Transportation hub passenger flow organization and transport capacity coordinated scheduling method, device, equipment, and storage medium

Abstract

The present application provides a method, device, equipment, and storage medium for passenger flow organization and coordinated dispatching of transport capacity at a transportation hub. The method includes: determining a transfer passenger flow matrix based on basic data of the transportation hub; determining the degree of conflict of each conflict point based on the transfer passenger flow matrix; determining a transportation hub passenger flow organization evaluation index value based on the degree of conflict; if it is greater than a preset index threshold, optimizing passenger flow organization with the goal of minimizing traffic flow conflicts and passenger travel time, and then optimizing transport capacity adjustment; if it is not greater than the preset index threshold, optimizing transport capacity adjustment. The method provided in the present application determines a transportation hub passenger flow organization evaluation index value based on basic data of the transportation hub; if it is greater than a preset index threshold, optimizing passenger flow organization and optimizing transport capacity adjustment with the goal of minimizing traffic flow conflicts and passenger travel time, thereby achieving reasonable optimization based on the relationship between transport capacity and transport volume, and between passenger flow organization and management.

Description

Technical Field

[0001] The present application relates to the field of rail transit technology, and in particular to a method, device, equipment, and storage medium for organizing passenger flow and coordinating transport capacity at a transportation hub. Background Art

[0002] Currently, methods for organizing passenger flow and coordinating transport capacity at transportation hubs focus on either transport capacity scheduling (such as vehicle scheduling and timetable optimization) or passenger flow organization (such as passenger flow distribution prediction, flow design, and emergency evacuation). While this one-sided approach can improve transportation hub operations to a certain extent, it struggles to fundamentally resolve the deep-seated contradictions between transportation capacity and volume, and between passenger flow organization and management. Summary of the Invention

[0003] In order to solve one of the above-mentioned technical defects, the present application provides a method, device, equipment and storage medium for organizing passenger flow and coordinating transport capacity at a transportation hub.

[0004] In a first aspect, the present application provides a method for organizing passenger flow and coordinating transport capacity at a transportation hub, the method comprising:

[0005] Obtain basic data of transportation hubs;

[0006] Determine the transfer passenger flow matrix of the transportation hub based on basic data;

[0007] Based on the transfer passenger flow matrix, the conflict degree of each conflict point in the transportation hub is determined; a conflict point is a space in the transportation hub where traffic flows from two modes of transportation pass through at the same time;

[0008] Determine the evaluation index value of passenger flow organization at the transportation hub according to the degree of conflict;

[0009] If the passenger flow organization evaluation index value of the transportation hub is greater than the preset index threshold, the passenger flow organization optimization is carried out with the goal of minimizing traffic flow conflicts and passenger travel time, and then the capacity adjustment optimization is carried out;

[0010] If the passenger flow organization evaluation index of the transportation hub is not greater than the preset index threshold, capacity adjustment optimization will be carried out.

[0011] Optionally, determining a transfer passenger flow matrix of a transportation hub based on basic data includes:

[0012] Based on basic data, determine the total number of transfers for each mode of transportation and the share of each mode of transportation in transferring to other modes of transportation;

[0013] Determine the transfer passenger flow of various modes of transportation to other modes of transportation and obtain the transfer passenger flow matrix; among them, the transfer passenger flow matrix N is the total number of transportation modes, V i is the transfer matrix of any transportation mode i, V i ={v i1 ,v i2 ,…,v ij ,…v iN};v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a i is the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j.

[0014] Optionally, based on the transfer passenger flow matrix, the conflict degree of each conflict point in the transportation hub is determined, including:

[0015] Based on the transfer passenger flow matrix, determine the number of passengers to be transported by various modes of transportation, where the number of passengers to be transported by any mode of transportation j is b j =v 1j +…+v ij +…+v Nj ;

[0016] Determine the conflict type of each conflict point in the transportation hub, where the conflict type of any conflict point is intersection conflict, confluence conflict, or diversion conflict;

[0017] Determine the conflict degree of each conflict point in the transportation hub, where the conflict degree of any conflict point u is in, and are the number of passengers to be transported by the two modes of transportation at any conflict point u, I u is the weight corresponding to the conflict type of any conflict point u.

[0018] Optionally, based on the degree of conflict, the evaluation index values ​​for passenger flow organization at the transportation hub are determined, including:

[0019] Determine the evaluation index value P of passenger flow organization at the transportation hub 1 =λ1×T 1 +λ2×K 1 ;

[0020] Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict degrees of all conflict points.

[0021] Optionally, λ1 and λ2 satisfy the following relationship:

[0022] λ1:λ2=α×(average transfer time: the mean of the weights corresponding to all conflict types);

[0023] Among them, α is the proportional weight.

[0024] Optionally, passenger flow organization optimization is performed with the goal of minimizing traffic flow conflicts and passenger travel time, including:

[0025] Determine passenger travel time t(n) = ∑ n t l1 +∑ n t l2 +∑ n t l3 +∑ n t g1 +∑ n t g2 ; where n is the transfer line identifier, t lx is the travel time of passengers in the x area on the transfer line, where x area is a horizontal line area, a stair area, or an elevator area. When x area is a horizontal line area, x=1; when x area is a stair area, x=2; when x area is an elevator area, x=3. q l is the passenger flow on the transfer line, t0 is the passenger walking time in free flow, μ and τ are preset coefficients, C x is the capacity of passenger walking facilities in area x; ∑ n t l1 is the total travel time of passengers in the horizontal connection area of ​​transfer connection n, ∑ n t l2 is the total travel time of passengers in the stair area of ​​transfer link n, ∑ n t l3 is the total travel time of passengers in the elevator area of ​​transfer line n; t gy It is the travel time of passengers at gate type y on the transfer line. Type y is manual ticket checking type or automatic ticket checking type. When type y is manual ticket checking type, y=1; when type y is automatic ticket checking type, y=2. q g is the passenger flow at the gate, C y is the capacity of type y gate, ∑ n t g1 is the total travel time of passengers at the manual ticket inspection gate of transfer line n, ∑ n t g2 is the total travel time of passengers at the automatic ticket gate of transfer link n;

[0026] Passenger flow organization optimization is performed based on the optimization objective function min(μ1T+μ2K), where μ1 and μ2 are preset parameters and μ1+μ2=1; T is based on the minimum objective function of passenger travel time. Where n is the transfer link identifier, NC is the total number of transfer links, and t(n) is the passenger travel time for any transfer link n; K is calculated based on the traffic flow conflict minimization objective function. We get u as the conflict point identifier, U as the total number of conflict points, and K u is the conflict degree of any conflict point u.

