A multi-path arterial signal coordination control method considering speed fluctuation

Abstract

The application provides a kind of multi-path arterial signal coordination control method considering speed fluctuation, comprising first collecting traffic data, including road network geometry data, traffic flow data and signal control data, determine a plurality of main paths according to traffic flow data.Then based on the driving speed of each vehicle on each main path, the average speed and speed fluctuation of the vehicle on each main path are calculated.Finally, a signal control optimization model is constructed: the maximum weighted green wave bandwidth of all paths is taken as the target, the objective function is constructed, and loop integer constraint, interference constraint, speed fluctuation space-time constraint, maximum speed fluctuation constraint and minimum speed fluctuation constraint are added, the signal control optimization model is solved, the optimized signal cycle and green wave bandwidth are obtained, and the optimized signal timing strategy is output.The signal timing generated by the method has good prospects in reducing travel delay and parking frequency, and can achieve better multi-path coordination effect.

Description

Technical Field

[0001] The present invention belongs to the field of urban road traffic signal control, and in particular relates to a multi-path trunk road signal coordinated control method considering speed fluctuations. Background Art

[0002] Cooperative signal control on urban arterial roads has long been considered one of the most effective ways to reduce travel time costs and pollutant emissions. A large number of signal cooperative control schemes have been designed to alleviate road traffic congestion. Among them, the signal cooperative control method oriented towards bandwidth maximization is favored by traffic engineers because of its intuitive and easy-to-solve characteristics. For the cooperative control method based on bandwidth maximization, the premise for the green wave band to be effective is that the fleet must travel at a fixed green wave band speed. However, due to the objective influence of uncertain factors, it is impossible to guarantee that all vehicles travel at the green wave band speed. Especially on arterial roads with multiple important path flows in different directions. Due to the interweaving of path flows in different directions in the arterial road section, the operating interference between vehicles will increase, resulting in inevitable fluctuations in vehicle speed, which greatly weakens the control effect of the coordinated signal control method on the arterial road. Summary of the Invention

[0003] In response to the problems existing in the prior art, the present invention provides a method for coordinated control of multi-path trunk road signals that takes speed fluctuations into account. The method of the present invention collects traffic flow, road network geometry data, and signal control data, calculates the speed fluctuation of the vehicle, and sets speed fluctuation constraints to ensure that the vehicle can still pass through multiple intersections smoothly under fluctuations. The core of the patent is to maximize the green wave bandwidth of each path by constructing and solving a signal control optimization model, thereby realizing intelligent coordinated control of traffic signals, improving the operating efficiency of traffic flow, and reducing waiting time and the number of stops. The signal timing generated by this model has good prospects in reducing travel delays and the number of stops, indicating that it can achieve better multi-path coordination effects.

[0004] To solve the above technical problems, the present invention provides the following technical solution: a multi-path trunk road signal coordinated control method considering speed fluctuations, comprising the following steps:

[0005] S1. Collect traffic data, including road network geometry data, traffic flow data, and signal control data, and determine several main routes based on the traffic flow data;

[0006] S2. Calculate the average speed and speed fluctuation of vehicles on each main path based on the speed of each vehicle on each main path ;

[0007] S3. Construct a signal control optimization model: With the goal of maximizing the weighted green wave bandwidth of all paths, construct an objective function, and simultaneously add loop integer constraints, interference constraints, speed fluctuation spatiotemporal constraints, maximum speed fluctuation constraints, and minimum speed fluctuation constraints. Solve the signal control optimization model, obtain the optimized signal period and green wave bandwidth, and output the optimized signal timing strategy.

[0008] Furthermore, in the aforementioned step S1, the road network geometry data includes: intersection locations and distances between adjacent intersections for calculating vehicle travel time; traffic flow data includes: traffic flow on each path, which is used to calculate the weight of each path; signal control data includes: signal cycle of each intersection , green light duration and red light duration, for signal timing optimization. Further, the aforementioned step S2 includes the following sub-steps:

[0009] S2.1. Obtain the actual driving speed of each vehicle , calculate the average speed on the path , as follows:

[0010]

[0011] in, is the total number of vehicles;

[0012] S2.2, according to the actual driving speed and average speed Calculate speed fluctuation , as follows:

[0013] .

