A city high-density road network mixed traffic flow cell transmission simulation prediction method

Abstract

The application discloses a kind of urban high-density road network mixed traffic flow cell transmission simulation prediction methods, comprising: with urban high-density road network area as modeling object, with road boundary end as traffic flow input position and output position, the road section between input position and output position includes urban expressway basic road section, access ramp and interchange, and urban non-expressway basic road section and intersection, the road section between input position and output position is divided into cell, and mixed mixed traffic flow cell transmission model is established to the cell, and the state of urban road network is simulated and predicted.The application comprehensively considers the traffic flow of urban expressway and urban non-expressway, effectively connects the cell of urban expressway with the cell of urban non-expressway, and designs and improves the cell division and modeling method of interweaving area and intersection, which is beneficial to the comprehensive study of traffic flow change in urban road network area and the traffic flow state simulation prediction for traffic flow control.

Description

Technical Field

[0001] This invention relates to the field of traffic simulation and traffic state prediction, and in particular to a method for simulating and predicting the cellular transmission of mixed traffic flow in urban high-density road networks. Background Technology

[0002] Urban expressways are a common type of transportation infrastructure in modern urban road systems. They are roads with central medians, grade-separated intersections (partially or entirely), and controlled access, allowing vehicles to travel at high speeds and maintain continuous flow. Due to their significant advantages, urban expressways attract more traffic flow, and during peak hours, traffic tends to concentrate on them. High-capacity surface roads in the road network are not fully utilized and remain largely low-density, thus failing to adequately alleviate the high-intensity traffic flow burden on expressways. Consequently, the traffic flow distribution in urban road networks dominated by expressways is extremely uneven, leading to traffic congestion.

[0003] Therefore, traffic flow management in urban road networks is necessary. Theoretically, through reasonable management methods, traffic flow can be evenly distributed across the entire road network, bringing the traffic efficiency of the urban road network to near its optimal state, while simultaneously increasing the utilization rate of unused high-capacity roads, thereby avoiding a sudden drop in traffic capacity and severe congestion.

[0004] Cellular transport models are an emerging traffic flow simulation method that represents the time and space evolution of a fluid dynamic system in a discrete form. They can capture discontinuous changes in network traffic flow, clearly describe the physical effects of queuing, and simulate traffic dynamics characteristics relatively well. However, cellular transport models are generally used for simulations of single-type road networks, such as urban expressway networks, highway networks, or urban non-expressway networks. There is a lack of research and practice in simulating mixed urban road networks that include both expressways and non-expressways, and they cannot effectively realize the exchange between expressway and non-expressway traffic flows, or the updating of traffic flow at intersections. Summary of the Invention

[0005] Purpose of the invention: To address the above problems, the purpose of this invention is to provide a cellular transmission simulation and prediction method for mixed traffic flow in urban high-density road networks. This method comprehensively considers the mixed road network composed of urban expressways and non-expressways, and based on the mixed cellular transmission model, studies the cell division and modeling methods for urban road segments, road weaving areas, and road intersections, and thereby realizes traffic flow simulation and prediction.

[0006] Technical Solution: The present invention provides a method for cellular transmission simulation and prediction of mixed traffic flow in urban high-density road networks, comprising: taking an urban high-density road network area as the modeling object, taking the boundary ends of roads within the road network area as the traffic flow input and output locations, the road segments between the input and output locations including basic road segments of urban expressways, ramps and interchanges, as well as basic road segments of urban non-expressways and intersections, dividing the road segments between the input and output locations into three types of cells: road segment cells, weaving cells, and intersection cells, establishing a mixed traffic flow cellular transmission model for the three types of cells, and simulating and predicting the state of the urban road network based on the mixed traffic flow cellular transmission model.

[0007] Furthermore, based on the traffic flow conservation theory, the hybrid road network cellular transport model includes the traffic flow density ρ within cell i. i Update formula and number of vehicles n i The time-varying update formulas are as follows:

[0008]

[0009] n i (k+1)=ρ i (k+1)*l i

[0010] In the formula, ρ i (k) represents the traffic flow density of cell i in the kth time step; This represents the traffic flow input in cell i at the k-th time step; The output of cell i in the k-th time step represents the traffic flow output; ΔT represents the time step value of cell update; l i Indicates the length of cell i; n i (k+1) represents the number of vehicles contained in cell i at the (k+1)th time step.

[0011] Furthermore, the interlacing cells are divided into split cells or merge cells.