[0027] Optionally, perform capacity adjustment optimization, including:

[0028] Determine the calculated value of transport capacity matching Among them, v is the traffic mode identifier, N is the total number of traffic modes, b v is the number of passengers to be transported by mode v, C v is the transport capacity of transport mode v;

[0029] Determine the calculated benefit value of each operating entity of the transportation mode, where the calculated benefit value of any operating entity z is C z is the operating cost of any operator z, r is the identifier of the transportation mode operated by any operator z, is the departure frequency of transportation mode r operated by any operator z, The single-trip operating cost of transportation mode r operated by any operator z;

[0030] I z is the operating income of any operating entity z, is the total amount of government subsidies for transportation mode r operated by any operator z, is the number of passengers of transport mode r operated by any operator z, is the average passenger fare for mode r operated by any operator z;

[0031] With the train interval, interval running time, station stay time and train capacity as constraints, the objective function Adjust and optimize capacity to achieve optimization goals.

[0032] In a second aspect, the present application provides a device for organizing passenger flow and coordinating transport capacity at a transportation hub, the device comprising:

[0033] Acquisition module, used to obtain basic data of transportation hubs;

[0034] A first determining module, configured to determine a transfer passenger flow matrix of a transportation hub based on the basic data acquired by the acquiring module;

[0035] a second determining module, configured to determine the degree of conflict at each conflict point in the transportation hub based on the transfer passenger flow matrix determined by the first determining module; wherein a conflict point is a space in the transportation hub where traffic flows of two modes of transportation pass through simultaneously;

[0036] A third determining module is used to determine the passenger flow organization evaluation index value of the transportation hub according to the conflict degree determined by the second determining module;

[0037] The adjustment module is used to optimize the passenger flow organization with the goal of minimizing traffic flow conflicts and passenger travel time when the passenger flow organization evaluation index value of the transportation hub determined by the third determination module is greater than the preset index threshold, and then perform capacity adjustment optimization; when the passenger flow organization evaluation index of the transportation hub is not greater than the preset index threshold, perform capacity adjustment optimization.

[0038] In a third aspect of the present application, an electronic device is provided, comprising:

[0039] Memory;

[0040] processor; and

[0041] computer programs;

[0042] The computer program is stored in the memory and is configured to be executed by the processor to implement the method as described in the first aspect above.

[0043] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored; the computer program is executed by a processor to implement the method described in the first aspect above.

[0044] The present application provides a method, apparatus, device, and storage medium for organizing passenger flow and coordinating transport capacity at a transportation hub. The method includes: obtaining basic data of the transportation hub; determining a transfer passenger flow matrix of the transportation hub based on the basic data; determining the degree of conflict of each conflict point in the transportation hub based on the transfer passenger flow matrix; wherein a conflict point is a space in the transportation hub where traffic flows of two modes of transportation pass through simultaneously; determining a passenger flow organization evaluation index value for the transportation hub based on the degree of conflict; if the passenger flow organization evaluation index value for the transportation hub is greater than a preset index threshold, optimizing the passenger flow organization with the goal of minimizing traffic flow conflict and minimizing passenger travel time, and then optimizing transport capacity; if the passenger flow organization evaluation index for the transportation hub is not greater than the preset index threshold, optimizing transport capacity.

[0045] The method provided in this application determines the passenger flow organization evaluation index value of the transportation hub based on the basic data of the transportation hub. When the passenger flow organization evaluation index value of the transportation hub is greater than the preset index threshold, the passenger flow organization is optimized with the goal of minimizing traffic flow conflicts and minimizing passenger travel time. Then, the capacity adjustment optimization is performed, thereby achieving reasonable optimization between the transportation capacity and volume of the transportation hub, and between passenger flow organization and management, improving the efficiency of passenger organization, and providing passengers with a more convenient and comfortable travel experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0047] Figure 1 A flow chart of a method for organizing passenger flow and coordinating transport capacity at a transportation hub provided in an embodiment of the present application;

[0048] Figure 2 A schematic diagram of the structure of a transportation hub passenger flow organization and transport capacity coordinated scheduling device provided in an embodiment of the present application;

[0049] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the technical solutions and advantages of the embodiments of the present application more clearly understood, the exemplary embodiments of the present application are further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, and are not an exhaustive list of all the embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other unless they conflict.

[0051] In the process of realizing this application, the inventors discovered that current methods for organizing passenger flow and coordinating transport capacity at transportation hubs focus on either transport capacity scheduling (such as vehicle scheduling and timetable optimization) or passenger flow organization (such as passenger flow distribution prediction, streamline design, and emergency evacuation). While this one-sided approach can improve the operation of transportation hubs to a certain extent, it is difficult to fundamentally resolve the deep-seated contradictions between transportation capacity and volume, and between passenger flow organization and management.

[0052] In response to the above problems, an embodiment of the present application provides a method, apparatus, equipment, and storage medium for passenger flow organization and coordinated transport capacity scheduling at a transportation hub, the method comprising: obtaining basic data of the transportation hub; determining a transfer passenger flow matrix of the transportation hub based on the basic data; determining the degree of conflict of each conflict point in the transportation hub based on the transfer passenger flow matrix; wherein a conflict point is a space in the transportation hub where traffic flows of two modes of transportation pass through at the same time; determining a passenger flow organization evaluation index value for the transportation hub based on the degree of conflict; if the passenger flow organization evaluation index value for the transportation hub is greater than a preset index threshold, then performing passenger flow organization optimization with the goal of minimizing traffic flow conflict and minimizing passenger travel time, and then performing transport capacity adjustment optimization; if the passenger flow organization evaluation index for the transportation hub is not greater than the preset index threshold, then performing transport capacity adjustment optimization. The method provided in this application determines the passenger flow organization evaluation index value of the transportation hub based on the basic data of the transportation hub. When the passenger flow organization evaluation index value of the transportation hub is greater than the preset index threshold, the passenger flow organization is optimized with the goal of minimizing traffic flow conflicts and minimizing passenger travel time. Then, the capacity adjustment optimization is performed, thereby achieving reasonable optimization between the transportation capacity and volume of the transportation hub, and between passenger flow organization and management, improving the efficiency of passenger organization, and providing passengers with a more convenient and comfortable travel experience.

[0053] See also Figure 1 This embodiment provides a method for organizing passenger flow and coordinating transport capacity at a transportation hub, and the implementation process is as follows:

[0054] 101. Obtain basic data of transportation hubs.

[0055] The basic data of transportation hubs include historical basic data and real-time basic data of transportation hubs. The specific basic data include at least one or more of the following: passenger flow, vehicle flow, passenger mobile phone signaling of various modes of transportation (including railways, rail transit, urban buses, taxis / online booking, bicycles, etc.), passenger flow density in areas within the hub (horizontal connection areas, stair areas, elevator areas, gates, etc.), passenger flow in areas within the hub, traffic capacity in areas within the hub, hub topology, camera information in the hub, passenger transfer time on each transfer line, passenger travel time on each transfer line, passenger flow on each transfer line, passenger flow and travel time of various types of gates on each transfer line, operating entities of various modes of transportation, departure frequency of various modes of transportation, single-trip operating costs of various modes of transportation, operating costs of each operating entity, operating income of each operating entity, government subsidies for various modes of transportation, number of passengers of various modes of transportation, and passenger fares for various modes of transportation.

