Signal control method and system based on traffic demand

Abstract

The invention discloses a traffic demand-based signal control method and system, and the method is used for carrying out the signal control of a target intersection, the target intersection is provided with a plurality of target path groups, and the method comprises the following steps: taking a next phase as a target phase when the next phase is in a control time period, and carrying out the signal control of the target intersection; determining a passing path group set corresponding to the target phase based on the time-delay overrun queue and the traffic demand data corresponding to each target path group, wherein the passing path group set comprises a plurality of target path groups which do not conflict with each other; the time lag overrun queue is used for placing an overtime path group, and the overtime path group is a target path group where a vehicle whose current time lag exceeds a preset time lag upper limit is located; the traffic demand data is used for indicating the traffic demand of the corresponding target path group at the target phase. According to the method, the phase sequence can be flexibly optimized according to the time-delay overrun queue and the traffic demand data, so that the traffic efficiency of the intersection is improved.

Description

Technical Field

[0001] The present invention relates to the field of traffic signal control, and in particular to a signal control solution based on traffic demand. Background Art

[0002] Optimizing signal timing is an important means to improve the efficiency of intersection traffic. Uneven traffic demand in all directions at intersections is common, which can easily lead to traffic problems such as wasted green light time, increased vehicle delays, and reduced traffic levels, as well as energy loss. This requires the signal system to fully utilize the efficiency of intersections and minimize delays while ensuring road traffic safety.

[0003] The current traffic signal control timing scheme usually uses signal cycles as units to allocate green light time according to a predetermined combination of phase sequence, duration, and target path. This method is relatively rigid and has limited dynamic response to changes in traffic demand. At intersections where traffic demand varies greatly between different paths, it is easy for green lights on some paths to be wasted while vehicles on other paths are queued, or for vehicles on some low-demand paths to wait for an excessively long time. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a signal control solution based on traffic demand, which can flexibly optimize the phase order according to the time-delay overrun queue and traffic demand data.

[0005] In order to solve the above technical problems, the present invention is solved by the following technical solutions:

[0006] A signal control method based on traffic demand is used to perform signal control on a target intersection, wherein the target intersection has a plurality of target path groups;

[0007] The signal control method comprises the following steps:

[0008] When the next phase is in the control period, the next phase is taken as the target phase, and the set of pass path groups corresponding to the target phase is determined based on the time delay overrun queue and the traffic demand data corresponding to each target path group, and the pass path group set includes a plurality of non-conflicting target path groups;

[0009] The time delay exceeding limit queue is used to place the timeout path group, and the timeout path group is the target path group where the vehicles whose current time delay exceeds the preset time delay upper limit are located;

[0010] The traffic demand data is used to indicate the traffic demand of the corresponding target path group in the target phase.

[0011] As an implementable method, the specific steps of determining the set of traffic path groups corresponding to the target phase based on the time delay excess queue and traffic demand data are as follows:

[0012] Preset an intersection model of the constructed intersection where the target intersection is located, the intersection model is an undirected graph model, the nodes of which are driving path groups corresponding to the constructed intersections, the edges represent that the driving path groups corresponding to the two connected nodes do not conflict with each other, and the driving path groups include a target path group;

[0013] When there is a timeout path group, construct a first candidate set based on the timeout path group, wherein the timeout path groups in the first candidate set do not conflict with each other;

[0014] Based on the intersection model and the traffic demand data, determining a set of pass path groups corresponding to the target phase, wherein the set of pass path groups corresponding to the target phase corresponds to a local maximum complete subgraph in the intersection model, and the set of pass path groups includes the first candidate set;

[0015] When there is no timeout path group, the first candidate set is set to an empty set.

[0016] As an implementable method:

[0017] Extracting a local maximum complete subgraph of the intersection model;

[0018] Screening a local maximum complete subgraph containing the first candidate set, and constructing a second candidate set based on the nodes of the local maximum complete subgraph obtained by screening;

[0019] Based on the traffic demand data, the traffic volume estimation data corresponding to each target path group of the second candidate set is calculated to obtain the total traffic volume estimation data corresponding to the second candidate set, wherein the traffic volume estimation data is used to indicate the estimated value of the vehicle flow that can pass through the corresponding target path group under the condition that the green light is given in the target phase;

[0020] The second candidate set with the largest total traffic volume estimation data is used as the traffic path group set corresponding to the target phase.

[0021] As an implementable method, when the first candidate set is obtained, or when there is no timeout path group:

[0022] The target path group that does not belong to the first candidate set is used as a candidate path group, and the traffic volume estimation data corresponding to each candidate path group is determined based on the traffic demand data, wherein the traffic volume estimation data is used to indicate the estimated value of the vehicle flow that can pass through the corresponding target path group under the condition that the green light is given in the target phase;

[0023] The candidate path groups are traversed in descending order according to the traffic volume estimation data, and the candidate path groups that do not conflict with the target path group in the first candidate set are added to the first candidate set to obtain the pass path group set corresponding to the target phase.

[0024] As an implementable method, after determining the set of pass path groups corresponding to the target phase, a time configuration step is further included, and the time configuration step includes:

[0025] Obtain the total demand data corresponding to the set of travel path groups in the current phase;

[0026] Obtaining total traffic volume estimation data corresponding to the set of traffic path groups in the target phase;

[0027] Based on the total demand data and the total traffic volume estimation data, the basic end time corresponding to the current phase is adjusted to determine the phase end time of the current phase; wherein the total demand data corresponding to the current phase is obtained by:

[0028] Based on a plurality of preset delay parameters, the second demand data of each target path group in the set of passing path groups corresponding to the current phase are accumulated to obtain total demand data corresponding to the delay parameters;

[0029] The second demand data is an estimated number of vehicles passing through the target intersection based on the target path group within a time range of a unit delay length from the candidate end time when the corresponding target path group is given a green light condition at the corresponding candidate end time; the second demand data corresponds to the delay parameter one by one;

[0030] The candidate end times correspond one-to-one to the delay parameters, and the candidate end times are the end times of the current phase determined based on the preset unit delay length and the corresponding delay parameters; wherein the total traffic volume estimate data is the sum of the traffic volume estimate data of each target path group in the corresponding pass path group set, and the traffic volume estimate data is an estimate of the vehicle flow that can pass through the corresponding target path group under the condition that a green light is given in the target phase based on the traffic demand data.

[0031] As an implementable method:

[0032] Delay parameters include -2, -1, 0, 1;

[0033] Condition 1: κdTail(-1, Current)<αeSum(Next,T);

[0034] Condition 2: κdTail(-2, Current)<αeSum(Next, T);

[0035] Condition 3: κdTail(0, Current)>βeSum(Next,T);

[0036] Condition 4: κdTail(1,Current)>βeSum(Next,T);

[0037] in:

[0038] Current represents the set of passing path groups in the current phase;

[0039] Next represents the set of passing path groups of the target phase;

[0040] T represents the phase start time of the next phase in the control period;

[0041] κd represents the phase reference duration, κ represents the adjustment parameter, which is a positive integer, and d represents the unit duration;

[0042] e represents the unit delay length, e<d;

[0043] α represents the first weight parameter;

[0044] β represents the second weight parameter;

[0045] Tail(i,Current) represents the total demand data corresponding to the set of travel path groups in the current phase when the delay parameter is i;

[0046] Sum(Next, T) represents the total traffic volume estimation data corresponding to the path group set of the target phase;

[0047] When both conditions 1 and 2 are met, let T′=T-2e, where T′ represents the phase end time of the current phase;

[0048] When condition 1 is met and condition 2 is not met, let T′ = Te;

[0049] When both condition 1 and condition 3 are not met, T′=T;

[0050] When condition 1 is not met, and conditions 3 and 4 are met, let T′=T+2e;

[0051] When condition 1 is not satisfied, condition 3 is satisfied, and condition 4 is not satisfied, let T′=T+e.