[0012] Furthermore, the intersection cell is divided into left-turning cells, straight-line cells, or right-turning cells.

[0013] Furthermore, the road segment cells only contain basic road segment traffic flow. The traffic flow update of road segment cell i is determined by the maximum sending traffic flow of the upstream cell and the maximum receiving traffic flow of cell i, expressed as:

[0014]

[0015] In the formula, S i-1 (k) represents the maximum traffic flow that cell i-1 can send within the k-th time step, Ri (k) represents the maximum traffic flow that cell i can receive in the k-th time step, and the expressions are as follows:

[0016]

[0017]

[0018] In the formula, This represents the maximum traffic flow in cell i-1; This represents the free flow velocity of cell i-1 within the k-th time step; This represents the maximum traffic flow in cell i; This represents the crowding wave velocity of cell i under crowded conditions. This represents the blocking density of cell i.

[0019] Furthermore, the traffic flow update of the weaving cell is determined by the merging and diverging characteristics of the traffic flow in the main road cell and the traffic flow in the ramp cell. When the weaving cell is a merging cell, the traffic flow update expression of the weaving cell is:

[0020]

[0021] When the interleaving cell is a splitting cell, the traffic flow update expression for the interleaving cell is:

[0022]

[0023] In the formula, This represents the traffic flow entering cell i from cell i-1 within the k-th time step, expressed as:

[0024]

[0025] In the formula, r i (k) represents the traffic flow that merges with or separates from cell i via the entry / exit ramps in the k-th time step, when r i When (k) represents the merging traffic flow, the expression is:

[0026]

[0027] When r i When (k) represents the diverted traffic flow, the expression is:

[0028]

[0029] In the formula, The traffic flow output of cell i in the k-th time step is expressed as:

[0030]

[0031] In the formula, G i (k) represents the maximum traffic flow merging into cell i at the entrance ramp within the k-th time step; α i (k) represents the proportion of the traffic flow merging into cell i at the entrance ramp during the k-th time step to the total traffic flow in the merging zone; β i (k) represents the proportion of the traffic flow from cell i through the exit ramp to the total traffic flow in the diversion zone during the k-th time step.

[0032] Furthermore, the traffic flow update of the intersection cell is determined by the maximum outgoing traffic flow, the input flow of each lane in each direction, and the maximum receiving flow of the corresponding exit lane in each direction, expressed as:

[0033]

[0034] In the formula, R i，L (k), R i，M (k) and R i，R (k) represents the maximum received traffic flow for left turns, straight ahead, and right turns of other intersection exit cells when cell i is an intersection entrance cell in the kth time step; as well as These represent the left-turn, straight-ahead, and right-turn traffic flows in the input traffic flow of cell i within the k-th time step, respectively, and their expressions are as follows:

[0035]

[0036]

[0037]

[0038] In the formula, γ L (k), γ M (k) and γ R (k) represent the proportions of left-turn, straight-through, and right-turn traffic flows in the input traffic flow of cell i within the k-th time step, respectively;

[0039] When the intersection cell is a left-turn cell, the output traffic flow expression of the intersection cell is:

[0040]

[0041] When the intersection cell is a through-traffic cell, the output traffic flow expression of the intersection cell is:

[0042]

[0043] When the intersection cell is a right-turn cell, the output traffic flow expression of the intersection cell is:

[0044]

[0045] Beneficial Effects: Compared with existing technologies, the significant advantages of this invention are: This invention comprehensively considers the traffic flow of urban expressways and urban non-expressways, performs simulation modeling of urban high-density road network areas, effectively connects urban expressway cells with urban non-expressway cells, and designs and improves the cell division and modeling methods for weaving areas and intersections. This is beneficial for the comprehensive study of traffic flow changes in urban road network areas and the simulation prediction of traffic flow states for traffic flow control, providing theoretical support for solving traffic congestion in urban road network areas; establishing cell models for different cells allows for a more accurate study of the evolution of urban road network areas under different traffic flow states. Attached Figure Description

[0046] Figure 1 This is a flowchart of the present invention;

[0047] Figure 2 Example diagram of a partial cell transmission model of a road network;

[0048] Figure 3 Example diagram of cell division for urban intersections. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments.

[0050] The flowchart of the cellular transmission simulation and prediction method for mixed traffic flow in urban high-density road networks described in this embodiment is as follows: Figure 1 As shown, the prediction method includes: taking a high-density urban road network area as the modeling object, taking the boundary of the road within the road network area as the traffic flow input and output locations, and the road segments between the input and output locations including basic urban expressway segments, ramps and interchanges, as well as basic urban non-expressway segments and intersections. The road segments between the input and output locations are divided into three types of cells: road segment cells, weaving cells, and intersection cells. A hybrid traffic flow cell transmission model is established for the three types of cells, and the urban road network status is simulated and predicted based on the hybrid traffic flow cell transmission model.