[0056] 102. Determine the transfer passenger flow matrix of the transportation hub based on the basic data.

[0057] As the basic function of a transportation hub, transportation function is mainly reflected in the distribution function, transfer function, guidance function and parking function of the transportation hub, among which transfer is the core function of the transportation hub. In order to achieve "seamless connection" of transportation modes such as railways, rail transit, urban buses, taxis / online bookings, bicycles, etc., and provide efficient and integrated transfer services, the transportation hub needs to select the passenger flow transfer mode based on different transportation modes, obtain the passenger flow sharing rate of different transportation modes, and then determine the transfer passenger flow matrix of the transportation hub. Therefore, the implementation method of step 102 is as follows:

[0058] 102-1. Based on basic data, determine the total number of transfers for various modes of transportation and the share of transfers from various modes of transportation to other modes of transportation.

[0059] The share ratio in step 102-1 can be derived based on a model of each connection mode's selection behavior. For example, each connection mode's selection behavior can be modeled based on factors such as occupation, age, travel time, travel cost, travel purpose, luggage quantity, socioeconomic attributes, and accessibility. Based on the basic data and the connection mode selection behavior model, the share ratio of each mode of transportation to other modes of transportation can be derived.

[0060] Alternatively, the share ratio in step 102-1 can be derived based on historical passenger flow data and camera data. For example, based on the camera information within the hub in the basic data, through camera coordinate positioning, pedestrian detection, pedestrian feature extraction, pedestrian re-identification, target positioning, and single-camera motion trajectory generation, passenger trajectory paths are generated, and the share ratio of various transportation modes to other modes of transportation is then derived.

[0061] Alternatively, the share ratio in step 102-1 can be obtained from passenger mobile phone signaling. For example, by cleaning and analyzing passenger mobile phone signaling in the basic data, the passenger's travel trajectory can be obtained. Based on the passenger's travel trajectory, the user's trip origin-destination (OD) pair is identified according to the base station dwell time, transfer speed, and transfer distance, and the share ratio of various transportation modes to other modes of transportation is calculated.

[0062] 102-2, determine the transfer passenger flow of various modes of transportation to other modes of transportation, and obtain a transfer passenger flow matrix.

[0063] For example, the types of transportation connection modes in the transportation hub (i.e., the total number of transportation modes) are N, and the share rate of any transportation mode i obtained through step 102-1 is: i ={r i1 ,r i2 ,…,r ij ,…,r iN}, where r ij is the share of any mode of transport i transferring to any other mode of transport j. Then, the transfer passenger flow v of any mode of transport i transferring to any other mode of transport j is ij =a i ·r ij , where a i is the total number of transfers for any mode of transportation i. Therefore, the transfer matrix V for any mode of transportation i is i =

[0064] {v i1 ,v i2 ,…,v ij ,…v iN In summary, the transfer passenger flow matrix of the transportation hub is

[0065]

[0066] Therefore, the transfer passenger flow matrix obtained in step 102-2 is N is the total number of transportation modes, V i is the transfer matrix of any transportation mode i, V i ={v i1 ,v i2 ,…,v ij ,…v iN}. v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a i is the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j.

[0067] 103. Based on the transfer passenger flow matrix, determine the conflict degree of each conflict point in the transportation hub.

[0068] When two traffic flows pass through a certain point in space at the same time, a traffic conflict will occur. Therefore, the conflict point is the space in the transportation hub where traffic flows of two modes of transportation pass through at the same time.

[0069] The implementation process of step 103 is as follows:

[0070] 103-1, based on the transfer passenger flow matrix, determine the number of passengers to be transported by various modes of transportation.

[0071] In step 102, the transfer passenger flow matrix is ​​obtained. After that, the number of passengers b that needs to be transported by any mode of transportation j can be calculated j, that is, the number of passengers to be transported by mode j is obtained. For example, the number of passengers to be transported by any mode j is b j =v 1j +…+v ij +…+v Nj .

[0072] 103-2, determine the conflict type of each conflict point in the transportation hub.

[0073] Traffic conflicts, the root cause of traffic delays and accidents, are influenced by conflict type and traffic flow. Conflict type can be categorized as crossing, merging, or diverging. Therefore, the conflict type at any conflict point is either crossing, merging, or diverging.

[0074] In addition, in order to quantify the impact of conflict types on traffic flow, different weights are assigned to these three conflict types.

[0075] 103-3, determine the degree of conflict at each conflict point in the transportation hub.

[0076] If the number of passengers to be transported by the two modes of transportation at any conflict point u is and Then the conflict degree of any conflict point u is

[0077] Among them, I u is the weight corresponding to the conflict type of any conflict point u. If the conflict type of any conflict point u is a cross conflict, then I i =I1, if the conflict type of any conflict point u is a confluence conflict, then I u =I2, if the conflict type of any conflict point u is diversion conflict, then I u =I3.

[0078] 104. Determine the evaluation index value of passenger flow organization at the transportation hub based on the degree of conflict.

[0079] Step 104 determines the evaluation index value of the passenger flow organization of the transportation hub based on the internal passenger flow transfer time and the conflict degree of the conflict point. For example, the evaluation index value P of the passenger flow organization of the transportation hub is determined. 1 =λ1×T 1 +λ2×K 1 .

[0080] Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict degrees of all conflict points.

[0081] In addition, λ1 and λ2 are pre-set empirical values, and λ1 and λ2 must satisfy the following relationship:

[0082] λ1:λ2=α×(average transfer time: the mean of the weights corresponding to all conflict types).

[0083] Among them, α is the proportional weight. In the specific implementation, α can be a minimum value, that is, λ1:λ2≈

[0084] Average transfer time: the average of the weights corresponding to all conflict types.

[0085] 105. If the value of the transportation hub passenger flow organization evaluation index is greater than the preset index threshold, passenger flow organization optimization is performed with the goal of minimizing traffic flow conflicts and passenger travel time, and then capacity adjustment optimization is performed. If the transportation hub passenger flow organization evaluation index is not greater than the preset index threshold, capacity adjustment optimization is performed.

[0086] In step 105, based on the evaluation index value of the passenger flow organization of the transportation hub obtained in step 104 (i.e., P 1 ) and the preset indicator threshold (such as P 0 ) determines whether to optimize passenger flow organization. If P 1 >P 0 , then it is necessary to optimize the passenger flow organization, so the passenger flow organization optimization is started, that is, when P 1 >P 0 When P is used, passenger flow organization optimization is first performed, and then capacity adjustment optimization is performed based on the passenger flow organization after optimization. 1 ≤P 0 , there is no need to optimize passenger flow organization. At this time, passenger flow organization optimization is not started, and capacity adjustment optimization is directly executed.

