A two-phase traffic signal timing method

Abstract

The application discloses a two-phase traffic signal timing method and relates to the technical field of intelligent transportation. The method comprises the following steps: obtaining input parameters of two-phase traffic signal timing; the input parameters comprise a coordination cycle, a traffic flow, a minimum distance from a previous intersection, a maximum difference between two-way traffic flows, and a minimum difference between two-way traffic flows; a fuzzy control model is constructed, and a green signal ratio is determined based on the fuzzy control model; the fuzzy control model takes the input parameters as inputs and takes the green signal ratio as an output; and two-phase traffic signal timing is obtained based on the green signal ratio output by the fuzzy control model. The application innovatively takes the distance from a previous intersection as a consideration factor for the input parameters, so that the signal timing is more coordinated, and the given timing scheme has a better effect.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a two-phase traffic signal timing method. Background Technology

[0002] Traffic lights are an important tool for urban traffic management. Their main purpose is to improve road capacity, reduce traffic congestion, and ensure traffic safety by rationally allocating the time and space of traffic flow. Two-phase traffic signal timing is a common signal control method, mainly used to handle relatively simple intersection traffic flows.

[0003] In two-phase traffic signal timing, traffic flow is divided into two phases: the primary phase and the secondary phase. The primary phase typically grants priority to vehicles on the main road, while the secondary phase grants priority to vehicles on secondary roads or pedestrians crossing the street. By adjusting the green light times of the two phases, effective control of traffic flow at intersections can be achieved.

[0004] At present, the control methods for single-point signal intersections, namely the traditional two-phase traffic signal timing method, are mainly three types: timed control, inductive control, and adaptive control. Timed control mainly divides the day into several control periods and sets different signal control methods according to the traffic volume of each control period. Compared with inductive control and adaptive control, timed control cannot dynamically and in real time adjust the signal control parameters according to the traffic flow of the intersection, resulting in poor timeliness. It is usually necessary to adjust the existing signal control scheme within a certain time interval. Nevertheless, timed control is still the main method of intersection signal control in China. The main reasons are: (1) In traffic environments where motor vehicles, non-motor vehicles, and pedestrians are mixed, the effects of inductive control and adaptive control, which mainly consider the operation of motor vehicles, are not very ideal in practical applications; (2) Timed control has lower requirements for signal controllers, roadside equipment, etc., with low investment costs, high reliability, and easy maintenance.

[0005] In practical applications, traffic flow throughout the day is complex and variable. Most intersections rely on multi-period, time-based control, primarily using manual intervention. The efficiency and effectiveness of this control depend heavily on the subjective judgment of the personnel, which is not only inefficient but also prone to errors, lacking scientific and precise control and management. Summary of the Invention

[0006] To address the aforementioned problems, this invention proposes a two-phase traffic signal timing method. This method uses a fuzzy algorithm to determine the green light ratio based on traffic flow and distance to the previous intersection, thereby achieving more accurate automatic signal timing and significantly improving the efficiency and accuracy of timing.

[0007] Therefore, the present invention adopts the following technical solution:

[0008] This invention provides a two-phase traffic signal timing method, the method comprising:

[0009] The input parameters for the timing of two-phase traffic signals are obtained. The input parameters include: coordination period, traffic flow in both east-west and south-north directions, minimum distance from the previous intersection in both east-west and south-north directions, maximum difference between traffic flow in both east-west and south-north directions, and minimum difference between traffic flow in both east-west and south-north directions.

[0010] A fuzzy control model is constructed, and the green ratio is determined based on the fuzzy control model, wherein the fuzzy control model takes the input parameters as input and the green ratio as output;

[0011] Based on the green ratio output by the fuzzy control model, the timing of the two-phase traffic signals is obtained.