[0051] In this embodiment, the road network of Kazimen Street in Nanjing is used as the target road network for modeling, such as... Figure 2As shown, the network includes two horizontally arranged basic sections of urban expressways and urban non-expressways. The top section represents the expressway built on an elevated structure, and the bottom section represents the non-expressway. The expressways and non-expressways are connected by weaving cells. The leftmost position is the traffic flow input position, and the rightmost position is the traffic flow output position. The input position is the input cell, and the output position is the output cell. The arrows indicate the direction of traffic flow. Expressway network cells can be divided into the following two categories: (1) segment cells that do not contain weaving zones; (2) weaving cells where the mainline traffic flow intersects with merging or outgoing traffic flows. Weaving cells are further divided into merging cells or diverging cells depending on whether they have entrance or exit ramps.

[0052] like Figure 3 As shown, intersection cells are divided according to traffic flow direction. Intersection cells can be divided into three categories: (1) left-turn cells, i.e. Figure 3 (2) Linear cells, i.e. Figure 3 Cell 3-M; (3) Right-turned cell, i.e. Figure 3 Cell 3-R is the merging cell for left-turn traffic from cell 0. Cell 1-L is the merging cell for both through and right-turn traffic from cell 0. Since the diverted cells cannot be directly diverted again, they need to be connected by transition cells. Therefore, cells 2-L and 2-MR are the transition cells for cells 1-L and 1-MR, respectively. Cell 3-M is the merging cell for through traffic from cell 2-MR, and cell 3-R is the merging cell for right-turn traffic from cell 2-MR. Cell 3-L receives the merging traffic from cell 2-L. Figure 3 The middle cells 3-L, 3-M, and 3-R constitute the divided intersection cells. Figure 3 Cell 1-L is the merging cell for left-turn traffic from cell 0, and cell 1-MR is the merging cell for both through and right-turn traffic from cell 0. Since the diverted cells cannot be directly diverted again, they need to be connected by transition cells. Therefore, cells 2-L and 2-MR are the transition cells for cells 1-L and 1-MR, respectively. Cell 3-M is the merging cell for through traffic from cell 2-MR, and cell 3-R is the merging cell for right-turn traffic from cell 2-MR. Cell 3-L receives the merging traffic from cell 2-L. Figure 3 The middle cells 3-L, 3-M, and 3-R constitute the divided intersection cells.

[0053] Weaving cells are divided into diverging cells or merging cells. A single weaving cell cannot simultaneously possess both diverging and merging attributes. Intersection cells are divided into left-turn cells, straight-ahead cells, or right-turn cells. A single intersection cell cannot be divided into left-turn, straight-ahead, and right-turn cells simultaneously; they require connection through road segment cells.

[0054] According to the traffic flow conservation theory, the hybrid road network cellular transport model includes the traffic flow density ρ within cell i. i Update formula and number of vehicles n i The time-varying update formulas are as follows:

[0055]

[0056] n i (k+1)=ρ i (k+1)*l i

[0057] In the formula, ρ i (k) represents the traffic flow density of cell i in the kth time step; This represents the traffic flow input in cell i at the k-th time step; The output of cell i in the k-th time step represents the traffic flow output; ΔT represents the time step value of cell update; l i Indicates the length of cell i; n i (k+1) represents the number of vehicles contained in cell i at the (k+1)th time step.

[0058] The above-mentioned road segment cells only contain basic road segment traffic flow, and there is no weaving or turning behavior. The traffic flow update of road segment cell i is determined by the maximum sending traffic flow of the upstream cell and the maximum receiving traffic flow of cell i, expressed as:

[0059]

[0060] In the formula, S i-1 (k) represents the maximum traffic flow that cell i-1 can send within the k-th time step, R i (k) represents the maximum traffic flow that cell i can receive in the k-th time step, and the expressions are as follows:

[0061]

[0062]

[0063] In the formula, This represents the maximum traffic flow in cell i-1; This represents the free flow velocity of cell i-1 within the k-th time step; This represents the maximum traffic flow in cell i; This represents the crowding wave velocity of cell i under crowded conditions. This represents the blocking density of cell i.

