A transport path algorithm for railway wagon flows
Patent Information
- Application Number
- CN202310174337.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-02-28
- Publication Date
- 2026-09-22
- Estimated Expiration
- 2043-02-28
AI Technical Summary
只在宝中线和包兰线模型测算，难以全国铁路推广应用
[0026]首先，本发明研发了中国铁路货物运输最短径路算法，实现了我国铁路站到站运输最短径路的快速和准确计算；
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Figure CN116433142B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of railway freight car flow route calculation and analysis technology, and in particular to a transportation route algorithm for railway freight car flow. Background Technology
[0002] Railway freight car routes are the foundation of my country's railway freight transport organization, the basic basis for organizing freight production and operation, and an important means to improve the efficiency of the railway network and the effectiveness of production and operation. In recent years, with the accelerated pace of railway construction and capacity expansion in my country, the operating mileage of conventional freight lines has reached 105,872 kilometers, including 40,318 kilometers of joint-venture local railways, 72,930 kilometers of electrified railways, and 51,600 kilometers of single-track railways. There are 6,845 conventional freight stations, including 3,765 freight operating stations, 16 network-wide marshalling yards, 24 regional marshalling yards, 28 local marshalling yards, and 320 section stations, making it the world's largest railway network. In 2018, railway freight volume reached 4.026 billion tons, increasing by 7.2% in 2019 and 3.2% in 2020. In 2020, both railway freight volume and turnover ranked first in the world, and the railway network's transport capacity was the world's largest. Calculating, optimizing, and adjusting traffic flow routes on such a large, busy, and complex road network is a global challenge.
[0003] In theory, freight car traffic between railway stations should follow the shortest route. However, in reality, influenced by factors such as transport capacity, corridor capacity, and freight density, actual traffic flow will choose efficient corridors based on the distribution of transport resources and traffic intensity. Especially in my country, due to limitations imposed by resource distribution, production layout, railway network scale and structure, as well as the capacity of some line sections and hubs, to ensure smooth and balanced transport on trunk lines, some traffic flows cannot be simply organized by choosing the shortest transport route. Therefore, specific routes need to be specified for adjustment and optimization, and parallel corridors need to be created for detour transport to improve the overall throughput capacity and efficiency of the railway network. This has resulted in a complex railway freight car traffic flow pattern with Chinese characteristics.
[0004] In existing technologies, the research on "A New Algorithm for the Transport Capacity of Railway Network Systems" (Zheng Yajing and Zhang Xingchen, *Logistics Technology*, 2011, No. 21) proposes the concept of transport capacity of railway network systems from the perspective of OD flow and constructs a two-level programming computer model for the transport capacity of railway network systems. However, railway transport capacity is difficult to quantify, making this research difficult to connect with reality. The research on "Optimization Model and Algorithm for Railway Network Traffic Flow Routes" (Su Shunhu and Chen Zhiya, *Journal of Railway Engineering*, 2008, No. 6) analyzes the existing problems with traffic flow routes and proposes the meaning of comprehensive optimal traffic flow routes to mathematically describe the railway network. However, it is only used for model calculations on the Baoji-Zhongwei Railway and the Baotou-Lanzhou Railway, making it difficult to promote and apply nationwide. Summary of the Invention
[0005] The purpose of this invention is to solve the problems mentioned in the background art and to propose a transportation route algorithm for railway freight car flow, so as to realize the rapid and accurate calculation and analysis of the transportation route of railway station-to-station transportation in my country.
[0006] To achieve the above objectives, the present invention provides the following technical solution:
[0007] A transportation route algorithm for railway freight car flow is characterized by including a shortest route algorithm, a specific route algorithm, a pivot route algorithm, and a pivot car flow algorithm.
[0008] Preferably, the shortest path algorithm includes a railway network basic data framework model, Dijkstra's algorithm theory, and the shortest path calculation process;
[0009] The railway network basic data framework model is the skeleton of traffic flow path calculation and analysis, directly affecting the efficiency of traffic flow path calculation and the size of storage space. This invention uses an adjacency list to store the network structure. In this storage method, a linked list is created for each node in the network. The i-th linked list in the network links all nodes adjacent to node i. That is, the edge from the head node to each node in the linked list represents the edge associated with the head node i. The head nodes are ordered and can be stored as an array for fast access to the linked lists of any node.