[0014] Furthermore, in the aforementioned step S3, the objective function is as follows:

[0015]

[0016] in, and The outgoing and incoming critical paths are The weight of and Outbound and inbound critical paths respectively Green wave bandwidth.

[0017] Furthermore, the weight of the aforementioned path is calculated as follows:

[0018]

[0019]

[0020] in, Critical Path of traffic, Respectively represent the set of all critical paths, Represents the set of all critical paths.

[0021] Furthermore, in the aforementioned step S3, the loop integer constraint, interference constraint, speed fluctuation spatiotemporal constraint, maximum speed fluctuation constraint, and minimum speed fluctuation constraint are specifically:

[0022] The loop integer constraint is as follows:

[0023]

[0024]

[0025]

[0026]

[0027] in, For intersections The phase difference offset, For adjacent intersections arrive The travel time between Outbound critical path At the intersection The loop integer variable at , Entering the critical path At the intersection The loop integer variable at , Outbound critical path At the intersection The length of the red light at Towards the critical path At the intersection The length of the red light at Indicates the critical path At the intersection The duration of the green light before the green wave band, Indicates the critical path At the intersection The duration of the green light after the green wave band, Towards the critical path The convoy is at the intersection The queue clearing time, Outbound critical path The convoy is at the intersection The queue clearing time, Represents the set of all critical paths, Represents the set of all critical paths; Indicates the critical path The corresponding intersection set, For intersections The phase difference offset, Outbound critical path At the intersection The length of the red light at Towards the critical path At the intersection The length of the red light at Indicates the critical path At the intersection The duration of the green light before the green wave band, Indicates the critical path At the intersection The duration of the green light after the green wave band, Outbound key path At the intersection The loop integer variable at , Towards the critical path At the intersection The loop integer variable at .

[0028] Furthermore, in the aforementioned step S3, the interference constraint is as follows:

[0029]

[0030]

[0031] in, Outbound critical path At the intersection The green light time, Towards the critical path At the intersection The green light time, Represents the set of all critical paths, Represents the set of all critical paths; Indicates the critical path The corresponding intersection set, and Outbound and inbound critical paths respectively Green wave bandwidth.

[0032] Furthermore, the speed fluctuation spatiotemporal constraints in the aforementioned step S3 are:

[0033]

[0034]

[0035]

[0036]

[0037] in, Indicates an intersection and The distance between is the inverse of the period length, is the preset green wave speed, is the velocity fluctuation, Outbound critical path At the intersection The green light time at the station.

[0038] 9. The method for coordinated multi-path trunk road signal control considering speed fluctuation according to claim 6, wherein the minimum speed fluctuation constraint in step S3 is as follows:

[0039]

[0040] The maximum speed fluctuation constraint is as follows:

[0041] .

[0042] is the minimum speed allowed on the road, is the maximum speed allowed on the road.

[0043] Furthermore, the aforementioned multi-path trunk road signal coordinated control method considering speed fluctuations solves the signal control optimization model through a mixed integer linear programming solver.

[0044] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0045] 1. Considering speed fluctuations: Existing coordinated signal control methods for arterial roads mostly assume that vehicles travel at a fixed speed and ignore the speed fluctuations caused by the interweaving of multi-path traffic flows. This invention overcomes this limitation by introducing spatiotemporal constraints on speed fluctuations, thereby improving the utilization efficiency of green wave bands under complex traffic flow interference.

[0046] 2. Multi-path signal collaborative control: Most existing technologies only optimize signals for a single path. However, the present invention proposes a signal collaborative control method for important traffic flows based on multiple paths, which can achieve coordinated optimization of traffic flows in multiple directions in a complex main road traffic environment, avoiding the impact of mutual interference between paths on traffic efficiency.

[0047] 3. Improved Control Effectiveness and Robustness: By establishing speed fluctuation optimization constraints, this invention improves the robustness of green band control in uncertain scenarios. Regardless of the minimum or maximum speed under speed fluctuations, vehicles can smoothly pass through multiple intersections under signal control, avoiding unnecessary stops and waiting time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flow chart of a multi-path trunk road signal coordinated control method considering speed fluctuations provided in accordance with an embodiment of the present invention;

[0049] Figure 2 This is an information diagram of each intersection. In the figure, (a) is a schematic diagram of the intersection location information, and (b) is a schematic diagram of the distance between each intersection.