[0087] Among them, when optimizing passenger flow organization, the goal is to minimize traffic flow conflicts and minimize passenger travel time. The specific optimization process is as follows:

[0088] 1.1 Determine the passenger travel time t(n).

[0089] Passenger travel time t(n) is determined by using graph theory to establish the topology of the transfer network. By considering factors such as flow rate and capacity, a passenger travel time calculation model for different connections (including horizontal connections, stairs, elevators, manual ticket gates, and automatic ticket gates) is established. For example, t(n) = ∑ n t l1 +∑ n t l2 +∑ n t l3 +∑ n t g1 +∑n t g2 .

[0090] Where n is the transfer line identifier.

[0091] t lx is the travel time of passengers in area x on the transfer line, where area x is a horizontal line area, a stair area, or an elevator area. When area x is a horizontal line area, x=1; when area x is a stair area, x=2; and when area x is an elevator area, x=3.

[0092] t lx Based on the walking speed and flow of passengers at the internal horizontal lines and stairs, the passenger flow can be established as q by using the BPR function (Bayesian Personalized Ranking, a function of the Federal Highway Administration in the United States) l The calculation formula of pedestrian link travel time is obtained, as q l is the passenger flow on the transfer line, t0 is the passenger walking time in free flow, μ and τ are preset coefficients, C x is the capacity of passenger walking facilities in area x.

[0093] ∑ n t l1 is the total travel time of passengers in the horizontal connection area of ​​transfer connection n, ∑ n t l2 is the total travel time of passengers in the stair area of ​​transfer link n, ∑ n t l3 is the total travel time of passengers in the elevator area of ​​transfer line n.

[0094] t gy It is the travel time of passengers at gate type y on the transfer line, where type y is manual ticket checking type or automatic ticket checking type. When type y is manual ticket checking type, y=1; when type y is automatic ticket checking type, y=2.

[0095] t gy Based on the knowledge of queuing theory, the average time spent by passengers in the queuing system can be calculated, such as q g is the passenger flow at the gate, C y is the capacity of the y-type gate,

[0096] ∑ n t g1 is the total travel time of passengers at the manual ticket inspection gate of transfer line n, ∑ n t g2 The total travel time of passengers at the automatic ticket gate on transfer line n.

[0097] 1.2 Optimize passenger flow organization based on the optimization objective function min(μ1T+μ2K).

[0098] Wherein, μ1 and μ2 are preset parameters, and μ1+μ2=1.

[0099] T is based on the passenger travel time minimum objective function get.

[0100] n is the transfer link identifier, NC is the total number of transfer links, and t(n) is the passenger travel time for any transfer link n.

[0101] K is based on the traffic flow conflict minimum objective function We get u as the conflict point identifier, U as the total number of conflict points, and K u is the conflict degree of any conflict point u.

[0102] When optimizing passenger flow organization, the optimization objectives are to minimize traffic flow conflicts and passenger travel time, and a hub passenger flow organization optimization model is constructed. By considering the influence of variables such as the type of internal hub facilities and equipment, passenger walking paths, and platform and station locations on the objective function, a comprehensive passenger flow organization optimization plan is provided, providing a theoretical basis for the reasonable design of transfer organization plans.

[0103] In addition, when adjusting and optimizing transport capacity, the passenger flow required by each mode of transport can be calculated based on the transfer passenger flow matrix of the transport hub. With transport capacity matching and economic benefits as the goals, a transport capacity scheduling optimization model for each mode of transport can be constructed. Based on the transport capacity scheduling optimization model, a genetic algorithm is used to coordinate and organize vehicle operations within the transfer hub with the goal of meeting passenger travel needs. This generates plans such as the number of vehicles required for each mode of transport in different time intervals, dynamic departure times, and dynamic departure intervals. The specific implementation method is as follows:

[0104] 2.1 Determine the calculated value of transport capacity matching

[0105] Among them, v is the traffic mode identifier, N is the total number of traffic modes, b v is the number of passengers to be transported by mode v, C v is the transport capacity of transport mode v.

[0106] The capacity matching degree is actually the weighted average of the passenger volume that needs to be evacuated by each mode of transportation during peak passenger flow hours and the transportation capacity of the mode of transportation.

[0107] 2.2 Determine the calculated benefit value of each operating entity of the transportation mode.

[0108] The operating entity's benefit will consider the optimal operating entity's profit. Its operating entity's profit is composed of two parts: operating costs and operating income. Operating costs include vehicle purchase costs, fuel consumption costs, vehicle depreciation costs, etc.; operating income includes government subsidies and ticket revenue. Therefore, the calculated benefit value E of any operating entity z is z =I z -C z .

[0109] C z is the operating cost of any operator z, r is the identifier of the transportation mode operated by any operator z, is the departure frequency of transportation mode r operated by any operator z, is the single-trip operating cost of transportation mode r operated by any operating entity z.

[0110] I z is the operating income of any operating entity z, is the total amount of government subsidies for transportation mode r operated by any operator z, is the number of passengers of transport mode r operated by any operator z, is the average passenger fare for mode r operated by any operator z.

[0111] 2.3 Taking the train interval, interval running time, station stay time and train capacity as constraints, the objective function Adjust and optimize capacity to achieve optimization goals.

[0112] When optimizing transport capacity, a capacity scheduling optimization model was established, using train headway, interval travel time, station dwell time, and train capacity as constraints, and optimal transport capacity matching and enterprise economic benefits as optimization goals. The optimal capacity matching degree, O = 0.8, was considered optimal.

[0113] The method for coordinated dispatching of passenger flow and transport capacity at transportation hubs provided in this embodiment can be used for the construction and optimization of coordinated dispatching systems at transportation hubs, and provide a reference for optimizing passenger flow organization, spatial layout, and transport capacity at transportation hubs and stations. It mainly addresses the problems of people arriving and leaving, people without cars, pulsed passenger flow, and short-term gatherings caused by the large scale, complex passenger flow, and multiple modes of transportation at transportation hubs. By constructing a coordinated dispatching model for multiple modes of transportation at transportation hubs and establishing a core system for coordinated dispatching at comprehensive transportation hubs, it addresses the key challenges of coordinated dispatching of people, vehicles, and goods, and realizes functions such as dynamic coordinated control of passenger flow organization and dynamic coordinated adjustment of multiple modes of transportation. It provides a reference for improving the efficiency of transportation hubs, informatization construction, and high-quality development, and supports the construction of comprehensive transportation hub systems.

[0114] The method for organizing passenger flow and coordinating transport capacity at a transportation hub, provided in this embodiment, not only comprehensively considers all aspects of the hub but also incorporates multi-network integration, aiming to achieve seamless integration and efficient coordination between different modes of transportation. This method can better design more reasonable passenger flow routes based on predicted passenger flow distribution, optimize facility layout, and achieve iterative optimization of passenger flow organization and coordinating transport capacity scheduling solutions, thereby improving the efficiency and level of passenger transport organization and providing passengers with a more convenient and comfortable travel experience.

