Traffic control method, device, equipment and readable storage medium

Abstract

This invention provides a traffic control method, apparatus, device, and readable storage medium, relating to the field of traffic control technology. The method includes acquiring the vehicle flow direction and target length of a target road; obtaining multiple target links and the link length of each target link; acquiring the initial traffic state of each target link at the current moment; obtaining the future traffic state; inputting the initial and future traffic states into a preset control variable prediction model to obtain target control variables; and controlling the maximum vehicle speed and lane width on each target link at the current moment based on the target speed limit and the target number of occupied lanes. This invention employs combined virtual obstacles to exert a moderate adverse effect on upstream traffic flow in a bottleneck area, reducing the flow entering the bottleneck area. Simultaneously, combined with variable speed limits, it slows the increase in bottleneck area density and maintains higher flow rates, thereby achieving lower delays and higher road utilization.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic control, and in particular to a traffic control method, device, equipment and a readable storage medium. Background Art

[0002] Highway congestion is a common traffic problem faced by many countries around the world. It not only prolongs driving time, but also causes excessive exhaust emissions, which has adverse effects on vehicle traffic, traffic safety and the environment. In the existing technology, a variable speed limit (VSL) is used to adjust the speed limit upstream of the bottleneck area, control the traffic flow entering the bottleneck area, and thus alleviate road congestion.

[0003] Although the method of controlling vehicle speed through VSL can accurately adjust the vehicle's status, it will be a huge challenge to computing resources when it is promoted to the entire road network level. Moreover, when a major traffic accident occurs, the effect of applying only VSL is not ideal. Summary of the invention

[0004] The purpose of the present invention is to provide a traffic control method, device, equipment and readable storage medium to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a traffic control method, comprising:

[0006] Obtain the vehicle flow direction and target length of the target road;

[0007] Dividing the target road based on the vehicle flow direction and the target length to obtain a plurality of target links and a link length of each target link;

[0008] Acquire the initial traffic state of each target link at the current moment, wherein the initial traffic state includes the average vehicle density and the average vehicle speed of each target link at the current moment;

[0009] Inputting the initial traffic state into a preset link queue model to obtain a future traffic state, wherein the future traffic state includes an average vehicle density and an average vehicle speed of each target link after a preset target time;

[0010] Bringing the initial traffic state and the future traffic state into a preset control variable prediction model to obtain target control variables, wherein the target control variables include a target speed limit value and a target number of occupied lanes for each target link;

[0011] Based on the target speed limit value and the target number of occupied lanes, the maximum vehicle speed and lane width on each target link at the current moment are controlled accordingly.

[0012] In a second aspect, the present application also provides a traffic control device, comprising:

[0013] A first acquisition unit, used to acquire the vehicle flow direction and target length of the target road;

[0014] A dividing unit, configured to divide the target road based on the vehicle flow direction and the target length to obtain a plurality of target links and a link length of each target link;

[0015] A second acquisition unit is used to acquire an initial traffic state of each target link at a current moment, wherein the initial traffic state includes an average vehicle density and an average vehicle speed of each target link at a current moment;

[0016] A first input unit, used to input the initial traffic state into a preset link queue model to obtain a future traffic state, wherein the future traffic state includes an average vehicle density and an average vehicle speed of each target link after a preset target time;

[0017] A first input unit is used to input the initial traffic state and the future traffic state into a preset control variable prediction model to obtain a target control variable, wherein the target control variable includes a target speed limit value and a target number of occupied lanes for each target link;

[0018] The control unit is used to control the maximum vehicle speed and lane width on each target link at the current moment accordingly based on the target speed limit value and the target number of occupied lanes.

[0019] In a third aspect, the present application also provides a traffic control device, including:

[0020] Memory for storing computer programs;

[0021] A processor is used to implement the steps of the traffic control method when executing the computer program.

[0022] In a fourth aspect, the present application further provides a readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the steps of the above-mentioned traffic control method.

[0023] The beneficial effects of the present invention are:

[0024] The present invention uses a combined virtual obstacle (VO) to exert a moderate adverse effect on the traffic flow upstream of the bottleneck area to reduce the flow entering the bottleneck area. At the same time, it cooperates with a variable speed limit (VSL) to slow down the growth of the density of the bottleneck area and maintain a higher flow, thereby achieving lower delays and higher road utilization.

[0025] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 A flow chart of a traffic control method according to an embodiment of the present invention;

[0028] Figure 2 A schematic diagram of a link described in an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of the relationship between road traffic flow and lane width described in an embodiment of the present invention;

[0030] Figure 4 A schematic diagram of the relationship between the road traffic flow and the number of occupied lanes described in an embodiment of the present invention;

[0031] Figure 5 Schematic diagram of the control flow described in an embodiment of the present invention;

[0032] Figure 6 It is a schematic diagram of the structure of the traffic control device described in an embodiment of the present invention;

[0033] Figure 7 It is a schematic diagram of the structure of the traffic control device described in the embodiment of the present invention.

[0034] Markings in the figure:

[0035] 10. First acquisition unit; 20. Division unit; 30. Second acquisition unit; 40. First input unit; 50. First bringing-in unit; 60. Control unit;

[0036] 800, traffic control device; 801, processor; 802, memory; 803, multimedia component; 804, I / O interface; 805, communication component. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0038] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0039] Embodiment 1:

[0040] This embodiment provides a traffic control method.