[0050] Figure 3 are the flow diagrams of each intersection; (a) is the flow diagram of intersection 1, (b) is the flow diagram of intersection 2, (c) is the flow diagram of intersection 3, (d) is the flow diagram of intersection 4, (e) is the flow diagram of intersection 5, and (f) is the flow diagram of intersection 6.

[0051] Figure 4 It is the signal timing diagram of each intersection.

[0052] Figure 5 It is a spatiotemporal diagram of the multipath signal cooperative control model considering speed fluctuations. DETAILED DESCRIPTION

[0053] In order to better understand the technical content of the present invention, specific embodiments are given and described below with reference to the accompanying drawings.

[0054] Various aspects of the present invention are described herein with reference to the accompanying drawings, which show a number of illustrative embodiments. The embodiments of the present invention are not limited to those described in the accompanying drawings. It should be understood that the present invention can be implemented by any of the various concepts and embodiments described above, as well as the concepts and implementations described in detail below, because the concepts and embodiments disclosed herein are not limited to any particular implementation. In addition, some aspects disclosed herein may be used alone or in any appropriate combination with other aspects disclosed herein.

[0055] In order to verify the effectiveness of the present invention, a certain trunk road section is selected as a test case. The road section contains six signal-controlled intersections and traffic flows on four key paths. The traffic flow includes straight flow and turning flow, such as Figure 3 As shown in Figure 2, multiple critical paths interweave on this main road, resulting in fluctuations in vehicle speeds due to the influence of path flows in different directions.

[0056] refer to Figure 1A multi-path trunk road signal coordinated control method considering speed fluctuations comprises the following steps:

[0057] S1. Collect traffic data, including road network geometry data, traffic flow data, and signal control data, and determine several main routes based on traffic flow data. Road network geometry data: including the location information of each intersection and the distance between adjacent intersections, which is used to calculate the vehicle travel time, such as Figure 2 As shown in the figure, (a) is a schematic diagram of the intersection location information, and (b) is a schematic diagram of the distance between each intersection. Traffic flow data: The flow of each intersection is obtained through real-time monitoring equipment, such as Figure 3 As shown in the figure, (a) is the flow diagram of intersection 1, (b) is the flow diagram of intersection 2, (c) is the flow diagram of intersection 3, (d) is the flow diagram of intersection 4, (e) is the flow diagram of intersection 5, and (f) is the flow diagram of intersection 6. (Time 7am-8am, unit: Veh / h). These flow data are used to calculate the weight of each path ;Signal control parameters: including the signal cycle of each intersection , green light duration and red light duration, such as Figure 4 shown.

[0058] This invention proposes a multi-path arterial road signal coordinated control method that takes into account speed fluctuations. First, during implementation, multiple critical paths on the arterial road must be determined based on actual peak hour traffic flow. This traffic flow data can be obtained through an Automatic Vehicle Identification (AVI) system or other real-time monitoring facilities. By evaluating the peak hour traffic flow of each path, the path with the highest peak hour traffic flow is selected as the critical path and used as the optimization target in the subsequent optimization process. The critical path in this example is as follows: Figure 5 .

[0059] Preferably, the traffic flow data obtained includes the traffic volume on each path , as shown in Table 1, the traffic flow table of the bus route to be optimized, which is used to calculate the path weight later .

[0060] Table 1 Traffic flow of bus routes to be optimized

[0061] Traffic flow path Path 1 Path 2 Path 3 Path 4 Traffic flow (vehicles / hour) 567 189 757 378

[0062] S2. Calculate the average speed and speed fluctuation of vehicles on each main path based on the speed of each vehicle on each main path Calculate the average speed , by obtaining the vehicle speed on each path And calculate the average speed, the formula is as follows:

[0063]

[0064] in, represents the number of vehicles on the path, For the The speed of the vehicle.

[0065] Calculate speed fluctuation , according to the vehicle's speed and average speed , calculate the velocity fluctuation of each path , the specific formula is:

[0066]

[0067] S3. Build a signal control optimization model to optimize the signal timing of each key path. Specifically, the objective is to maximize the weighted green wave bandwidth of all paths and construct an objective function as follows:

[0068] in, and The outgoing and incoming critical paths are The weight of and Outbound and inbound critical paths respectively Green wave bandwidth.