[0115] The method for coordinated dispatching passenger flow organization and transport capacity at transportation hubs of this embodiment determines an evaluation index value for passenger flow organization at transportation hubs based on basic data of transportation hubs. When the evaluation index value for passenger flow organization at transportation hubs is greater than a preset index threshold, passenger flow organization is optimized with the goal of minimizing traffic flow conflicts and passenger travel time. Then, transport capacity adjustment optimization is performed, thereby achieving reasonable optimization between transport capacity and transport volume, and between passenger flow organization and management at transportation hubs, improving the efficiency of passenger transport organization, and providing passengers with a more convenient and comfortable travel experience.

[0116] Based on the same inventive concept of the method for organizing passenger flow at a transportation hub and coordinating transport capacity, this embodiment provides a device for organizing passenger flow at a transportation hub and coordinating transport capacity, see Figure 2 , the device comprises:

[0117] The acquisition module 201 is used to acquire basic data of the transportation hub.

[0118] The first determining module 202 is configured to determine a transfer passenger flow matrix of the transportation hub based on the basic data acquired by the acquiring module 201 .

[0119] The second determining module 203 is configured to determine the conflict degree of each conflict point in the transportation hub based on the transfer passenger flow matrix determined by the first determining module 202. A conflict point is a space in the transportation hub where traffic flows of two transportation modes pass through simultaneously.

[0120] The third determining module 204 is configured to determine a passenger flow organization evaluation index value for a transportation hub according to the conflict degree determined by the second determining module 203 .

[0121] Adjustment module 205 is configured to optimize passenger flow organization with the goal of minimizing traffic flow conflicts and passenger travel time, and then perform capacity adjustment optimization when the transportation hub passenger flow organization evaluation index value determined by third determination module 204 is greater than a preset index threshold. If the transportation hub passenger flow organization evaluation index determined by third determination module 204 is not greater than the preset index threshold, capacity adjustment optimization is performed.

[0122] The first determination module 202 is used to determine the total number of transfers of various modes of transportation and the share of transfers from various modes of transportation to other modes of transportation based on the basic data. The transfer passenger flow of various modes of transportation to other modes of transportation is determined to obtain a transfer passenger flow matrix. N is the total number of transportation modes, V i is the transfer volume matrix of any transportation mode i,

[0123] V i ={v i1 ,v i2 ,…,v ij ,…v iN}. v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a i is the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j.

[0124] The second determining module 203 is used to determine the number of passengers to be transported by various modes of transportation based on the transfer passenger flow matrix, wherein the number of passengers to be transported by any mode of transportation j is b j =v 1j +…+v ij +…+v Nj Determine the conflict type of each conflict point in the transportation hub, where the conflict type of any conflict point is intersection conflict, confluence conflict or divergence conflict. Determine the conflict degree of each conflict point in the transportation hub, where the conflict degree of any conflict point u is in, and are the number of passengers to be transported by the two modes of transportation at any conflict point u, I u is the weight corresponding to the conflict type of any conflict point u.

[0125] The third determining module 204 is used to determine the evaluation index value of the passenger flow organization of the transportation hub.

[0126] P 1 =λ1×T 1 +λ2×K 1 .

[0127] Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict degrees of all conflict points.

[0128] Among them, λ1 and λ2 satisfy the following relationship:

[0129] λ1:λ2=α×(average transfer time: the mean of the weights corresponding to all conflict types).

[0130] Among them, α is the proportional weight.

[0131] The adjustment module 205 is used to determine the passenger travel time t(n)=∑ n t l1 +∑ n t l2 +

[0132] ∑ n t l3 +∑ n t g1 +∑ n t g2 Where n is the transfer line identifier, t lx is the travel time of passengers in the x area on the transfer line, where x area is a horizontal line area, a stair area, or an elevator area. When x area is a horizontal line area, x=1; when x area is a stair area, x=2; when x area is an elevator area, x=3. q l is the passenger flow on the transfer line, t0 is the passenger walking time in free flow, μ and τ are preset coefficients, C x is the capacity of passenger walking facilities in area x. n t l1 is the total travel time of passengers in the horizontal connection area of ​​transfer connection n, ∑ n t l2 is the total travel time of passengers in the stair area of ​​transfer link n, ∑ n t l3 is the total travel time of passengers in the elevator area of ​​transfer link n. gy It is the travel time of passengers at gate type y on the transfer line. Type y is manual ticket checking type or automatic ticket checking type. When type y is manual ticket checking type, y=1; when type y is automatic ticket checking type, y=2. q g is the passenger flow at the gate, C y is the capacity of the y-type gate,

[0133] ∑ n t g1 is the total travel time of passengers at the manual ticket inspection gate of transfer line n, ∑ n t g2is the total travel time of passengers at the automatic ticket gate of transfer line n. Passenger flow organization optimization is performed based on the optimization objective function min(μ1T+μ2K), where μ1 and μ2 are preset parameters and μ1+μ2=1. T is based on the passenger travel time minimum objective function Where n is the transfer link identifier, NC is the total number of transfer links, and t(n) is the passenger travel time for any transfer link n. K is calculated based on the traffic flow conflict minimization objective function We get u as the conflict point identifier, U as the total number of conflict points, and K u is the conflict degree of any conflict point u.

[0134] The adjustment module 205 is used to determine the calculated value of the transport capacity matching degree. Among them, v is the traffic mode identifier, N is the total number of traffic modes, b v is the number of passengers to be transported by mode v, C v is the transport capacity of transport mode v. Determine the calculated benefit value of each operating entity of the transport mode, where the calculated benefit value of any operating entity z is C z is the operating cost of any operator z, r is the identifier of the transportation mode operated by any operator z, is the departure frequency of transportation mode r operated by any operator z, is the single-trip operating cost of transportation mode r operated by any operating entity z. I z is the operating income of any operating entity z, is the total amount of government subsidies for transportation mode r operated by any operator z, is the number of passengers of transport mode r operated by any operator z, is the average fare for passengers of transport mode r operated by any operator z. With the driving interval, interval running time, station stay time and train capacity as constraints, the objective function Adjust and optimize capacity to achieve optimization goals.

[0135] The device provided in this embodiment determines the passenger flow organization evaluation index value of the transportation hub based on the basic data of the transportation hub. When the passenger flow organization evaluation index value of the transportation hub is greater than a preset index threshold, the device optimizes the passenger flow organization with the goal of minimizing traffic flow conflicts and passenger travel time, and then performs capacity adjustment optimization, thereby achieving reasonable optimization between the transportation capacity and volume of the transportation hub, and between passenger flow organization and management, improving the efficiency of passenger organization, and providing passengers with a more convenient and comfortable travel experience.

[0136] Based on the same inventive concept of a method for organizing passenger flow at a transportation hub and coordinating transport capacity, this embodiment provides an electronic device such as Figure 3 As shown, it includes: a memory 301, a processor 302, and a computer program.