[0041] See also Figure 1 , the figure shows that the method includes step S10, step S20, step S30, step S40, step S50 and step S60.

[0042] Step S10. Obtaining the vehicle flow direction and target length of the target road;

[0043] Step S20. Divide the target road based on the vehicle flow direction and the target length to obtain a plurality of target links and the link length of each target link;

[0044] Specifically, a Link Queue Model (LQM) is established on the highway to simulate the road traffic operation status. Assume that the total length of the road is L, which is divided into N links, such as Figure 2 As shown, link i represents link i; linki+1 represents link i+1; ρ i (k) is the average vehicle density of link i at time k*T; ρ i+1(k) is the average vehicle density of link i+1 at time k*T; q i-1 (k) is the traffic flow leaving link i-1 at time k*T; q i (k) is the traffic flow leaving link i at time k*T; q i+1 (k) is the traffic flow leaving link i+1 at time k*T; T is the unit time step; in this application, the unit time step is set to 10 seconds, which can be set according to actual conditions and is not particularly limited here.

[0045] Step S30. Obtaining the initial traffic state of each target link at the current moment, the initial traffic state includes the average vehicle density and average vehicle speed of each target link at the current moment;

[0046] Step S40. Input the initial traffic state into the preset link queue model to obtain the future traffic state, which includes the average vehicle density and average vehicle speed of each target link after the preset target time;

[0047] Specifically, the traffic status at a certain moment in the future is predicted based on the traffic status at the current moment. When a slow-moving vehicle appears in the predicted traffic status at the future moment, the vehicle driving status at the current moment is adjusted in time to ensure that there will be no slow-moving sections in the traffic status at the future moment, thereby improving the driving experience of the driver and passengers.

[0048] Step S50. Bring the initial traffic state and the future traffic state into the preset control variable prediction model to obtain the target control variable, which includes the target speed limit value and the target number of occupied lanes for each target link;

[0049] Specifically, the present application adopts a coordinated control of a combination of virtual obstacle (VO) and variable speed limit (VSL) to ensure a smooth transition of traffic status when a bottleneck occurs on the road; the implementation of VSL aims to control the traffic flow entering the bottleneck area by adjusting the speed limit upstream of the bottleneck area, and the implementation of VO aims to take some measures upstream of the bottleneck area to impose virtual obstacles on the upstream traffic flow to occupy part of the lanes, thereby reducing the flow entering the bottleneck area; VO and VSL work together to reduce the flow entering the bottleneck area, slow down the growth of the density of the bottleneck area and maintain a higher flow, thereby achieving lower delays and higher road utilization.

[0050] Specifically, step S50 specifically includes step S501, step S502, step S503, step S504, step S505 and step S506:

[0051] Step S501. Generate initial control variables based on future traffic conditions, the initial control variables including an initial speed limit value and an initial number of occupied lanes for each target link;

[0052] Step S502. First adjustment operation: updating the initial traffic state based on the initial control variable to obtain a first traffic state;

[0053] Specifically, step S502 specifically includes step S5021, step S5022, step S5023, step S5024, step S5025, step S5026 and step S5027:

[0054] Step S5021. Based on the initial speed limit value of each target link and the average speed of vehicles at the current moment, a receiving flow function and a sending flow function of each target link are established. The receiving flow function is used to characterize the traffic flow change arriving at the target link, and the sending flow function is used to characterize the traffic flow change leaving the target link;

[0055] Specifically, it is assumed that all vehicles are of the same type, that is, the impact of vehicle type on traffic flow is not considered, where the vehicle density ρ of link i at any time i (k)∈[0,ρ jam ],ρ jam is the blocking density of link i. With the implementation of VSL, the VSL-induced critical density of link i is expressed by the following formula:

[0056]

[0057] in, is the critical density induced by VSL; v lim is the speed limit value for applying VSL;

[0058] The VSL induced capacity of link i is expressed by the following formula:

[0059]

[0060] in, is the traffic flow induced by VSL; v lim is the speed limit value for applying VSL;

[0061] Any road is connected in series by multiple links. The sending flow function and receiving flow function of the link can be expressed as:

[0062]

[0063] Among them, S(S(ρ i (k))) is the sending flow function of link i; R(R(ρ i (k))) is the receiving flow function of link i; q(ρi (k)) is the traffic flow of link i at time k*T; is the capacity induced by VSL;

[0064] Step S5022. Based on the receiving flow function and the sending flow function of each target link, determine the first flow of each target link in a unit time, the first flow is used to characterize the traffic flow entering the target link in a unit time under the influence of the initial speed limit value;

[0065] Specifically, for link i, its incoming traffic is the minimum value of the sending traffic of link (i-1) and the receiving traffic of link i:

[0066] q i (k) = min{S(ρ i-1 (k)), R(ρ i (k))}

[0067] Among them, q i (k) is the traffic flow of link i at time k*T; S(ρ i-1 (k)) is the transmission flow of link (i-1) at time k*T; R(ρ i (k)) is the received traffic of link i at time k*T.

