A trunk line adaptive coordination control method based on indefinite period
By using an adaptive coordinated control method for trunk lines with variable cycles, traffic flow is dynamically adjusted, solving the congestion problem caused by excessively long cycles in traditional trunk line traffic control. This achieves more efficient and scientific traffic management, reducing delays and carbon emissions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DALIAN MARITIME UNIVERSITY
- Filing Date
- 2026-01-06
- Publication Date
- 2026-05-26
AI Technical Summary
Traditional trunk line traffic control methods result in excessively long cycles at non-critical intersections and significant traffic delays, which can easily lead to congestion and traffic accidents. They lack flexibility and scientific rigor, making it difficult to effectively alleviate urban traffic congestion.
An adaptive coordinated control method based on indefinite cycle is adopted. By collecting intersection information, an indefinite cycle coordinated control timing optimization model for arterial traffic is established. Webster's theory and genetic algorithm are used to calculate green light time and phase difference. Combined with speed guidance strategy, traffic flow is dynamically adjusted.
It has improved the efficiency and accuracy of traffic management, reduced vehicle delays and carbon emissions, enhanced the scientific nature and reliability of traffic management, avoided road congestion, and improved traffic safety and stability.
Smart Images
Figure CN122090641A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of intelligent traffic management technology, and specifically relates to a trunk line adaptive coordinated control method based on an indefinite period. Background Technology
[0002] With the accelerating pace of urbanization, traffic congestion on urban arterial roads has always been a challenging issue for urban management. Currently, many countries around the world, including developed countries, widely adopt intelligent traffic control systems to alleviate urban traffic congestion.
[0003] Traditional arterial road traffic control methods primarily involve selecting key intersections on the arterial road and then using the signal cycle length of these key intersections as a common cycle for signal timing at all intersections on the arterial road. However, this method can lead to excessively long cycles at non-critical intersections on the arterial road, resulting in significant delays in traffic flow in the opposite direction of the arterial road. This can easily cause congestion and traffic accidents, exhibiting a degree of arbitrariness and posing considerable challenges to urban traffic management. Summary of the Invention
[0004] To address the aforementioned problems in existing technologies, this invention discloses a trunk line adaptive coordinated control method based on an indefinite period, which can improve the macro-management level of urban traffic management departments over urban road networks, while also reducing vehicle delays and carbon emissions from urban road networks.
[0005] The technical solution of the present invention is as follows: A trunk line adaptive coordinated control method based on an indefinite period, comprising the following steps: A. Collect intersection information The intersection information is collected using a manual survey method. The intersection information includes the distance between intersections, traffic flow data at intersections, the current signal timing status of each intersection, and the channelization scheme for each intersection.
[0006] B. Establish a timing optimization model for coordinated control of trunk lines with irregular cycles. The optimization objectives are to minimize vehicle delays, maximize intersection capacity, and minimize the number of stops, and to construct a timing optimization model for coordinated control of trunk lines with irregular cycles.
[0007] C. Solving the timing optimization model for indeterminate period trunk line coordinated control Based on Webster's theory and using Matlab software, the timing optimization model and timing optimization parameters for the indeterminate period trunk line coordinated control are calculated. The indeterminate period trunk line adaptive coordinated timing optimization parameters include indeterminate period, green light time, flow rate ratio, and flow ratio.
[0008] D. Establish an optimization model for coordinated control of indeterminate periodic phase difference. The allocation ratio is determined based on the flow ratio, and an optimization model for phase difference coordination control with an indefinite period is constructed. Based on the existing phase difference, vehicle speed is guided for vehicles outside the green wave band, so that vehicles pass through the intersection continuously, reducing congestion on the main road.
[0009] E. Solving the indeterminate period phase difference coordinated control optimization model The improved MAXBAND model, which is a genetic algorithm, is used to solve the problem and obtain the phase difference of indefinite period and the induced vehicle speed. F. Output a trunk line coordination timing optimization scheme based on an indeterminate period. Combining the calculation results of steps C and E, a trunk line coordination timing optimization scheme based on an indefinite period is generated and output to provide decision-making information for traffic management personnel.
[0010] Furthermore, the steps in step B for establishing the timing optimization model for coordinated control of trunk lines with indefinite periods are as follows: B1. Establish a vehicle delay model The vehicle delay model formula is as follows:
[0011] in: i The phase number is calculated by the timing optimization model for coordinated control of trunk lines with indefinite periods. j Number the lanes at different intersections on the main road; For the first Phase 1 Average vehicle delay time per lane, measured in seconds; This represents the intersection cycle length, in seconds (s). For the first Phase green ratio; For the first Phase 1 Vehicle arrival rate of the lane, in units of pcu / h; For the first The saturation flux of the phase; for and The ratio.
[0012] B2. Establish an intersection capacity model The intersection capacity model is represented as follows:
[0013]
[0014] In the formula: Q j For the first j Lane capacity;QS j For the first j The saturation flow rate of the lane; For the first The effective green light time for a phase; B3. Establish a parking frequency model The parking frequency model is represented as follows:
[0015]
[0016] In the formula: For the first Average number of stops per phase; For the first Phase saturation, which is the ratio of traffic flow to capacity; For phase The flow ratio; For phase Traffic flow; For phase Traffic capacity; x This represents the saturation level at the intersection.
[0017] B4. Construct a trunk line coordinated control timing optimization model The objective function of the trunk line coordinated control timing optimization model is to achieve the optimization goals of minimizing delays, maximizing intersection capacity, and minimizing stops. It is expressed as follows:
[0018] In the formula: The optimal cycle length must be an integer. For phase i Vehicle delays; For phase i The capacity of the intersection; For phase i Number of parking sessions.
