Multi-path main road signal cooperative control method considering speed fluctuation

Abstract

The invention provides a multi-path main road signal cooperative control method considering speed fluctuation, and the method comprises the steps: firstly collecting traffic data, including road network geometric data, traffic flow data and signal control data, and determining a plurality of main paths according to the traffic flow data; then, based on the running speed of each vehicle on each main path, the vehicle running average speed and the speed fluctuation quantity on each main path are calculated; and finally, constructing a signal control optimization model: constructing a target function by taking weighted green wave bandwidth maximization of all paths as a target, adding a loop integer constraint, an interference constraint, a speed fluctuation space-time constraint, a highest speed fluctuation constraint and a lowest speed fluctuation constraint, solving the signal control optimization model, and obtaining an optimized signal period and green wave bandwidth. And outputting the optimized signal timing strategy. The signal timing generated by the method has a good prospect in the aspect of reducing travel delay and parking times, and a better multi-path collaborative effect can be realized.

Description

Technical Field

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

[0002] Cooperative signal control on urban arterial roads has long been considered one of the most effective ways to reduce traffic 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 to 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 the main roads with important path flows in multiple different directions. Due to the interweaving of path flows in different directions in the main road section, the operating interference between vehicles will increase, resulting in inevitable fluctuations in vehicle speed, which greatly weakens the control effect of the main road cooperative signal control method. Summary of the invention

[0003] In view of the problems existing in the prior art, the present invention provides a method for coordinated control of multi-path trunk road signals taking into account speed fluctuations. 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, realize intelligent coordinated control of traffic signals, improve the operating efficiency of traffic flow, and reduce 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] In order to solve the above technical problems, the present invention provides the following technical solutions: 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. Based on the driving speed of each vehicle on each main path, calculate the average driving speed and speed fluctuation ε of the vehicles 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 add loop integer constraints, interference constraints, speed fluctuation time and space 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: the intersection location and the distance between adjacent intersections are used to calculate the vehicle travel time; the traffic flow data includes: the flow on each path, and the flow on the path is used to calculate the weight of each path; the signal control data includes: the signal cycle C, green light duration and red light duration of each intersection, which are used for signal timing optimization. Furthermore, the aforementioned step S2 includes the following sub-steps: S2.1, obtain the actual driving speed v of each vehicle i , calculate the average speed on the path As follows:

[0009]

[0010] Where N is the total number of vehicles;

[0011] S2.2, according to the actual driving speed v i and average speed Calculate the speed fluctuation ε as follows:

[0012]

[0013] Furthermore, in the aforementioned step S3, the objective function is as follows:

[0014]

[0015] in, and are the weights of the critical path i of the outgoing and incoming paths, respectively, and b i and are the green wave bandwidths of the outgoing and incoming critical path i respectively.

[0016] Furthermore, the weight of the aforementioned path is calculated as follows:

[0017]

[0018] Among them, f i is the flow of critical path i, Ω represents the set of all critical paths, Represents the set of all critical paths.

[0019] Furthermore, in the aforementioned step S3, the loop integer constraint, the interference constraint, the speed fluctuation time-space constraint, the maximum speed fluctuation constraint, and the minimum speed fluctuation constraint are specifically:

[0020] The loop integer constraint is as follows:

[0021] θ k +r i,k +w i,k +t k +n i,k =θ k+1 +r i,k+1 +w i,k+1 +τ i,k+1 +n i,k+1

[0022]

[0023] Among them, θ k is the phase difference offset of intersection k, t k is the travel time between adjacent intersections k to k+1, n i,k is the loop integer variable of the outgoing critical path i at intersection k, is the loop integer variable for the critical path i at intersection k, r i,k is the red light duration of the outbound critical path i at intersection k, is the red light duration of critical path i at intersection k, w i,k represents the green light duration before the green wave band at intersection k on critical path i, represents the green light duration of critical path i after the green wave band at intersection k, is the queue clearing time of the convoy heading towards critical path i at intersection k, τ i,k+1 is the queue clearing time of the team heading to critical path i at intersection k+1, Ω represents the set of all outgoing critical paths, represents the set of all critical paths; σ i represents the set of intersections corresponding to the critical path i, θ k+1 is the phase difference offset of intersection k+1, r i,k+1 is the red light duration of the outbound critical path i at intersection k+1, is the red light duration of critical path i at intersection k+1, w i,k+1 It indicates the green light duration before the green wave band at intersection k+1 on the critical path i. represents the green light duration after the green wave band at intersection k+1 on the critical path i, n i,k+1 is the loop integer variable of the outgoing key path i at the intersection k+1, is the loop integer variable for the critical path i at intersection k+1.