[0012] Furthermore, a fuzzy control model is constructed, including:

[0013] Create the traffic flow difference ef between east-west and south-north directions, the difference ed between the minimum distance from the previous intersection between east-west and north-south directions, and the fuzzy universe of discourse for the green ratio u;

[0014] By employing scaling transformation, the input quantities of traffic flow difference between east-west and south-north directions, and the input quantities of minimum distance from the previous intersection between east-west and north-south directions are transformed to the required fuzzy universe of discourse.

[0015] Triangles are used as the difference between east-west and south-north traffic flow, the difference between the minimum distance from the previous intersection in the east-west and north-south directions, and the fuzzy set membership function of the green light ratio;

[0016] Based on expert knowledge and control objectives, a fuzzy rule table is developed.

[0017] The maximum-min method is used to obtain the relation matrix of each rule based on the fuzzy rule table. and

[0018]

[0019] By R A and R B The green ratio output is:

[0020] The weighted average method is used to calculate the clarity of the fuzzy green signal ratio;

[0021] After obtaining the clear value u0, the u0 scale is transformed into the actual control quantity.

[0022] Furthermore, the differences in traffic flow between east-west and south-north directions (ef) and the differences in minimum distances from the previous intersection between east-west and north-south directions (ed), as well as the fuzzy universe of discourse for the green light ratio u, are created, including:

[0023] Set the traffic flow difference ef between east-west and south-north directions as {-3, -2, -1, 0, 1, 2, 3};

[0024] The difference ed between the minimum distances from the previous intersection in the east-west and north-south directions is {-3, -2, -1, 0, 1, 2, 3};

[0025] The green light ratio u is {-3, -2, -1, 0, 1, 2, 3};

[0026] Define a fuzzy subset:

[0027] The fuzzy subset of the traffic flow difference ef between east-west and south-north directions is {NMef, NSef, ZOef, PSef, PMef};

[0028] The fuzzy subset of the difference ed between the minimum distances from the previous intersection in both the east-west and north-south directions is {NMed, NSed, ZOed, PSed, PMed};

[0029] The fuzzy subset of the green signal is {NMu, NSu, ZOu, PSu, PMu}.

[0030] Furthermore, scaling transformation is employed to transform the input quantities of traffic flow differences between east-west and south-north directions, and the input quantities of minimum distances from the previous intersection between east-west and north-south directions, to the required fuzzy universe of discourse, including:

[0031] Actual input volume of traffic flow difference between east-west and south-north directions The actual range of variation is If the fuzzy universe of discourse is [-3, 3], then:

[0032]

[0033] in, This represents the maximum actual input value of the difference in traffic flow between east-west and south-north directions. This represents the minimum actual input value of the difference between traffic flow in both east-west and south-north directions.

[0034] The actual input quantity is the difference between the minimum distance from the previous intersection in both the east-west and north-south directions. The actual range of variation is If the fuzzy universe of discourse is [-3, 3], then:

[0035]

[0036] in, The maximum value of the actual input is the difference between the minimum distance from the previous intersection in both the east-west and north-south directions. The minimum value of the actual input is the difference between the minimum distance from the previous intersection in both the east-west and north-south directions.

[0037] Furthermore, the membership function of the traffic flow difference ef between the east-west and south-north directions is:

[0038]

[0039] The membership function of the difference between the minimum distances from the previous intersection in the east-west and north-south directions is:

[0040]

[0041] The membership function of the green credit ratio u is:

[0042]

[0043] Among them, NMef, NSef, ZOef, PSef, and PMef represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the traffic flow difference ef between east-west and south-north directions, respectively; NMed, NSed, ZOed, PSed, and PMed represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the difference ed between the minimum distance from the previous intersection between east-west and north-south directions, respectively; and NMu, NSu, ZOu, PSu, and PMu represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the green light ratio u, respectively.

[0044] Furthermore, the fuzzy rule table is as follows:

[0045]

[0046] Among them, NMef, NSef, ZOef, PSef, and PMef represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the traffic flow difference ef between east-west and south-north directions, respectively; NMed, NSed, ZOed, PSed, and PMed represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the difference ed between the minimum distance from the previous intersection between east-west and north-south directions, respectively; and NMu, NSu, ZOu, PSu, and PMu represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the green light ratio u, respectively.