[0019] Furthermore, the method for solving the timing optimization model for coordinated control of trunk lines with indeterminate periods, as described in step C, includes the following steps: C1. Determine the indefinite period C11. Determine the assumptions The assumptions are as follows: 1) Assume there are three intersections within the main road system. , D 2. The corresponding period duration is , T 2. ; 2) The distance between adjacent intersections is 100-500m; 3) Traffic flow from Flow direction , The flow is upward, and the opposite direction is downward. 4) It is a key intersection with high traffic volume; , Intersection with indefinite period 5) The runtime of an irregular cycle shall not exceed 15 minutes; C12. Calculate the duration of an indeterminate period. To ensure that the entire indeterminate period duration is an integer multiple of the critical phase period duration, the intersection S 2. The initial period minimum value is set at the critical intersection. S Half the duration of a cycle will be the key intersection. S The half-cycle duration is divided into equal parts. n Select one portion based on the flow ratio. k The formula for calculating the duration of a variable period is as follows:
[0020]
[0021] In the formula: For phase i The value of , i =0,1,2,… p ; for Return to the initial phase difference and repeat the cycle an indefinite number of times; The value is 0 ~n It is determined by the upstream and downstream flow ratio; Similarly, the indefinite period duration is obtained. The calculation formula is as follows:
[0022]
[0023] In the formula: m si For phase si The value of , si =0,1,2… p '; for Return to the initial phase difference and repeat the cycle an indefinite number of times; C2. Improve the allocation of green light time C21. The formula for calculating the minimum green light time in the coordinated phase of a critical intersection is as follows:
[0024] In the formula: The minimum green light time in the coordinated phase at a critical intersection; This represents the total lost time for non-critical intersections; This refers to through traffic at non-critical intersections. This is the sum of the flows across all phases; C22. The formula for calculating the minimum effective green light time in non-coordinated phases at non-critical intersections is as follows:
[0025] In the formula: t EGmn The first non-critical intersection non-coordinated phase mn Minimum effective green light time for a phase, in seconds; Q mn The first non-critical intersection non-coordinated phase mn Traffic volume per phase, pcu / h; SX mn The first non-critical intersection non-coordinated phase mn The saturation flux of the phase; This represents the actual saturation value in the non-coordinated phase of a non-critical intersection; y mn The first non-critical intersection non-coordinated phase mn Phase flow ratio; C23. The formula for calculating the effective green light time in non-coordinated phases at non-critical intersections is as follows:
[0026] In the formula: The effective green time for coordinating phases at non-critical intersections; This represents the total lost time at non-critical intersections.
[0027] Furthermore, the steps in step D for establishing the variable-period phase difference coordinated control optimization model are as follows: D1. Establish the improved maximum green band model, i.e., the MAXBAND model. Introducing allocation ratio k To determine the period of the indeterminate period, where k ∈(0.5, 1). The improved maximum green band model is expressed as follows:
[0028]
[0029] In the formula: This represents the ratio of uplink to downlink green wave bandwidth, where... In the formula: b This refers to traffic flow in the upbound direction. This refers to the traffic flow in the downstream direction; CM 1 is the minimum period. CM 2 is the maximum period; The distance between the two intersections; e ii This represents the minimum upward green wave propulsion speed. This represents the minimum speed of the downlink green wave propagation. f ii This represents the maximum speed of the upward green wave propagation. This represents the maximum speed of the downlink green wave propagation. It should be an integer multiple of the period length; ω ii For the first The time difference between the end of the red light at an intersection and the green wave band at the edge of the traffic flow; For the first The time difference between the start of the red light at an intersection and the green wave band at the edges of both directions; t ii This is the time required to clear the queue of vehicles before the arrival of the upstream main line traffic. This is the time required to clear the queue of vehicles before the arrival of the downstream main line traffic. r ii For the first The red light duration for northbound traffic at each intersection; For the first Red light duration for southbound traffic at intersections; b For the uplink green wave bandwidth; This refers to the downlink green wave bandwidth; D2. Establish a speed-guided strategy D21. Speed guidance method for trunk line upward movement D211, Trunk Line Upward Acceleration Guidance Upward acceleration of trunk line guidance speed v a,k exist v 1 and v Between 2, the formula is as follows:
[0030] In the formula: v a,k To accelerate the upward guidance speed; v max This represents the upper limit of the allowable value for the guiding speed in the uphill direction of the main line; v min This is the lower limit of the allowable value for the guiding speed in the upward direction of the main line; The speed before guidance; v 1 and v The formula for calculating 2 is as follows:
[0031]
[0032]
[0033] In the formula: Intersection Intersection The distance between them; Intersection In the k - The last car in one cycle departs at the time of arrival at the downstream intersection. Travel time; Intersection In the k -1 time interval between the departure time of the last car in a cycle and the end time of the green light; Intersection Red light time; To maintain a safe distance from the front of the vehicle; D212, Mainline Upward Deceleration Guidance Mainline uphill deceleration guide speed v d,k exist v 3 and v Between 4, the formula is as follows:
[0034] v 3 and v The formula for calculating 4 is as follows:
[0035]
[0036]
[0037] In the formula: Intersection In the k During the +1 green light cycle, the first vehicle proceeds to the downstream intersection. Travel time; Intersection In the k +1 time interval between the departure of the first vehicle during a green light cycle and the start of the green light in that cycle; Intersection In the kThe time interval between the departure time of the first vehicle under deceleration guidance during a green light cycle and the end time of that green light cycle.