[0024] Furthermore, in the aforementioned step S3, the interference constraint is as follows:

[0025]

[0026] Among them, g i,k is the green light time of the outbound critical path i at intersection k, is the green light time of the incoming critical path i at the intersection k, Ω represents the set of all outgoing critical paths, represents the set of all critical paths; σ i represents the set of intersections corresponding to the critical path i, b i and are the green wave bandwidths of the outgoing and incoming critical path i respectively.

[0027] Furthermore, the speed fluctuation spatiotemporal constraints in the aforementioned step S3 are:

[0028]

[0029]

[0030] Among them, d k represents the distance between intersections k and k+1, z is the inverse of the cycle length, v is the preset green wave speed, ε is the speed fluctuation, g i,k+1 is the green light time of the outbound critical path i at intersection k+1.

[0031] 9. A multi-path trunk road signal coordinated control method considering speed fluctuation according to claim 6, characterized in that the minimum speed fluctuation constraint in step S3 is as follows:

[0032]

[0033] The maximum speed fluctuation constraint is as follows:

[0034]

[0035] V min is the minimum speed allowed by the road, V min It is the maximum speed allowed on the road.

[0036] Furthermore, the aforementioned multi-path trunk road signal coordinated control method considering speed fluctuation solves the signal control optimization model through a mixed integer linear programming solver.

[0037] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0038] 1. Consider speed fluctuation factors: Most existing trunk road signal coordinated control methods assume that vehicles travel at a fixed speed and ignore the speed fluctuation problem caused by the interweaving of multi-path flows. The present invention overcomes this defect by introducing spatiotemporal constraints on speed fluctuations, and can improve the utilization efficiency of green wave bands under complex traffic flow interference.

[0039] 2. Multi-path signal collaborative control: Most of the existing technologies only perform signal optimization for a single path, while 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.

[0040] 3. Improve control effect and robustness: By constructing speed fluctuation optimization constraints, the present invention improves the robustness of green band control in uncertain scenarios. Regardless of the lowest speed or the highest speed under speed fluctuation, vehicles can pass through multiple intersections smoothly under signal control, avoiding unnecessary parking and waiting time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of a multi-path trunk road signal cooperative control method considering speed fluctuations provided in accordance with an embodiment of the present invention;

[0042] Figure 2 It is an information diagram of each intersection, in which (a) is a schematic diagram of the intersection location information, and (b) is a schematic diagram of the distance between each intersection.

[0043] 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.

[0044] Figure 4 It is the signal timing diagram for each intersection.

[0045] Figure 5 It is a spatiotemporal diagram of the multipath signal cooperative control model considering speed fluctuation. DETAILED DESCRIPTION

[0046] In order to better understand the technical content of the present invention, specific embodiments are given and described as follows in conjunction with the accompanying drawings.

[0047] Various aspects of the invention are described herein with reference to the accompanying drawings, in which many illustrative embodiments are shown. The embodiments of the invention are not limited to those described in the accompanying drawings. It should be understood that the invention is implemented by any of the various concepts and embodiments described above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed in the invention are not limited to any implementation. In addition, some aspects disclosed in the invention may be used alone or in any appropriate combination with other aspects disclosed in the invention.

[0048] 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 traffic and turning traffic. Figure 3 As shown in Figure 2, since multiple key paths are intertwined on this main road, the vehicle speed fluctuates under the influence of path flows in different directions.

[0049] refer to Figure 1 , a multi-path trunk road signal coordinated control method considering speed fluctuations, comprising the following steps:

[0050] 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, (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 C, green light duration and red light duration of each intersection, such as Figure 4 shown.

[0051] The present invention proposes a multi-path trunk road signal coordinated control method considering speed fluctuations. First, in the implementation process, multiple key paths on the trunk road need to be determined according to the actual peak hour traffic flow. These traffic flow data can be obtained through the Automatic Vehicle Identification System (AVI) or other real-time monitoring facilities. By evaluating the peak hour flow of each path, the path with larger peak hour flow is selected as the key path, which is used as the optimization target in the subsequent optimization process. The key path in this example is as follows: Figure 5 .

