Urban traffic bottleneck area flexible boundary robust control method and device

Abstract

The application discloses a kind of urban traffic bottleneck area flexible boundary robust control method and equipment, belong to intelligent transportation technical field, for solving the technical problem that the interference rejection capability of urban traffic bottleneck area boundary control method of static boundary constraint is poor, robustness is insufficient.Method includes: real-time acquisition urban traffic bottleneck area's dynamic static traffic information;According to dynamic static traffic information, determine the comprehensive traffic correlation degree of each boundary section;According to the comprehensive traffic correlation degree of each boundary section, determine the all dynamic threshold control intersections of urban traffic bottleneck area;The connection of all dynamic threshold control intersections is dynamic control boundary;Through MFD model, estimate the best vehicle accumulation in dynamic control boundary range, and determine the traffic control distribution of each boundary section;According to traffic control distribution, calculate the traffic signal lamp duration of each dynamic threshold control intersection, obtain bottleneck area traffic signal flexible boundary control scheme.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation technology, and in particular to a method and device for robust control of flexible boundaries in urban traffic bottleneck areas. Background Technology

[0002] With socio-economic development and the increase in motor vehicle ownership, urban traffic is characterized by high spatial and temporal concentration and high frequency, leading to frequent regional traffic congestion and intersections prone to overflow or blockage. However, conventional traffic control strategies, technologies, and methods are insufficient to effectively alleviate regional traffic congestion. Therefore, under the background of high-intensity travel, effective traffic management strategies and methods for addressing urban traffic bottlenecks are a current research focus in the field of intelligent transportation.

[0003] Regional boundary control can effectively solve the problem of urban regional traffic congestion. Many researchers have proposed different solutions, such as dividing the control area of ​​saturated intersection groups into congestion areas and transition areas, obtaining the MFD of the control area, and using a feedforward feedback iterative learning controller to achieve two-layer boundary control of the congestion area and the transition area; another is a two-layer boundary control method for urban congested road networks, where the first layer is the total volume control of the regional road network boundary, and the second layer is the optimization of the total control volume allocation considering queuing overflow and road network operation efficiency, thereby improving the road network operation efficiency and solving the queuing overflow problem caused by control; and yet another is to construct vehicle balance equations by analyzing the impact of disturbance factors on the performance of control in actual traffic system operation, so as to achieve road network boundary control under different degrees of disturbance.

[0004] The above-mentioned schemes all involve boundary control methods for urban traffic bottleneck areas. However, these studies all use static boundaries to achieve traffic diversion, without fully considering the differences in road conditions and the dynamic changes in traffic on the threshold boundary road sections. This results in problems such as poor anti-interference ability and insufficient robustness of the traffic system in the bottleneck area controlled by the boundary. Summary of the Invention

[0005] This application provides a robust control method and device for elastic boundaries in urban traffic bottleneck areas, which addresses the following technical problem: boundary control methods for urban traffic bottleneck areas constrained by static boundaries have poor anti-interference capabilities and insufficient robustness.

[0006] The embodiments of this application adopt the following technical solutions:

[0007] On one hand, this application provides a robust control method for flexible boundaries in urban traffic bottleneck areas. The method includes: acquiring dynamic and static traffic information of urban traffic bottleneck areas in real time; wherein, the urban traffic bottleneck area includes a central bottleneck area, several boundary intersections, several boundary road segments, and several upstream intersections; determining the comprehensive traffic correlation of each boundary road segment based on the dynamic and static traffic information; determining all dynamic threshold control intersections in the urban traffic bottleneck area based on the comprehensive traffic correlation of each boundary road segment; the line connecting all dynamic threshold control intersections is the dynamic control boundary; estimating the optimal vehicle accumulation within the dynamic control boundary range using an MFD model, and determining the traffic control allocation for each boundary road segment based on the optimal vehicle accumulation; calculating the traffic light duration for each dynamic threshold control intersection based on the traffic control allocation, thereby obtaining a flexible boundary control scheme for traffic signals in the bottleneck area.

[0008] In one feasible implementation, the dynamic and static traffic information includes road network data, signal control data, and traffic operation data. Based on the dynamic and static traffic information, the comprehensive traffic correlation of the boundary road segment is determined, specifically including: determining, based on the dynamic and static traffic information, the spatial obstruction-type traffic correlation index and the temporal obstruction-type traffic correlation index for each boundary road segment within the current time interval; normalizing the spatial obstruction-type traffic correlation index and the temporal obstruction-type traffic correlation index respectively, and determining the larger value after normalization as the comprehensive traffic correlation of the corresponding boundary road segment within the current time interval.

[0009] In one feasible implementation, based on the dynamic and static traffic information, the spatial obstruction-type traffic correlation index and the temporal obstruction-type traffic correlation index for each boundary road segment within the current time interval are determined. Specifically, this includes: acquiring road network data and traffic operation data from the dynamic and static traffic information; wherein the road network data includes at least road segment length, number of lanes, vehicle distribution, and cross-sectional shape, and the traffic operation data includes at least road segment flow rate, traffic occupancy rate, traffic congestion density, and traffic volume in each direction at intersections; based on... Calculate the spatial obstruction-type traffic correlation index of boundary road segment m within the current time interval t. Where i represents the first upstream intersection outside the boundary road segment m; j represents the boundary intersection; This represents the input traffic volume of the boundary road segment m from direction i to j within the current time interval t. This represents the amount of traffic congested on the boundary road segment m from direction i to j within the previous time interval (t-1). This represents the output traffic volume of boundary road segment m from direction i to j within the current time interval t. L represents the number of lanes in the boundary segment m from direction i to j; m K is the length of the boundary segment m; jam Let m be the traffic congestion density of the boundary road segment; according to Calculate the time-delay traffic correlation index of boundary road segment m within the current time interval t. Among them, o m,i→j (t) represents the average traffic occupancy rate of boundary road segment m from i to j within the current time interval t; This represents the actual travel time of boundary segment m from direction i to j within the current time interval t. Let m be the free-flow travel time of the boundary segment m from i to j.