[0068] Step S5023. Based on the initial number of occupied lanes of each target link, determine the second flow rate of each target link in a unit time, the second flow rate is used to characterize the traffic flow entering the target link in a unit time under the influence of the initial number of occupied lanes;

[0069] Specifically, in the prior art, there is a quadratic curve relationship between road traffic volume and lane width, such as Figure 3 As shown, the formula is as follows:

[0070] q max =-2184-22.6(w R ) 2 +857.4(w R )

[0071] Among them, w R is the road width, q max is the road traffic volume;

[0072] When the road width is between 6 meters and 12 meters, the road traffic flow and road width show an approximately linear relationship. In order to simplify the model, this application uses a linear model to describe the impact of road width on traffic flow, such as Figure 4 As shown, in order to enhance the applicability of the model, it is assumed that all highway lanes are standard lanes with the same width, thereby obtaining the relationship between lane width and traffic capacity in this application:

[0073]

[0074] Among them, q max is the traffic capacity of the regular road section. is the traffic capacity of the bottleneck section, N R is the number of lanes on a regular road section, N VO The number of lanes occupied by VO.

[0075] Step S5024. Based on the first flow and the second flow, determine the target flow of each target link, the target flow is used to characterize the flow that actually enters the target link within a unit time;

[0076] Step S5025. Update the average vehicle density of each target link based on the target flow of each target link to obtain the updated average vehicle density of each target link;

[0077] Specifically, according to the conservation law, the number of vehicles in link i at time (k+1)*T is equal to the number of vehicles in link i at time k*T plus the number of vehicles entering link i, minus the number of vehicles leaving link i. The calculation formulas for the number of vehicles in the link and the vehicle density are as follows:

[0078] x i (k+1)=x i (k)+[q i-1 (k)-q i (k)]*T

[0079] Among them, x i (k+1) is the number of vehicles on link i at time (k+1)*T; x i (k) is the number of vehicles on link i at time k*T; q i-1 (k) is the traffic flow of link i-1 at time k*T; q i (k) is the traffic flow of link i at time k*T; T is the unit time step; l i is the length of link i;

[0080]

[0081] Among them, ρ i (k+1) is the average vehicle density of link i at time (k+1)*T; ρ i (k) is the average vehicle density of link i at time k*T; q i-1 (k) is the traffic flow of link i-1 at time k*T; q i (k) is the traffic flow of link i at time k*T; T is the unit time step; l i is the length of link i;

[0082] Step S5026. Update the average vehicle speed of each target link based on the updated average vehicle density of each target link to obtain the updated average vehicle speed of each target link;

[0083] Specifically, step S5026 specifically includes step S50261, step S50262, step S50263, step S50264, step S50265 and step S50266:

[0084] Step S50261. Calculate the ratio of the updated average vehicle density of each target link to the first set threshold value to obtain a plurality of first values;

[0085] Step S50262. Calculate the function value with each first value as the base and the second set threshold as the exponent to obtain multiple second values;

[0086] Step S50263. Calculate the opposite of each second value to obtain a plurality of third values;

[0087] Step S50264. Calculate the function value with the natural constant as the base and each third value as the exponent to obtain a plurality of fourth values;

[0088] Step S50265. Calculate the product of each fourth value and the third set threshold value respectively to obtain multiple fifth values;

[0089] Step S50266. Compare the initial speed limit value corresponding to each target link with the corresponding fifth value, and use the smaller value between the fourth value and the initial speed limit value as the updated average vehicle speed of each target link;

[0090] Specifically, the average speed of vehicles in the link is calculated as follows:

[0091]

[0092] Among them, v(ρ i (k)) is the average speed of vehicles on link i at time k*T; v i lim (k) is the speed limit value of VSL applied to link i at time k*T; ρ i (k) is the average vehicle density of link i at time k*T.

[0093] Step S5027. Taking the updated average vehicle density and the updated average vehicle speed of each target link as the first traffic state;

[0094] Specifically, the average vehicle density and the average vehicle speed of each target link are updated based on the applied VSL.

[0095] Step S503. Input operation: input the first traffic state into the link queue model for calculation to obtain the second traffic state;

[0096] Step S504. Calculation operation: Calculate a preset first objective function based on the first traffic state and the second traffic state to obtain an objective function value;

[0097] Specifically, the present application takes the improvement of system traffic efficiency as the optimization goal, and the objective function consists of three parts: the first part is the total travel time (TTT), which is the sum of the driving time of all vehicles during the simulation, including the driving time of the vehicle on the target road and the queuing time of the vehicle before entering the target road; the second part is the total travel distance (TTD), which represents the total travel distance of all vehicles during the simulation. This indicator reflects the utilization rate of the road system; the third part is the penalty term for speed limit changes, namely abrupt variations in speed (AVS). The introduction of this indicator aims to balance the changes in the speed limit control signal.

[0098] Specifically, step S504 specifically includes step S5041, step S5042, step S5043, step S5044, step S5045, step S5046, step S5047, step S5048, step S50410, step S50411 and step S50412:

[0099] Step S5041. Obtain the initial number of lanes and speed limit value of each target link;

[0100] Step S5042. Determine multiple time points within the target time as multiple target time points;

[0101] Step S5043. Obtain the number of vehicles that failed to enter the target road corresponding to each target time point;

[0102] Step S5044. Obtain the vehicle density of each target link and the number of occupied lanes of each target link corresponding to each target time point;

[0103] Step S5045. Based on the average vehicle density, link length, number of initial lanes, number of occupied lanes, and number of vehicles that failed to enter the target road at each target time point, the total travel time is calculated. The total travel time is used to represent the driving time of all vehicles on the target road and the waiting time before entering the target road;

[0104] Step S5046. Based on the average vehicle density, average vehicle speed, link length, number of initial lanes, number of occupied lanes and a preset total mileage coefficient of each target link corresponding to each target time point, the total mileage is calculated, and the total mileage is used to characterize the lane utilization rate of the target road;