[0010] Figure 3 for Figure 1 , 2 The adjacency list representation method is used, such as the linked list of node "10" representing the edges of nodes adjacent to node "10". In the road network, a station can be called a node; from a graph theory perspective, it is a node with a degree greater than 2. In this paper, we consider stations with a degree greater than 2, railway bureau boundary stations, line attribute critical stations, and marshalling yards as road network nodes, totaling approximately 1200 nodes. The space complexity is O(n^m) (where n represents the number of nodes and m represents the average number of adjacent nodes).
[0011] The Dijkstra algorithm is theoretically as follows: Let G = (V, E) be a weighted directed graph. Divide the set of vertices V in the graph into two groups. The first group is the set of vertices for which the shortest path has been found, denoted by S. Initially, S contains only one source vertex. After each shortest path is found, the endpoint vertex is added to the set S until all vertices are added to S, at which point the algorithm ends. The second group is the set of vertices for which the shortest path has not been determined, denoted by U. Vertices in the second group are added to S in ascending order of shortest path length.
[0012] Preferably, during the addition process, the shortest path length from the source point v to each vertex in S is always kept no greater than the shortest path length from the source point v to any vertex in U; in addition, each vertex corresponds to a distance, the distance of a vertex in S is the shortest path length from v to this vertex; the distance of a vertex in U is the current shortest path length from v to this vertex, including only vertices in S as intermediate vertices.
[0013] The shortest path calculation process includes:
[0014] ① Initially, S contains only the source vertex, i.e., S = v, and the distance from v to v is 0; U contains all vertices except v. If v and u have an edge, the distance of vertex u in U is the weight of the edge; if u is not an outgoing edge adjacent vertex of v, the distance of vertex u in U is ∞.
[0015] ② Select a vertex k from U that has the smallest distance to v, and add k to S. The selected distance is the shortest path length from v to k.
[0016] ③ Using k as the new intermediate point, modify the distances of each vertex in U; if the distance from the source point v to vertex u (u∈U) (passing through vertex k) is shorter than the original distance (not passing through vertex k), then modify the distance value of vertex u. The modified distance value is the distance of vertex k plus the weight of the edge.
[0017] ④ Repeat steps ② and ③ until all vertices are contained in S. At this point, the shortest paths from the source vertex to the remaining vertices have been obtained.
[0018] By repeatedly executing Dijkstra's algorithm n times with one vertex as the source, the shortest path between each pair of vertices can be found; the total execution time is O(n^3).
[0019] The calculation principle of the shortest path from one station to another adopts Dijkstra's algorithm. Dijkstra's algorithm, proposed by the Dutch computer scientist Dijkstra in 1959, is an algorithm for finding the shortest path from one vertex to all other vertices, solving the shortest path problem in a directed graph. The main characteristic of Dijkstra's algorithm is that it expands outwards layer by layer from the starting vertex until it reaches the destination.
[0020] Preferably, the specific path business logic of the specific path algorithm is divided into two categories: aggregation type and change route type;
[0021] The aggregation type is the most important type of specific traffic flow route. Simply put, it involves aggregating traffic flow to a certain technical station and then executing the traffic flow route corresponding to that technical station. Traffic flow from that technical station to a certain area may aggregate to the next technical station according to a specific route, or it may arrive at the destination station according to the shortest route. By solving the shortest route between the originating station and the aggregation station, the route and mileage of the specific traffic flow can be obtained.
[0022] The changed route class is the most common type in the specific traffic flow route description language. According to different business logic, it can be divided into two sub-classes: original route changed route class and origin-destination domain changed route class. The shortest path is calculated between the origin-destination station and the changed route station to obtain the specific traffic flow route and mileage.
[0023] Preferably, the pivot path algorithm includes: after selecting the departure station A, selecting a pivot station, treating other stations nationwide as arrival stations, and calculating the traffic flow path accordingly. Arrivals passing through the pivot station are placed into set U, which represents the reach range of the pivot path that meets the conditions, and arrival stations not passing through the pivot station are placed into set V. Similarly, after selecting the arrival station C, selecting a pivot station, treating other stations nationwide as departure stations, and calculating the traffic flow path accordingly, placing departure stations passing through the pivot station into set S, which represents the send-off range of the pivot path that meets the conditions.
[0024] Preferably, the pivot traffic flow algorithm includes: rapid multi-condition filtering of freight data, rapid calculation of traffic flows via multiple pivots and non-pivots, storage of freight and traffic flows in the road network basic framework model, and visualization vector analysis of pivot traffic flows.
[0025] Compared with the prior art, the beneficial effects of the present invention are:
[0026] First, this invention developed a shortest route algorithm for freight transportation on Chinese railways, enabling rapid and accurate calculation of the shortest route for station-to-station transportation on Chinese railways.