[0052] Preferably, the acquired traffic flow data includes the traffic flow size f on each path i , 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

[0053] Table 1 Traffic flow of bus routes to be optimized

[0054]

[0055] S2. Based on the driving speed of each vehicle on each main path, calculate the average driving speed and speed fluctuation ε of the vehicles on each main path. Calculate the average speed v by obtaining the driving speed v of the vehicles on each path. i And calculate the average speed, the formula is as follows:

[0056]

[0057] Where N represents the number of vehicles on the path, v i is the speed of the i-th vehicle.

[0058] Calculate the speed fluctuation ε according to the vehicle's driving speed v i and average speed Calculate the velocity fluctuation of each path ε = 6.8 m / s, the specific formula is:

[0059]

[0060] S3. Construct 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:

[0061]

[0062] in, and are the weights of the critical path i of the outgoing and incoming paths, respectively, and b i and are the green wave bandwidths of the outgoing and incoming critical path i respectively.

[0063] 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.

[0064] according to Figure 5 In the space-time diagram shown, in order to ensure the continuity of the green wave band between adjacent intersections and avoid vehicles stopping at red lights within the green wave band, a loop integer constraint is added:

[0065] θ k +r i,k +w i,k +t k +n i,k =θ k+1 +r i,k+1 +w i,k+1 +τ i,k+1 +n i,k+1

[0066]

[0067] Among them, θ k is the phase difference offset of intersection k, t k is the travel time between adjacent intersections k to k+1, n i,k is the loop integer variable of the outgoing critical path i at intersection k, is the loop integer variable for the critical path i at intersection k, r i,k is the red light duration of the outbound critical path i at intersection k, is the red light duration of critical path i at intersection k, w i,k represents the green light duration before the green wave band at intersection k on critical path i, represents the green light duration of critical path i after the green wave band at intersection k, is the queue clearing time of the convoy heading towards critical path i at intersection k, τ i,k+1 is the queue clearing time of the team heading to critical path i at intersection k+1, Ω represents the set of all outgoing critical paths, represents the set of all critical paths; σ i represents the set of intersections corresponding to the critical path i, θ k+1 is the phase difference offset of intersection k+1, r i,k+1 is the red light duration of the outbound critical path i at intersection k+1, is the red light duration of critical path i at intersection k+1, wi,k+1 It indicates the green light duration before the green wave band at intersection k+1 on the critical path i. represents the green light duration after the green wave band at intersection k+1 on the critical path i, n i,k+1 is the loop integer variable of the outgoing key path i at the intersection k+1, is the loop integer variable for the critical path i at intersection k+1.

[0068] 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:

[0069]

[0070] Among them, g i,k is the green light time of the outbound critical path i at intersection k, is the green light time of the incoming critical path i at the intersection k, Ω represents the set of all outgoing critical paths, represents the set of all critical paths; σ i represents the set of intersections corresponding to the critical path i, b i and are the green wave bandwidths of the outgoing and incoming critical path i respectively.

[0071] To ensure that the convoy can still pass through the intersection smoothly when the speed is higher or lower than the design speed v, the following speed fluctuation spatiotemporal constraints are set:

[0072] When the convoy's speed is lower than the preset speed v, 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:

[0073]

[0074] When the convoy's speed is higher than the preset speed v, whether the leading vehicle can encounter a green light at the intersection determines whether the convoy can continue to pass. The specific constraints are:

[0075]

[0076] Among them, d k represents the distance between intersections k and k+1, z is the inverse of the cycle length, v is the preset green wave speed, ε is the speed fluctuation, g i,k+1 is the green light time of the outbound critical path i at intersection k+1.

[0077] 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:

[0078] Minimum speed fluctuation constraint: The vehicle's speed must not be lower than the allowed minimum speed V min , satisfying the conditions:

[0079]

[0080] Maximum speed fluctuation constraint: The vehicle's speed must not exceed the maximum allowed speed V max , satisfying the conditions:

[0081]

[0082] Finally, the present invention outputs the optimized signal control parameters of each intersection in the trunk line through the above-mentioned signal control optimization model, and obtains that the sum of the weighted bandwidths of multiple critical paths is 35 seconds, the green wave speed is 15m / s, and the weighted green wave bandwidth values ​​of each critical path are shown in Table 2, the weighted green wave bandwidth value table of critical paths.

[0083] Table 2

[0084]

[0085] The specific settings are based on actual construction requirements and are not specifically limited in this application.