[0052] As an implementable method:

[0053] Determine time configuration data based on the phase end time of the current phase and the set of pass path groups of the target phase;

[0054] The time configuration data includes a first signal switching time, a second signal switching time, and a third signal switching time;

[0055] The first signal switching time is used to indicate the time for opening the waiting area corresponding to the target phase in advance;

[0056] The second signal switching time is used to indicate the yellow light start time corresponding to the current phase;

[0057] The second signal switching time is the phase end time of the current phase, and is used to indicate the green light start time corresponding to the target phase.

[0058] As an implementable method:

[0059] It also includes a preparation period, which enters the preparation period and the control period in sequence based on time, and the preparation period includes several phases;

[0060] When the current phase is in the preparation period or control period:

[0061] Collect vehicle dynamic information of each vehicle at the target intersection;

[0062] Calculating a time lag of a corresponding vehicle based on the vehicle dynamic information;

[0063] Based on the preset time delay limit and the time delay of each vehicle, the time delay exceeding limit queue is updated in real time;

[0064] Traffic demand data corresponding to the next phase is predicted based on the vehicle dynamic information.

[0065] As an implementable method:

[0066] The traffic demand data of the target phase includes the state data and the first demand data corresponding to each target path group;

[0067] Generate corresponding traffic volume estimation data based on the status data and demand data of the corresponding target path group;

[0068] The state data is used to indicate the number of vehicles queuing at the vehicle detection area before the basic end time when the corresponding target path group is given a red light condition at the basic end time of the current phase;

[0069] The first demand data is used to indicate the estimated number of vehicles passing through the target intersection based on the target path group within a phase reference time range starting from the basic end time of the current phase when the corresponding target path group is given a green light condition at the basic end time of the current phase.

[0070] The present invention also proposes a traffic demand-based signal control system, which is used to execute any one of the traffic demand-based signal control methods described above.

[0071] The present invention has significant technical effects due to the adoption of the above technical solution:

[0072] The present invention determines the set of passing path groups corresponding to the target phase through the time-delay overrun queue and traffic demand data, that is, determines the target path group given to the target phase, which is not restricted by the phase order in the preset control scheme;

[0073] The present invention solves the problem of excessive waiting time for vehicles through a time-delay excessive queue, and uses traffic demand data to make the next phase meet the traffic demand of the road as much as possible, which can improve the traffic efficiency of the intersection, reduce the average time delay, and effectively resolve the problem of temporary traffic capacity drop caused by emergency lane changing of vehicles, thereby preventing the formation and spread of congestion. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0075] Figure 1 is a schematic diagram of a flow chart of determining a phase end time corresponding to a current phase in an embodiment;

[0076] Figure 2 This is a schematic diagram of the structure of the intersection constructed in the example;

[0077] Figure 3 yes Figure 2 The intersection model corresponding to the constructed intersection shown;

[0078] Figure 4 yes Figure 3 All local maximum complete subgraphs of the corresponding intersection model. DETAILED DESCRIPTION

[0079] The present invention is further described in detail below in conjunction with embodiments. The following embodiments are for explanation of the present invention but the present invention is not limited to the following embodiments.

[0080] A signal control method based on traffic demand is used for signal control of a target intersection.

[0081] S100: data configuration;

[0082] S110, determining the intersection model corresponding to the target intersection:

[0083] The intersection model is an undirected graph model of a constructed intersection including the target intersection;

[0084] The constructed intersection does not limit the type and layout of the intersection, such as the constructed intersection can be a single intersection or multiple intersections; Single intersection: The constructed intersection only includes the target intersection;

[0085] Multiple intersections: constructing an intersection including the target intersection and the secondary intersections of the target intersection;

[0086] When there are one or more intersections that are too close to the target intersection, such intersections with ultra-short spacing are combined for consideration, that is, such intersections with ultra-short spacing are regarded as slave intersections corresponding to the target intersection, and the target intersection and its slave intersections are considered as a whole. In actual applications, based on the signal control situation of the target intersection, the slave intersections are coordinated and controlled accordingly.

[0087] In this embodiment, the waiting area of ​​the target intersection is marked as a special section. The local path passing through a waiting area includes: a path formed by the upstream section entering the target intersection and the waiting area, and a path formed by the waiting area and the downstream section leaving the target intersection.

[0088] The intersection model G = (I, E) for constructing an intersection is an undirected graph model representing the non-conflicting relationship between target path groups for constructing an intersection, where I is a set of driving path groups, and the elements are represented by nodes, and E is a set of non-conflicting undirected path group pairs, and the elements are represented by edges connecting nodes, that is, an edge represents that the driving path groups corresponding to the two connected nodes do not conflict with each other;

[0089] The paths corresponding to the driving path group can be divided into the following two categories:

[0090] Only the target path group is included, that is, the driving path group that enters and exits the constructed intersection from the target intersection;

[0091] It includes a target path group and a local path group, that is, a driving path group that enters the constructed intersection from the intersection and exits the constructed intersection from the target intersection;

[0092] The above two types of driving path groups both contain target path groups. The target path groups corresponding to driving path groups that do not conflict with each other also do not conflict. Even if the constructed intersection is a multi-intersection, the conflict relationship between the target path groups can be determined based on the intersection model.

[0093] Given an intersection model G = (I, E), each of its local maximum complete subgraphs All nodes in are connected to each other, and there is no subgraph

[0094] A local maximum complete subgraph is extracted from the intersection model G = (I, E). Each local maximum complete subgraph corresponds to the maximum combination of all non-conflicting driving path groups of the constructed intersection. The driving path groups in each maximum combination can pass at the same time, so the target path groups in each maximum combination can also pass at the same time.

[0095] After knowing the signal control scheme of the target intersection, those skilled in the art can coordinate the signal control schemes of the slave intersections according to actual needs. Therefore, this specification will provide a detailed introduction by taking the scenario of constructing an intersection that only includes the target intersection as an example.