[0038] D22. Methods for guiding the speed of trunk line travel. D221, Main Line Downstream Acceleration Guidance Mainline downhill deceleration guide speed exist and The formula is as follows:
[0039] and The calculation formula is as follows:
[0040]
[0041]
[0042] In the formula: Intersection In the The time interval between the departure time of the lead vehicle guided by speed within a cycle and the time when the green light turns on in that cycle; Intersection From the midpoint of the red light to the intersection The time difference at the midpoint of the upward red light; Intersection Green light time; D222, Main Line Downward Slowdown Guidance Mainline downhill deceleration guide speed exist and between, The specific values are as follows:
[0043] and The calculation formula is as follows:
[0044]
[0045]
[0046] Compared with the prior art, the present invention has the following beneficial effects: 1. Because the trunk line coordination control based on the indefinite period of this invention can be more flexibly adjusted according to real-time traffic demand, it is different from the existing trunk line static coordination control and has the characteristics of strong versatility and wide coverage. 2. This invention constructs a maximum green wave band model applicable to indeterminate periods, determines the allocation ratio based on the flow ratio, making it applicable to different periods on the trunk line, and solves it through a genetic algorithm, which has fast convergence speed and high calculation accuracy; 3. The non-fixed-period trunk line coordination control established by this invention can be dynamically adjusted according to real-time traffic data, which can better grasp the traffic situation and improve the efficiency and accuracy of traffic management. 4. Because this invention can provide an accurate trunk line adaptive coordinated control scheme, it is highly scientific, has high calculation accuracy, and good reliability; 5. Because the non-fixed-period arterial coordination control of this invention can be dynamically adjusted based on real-time traffic data, it avoids road congestion and traffic delays caused by fixed periods. This not only improves the safety and stability of road traffic but also effectively reduces vehicle delays and carbon emissions in urban road networks, resulting in good economic efficiency.
[0047] 6. By adopting the non-fixed-period trunk line coordinated control method proposed in this invention, urban traffic management departments can conduct dynamic macro-management of vehicles within the urban road network. Attached Figure Description
[0048] This invention has a total of appendices Figure 21 Zhang, of which: Figure 1 This is a technical roadmap of the present invention.
[0049] Figure 2 This is a schematic diagram of the intersection of Lushun South Road.
[0050] Figure 3 This is a diagram of the trunk line system.
[0051] Figure 4 This is a schematic diagram of the Huaxin intersection signal timing scheme (early).
[0052] Figure 5 This is a schematic diagram of the signal timing scheme (night) at the Huaxin intersection.
[0053] Figure 6 This is the signal timing diagram for the first phase of the intersection.
[0054] Figure 7 This is the signal timing diagram for the second phase intersection (early).
[0055] Figure 8 This is the signal timing diagram for the second phase intersection (nighttime).
[0056] Figure 9 This is a schematic diagram of the intersection of Huaxin Software Park and the south side of Hengda Yunxi.
[0057] Figure 10 This is a schematic diagram of the intersection on the north side of Provence Phase I.
[0058] Figure 11 This is a schematic diagram of the intersection of Provence Phase II and III and Lushun South Road.
[0059] Figure 12 This is the solution flowchart.
[0060] Figure 13 This is a diagram showing the current status of green wave coordinated control.
[0061] Figure 14 It is a time-distance diagram guiding the uplink speed on the main line.
[0062] Figure 15 This is a graph showing the guide values for the upstream speed of the main line.
[0063] Figure 16 This is a diagram showing the deceleration guidance values for the main line.
[0064] Figure 17 This is a time-distance diagram showing the downlink speed guidance for trunk lines.
[0065] Figure 18 This refers to the range of values for the trunk line downlink speed guide.
[0066] Figure 19 This is a flowchart of a genetic algorithm.
[0067] Figure 20 This is a schematic diagram of the VISSIM simulation steps.
[0068] Figure 21 This is a schematic diagram of a road network simulated by VISSIM. Detailed Implementation
[0069] The invention will now be further described with reference to the accompanying drawings. Figure 1 As shown, the method for guiding real-time dynamic routes of ships is suitable for both inland waterways and ocean routes, and includes the following steps: 1. Information Collection This invention investigates the distances between Lushun South Road and the intersections of three surrounding residential areas, traffic flow data at these intersections, the current signal timing at each intersection, and the channelization schemes for each intersection. Specific details of the intersections are shown in Table 1 and... Figure 2 As shown Table 1 Current Status of the Intersection
[0070] This invention is for signal timing during morning and evening rush hours. It determines the morning and evening rush hour periods based on traffic volume surveys conducted every 15 minutes, compiles the traffic flow during these periods, and also determines the number of various vehicle types in the traffic volume survey. The traffic flow data obtained from the survey is then converted according to the urban road vehicle type classification standards. The urban road vehicle type classification standards are specified in my country's "Highway Engineering Technical Standards" and "Urban Road Design Specifications", as shown in Table 2.
[0071] Table 2. Vehicle Classification Standards for Urban Roads
[0072] In the information collection process, this invention sets up three vehicle observation points on the eastern section of Lushun South Road to conduct traffic surveys: No. 1 Huangnichuan-Huaxin Software Park, No. 2 Huaxin Software Park, and No. 3 Yida Information Park-Kaiteli Company. Traffic flow at each observation point is statistically analyzed from 6:30 AM to 8:30 PM daily. Figure 3 As shown in Table 3, the survey was conducted manually, using tools such as questionnaires and cameras.
[0073] Table 3 Summary of Traffic Flow Survey
[0074] The current signal timing schemes and intersection types for each intersection, such as... Figure 4 — Figure 11 As shown.
[0075] 2. Establish a timing optimization model for coordinated control of trunk lines with irregular periods. This invention takes minimizing vehicle delays, maximizing intersection capacity, and minimizing the number of stops as the optimization objectives for traffic control benefits, and constructs a new arterial coordinated timing optimization model to maximize the overall traffic efficiency of vehicles.
