint is the constraint condition on the number of vehicles passing through each lane at each moment. In order to minimize the value of the target optimization equation and obtain the vehicle's driving decision strategy, the 1-opt local search algorithm can be used to obtain the optimal solution, and its candidate vector consists of all possible solutions of the univariate Hamming distance. This algorithm has low computational complexity and a running time of O(|d| 3 ). The driving decision obtained needs to be judged with the vehicle's driving time to see if it meets the vehicle's driving time. If it does not meet the requirements, the driving decision is abandoned and other optimal solutions are used.

[0074]

[0075] Optionally, this application is passed The restriction is Determine to calculate an optimal driving decision strategy at each moment to minimize the vehicle driving cost as much as possible. Where E represents the mean value, It represents the average cost of vehicle driving decisions, and the constraint condition means that the vehicle queues in all lanes are stable.

[0076] Optionally, T(a(t))=[T1(t),T1(t),…,T N (t)] indicates that at the target time t, the actual driving time of the target vehicle passing through the intersection after the algorithm decision is: And through Indicates that at the target time t, the target lane that the target vehicle is traveling in at the target intersection is a n (t), the corresponding driving cost.

[0077] Optionally, the present application determines the preset control parameters based on the Lyapunov transfer function: According to Lyapunov optimization theory, the penalty term is minimized while ensuring the stability of the queue, that is, the cost is minimized. The Lyapunov penalty term is determined as the cost of the vehicle driving decision, that is, That is, the Lyapunov transfer penalty term is: V(t)+VE{b(a(t))|Q(t)}. In order to determine the lowest driving cost of the target vehicle, it is necessary to find the upper bound of the Lyapunov transfer penalty term. By finding a suitable driving decision a n(t), minimize the upper bound function, and the upper bound can be obtained by the following formula 4:

[0078]

[0079] Among them, the right side of the equation is the upper bound function. Ignoring its constant terms, the above target optimization equation (i.e., Formula 2) can be obtained according to the optimization target.

[0080] Optional, such as Figure 5 As shown, the embodiment of the present application takes into account the number of vehicles that can pass through each lane, dynamically adjusts the driving decision strategy of each vehicle at each moment according to the number of vehicles that are about to arrive, and minimizes the cost of the entire system through the obtained optimal driving strategy. In order to ensure that the obtained driving decision strategy minimizes the cost of the system, the queue length, queue status of all vehicles and each lane, as well as the time of passing through are comprehensively considered, and the driving decision strategy of all vehicles at each time interval is dynamically adjusted through Lyapunov optimization. Through the above scheme, the stability of the lane vehicle queue and the minimization of the cost can be ensured at the same time, while satisfying the overall driving time of the vehicle, and obtaining the optimal driving plan.

[0081] In the embodiment of the present application, when the target vehicle passes through the target intersection, the distance from the target vehicle to the mth lane in the target intersection can be determined. The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), thus based on v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection And further based on the first parameter and the second parameter, determine the driving cost of the target vehicle traveling to the mth lane in the target intersection Thus, based on the preset control parameters and the data obtained in advance, the target lane in which the target vehicle is traveling in the target intersection is determined when the target optimization equation takes the minimum value. Through the above method, when the target vehicle passes through the target intersection, based on the specific driving information of the vehicle (i.e., the distance from the target vehicle to the mth lane in the target intersection, the current driving speed of the target vehicle) and the road information (i.e., the number of vehicles allowed to pass through the mth lane in the target intersection at the target time, the queue length of the vehicles included in the mth lane in the target intersection), the target lane in which the target vehicle is traveling in the target intersection is accurately determined by taking the minimum value of the target optimization equation, thereby ensuring that the target vehicle can pass through the target intersection in the shortest time with the lowest energy consumption, and improving the accuracy of the vehicle's lane selection and the traffic efficiency.

[0082] In some embodiments, Figure 6 As shown, a vehicle queuing method provided in an embodiment of the present application may further include S301-S302:

[0083] S301, determine the number of vehicles f arriving at the mth lane of the target intersection at the target time t m (t).