[0047] Furthermore, the u0 scale is transformed into actual control quantities, including: the transformation range of u0 is [-3, 3], and the transformation range of the actual green ratio is [u min ,u max ],but:

[0048]

[0049] in, This is called the quantization factor, u max =1, u min =0.

[0050] Advantages and positive effects of the present invention:

[0051] (1) This invention innovatively proposes that the input parameter should take the distance from the previous intersection as a consideration, which makes the signal timing more effective and coordinated, and the given timing scheme is more efficient. Traditional methods consider factors such as queue length and overall delay. When timing is adjusted based on these factors, the adjustment of the next intersection often affects the previously adjusted intersection. However, this method uses factors with relatively small intersection changes as input quantities, and traffic flow and distance from the previous intersection as influencing factors. This minimizes the impact of the timing of the intersection on the timing of surrounding adjacent intersections. As a result, the timing effect is better and it is more convenient to use. Regional coordinated timing can be achieved by adjusting the timing of an intersection only once.

[0052] (2) Traditional two-phase single-point intersection timing methods only consider the current traffic flow and overall delay time at the intersection, and some parameters, such as delay time, are not available in the application process. Therefore, this invention selects parameters that can be obtained in actual application as input quantities, making the algorithm more practical. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart of a two-phase traffic signal timing method according to an embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram of the membership function of the traffic flow difference ef between east-west and south-north directions in an embodiment of the present invention;

[0056] Figure 3 This is a schematic diagram of the membership function of the difference ed between the minimum distances from the previous intersection in the east-west and north-south directions in an embodiment of the present invention;

[0057] Figure 4 This is a schematic diagram of the membership function of the green information ratio u in an embodiment of the present invention. Detailed Implementation

[0058] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0059] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0060] like Figure 1 As shown, a two-phase traffic signal timing method in an embodiment of the present invention specifically includes the following steps:

[0061] S1. Obtain the input parameters for two-phase traffic signal timing;

[0062] The input parameters include: coordination cycle, traffic flow in both east-west and south-north directions, minimum distance from the previous intersection in both east-west and south-north directions, maximum difference between traffic flow in both east-west and south-north directions, and minimum difference between traffic flow in both east-west and south-north directions.

[0063] These parameters are commonly used in traffic engineering and traffic signal timing to describe and analyze traffic conditions at intersections. In practical applications, accurate numerical values ​​for these parameters are crucial. The following is an explanation of these parameters:

[0064] Coordination cycle: This refers to the signal cycle set to coordinate traffic lights at multiple adjacent intersections. By adjusting the signal cycles of adjacent intersections, vehicles can travel continuously on the main road, reducing the number of stops and improving traffic efficiency.

[0065] East-west bidirectional traffic flow: East-west bidirectional traffic flow refers to the total number of vehicles passing through a road segment or intersection in the east-west direction within a specific time period. This parameter reflects the traffic demand in the east-west direction.

[0066] North-South Bidirectional Traffic Flow: North-South bidirectional traffic flow refers to the total number of vehicles passing through a road segment or intersection in the north-south direction within a specific time period. This parameter reflects the traffic demand in the north-south direction.

[0067] East-West Dual-Direction Lanes: This refers to the total number of lanes in the east-west direction of the intersection. This parameter affects the traffic capacity in that direction, i.e., how many vehicles can be accommodated simultaneously.

[0068] Number of lanes in both north-south directions: This refers to the total number of lanes in the north-south direction of the intersection. This parameter affects the traffic capacity in that direction.

[0069] Minimum distance from the previous intersection in both east-west directions: This refers to the minimum distance between the current intersection and its upstream adjacent intersection in the east-west direction. This parameter is crucial for setting appropriate signal timing to ensure vehicles can smoothly pass through two intersections during green light periods and avoid frequent stops.