[0137] The computer program is stored in the memory 301 and is configured to be executed by the processor 302 to implement the above-mentioned method for organizing passenger flow and coordinating transport capacity at a transportation hub.

[0138] Specifically,

[0139] Obtain basic data of transportation hubs;

[0140] Determine the transfer passenger flow matrix of the transportation hub based on basic data;

[0141] Based on the transfer passenger flow matrix, the conflict degree of each conflict point in the transportation hub is determined; a conflict point is a space in the transportation hub where traffic flows from two modes of transportation pass through at the same time;

[0142] Determine the evaluation index value of passenger flow organization at the transportation hub according to the degree of conflict;

[0143] If the passenger flow organization evaluation index value of the transportation hub is greater than the preset index threshold, the passenger flow organization optimization is carried out with the goal of minimizing traffic flow conflicts and passenger travel time, and then the capacity adjustment optimization is carried out;

[0144] If the passenger flow organization evaluation index of the transportation hub is not greater than the preset index threshold, capacity adjustment optimization will be carried out.

[0145] Optionally, determining a transfer passenger flow matrix of a transportation hub based on basic data includes:

[0146] Based on basic data, determine the total number of transfers for each mode of transportation and the share of each mode of transportation in transferring to other modes of transportation;

[0147] Determine the transfer passenger flow of various modes of transportation to other modes of transportation and obtain the transfer passenger flow matrix; among them, the transfer passenger flow matrix N is the total number of transportation modes, V i is the transfer matrix of any transportation mode i, V i ={v i1 ,v i2 ,…,v ij ,…v iN};v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a iis the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j.

[0148] Optionally, based on the transfer passenger flow matrix, the conflict degree of each conflict point in the transportation hub is determined, including:

[0149] Based on the transfer passenger flow matrix, determine the number of passengers to be transported by various modes of transportation, where the number of passengers to be transported by any mode of transportation j is b j =v 1j +…+v ij +…+v Nj ;

[0150] Determine the conflict type of each conflict point in the transportation hub, where the conflict type of any conflict point is intersection conflict, confluence conflict, or diversion conflict;

[0151] Determine the conflict degree of each conflict point in the transportation hub, where the conflict degree of any conflict point u is

[0152] in, and are the number of passengers to be transported by the two modes of transportation at any conflict point u, I u is the weight corresponding to the conflict type of any conflict point u.

[0153] Optionally, based on the degree of conflict, the evaluation index values ​​for passenger flow organization at the transportation hub are determined, including:

[0154] Determine the evaluation index value P of passenger flow organization at the transportation hub 1 =λ1×T 1 +λ2×K 1 ;

[0155] Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict degrees of all conflict points.

[0156] Optionally, λ1 and λ2 satisfy the following relationship:

[0157] λ1:λ2=α×(average transfer time: the mean of the weights corresponding to all conflict types);

[0158] Among them, α is the proportional weight.

[0159] Optionally, passenger flow organization optimization is performed with the goal of minimizing traffic flow conflicts and passenger travel time, including:

[0160] Determine passenger travel time t(n) = ∑ n t l1 +∑ n t l2 +∑ n t l3 +∑ n t g1 +∑ n t g2 ; where n is the transfer line identifier, t lx is the travel time of passengers in the x area on the transfer line, where x area is a horizontal line area, a stair area, or an elevator area. When x area is a horizontal line area, x=1; when x area is a stair area, x=2; when x area is an elevator area, x=3. q l is the passenger flow on the transfer line, t0 is the passenger walking time in free flow, μ and τ are preset coefficients, C x is the capacity of passenger walking facilities in area x; ∑ n t l1 is the total travel time of passengers in the horizontal connection area of ​​transfer connection n, ∑ n t l2 is the total travel time of passengers in the stair area of ​​transfer link n, ∑ n t l3 is the total travel time of passengers in the elevator area of ​​transfer line n; t gy It is the travel time of passengers at gate type y on the transfer line. Type y is manual ticket checking type or automatic ticket checking type. When type y is manual ticket checking type, y=1; when type y is automatic ticket checking type, y=2. q g is the passenger flow at the gate, C y is the capacity of type y gate, ∑ n t g1 is the total travel time of passengers at the manual ticket inspection gate of transfer line n, ∑ n t g2 is the total travel time of passengers at the automatic ticket gate of transfer link n;

[0161] Passenger flow organization optimization is performed based on the optimization objective function min(μ1T+μ2K), where μ1 and μ2 are preset parameters and μ1+μ2=1; T is based on the minimum objective function of passenger travel time. Where n is the transfer link identifier, NC is the total number of transfer links, and t(n) is the passenger travel time for any transfer link n; K is calculated based on the traffic flow conflict minimization objective function. We get u as the conflict point identifier, U as the total number of conflict points, and K u is the conflict degree of any conflict point u.

[0162] Optionally, perform capacity adjustment optimization, including:

[0163] Determine the calculated value of transport capacity matching Among them, v is the traffic mode identifier, N is the total number of traffic modes, b v is the number of passengers to be transported by mode v, C v is the transport capacity of transport mode v;

[0164] Determine the calculated benefit value of each operating entity of the transportation mode, where the calculated benefit value E of any operating entity z is z =I z -C z , C z is the operating cost of any operator z, r is the identifier of the transportation mode operated by any operator z, is the departure frequency of transportation mode r operated by any operator z, The single-trip operating cost of transportation mode r operated by any operator z;

[0165] I z is the operating income of any operating entity z, is the total amount of government subsidies for transportation mode r operated by any operator z, is the number of passengers of transport mode r operated by any operator z, is the average passenger fare for mode r operated by any operator z;

[0166] With the train interval, interval running time, station stay time and train capacity as constraints, the objective function Adjust and optimize capacity to achieve optimization goals.

[0167] The electronic device provided in this embodiment has a computer program on which a processor is executed to determine an evaluation index value for passenger flow organization at a transportation hub based on basic data of the transportation hub. When the evaluation index value for passenger flow organization at a transportation hub is greater than a preset index threshold, passenger flow organization is optimized with the goal of minimizing traffic flow conflicts and passenger travel time, and then capacity adjustment optimization is performed, thereby achieving reasonable optimization between the transportation capacity and volume of the transportation hub, and between passenger flow organization and management, improving the efficiency of passenger organization, and providing passengers with a more convenient and comfortable travel experience.

[0168] Based on the same inventive concept of a method for organizing passenger flow and coordinating transport capacity at a transportation hub, this embodiment provides a computer-readable storage medium having a computer program stored thereon. The computer program is executed by a processor to implement the method for organizing passenger flow and coordinating transport capacity at a transportation hub.