[0027] Secondly, this invention has independently innovated a computer description language for specific traffic flow routes, enabling efficient computation of complex specific traffic flow routes;
[0028] Furthermore, this invention proposes a pivot path technology and application, which realizes the automated determination of the traffic flow coverage area from pivot station to pivot station;
[0029] Furthermore, this invention innovatively proposes a pivot point traffic flow analysis and application, realizing the vector calculation of traffic flow intensity from pivot point station to pivot point station;
[0030] Finally, this invention establishes a visualization platform for my country's railway network, enabling the visualization and analysis of the network, traffic flow, and routes. Attached Figure Description
[0031] Figure 1 This is a diagram showing the connection relationship between stations and lines in the railway network model of Embodiment 1 of the present invention;
[0032] Figure 2 This is the adjacency matrix diagram of the railway network model in Embodiment 1 of the present invention;
[0033] Figure 3 In Embodiment 1 of the present invention Figure 1 and Figure 2 The adjacency list;
[0034] Figure 4 This is a flowchart of the shortest path algorithm for my country's railways in Embodiment 2 of the present invention;
[0035] Figure 5 This is a diagram illustrating the process of solving a specific traffic flow path in Embodiment 3 of the present invention;
[0036] Figure 6 This is the fulcrum path diagram obtained by using a launch station in Embodiment 4 of the present invention;
[0037] Figure 7 This is a map showing the area covered by Yingshuiqiao Station via Yuci Support Point in Embodiment 4 of the present invention.
[0038] Figure 8 This is a vector diagram of the traffic flow passing through Wuwei South and Baoji East branch points in Embodiment 5 of the present invention;
[0039] Figure 9 This is a map showing the freight and vehicle flow information between Maoling and Guozhen on the Longhai Railway in Embodiment 5 of the present invention;
[0040] Figure 10 This is an example of an embodiment 6 of the present invention, which demonstrates and analyzes the inheritance relationship diagram of the visualization platform's graph elements.
[0041] Figure 11 This is a diagram of the main interface in Embodiment 6 of the present invention. Detailed Implementation
[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0043] Example 1: Railway Network Basic Data Framework Model
[0044] The railway network's basic data framework model is the skeleton of traffic flow path calculation and analysis, directly affecting the efficiency of traffic flow path calculation and the size of storage space. This invention uses an adjacency list to store the network structure. In this storage method, a linked list is created for each node in the network. The i-th linked list in the network links all nodes adjacent to node i. That is, the edges from the head node to each node in the linked list represent the edges associated with the head node i. The head nodes are ordered and can be stored as an array for fast access to the linked lists of any node.
[0045] Figure 3 for Figure 1 , 2 The adjacency list representation method is used, such as the linked list of node "10" representing the edges of nodes adjacent to node "10". In the road network, a station can be called a node; from a graph theory perspective, it is a node with a degree greater than 2. In this paper, we consider stations with a degree greater than 2, railway bureau boundary stations, line attribute critical stations, and marshalling yards as road network nodes, totaling approximately 1200 nodes. The space complexity is O(n^m) (where n represents the number of nodes and m represents the average number of adjacent nodes).
[0046] Example 2: Rapid Calculation of the Shortest Path from Station to Station
[0047] The calculation principle of the shortest path from one station to another adopts Dijkstra's algorithm. Dijkstra's algorithm, proposed by the Dutch computer scientist Dijkstra in 1959, is an algorithm for finding the shortest path from one vertex to all other vertices, solving the shortest path problem in a directed graph. The main characteristic of Dijkstra's algorithm is that it expands outward layer by layer from the starting vertex until it reaches the destination.
[0048] (1) Dijkstra's Algorithm Theory: Let G = (V, E) be a weighted directed graph. Divide the vertex set V into two groups. The first group is the set of vertices for which the shortest path has been found (denoted by S; initially, S contains only one source vertex. Each time a shortest path is found, the endpoint is added to S until all vertices are added to S, at which point the algorithm terminates). The second group is the set of vertices for which the shortest path has not yet been determined (denoted by U). Vertices in the second group are added to S in ascending order of shortest path length. During the addition process, the shortest path length from the source vertex v to any vertex in S is always maintained at no greater than the shortest path length from the source vertex v to any vertex in U. Furthermore, each vertex corresponds to a distance. The distance between vertices in S is the shortest path length from v to that vertex; the distance between vertices in U is the current shortest path length from v to that vertex, including only vertices in S as intermediate vertices.