[0010] In one feasible implementation, all dynamically threshold-controlled intersections in the urban traffic bottleneck area are determined based on the comprehensive traffic connectivity, specifically including: determining the traffic state of each boundary road segment based on the comprehensive traffic connectivity of each boundary road segment; wherein the traffic state includes a stable domain, an extensible domain, and an unstable domain; if the boundary road segment is in a stable domain, the boundary intersection inside the boundary road segment is determined as a single-layer dynamically threshold-controlled intersection; if the boundary road segment is in an extensible domain, the comprehensive traffic connectivity of the road segment between the second upstream intersection outside the boundary road segment and the boundary intersection is calculated; if the comprehensive traffic connectivity is less than a second preset threshold, the intersections on both sides of the boundary road segment are determined as double-layer dynamically threshold-controlled intersections; if the comprehensive traffic connectivity is greater than or equal to the second preset threshold, the intersections on both sides of the boundary road segment are determined as double-layer dynamically threshold-controlled intersections. All intersections are designated as statically controlled intersections. If the boundary road segment is in an unstable region, the comprehensive traffic correlation degree of the road segment between the second upstream intersection and the first upstream intersection is calculated, and the traffic state of the road segment is determined. If the road segment is in a stable region, the upstream intersection inside the road segment is directly designated as a single-layer dynamic threshold controlled intersection. If the road segment is in an extensible region, the comprehensive traffic correlation degree of the road segment between the third upstream intersection and the first upstream intersection is calculated. If the comprehensive traffic correlation degree is less than a second preset threshold, the intersections on both sides of the road segment are designated as double-layer dynamic threshold controlled intersections. If the comprehensive traffic correlation degree is greater than or equal to the second preset threshold, the intersections on both sides of the road segment are designated as statically controlled intersections. If the road segment is in an unstable region, the boundary intersection and all corresponding upstream intersections are designated as statically controlled intersections.

[0011] In one feasible implementation, the traffic state of each boundary road segment is determined based on the comprehensive traffic correlation degree of each boundary road segment. Specifically, this includes: if the comprehensive traffic correlation degree is less than or equal to a first preset threshold, it indicates that the spatiotemporal obstruction of the incoming traffic flow in the corresponding boundary road segment is small, and the traffic state of the boundary road segment is determined as a stable domain; if the comprehensive traffic correlation degree is greater than the first preset threshold and less than a second preset threshold, it indicates that the spatiotemporal obstruction of the incoming traffic flow in the corresponding boundary road segment is moderate, and the traffic state of the boundary road segment is determined as an extensible domain; if the comprehensive traffic correlation degree is greater than or equal to the second preset threshold, it indicates that the spatiotemporal obstruction of the incoming traffic flow in the corresponding boundary road segment is large, and the traffic state of the boundary road segment is determined as an unstable domain.

[0012] In one feasible implementation, the optimal vehicle accumulation within the dynamic control boundary range is estimated using an MFD model, specifically including: based on... Calculate the real-time cumulative vehicle volume N(t) within the dynamic control boundary range; where Z is the set of road segments within the dynamic control boundary range, and z is the z-th road segment in the set of road segments; L z n is the length of road segment z; z,lane The number of lanes in road segment z; o z (t) represents the average traffic occupancy rate of road segment z within the current time interval t; λ represents the average vehicle length; the number of vehicles that leave the dynamic control boundary within the current time interval t is counted and denoted as G(t); based on the sample data of N(t) and G(t), the MFD model of the urban traffic bottleneck area is constructed: G(t) = aN 3 (t)+bN 2 (t)+cN(t); where a, b, and c are model parameters; plot the MFD curve corresponding to the MFD model, and determine the ordinate value corresponding to the highest point of the MFD curve as the optimal vehicle accumulation.

[0013] In one feasible implementation, the traffic control allocation for each boundary road segment is determined based on the optimal vehicle accumulation amount, specifically including: according to Q(t+1)=N(t)-N cri Calculate the total traffic volume Q(t+1) within the dynamic control boundary range in the next time interval (t+1); where N(t) is the real-time cumulative vehicle volume within the dynamic control boundary range; N cri The optimal vehicle accumulation within the dynamic control boundary range; if the boundary segment m contains a dynamically threshold controlled intersection, then according to Calculate the traffic control allocation for boundary road segment m in the next time interval (t+1); where,

[0014] R represents the set of dynamically threshold-controlled intersections in the urban traffic bottleneck area within the current time interval t, including a single-level dynamically threshold-controlled intersection set J1(t) and a double-level dynamically threshold-controlled intersection set J2(t); m (t) represents the comprehensive traffic connectivity of the boundary segment m containing the dynamically threshold-controlled intersection within the current time interval t; n m,lane n is the number of entering lanes in boundary road segment m; w is any dynamically threshold controlled intersection in the set of dynamically threshold controlled intersections; n w,lane To dynamically control the number of lanes in the approach direction segment of intersection w; R w (t) represents the comprehensive traffic connectivity of the approach road segment at the intersection w with dynamic threshold control.