[0076] (1) Vehicle delay model Vehicle delays refer to the extra travel time caused by traffic control measures or queuing vehicles during normal driving. It is a key factor in evaluating the service conditions of intersections.
[0077] 1) HCM model The U.S. Road Traffic Manual (HCM2000) proposes a model for calculating intersection vehicle delays. This model categorizes vehicle delays into three types: uniform delay, incremental delay, and initial queue delay. The specific formulas are as follows:
[0078] In the formula: For vehicle average control delay; To ensure even delays; For incremental delays; Delay due to initial queuing; This is the signal linkage correction coefficient;
[0079] In the formula: The duration of the signal period; The effective green light time for the lane; The saturation level of the vehicles;
[0080] In the formula: For analysis time; π This is the incremental delay sensing adjustment coefficient; To improve the traffic capacity of the lane group; These are the control and filtering adjustment coefficients for upstream signals;
[0081] In the formula: For analysis time The initial number of vehicles in the queue; For delay parameters; in: ,
[0082] 2) Webster Delay Model The Webster delay model is also a commonly used model for calculating vehicle delays. Based on the assumption that vehicle arrivals follow a Poisson distribution, it modifies the given intersection vehicle delay model. The specific formula is as follows:
[0083] In the formula: —Average intersection delay, s / pcu; —Intersection saturation; —Lane flow ratio; —Vehicle arrival rate, pcu / h.
[0084] This invention uses the calculated delays of the Webster delay model and the HCM2000 model as a basis, and constructs a new delay model by considering the delays generated in signal linkage. The calculation formula is shown in step B1.
[0085] (2) Intersection capacity model The U.S. Road Traffic Manual (HCM2000) proposes a capacity model as shown in step B2, which is calculated as follows.
[0086] (3) Parking frequency model Within a given cycle, the number of times a vehicle comes to a complete stop due to traffic control at an intersection is called the number of stops. An increase in the number of stops leads to an increase in vehicle delays and is inversely proportional to the saturation level. It is an important indicator for measuring the traffic operation of an intersection. The formula for calculating the number of vehicle stops is shown in step B3.
[0087] (4) Construct a trunk line coordination timing optimization model As can be seen from the above formula, the signal period is positively correlated with delay and traffic capacity, but negatively correlated with the number of stops. In order to achieve the optimization goals of minimizing delay, maximizing intersection traffic capacity and minimizing the number of stops, the trunk line coordinated timing optimization model is shown in step B4.
[0088] The solution process is as follows: Figure 12 As shown. First, the period of each individual phase is calculated separately, and then the model parameters are substituted into MATLAB for solution.
[0089] 3. Calculation of trunk line coordination timing optimization model This invention uses Webster's theory to solve for relevant parameters such as indeterminate period, green light time, flow rate ratio, and total loss time in the trunk line coordination timing optimization model.
[0090] 3.1 Determination of Indeterminate Period The limitations of common cycles in the arterial coordinated control system have severely affected the implementation of the line-to-surface traffic control strategy and the promotion of coordinated control technology to urban roads.
[0091] When using variable-cycle coordinated control, the system has multiple cycle times: a critical cycle with high traffic volume and a variable cycle with low traffic volume. After determining an initial phase difference, it returns to the initial phase difference after several cycles. Because the cycles within the variable-cycle coordinated control system are not equal, the relative phase difference of the intersection changes after the first signal cycle of a fixed-cycle intersection ends. Therefore, the initial phase difference is particularly important, determining the delays and traffic efficiency of the entire arterial system.
[0092] Assumptions: 1) Assume there are three intersections within the main road system. , D 2. The corresponding period is , T 2.
[0093] 2) The distance between adjacent intersections is 100-500m 3) Traffic flow Flow direction , The flow is upward, and the opposite direction is downward. 4) It is a key intersection with high traffic volume; , Intersection with indefinite period 5) The maximum cycle time for indefinite cycles shall not exceed 15 minutes. To ensure that the entire indeterminate cycle is an integer multiple of the critical phase cycle, The initial period minimum value is set at the critical intersection. Halfway through the cycle time, the key intersection will be reached. Half-cycle time is divided into equal parts n Select one portion based on the flow ratio. You can get a portion. The calculation formula is shown in step B5.
[0094] 3.2 Improve the allocation of green light time When allocating green light time in trunk line green wave coordination control, critical intersections and non-critical intersections should be calculated separately. Critical intersections can be calculated according to single-point signal timing, while non-critical intersections should be adjusted according to the traffic flow at critical intersections.
[0095] 1. Minimum green light time in the coordinated phase of a critical intersection The minimum green light time in the coordinated phase should be the maximum green light time in the coordinated phase of non-critical intersections, as shown in step B61.
[0096] 2. The minimum effective green light time in the non-coordinated phase of a non-critical intersection is calculated as shown in step B62.
[0097] 3. Effective green light time in non-critical intersections and non-coordinated phases The green light time of the non-critical intersection coordinated phase within the mainline green wave coordinated control should not be less than the green light time of the critical intersection coordinated phase. In order to maximize the green wave band, after determining the minimum green light time of the non-coordinated phase, the remaining green light time should be adjusted to the coordinated phase. The calculation is shown in step B63.
[0098] 4. Establish an optimization model for coordinated control of indeterminate periodic phase difference. (1) Improved MAXBAND model The model used in this invention is an improved MAXBAND model. When dealing with situations where traffic flow varies significantly at intersections, the maximum green wave method does not provide a clear solution. Therefore, this invention employs a variable-period trunk line coordinated control method to address similar problems. The allocation ratio is introduced here. kTo determine the specific period length of the indeterminate period, among which k ∈(0.5, 1). The specific model is shown in step D1.