[0096] S120, determining a relevant function for indicating traffic demand;

[0097] For all w∈Entry, the state State(w,,t) of the target path group at all times t and all reasonable traffic demands Pass(w,t,s) of finite duration s;

[0098] Wherein, Entry represents the set of target path groups; all paths in the same target path group have the same road to enter the target intersection, and the merging rule is to first distinguish by path, that is, if different lanes have the same path, they belong to the same target path group; then distinguish by lane, that is, if different paths share the same lane, these paths belong to the same target path group; given a target path group w, Exit(w) represents the set of paths with the lane corresponding to the target path group w as the road exit or intersection entrance;

[0099] State(w, t) represents the number of vehicles that pass through the target path group w and meet the following conditions: if the light is green at time t, the vehicles have entered the target intersection at the end of w at a free speed or have left the target intersection, but due to the red light, these vehicles queue up and enter the target intersection after t;

[0100] Pass(w, t, s) represents the number of vehicles that enter the intersection at the end of w in a given time period s, assuming that all vehicles in w travel at free speed;

[0101] The state State(w, t) of the target path group and the traffic demand Pass(w, t, s) of the target path group are estimated based on the collected vehicle dynamic information;

[0102] Specifically:

[0103] Using lane radar sensors and magnetic coils, or using the vehicle's own onboard system and global positioning system, the vehicle dynamic information is obtained. In this embodiment, the vehicle dynamic information includes information such as the vehicle's location, driving speed and driving direction, as well as information such as the road traffic volume and the number of vehicles in queue;

[0104] Based on the vehicle dynamic information, the number of vehicles on the target path group w that reach the end of the road before time t but fail to enter the intersection is predicted, and the corresponding state State(w, t) is obtained;

[0105] Based on the vehicle dynamic information, the number of vehicles entering the intersection on the target path group w in the period from t to t+s is predicted to obtain the corresponding traffic demand Pass(w, t, s);

[0106] After knowing the vehicle dynamic information, those skilled in the art can use existing publicly available technical solutions to predict the status and traffic demand, for example, by constructing a calculation formula or training a neural network model, etc., which will not be described in detail in this specification.

[0107] S130, configuring preparation parameters;

[0108] The preparation parameter n is a positive integer, which is used to indicate the number of phases corresponding to the preparation period. In this embodiment, the value range of the preparation parameter n is 3 to 5.

[0109] S140, configuring the control start time and the control end time;

[0110] The above control start time and control end time can be determined by pre-manual configuration or real-time manual configuration;

[0111] A control period can be determined based on the control start time and the control end time;

[0112] A preparation period can be determined based on the control start time and the preparation parameter, the preparation period includes a number of phases, the number of phases in the preparation period corresponds to the preparation parameter, and the phases in the preparation period are phases that are fixedly controlled based on a preset phase reference duration;

[0113] The preparation period and the control period are continuous. In actual application, the preparation period and the control period will be entered in sequence as time goes by.

[0114] In this embodiment, the control start time is set as T, which is used to indicate the basic start time of the next phase entering the control period;

[0115] When the current time does not reach T, T is not updated;

[0116] When the current time reaches T, T is updated based on the phase start time of the current phase, that is, T continues to indicate the basic start time of the next phase entering the control period, and at this time T can also represent the basic end time of the current phase.

[0117] S200, performing signal control on the target intersection;

[0118] S210, when the preparation period has not yet begun;

[0119] The signal is switched based on a preset fixed control scheme.

[0120] S220, when in the preparation period and the control period;

[0121] S221, collecting vehicle dynamic information of each vehicle at the target intersection;

[0122] The target intersection includes the target intersection and a road section connecting the target intersection;

[0123] Collect vehicle dynamic information using lane radar sensors and magnetic induction coils, or using the vehicle's own onboard system and global positioning system;

[0124] In this embodiment, the vehicle dynamic information includes information such as the vehicle's location, driving speed and driving direction, as well as information such as the road traffic volume and the number of vehicles in queue.

[0125] S222, updating the time-delay excess queue in real time based on the vehicle dynamic information;

[0126] The time delay exceeding limit queue is used to place a timeout path group, and the timeout path group is a target path group for vehicles whose current time delay exceeds a preset time delay upper limit.

[0127] Specifically:

[0128] Calculating a time lag of a corresponding vehicle based on the vehicle dynamic information;

[0129] Based on the preset time delay limit and the time delay of each vehicle, the time delay exceeding limit queue is updated in real time.

[0130] Time lag refers to the difference between the time when the corresponding vehicle actually enters the target intersection and the time when the vehicle enters the target intersection under the condition of driving at a free speed on the entrance section.

[0131] In this embodiment, a non-rigid upper limit of the time lag is adopted, for example, between 2 and 3 signal cycles corresponding to the fixed time control may be adopted.

[0132] In this embodiment, the elements of the time delay exceeding limit queue are arranged in a first-in-first-out order.

[0133] S223, predicting the traffic demand data corresponding to the next phase based on the vehicle dynamic information;

[0134] The traffic demand data is used to indicate the traffic demand of the corresponding target path group in the target phase.

[0135] In this embodiment, the traffic demand data includes:

[0136] Status data and first demand data corresponding to each target path group;

[0137] The state data is used to indicate the number of vehicles queuing at the vehicle detection area before the basic end time when the corresponding target path group is given a red light condition at the basic end time of the current phase;

[0138] The first demand data is used to indicate the estimated number of vehicles passing through the target intersection based on the target path group within a phase reference time range starting from the basic end time of the current phase when the corresponding target path group is given the green light condition at the basic end time of the current phase, that is, the estimated number of vehicles passing through the target intersection by the target path group when the green light condition is given at the target phase.

[0139] S224, predicting the traffic arrival data corresponding to the next phase in the control period based on the vehicle dynamic information;

[0140] The traffic arrival data includes a plurality of second demand data;

[0141] The second demand data is used to indicate the estimated number of vehicles passing through the target intersection based on the target path group within a time range of a unit delay length from the candidate end time when the corresponding target path group gives a green light condition at the candidate end time;

[0142] The candidate end time is a time obtained by adjusting the basic end time of the next phase in the control period based on the preset unit delay length and a plurality of delay parameters. The candidate end time corresponds to the delay parameter one-to-one, and the second demand data also corresponds to the delay parameter one-to-one.

[0143] The traffic arrival data is used to reflect the traffic demand of the target path group in the time interval near the end time of the next phase in the control period.

[0144] set up:

[0145] T represents the phase start time of the next phase in the control period. In the initial state, the control start time is recorded as T;

[0146] TICK() represents the current time;

[0147] n represents the preparation parameter;

[0148] κd represents the phase reference duration;

[0149] d represents the unit duration, and each signal selection will determine the duration of κd to open the green light for the specified target path group;

[0150] κ represents an adjustment parameter, which is a positive integer. In this embodiment, the adjustment parameter κ can be 2, 3 or 4;

[0151] When Tick()=T-nκd, it enters the preparation period. After entering the preparation period:

[0152] When Tick()<T, fixed time control is implemented with κd as the phase duration until Tick()>T-κd;

[0153] And the real-time update element is the queue θ of the target path group of vehicles with a time delay exceeding Υ.

[0154] Υ represents the upper limit of the time lag. In this embodiment, Υ is a non-rigid upper limit of the time lag, which can be between 2 and 3 signal cycles corresponding to the fixed time control, that is, between 2κd and 3κd;

[0155] The time delay overrun queue θ=[θ p ] stores the target path group of vehicles with time delay exceeding the upper limit Υ, and its elements are arranged in the order of first-in-first-out, where θ p is the p-th element in θ.

[0156] After entering the preparation period, for k=n-1, ...0, in this order, each phase in the preparation period is switched based on the fixed time;

[0157] That is, the phase start time of the current phase is T-(k+1)κd, and the basic end time of the current phase and the basic start time of the next phase are T-kκd.

[0158] In the preparation period and the control period, predicting the traffic demand data corresponding to the next phase in the current phase, and the traffic arrival data corresponding to the next phase in the control period;

[0159] As an implementable method, when the current phase is in the preparation period, the following processes are operated in parallel:

[0160] Predict State(w,T-kκd), Pass(w,T-kκd,κd) for all w,∈Entry and Pass(w,T+κd+ie,e) for each i=-2,-1,0,1;

[0161] in:

[0162] e represents the unit delay length, e<d, and d is divisible by e, for example, e can be half or one third of d;

[0163] Υ represents the upper limit of the time lag. In this embodiment, Υ is a non-rigid upper limit of the time lag, which can be between 2 and 3 signal cycles corresponding to the fixed time control;

[0164] The vehicle delay is defined as the difference between the time it actually enters the intersection and the time it enters the intersection if it has been driving at free speed on the entrance section.