[0084] It can be understood that each lane will have a certain number of vehicles arriving at each time interval, and which lane the vehicle drives to needs to be determined by an algorithm. Therefore, the number of vehicles arriving in each lane queue is determined by an algorithm. m (t) represents the number of vehicles that reach the target lane (i.e., the mth lane) at the target time t after the driving strategy judgment, i.e.

[0085] S302, based on P m (t), Q m (t), f m (t), the queue length Q of the vehicles in the mth lane of the target intersection at the next moment after the target moment is determined m (t+1).

[0086] Optionally, after determining the optimal driving decision strategy of the target vehicle (i.e., the target lane in which the target vehicle is traveling at the target intersection), the number of vehicles in all lanes needs to be updated. m (t+1)=max{Q m (t)-p m (t),0}+f m (t) OK.

[0087] Understandable, Q mThe larger (t) is, the longer the queue waiting time is. Based on Lyapunov optimization theory, based on Lyapunov function Then Q m Substituting (t+1) into L(t+1)-L(t) for derivation, we can get Formula 5:

[0088]

[0089] The derivation of the function refers to a theorem: Assuming that W, U, μ and A are non-negative positive real numbers, and W = max[U-μ,0]+A, we can get W 2 ≤U 2 +A 2 -2U(μ-A).

[0090] In the embodiment of the present application, the number of vehicles f arriving at the mth lane of the target intersection at the target time t can be further determined. m (t), so that at the next moment after the target moment, the queue length Q of the vehicles included in the mth lane of the target intersection is predetermined m (t+1), so that at the next moment after the target moment, the queue length Q of the vehicles included in the mth lane in the target intersection can be calculated based on m (t+1), determine the lanes that other vehicles are traveling in at the target intersection

[0091] In some embodiments, Figure 7 As shown, in a vehicle queuing method provided in an embodiment of the present application, the method in S202 above may specifically include S401-S402:

[0092] S401, confirm With v n The first ratio between m (t) and P m (t) is a second ratio between the two.

[0093] S402: Determine the sum of the first ratio and the second ratio as the driving time of the target vehicle to the mth lane in the target intersection

[0094] Optionally, the driving time of the target vehicle in the queue of each lane can be obtained according to Formula 6.

[0095]

[0096] In the embodiment of the present application, the distance from the target vehicle to the mth lane in the target intersection can be The current speed of the target vehicle v n, the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), accurately determine the driving time of the target vehicle to the mth lane of the target intersection through a specific algorithm Thereby, the accuracy of determining the driving time of the target vehicle to the mth lane in the target intersection can be improved.

[0097] In some embodiments, Figure 8 As shown, in a vehicle queuing method provided by an embodiment of the present application, the method in S203 above may specifically include S501-S502:

[0098] S501. Determine a first product between a first ratio and a first parameter, and determine a first product between a second ratio and a second parameter.

[0099] S502: Determine the sum of the first product and the second product as the driving cost of the target vehicle traveling to the mth lane in the target intersection.

[0100] Optionally, the driving cost of the target vehicle in each lane at the target intersection can be determined as in It represents the cost that the target vehicle has to pay to travel to the queue in the mth lane at the target time t.

[0101] Optionally, the driving cost of the target vehicle traveling to each lane can be obtained according to Formula 7, where: is the first parameter, which indicates the driving cost of the vehicle per unit time. is the second parameter, which represents the waiting cost of the vehicle in the queue per unit time.

[0102]

[0103] In the embodiment of the present application, the distance from the target vehicle to the mth lane in the target intersection can be The current speed of the target vehicle v n , the number of vehicles P allowed to pass through the mth lane at the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), further combining the preset first parameter and the second parameter, through a specific algorithm, accurately determine the driving cost of the target vehicle traveling to the mth lane in the target intersection Thereby, the accuracy of determining the driving cost of the target vehicle traveling to the mth lane in the target intersection can be improved.

[0104] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, the vehicle queuing device or electronic device includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0105] The embodiments of the present application can exemplarily divide the functional modules of the vehicle queuing device or the electronic device according to the above method. For example, the vehicle queuing device or the electronic device can include various functional modules corresponding to the various functional divisions, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0106] Fig. 9 is a block diagram of a vehicle queuing device according to an exemplary embodiment. Fig. 9 The vehicle queuing device 900 includes: a processing module 901.