[0015] In one feasible implementation, based on the traffic control allocation, the green light duration of the traffic signal at each dynamically threshold-controlled intersection is calculated to obtain a flexible boundary control scheme for the bottleneck area traffic signal. Specifically, this includes: acquiring signal control data from the dynamic and static traffic information; wherein the signal control data includes at least the signal control method, signal cycle duration, and green light duration; if the boundary segment m contains a single-layer dynamically threshold-controlled intersection, then according to... Calculate the green light duration adjustment value for the entering direction of the single-layer dynamic threshold control intersection in the boundary road segment m within the next time interval (t+1). Where, q m,control (t+1) represents the traffic control allocation for boundary road segment m, and n m,lane Let m be the number of entering lanes in boundary segment m, α be the saturation headway, T be the unit time interval length, and C0 be the signal cycle duration of a single-layer dynamic threshold control intersection; then according to Calculate the green light duration for the entering direction at a single-layer dynamic threshold controlled intersection in the boundary road segment m within the next time interval (t+1). This yields a flexible boundary control scheme for traffic signals in the bottleneck area of ​​a single-level dynamic intersection; among which, g represents the green light duration for the entering direction of the single-layer threshold boundary control intersection corresponding to the boundary road segment m within the current time interval t; min This is the minimum green light duration for a given phase; if the boundary segment m contains two dynamically threshold controlled intersections m1 and m2, then according to... Calculate the traffic signal phase difference at a dual-layer dynamic threshold control intersection Wherein, m1→m2 represents the road segment between the two-layer dynamic threshold control intersections m1 and m2, which is the direction of entering the central bottleneck area; This represents the length of the queue for vehicles entering the road segment between m1 and m2 within the current time interval t; v w The dissipation wave velocity of the queued vehicles; The length of the road segment between m1 and m2; The average speed of the road segment; according to Calculate the green wave bandwidth variation value of a dual-layer dynamic threshold control intersection. Among them, C m The signal cycle duration of the dual-layer dynamic threshold control intersection is defined as follows: the signal cycle duration of the two intersections in the dual-layer dynamic threshold control intersection is the same; based on the green wave bandwidth change value, the green light ratio of the direction entering the central bottleneck area of ​​the dual-layer dynamic threshold control intersection is adjusted, and the coordinated phase green light duration of the direction entering the dual-layer dynamic threshold control intersection is updated, thereby obtaining the flexible boundary control scheme for the bottleneck area traffic signal corresponding to the dual-layer dynamic intersection.

[0016] In one feasible implementation, before acquiring the dynamic and static traffic information of the urban traffic bottleneck area in real time, the method further includes: determining the traffic congestion area in the urban traffic system as the central bottleneck area based on the prior knowledge of traffic managers; determining a number of ring roads and a number of radial roads within a preset distance centered on the central bottleneck area, the intersections of the ring roads and the radial roads forming a network of intersections around the central bottleneck area; dividing each intersection on the same radial road into a boundary intersection and a number of corresponding upstream intersections according to their proximity to the central bottleneck area; wherein, the boundary intersection is the intersection closest to the central bottleneck area; determining the road segment between the boundary intersection and the adjacent upstream intersection as the boundary road segment; the boundary road segment, the bottleneck area, the boundary intersection, and the corresponding number of upstream intersections together constitute the urban traffic bottleneck area.

[0017] On the other hand, embodiments of this application also provide a robust control device for flexible boundaries in urban traffic bottleneck areas. The device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to execute a robust control method for flexible boundaries in urban traffic bottleneck areas according to any of the above embodiments.

[0018] This application provides a robust control method and device for flexible boundaries in urban traffic bottleneck areas. Starting from the differences in road conditions and the dynamic changes in traffic on the boundary road sections of urban traffic bottleneck areas, it analyzes the spatiotemporal density of traffic flow on the road sections, proposes spatial hindrance traffic correlation indices and temporal hindrance traffic correlation indices, and constructs a comprehensive traffic correlation calculation model for road sections based on the two factors of spatiotemporal hindrance. This provides an accurate and reliable quantitative basis for the classification of traffic states and optimization of signal timing on the boundary road sections of bottleneck areas.

[0019] Based on the traffic state classification results of regional boundary road segments, this application determines threshold boundary control intersections by region, forming dynamic control boundaries, and designs elastic boundaries including single-layer dynamic boundaries, double-layer dynamic boundaries, and static boundaries, thus designing a robust control scheme for elastic boundary signals in bottleneck areas. This scheme can not only actively alleviate internal traffic congestion in bottleneck areas, but also effectively avoid local traffic jams caused by boundary signal regulation on regional boundary road segments. Overall, the robust control method and equipment for elastic boundary signals in urban traffic bottleneck areas have good robustness and reliability, and can significantly improve the anti-interference capability of the traffic system in bottleneck areas. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0021] Figure 1 A flowchart illustrating a robust control method for elastic boundaries in urban traffic bottleneck areas, provided in this application embodiment;

[0022] Figure 2 A schematic diagram of the spatial distribution of urban traffic bottleneck areas is provided for an embodiment of this application;

[0023] Figure 3 This is a structural schematic diagram of a robust control device for elastic boundaries in urban traffic bottleneck areas, provided as an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0025] This application provides a robust control method for flexible boundaries in urban traffic bottleneck areas, such as... Figure 1 As shown, the robust control method for elastic boundaries in urban traffic bottleneck areas specifically includes steps S101-S106:

[0026] S101, Identify urban traffic bottleneck areas.

[0027] For cities that need to implement traffic bottleneck area signal control, it is necessary to first identify the urban traffic bottleneck areas, and then implement dynamic boundary control on the identified urban traffic bottleneck areas to alleviate traffic congestion.

[0028] The specific method for identifying urban traffic bottleneck areas is as follows: Based on the prior knowledge of traffic managers, the traffic congestion areas in the urban traffic system are identified as central bottleneck areas. Then, with the central bottleneck area as the center, several ring roads and several radial roads are determined within a preset distance. The intersections of the ring roads and radial roads form a network of intersections around the central bottleneck area. The preset distance can be flexibly set based on expert experience and is not specifically limited in this application.

[0029] Furthermore, intersections along the same radial road are divided into a boundary intersection and multiple upstream intersections based on their proximity to the central bottleneck area. The boundary intersection is the one closest to the central bottleneck area. The road segment between the boundary intersection and its adjacent upstream intersection is defined as the boundary road segment. Finally, the boundary road segment, the bottleneck area, the boundary intersection, and the multiple upstream intersections together constitute an urban traffic bottleneck area.