[0165] Queue θ = [θ p ] stores the target path group of vehicles with time delay exceeding the upper limit Υ, and its elements are arranged in the order of first-in-first-out, where θ p is the p-th element in θ;

[0166] State(w, T-kκd) represents the state data corresponding to the target path group w;

[0167] Pass(w, T-kκd, κd) represents the first demand data corresponding to the target path group w;

[0168] Pass(w, T+κd+ie, e) represents the second demand data corresponding to the target path group w when the delay parameter is i.

[0169] S230, when the next phase is in the control period;

[0170] The next phase is used as the target phase.

[0171] While executing step S220, the following steps are executed:

[0172] S231, determining a set of passing path groups of a target phase;

[0173] The pass path group set includes several non-conflicting target path groups.

[0174] As an embodiment, the specific steps of determining the set of traffic path groups corresponding to the target phase based on the time delay exceeding queue and the traffic demand data are:

[0175] A100. When a timeout path group exists, construct a first candidate set based on the timeout path group;

[0176] The timeout path groups in the first candidate set do not conflict with each other.

[0177] In this embodiment:

[0178] Based on a preset screening order, traverse the timeout path groups in the time delay excess queue, and add the timeout path groups that do not conflict with the target path groups in the first candidate set to the first candidate set;

[0179] The first candidate set is initially an empty set;

[0180] The filter order can be:

[0181] Screening is performed based on the order in which the timeout path group is arranged in the time delay excess queue;

[0182] Based on the maximum time delay corresponding to the timeout path group, the selection is performed in descending order. In this embodiment, the maximum time delay corresponding to the timeout path group is the maximum value of the time delay of each vehicle in the timeout path group.

[0183] A200, determining a set of traffic path groups corresponding to the target phase based on the intersection model and the traffic demand data;

[0184] The passing path group set corresponding to the target phase corresponds to a local maximum complete subgraph in the intersection model, and the passing path group set includes the first candidate set.

[0185] As an example:

[0186] A211. Determine a second candidate set;

[0187] The second candidate set includes the first candidate set, and target paths in the second candidate set do not conflict with each other;

[0188] In this embodiment:

[0189] Extracting the local maximum complete subgraph of the intersection model to obtain several local maximum complete subgraphs;

[0190] The local maximum complete subgraph containing the first candidate set is screened, and a second candidate set is constructed based on the nodes of the local maximum complete subgraph obtained by the screening to obtain at least one second candidate set.

[0191] A212, determining a set of travel path groups corresponding to the target phase from each second candidate set based on the traffic demand data;

[0192] Calculating traffic volume estimation data corresponding to each target path group of the second candidate set based on the traffic demand data, and obtaining total traffic volume estimation data corresponding to the second candidate set, wherein the traffic volume estimation data is used to indicate an estimation value of the vehicle flow that can pass through the corresponding target path group under the condition that a green light is given at the target phase;

[0193] The second candidate set with the largest total traffic volume estimation data is used as the traffic path group set corresponding to the target phase.

[0194] The traffic demand data includes state data and first demand data corresponding to each target path group;

[0195] In this embodiment, the state data of the target path group and the first demand data are summed to obtain the traffic volume estimation data corresponding to the target path group;

[0196] In this embodiment, the traffic volume estimation data of each target path group in the second candidate set is accumulated to obtain the total traffic volume estimation data corresponding to the second candidate set.

[0197] For example:

[0198] Let the first candidate set be

[0199] from start( is an empty set), compare all elements in the time delay overrun queue θ with the existing elements of the first candidate set ω one by one according to their order in the time delay overrun queue θ, if they are connected to each existing element in the first candidate set ω in pairs in the intersection model G, it means that they are evenly distributed with each element in the first candidate set ω, then add them to the first candidate set ω;

[0200] Calculate a set x of all local maximum complete subgraphs covering the first candidate set ω, where the elements of the set x are the second candidate sets x corresponding to the local maximum complete subgraphs;

[0201] For each x∈χ, read the state State(w,T) and traffic demand Pass(w,T,κd) of all target path groups w contained in the second candidate set x, and sum them to obtain the total traffic volume estimation data Sum(x,T) corresponding to the second candidate set x. The calculation formula is:

[0202]

[0203] Compare the total traffic volume estimated data Sum(x, T) corresponding to all second candidate sets x, and determine the second candidate set x with the largest total traffic volume estimated data Sum(x, T) as the traffic path group set Next of the target phase. The calculation method is:

[0204] Select Next∈χ such that for all x∈χ, Sum(Next, T)≥Sum(x, T).

[0205] As another example:

[0206] A221. Determine candidate route groups, and determine traffic volume estimation data corresponding to each candidate route group based on traffic demand data;

[0207] In this embodiment, the target path group that does not belong to the first candidate set is used as a candidate path group;

[0208] The traffic volume estimation data is used to indicate an estimated value of the vehicle flow that can pass through the corresponding target path group under the condition that a green light is given in the target phase.

[0209] A222, selecting a candidate path group based on the traffic volume estimation data and placing it into a first candidate set to generate a set of passing path groups corresponding to the target phase;

[0210] The candidate path groups are traversed in descending order according to the traffic volume estimation data, and the candidate path groups that do not conflict with the target path group in the first candidate set are added to the first candidate set, and the obtained first candidate set is used as the pass path group set.

[0211] The final set of travel path groups will correspond to a local maximum complete subgraph in the intersection model.

[0212] Determine the conflict relationship between path groups based on the intersection model. For example:

[0213] ① If there are timeout path groups, these timeout path groups are arranged according to the time delay of the vehicle with the largest time delay, and the timeout path groups with non-conflicting corresponding paths are added to the pass path group set Next in turn; the calculation method is:

[0214] make For p increasing from 1 to |θ|, if for all θ q ∈Next, all u∈Exit(θ q ) and all w∈Exit(θ p ), there is {(θ p , w), (θ q ,u)}∈E, then Next←Next∪{θ p}; where |θ| represents the number of elements contained in the time-delay exceeding queue θ, and p represents the pth element in the queue.

[0215] ② If there is no target path group containing vehicles with excessive time delay, or after taking the target path group containing vehicles with excessive time delay in the queue θ, sort the other target path groups of the intersection according to the corresponding traffic volume estimation data order; the calculation method is:

[0216] Let A←[], that is, an empty queue. For each w∈Entry\Next, execute Sum(w, T)←State(w, T)+Pass(w, T, κd) and insert w into A in descending order of Sum(·, T).

[0217] ③. According to the order of the target path groups sorted by the size of the traffic volume estimation data, the target path groups that do not conflict with the target path groups in the traffic path group set Next that have been added to the target phase are added to Next until they cannot be added; the calculation method is:

[0218] For p increasing from 1 to |A|, if for all θ q ∈Next, all u∈Exit(θ q ) and all w∈Exit(A p ) has {(A p , w), (θ q ,u)}∈E, then Next←Next∪{A p}, |A| represents the number of elements in queue A.