[0070] Minimum distance from the previous intersection in both north-south directions: This refers to the minimum distance between the current intersection and its upstream adjacent intersection in the north-south direction. This parameter is also crucial for signal timing settings.

[0071] Maximum East-West and South-North Bidirectional Traffic Flow Difference: This refers to the maximum difference in traffic flow between the east-west and north-south directions during the observation period. This parameter helps to understand which direction experiences greater traffic congestion at different times, allowing for more appropriate signal timing.

[0072] Minimum difference in traffic flow between east-west and south-north directions: This refers to the minimum difference in traffic flow between the east-west and north-south directions during the observation period. This parameter also helps to understand the traffic conditions in each direction at different times and how to balance the green light time allocation in each direction.

[0073] S2. Create the difference ef between east-west and south-north traffic flow and the difference ed between the minimum distance from the previous intersection between east-west and north-south traffic flow, as well as the fuzzy universe of discourse for the green signal ratio u.

[0074] (1) Set the traffic flow difference ef between east-west and south-north directions as {-3, -2, -1, 0, 1, 2, 3};

[0075] The difference ed between the minimum distances from the previous intersection in the east-west and north-south directions is {-3, -2, -1, 0, 1, 2, 3};

[0076] The green light ratio u is {-3, -2, -1, 0, 1, 2, 3}; the green light ratio refers to the proportion of time available for vehicle passage within one cycle of a traffic light, that is, the ratio of the effective green light time of a certain phase to the cycle length.

[0077] (2) Define fuzzy subsets

[0078] The fuzzy subset of the traffic flow difference ef between east-west and south-north directions is {NMef, NSef, ZOef, PSef, PMef};

[0079] The fuzzy subset of the difference ed between the minimum distances from the previous intersection in both the east-west and north-south directions is {NMed, NSed, ZOed, PSed, PMed};

[0080] The fuzzy subset of the green signal is {NMu, NSu, ZOu, PSu, PMu}.

[0081] S3. Use scaling transformation to transform the input quantity to the required fuzzy universe of discourse.

[0082] (1) Actual input volume of traffic flow difference between east-west and south-north directions The actual range of variation is If the fuzzy universe of discourse is [-3, 3], then:

[0083]

[0084] (2) Actual input amount: the difference between the minimum distance from the previous intersection in both the east-west and north-south directions. The actual range of variation is If the fuzzy universe of discourse is [-3, 3], then:

[0085]

[0086] S4. Select the triangle based on the membership function of the fuzzy set.

[0087] (1) Membership function of the traffic flow difference ef between east-west and south-north directions, such as Figure 2 As shown in Table 1.

[0088] Table 1

[0089]

[0090] (2) The membership function of the difference ed between the minimum distances from the previous intersection in both the east-west and north-south directions is shown in Table 2. Figure 3 As shown.

[0091] Table 2

[0092]

[0093] (3) Membership function of green credit ratio u, as shown in Table 3 and Figure 4 As shown.

[0094] Table 3

[0095]

[0096] S5. Define the fuzzy rule table;

[0097] In fuzzy control systems, fuzzy rules are a series of rules used to describe the relationship between input and output variables. These rules are typically based on human natural language and empirical knowledge, expressed using structures such as "if-then". Terminology in fuzzy rules: NM, NS, ZO, PS, and PM stand for Negative Middle, Negative Small, Zero, Positive Small, and Positive Middle, respectively. These terms describe the degree of membership of elements in a fuzzy set and are vocabulary used in fuzzy control to describe the states of input and output variables. Specifically:

[0098] NM (Negative Middle): Indicates that a value is in the middle range of the negative region, that is, it tends to be negative but is not particularly large.

[0099] NS (Negative Small): Indicates a value that is in the negative region and is small in value.

[0100] ZO (Zero): Represents a value that is close to zero or in a neutral state between positive and negative.

[0101] PS (Positive Small): Indicates that a value is in the positive range and the value is small.