[0099] (2) Speed-guided strategy Traditional trunk line green wave coordinated control in use with irregular cycles, such as the green light start-up time distance Figure 13 As shown in the diagram. It can be seen from the diagram that the intersection... In the The first cycle and the first Vehicles released during the first week will encounter a green light when they travel at the prescribed green wave speed to the downstream intersection. And during the second week... Vehicles that are allowed to pass within a cycle will encounter red lights when traveling at the green wave speed, and the above phenomenon will occur periodically.
[0100] The parking problem is addressed by using speed guidance methods, and the cycle... Within the traffic flow, the initial section can be guided by acceleration, while the subsequent section can be guided by deceleration. Speed guidance allows vehicles to smoothly pass through downstream intersections. Therefore, the speed guidance model becomes extremely important. To facilitate model construction, the following assumptions are made: a) Under vehicle-road cooperative systems, information about the intersection and vehicles, such as vehicle position, speed, and number, as well as intersection information, are available; b) Vehicles can follow the speed guidance strategy and respond promptly; c) The impact of pedestrians crossing the street and non-motorized vehicles is not considered.
[0101] 1) Speed guidance method for trunk line uplink When vehicles come from the intersection Drive to the intersection For the northbound direction of the main road, there will be instances of stopping and smooth passage. The solution is as follows: [The text abruptly shifts to a different topic] At the The green light cycle is divided into two parts. The first part is used to accelerate and guide traffic, allowing it to utilize the intersection... The Green wave bandwidth and spare time within each cycle This allows vehicles to accelerate and pass through the downstream intersection continuously. The latter half involves deceleration guidance, utilizing the intersection. The Green wave bandwidth allowance time within each cycle This allows vehicles to slow down and pass through the downstream intersection continuously. Upward speed guidance, such as Figure 14 , Figure 15 As shown.
[0102] ① Guiding the acceleration of upstream travel on trunk lines Uplink acceleration guides value retrieval as follows Figure 15 As shown, the upward acceleration guides the speed. Should be in The calculation formula is shown in step D211.
[0103] To maximize the traffic capacity of the intersection, its speed of acceleration guidance is required. The value range should include: for intersections No. The first vehicle during each green light cycle will be accelerated and guided to the downstream intersection. The time point and the first Within each cycle, the last vehicle traveling according to the green wave should arrive at the intersection as close as possible to the next vehicle's arrival time. In the Each cycle has more green light time allocated to vehicles accelerating and guided, maximizing the use of the cycle. The green light time. The specific values are shown in step D211.
[0104] ② Guidance for slowing down on the main line Values for deceleration guidance on the main line are as follows: Figure 16 As shown, the deceleration guide speed on the main line is... Should be in The calculation formula is shown in step D212.
[0105] For deceleration guide speed There is also a corresponding range of values: corresponding to the intersection In the The first vehicle that slows down during the green light period within a cycle proceeds to the downstream intersection. The timing should also be related to the intersection. In the During each green light cycle, the first vehicle traveling at the downstream intersection should arrive at a point as far away as possible to ensure it arrives at the intersection on the first green light cycle. More time is allocated within each cycle to vehicles that are slowing down and guided. The specific values are shown in step D212.
[0106] 2) Speed guidance method for trunk line downlink When vehicles come from the intersection Drive to the intersection For the downstream direction of the main road, there will be instances of stopping and smooth passage in sections. The solution is as follows: at the intersection... At the The green light cycle is divided into three parts, with the middle part following the speed set by the green wave band. The cycle travels to the downward intersection. For green wave bandwidth, the margin of error The vehicles were accelerated and guided, allowing vehicles that should have stopped to proceed within a certain timeframe. Continuous passage through downstream intersection For green wave bandwidth and subsequent margin time Vehicles within the area are guided to slow down so that they can reach the next level. Successfully passed the downstream intersection within the cycle. Downward speed guidance, such as Figure 17 As shown in the figure: For the first The period after the green light in each cycle; For the first The green light cycle was in effect some time ago; To guide the downward deceleration speed; To accelerate the downward guidance speed.
[0107] ① Guiding the acceleration of trunk line outbound traffic Trunk line downlink acceleration guides value retrieval, such as Figure 18 As shown, the guide speed for the downhill section is reduced. Should be in The calculation formula is shown in step D221.
[0108] To maximize the traffic capacity of the intersection, its speed of acceleration guidance is required. The value range should include: for intersections No. Pre-circuit bandwidth allowance time for each green wave cycle The lead vehicle inside is accelerated and guided to the downstream intersection. Time points and cycles The start times of the inner green light should be as close as possible to each other, so that the intersection... In the Each cycle has more green light time allocated to vehicles accelerating and guided, maximizing the use of the cycle. The green light time. The specific values are shown in step D221.
[0109] ② Guidance for slowing down on main lines The value for deceleration guidance on the main line is also as follows. Figure 18 As shown, the guide speed for the downhill section is reduced. It should be in The calculation formula is shown in step D222.
[0110] For intersections No. After the green wave bandwidth of each cycle, there is a spare time. The lead vehicle inside the intersection should be slowed down and guided to the downstream intersection. The time point and the first The start time of the green light should be as close as possible within each cycle, so that the intersection... In the Each cycle has more green light time allocated to vehicles accelerating and guided, maximizing the use of the cycle. The green light time. The specific values are shown in step D222.
[0111] 5. Solve the optimization model for coordinated control of indeterminate periodic phase difference. This invention employs a genetic algorithm to solve the optimization model for coordinated control of indeterminate periodic phase differences and vehicle speed induction. The implementation process of the genetic algorithm is as follows: Figure 19 As shown.