[0105] Step S5047. Obtaining a preset control time;

[0106] Step S5048. Obtain the original speed limit value of each target link, where the original speed limit value is the speed limit value of the target link at the current moment;

[0107] Step S5049. Determine multiple time points within the control time as multiple control time points;

[0108] Step S50410. Determine a link whose initial speed limit value differs from the original speed limit value from among the multiple target links as a speed limit link;

[0109] Step S50411. Based on the initial speed limit value, the maximum speed limit value and the preset speed mutation coefficient of each control link corresponding to each control time point, a speed mutation value is calculated, and the speed mutation value is used to characterize the change range of the initial speed limit value;

[0110] Step S50412. Sum the total travel time, total mileage and speed mutation value to obtain the objective function value;

[0111] Specifically, the formula of the objective function is:

[0112]

[0113] Among them, J(k c ) is the objective function; T is the unit time step; k c is the discrete time index of the controller; N p N is the time range for predicting traffic status; c is the time range for applying the control signal; l i is the link length of link i; N R is the number of lanes in a normal road section; is the number of lanes occupied by VO at time j; ω(j) is the number of vehicles that failed to enter the target road due to congestion at time j; ξ TTD is the coefficient of TTD; v i (h) is the average speed of vehicles on link i at time j; ξ AVS is the coefficient of AVS; For link i in l c The speed limit value of VSL applied at the moment; v max is the maximum speed limit of the road; I allis the index set of all links; I speed is the index set of the links to which VSL is applied; M is a positive integer;

[0114] In order to control the impact of speed limit changes on drivers and make it easier for drivers to adapt to traffic conditions, this application limits the speed limit change range, limits the speed limit change of the same link within two adjacent control cycles, limits the speed limit change of two adjacent links at the same time, and limits the maximum and minimum values ​​of VSL, thereby enhancing the overall stability of the control strategy. The speed limit formula is as follows:

[0115]

[0116] in, is the maximum driving speed of link i when VSL is applied at time k*T; Δv max is the preset speed limit change threshold; v min is the minimum speed limit of the road; v max is the maximum speed limit of the road;

[0117] Similarly, for the sake of safety and traffic flow, this study limits the number of VO lanes occupied, limits the maximum change of the number of VO lanes occupied between two adjacent control cycles, and limits the maximum and minimum values ​​of the number of VO lanes occupied. The formula for limiting the number of lanes occupied is as follows:

[0118]

[0119] in, is the number of occupied lanes for link i to which VO is applied at time k*T; ΔN max is a preset threshold value for the change in the number of occupied lanes; is the maximum number of occupied lanes on the road; is the minimum number of occupied lanes on the road.

[0120] Step S505. Second adjustment operation: optimizing the initial control variables based on the genetic algorithm, and updating the initial control variables based on the optimization results to obtain optimized initial control variables;

[0121] Specifically, the traditional genetic algorithm randomly generates a population based on the upper and lower limit constraints of the control variables, but not all randomly generated individuals are feasible solutions, that is, the randomly generated individuals cannot meet all the constraints of this study. The change of the speed limit value of a link will not only affect the current link speed limit, but also affect the speed limit values ​​of the subsequent control time domain and the subsequent links. Due to the large number of these coupled constraints, if these constraints are roughly used as penalty items, the penalty item will be larger than the objective function. At the same time, due to the large variation range of the penalty item, the randomness of the solution is greatly increased, which greatly affects the effect of the solution, and may even fail to obtain a solution better than the initial solution. In order to overcome this problem, after randomly generating individuals or mutations, this study corrects the individuals that do not meet the constraints. At the same time, in order to enhance the local search ability of the genetic algorithm, this study adopts Gray coding. When performing function optimization, Gray coding can better eliminate the "Hamming cliff" problem.

[0122] Step S505 specifically includes step S5051, step S5052, step S5053, step S5054, step S5055, step S5056, step S5057, step S5058 and step S5059:

[0123] Step S5051. Generate a target range based on the initial control variable and the preset range value;

[0124] Step S5052. Randomly generate a plurality of first control variables within the target range;

[0125] Step S5053. Represent each first control variable based on Gray coding to obtain multiple second control variables;

[0126] Step S5054. Calculate the fitness of each second control variable to obtain a plurality of first fitness values;

[0127] Step S5055. Based on the preset roulette wheel selection strategy and the plurality of first fitness values, a plurality of third control variables are determined from the plurality of second control variables;

[0128] Step S5056. Perform a crossover operation on all third control variables to generate multiple fourth control variables;

[0129] Step S5057. Perform a mutation operation on each fourth control variable to generate multiple fifth control variables;

[0130] Step S5058. Calculate a preset second objective function based on the fifth control variable to obtain a variable function value;

[0131] Step S5059. Determine the minimum variable function value from the multiple variable function values, and perform inverse Gray coding on the fifth control variable corresponding to the minimum variable function value to obtain an adjusted initial control variable;

[0132] Specifically, first initialize the population, randomly generate a certain number of control variable individuals, each control variable individual contains two types of parameters, namely, speed limit value and number of occupied lanes, and all control variable individuals constitute the initial population; Gray code all control variable individuals to obtain control variable individuals in Gray code form; calculate the fitness of each individual, and measure the quality of the individual according to the calculated fitness value; select individuals according to the fitness value, usually using roulette selection or tournament selection, and select individuals with higher fitness as parents for the next generation; perform crossover operations on the selected parent individuals to generate new control variable individuals to increase the diversity and exploration space of the population; perform mutation operations on the generated new individuals to increase the diversity of the population and avoid falling into the local optimal solution; update the current population according to the new individuals generated by selection, crossover and mutation operations. Repeat the above steps until the stop condition is reached, such as reaching the maximum number of iterations or the convergence of the objective function value, etc., perform Gray decoding on the optimal control variable individual, and output the optimal control variable individual.