[0030] In one embodiment, Figure 2 A schematic diagram of the spatial distribution of urban traffic bottleneck areas is provided for an embodiment of this application, such as... Figure 2 As shown in the figure, the intersections on a radial road running along the middle of the right side of the central bottleneck area are categorized by their distance from the central bottleneck area as follows: boundary intersection j, upstream intersection i, upstream intersection h, and upstream intersection k. The road segment between boundary intersection j and the first upstream intersection i is a boundary segment m. Similarly, the road segments at the same location on other radial roads are also boundary segments. Figure 2 The example shown is just one road segment and does not represent that a city's traffic bottleneck area contains only one boundary road segment.

[0031] S102. Real-time acquisition of dynamic and static traffic information in urban traffic bottleneck areas.

[0032] Specifically, the dynamic and static traffic information of urban traffic bottleneck areas includes road network data, signal control data, and traffic operation data. Among them, road network data includes data such as road segment length, number of lanes, vehicle distribution, and cross-sectional shape; traffic operation data includes data such as road segment flow, traffic occupancy rate, traffic congestion density, and traffic volume in each direction at intersections; signal control data includes data such as signal control methods, signal cycle duration, and green light duration.

[0033] All of the above data can be obtained in urban transportation systems using existing methods, and this application will not elaborate on the specific acquisition methods.

[0034] S103. Determine the comprehensive traffic correlation of each boundary road segment based on dynamic and static traffic information.

[0035] Specifically, based on the acquired dynamic and static traffic information, the spatial obstruction traffic correlation index and the temporal obstruction traffic correlation index of each boundary road segment are determined within the current time interval. Then, the spatial obstruction traffic correlation index and the temporal obstruction traffic correlation index are normalized respectively, and the larger value after normalization is determined as the comprehensive traffic correlation of the corresponding boundary road segment within the current time interval.

[0036] As a possible implementation method, such as Figure 2 As shown, taking boundary road segment m as an example, based on dynamic and static traffic information, the spatial stagnation traffic correlation index and the temporal stagnation traffic correlation index of boundary road segment m within the current time interval are determined, specifically including:

[0037] Obtain road network data and traffic operation data from dynamic and static traffic information, and then apply the formula. Calculate the spatial obstruction-type traffic correlation index of boundary road segment m within the current time interval t. Where i represents the first upstream intersection outside the boundary road segment m; j represents the boundary intersection; This represents the input traffic volume of the boundary road segment m from direction i to j within the current time interval t. This represents the amount of traffic congested on the boundary road segment m from direction i to j within the previous time interval (t-1). This represents the output traffic volume of boundary road segment m from direction i to j within the current time interval t. L represents the number of lanes in the boundary segment m from direction i to j; m K is the length of the boundary segment m; jam Let m be the traffic congestion density of the boundary road segment.

[0038] Then according to the formula Calculate the time-delay traffic correlation index of boundary road segment m within the current time interval t. Among them, o m,i→j (t) represents the average traffic occupancy rate of boundary road segment m from i to j within the current time interval t; This represents the actual travel time of boundary segment m from direction i to j within the current time interval t. Let m be the free-flow travel time of the boundary segment m from i to j.

[0039] Furthermore, through right and perform normalization processing, and, through right Perform normalization; then according to The larger value after normalization is determined as the comprehensive traffic connectivity of boundary segment m within the current time interval t.

[0040] Using the above methods, the comprehensive traffic correlation of all boundary road segments in the current time interval can be calculated.

[0041] S104. Based on the comprehensive traffic correlation of each boundary road segment, determine all dynamically controlled intersections in the urban traffic bottleneck area, and the line connecting all dynamically controlled intersections is the dynamic control boundary.

[0042] Specifically, based on the calculated comprehensive traffic correlation degree of each boundary road segment, the traffic state of each boundary road segment is determined, including: if the comprehensive traffic correlation degree is less than or equal to a first preset threshold, it indicates that the spatiotemporal hindrance of the incoming traffic in the corresponding boundary road segment is small, and the traffic state of the boundary road segment is determined as a stable domain; if the comprehensive traffic correlation degree is greater than the first preset threshold and less than a second preset threshold, it indicates that the spatiotemporal hindrance of the incoming traffic in the corresponding boundary road segment is moderate, and the traffic state of the boundary road segment is determined as an extensible domain; if the comprehensive traffic correlation degree is greater than or equal to the second preset threshold, it indicates that the spatiotemporal hindrance of the incoming traffic in the corresponding boundary road segment is large, and the traffic state of the boundary road segment is determined as an unstable domain.

[0043] In one embodiment, if the comprehensive traffic correlation degree is less than or equal to 0.35, it indicates that the congestion level of this boundary road segment is low and the traffic state is in the stable domain; if the comprehensive traffic correlation degree is greater than 0.35 and less than 0.85, it indicates that the congestion level of this boundary road segment is moderate and the traffic state is in the extensible domain; if the comprehensive traffic correlation degree is greater than or equal to 0.85, it indicates that the congestion level of this boundary road segment is high and the traffic state is in the unstable domain.

[0044] Furthermore, after defining the traffic states of the boundary road segments, if the boundary road segment is a stable region, the boundary intersections inside the boundary road segment are directly designated as single-layer dynamic threshold controlled intersections. If the boundary road segment is an extensible region, the comprehensive traffic connectivity between the second upstream intersection outside the boundary road segment and the boundary intersection is calculated. If the comprehensive traffic connectivity is less than a second preset threshold, the intersections on both sides of the boundary road segment are designated as double-layer dynamic threshold controlled intersections; if the comprehensive traffic connectivity is greater than or equal to the second preset threshold, the intersections on both sides of the boundary road segment are designated as statically controlled intersections. If the boundary road segment is in an unstable region, the comprehensive traffic connectivity between the second upstream intersection and the first upstream intersection is calculated, and the traffic state of the segment is determined. If the segment is in a stable region, the upstream intersection inside the segment is directly designated as a single-layer dynamic threshold control intersection. If the segment is in an extensible region, the comprehensive traffic connectivity between the third upstream intersection and the first upstream intersection is calculated. If the comprehensive traffic connectivity is less than a second preset threshold, the intersections on both sides of the segment are designated as double-layer dynamic threshold control intersections. If the comprehensive traffic connectivity is greater than or equal to the second preset threshold, the intersections on both sides of the segment are designated as static control intersections. If the segment is in an unstable region, the boundary intersection and all corresponding upstream intersections are designated as static control intersections.