[0064] From the traffic flow update method of the above road segment cells, it can be seen that the flow of cell i is limited by two factors: the maximum output flow value of the previous cell i-1 and the maximum received flow value of cell i. The input flow of cell i... It represents the actual free flow output of cell i-1, but is affected by the maximum traffic flow of cell i-1, the maximum traffic flow of cell i, and the congestion wave traffic flow under congestion conditions.

[0065] For merging cells within weaving cells, there are two types of traffic flows: merging traffic and mainline traffic, which intersect in the merging zone. Therefore, the merging zone is constrained by these two traffic flows: firstly, cell i can receive all the merging traffic flow and the mainline traffic flow from cell i-1; secondly, the maximum traffic flow that cell i can receive is less than the merging traffic flow and the mainline traffic flow from cell i-1. The traffic flow update for weaving cells is determined by the merging and diverging characteristics of the mainline and ramp traffic flows. When the weaving cell is a merging cell, the traffic flow update expression for the weaving cell is:

[0066]

[0067] For a branching cell within an interleaving cell, the cell contains two traffic flows: outbound traffic and mainline traffic, and these two traffic flows intersect in the branching zone. When an interleaving cell is a branching cell, the traffic flow update expression for the interleaving cell is:

[0068]

[0069] In the formula, This represents the traffic flow entering cell i from cell i-1 within the k-th time step, expressed as:

[0070]

[0071] In the formula, r i (k) represents the traffic flow that merges with or separates from cell i via the entry / exit ramps in the k-th time step, when r i When (k) represents the merging traffic flow, the expression is:

[0072]

[0073] When r i When (k) represents the diverted traffic flow, the expression is:

[0074]

[0075] In the formula, The traffic flow output of cell i in the k-th time step is expressed as:

[0076]

[0077] In the formula, G i (k) represents the maximum traffic flow merging into cell i at the entrance ramp within the k-th time step; α i (k) represents the proportion of the traffic flow merging into cell i at the entrance ramp during the k-th time step to the total traffic flow in the merging zone; β i (k) represents the proportion of the traffic flow from cell i through the exit ramp to the total traffic flow in the diversion zone during the k-th time step.

[0078] The criterion for determining whether a merging cell can receive traffic flow is whether cell i can receive the maximum output traffic flow of cell i-1 and the merging traffic flow from the entrance ramp, i.e., R. i Is (k) greater than S? i-1 (k) and G i The sum of (k). If R i (k)≥S i-1 (k)+G i (k), then r represents the maximum output traffic flow of cell i-1. i (k) represents the maximum traffic flow merging into cell i at the entrance ramp.

[0079] For intersection cells, which separate left-turning, straight-through, and right-turning vehicles, it's necessary to divide the intersection approach lanes in different directions into multiple cells to connect downstream cells in different directions. The traffic flow update for an intersection cell is determined by the maximum outgoing traffic flow, the input flow of each lane in each direction, and the maximum receiving flow of the corresponding exit lane in each direction, expressed as:

[0080]

[0081] In the formula, R i，L (k), R i，M (k) and R i，R (k) represents the maximum received traffic flow for left turns, straight ahead, and right turns of other intersection exit cells when cell i is an intersection entrance cell in the kth time step; as well as These represent the left-turn, straight-ahead, and right-turn traffic flows in the input traffic flow of cell i within the k-th time step, respectively, and their expressions are as follows:

[0082]

[0083]

[0084]

[0085] In the formula, γ L (k), γ M (k) and γ R (k) represent the proportions of left-turn, straight-through, and right-turn traffic flows in the input traffic flow of cell i within the k-th time step, respectively;

[0086] When the intersection cell is a left-turn cell, the output traffic flow expression of the intersection cell is:

[0087]

[0088] When the intersection cell is a through-traffic cell, the output traffic flow expression of the intersection cell is:

[0089]

[0090] When the intersection cell is a right-turn cell, the output traffic flow expression of the intersection cell is:

[0091]

[0092] When the intersection cell in this embodiment is a signalized intersection, signal control needs to be considered, that is, the signal timing scheme needs to be incorporated into the model. Specifically: when the time step is a green light, the corresponding intersection cell is open, allowing traffic flow to be input or output; when the time step is a red light, the corresponding intersection cell is closed, allowing traffic flow to be input but not output. After the intersection cells are divided according to traffic flow direction, the output traffic flow of the intersection cell is limited by the maximum received traffic flow of the intersection exit cell, the maximum output traffic flow of the intersection cell, and the input traffic flow proportional to the direction input to the intersection cell.