[0107] Processing module 901 is used to determine vehicle driving information and road information for a target vehicle passing through a target intersection at a target time t, wherein the vehicle driving information includes: the distance from the target vehicle to the mth lane in the target intersection; The current speed of the target vehicle v n , the road information includes: the number of vehicles P allowed to pass in the mth lane of the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), the target intersection includes M lanes, and the target vehicle is the nth vehicle among the N vehicles passing through the target intersection at the target time; the processing module 901 is also used for v n , P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection The processing module 901 is also used based on v n , P m (t), Q m (t), the first parameter, and the second parameter determine the driving cost of the target vehicle traveling to the mth lane in the target intersection The first parameter is used to indicate the driving cost of the target vehicle per unit time, and the second parameter is used to indicate the waiting cost of the target vehicle in the queue per unit time; the processing module 901 is also used to calculate the target vehicle's waiting cost based on the preset control parameters, Q m (t) v n , P m (t) and A target lane for a target vehicle to travel in a target intersection when a target optimization equation takes a minimum value is determined, and a preset control parameter is used to indicate the degree of emphasis on the minimum cost.

[0108] In a possible implementation, the processing module 901 is further configured to determine the number of vehicles f arriving at the mth lane of the target intersection at the target time t. m (t); Processing module 901 is also used based on P m (t), Q m (t), f m (t), the queue length Q of the vehicles in the mth lane of the target intersection at the next moment after the target moment is determined m (t+1).

[0109] In a possible implementation, the processing module 901 is specifically configured to determine With v n The first ratio between m (t) and P m (t); a processing module 901, specifically for determining the sum of the first ratio and the second ratio as the driving time of the target vehicle to the mth lane in the target intersection

[0110] In a possible implementation, the processing module 901 is specifically used to determine a first product between the first ratio and the first parameter, and to determine a first product between the second ratio and the second parameter; the processing module is specifically used to determine the sum of the first product and the second product as the driving cost of the target vehicle traveling to the mth lane in the target intersection.

[0111] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0112] Fig.10 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Fig.10 As shown, the electronic device 1000 includes but is not limited to: a processor 1001 and a memory 1002 .

[0113] The memory 1002 is used to store executable instructions of the processor 1001. It can be understood that the processor 1001 is configured to execute instructions to implement the vehicle queuing method in the above embodiment.

[0114] It should be noted that those skilled in the art can understand that Fig.10 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and the electronic device may include Fig.10 More or fewer components may be shown, or certain components may be combined, or the components may be arranged differently.

[0115] The processor 1001 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 1002, and calling data stored in the memory 1002, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. The processor 1001 may include one or more processing units. Optionally, the processor 1001 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 1001.

[0116] The memory 1002 may be used to store software programs and various data. The memory 1002 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one functional module (such as an acquisition module, a processing module, etc.), etc. In addition, the memory 1002 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0117] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 1002 including instructions. The above instructions can be executed by the processor 801 of the electronic device 1000 to implement the vehicle queuing method in the above embodiment.

[0118] In actual implementation, Fig. 9 The functions of the processing module 901 in Fig.10 The processor 1001 in the memory 1002 calls the computer program stored in the memory 1002. The specific execution process can refer to the description of the vehicle queuing method in the above embodiment, which will not be repeated here.

[0119] Optionally, the computer-readable storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0120] In an exemplary embodiment, the embodiment of the present application also provides a computer program product including one or more instructions, which can be executed by the processor 1001 of the electronic device 1000 to complete the vehicle queuing method in the above embodiment.

[0121] It should be noted that when the instructions in the above-mentioned computer-readable storage medium or one or more instructions in the computer program product are executed by the processor of the electronic device, the various processes of the above-mentioned vehicle queuing method embodiment are implemented, and the same technical effect as the above-mentioned vehicle queuing method can be achieved. In order to avoid repetition, they will not be repeated here.

[0122] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0123] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0124] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0125] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the full classification part or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute the full classification part or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, ROM, RAM, disk or CD and other media that can store program code.