[0169] Specifically,

[0170] Obtain basic data of transportation hubs;

[0171] Determine the transfer passenger flow matrix of the transportation hub based on basic data;

[0172] Based on the transfer passenger flow matrix, the conflict degree of each conflict point in the transportation hub is determined; a conflict point is a space in the transportation hub where traffic flows from two modes of transportation pass through at the same time;

[0173] Determine the evaluation index value of passenger flow organization at the transportation hub according to the degree of conflict;

[0174] If the passenger flow organization evaluation index value of the transportation hub is greater than the preset index threshold, the passenger flow organization optimization is carried out with the goal of minimizing traffic flow conflicts and passenger travel time, and then the capacity adjustment optimization is carried out;

[0175] If the passenger flow organization evaluation index of the transportation hub is not greater than the preset index threshold, capacity adjustment optimization will be carried out.

[0176] Optionally, determining a transfer passenger flow matrix of a transportation hub based on basic data includes:

[0177] Based on basic data, determine the total number of transfers for each mode of transportation and the share of each mode of transportation in transferring to other modes of transportation;

[0178] Determine the transfer passenger flow of various modes of transportation to other modes of transportation and obtain the transfer passenger flow matrix; among them, the transfer passenger flow matrix N is the total number of transportation modes, V i is the transfer matrix of any transportation mode i, V i ={v i1 ,v i2 ,…,v ij ,…v iN};v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a i is the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j.

[0179] Optionally, based on the transfer passenger flow matrix, the conflict degree of each conflict point in the transportation hub is determined, including:

[0180] Based on the transfer passenger flow matrix, determine the number of passengers to be transported by various modes of transportation, where the number of passengers to be transported by any mode of transportation j is b j =v 1j +…+v ij +…+v Nj ;

[0181] Determine the conflict type of each conflict point in the transportation hub, where the conflict type of any conflict point is intersection conflict, confluence conflict, or diversion conflict;

[0182] Determine the conflict degree of each conflict point in the transportation hub, where the conflict degree of any conflict point u is

[0183] in, and are the number of passengers to be transported by the two modes of transportation at any conflict point u, I u is the weight corresponding to the conflict type of any conflict point u.

[0184] Optionally, based on the degree of conflict, the evaluation index values ​​for passenger flow organization at the transportation hub are determined, including:

[0185] Determine the evaluation index value P of passenger flow organization at the transportation hub 1 =λ1×T 1 +λ2×K 1 ;

[0186] Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict degrees of all conflict points.

[0187] Optionally, λ1 and λ2 satisfy the following relationship:

[0188] λ1:λ2=α×(average transfer time: the mean of the weights corresponding to all conflict types);

[0189] Among them, α is the proportional weight.

[0190] Optionally, passenger flow organization optimization is performed with the goal of minimizing traffic flow conflicts and passenger travel time, including:

[0191] Determine passenger travel time t(n) = ∑ n t l1 +∑ n t l2 +∑ n t l3 +∑ n t g1 +∑ n tg2 ; where n is the transfer line identifier, t lx is the travel time of passengers in the x area on the transfer line, where x area is a horizontal line area, a stair area, or an elevator area. When x area is a horizontal line area, x=1; when x area is a stair area, x=2; when x area is an elevator area, x=3. q l is the passenger flow on the transfer line, t0 is the passenger walking time in free flow, μ and τ are preset coefficients, C x is the capacity of passenger walking facilities in area x; ∑ n t l1 is the total travel time of passengers in the horizontal connection area of ​​transfer connection n, ∑ n t l2 is the total travel time of passengers in the stair area of ​​transfer link n, ∑ n t l3 is the total travel time of passengers in the elevator area of ​​transfer line n; t gy It is the travel time of passengers at gate type y on the transfer line. Type y is manual ticket checking type or automatic ticket checking type. When type y is manual ticket checking type, y=1; when type y is automatic ticket checking type, y=2. q g is the passenger flow at the gate, C y is the capacity of type y gate, ∑ n t g1 is the total travel time of passengers at the manual ticket inspection gate of transfer line n, ∑ n t g2 is the total travel time of passengers at the automatic ticket gate of transfer link n;

[0192] Passenger flow organization optimization is performed based on the optimization objective function min(μ1T+μ2K), where μ1 and μ2 are preset parameters and μ1+μ2=1; T is based on the minimum objective function of passenger travel time. Where n is the transfer link identifier, NC is the total number of transfer links, and t(n) is the passenger travel time for any transfer link n; K is calculated based on the traffic flow conflict minimization objective function. We get u as the conflict point identifier, U as the total number of conflict points, and K u is the conflict degree of any conflict point u.

[0193] Optionally, perform capacity adjustment optimization, including:

[0194] Determine the calculated value of transport capacity matching Among them, v is the traffic mode identifier, N is the total number of traffic modes, b v is the number of passengers to be transported by mode v, Cv is the transport capacity of transport mode v;

[0195] Determine the calculated benefit value of each operating entity of the transportation mode, where the calculated benefit value E of any operating entity z is z =I z -C z , C z is the operating cost of any operator z, r is the identifier of the transportation mode operated by any operator z, is the departure frequency of transportation mode r operated by any operator z, The single-trip operating cost of transportation mode r operated by any operator z;

[0196] I z is the operating income of any operating entity z, is the total amount of government subsidies for transportation mode r operated by any operator z, is the number of passengers of transport mode r operated by any operator z, is the average passenger fare for mode r operated by any operator z;

[0197] With the train interval, interval running time, station stay time and train capacity as constraints, the objective function Adjust and optimize capacity to achieve optimization goals.

[0198] The computer-readable storage medium provided in this embodiment has a computer program thereon executed by a processor to determine a transportation hub passenger flow organization evaluation index value based on basic data of the transportation hub. When the transportation hub passenger flow organization evaluation index value is greater than a preset index threshold, passenger flow organization is optimized with the goal of minimizing traffic flow conflicts and passenger travel time, and then capacity adjustment optimization is performed, thereby achieving reasonable optimization between the transportation capacity and volume of the transportation hub, and between passenger flow organization and management, improving the efficiency of passenger transportation organization, and providing passengers with a more convenient and comfortable travel experience.