[0112] (1) Chromosome encoding and decoding Chromosome encoding refers to converting the signal period length and phase green light time to be optimized into binary symbol strings for representation, mapping the problem's phenotype to its genotype. For signal optimization problems with indeterminate periods, a hybrid encoding method can be used, where the period length and green light time are encoded separately to ensure that the genetic algorithm can optimize for different encoded objects. During decoding, the binary symbol strings are converted into corresponding decimal values to obtain the corresponding signal period length and green light time, thus enabling the decoding operation of the signal optimization scheme. Through this encoding and decoding method, the genetic algorithm can optimize the phase difference, thereby achieving an improved maximum green band control strategy.
[0113] (2) Generate the initial population In genetic algorithms, the method of generating the initial population has a significant impact on the algorithm's convergence and search efficiency. Typically, the population size is set to 20-100. In the improved maximum green band model, a random generation method can be used to generate the initial population to ensure the diversity among individuals. Individuals in the initial population need to conform to the range of green light duration and phase difference values, and random generation is necessary to guarantee population diversity. Furthermore, to avoid getting trapped in local optima, heuristic methods can be used to generate the initial population to improve the algorithm's search efficiency.
[0114] (3) Fitness function design The fitness function is a crucial concept in genetic algorithms. It defines the fitness level of an individual and directly affects the probability of each individual being inherited by the next generation. When determining the fitness function, the characteristics of the actual problem and the optimization objective must be considered. The following formula describes the adaptability of an individual to its environment, and its calculation is as follows: in: It's about adaptability. For the individual's target value, ε It is a very small constant to avoid the denominator being zero.
[0115] (4) Select operation Selection is a crucial step in genetic algorithms. In selection, a roulette wheel algorithm is typically used to calculate the fitness value of individuals, and individuals are randomly selected as parents for crossover and mutation based on their fitness values. (Calculating the fitness value of an individual...) The specific formula is as follows:
[0116] In the formula: -individual The probability of being selected; -individual The fitness value.
[0117] (5) Cross operations Crossover occurs by randomly combining chromosomes from different individuals to generate new individuals. To avoid getting trapped in local optima, a relatively high crossover probability is chosen to prevent premature convergence. Throughout different stages of the algorithm, as the number of evolutions increases, the crossover probability and search range should be gradually reduced to improve accuracy. The crossover probability is calculated using the following formula:
[0118] In the formula: The maximum crossover probability; Minimum crossover probability; The higher fitness among the two individuals at the intersection; f avg The average fitness of each generation of the population; —The maximum fitness in the population.
[0119] (6) Mutation operation Mutation operations alter an individual's genes by performing inverse operations or substitutions, thereby creating a new individual. Unlike crossover, mutation operations typically affect only a subset of individuals. The mutation probability is calculated using the formula shown below.
[0120]
[0121] In the formula: The maximum mutation probability; This represents the minimum mutation probability.
[0122] (7) Algorithm termination condition Typically, to ensure that the algorithm can obtain relatively accurate and stable results within a reasonable time, genetic algorithms use a maximum number of iterations and specific principles as termination conditions. The termination iteration count is usually set between 100 and 1000 to ensure that the algorithm can obtain relatively stable and accurate results after running a certain number of times.
[0123] 6. Output a trunk line coordination timing optimization scheme based on an irregular period. Combining the calculated indefinite cycle, green light time, phase difference, and induced vehicle speed, an optimized arterial coordination timing scheme based on the indefinite cycle is generated and output to provide decision-making information for traffic management personnel.
[0124] This invention utilizes the COM interface technology of VISSIM software, combined with the MATLAB programming environment and external program development, to achieve real-time data acquisition and real-time calculation of driver behavior and signal control schemes. The calculation results are then fed back into the VISSIM simulation software, thereby realizing the trunk line coordinated control model. After preparing the basic data, simulation is performed using the software, mainly involving the following five steps: Figure 20 As shown.
[0125] VISSIM was used to simulate the surveyed road segment, and simulations were performed to verify the existing scheme, the traditional arterial coordinated control scheme, and the arterial coordinated control scheme with an indefinite cycle. The verification time was set to 3600s, and the output results are the average vehicle delay, the number of vehicle stops, and the intersection capacity. Figure 21 As shown.
[0126] (1) Simulation data analysis 1) Simulation analysis of the current control scheme Simulations were performed on the current timing scheme, and the results are shown in Table 4.
[0127] Table 4 Simulation results of the original matching scheme
[0128] The simulation results show that during peak hours, traffic congestion is severe at the three intersections of Lushun South Road. The second-phase intersection has the longest cycle, the largest flow, and the greatest capacity. The first-phase intersection has the greatest vehicle delay and the most severe congestion. The Huaxin intersection has the smallest vehicle delay, the fewest average number of stops, and the least capacity.
[0129] 2) Simulation Analysis of Traditional Trunk Line Coordination Control Traditional trunk line coordination technology uses the conventional Webster timing method, identifying the intersection with the highest traffic volume as the critical intersection, i.e., the second-phase intersection. The common cycle is set at 156 seconds. After phase difference optimization, the phase difference between the second-phase and first-phase intersections is 28.7 seconds, and the phase difference between the first-phase and Huaxin intersections is 12.5 seconds. The simulation results using VISSIM are shown in Table 5.
[0130] Table 5 Simulation results of traditional trunk line coordination optimization scheme
[0131] As can be seen from the traditional trunk line coordination scheme, after the traditional trunk line coordination control, the cycle becomes 156 seconds. The vehicle delay and traffic capacity of the second-phase intersection with the largest traffic volume and the first-phase intersection with the most severe congestion are optimized. However, the delay of the Huaxin intersection with the smaller traffic volume has increased.