[0127] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A vehicle queuing method, characterized in that: include: For a target vehicle passing through a target intersection at a target time t, determine vehicle driving information and road information, wherein the vehicle driving information includes: the distance from the target vehicle to the mth lane in the target intersection; The current speed v of the target vehicle n , the road information includes: the number of vehicles P allowed to pass through the mth lane in the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), the target intersection includes M lanes, and the target vehicle is the nth vehicle among N vehicles passing through the target intersection at the target time; Based on the The v n , the P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection Based on the The v n , the P m (t), Q m (t), the first parameter, the second parameter, determine the driving cost of the target vehicle to the mth lane in the target intersection The first parameter is used to indicate the driving cost of the target vehicle per unit time, and the second parameter is used to indicate the waiting cost of the target vehicle queuing in a queue per unit time; Based on the preset control parameters, the Q m (t), The v n , the P m (t), and stated A target lane for the target vehicle to travel in the target intersection is determined when the target optimization equation takes a minimum value, and the preset control parameter is used to indicate the degree of emphasis on the minimum cost.

2. The method according to claim 1, characterized in that: The method further comprises: Determine the number of vehicles f that arrive at the mth lane of the target intersection at the target time t m (t); Based on the P m (t), Q m (t), said f m (t), when determining the next moment after the target moment, the queue length Q of the vehicles in the mth lane of the target intersection m (t+1).

3. The method according to claim 1 or 2, characterized in that: Based on the The v n , the P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection include: Determine the With the v n The first ratio between the m (t) with the P m (t) a second ratio between; The sum of the first ratio and the second ratio is determined as the driving time of the target vehicle to the mth lane in the target intersection.

4. The method according to claim 3, characterized in that Based on the The v n , the P m (t), Q m (t), the first parameter, the second parameter, determine the driving cost of the target vehicle to the mth lane in the target intersection include: determining a first product between the first ratio and the first parameter, and determining a first product between the second ratio and the second parameter; The sum of the first product and the second product is determined as the driving cost of the target vehicle traveling to the mth lane in the target intersection.

5. A vehicle queuing device, characterized in that: The vehicle queuing device comprises: a processing module; The processing module is used to determine vehicle driving information and road information for a target vehicle passing through a target intersection at a target time t, wherein the vehicle driving information includes: the distance from the target vehicle to the mth lane in the target intersection The current speed v of the target vehicle n , the road information includes: the number of vehicles P allowed to pass through the mth lane in the target intersection at the target time m (t), the queue length Q of the vehicles in the mth lane at the target intersection m (t), the target intersection includes M lanes, and the target vehicle is the nth vehicle among N vehicles passing through the target intersection at the target time; The processing module is also used to The v n , the P m (t), Q m (t), determine the driving time of the target vehicle to the mth lane in the target intersection The processing module is also used to The v n , the P m (t), Q m (t), the first parameter, the second parameter, determine the driving cost of the target vehicle to the mth lane in the target intersection The first parameter is used to indicate the driving cost of the target vehicle per unit time, and the second parameter is used to indicate the waiting cost of the target vehicle queuing in a queue per unit time; The processing module is also used to control the Q m (t), The v n , the P m (t), and stated A target lane for the target vehicle to travel in the target intersection is determined when the target optimization equation takes a minimum value, and the preset control parameter is used to indicate the degree of emphasis on the minimum cost.

6. The vehicle queuing device according to claim 5, characterized in that: The processing module is also used to determine the number of vehicles f arriving at the mth lane in the target intersection at the target time t. m (t); The processing module is also used to m (t), Q m (t), said f m (t), when determining the next moment after the target moment, the queue length Q of the vehicles in the mth lane of the target intersection m (t+1).

7. The vehicle queuing device according to claim 5 or 6, characterized in that: The processing module is specifically used to determine the With the v n The first ratio between the m (t) with the P m (t) a second ratio between; The processing module is specifically used to determine the sum of the first ratio and the second ratio as the driving time of the target vehicle to the mth lane in the target intersection.

8. An electronic device, characterized in that: include: A processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer-executable instructions. When the electronic device is running, the processor executes the computer-executable instructions stored in the memory to enable the electronic device to perform the method described in any one of claims 1 to 4.

9. A computer-readable storage medium, characterized in that: When the computer-executable instructions stored in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can perform the method as claimed in any one of claims 1 to 4.

10. A vehicle, characterized in that: The vehicle comprises the vehicle queuing device according to claim 6, and the vehicle is used to implement the method according to any one of claims 1 to 4.

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