[0219] In practical applications, those skilled in the art may select the method for determining a pass path group set disclosed in the above embodiment, or combine the methods for determining a pass path group set disclosed in the above two embodiments according to actual conditions;

[0220] like:

[0221] When the current phase is in the preparation period and the next phase is in the control period, a set of passing path groups of the next phase is determined based on step A211 and step A212;

[0222] When both the current phase and the next phase are in the control period, a set of passing path groups of the next phase is determined based on step A221 and step A222.

[0223] The present invention determines the set of traffic path groups of the target phase based on the traffic volume estimation data of the timeout path group and each target path group, which can meet the traffic demand while taking into account the situation where the vehicle waiting time exceeds the limit, avoid the formation and spread of road congestion, and effectively deal with the problems of reduced traffic efficiency and excessive vehicle waiting time caused by uneven traffic flow at intersections.

[0224] S233, determining the phase end time of the current phase;

[0225] The specific steps include:

[0226] B100, obtaining the total demand data corresponding to the set of travel path groups in the current phase;

[0227] Obtain the total demand data corresponding to the set of travel path groups in the current phase;

[0228] Obtaining total traffic volume estimation data corresponding to the set of traffic path groups in the target phase;

[0229] Based on the total demand data and the total traffic volume estimation data, the basic end time corresponding to the current phase is adjusted to determine the phase end time of the current phase; wherein the total demand data corresponding to the current phase is obtained by:

[0230] Based on a plurality of preset delay parameters, the second demand data of each target path group in the set of passing path groups corresponding to the current phase are accumulated to obtain total demand data corresponding to the delay parameters;

[0231] The second demand data is an estimated number of vehicles passing through the target intersection based on the target path group within a time range of a unit delay length from the candidate end time when the corresponding target path group is given a green light condition at the corresponding candidate end time; the second demand data corresponds to the delay parameter one by one;

[0232] The candidate end time corresponds to the delay parameter one by one, and the candidate end time is the end time of the current phase determined based on the preset unit delay length and the corresponding delay parameter.

[0233] The delay parameter is used to indicate the adjustment amount of the end time, that is, the unit delay length is weighted based on the delay parameter to obtain the corresponding adjustment amount. In actual applications, the basic end time of the corresponding phase is adjusted based on the adjustment amount to obtain the candidate end time of the phase.

[0234] In this embodiment, the delay parameter i = -2, -1, 0, 1;

[0235] The total demand data corresponding to the set of travel path groups in the current phase is expressed as:

[0236]

[0237] in:

[0238] Current is the set of passing path groups corresponding to the current phase, that is, the set of target path groups with green lights in the current phase;

[0239] Tail(i, Current) represents the total demand data corresponding to the set of traffic path groups corresponding to the current phase when the delay parameter is i;

[0240] Pass(w, T+ie, e) represents the second demand data corresponding to the target path group w when the delay parameter is i in the current phase;

[0241] T represents the phase start time of the next phase in the control period, which is the basic end time of the current phase;

[0242] e represents the unit delay length, and T+ie represents the candidate end time of the current phase corresponding to the delay parameter i.

[0243] B200, calculating the total traffic volume estimation data corresponding to the set of traffic path groups of the target phase;

[0244] The total traffic volume estimation data is the sum of the traffic volume estimation data of each target path group in the corresponding pass path group set;

[0245] Corresponding traffic volume estimation data is obtained based on the state data and traffic demand data of the target path group. The specific method step A200 has been described, so it will not be repeated here.

[0246] B300, based on the total demand data and the total traffic volume estimation data, adjusting the basic end time corresponding to the current phase to determine the phase end time of the current phase;

[0247] Based on the delay parameter and the total demand data, generating a first average traffic volume corresponding to the delay parameter;

[0248] Based on the delay parameter and the total traffic volume estimation data, generating a second average traffic volume corresponding to the delay parameter;

[0249] Comparing the corresponding first average traffic volume with the second average traffic volume based on the delay parameter to obtain a corresponding comparison result;

[0250] Based on the obtained comparison result and the basic end time corresponding to the current phase, the phase end time corresponding to the current phase is determined.

[0251] In this embodiment:

[0252] The first average traffic volume corresponding to the delay parameter i is κdTail(i, Current);

[0253] When the delay parameter i is less than 0, the second average traffic volume corresponding to the delay parameter i is aeSum(Next,T), wherein α is a preset first weight parameter, and in this embodiment, α=0.8. Those skilled in the art can set the value of α according to actual conditions;

[0254] When the delay parameter i≥0, the second average traffic volume corresponding to the delay parameter i is βeSum(Next, T), where β is a preset second weight parameter. In this embodiment, β=1.2. Those skilled in the art can set the value of β according to actual conditions.

[0255] Those skilled in the art may set an adjustment rule for adjusting the basic end time corresponding to the current phase based on the obtained comparison result according to actual needs. As an implementable embodiment:

[0256] Condition 1: κdTail(-1, Current)<aeSum(Next, T);

[0257] Condition 2: κdTail(-2, Current)<αeSum(Next, T);

[0258] Condition 3: κdTail(0, Current)>βeSum(Next,T);

[0259] Condition 4: κdTail(1,Current)>βeSum(Next,T);

[0260] in:

[0261] Current represents the set of passing path groups in the current phase;

[0262] Next represents the set of passing path groups of the target phase;

[0263] T represents the phase start time of the next phase in the control period;

[0264] κd represents the phase reference duration, κ represents the adjustment parameter, which is a positive integer, and d represents the unit duration;

[0265] e represents the unit delay length, e<d;

[0266] α represents the first weight parameter;

[0267] β represents the second weight parameter;

[0268] Tail(i,Current) represents the total demand data corresponding to the set of traffic paths in the current phase when the delay parameter is i; Sum(Next, T) represents the total traffic volume estimate data corresponding to the set of paths in the target phase;

[0269] When both conditions 1 and 2 are met, let T′=T-2e, where T′ represents the phase end time of the current phase;

[0270] When condition 1 is met and condition 2 is not met, let T′ = Te;

[0271] When both condition 1 and condition 3 are not met, T′=T;

[0272] When condition 1 is not met, and conditions 3 and 4 are met, let T′=T+2e;

[0273] When condition 1 is not satisfied, condition 3 is satisfied, and condition 4 is not satisfied, let T′=T+e.

[0274] Reference Figure 1 In practical applications, the phase end time of the current phase can be determined based on the following steps:

[0275] (1) Judgment condition 1κdTail(-1, Current)<aeSum(Next, T);

[0276] If established, execute (2);

[0277] If not, execute (3).

[0278] (2) Judgment condition 2κdTail(-2, Current)<aeSum(Next, T);

[0279] If true, let T′ = T-2e;

[0280] If not, set T′=Te.

[0281] (3) Judgment condition 3κdTail(0, Current)>βeSum(Next, T);

[0282] If established, execute (4);

[0283] If not, set T′=T.

[0284] (4) Judgment condition 4κdTail(1, Current)>βeSum(Next, T);

[0285] If true, let T′=T+2e;

[0286] If not, set T′=T+e.

[0287] S234, adjusting time configuration data;

[0288] Determine time configuration data based on the phase end time of the current phase and the set of pass path groups of the target phase;

[0289] The time configuration data includes a first signal switching time, a second signal switching time, and a third signal switching time;

[0290] The first signal switching time is used to indicate the time for opening the waiting area corresponding to the target phase in advance;

[0291] The second signal switching time is used to indicate the yellow light start time corresponding to the current phase;

[0292] The second signal switching time is the phase end time of the current phase, and is used to indicate the green light start time corresponding to the target phase.