[0093] This method comprehensively considers both urban expressway and non-expressway networks, dividing the urban road network area into cells. Based on the mature cellular transmission model, it designs and improves a modeling method for a hybrid cellular transmission model for urban road networks, and uses the constructed model to simulate and predict mixed traffic flow in high-density urban road networks. This method is beneficial for studying the evolution of traffic flow states in urban road network areas, realizing the connection between expressways and non-expressways, and providing a theoretical basis for the development of traffic control technologies for urban road network areas.

Claims

1. A method for cellular transmission simulation and prediction of mixed traffic flow in urban high-density road networks, characterized in that, include: Using urban high-density road network areas as the modeling object, the boundary ends of roads within the road network area are taken as traffic flow input and output locations. The road segments between the input and output locations include basic road segments of urban expressways, ramps and interchanges, as well as basic road segments and intersections of urban non-expressways. The road segments between the input and output locations are divided into three types of cells: road segment cells, weaving cells, and intersection cells. A hybrid traffic flow cell transmission model is established for the three types of cells. The urban road network status is simulated and predicted based on the hybrid traffic flow cell transmission model. The interlacing cells are divided into branching cells or merging cells; the intersection cells are divided into left-turning cells, straight-line cells, or right-turning cells; The traffic flow update of the weaving cell is determined by the merging and diverging characteristics of the traffic flow in the main road cell and the traffic flow in the ramp cell. When the weaving cell is a merging cell, the traffic flow update expression of the weaving cell is: ； When the interleaving cell is a splitting cell, the traffic flow update expression for the interleaving cell is: ； In the formula, Indicates the first Within a time step, the cells Entering the cell Traffic flow, expressed as: ； In the formula, Indicates the first Within a time step, passing through the entrance / exit ramps and cells When traffic flows merge or separate, When it is the merging traffic flow, the expression is: ； when When diverting traffic flow, the expression is: ； In the formula, Represents a cell In the The traffic flow output within a time step is expressed as follows: ； In the formula, Indicates the first Within a time step, cells converge at the entrance ramp. Maximum traffic flow; Indicates the first Within a time step, cells converge at the entrance ramp. The proportion of traffic flow in the merging zone to the total traffic flow; Indicates the first Cells within a time step The proportion of traffic flow merging through the exit ramps to the total traffic flow in the diversion area; The traffic flow update of the intersection cell is determined by the maximum outgoing traffic flow, the input flow of each lane in each direction, and the maximum receiving flow of the corresponding exit lane in each direction, expressed as: ； In the formula, , as well as They represent the first time. Within a time step, cells When acting as an intersection entrance cell, the maximum traffic flow received by other intersection exit cells for left turns, straight-through traffic, and right turns; , as well as They represent the first time. Cells within a time step Input the left-turn, straight-ahead, and right-turn traffic flows, with the following expressions: ； ； ； In the formula, , as well as They represent the first time. Cells within a time step The proportion of left-turn, straight-through, and right-turn traffic flow in the total input traffic flow; When the intersection cell is a left-turn cell, the output traffic flow expression of the intersection cell is: ； When the intersection cell is a through-traffic cell, the output traffic flow expression of the intersection cell is: ； When the intersection cell is a right-turn cell, the output traffic flow expression of the intersection cell is: 。 2. The cell transport simulation prediction method according to claim 1, characterized in that, According to the traffic flow conservation theory, the mixed traffic flow cellular transport model includes cells. Traffic flow density within Update formula and number of vehicles The time-varying update formulas are as follows: ； ； In the formula, Represents a cell In the Traffic flow density within a time step; Represents a cell In the Traffic flow input within a time step; Represents a cell In the Traffic flow output within a time step; This represents the time step value for cell updates; Represents a cell Length; Represents a cell In the The number of vehicles included within a time step.

3. The cell transport simulation prediction method according to claim 2, characterized in that, The road segment cells only contain basic road segment traffic flow. Traffic flow updates are determined by the maximum sent traffic flow of the upstream cell and the cell's maximum sent traffic flow. The maximum received bandwidth is determined by the following expression: ； In the formula, Represents a cell In the The maximum traffic flow that can be sent within a time step. Represents a cell In the The maximum traffic flow that can be received within each time step is expressed as follows: ； ； In the formula, Represents a cell Maximum traffic flow; Represents a cell In the Free flow velocity within a time step; Represents a cell Maximum traffic flow; Represents a cell in a crowded state The speed of the crowded wave; Represents a cell The blocking density.

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