[0049] (2) Shortest route calculation process: The station-to-station shortest route algorithm is the soul of traffic flow route calculation and analysis, and the core of whether a specific traffic flow route algorithm can be supported. The specific algorithm process is as follows.
[0050] ① Initially, S contains only the source vertex, i.e., S = v, and the distance from v to v is 0. U contains all other vertices except v, and the distance from vertex u in U is the weight of the edge (if v and u have an edge) or ∞ (if u is not an outgoing edge adjacent to v).
[0051] ② Select a vertex k from U that has the smallest distance from v, and add k to S (the selected distance is the shortest path length from v to k).
[0052] ③ Using k as the new intermediate point, modify the distances of each vertex in U; if the distance from the source point v to vertex u (u∈U) (passing through vertex k) is shorter than the original distance (not passing through vertex k), then modify the distance value of vertex u. The modified distance value is the distance of vertex k plus the weight of the edge.
[0053] ④ Repeat steps ② and ③ until all vertices are contained in S. At this point, the shortest paths from the source vertex to the remaining vertices have been determined.
[0054] Each time, starting from a vertex, Dijkstra's algorithm is executed n times (there are n vertices in the graph), and the shortest path between each pair of vertices can be found. The total execution time is O(n^3).
[0055] (3) Shortest Path Algorithm Source Code: The following source code is the shortest path algorithm from the ipoint node to other nodes in the road network. By solving for other nodes in the road network in turn, the shortest path between any two nodes can be obtained (e.g., ...). Figure 4 As shown):
[0056]
[0057]
[0058] (4) Shortest path query process: During system initialization, the shortest path and shortest mileage between node stations are stored in the corresponding node stations. To solve for the shortest path between stations, it is only necessary to search and accumulate the results by node. In addition, special processing is required for lines that only handle local arrivals and departures.
[0059] Example 3: Computer Description Language for Specific Traffic Flow Routes
[0060] The computer description language for specific traffic flows is crucial to whether these flows can meet the actual operational logic of railways. This invention's specific route description language has reached 1000 entries. In 2022, the OD flow executing specific routes accounted for 30% of the national railway loading statistics, demonstrating the significant importance of specific routes. Furthermore, with the increasing complexity of railway networks in recent years, the complexity of specific routes has also increased. Specific routes from Fengtai West marshalling yard to Zhuzhou North marshalling yard are recursively structured, and specific routes from Wuwei South marshalling yard to Xuzhou North marshalling yard are nested. This places very high demands on the design of the specific route description language, requiring it to meet complex railway operational needs, consider the efficiency of route calculation, and also balance the complexity of language maintenance. This invention divides the specific route operational logic into two categories: aggregation type and route change type.
[0061] (1) Gathering type
[0062] Aggregation type is the most important type of specific traffic flow route. Simply put, it is to aggregate traffic flow to a certain technical station and then execute the traffic flow route corresponding to that technical station. Traffic flow from that technical station to a certain area may aggregate to the next technical station according to a specific route, or it may reach the station according to the shortest route.
[0063] For example, Article 12 of the China Railway Transportation Document
[2014] No. 161 stipulates that "(x) Heavy cars loaded between stations south of Yuanzhai, west of Luqiao, and north of Sanlipu of the Shanghai Railway Bureau and stations east of Nanjing, south of Yuxikou, and south of Jingjiang South of the Shanghai Railway Bureau shall be transported at Hefei East hub." This article stipulates that the train flow should be concentrated at Hefei East marshalling yard.
[0064] "(xi) All loaded wagons that pass through the Hefei East (Wuhu East) hub (including the Shuibang Line and the Ningwu Line Taqiao-Ma'anshan stations) and are loaded between stations east of Xuancheng, south of Wuxi West, and east of Huangdu of the Shanghai Railway Bureau shall be transported via the Anhui-Jiangxi Line and the Xuanhang Line." This clause stipulates that loaded wagons loaded at the Hefei East Technical Station and transported to stations further than Nanxiang shall be gathered at the Qiaosi Technical Station. The specific wagon flow route is described in the following computer language:
[0065]
[0066]
[0067] By solving for the shortest path between the originating and destination stations and the assembly station, the route and mileage of a specific traffic flow can be obtained.
[0068] (2) Change via class
[0069] The route change class is one of the most common types in specific traffic flow route description languages. According to different business logic, it can be divided into two sub-categories: original route change class and destination domain change class. Examples are given below.