[0133] Step S506. Repeat the first adjustment operation, input operation, calculation operation and second adjustment operation until the objective function value converges, and take the initial control variable corresponding to the minimum objective function value as the target control variable;

[0134] Specifically, the present application adopts a model predictive control (MPC) strategy to solve the infinite time domain optimal control problem online through rolling iterations in a finite time domain. It has the advantage of overcoming the interference of system uncertainties, and at the same time exhibits strong robustness, good control effect, and is easy to handle multiple variables and multiple constraints. In an interconnected environment based on MPC and LQM, the present application designs a VSL&VO controller.

[0135] The entire control process of the VSL&VO controller based on LQM is as follows: Figure 5 As shown in the figure, λ(k) represents the vehicle arrival rate at time k*T, ρ(k) represents the average vehicle density at time k*T, and u(k c ) indicates that at control time k c *T c The available control matrix, u * (k c ) represents the input part of the optimal control signal, T is the unit time step, T c To control the time step, k crepresents the discrete time index of the controller, and T and T c Meet T c =M*T, M is a positive integer, N p is the range of predicted traffic status, N c is the range of the applied control signal, in this application N p and N c The units are all in control time step; the initial traffic state is obtained through the road side unit (RSU) and transmitted to the traffic control center (TCC). In the TCC, the collected initial traffic state is used for LQM prediction, and the objective function value is evaluated based on the predicted traffic state at a certain moment in the future and the control variables, and the genetic algorithm (GA) is used as the optimizer of MPC.

[0136] In the rolling horizon scheme, a rolling optimization strategy is adopted, which means that in each control time step, only the control actions of the optimal control signal are applied to the road system for traffic control, and then the time axis is moved by time steps, the model is updated and the process is restarted.

[0137] Step S60. Based on the target speed limit value and the target number of occupied lanes, the maximum vehicle speed and lane width on each target link at the current moment are controlled accordingly;

[0138] Specifically, according to the obtained speed limit value and the number of occupied lanes of each link, corresponding control is performed on the vehicles on each link at the current moment, so as to alleviate the traffic congestion that may occur at a future moment in advance.

[0139] Embodiment 2:

[0140] like Figure 6 As shown, this embodiment provides a traffic control device, the device includes

[0141] A first acquisition unit 10 is used to acquire the vehicle flow direction and target length of the target road;

[0142] A division unit 20, configured to divide the target road based on the vehicle flow direction and the target length, and obtain a plurality of target links and a link length of each target link;

[0143] A second acquisition unit 30 is used to acquire an initial traffic state of each target link at a current moment, where the initial traffic state includes an average vehicle density and an average vehicle speed of each target link at a current moment;

[0144] A first input unit 40 is used to input the initial traffic state into a preset link queue model to obtain a future traffic state, wherein the future traffic state includes an average vehicle density and an average vehicle speed of each target link after a preset target time;

[0145] A first input unit 50 is used to input the initial traffic state and the future traffic state into a preset control variable prediction model to obtain a target control variable, wherein the target control variable includes a target speed limit value and a target number of occupied lanes for each target link;

[0146] The control unit 60 is used to control the maximum vehicle speed and lane width on each target link at the current moment accordingly based on the target speed limit value and the target number of occupied lanes.

[0147] In a specific embodiment disclosed in the present application, the first bringing-in unit 50 includes:

[0148] A first generating unit 51 is used to generate initial control variables based on future traffic conditions, wherein the initial control variables include an initial speed limit value and an initial number of occupied lanes for each target link;

[0149] A first adjustment unit 52 is used for a first adjustment operation: updating an initial traffic state based on an initial control variable to obtain a first traffic state;

[0150] The second input unit 53 is used for input operation: inputting the first traffic state into the link queue model for calculation to obtain the second traffic state;

[0151] A first calculation unit 54 is used for calculation operation: calculating a preset first objective function based on the first traffic state and the second traffic state to obtain an objective function value;

[0152] The second adjustment unit 55 is used for a second adjustment operation: optimizing the initial control variables based on the genetic algorithm, and updating the initial control variables based on the optimization result to obtain the optimized initial control variables;

[0153] The repeating unit 56 is used to repeat the first adjustment operation, the input operation, the calculation operation and the second adjustment operation until the objective function value converges, and the initial control variable corresponding to the minimum objective function value is used as the target control variable.