[0045] Furthermore, the line connecting all the identified dynamic threshold control intersections is the dynamic control boundary.

[0046] As a possible implementation method, such as Figure 2 As shown, if the boundary road segment m is a stable region, the boundary intersection j is directly selected as a single-layer threshold boundary control intersection (i.e., a single-layer dynamic threshold control intersection). At this time, the real-time integrated traffic correlation degree corresponding to the boundary road segment m is... The number of input lanes corresponding to the boundary segment m is the number of lanes in a single road segment, i.e.

[0047] If the boundary segment m is an extensible region, then according to the formula... Calculate the comprehensive traffic connectivity from upstream intersection h to boundary intersection j. If this comprehensive traffic connectivity is less than 0.85, then boundary intersection j and upstream intersection i are selected as dual-layer gradually changing threshold boundary control intersections (i.e., dual-layer dynamic threshold control intersections). In this case, the real-time comprehensive traffic connectivity corresponding to boundary segment m is... The number of input lanes corresponding to the boundary segment m is the average number of lanes along the path, i.e. If the overall traffic correlation is greater than or equal to 0.85, then the boundary intersection j and any of its upstream intersections will not be treated as threshold boundary controlled intersections, but will all be set as static controlled intersections.

[0048] If the boundary road segment m is an unstable region, then skip the boundary intersection j, and use the upstream intersection i as the initial point to calculate the comprehensive traffic connectivity of the road segment from the upstream intersection h to i, and classify the traffic state in the direction from road segment h to i. If the road segment is a stable region, then directly select the upstream intersection i as the single-layer threshold boundary control intersection. In this case, the real-time comprehensive traffic connectivity corresponding to the boundary road segment m is: The number of input lanes corresponding to the boundary segment m is the number of lanes in a single road segment, i.e. If the road segment is an extensible domain, the comprehensive traffic correlation degree from upstream intersection k to i is calculated. If the calculation result is less than 0.85, upstream intersection i and upstream intersection h are selected as double-layer gradually changing threshold boundary control intersections (i.e., double-layer dynamic threshold control intersections). If the calculation result is greater than or equal to 0.85, boundary intersection j and any of its upstream intersections are not used as threshold boundary control intersections, but are all set as static control intersections.

[0049] If the road segment from h to i is an unstable region, then the boundary intersection j and any of its upstream intersections will not be treated as threshold boundary control intersections, but will all be set as static control intersections.

[0050] As a feasible implementation method, the boundary connected to a single-layer dynamic threshold controlled intersection is a single-layer dynamic boundary, the boundary connected to a double-layer dynamic threshold controlled intersection is a double-layer dynamic boundary, and the boundary connected to a statically controlled intersection is a static boundary. The single-layer dynamic boundary, the double-layer dynamic boundary, and the static boundary together constitute the flexible boundary proposed in this application. The flexible boundary can change according to changes in real-time traffic data, thereby better adapting to changing traffic conditions.

[0051] S105. Using the MFD model, estimate the optimal vehicle accumulation within the dynamic control boundary range, and determine the traffic control allocation for each boundary segment based on the optimal vehicle accumulation.

[0052] Specifically, according to Calculate the real-time cumulative vehicle volume N(t) within the dynamic control boundary; where Z is the set of road segments within the dynamic control boundary, and z is the z-th road segment in the set; L z n is the length of road segment z; z,lane The number of lanes in road segment z; o z (t) represents the average traffic occupancy rate of road segment z within the current time interval t; λ represents the average vehicle length.

[0053] Furthermore, the number of vehicles that leave the dynamic control boundary within the current time interval t is counted and denoted as G(t); then, based on the sample data of N(t) and G(t), an MFD model of the urban traffic bottleneck area is constructed: G(t) = aN 3 (t)+bN 2(t)+cN(t); where a, b, and c are model parameters. Plot the MFD curve corresponding to the MFD model, and determine the ordinate value corresponding to the highest point of the MFD curve as the optimal vehicle accumulation within the dynamic control boundary.

[0054] Furthermore, according to Q(t+1)=N(t)-N cri Calculate the total traffic control volume Q(t+1) within the dynamic control boundary range in the next time interval (t+1).

[0055] As a feasible implementation method, when Q(t+1)≤0, the traffic signal control scheme of the corresponding urban traffic bottleneck area remains unchanged, and when Q(t+1)>0, the traffic signal elastic boundary control scheme of the urban traffic bottleneck area is triggered again.

[0056] Furthermore, after calculating the total traffic control volume within the dynamic control boundary, the traffic control allocation volume for all boundary road segments containing dynamically threshold-controlled intersections in the next time interval is calculated. This allocates the total traffic control volume to the boundary road segments containing dynamically threshold-controlled intersections. The specific calculation method is as follows: traverse the boundary road segments; if any traversed boundary road segment m contains a dynamically threshold-controlled intersection, then according to the formula... Calculate the traffic control allocation for boundary segment m in the next time interval (t+1). After traversing all the boundary segments including dynamic threshold control intersections, the traffic control allocation for the next time interval can be obtained.

[0057] in, R represents the set of dynamically threshold-controlled intersections in the urban traffic bottleneck area within the current time interval t, including a single-level dynamically threshold-controlled intersection set J1(t) and a double-level dynamically threshold-controlled intersection set J2(t); m (t) represents the comprehensive traffic connectivity of the boundary segment m containing the dynamically threshold-controlled intersection within the current time interval t; n m,lane n is the number of entering lanes in boundary segment m; w is any dynamically threshold controlled intersection in the set of dynamically threshold controlled intersections; n w,lane To dynamically control the number of lanes in the approach direction segment of intersection w; R w (t) represents the comprehensive traffic connectivity of the approach road segment at the intersection w with dynamic threshold control.