[0132] 3) Simulation analysis of coordinated control scheme for trunk lines with irregular periods Based on the aforementioned multi-objective single-point signal timing scheme, the signal timing scheme for each intersection is determined, then the key intersections are identified, and the variable period for each intersection is determined according to the traffic flow ratio to calculate the green light allocation time. Then, the phase difference is obtained by solving the improved MAXBAND model using a genetic algorithm. The vehicle speed guidance scheme is then determined in MATLAB, and the simulation results are shown in Table 6.
[0133] Table 6 Simulation results of the indeterminate period trunk line coordination optimization scheme
[0134] As can be seen from the table above, after adopting the non-fixed-period trunk line coordinated control scheme, the vehicle delay, traffic capacity, and average number of stops at the intersection have been significantly optimized, as shown in Table 7.
[0135] Table 7 Comparison of Overall Schemes for the Intersection of Lushun South Road
[0136] In terms of average delay, the average vehicle delay time of the irregular-period trunk line coordination optimization scheme is reduced by 12.59% compared with the original timing scheme and by 9.83% compared with the traditional trunk line coordination control optimization scheme. In terms of average number of stops, the average number of stops of the irregular-period trunk line coordination optimization scheme is reduced by 6.71% compared with the original timing scheme and by 3.77% compared with the traditional scheme. In terms of average capacity, the average capacity of intersections of the irregular-period trunk line coordination optimization scheme is increased by 9.1% compared with the original timing scheme and by 4.43% compared with the traditional trunk line coordination control scheme.
[0137] In summary, this invention proposes a method for determining the indefinite period using the traffic flow ratio. Simultaneously, a maximum green wave band model applicable to indefinite periods is constructed, the allocation ratio is determined based on the traffic flow ratio, and the solution is obtained through a genetic algorithm, exhibiting broad coverage and strong applicability. This invention differs from traditional arterial intersection coordination control by designing and developing an adaptive coordinated timing scheme for arterial intersections based on indefinite periods. This scheme requires less work, is economical, and has strong versatility. This invention only needs to utilize data from the distance between intersections, traffic flow data at intersections, current signal timing at each intersection, and channelization schemes at each intersection to calculate the adaptive timing scheme for traffic lights at each intersection on the arterial road network, thereby achieving real-time dynamic macro-management of vehicles in the urban road network.
[0138] This invention is not limited to this embodiment. Any equivalent concept or modification within the technical scope disclosed in this invention shall be included within the protection scope of this invention.
Claims
1. A trunk line adaptive coordinated control method based on indefinite period, characterized in that: Includes the following steps: A. Collect intersection information The intersection information is collected using manual surveys. The intersection information includes the distance between intersections, traffic flow data at intersections, the current signal timing status of each intersection, and the channelization scheme for each intersection. B. Establish a timing optimization model for coordinated control of trunk lines with irregular cycles. A timing optimization model for coordinated control of trunk lines with an indefinite period is constructed with minimizing vehicle delays, maximizing intersection capacity, and minimizing the number of stops as optimization objectives. C. Solving the timing optimization model for indeterminate period trunk line coordinated control Based on Webster's theory and using Matlab software to programmatically calculate the timing optimization model and timing optimization parameters for indeterminate period trunk line coordinated control, the indeterminate period trunk line adaptive coordinated timing optimization parameters include indeterminate period, green light time, flow rate ratio and flow rate ratio; D. Establish an optimization model for coordinated control of indeterminate periodic phase difference. The allocation ratio is determined based on the flow ratio, and an optimization model for phase difference coordination control with an indefinite period is constructed. Based on the existing phase difference, vehicle speed is guided for vehicles outside the green wave band, so that vehicles pass through the intersection continuously, reducing congestion on the main road. E. Solving the indeterminate period phase difference coordinated control optimization model The improved MAXBAND model, which is a genetic algorithm, is used to solve the problem and obtain the indeterminate periodic phase difference and the induced vehicle speed. F. Output a trunk line coordination timing optimization scheme based on an indeterminate period. Combining the calculation results of steps C and E, a trunk line coordination timing optimization scheme based on an indefinite period is generated and output to provide decision-making information for traffic management personnel.
2. The trunk line adaptive coordinated control method based on indefinite period as described in claim 1, characterized in that: The steps for establishing the timing optimization model for coordinated control of trunk lines with indefinite periods, as described in step B, are as follows: B1. Establish a vehicle delay model The vehicle delay model formula is as follows: in: i The phase number is calculated by the timing optimization model for coordinated control of trunk lines with indefinite periods. j Number the lanes at different intersections on the main road; For the first Phase 1 Average vehicle delay time per lane, measured in seconds; This represents the intersection cycle length, in seconds (s). For the first Phase green ratio; For the first Phase 1 Vehicle arrival rate of the lane, in units of pcu / h; For the first The saturation flux of the phase; for and The ratio; B2. Establish an intersection capacity model The intersection capacity model is represented as follows: In the formula: Q j For the first j Lane capacity; QS j For the first j The saturation flow rate of the lane; For the first The effective green light time for a phase; B3. Establish a parking frequency model The parking frequency model is represented as follows: In the formula: For the first Average number of stops per phase; For the first Phase saturation, which is the ratio of traffic flow to capacity; For phase The flow ratio; For phase Traffic flow; For phase Traffic capacity; x Intersection saturation; B4. Construct a trunk line coordinated control timing optimization model The objective function of the trunk line coordinated control timing optimization model is to achieve the optimization goals of minimizing delays, maximizing intersection capacity, and minimizing stops. It is expressed as follows: In the formula: The optimal cycle length must be an integer. For phase i Vehicle delays; For phase i The capacity of the intersection; For phase i Number of parking sessions.