[0154] In a specific implementation disclosed in the present application, the first adjustment unit 52 includes:

[0155] An establishing unit 521 is used to establish a receiving flow function and a sending flow function of each target link based on the initial speed limit value of each target link and the average speed of the vehicle at the current moment, wherein the receiving flow function is used to characterize the flow change arriving at the target link, and the sending flow function is used to characterize the flow change leaving the target link;

[0156] A first determining unit 522 is used to determine a first flow rate of each target link within a unit time based on a receiving flow rate function and a sending flow rate function of each target link, wherein the first flow rate is used to characterize a traffic flow rate entering the target link within a unit time under the influence of the initial speed limit value;

[0157] A second determining unit 523 is used to determine a second flow rate of each target link in a unit time based on the initial number of occupied lanes of each target link, where the second flow rate is used to characterize the traffic flow entering the target link in a unit time under the influence of the initial number of occupied lanes;

[0158] A third determining unit 524 is used to determine a target flow rate of each target link based on the first flow rate and the second flow rate, where the target flow rate is used to characterize the flow rate actually entering the target link within a unit time;

[0159] A first updating unit 525, configured to update the average vehicle density of each target link based on the target flow of each target link, and obtain an updated average vehicle density of each target link;

[0160] A second updating unit 526, configured to update the average vehicle speed of each target link based on the updated average vehicle density of each target link to obtain the updated average vehicle speed of each target link;

[0161] As unit 527, it is used to use the updated average vehicle density and the updated average vehicle speed of each target link as the first traffic state.

[0162] In a specific implementation disclosed in the present application, the first calculation unit 54 includes:

[0163] The third acquisition unit 541 is used to acquire the initial number of lanes and speed limit value of each target link;

[0164] A fourth determining unit 542 is used to determine multiple time points within the target time as multiple target time points;

[0165] The fourth acquisition unit 543 is used to acquire the number of vehicles that failed to enter the target road corresponding to each target time point;

[0166] A fifth acquisition unit 544 is used to acquire the vehicle density of each target link and the number of occupied lanes of each target link corresponding to each target time point;

[0167] The second calculation unit 545 is used to calculate the total travel time based on the average vehicle density, link length, initial lane number, occupied lane number and number of vehicles that failed to enter the target road of each target link corresponding to each target time point, where the total travel time is used to represent the travel time of all vehicles on the target road and the waiting time before entering the target road;

[0168] The third calculation unit 546 is used to calculate the total mileage based on the average vehicle density, average vehicle speed, link length, number of initial lanes, number of occupied lanes and a preset total mileage coefficient of each target link corresponding to each target time point, and the total mileage is used to characterize the lane utilization rate of the target road;

[0169] A sixth obtaining unit 547, used to obtain a preset control time;

[0170] The seventh acquisition unit 548 is used to acquire the original speed limit value of each target link, where the original speed limit value is the speed limit value of the target link at the current moment;

[0171] A fifth determining unit 549, configured to determine a plurality of time points within the control time as a plurality of control time points;

[0172] The sixth determining unit 5410 is configured to determine, from the plurality of target links, a link whose initial speed limit value differs from the original speed limit value as a speed limit link;

[0173] The fourth calculation unit 5411 is used to calculate a speed mutation value based on the initial speed limit value, the maximum speed limit value and the preset speed mutation coefficient of each control link corresponding to each control time point, where the speed mutation value is used to characterize the change range of the initial speed limit value;

[0174] The summing unit 5412 is used to sum the total travel time, the total mileage and the speed mutation value to obtain the objective function value.

[0175] In a specific implementation disclosed in the present application, the second adjustment unit 55 includes:

[0176] A second generating unit 551 is used to generate a target range based on the initial control variable and a preset range value;

[0177] A third generating unit 552 is used to randomly generate a plurality of first control variables within a target range;

[0178] A representation unit 553, used for representing each first control variable based on Gray coding to obtain a plurality of second control variables;

[0179] A fifth calculation unit 554 is used to calculate the fitness of each second control variable to obtain a plurality of first fitness values;

[0180] A seventh determination unit 555, configured to determine a plurality of third control variables from a plurality of second control variables based on a preset roulette wheel selection strategy and a plurality of first fitness values;

[0181] A third generating unit 556, configured to perform a crossover operation on all third control variables to generate a plurality of fourth control variables;

[0182] A fourth generating unit 557, configured to perform a mutation operation on each fourth control variable to generate a plurality of fifth control variables;

[0183] A sixth calculation unit 558, configured to calculate a preset second objective function based on the fifth control variable to obtain a variable function value;

[0184] The eighth determining unit 559 is used to determine the minimum variable function value from the multiple variable function values, and perform inverse Gray coding on the fifth control variable corresponding to the minimum variable function value to obtain an adjusted initial control variable.

[0185] In a specific implementation disclosed in the present application, the second updating unit 526 includes:

[0186] The seventh calculation unit 5261 is used to calculate the ratio of the updated average vehicle density of each target link to the first set threshold value to obtain multiple first values;

[0187] An eighth calculation unit 5262, configured to calculate a function value with each first value as a base and a second set threshold as an exponent to obtain a plurality of second values;

[0188] A ninth calculating unit 5263, configured to calculate the opposite of each second value to obtain a plurality of third values;

[0189] A tenth calculation unit 5264, used for calculating a function value with a natural constant as a base and each third value as an exponent to obtain a plurality of fourth values;

[0190] an eleventh calculating unit 5265, configured to respectively calculate the product of each fourth value and the third set threshold value to obtain a plurality of fifth values;

[0191] The comparison unit 5266 is used to compare the initial speed limit value corresponding to each target link with the corresponding fifth value, and take the smaller value between the fourth value and the initial speed limit value as the updated average vehicle speed of each target link.

[0192] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0193] Embodiment 3:

[0194] Corresponding to the above method embodiment, a traffic control device is also provided in this embodiment. The traffic control device described below and the traffic control method described above can refer to each other.