[0293] The prior art discloses a scheme to improve the green light utilization rate by setting different optimization targets or multiple targets, such as average delay, queue length, intersection capacity, etc., and adjusting the weights of the indicators to determine the signal timing; however, such schemes often simplify the layout and phase division of intersections and are difficult to apply to complex traffic scenarios in practice;

[0294] This embodiment is applicable to intersections with waiting areas, has a wide range of applications, and meets the needs of signal control in complex traffic scenes in practice.

[0295] As an example:

[0296] C100, determining the first signal switching time T′-ke of the target phase;

[0297] In this embodiment, Wait(Tick()<T′-me) is executed in sequence:

[0298] Turn on the red light for leaving the waiting area corresponding to the first configured path group in the passing path group set Next corresponding to the target phase;

[0299] Turn on the green light for entering the waiting area corresponding to the second configured path group in the pass path group set Next.

[0300] The first configured path group is a target path group that belongs to the target phase corresponding pass path group set Next but does not belong to the current phase corresponding pass path group set Current;

[0301] The second configured path group is a target path group that belongs to the pass path group set Next corresponding to the target phase, and does not conflict with the target path group that corresponds to the pass path group set Current of the current phase.

[0302] Note: Wait(P) indicates a waiting function whose input P is a predicate. When P is true, the execution of the control program is suspended at the location of Wait(P); when P becomes false, the subsequent statements are executed immediately.

[0303] Those skilled in the art can determine the value of parameter m according to the capacity of the waiting area. In this embodiment, m=2 or 3. Parameter m is used to control the time in advance when vehicles of the target path group corresponding to the target phase can enter the waiting area.

[0304] C200, determining a second signal switching time T′-o;

[0305] Among them, o represents the duration of the yellow light, which must satisfy o≤e;

[0306] When considering the number of vehicles leaving road w during the green light period, the corresponding vehicle start-up loss time ι needs to be deducted from the total green light duration w To obtain the effective green light duration; for the control of the yellow light, the last few seconds before the green light turns red can be occupied.

[0307] In this embodiment, Wait(Tick()<T′-o) executes:

[0308] Switch the third configuration path group to yellow light, and if the third configuration path group has a corresponding waiting area, keep the signal of leaving the waiting area green light;

[0309] The third configured path group is a target path group that belongs to the current phase corresponding pass path group set Current, but does not belong to the target phase corresponding pass path group set Next.

[0310] C300, determining a third signal switching time T′;

[0311] In this embodiment, Wait(Tick()<T′) is executed in sequence:

[0312] Switch the fourth configuration path group to red, and if the fourth configuration path group has a corresponding waiting area, keep its leaving waiting area signal green;

[0313] Switch the fifth configuration path group signal to green, and if the fifth configuration path group has a corresponding waiting area, switch its leaving waiting area signal to green;

[0314] Let Current←Next and T←T′+κd, that is, perform phase switching, and update the set of pass path groups corresponding to the current phase and the basic end time.

[0315] The fourth configured path group is a target path group that does not belong to the pass path group set Next corresponding to the target phase;

[0316] The fifth configured path group is a target path group belonging to the pass path group set Next corresponding to the target phase.

[0317] As an implementable method, the specific steps of signal control based on time configuration data are:

[0318] When the current time reaches the first signal switching time T′-me, for each w∈Next, the following operations are performed in parallel:

[0319] If there are paths in w that connect to the waiting areas, and these waiting areas do not conflict with the paths in Current, then

[0320] Set the signal leaving the waiting area w to red, and then set the signal of the corresponding path group (entering the waiting area) to green.

[0321] When the current time reaches the second signal switching time T′-o, for each w∈Current\Next, the following operations are performed in parallel:

[0322] Set the w signal to yellow.

[0323] When the current time reaches the third signal switching time T′:

[0324] For each w∈Current\Next, operate in parallel and set the signal of w to red;

[0325] For each w∈Next, do the following in parallel:

[0326] If there is a path in w that connects to the waiting area, the signal of w is set to green;

[0327] Otherwise, further determine whether the signal of w and the signal leaving its waiting area are both red;

[0328] If the signal of w and the signal of leaving its waiting area are both red, then the signal of w and the signal of leaving its waiting area are both set to green;

[0329] If the signal at w and the signal leaving its waiting area are not both red, then the signal leaving the waiting area of ​​w will be set to green.

[0330] The present invention optimizes the phase end time of the current phase based on traffic demand data and the determined travel path group set of the target phase, which can further reduce the impact caused by uneven traffic flow and further improve traffic efficiency.

[0331] As an embodiment, after obtaining the phase end time T′ of the current phase, the traffic demand data, traffic arrival data, and total demand data corresponding to the target phase are predicted;

[0332] Right now;

[0333] Based on the phase end time T′, the state data State(w, T′+κd), the first demand data Pass(w, T′+κd, κd) of the next phase and the second demand data Pass(w, T′+κd+ie, e) corresponding to the delay parameter are predicted, and based on the predicted second demand data Pass(w, T′+κd+ie, e), the total demand data Tail(i, Next) corresponding to the target phase is predicted for the set of pass path groups Next corresponding to the target phase;

[0334] The second method of obtaining the demand data is:

[0335] Based on the phase end time T′ of the current phase and each delay parameter i, determine each candidate end time T′+κd+ie corresponding to the target phase;

[0336] It is predicted that when the corresponding target path group gives the green light condition at the corresponding candidate end time T′+κd+ie, within a time range of one unit delay length from the updated candidate end time, based on the estimated number of vehicles passing through the target intersection by the target path group, the second demand data corresponding to the target path group under the delay parameter i is obtained.

[0337] The calculation formula for predicting total demand data Tail(i, Next) is:

[0338]

[0339] The predicted Tail(i, Next) is the Tail(i, Current) of the target phase.

[0340] If the current phase enters the control period for the first time and the total demand data corresponding to the current phase is empty, the corresponding total demand data is calculated based on the above-mentioned Tail(i, Current) calculation formula, and after the phase end time of the current phase is determined, the total demand data corresponding to the next phase is predicted based on the phase end time, so that the next phase can use it to determine its phase end time.

[0341] In the actual application process, after the phase is switched, the pass path group, phase start time and basic end time of the phase will be updated accordingly, that is, the pass path group set Next obtained in the previous phase is used as the pass path group set Current of the current phase, the phase start time of the current phase is updated to T′, and the basic end time of the current phase is T′+κd, that is, T←T′+κd;

[0342] In the process of signal control for the current phase, the traffic demand data, traffic arrival data and total demand data predicted in the previous phase are used to determine the set of traffic path groups for the next phase and determine the phase end time of the current phase;

[0343] Repeat the above steps until the control period ends.

[0344] As an embodiment, the method for constructing the intersection model in step S110 is specifically as follows:

[0345] S111, combining the driving path groups corresponding to the constructed intersections in pairs to generate a number of undirected pairs, and obtaining a first undirected pair set;

[0346] Based on the set I of driving path groups established previously, a first undirected pair set K consisting of all driving path groups in the set I is constructed.

[0347] S112, forming an undirected pair of two conflicting driving path groups to obtain a conflicting path group pair, and constructing a second undirected pair set based on the obtained conflicting path group pair;

[0348] Based on the previously established set I of driving path groups, a second undirected pair set of conflicting path group pairs in set I is constructed.