3. The trunk line adaptive coordinated control method based on indefinite period as described in claim 1, characterized in that: The method for solving the timing optimization model for coordinated control of trunk lines with indeterminate periods, as described in step C, includes the following steps: C1. Determine the indefinite period C11. Determine the assumptions The assumptions are as follows: 1) Assume there are three intersections within the main road system. , D 2. The corresponding period duration is , T 2. ; 2) The distance between adjacent intersections is 100-500m; 3) Traffic flow from Flow direction , The flow is upward, and the opposite direction is downward. 4) It is a key intersection with high traffic volume; , Intersection with indefinite period 5) The runtime of an irregular cycle shall not exceed 15 minutes; C12. Calculate the duration of an indeterminate period. To ensure that the entire indeterminate period duration is an integer multiple of the critical phase period duration, the intersection S 2. The initial period minimum value is set at the critical intersection. S Half the duration of a cycle will be the key intersection. S The half-cycle duration is divided into equal parts. n Select one portion based on the flow ratio. k The formula for calculating the duration of a variable period is as follows: In the formula: For phase i The value of , i =0,1,2,… p ; for Return to the initial phase difference and repeat the cycle an indefinite number of times; The value is 0 ~n It is determined by the upstream and downstream flow ratio; Similarly, the indefinite period duration is obtained. The calculation formula is as follows: In the formula: m si For phase si The value of , si =0,1,2… p '; for Return to the initial phase difference and repeat the cycle an indefinite number of times; C2. Improve the allocation of green light time C21. The formula for calculating the minimum green light time in the coordinated phase of a critical intersection is as follows: In the formula: The minimum green light time in the coordinated phase at a critical intersection; This represents the total lost time for non-critical intersections; This refers to through traffic at non-critical intersections. This is the sum of the flows across all phases; C22. The formula for calculating the minimum effective green light time in non-coordinated phases at non-critical intersections is as follows: In the formula: t EGmn The first non-critical intersection non-coordinated phase mn Minimum effective green light time for a phase, in seconds; Q mn The first non-critical intersection non-coordinated phase mn Traffic volume per phase, pcu / h; SX mn The first non-critical intersection non-coordinated phase mn The saturation flux of the phase; This represents the actual saturation value in the non-coordinated phase of a non-critical intersection; y mn The first non-critical intersection non-coordinated phase mn Phase flow ratio; C23. The formula for calculating the effective green light time in non-coordinated phases at non-critical intersections is as follows: In the formula: The effective green time for coordinating phases at non-critical intersections; This represents the total lost time at non-critical intersections.
4. The trunk line adaptive coordinated control method based on indefinite period as described in claim 1, characterized in that: The steps for establishing the variable-period phase difference coordinated control optimization model described in step D are as follows: D1. Establish the improved maximum green band model, i.e., the MAXBAND model. Introducing allocation ratio k To determine the period of the indeterminate period, where k ∈(0.5, 1); the improved maximum green band model is expressed as follows: In the formula: This represents the ratio of uplink to downlink green wave bandwidth, where... In the formula: b This refers to traffic flow in the upbound direction. This refers to the traffic flow in the downstream direction; CM 1 is the minimum period. CM 2 is the maximum period; The distance between the two intersections; e ii This represents the minimum upward green wave propulsion speed. This represents the minimum speed of the downlink green wave propagation. f ii This represents the maximum speed of the upward green wave propagation. This represents the maximum speed of the downlink green wave propagation. It should be an integer multiple of the period length; ω ii For the first The time difference between the end of the red light at an intersection and the green wave band at the edge of the traffic flow; For the first The time difference between the start of the red light at an intersection and the green wave band at the edges of both directions; t ii This is the time required to clear the queue of vehicles before the arrival of the upstream main line traffic. This is the time required to clear the queue of vehicles before the arrival of the downstream main line traffic. r ii For the first The red light duration for northbound traffic at each intersection; For the first Red light duration for southbound traffic at intersections; b For the uplink green wave bandwidth; This refers to the downlink green wave bandwidth; D2. Establish a speed-guided strategy D21. Speed guidance method for trunk line upward movement D211, Trunk Line Upward Acceleration Guidance Upward acceleration of trunk line guidance speed v a,k exist v 1 and v Between 2, the formula is as follows: In the formula: v a,k To accelerate the upward guidance speed; v max This represents the upper limit of the allowable value for the guiding speed in the uphill direction of the main line; v min This is the lower limit of the allowable value for the guiding speed in the upward direction of the main line; The speed before guidance; v 1 and v The formula for calculating 2 is as follows: In the formula: Intersection Intersection The distance between them; Intersection In the k - The last car in one cycle departs at the time of arrival at the downstream intersection. Travel time; Intersection In the k -1 time interval between the departure time of the last car in a cycle and the end time of the green light; Intersection Red light time; To maintain a safe distance from the front of the vehicle; D212, Mainline Upward Deceleration Guidance Mainline uphill deceleration guide speed v d,k exist v 3 and v Between 4, the formula is as follows: v 3 and v The formula for calculating 4 is as follows: In the formula: Intersection In the k During the +1 green light cycle, the first vehicle proceeds to the downstream intersection. Travel time; Intersection In the k +1 time interval between the departure of the first vehicle during a green light cycle and the start of the green light in that cycle; Intersection In the k The time interval between the departure time of the first vehicle under deceleration guidance during a green light cycle and the end time of that green light cycle; D22. Methods for guiding the speed of trunk line travel. D221, Main Line Downstream Acceleration Guidance Mainline downhill deceleration guide speed exist and The formula is as follows: and The calculation formula is as follows: In the formula: Intersection In the The time interval between the departure time of the lead vehicle guided by speed within a cycle and the time when the green light turns on in that cycle; Intersection From the midpoint of the red light to the intersection The time difference at the midpoint of the upward red light; Intersection Green light time; D222, Main Line Downward Slowdown Guidance Mainline downhill deceleration guide speed exist and between, The specific values are as follows: and The calculation formula is as follows: 。