[0195] Figure 7 8 is a block diagram of a traffic control device 800 according to an exemplary embodiment. Figure 7 As shown, the traffic control device 800 may include: a processor 801 and a memory 802. The traffic control device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0196] The processor 801 is used to control the overall operation of the traffic control device 800 to complete all or part of the steps in the above-mentioned traffic control method. The memory 802 is used to store various types of data to support the operation of the traffic control device 800. These data may include, for example, instructions for any application or method operated on the traffic control device 800, and application-related data, such as contact data, messages sent and received, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent through the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the traffic control device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 may include: Wi-Fi module, Bluetooth module, NFC module.

[0197] In an exemplary embodiment, the traffic control device 800 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned traffic control method.

[0198] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned traffic control method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions can be executed by the processor 801 of the traffic control device 800 to complete the above-mentioned traffic control method.

[0199] Embodiment 4:

[0200] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the traffic control method described above can refer to each other.

[0201] A readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the traffic control method of the above method embodiment are implemented.

[0202] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0203] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0204] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0205] Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A traffic control method, characterized in that: include: Obtain the vehicle flow direction and target length of the target road; Dividing the target road based on the vehicle flow direction and the target length to obtain a plurality of target links and a link length of each target link; Acquire the initial traffic state of each target link at the current moment, wherein the initial traffic state includes the average vehicle density and the average vehicle speed of each target link at the current moment; Inputting the initial traffic state into a preset link queue model to obtain a future traffic state, wherein the future traffic state includes an average vehicle density and an average vehicle speed of each target link after a preset target time; Bringing the initial traffic state and the future traffic state into a preset control variable prediction model to obtain target control variables, wherein the target control variables include a target speed limit value and a target number of occupied lanes for each target link; Based on the target speed limit value and the target number of occupied lanes, the maximum speed of vehicles and the lane width on each target link at the current moment are controlled accordingly; The initial traffic state and the future traffic state are brought into a preset control variable prediction model to obtain a target control variable, including: generating initial control variables based on the future traffic state, the initial control variables including an initial speed limit value and an initial number of occupied lanes for each target link; A first adjustment operation: updating the initial traffic state based on the initial control variable to obtain a first traffic state; Input operation: inputting the first traffic state into the link queue model for calculation to obtain a second traffic state; Calculation operation: calculating a preset first objective function based on the first traffic state and the second traffic state to obtain an objective function value; The second adjustment operation: optimizing the initial control variables based on a genetic algorithm, and updating the initial control variables based on the optimization results to obtain optimized initial control variables; The first adjustment operation, the input operation, the calculation operation and the second adjustment operation are repeated until the objective function value converges, and the initial control variable corresponding to the minimum objective function value is used as the target control variable.

2. The traffic control method according to claim 1, characterized in that ,The first adjustment operation: adjusting the initial traffic state based on the initial control variable to obtain a first traffic state, including: Based on the initial speed limit value of each target link and the average speed of vehicles at the current moment, a receiving flow function and a sending flow function of each target link are established, wherein the receiving flow function is used to characterize the change of traffic flow arriving at the target link, and the sending flow function is used to characterize the change of traffic flow leaving the target link; Determine, based on a receiving flow function and a sending flow function of each target link, a first flow of each target link within a unit time, wherein the first flow is used to characterize the flow entering the target link within a unit time under the influence of the initial speed limit value; Based on the initial number of occupied lanes of each target link, determine a second flow rate of each target link within a unit time, where the second flow rate is used to characterize the flow rate entering the target link within a unit time under the influence of the initial number of occupied lanes; Determine a target flow of each target link based on the first flow and the second flow, where the target flow is used to characterize the flow actually entering the target link within a unit time; Based on the target flow of each target link, the average vehicle density of each target link is updated to obtain the updated average vehicle density of each target link; Based on the updated average vehicle density of each target link, the average vehicle speed of each target link is updated to obtain the updated average vehicle speed of each target link; The updated average vehicle density and the updated average vehicle speed of each target link are used as the first traffic state.

3. The traffic control method according to claim 1, characterized in that ,Calculation operation: Calculate the objective function based on the first traffic state and the second traffic state to obtain the objective function value, including: Obtain the initial number of lanes and speed limit value for each target link; Determine multiple time points within the target time as multiple target time points; Obtaining the number of vehicles that failed to enter the target road corresponding to each target time point; Obtain the vehicle density of each target link and the number of occupied lanes of each target link corresponding to each target time point; Based on the average vehicle density, link length, number of initial lanes, number of occupied lanes, and number of vehicles that failed to enter the target road of each target link corresponding to each target time point, the total travel time is calculated, and the total travel time is used to represent the driving time of all vehicles on the target road and the waiting time before entering the target road; Based on the average vehicle density, average vehicle speed, link length, number of initial lanes, number of occupied lanes and a preset total mileage coefficient of each target link corresponding to each target time point, the total mileage is calculated, and the total mileage is used to characterize the lane utilization rate of the target road; Get the preset control time; Obtaining an original speed limit value of each target link, where the original speed limit value is the speed limit value of the target link at the current moment; Determining multiple time points within the control time as multiple control time points; Determine, from the plurality of target links, a link whose initial speed limit value is different from the original speed limit value as a speed limit link; Based on the initial speed limit value, the maximum speed limit value and the preset speed mutation coefficient of each control link corresponding to each control time point, a speed mutation value is calculated, and the speed mutation value is used to characterize the change range of the initial speed limit value; The total travel time, the total mileage and the speed mutation value are summed up to obtain the objective function value.