[0070] Article 12 of the China Railway Transportation Department document
[2014] No. 161 stipulates regarding the Shanghai and Nanchang lines: "(iv) All loaded cars that are loaded onto the Chengdu Railway Bureau (excluding stations between Guanghan and Guangyuan) via the Xiangtang West branch point shall be transported via the Shanghai-Kunming Railway and via the Zhuzhou North branch point." This is the most common type of route change. The article does not specify which departure stations are via the Xiangtang West branch point. The departure station is determined by calculating the shortest route and specific routes. Each destination station may correspond to a different departure area. The specific route parameter language is designed as follows:
[0071]
[0072] Article 13 of the China Railway Transportation Department's document
[2014] No. 161 stipulates that "(XXXIII) Heavy cars loaded at stations on the Chengdu-Kunming Railway of the Chengdu Railway Bureau and transported to stations south of Litang of the Nanning Railway Bureau shall be transported via the Panzhihua Boundary Station." This article is a typical example of a change in the origin and destination domain. The article clearly defines the scope of the origin and destination domains. The specific route description parameter language is designed as follows:
[0073]
[0074] By solving for the shortest path between the originating and destination stations and the changing transit stations, the route and mileage of a specific traffic flow can be obtained.
[0075] Solution process for specific traffic flow routes Figure 5 As shown.
[0076] Example 4: Calculation and Analysis Techniques for Support Paths
[0077] Based on the shortest path and specific paths, the calculation and analysis of pivot paths naturally follow. The concept of a pivot path is the area that a departure (or arrival) station can reach (send) through several pivot stations. For example, Baoji East Station, via Lanzhou North pivot station, mainly reaches stations in Gansu Province, Qinghai Province, Xinjiang Uygur Autonomous Region, and Tibet Autonomous Region; and via Hami pivot station, it mainly reaches stations in Xinjiang Uygur Autonomous Region.
[0078] (1) Calculation of the pivot path
[0079] After selecting departure station A, a transit point station is chosen, and all other stations nationwide are considered arrival stations. Traffic flow routes are calculated accordingly. Arrivals via the transit point station are placed in set U, which represents the reachable range of the transit route meeting the conditions. Arrivals not via the transit point station are placed in set V. Similarly, after selecting arrival station C, a transit point station is chosen, and all other stations nationwide are considered departure stations. Traffic flow routes are calculated accordingly, and departure stations via the transit point station are placed in set S, which represents the send-off range of the transit route meeting the conditions. For example, the transit route can be solved by using departure stations as follows: Figure 6As shown:
[0080] (2) Analysis of the fulcrum path
[0081] Building upon the foundation of pivot path calculation, the connotation of pivot path is further enriched by adding multiple logical judgments regarding whether or not the path passes through pivot stations, thereby providing technical support for complex business logic. Figure 7 The area covered by Yingshuiqiao Station via Yuci Branch Station is shown in red (red dots represent departure stations, green dots represent branch stations, yellow lines represent traffic flow routes, and blue lines represent the area covered).
[0082] Example 5: Calculation and Analysis Model of Vehicle Flow Vector at the Pivot Point
[0083] The concept of pivot point traffic flow vector calculation and analysis involves calculating and analyzing the direction and magnitude of traffic flow through pivot points in the road network. The key elements of this model are the filtering of freight source data, the calculation of pivot point routes, and the storage of freight and vehicle flow.
[0084] (1) Filtering of cargo flow data
[0085] Freight flow data refers to railway loading data, which includes information such as departure station, arrival station, category, wagon type, and number of wagons. Data such as category and wagon type can be filtered and quickly searched according to specific business needs.
[0086] (2) Calculation of traffic flow at the pivot point
[0087] The filtered cargo data is used to calculate the traffic flow routes in batches, and the cargo data and traffic flow routes that meet the criteria of passing through the pivot point are stored on the road network.
[0088] (3) Storage of freight and vehicle traffic
[0089] The storage of freight and vehicle flows is closely linked to the road network's basic data framework model. Node stations store information such as the category, vehicle type, and number of vehicles for freight data; node edges store vehicle flow.
[0090] (4) Pivot point traffic vector analysis
[0091] After storing freight and vehicle traffic on the road network, multi-dimensional analysis can be performed on the freight data of node stations and the traffic flow at the node edges.
[0092] This model is an important technical tool for my country's railways to analyze freight traffic routes and formulate train formation plans. Figure 8 This is a vector diagram of traffic flow passing through the Wuwei South and Baoji East nodes. The thickness of the line segments represents the volume of traffic, red represents loading areas, green represents nodes, and blue represents unloading areas. Figure 9 This provides information on freight and vehicle traffic between Maoling and Guozhen on the Longhai Railway.