[0102] PM (Positive Middle): Indicates that a value is in the middle range of the positive region, that is, it tends to be positive but is not particularly large.

[0103] These terms are used to describe the degree of membership, that is, the degree to which a value belongs to a certain fuzzy set.

[0104] In this embodiment, a series of fuzzy rules are formulated based on expert knowledge and control objectives, as shown in Table 4.

[0105] Table 4

[0106]

[0107] S6. Use fuzzy reasoning to obtain the fuzzy relation matrix.

[0108] In this embodiment, fuzzy inference employs the max-min method, and the relation matrix R for each rule is obtained based on the fuzzy rule table. Ai R Bi Obtain the fuzzy relation matrix and in:

[0109]

[0110]

[0111] By R A and R B The green light ratio output can be obtained as follows: in, Represents a compound symbol, a type of operator.

[0112] S7. Defuzzification: The weighted average method is used to calculate the fuzziness level.

[0113]

[0114] Where, x i μ is the value of the universe of discourse. i (x i x is the value of the universe of discourse. i Membership degree value.

[0115] S8, Green Ratio Universe Transformation;

[0116] After obtaining the sharpness value u0, it needs to be scaled to become the actual control quantity. The scaling range of u0 is [-3, 3], and the scaling range of the actual green ratio is [u...]. min ,u max ],but:

[0117]

[0118] in, This is called the quantization factor, where umax = 1 and umin = 0.

[0119] The above steps use a fuzzy algorithm to obtain the green light ratio.

[0120] S9. Based on the green ratio, obtain the signal timing.

[0121] The above embodiments innovatively propose using the distance from the previous intersection as a factor in the input parameters, making signal timing more effective and synergistic, and resulting in a more efficient timing scheme. These embodiments use factors with minimal intersection changes as input quantities, with traffic volume and distance from the previous intersection as influencing factors. This minimizes the impact of timing at an intersection on the timing of adjacent intersections. Consequently, the timing effect is better, and the method is more convenient to use; regional coordinated timing can be achieved with only one timing adjustment per intersection.

[0122] Traditional two-phase single-point intersection timing methods only consider the current traffic flow and overall delay time at the intersection, and some parameters, such as delay time, are simply unavailable in practical applications. Therefore, this invention selects parameters that can be obtained in actual applications as input quantities, making the algorithm more practical.

[0123] To facilitate understanding, the following detailed explanation of the two-phase traffic signal timing method will be provided with specific examples.

[0124] Assuming the difference in traffic flow between east-west and south-north directions, then

[0125] Based on actual input according to have to:

[0126] Assuming the difference between the minimum distances from the previous intersection in both the east-west and north-south directions, then

[0127] Based on actual input according to have to

[0128] According to the membership function: ef = [0,0,0,0.5,1,0.5,0]; ed = [0,0.5,1,0.5,0,0,0];

[0129]

[0130] according to get:

[0131]

[0132] according to We get: u = 0.5 + 0.135 / 6 = 0.5225;

[0133] This yields a green signal ratio of 52.25%, which indicates the timing of signals in the east-west and north-south directions.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A two-phase traffic signal timing method, characterized in that, The method includes: The input parameters for the timing of two-phase traffic signals are obtained. The input parameters include: coordination period, traffic flow in both east-west and south-north directions, minimum distance from the previous intersection in both east-west and south-north directions, maximum difference between traffic flow in both east-west and south-north directions, and minimum difference between traffic flow in both east-west and south-north directions. A fuzzy control model is constructed, and the green ratio is determined based on the fuzzy control model, wherein the fuzzy control model takes the input parameters as input and the green ratio as output; Based on the green ratio output by the fuzzy control model, the timing of the two-phase traffic signals is obtained; The construction of the fuzzy control model includes: Create the traffic flow difference ef between east-west and south-north directions, the difference ed between the minimum distance from the previous intersection between east-west and north-south directions, and the fuzzy universe of discourse for the green ratio u; By employing scaling transformation, the input quantities of traffic flow difference between east-west and south-north directions, and the input quantities of minimum distance from the previous intersection between east-west and north-south directions are transformed to the required fuzzy universe of discourse. Triangles are used as the difference between east-west and south-north traffic flow, the difference between the minimum distance from the previous intersection in the east-west and north-south directions, and the fuzzy set membership function of the green light ratio; Based on expert knowledge and control objectives, a fuzzy rule table is developed. The maximum-min method is used to obtain the relation matrix of each rule based on the fuzzy rule table. and ; Depend on and The green ratio output is: ;in, Represents a compound symbol, a type of operator; The weighted average method is used to calculate the clarity of the fuzzy green signal ratio; After obtaining the clear value u0, the u0 scale is transformed into the actual control quantity.