[0349] In this embodiment, an undirected graph model for constructing conflict path pairs is also constructed.

[0350] In the undirected graph model In , each node represents a set of driving path groups, and the edge between two nodes represents the conflict between the path groups corresponding to the two connected nodes.

[0351] S113, obtaining the complement of the second undirected pair set in the first undirected pair set to obtain a third undirected pair set; the undirected pairs in the third undirected pair set are non-conflicting path pairs;

[0352] That is, the second undirected pair set corresponding to the conflicting path pair is removed from the first undirected pair set consisting of all driving path pairs to determine the non-conflicting path pair.

[0353] The third undirected pair set is the edge set E in the intersection model, which can remove the second undirected pair set corresponding to the conflicting path groups from the first undirected pair set K composed of all driving path groups. Get, that is Where K = {{u, v}: u, v∈V∧u≠v}.

[0354] S114. Construct the intersection model G=(I, E) based on the third undirected pair set.

[0355] In summary, the present invention proposes a signal control method based on traffic demand, which flexibly optimizes the phase order and adjusts the green light duration according to the traffic demand data and vehicle delay of each path group at the intersection, and fully takes into account the situation of excessive waiting time of vehicles while trying to pass the path group with greater traffic demand; it can improve the traffic efficiency of the intersection, reduce the average delay, and effectively resolve the problem of temporary traffic capacity drop caused by emergency lane change of vehicles, thereby preventing the formation and spread of congestion. In addition, the present invention can also give full play to the role of the waiting area.

[0356] The present invention is further described below based on an example of a certain traffic situation. Figure 2As shown in the figure, the example constructed intersection is a cross-shaped signalized intersection, which includes four types of turns: U-turn, left turn, straight and right turn. In the east-west direction, the U-turn and left turn paths on the same road are merged into one target path group; in the north-south direction, the straight and right turn paths are merged into one target path group. There are a total of 10 target path groups in the entire intersection, recorded as n1, n2, ...n 10 ; A waiting area is set for left turns in each direction, and these waiting areas do not conflict with the opposite straight path or the intersecting left-turn path.

[0357] The intersection signal parameters and road traffic parameters are set as follows: unit duration d = 20s, κ = 2, that is, each phase duration κd = 40s, green light extension or shortening duration e = 10s, vehicle delay upper limit Υ = 200s, yellow light time o = 3s, vehicle start loss time ι w =2s, the vehicle arrival rates of the single lanes in the east-west direction and the north-south direction obey the Poisson distribution of λ1=1 / 6 and λ2=1 / 15 vehicle / second respectively, the average release rate of a single lane is 3 seconds / vehicle, and the parameter k that controls vehicles to enter the waiting area in advance is 2.

[0358] The control algorithm is used to determine the target path group and phase duration that are passable for the next signal phase.

[0359] Y1. Refer to step S100 to perform data configuration:

[0360] Obtain the signal control framework for constructing the intersection, including an undirected graph of non-conflicting relationships between target path groups at the intersection (e.g. Figure 3 ) and all local maximum complete subgraphs (such as Figure 4 As shown), each subgraph is a local maximum complete subgraph of a non-conflicting undirected graph, representing the maximum combination of non-conflicting and simultaneously accessible target path groups;

[0361] Y2. When the next phase is in the control period, refer to step S220 to obtain traffic dynamic information of the constructed intersection;

[0362] The traffic dynamic information includes the traffic status of each target path group, the vehicle delay status, the status data and the first demand data.

[0363] For example, after a certain signal switching time T-κd, the traffic status of each target path group (whether it belongs to the traffic path group set of the current phase), the vehicle delay status (whether it contains vehicles with excessive delay), the state data State(w, T) and the first demand data Pass(w, T, κd) are obtained, as shown in Table 1, where the time delay excess queue θ=[n7, n9]:

[0364] Table 1

[0365]

[0366] Y3. Refer to step S230 to perform signal control;

[0367] Refer to step B100 to calculate the total demand data Tail(i, Current) corresponding to each delay parameter. To simplify the description, only the average traffic arrival rate of one phase duration (κd) is used for calculation. In practice, the arrival rate of each time interval e monitored in real time can be used for calculation.

[0368] Referring to step A200, the set of traffic path groups corresponding to the next phase is determined. Specifically, it is determined that there is no conflict between the target path groups n7 and n9 with excessive time delays, and they can be added to the first candidate set; based on the intersection model of the intersection, the non-conflicting relationship between other target path groups and n7 and n9 is determined, and the total traffic volume estimation data corresponding to the local maximum complete subgraph containing n7 and n9 is calculated and compared; here, the local maximum complete subgraph that meets the conditions is unique (such as Figure 4 As shown in the neutron diagram (9), by selecting the target path groups n3 and n6 in turn, the traffic path group set Next = {n7, n9, n3, n6} of the next phase can be determined, and the total traffic volume estimation data Sum (Next, T) corresponding to the traffic path group can be obtained.

[0369] Referring to step B300, based on the total demand data Tail(i, Current) obtained above and the total traffic volume estimation data Sum(Next, T), the phase end time of the current phase is determined;

[0370] In this example, parameters α=0.8 and β=1.2, Tail(1, Current) / e=1.0, Sum(Next, T) / kd=0.825, and κdTail(1, Current)>βeSum(Next, T) are obtained, so the phase end time T′=T+2P is set, that is, the current phase is extended by 20s.

[0371] For each i=-2, -1, 0, 1, the total demand data Tail(i, Next) is obtained to estimate the end time of the next phase.

[0372] Referring to step S234, based on the obtained phase end time T′ and the set of traffic path groups Next={n7, n9, n3, n6}, the intersection is controlled to perform signal switching: specifically:

[0373] The waiting area of ​​the target path group n7, n9 in the passing path group set of the next phase does not conflict with the target path group n2, n5 in the current phase, so the green light signal for n7, n9 to enter the waiting area is turned on at time T′-me. In this example, m=2;

[0374] At T′-o, the traffic lights of the current target path group n2 and n5 are switched to yellow. In this example, o is 3s.

[0375] At time T′, the traffic lights of n2 and n5 are switched to red. At the same time, the green lights of target path groups n7 and n9 leaving the waiting area are turned on, and the traffic lights of target path groups n3 and n6 are still green. Other traffic lights are not switched, among which the traffic lights of the waiting area of ​​n1 and n4 are green, and the remaining traffic lights are all red.

[0376] At this point, the signal switching process of a new phase at the example intersection is completed. According to the above control method, steps Y2 and Y3 are repeated until the control period ends.

[0377] A signal control system based on traffic demand is used to execute the signal control method based on traffic demand described in any of the above embodiments.

[0378] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0379] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0380] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0381] The present invention is described with reference to the flowcharts and / or block diagrams of the method, terminal device (system), and computer program product according to the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0382] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0383] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0384] It should be noted that:

[0385] The "one embodiment" or "embodiment" mentioned in the specification means that the specific features, structures or characteristics described in conjunction with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrases "one embodiment" or "embodiment" appearing in various places throughout the specification do not necessarily refer to the same embodiment.