[0058] S106. Based on the traffic control allocation, calculate the green light duration of the traffic signal at each dynamic threshold control intersection to obtain the flexible boundary control scheme for traffic signals in the bottleneck area.

[0059] Specifically, after calculating the traffic control allocation for each boundary road segment, signal control data is obtained from dynamic and static traffic information.

[0060] If the boundary segment m contains a single-level dynamically threshold controlled intersection, then according to Calculate the green light duration adjustment value for the entering direction of the single-layer dynamic threshold control intersection in the boundary road segment m within the next time interval (t+1). Where, q m,control (t+1) represents the traffic control allocation for boundary road segment m, and n m,lane Let m be the number of lanes entering the boundary segment, α be the saturation headway, T be the unit time interval length, and C0 be the signal cycle duration of a single-layer dynamic threshold control intersection.

[0061] Furthermore, based on Calculate the green light duration for the entering direction at a single-layer dynamic threshold controlled intersection in the boundary road segment m within the next time interval (t+1). This yields a flexible boundary control scheme for traffic signals in the bottleneck area of ​​a single-level dynamic intersection; among which, g represents the green light duration for the entering direction of the single-layer threshold boundary control intersection corresponding to the boundary road segment m within the current time interval t; min This is the minimum duration of the green light for a given phase.

[0062] As a feasible implementation method, after calculating the green light duration for the entering direction at a single-layer dynamic threshold controlled intersection, if the total traffic control volume Q(t+1) within the dynamic control boundary range is greater than 0, then all single-layer dynamic threshold controlled intersections will implement the bottleneck area traffic signal elastic boundary control scheme corresponding to the single-layer dynamic intersection: the green light duration will be adjusted to the calculated green light duration.

[0063] Furthermore, if the boundary segment m contains two-level dynamically threshold controlled intersections, denoted as m1 and m2 respectively, then according to... Calculate the traffic signal phase difference at the dual-layer dynamic threshold controlled intersection in the boundary road segment m within the next time interval (t+1). Where m1→m2 represents the road segment between m1 and m2 at the dual-layer dynamic threshold control intersection, heading towards the central bottleneck area; This represents the length of the queue for vehicles entering the road segment between m1 and m2 within the current time interval t; v w The dissipation wave velocity of the queued vehicles; The length of the road segment between m1 and m2; This represents the average speed across the road segment.

[0064] Furthermore, based on Calculate the green wave bandwidth variation value of a dual-layer dynamic threshold control intersection. Among them, C mThe signal cycle duration is the same for the two intersections in a dual-layer dynamic threshold control intersection.

[0065] It should be noted that in the formulas involved in this application, 'm' refers to the label of any boundary segment, not the label of a specific boundary segment. Figure 2 The location of the middle boundary segment m is merely an example and does not represent a fixed location. All formulas proposed in this application are also general formulas, not just applicable to a specific boundary segment.

[0066] Furthermore, based on the change in green wave bandwidth, the green light ratio of the direction entering the central bottleneck area of ​​the dual-layer dynamic threshold control intersection is adjusted, and the green light duration of the coordinated phase of the direction entering the dual-layer dynamic threshold control intersection is updated, thereby obtaining the flexible boundary control scheme for traffic signals in the bottleneck area corresponding to the dual-layer dynamic intersection.

[0067] As a feasible implementation method, after calculating the coordinated phase green light duration for the entering direction of the dual-layer dynamic threshold control intersection, if the total traffic control volume Q(t+1) within the dynamic control boundary range is greater than 0, then all dual-layer dynamic threshold control intersections will implement the bottleneck area traffic signal elastic boundary control scheme corresponding to the dual-layer dynamic intersection: the two dynamic threshold control intersections in the dual-layer dynamic threshold control intersection will be set according to the calculated coordinated phase green light duration.

[0068] It should be noted that the method of adjusting the green signal ratio based on the change in filter bandwidth can be easily implemented using existing technologies and is not the focus of this application; therefore, it will not be described in detail here.

[0069] The solution provided in this application divides intersections in urban traffic bottleneck areas into dynamically controlled intersections and statically controlled intersections based on the comprehensive traffic correlation of road segments. This determines the dynamic control boundary. The optimal vehicle accumulation volume and real-time vehicle accumulation volume within the dynamic control boundary are then calculated, allowing the determination of the number of vehicles requiring control within the dynamic control boundary. These vehicles are then evenly distributed among the dynamically controlled intersections, resulting in the traffic control allocation for each intersection. This traffic control allocation for each intersection is then converted into a green light duration adjustment value, leading to a dynamic traffic signal adjustment scheme. This method alleviates traffic congestion in urban traffic bottleneck areas by evenly distributing the vehicles requiring control across multiple dynamically controlled intersections, minimizing vehicle travel time while easing traffic pressure. Furthermore, the determined dynamically controlled intersections and dynamic control boundaries change accordingly with real-time traffic conditions, automatically adjusting the control scheme based on real-time traffic conditions, thus improving the robustness of the solution.

[0070] In addition, embodiments of this application also provide a robust control device for flexible boundaries in urban traffic bottleneck areas, such as... Figure 3 As shown, the robust control device for flexible boundaries in urban traffic bottleneck areas specifically includes:

[0071] At least one processor; and a memory communicatively connected to the at least one processor; wherein,

[0072] The memory stores instructions that can be executed by at least one processor, so that at least one processor can perform the following:

[0073] Real-time acquisition of dynamic and static traffic information in urban traffic bottleneck areas; wherein, the urban traffic bottleneck areas include central bottleneck areas, several boundary intersections, several boundary road segments, and several upstream intersections;

[0074] Based on the dynamic and static traffic information, determine the comprehensive traffic correlation of each boundary road segment;

[0075] Based on the comprehensive traffic correlation of each boundary road segment, all dynamically controlled intersections in the urban traffic bottleneck area are determined; the line connecting all dynamically controlled intersections is the dynamic control boundary.