2. The two-phase traffic signal timing method according to claim 1, characterized in that, Create the traffic flow difference ef between east-west and south-north directions, the difference ed between the minimum distances from the previous intersection between east-west and north-south directions, and the fuzzy universe of discourse for the green light ratio u, including: Set the traffic flow difference ef between east-west and south-north directions as {-3, -2, -1, 0, 1, 2, 3}; The difference ed between the minimum distances from the previous intersection in the east-west and north-south directions is {-3, -2, -1, 0, 1, 2, 3}; The green light ratio u is {-3, -2, -1, 0, 1, 2, 3}; Define a fuzzy subset: The fuzzy subset of the traffic flow difference ef between east-west and south-north directions is {NMef, NSef, ZOef, PSef, PMef}; The fuzzy subset of the difference ed between the minimum distances from the previous intersection in both the east-west and north-south directions is {NMed, NSed, ZOed, PSed, PMed}; The fuzzy subset of the green signal is {NMu, NSu, ZOu, PSu, PMu}; Among them, NMef, NSef, ZOef, PSef, and PMef represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the traffic flow difference ef between east-west and south-north directions, respectively; NMed, NSed, ZOed, PSed, and PMed represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the difference ed between the minimum distance from the previous intersection between east-west and north-south directions, respectively; and NMu, NSu, ZOu, PSu, and PMu represent the negative middle, negative small, zero, positive small, and positive middle values ​​of the green light ratio u, respectively.

3. The two-phase traffic signal timing method according to claim 1, characterized in that, Scale transformation is employed to transform the input quantities of traffic flow differences between east-west and south-north directions, and the input quantities of minimum distances from the previous intersection between east-west and north-south directions, to the required fuzzy universe of discourse, including: Actual input volume of traffic flow difference between east-west and south-north directions The actual range of variation is If the fuzzy universe of discourse is [-3, 3], then: ； in, This represents the maximum actual input value of the difference in traffic flow between east-west and south-north directions. This represents the minimum actual input value of the difference between traffic flow in both east-west and south-north directions. The actual input quantity is the difference between the minimum distance from the previous intersection in both the east-west and north-south directions. The actual range of variation is If the fuzzy universe of discourse is [-3, 3], then: ； in, The maximum value of the actual input is the difference between the minimum distance from the previous intersection in both the east-west and north-south directions. The minimum value of the actual input is the difference between the minimum distance from the previous intersection in both the east-west and north-south directions.

4. The two-phase traffic signal timing method according to claim 2, characterized in that, The membership function of the traffic flow difference between east-west and south-north directions, ef, is: The membership function of the difference between the minimum distances from the previous intersection in the east-west and north-south directions is: The membership function of the green credit ratio u is: 。 5. A two-phase traffic signal timing method according to claim 2, characterized in that, The fuzzy rule table is as follows: 。 6. The two-phase traffic signal timing method according to claim 1, characterized in that, Transforming the u0 scale into actual control quantities includes: the transformation range of u0 is [-3, 3], and the transformation range of the actual green ratio is... ,but: ； in, This is called the quantification factor. =1, =0.

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