[0386] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0387] In addition, it should be noted that the shapes and names of the parts and components of the specific embodiments described in this specification may be different. Any equivalent or simple changes made based on the structure, features and principles described in the patent concept of the present invention are included in the protection scope of the patent of the present invention. The technicians in the technical field of the present invention can make various modifications or supplements to the specific embodiments described or replace them in a similar manner, as long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A signal control method based on traffic demand, used for signal control of a target intersection, wherein the target intersection has a plurality of target path groups, characterized in that: The following steps are involved: When the next phase is in the control period, the next phase is taken as the target phase, and the set of pass path groups corresponding to the target phase is determined based on the time delay overrun queue and the traffic demand data corresponding to each target path group, and the pass path group set includes a plurality of non-conflicting target path groups; The time delay exceeding limit queue is used to place the timeout path group, and the timeout path group is the target path group where the vehicles whose current time delay exceeds the preset time delay upper limit are located; The traffic demand data is used to indicate the traffic demand of the corresponding target path group in the target phase.

2. The signal control method based on traffic demand according to claim 1, characterized in that: The specific steps of determining the set of traffic path groups corresponding to the target phase based on the time delay excess queue and traffic demand data are as follows: Preset an intersection model of the constructed intersection where the target intersection is located, the intersection model is an undirected graph model, the nodes of which are driving path groups corresponding to the constructed intersections, the edges represent that the driving path groups corresponding to the two connected nodes do not conflict with each other, and the driving path groups include a target path group; When there is a timeout path group, construct a first candidate set based on the timeout path group, wherein the timeout path groups in the first candidate set do not conflict with each other; When there is no timeout path group, let the first candidate set be an empty set; Based on the intersection model and the traffic demand data, a set of pass path groups corresponding to the target phase is determined, the pass path group set corresponding to the target phase corresponds to a local maximum complete subgraph in the intersection model, and the pass path group set includes the first candidate set.

3. The signal control method based on traffic demand according to claim 2, characterized in that: Extracting a local maximum complete subgraph of the intersection model; Screening a local maximum complete subgraph containing the first candidate set, and constructing a second candidate set based on the nodes of the local maximum complete subgraph obtained by screening; Based on the traffic demand data, the traffic volume estimation data corresponding to each target path group of the second candidate set is calculated to obtain the total traffic volume estimation data corresponding to the second candidate set, wherein the traffic volume estimation data is used to indicate the estimated value of the vehicle flow that can pass through the corresponding target path group under the condition that the green light is given in the target phase; The second candidate set with the largest total traffic volume estimation data is used as the traffic path group set corresponding to the target phase.

4. The signal control method based on traffic demand according to claim 2, characterized in that: When the first candidate set is obtained, or there is no timeout path group: The target path group that does not belong to the first candidate set is used as a candidate path group, and the traffic volume estimation data corresponding to each candidate path group is determined based on the traffic demand data. The flux estimation data is used to indicate the estimated value of the vehicle flow that can pass through the corresponding target path group under the condition that the green light is given in the target phase; The candidate path groups are traversed in descending order according to the traffic volume estimation data, and the candidate path groups that do not conflict with the target path group in the first candidate set are added to the first candidate set to obtain the pass path group set corresponding to the target phase.

5. The signal control method based on traffic demand according to claim 1, characterized in that: After determining the set of passing path groups corresponding to the target phase, a time configuration step is also included, and the time configuration step includes: Obtain the total demand data corresponding to the set of travel path groups in the current phase; Obtaining total traffic volume estimation data corresponding to the set of traffic path groups in the target phase; Based on the total demand data and the total traffic volume estimation data, adjusting the basic end time corresponding to the current phase to determine the phase end time of the current phase; Among them, the method for obtaining the total demand data corresponding to the current phase is: Based on a plurality of preset delay parameters, the second demand data of each target path group in the set of passing path groups corresponding to the current phase are accumulated to obtain total demand data corresponding to the delay parameters; The second demand data is an estimated number of vehicles passing through the target intersection based on the target path group within a time range of a unit delay length from the candidate end time when the corresponding target path group is given a green light condition at the corresponding candidate end time; the second demand data corresponds to the delay parameter one by one; The candidate end time corresponds to the delay parameter one by one, and the candidate end time is the end time of the current phase determined based on the preset unit delay length and the corresponding delay parameter; Among them, the total traffic volume estimation data is the sum of the traffic volume estimation data of each target path group in the corresponding pass path group set. The traffic volume estimation data is an estimated value of the vehicle flow that can pass through the corresponding target path group under the condition that the green light is given in the target phase based on the traffic demand data.

6. The signal control method based on traffic demand according to claim 5, characterized in that: Delay parameters include -2, -1, 0, 1; Condition 1: κdTail(-1, Current)<αeSum(Next, T); Condition 2: κdTail(-2, Current)<αeSum(Next, T); Condition 3: κdTail(0, Current)>βeSum(Next, T); Condition 4: κdTail(1, Current)>βeSum(Next, T); in: Current represents the set of passing path groups in the current phase; Next represents the set of passing path groups of the target phase; T represents the phase start time of the next phase in the control period; κd represents the phase reference duration, κ represents the adjustment parameter, which is a positive integer, and d represents the unit duration; e represents the unit delay length, e<d; α represents the first weight parameter; β represents the second weight parameter; Tail(i, Current) represents the total demand data corresponding to the set of travel path groups in the current phase when the delay parameter is i; Sum(Next, T) represents the total traffic volume estimation data corresponding to the path group set of the target phase; When both conditions 1 and 2 are met, let T′=T-2e, where T′ represents the phase end time of the current phase; When condition 1 is met and condition 2 is not met, let T′ = Te; When both condition 1 and condition 3 are not met, T′=T; When condition 1 is not met, and conditions 3 and 4 are met, let T′=T+2e; When condition 1 is not satisfied, condition 3 is satisfied, and condition 4 is not satisfied, let T′=T+e.

7. The signal control method based on traffic demand according to claim 6, characterized in that: Determine time configuration data based on the phase end time of the current phase and the set of pass path groups of the target phase; The time configuration data includes a first signal switching time, a second signal switching time, and a third signal switching time; The first signal switching time is used to indicate the time for opening the waiting area corresponding to the target phase in advance; The second signal switching time is used to indicate the yellow light start time corresponding to the current phase; The second signal switching time is the phase end time of the current phase, and is used to indicate the green light start time corresponding to the target phase.

8. The signal control method based on traffic demand according to claim 1, characterized in that: It also includes a preparation period, which enters the preparation period and the control period in sequence based on time, and the preparation period includes several phases; When the current phase is in the preparation period or control period: Collect vehicle dynamic information of each vehicle at the target intersection; Calculating a time lag of a corresponding vehicle based on the vehicle dynamic information; Based on the preset time delay limit and the time delay of each vehicle, the time delay exceeding limit queue is updated in real time; Traffic demand data corresponding to the next phase is predicted based on the vehicle dynamic information.

9. The signal control method based on traffic demand according to any one of claims 1 to 8, characterized in that: The traffic demand data of the target phase includes the state data and the first demand data corresponding to each target path group; Generate corresponding traffic volume estimation data based on the status data and demand data of the corresponding target path group; The state data is used to indicate the number of vehicles queuing at the vehicle detection area before the basic end time when the corresponding target path group is given a red light condition at the basic end time of the current phase; The first demand data is used to indicate the estimated number of vehicles passing through the target intersection based on the target path group within a phase reference time range starting from the basic end time of the current phase when the corresponding target path group is given a green light condition at the basic end time of the current phase.

10. A signal control system based on traffic demand, characterized in that: Used to implement the traffic demand-based signal control method described in any one of claims 1 to 9.

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