[0076] The optimal vehicle accumulation within the dynamic control boundary is estimated using the MFD model, and the traffic control allocation for each boundary segment is determined based on the optimal vehicle accumulation.

[0077] Based on the traffic control allocation, the duration of traffic lights at each dynamic threshold control intersection is calculated to obtain a flexible boundary control scheme for traffic signals in the bottleneck area.

[0078] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0079] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0080] The above description is merely an embodiment of this application and is not intended to limit this application. For those skilled in the art, various modifications and variations can be made to the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of this application should be included within the scope of the claims of this application.

Claims

1. A robust control method for elastic boundaries in urban traffic bottleneck areas, characterized in that, The method includes: Real-time acquisition of dynamic and static traffic information in urban traffic bottleneck areas; wherein, the urban traffic bottleneck areas include central bottleneck areas, several boundary intersections, several boundary road sections, and several upstream intersections; the dynamic and static traffic information includes road network data, signal control data, and traffic operation data; Based on the dynamic and static traffic information, the comprehensive traffic correlation of each boundary road segment is determined, specifically including: Based on the dynamic and static traffic information, determine the spatial obstruction traffic correlation index and the temporal obstruction traffic correlation index for each boundary road segment within the current time interval; normalize the spatial obstruction traffic correlation index and the temporal obstruction traffic correlation index respectively, and determine the larger value after normalization as the comprehensive traffic correlation of the corresponding boundary road segment within the current time interval. Based on the comprehensive traffic connectivity of each boundary road segment, all dynamically threshold-controlled intersections in the urban traffic bottleneck area are determined, specifically including: Based on the comprehensive traffic correlation of each boundary road segment, the traffic state of each boundary road segment is determined; wherein, the traffic state includes stable domain, extension domain, and unstable domain; When the boundary road segment is a stable region, the boundary intersection inside the boundary road segment is determined as a single-layer dynamic threshold control intersection; When the boundary road segment is an extensible domain, the comprehensive traffic connectivity degree of the road segment between the second upstream intersection outside the boundary road segment and the boundary intersection is calculated. If the comprehensive traffic connectivity degree is less than a second preset threshold, the intersections on both sides of the boundary road segment are determined as dual-layer dynamic threshold control intersections; if the comprehensive traffic connectivity degree is greater than or equal to the second preset threshold, the intersections on both sides of the boundary road segment are determined as static control intersections. When the boundary road segment is an unstable region, calculate the comprehensive traffic correlation degree of the road segment between the second upstream intersection and the first upstream intersection, and determine the traffic state of the road segment; If the road segment is in a stable region, the upstream intersection inside the road segment is directly determined as a single-layer dynamic threshold control intersection. If the road segment is in an extensible domain, the comprehensive traffic correlation degree from the third upstream intersection to the first upstream intersection is calculated. If the comprehensive traffic correlation degree is less than the second preset threshold, the intersections on both sides of the road segment are determined as dual-layer dynamic threshold control intersections. If the comprehensive traffic correlation degree is greater than or equal to the second preset threshold, the intersections on both sides of the road segment are determined as static control intersections. If the road segment is in an unstable region, the boundary intersection and all corresponding upstream intersections are defined as statically controlled intersections; the line connecting all dynamic threshold controlled intersections is the dynamic control boundary. The optimal vehicle accumulation within the dynamic control boundary is estimated using the MFD model, and the traffic control allocation for each boundary segment is determined based on the optimal vehicle accumulation. Based on the traffic control allocation, the green light duration of the traffic signal at each dynamically threshold-controlled intersection is calculated to obtain the flexible boundary control scheme for traffic signals in the bottleneck area.

2. The robust control method for elastic boundaries in urban traffic bottleneck areas according to claim 1, characterized in that, Based on the dynamic and static traffic information, determine the spatial and temporal traffic correlation indices for each boundary road segment within the current time interval, specifically including: Obtain road network data and traffic operation data from the dynamic and static traffic information; wherein, the road network data includes at least road segment length, number of lanes, vehicle distribution and cross-sectional form, and the traffic operation data includes at least road segment flow, traffic occupancy rate, traffic congestion density and traffic volume in each direction at intersections; according to Calculate the current time interval t Inner, boundary road section m Spatial obstruction traffic correlation index ; in, i Represents the boundary section m The first upstream intersection on the outer side; j Represents a boundary intersection; Current time interval t Inner boundary road section m from i arrive j Traffic volume entering in a particular direction; The previous time interval (t-1) Inner boundary road section m from i arrive j Traffic congestion in the direction; Current time interval t Inner boundary road section m from i arrive j Traffic volume in the direction; Boundary section m from i arrive j Number of lanes in each direction; Boundary section m Length; Boundary section m Traffic congestion density; according to Calculate the current time interval t Inner, boundary road section m Time-delay traffic correlation index ; in, Current time interval t Inner boundary road section m from i arrive j Average traffic occupancy in each direction; Current time interval t Inner boundary road section m from i arrive j Actual travel time in the direction; Boundary section m from i arrive j Free-flow travel time in direction.

3. The robust control method for elastic boundaries in urban traffic bottleneck areas according to claim 1, characterized in that, Based on the comprehensive traffic connectivity of each boundary road segment, the traffic status of each boundary road segment is determined, specifically including: If the comprehensive traffic correlation degree is less than or equal to the first preset threshold, it indicates that the spatiotemporal obstruction of the incoming traffic flow in the corresponding boundary road segment is small, and the traffic state of the boundary road segment is determined as a stable domain. If the comprehensive traffic correlation degree is greater than the first preset threshold and less than the second preset threshold, it indicates that the spatiotemporal stagnation of the incoming traffic in the corresponding boundary road segment is moderate, and the traffic state of the boundary road segment is determined as an extensible domain. If the comprehensive traffic correlation degree is greater than or equal to the second preset threshold, it indicates that the spatiotemporal stagnation of the incoming traffic flow in the corresponding boundary road segment is relatively large, and the traffic state of the boundary road segment is determined as an unstable domain.