4. A traffic control device, characterized in that: include: A first acquisition unit, used to acquire the vehicle flow direction and target length of the target road; A dividing unit, configured to divide the target road based on the vehicle flow direction and the target length to obtain a plurality of target links and a link length of each target link; A second acquisition unit is used to acquire an initial traffic state of each target link at a current moment, wherein the initial traffic state includes an average vehicle density and an average vehicle speed of each target link at a current moment; A first input unit, used to input the initial traffic state into a preset link queue model to obtain a future traffic state, wherein the future traffic state includes an average vehicle density and an average vehicle speed of each target link after a preset target time; A first input unit is used to input the initial traffic state and the future traffic state into a preset control variable prediction model to obtain a target control variable, wherein the target control variable includes a target speed limit value and a target number of occupied lanes for each target link; A control unit, configured to control the maximum speed and lane width of vehicles on each target link at the current moment accordingly based on the target speed limit value and the target number of occupied lanes; Wherein, the first bringing-in unit comprises: A first generating unit, configured to generate initial control variables based on the future traffic state, wherein the initial control variables include an initial speed limit value and an initial number of occupied lanes for each target link; A first adjustment unit, configured for a first adjustment operation: updating the initial traffic state based on the initial control variable to obtain a first traffic state; A second input unit is used for input operation: inputting the first traffic state into the link queue model for calculation to obtain a second traffic state; A first calculation unit, configured to perform a calculation operation: calculating a preset first objective function based on the first traffic state and the second traffic state to obtain an objective function value; A second adjustment unit is used for a second adjustment operation: optimizing the initial control variables based on a genetic algorithm, and updating the initial control variables based on the optimization result to obtain optimized initial control variables; A repeating unit is used to repeat the first adjustment operation, the input operation, the calculation operation and the second adjustment operation until the objective function value converges, and use the initial control variable corresponding to the minimum objective function value as the target control variable.

5. The traffic control device according to claim 4, characterized in that: The first adjustment unit comprises: An establishing unit, used to establish a receiving flow function and a sending flow function of each target link based on the initial speed limit value of each target link and the average speed of vehicles at the current moment, wherein the receiving flow function is used to characterize the change of traffic flow arriving at the target link, and the sending flow function is used to characterize the change of traffic flow leaving the target link; a first determining unit, configured to determine a first flow rate of each target link within a unit time based on a receiving flow rate function and a sending flow rate function of each target link, wherein the first flow rate is used to characterize a traffic flow rate entering the target link within a unit time under the influence of the initial speed limit value; A second determination unit is used to determine a second flow rate of each target link within a unit time based on the initial number of occupied lanes of each target link, wherein the second flow rate is used to characterize the traffic flow entering the target link within a unit time under the influence of the initial number of occupied lanes; A third determining unit, configured to determine a target flow rate of each target link based on the first flow rate and the second flow rate, wherein the target flow rate is used to characterize the flow rate actually entering the target link within a unit time; A first updating unit, configured to update the average vehicle density of each target link based on the target flow of each target link, to obtain an updated average vehicle density of each target link; A second updating unit is used to update the average vehicle speed of each target link based on the updated average vehicle density of each target link to obtain the updated average vehicle speed of each target link; As a unit, it is used to take the updated average vehicle density and the updated average vehicle speed of each target link as the first traffic state.

6. The traffic control device according to claim 4, characterized in that: The first computing unit comprises: A third acquisition unit is used to acquire the initial number of lanes and speed limit value of each target link; A fourth determining unit, configured to determine a plurality of time points within the target time as a plurality of target time points; A fourth acquisition unit, used to acquire the number of vehicles that fail to enter the target road corresponding to each target time point; A fifth acquisition unit, used to acquire the vehicle density of each target link and the number of occupied lanes of each target link corresponding to each target time point; A second calculation unit is used to calculate a total travel time based on an average vehicle density, a link length, an initial number of lanes, a number of occupied lanes, and a number of vehicles that fail to enter the target road of each target link corresponding to each target time point, wherein the total travel time is used to represent the travel time of all vehicles on the target road and the waiting time before entering the target road; A third calculation unit is used to calculate the total mileage based on the average vehicle density, average vehicle speed, link length, initial lane number, occupied lane number and a preset total mileage coefficient of each target link corresponding to each target time point, wherein the total mileage is used to characterize the lane utilization rate of the target road; A sixth obtaining unit, used to obtain a preset control time; A seventh acquisition unit, configured to acquire an original speed limit value of each target link, wherein the original speed limit value is the speed limit value of the target link at a current moment; A fifth determining unit, configured to determine a plurality of time points within the control time as a plurality of control time points; a sixth determining unit, configured to determine, from a plurality of target links, a link having a difference between the initial speed limit value and the original speed limit value as a speed limit link; a fourth calculation unit, configured to calculate a speed mutation value based on the initial speed limit value, the maximum speed limit value and a preset speed mutation coefficient of each control link corresponding to each control time point, wherein the speed mutation value is used to characterize a change range of the initial speed limit value; The summing unit is used to sum the total travel time, the total mileage and the speed mutation value to obtain the objective function value.

7. A traffic control device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the traffic control method according to any one of claims 1 to 3 when executing the computer program.

8. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the traffic control method according to any one of claims 1 to 3 are implemented.

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