[0093] Example 6: Visualization and Analysis Platform for Railway Network, Routes, and Traffic Flow
[0094] The platform for displaying and analyzing railway network, routes, and traffic flow is designed using Qt's graphics library. The visualization window inherits from QGraphicsView (Qt's graphics view framework), dots inherit from QGraphicsElementItem, line segments inherit from QGraphicsLineItem, text inherits from QGraphicsSimpleTextItem, and paths inherit from QGraphicsPathItem. Graphical attributes correspond one-to-one with the data in the railway network's basic data framework model, forming an efficient mapping relationship. Figure 10 To display and analyze the inheritance relationship diagram of graphic elements in the visualization platform; the platform also has basic graphic operations such as left and right mouse buttons, scroll wheel and keyboard shortcuts. Figure 11 This is the main interface of the present invention.
[0095] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A transportation route algorithm for railway freight car flow, characterized in that, This includes shortest path algorithm, specific path algorithm, pivot path algorithm, and pivot traffic flow algorithm; The shortest path algorithm includes a basic data framework model of the railway network, Dijkstra's algorithm theory, and the shortest path calculation process. The basic data framework model of the railway network is the skeleton of traffic flow path calculation and analysis, directly affecting the efficiency of traffic flow path calculation and the size of the storage space. This invention uses an adjacency list to store the network structure. In this storage method, a linked list is established for each node in the network. The i-th linked list in the network links all nodes adjacent to node i. That is, the edge from the head node to each node in the linked list represents the edge associated with the head node i. The vertices are ordered and can be stored in an array for quick access to the linked list of any node. The theory behind Dijkstra's algorithm is as follows: Let G=(V,E) be a weighted directed graph. Divide the set of vertices V into two groups. The first group is the set of vertices for which the shortest path has been found, denoted by S. Initially, S contains only one source vertex. As each shortest path is found, the endpoint vertex is added to set S until all vertices are added to S, at which point the algorithm ends. The second group is the set of vertices for which the shortest path has not been determined, denoted by U. Vertices in the second group are added to S in ascending order of shortest path length. The shortest path calculation process includes: Initially, S contains only the source vertex, i.e., S = v, and the distance from v to v is 0; U contains all other vertices except v. If v and u have an edge, the distance of vertex u in U is the weight of the edge; if u is not an outgoing edge adjacent vertex of v, the distance of vertex u in U is ∞. Select a vertex k from U that has the smallest distance to v, and add k to S. The selected distance is the shortest path length from v to k. Using k as the new intermediate point, modify the distances of each vertex in U; if the distance from the source point v through vertex k to vertex u is shorter than the original distance without passing through vertex k, and u∈U, then modify the distance value of vertex u. The modified distance value is the distance of vertex k plus the weight of the edge. Repeat steps and Until all vertices are contained in S, the shortest paths from the source vertex to the remaining vertices are obtained; The specific route algorithm's specific route computer description language is divided into two categories: aggregation type and route change type. The aggregation type is the most important type of specific traffic flow route, which aggregates traffic flow to a certain technical station and then executes the traffic flow route corresponding to that technical station. Traffic flow from that technical station to a certain area may aggregate to the next technical station according to the specific route, or it may arrive at the destination station according to the shortest route. Solving for the shortest route between the originating station and the aggregation station yields the specific traffic flow route and mileage. The route change type is the most common type of specific traffic flow route description language, which can be divided into two subcategories according to different business logic: original route change type and originating-destination domain change type. Solving for the shortest route between the originating station and the route change station yields the specific traffic flow route and mileage. The pivot path algorithm includes: after selecting the departure station A, selecting a pivot station, treating other stations nationwide as arrival stations, and calculating the traffic flow path accordingly. Arrivals passing through the pivot station are placed into set U, which is the reach range of the pivot path that meets the conditions. Arrivals not passing through the pivot station are placed into set V. Similarly, after selecting the arrival station C, selecting a pivot station, treating other stations nationwide as departure stations, and calculating the traffic flow path accordingly. Departure stations passing through the pivot station are placed into set S, which is the send range of the pivot path that meets the conditions. The pivot point traffic flow algorithm includes: rapid multi-condition filtering of freight data, rapid calculation of traffic flow via multiple pivot points and non-pivot points, storage of freight and traffic flow in the road network basic framework model, and visualization vector analysis of pivot point traffic flow.