[0069] At the same time, loop integer constraints, interference constraints, speed fluctuation time and space constraints, maximum speed fluctuation constraints, and minimum speed fluctuation constraints are added. By solving the signal control optimization model, the optimized signal period and green wave bandwidth are obtained, and the optimized signal timing strategy is output.

[0070] according to Figure 5 In the space-time diagram shown, to ensure the continuity of the green wave band between adjacent intersections and to prevent vehicles from stopping at red lights within the green wave band, a loop integer constraint is added:

[0071]

[0072]

[0073]

[0074]

[0075] in, For intersections The phase difference offset, For adjacent intersections arrive The travel time between Outbound critical path At the intersection The loop integer variable at , Entering the critical path At the intersection The loop integer variable at , Outbound critical path At the intersection The length of the red light at Towards the critical path At the intersection The length of the red light at Indicates the critical path At the intersection The duration of the green light before the green wave band, Indicates the critical path At the intersection The duration of the green light after the green wave band, Towards the critical path The convoy is at the intersection The queue clearing time, Outbound critical path The convoy is at the intersection The queue clearing time, Represents the set of all critical paths, Represents the set of all critical paths; Indicates the critical path The corresponding intersection set, For intersections The phase difference offset, Outbound critical path At the intersection The length of the red light at Towards the critical path At the intersection The length of the red light at Indicates the critical path At the intersection The duration of the green light before the green wave band, Indicates the critical path At the intersection The duration of the green light after the green wave band, Outbound key path At the intersection The loop integer variable at , Towards the critical path At the intersection The loop integer variable at .

[0076] In order to ensure that the green wave band does not exceed the green light duration of the intersection, the model sets the interference constraint as follows:

[0077]

[0078] in, Outbound critical path At the intersection The green light time, Towards the critical path At the intersection The green light time, Represents the set of all critical paths, Represents the set of all critical paths; Indicates the critical path The corresponding intersection set, and Outbound and inbound critical paths respectively Green wave bandwidth.

[0079] To ensure that the convoy travels at a speed higher or lower than the design speed When , the convoy can still pass through the intersection smoothly, and the following speed fluctuation spatiotemporal constraints are set:

[0080] When the convoy's speed is lower than the preset speed Whether the rear vehicle can encounter a green light at the intersection determines whether the convoy can pass through the intersection smoothly. The specific constraints are:

[0081]

[0082]

[0083] When the convoy's speed exceeds the preset speed Whether the leading vehicle can encounter a green light at the intersection determines whether the convoy can continue to pass. The specific constraints are:

[0084]

[0085]

[0086] in, Indicates an intersection and The distance between is the inverse of the period length, is the preset green wave speed, is the velocity fluctuation, Outbound critical path At the intersection The green light time at the station.

[0087] Preferably, upper and lower limits of speed fluctuation are set to ensure that the vehicle speed is within the permitted driving range. The specific constraints are as follows:

[0088] Minimum speed fluctuation constraint: The vehicle's speed must not be lower than the minimum speed allowed , meeting the conditions:

[0089] Maximum speed fluctuation constraint: The vehicle's speed must not exceed the maximum speed allowed , meeting the conditions: .

[0090] Finally, the present invention uses the above-mentioned signal control optimization model to output the optimized signal control parameters for each intersection on the trunk line, and obtains a weighted bandwidth sum of multiple critical paths of 35 seconds and a green wave speed of 15 m / s. The weighted green wave bandwidth values ​​of each critical path are shown in Table 2.

[0091] Table 2

[0092] Bus routes Path 1 Path 2 Path 3 Path 4 Bandwidth (seconds) 59.3 38.1 20.3 26.3

[0093] The specific settings are based on actual construction requirements and are not specifically limited in this application.

[0094] The examples show that:

[0095] After using the method of the present invention, the vehicle can more effectively utilize the green wave band under the condition of speed fluctuation, thereby reducing the waste of green wave bandwidth caused by the speed deviating from the ideal speed.

[0096] Compared with traditional signal control methods, the present invention has significantly improved the overall operating performance of main roads, the traffic efficiency of intersections, and the travel performance of each key path.