[0086] The examples show that:

[0087] 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.

[0088] Compared with traditional signal control methods, the present invention significantly improves the overall operating performance of main roads, the traffic efficiency of intersections, and the travel performance of each key path.

[0089] Through the simulation study of 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.

[0090] Although the present invention has been described above with preferred embodiments, it is not intended to limit the present invention. A person skilled in the art of the present invention may make various modifications and improvements 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 definition of the 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. Based on the driving speed of each vehicle on each main path, calculate the average driving speed and speed fluctuation ε of the vehicles on each main path; 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 add loop integer constraints, interference constraints, speed fluctuation time and space 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.

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

3. The method for coordinated control of multi-path trunk road signals considering speed fluctuation according to claim 1, characterized in that: Step S2 includes the following sub-steps: S2.

1. Obtain the actual driving speed v of each vehicle i , calculate the average speed on the path As follows: Where N is the total number of vehicles; S2.2, according to the actual driving speed v i and average speed Calculate the speed fluctuation ε as follows:

4. The method for coordinated control of multi-path trunk road signals considering speed fluctuation according to claim 1, characterized in that: In step S3, the objective function is as follows: in, and are the weights of the critical path i of the outgoing and incoming paths, respectively, and b i and are the green wave bandwidths of the outgoing and incoming critical path i respectively.

5. The method for coordinated control of multi-path trunk road signals considering speed fluctuation according to claim 1, characterized in that: The weight of the path is calculated as follows: Among them, f i is the flow of critical path i, Ω represents the set of all critical paths, Represents the set of all critical paths.

6. The method for coordinated control of multi-path trunk road signals considering speed fluctuation according to claim 1, characterized in that: In step S3, the loop integer constraint, interference constraint, speed fluctuation time and space constraint, maximum speed fluctuation constraint, and minimum speed fluctuation constraint are specifically: The loop integer constraint is as follows: i k +r i,k +w i,k +t k +n i,k =θ k+1 +r i,k+1 +w i,k+1 +t i,k+1 +n i,k+1 Among them, θ k is the phase difference offset of intersection k, t k is the travel time between adjacent intersections k to k+1, n i,k is the loop integer variable of the outgoing critical path i at intersection k, is the loop integer variable for the critical path i at intersection k, r i,k is the red light duration of the outbound critical path i at intersection k, is the red light duration of critical path i at intersection k, w i,k represents the green light duration before the green wave band at intersection k on critical path i, represents the green light duration of critical path i after the green wave band at intersection k, is the queue clearing time of the convoy heading towards critical path i at intersection k, τ i,k+1 is the queue clearing time of the team heading to critical path i at intersection k+1, Ω represents the set of all outgoing critical paths, represents the set of all critical paths; σ i represents the set of intersections corresponding to the critical path i, θ k+1 is the phase difference offset of intersection k+1, r i,k+1 is the red light duration of the outbound critical path i at intersection k+1, is the red light duration of critical path i at intersection k+1, w i,k+1 It indicates the green light duration before the green wave band at intersection k+1 on the critical path i. represents the green light duration after the green wave band at intersection k+1 on the critical path i, n i,k+1 is the loop integer variable of the outgoing key path i at the intersection k+1, is the loop integer variable for the critical path i at intersection k+1.

7. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 6, characterized in that: In step S3, the interference constraint is as follows: Among them, g i,k is the green light time of the outbound critical path i at intersection k, is the green light time of the incoming critical path i at the intersection k, Ω represents the set of all outgoing critical paths, represents the set of all critical paths; σ i represents the set of intersections corresponding to the critical path i, b i and are the green wave bandwidths of the outgoing and incoming critical path i respectively.

8. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 6, characterized in that: Speed ​​fluctuation spatiotemporal constraints in step S3: Among them, d k represents the distance between intersections k and k+1, z is the inverse of the cycle length, v is the preset green wave speed, ε is the speed fluctuation, g i,k+1 is the green light time of the outbound critical path i at intersection k+1.

9. The method for coordinated control of multi-path trunk road signals considering speed fluctuations according to claim 6, characterized in that: The minimum speed fluctuation constraint in step S3 is as follows: The maximum speed fluctuation constraint is as follows: V min is the minimum speed allowed by the road, V min It is the maximum speed allowed on the road.

10. The method for coordinated control of multi-path trunk road signals considering speed fluctuation 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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