4. The robust control method for elastic boundaries in urban traffic bottleneck areas according to claim 1, characterized in that, The optimal vehicle accumulation within the dynamic control boundary range is estimated using the MFD model, specifically including: according to Calculate the real-time cumulative vehicle volume within the dynamic control boundary range. ;in, Z The set of road segments within the dynamic control boundary range. z The first in the set of road segments z This section of road; For road section z Length; Let z be the number of lanes in road segment z; Current time interval t Inner section z The average traffic occupancy rate; This represents the average vehicle length. Statistical analysis of the current time interval t The number of vehicles that drive out of the dynamic control boundary is denoted as . ; based on and Using the sample data, construct the MFD model for the urban traffic bottleneck area: Where a, b, and c are model parameters; Plot the MFD curve corresponding to the MFD model, and determine the ordinate value corresponding to the highest point of the MFD curve as the optimal vehicle accumulation amount.

5. A robust control method for elastic boundaries in urban traffic bottleneck areas according to claim 1, characterized in that, Based on the optimal vehicle accumulation volume, the traffic control allocation for each boundary road segment is determined, specifically including: according to Calculate the next time interval (t+1) Within the dynamic control boundary, the total traffic control volume. ;in, The real-time cumulative number of vehicles within the dynamic control boundary range; This represents the optimal vehicle accumulation within the dynamic control boundary range; If the boundary section m If the intersection includes a dynamic threshold control intersection, then according to Calculate the next time interval (t+1) Inner, boundary road section m Traffic control allocation; in, Current time interval t The set of dynamically threshold-controlled intersections in urban traffic bottleneck areas, including the set of single-level dynamically threshold-controlled intersections. and dual-layer dynamic threshold control intersection set ; Boundary road sections that include dynamically threshold-controlled intersections m The overall traffic connectivity within the current time interval t; Boundary section m The number of lanes into which the vehicle enters; w For any one of the dynamically threshold-controlled intersections in the set of dynamically threshold-controlled intersections; For dynamic threshold control intersections w The number of lanes in the direction of entry; For dynamic threshold control intersections w The overall traffic connectivity of the road segment in the direction of entry.

6. The robust control method for elastic boundaries in urban traffic bottleneck areas according to claim 1, characterized in that, Based on the traffic control allocation, the green light duration of the traffic signal at each dynamically threshold-controlled intersection is calculated to obtain a flexible boundary control scheme for traffic signals in the bottleneck area, specifically including: Obtain signal control data from the dynamic and static traffic information; wherein, the signal control data includes at least the signal control mode, signal cycle duration, and green light duration; If the boundary section m If it includes a single-layer dynamic threshold control intersection, then according to Calculate the next time interval (t+1) Inner, boundary road section m The green light duration adjustment value for the entering direction at a single-layer dynamic threshold control intersection. ;in, Boundary section m Traffic control allocation. Boundary section m The number of lanes to enter, To achieve saturation headway, The unit time interval length The signal cycle duration for a single-layer dynamic threshold control intersection; Then according to Calculate the next time interval (t+ 1) Inner, boundary road section m The duration of the green light for the entering direction at a single-layer dynamic threshold control intersection. Thus, a flexible boundary control scheme for traffic signals in the bottleneck area corresponding to a single-level dynamic intersection is obtained; among which, The green light duration for the inbound direction at the single-layer threshold boundary control intersection corresponding to the boundary road segment m within the current time interval t; This is the minimum duration of the green light for a given phase. If the boundary section m Includes dual-layer dynamic threshold control intersections and According to Calculate the next time interval (t+1) Inner, boundary road section m Traffic signal phase difference at a dual-layer dynamic threshold control intersection ; in, Indicates a two-layer dynamic threshold control intersection and The section of road leading into the central bottleneck area; Indicates the current time interval t Inside and The length of the queue for vehicles entering the road between the sections; The dissipation wave velocity of the queued vehicles; for and The length of the road segment between them; The average speed of the road segment; according to Calculate the green wave bandwidth variation value of a dual-layer dynamic threshold control intersection. ;in, The signal cycle duration of a dual-layer dynamic threshold control intersection is defined as follows: the signal cycle durations of the two intersections in a dual-layer dynamic threshold control intersection are the same. Based on the green wave bandwidth change value, the green light ratio of the direction of entry into the central bottleneck area of ​​the dual-layer dynamic threshold control intersection is adjusted, and the green light duration of the coordinated phase of the direction of entry into the dual-layer dynamic threshold control intersection is updated, thereby obtaining the flexible boundary control scheme for traffic signals in the bottleneck area corresponding to the dual-layer dynamic intersection.

7. A robust control method for elastic boundaries in urban traffic bottleneck areas according to claim 1, characterized in that, Before acquiring real-time dynamic and static traffic information of urban traffic bottleneck areas, the method further includes: Based on the prior knowledge of traffic managers, the traffic congestion areas in the urban traffic system are identified as the central bottleneck areas. Centered on the central bottleneck area, several ring roads and several radial roads are determined within a preset distance. The intersections of the ring roads and the radial roads form a network of intersections around the central bottleneck area. Each intersection on the same radial road is divided into a boundary intersection and multiple corresponding upstream intersections according to their proximity to the central bottleneck area; wherein, the boundary intersection is the intersection closest to the central bottleneck area. The road segment between the boundary intersection and the adjacent upstream intersection is defined as the boundary road segment; The boundary road segment, the bottleneck area, the boundary intersection, and the corresponding multiple upstream intersections together constitute the urban traffic bottleneck area.

8. A robust control device for flexible boundaries in urban traffic bottleneck areas, characterized in that, The device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, enabling the at least one processor to execute a robust control method for flexible boundaries in urban traffic bottleneck areas according to any one of claims 1-7.

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