[0097] Through simulation research on this example, the superiority of the present invention under complex traffic flow conditions is verified. In particular, when considering vehicle speed fluctuations, its signal control method can significantly improve traffic operation efficiency.

[0098] While the present invention has been described above with reference to preferred embodiments, this is not intended to limit the present invention. Persons skilled in the art will readily appreciate that various modifications and variations can be made without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A multi-path trunk road signal coordinated control method considering speed fluctuations, characterized in that: The following steps are involved: S1. Collect traffic data, including road network geometry data, traffic flow data, and signal control data, and determine several main routes based on the traffic flow data; S2. Calculate the average speed and speed fluctuation of vehicles on each main path based on the speed of each vehicle on each main path ; It includes the following sub-steps: S2.

1. Obtain the actual driving speed of each vehicle , calculate the average speed on the path , as follows: ； in, is the total number of vehicles; S2.2, according to the actual driving speed and average speed Calculate speed fluctuation , as follows: ； S3. Construct a signal control optimization model: With the goal of maximizing the weighted green wave bandwidth of all paths, construct an objective function. Simultaneously, add loop integer constraints, interference constraints, speed fluctuation spatiotemporal constraints, maximum speed fluctuation constraints, and minimum speed fluctuation constraints. Solve the signal control optimization model to obtain the optimized signal period and green wave bandwidth, and output the optimized signal timing strategy. The objective function is as follows: , in, and The outgoing and incoming critical paths are The weight of and Outbound and inbound critical paths respectively Green wave bandwidth.

2. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 1, characterized in that: In step S1, the road network geometry data includes: intersection locations and distances between adjacent intersections for calculating vehicle travel time; traffic flow data includes: traffic flow on each path, which is used to calculate the weight of each path; signal control data includes: signal cycle of each intersection , green light duration, and red light duration for signal timing optimization.

3. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 1, characterized in that: The weight of the path is calculated as follows: ； ； in, Critical Path of traffic, Respectively represent the set of all critical paths, Represents the set of all critical paths.

4. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 1, characterized in that: In step S3, the loop integer constraint, interference constraint, speed fluctuation spatiotemporal constraint, maximum speed fluctuation constraint, and minimum speed fluctuation constraint are specifically: The loop integer constraint is as follows: ， ； ， ； in, For intersections The phase difference offset, For adjacent intersections arrive The travel time between Outbound critical path At the intersection The loop integer variable at , Entering the critical path At the intersection The loop integer variable at , Outbound critical path At the intersection The length of the red light at Towards the critical path At the intersection The length of the red light at Indicates the critical path At the intersection The duration of the green light before the green wave band, Indicates the critical path At the intersection The duration of the green light after the green wave band, Towards the critical path The convoy is at the intersection The queue clearing time, Outbound critical path The convoy is at the intersection The queue clearing time, Represents the set of all critical paths, Represents the set of all critical paths; Indicates the critical path The corresponding intersection set, For intersections The phase difference offset, Outbound critical path At the intersection The length of the red light at Towards the critical path At the intersection The length of the red light at Indicates the critical path At the intersection The duration of the green light before the green wave band, Indicates the critical path At the intersection The duration of the green light after the green wave band, Outbound key path At the intersection The loop integer variable at , Towards the critical path At the intersection The loop integer variable at .

5. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 4, characterized in that: In step S3, the interference constraint is as follows: ， ， in, Outbound critical path At the intersection The green light time, Towards the critical path At the intersection The green light time, Represents the set of all critical paths, Represents the set of all critical paths; Indicates the critical path The corresponding intersection set, and Outbound and inbound critical paths respectively Green wave bandwidth.

6. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 4, characterized in that: Speed ​​fluctuation spatiotemporal constraints in step S3: ， ， ， ， in, Indicates an intersection and The distance between is the inverse of the period length, is the preset green wave speed, is the velocity fluctuation, Outbound critical path At the intersection The green light time at the station.

7. A multi-path trunk road signal coordinated control method considering speed fluctuations according to claim 4, characterized in that: The minimum speed fluctuation constraint in step S3 is as follows: ， The maximum speed fluctuation constraint is as follows: ， is the minimum speed allowed on the road, is the maximum speed allowed on the road.

8. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 1, characterized in that: The signal control optimization model is solved by a mixed-integer linear programming solver.

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