[0199] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0200] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0201] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0202] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0203] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. Throughout the description of this application, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0204] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0205] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for organizing passenger flow and coordinating transport capacity at a transportation hub, characterized in that: The method comprises: Obtain basic data of transportation hubs; Determining the transfer passenger flow matrix of the transportation hub based on the basic data includes: determining the total transfer volume of various transportation modes and the share of various transportation modes transferred to other transportation modes based on the basic data; determining the transfer passenger flow of various transportation modes transferred to other transportation modes to obtain the transfer passenger flow matrix; wherein the transfer passenger flow matrix N is the total number of transportation modes, V i is the transfer matrix of any transportation mode i, V i ={v i1 ,v i2 ,…,v ij ,…v iN };v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a i is the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j; Determining the conflict degree of each conflict point in the transportation hub based on the transfer passenger flow matrix includes: determining the number of passengers to be transported by various modes of transportation based on the transfer passenger flow matrix, wherein the number of passengers to be transported by any mode of transportation j is b j =v 1j +…+v ij +…+v Nj ; Determine the conflict type of each conflict point in the transportation hub, where the conflict type of any conflict point is intersection conflict, confluence conflict or diversion conflict; Determine the conflict degree of each conflict point in the transportation hub, where the conflict degree of any conflict point u is in, and are the number of passengers to be transported by the two modes of transportation at any conflict point u, I u is the weight corresponding to the conflict type of any conflict point u; where the conflict point is the space in the transportation hub where traffic flows of two modes of transportation pass through at the same time; According to the conflict degree, determining the evaluation index value of the passenger flow organization of the transportation hub includes: determining the evaluation index value P of the passenger flow organization of the transportation hub 1 =λ1×T 1 +λ2×K 1 ; Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict levels of all conflict points; If the passenger flow organization evaluation index value of the transportation hub is greater than the preset index threshold, the passenger flow organization is optimized with the goal of minimizing traffic flow conflicts and minimizing passenger travel time, and then the transportation capacity is adjusted and optimized; If the passenger flow organization evaluation index of the transportation hub is not greater than the preset index threshold, capacity adjustment optimization is performed.

2. The method according to claim 1, characterized in that The λ1 and λ2 satisfy the following relationship: λ1:λ2=α×(average transfer time: the mean of the weights corresponding to all conflict types); Among them, α is the proportional weight.

3. The method according to claim 1, characterized in that With the goal of minimizing traffic flow conflicts and passenger travel time, passenger flow organization optimization is carried out, including: Determine passenger travel time t(n) = ∑ n t l1 +∑ n t l2 +∑ n t l3 +∑ n t g1 +∑ n t g2 ; where n is the transfer line identifier, t lx is the travel time of passengers in the x area on the transfer line, where x area is a horizontal line area, a stair area, or an elevator area. When x area is a horizontal line area, x=1; when x area is a stair area, x=2; when x area is an elevator area, x=3. q l is the passenger flow on the transfer line, t0 is the passenger walking time in free flow, μ and τ are preset coefficients, C x is the capacity of passenger walking facilities in area x; ∑ n t l1 is the total travel time of passengers in the horizontal connection area of ​​transfer connection n, ∑ n t l2 is the total travel time of passengers in the stair area of ​​transfer link n, ∑ n t l3 is the total travel time of passengers in the elevator area of ​​transfer line n; t gy It is the travel time of passengers at gate type y on the transfer line. Type y is manual ticket checking type or automatic ticket checking type. When type y is manual ticket checking type, y=1; when type y is automatic ticket checking type, y=2. q g is the passenger flow at the gate, C y is the capacity of type y gate, ∑ n t g1 is the total travel time of passengers at the manual ticket inspection gate of transfer line n, ∑ n t g2 is the total travel time of passengers at the automatic ticket gate of transfer link n; Passenger flow organization optimization is performed based on the optimization objective function min(μ1T+μ2K), where μ1 and μ2 are preset parameters and μ1+μ2=1; T is based on the minimum objective function of passenger travel time. Where n is the transfer link identifier, NC is the total number of transfer links, and t(n) is the passenger travel time for any transfer link n; K is calculated based on the traffic flow conflict minimization objective function. We get u as the conflict point identifier, U as the total number of conflict points, and K u is the conflict degree of any conflict point u.

4. The method according to claim 1, wherein Carry out capacity adjustment and optimization, including: Determine the calculated value of transport capacity matching Among them, v is the traffic mode identifier, N is the total number of traffic modes, b v is the number of passengers to be transported by mode v, C v is the transport capacity of transport mode v; Determine the calculated benefit value of each operating entity of the transportation mode, where the calculated benefit value E of any operating entity z is z =I z -C z , C z is the operating cost of any operator z, r is the identifier of the transportation mode operated by any operator z, is the departure frequency of transportation mode r operated by any operator z, The single-trip operating cost of transportation mode r operated by any operator z; I z is the operating income of any operating entity z, is the total amount of government subsidies for transportation mode r operated by any operator z, is the number of passengers of transport mode r operated by any operator z, is the average passenger fare for mode r operated by any operator z; With the train interval, interval running time, station stay time and train capacity as constraints, the objective function Adjust and optimize capacity to achieve optimization goals.

5. A passenger flow organization and transport capacity coordinated dispatching device for a transportation hub, characterized in that: The device comprises: Acquisition module, used to obtain basic data of transportation hubs; The first determination module is used to determine the transfer passenger flow matrix of the transportation hub based on the basic data obtained by the acquisition module, including: determining the total transfer volume of various transportation modes and the share of various transportation modes from other transportation modes based on the basic data; determining the transfer passenger flow of various transportation modes from other transportation modes to obtain the transfer passenger flow matrix; wherein the transfer passenger flow matrix N is the total number of transportation modes, V i is the transfer matrix of any transportation mode i, V i ={v i1 ,v i2 ,…,v ij ,…v iN };v ij is the passenger flow from any mode of transportation i to any other mode of transportation j, v ij =a i ·r ij , a i is the total number of transfers for any mode of transportation i, r ij is the share of any mode of transportation i transferring to any other mode of transportation j; The second determination module is used to determine the conflict degree of each conflict point in the transportation hub based on the transfer passenger flow matrix determined by the first determination module, including: determining the number of passengers to be transported by various modes of transportation based on the transfer passenger flow matrix, wherein the number of passengers to be transported by any mode of transportation j is b j =v 1j +…+v ij +…+v Nj ; Determine the conflict type of each conflict point in the transportation hub, where the conflict type of any conflict point is intersection conflict, confluence conflict or diversion conflict; Determine the conflict degree of each conflict point in the transportation hub, where the conflict degree of any conflict point u is in, and are the number of passengers to be transported by the two modes of transportation at any conflict point u, I u is the weight corresponding to the conflict type of any conflict point u; where the conflict point is the space in the transportation hub where traffic flows of two modes of transportation pass through at the same time; The third determining module is used to determine the evaluation index value of the passenger flow organization of the transportation hub according to the conflict degree determined by the second determining module, including: determining the evaluation index value P of the passenger flow organization of the transportation hub 1 =λ1×T 1 +λ2×K 1 ; Among them, λ1 is the transfer time parameter, λ2 is the conflict degree parameter, T 1 is the total transfer time for passengers on all transfer lines, K 1 It represents the sum of the conflict levels of all conflict points; The adjustment module is used to optimize the passenger flow organization with the goal of minimizing traffic flow conflicts and passenger travel time when the passenger flow organization evaluation index value of the transportation hub determined by the third determination module is greater than the preset index threshold, and then perform capacity adjustment optimization; when the passenger flow organization evaluation index of the transportation hub is not greater than the preset index threshold, perform capacity adjustment optimization.

6. An electronic device, characterized in that: include: Memory; processor; as well as computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that A computer program is stored thereon; the computer program is executed by a processor to implement the method according to any one of claims 1 to 4.

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