A method, apparatus and equipment for generating efficient path sets with controllable scale
By generating an effective path set of controllable size using the Dial rule family and the maximum flow algorithm, the problem of uncontrollable path quantity in large-scale networks is solved, and the control and allocation of path set size is realized in a realistic way.
Patent Information
- Application Number
- CN202411814474.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-11
- Publication Date
- 2026-01-30
- Estimated Expiration
- 2044-12-11
AI Technical Summary
In existing technologies, the number of effective path sets cannot be effectively controlled, especially in large-scale networks where there are limitations in terms of computational efficiency and the practicality of path allocation, resulting in an unrealistic number of paths.
The Dial rule family is used to filter effective paths. By creating rules that are farther away from the starting point and closer to the ending point, and combining the maximum flow algorithm in graph theory, the minimum edge cut is determined, a sub-network is constructed, and the preceding and following effective paths are combined to generate a set of effective paths of controllable size.
It achieves control over the number of effective paths in the transportation network, generates a centrally sized path set, avoids the problem of uncontrolled path quantity, and ensures the realism and computational efficiency of path allocation.
Smart Images
Figure CN119761604B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of path planning, and in particular to a method, apparatus, and device for generating efficient path sets with controllable scale. Background Technology
[0002] In traffic network analysis and traffic flow assignment, identifying efficient path sets is crucial for understanding and optimizing traffic flow allocation. Efficient path sets typically refer to routes between the origin and destination that are "reasonable" or "efficient" for drivers. These paths are not only fundamental to traffic planning and optimization but also have wide applications in traffic engineering, urban planning, and intelligent transportation system design.
[0003] In previous studies, the uncontrollable number of effective paths has been a persistent challenge. Therefore, finding a method to control the number of effective paths is an urgent problem to be solved. Summary of the Invention
[0004] The purpose of this application is to provide a method, apparatus, and device for generating a set of effective paths with controllable scale, which can control the number of effective paths.
[0005] To achieve the above objectives, this application provides the following solution:
[0006] In a first aspect, this application provides a method for generating a set of effective paths with controllable scale, comprising: creating a family of Dial rules for filtering effective paths; the Dial rule family includes at least: a rule of moving further away from the starting point and a rule of moving closer to the ending point; selecting a rule from the Dial rule family as a compression rule, and filtering road segments in the traffic network that satisfy the compression rule; forming a subnetwork from the filtered road segments that satisfy the compression rule; using the maximum flow algorithm in graph theory to determine the minimum edge cut from the starting point to the ending point in the subnetwork; determining a set of preceding effective paths from the starting point to the preceding node of the minimum edge cut that satisfy the rule of moving further away from the starting point; determining a set of subsequent effective paths from the following node of the minimum edge cut to the ending point that satisfy the rule of moving closer to the ending point; and combining the preceding effective paths, the minimum edge cut, and the subsequent effective paths in the set of subsequent effective paths to obtain a set of effective paths from the starting point to the ending point.
[0007] Secondly, this application provides a scalable and efficient path set generation apparatus, comprising:
[0008] The rule family creation module is used to create Dial rule families for filtering valid paths; the Dial rule family includes at least: rules that move further away from the starting point and rules that move closer to the ending point;
[0009] The road segment filtering module is used to select a rule from the Dial rule family as a compression rule, and to filter road segments in the traffic network that satisfy the compression rule;
[0010] The sub-network construction module is used to form a sub-network from the selected road segments that meet the compression rules;
[0011] The minimum edge cut determination module is used to determine the minimum edge cut from the start point to the end point in the sub-network using the maximum flow algorithm in graph theory.
[0012] The preceding path determination module is used to determine the set of valid preceding paths from the starting point to the preceding node with the minimum edge cut that satisfy the rule of getting further and further away from the starting point.
[0013] The post-path determination module is used to determine the set of valid post-paths from the post-node of the minimum edge cut to the endpoint that satisfy the rule of getting closer and closer to the endpoint.
[0014] The effective path combination module is used to combine the previous effective paths and the minimum edge cut from the previous effective path set and the subsequent effective paths from the subsequent effective path set to obtain the effective path set from the starting point to the ending point.
[0015] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for generating a scalable and efficient path set as described above.
[0016] According to the specific embodiments provided in this application, this application has the following technical effects:
[0017] This application provides a method, apparatus, and device for generating a set of effective paths with controllable scale. The method selects road segments that meet compression rules in a traffic network, and then forms a sub-network from the selected road segments that meet the compression rules. Effective paths are determined in the sub-network of this method, which ensures that the number of effective paths has an upper bound, controls the output scale of the set of effective paths from the starting point to the end point, and realizes the control of the number of effective paths. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1A flowchart illustrating a method for generating an effective path set with controllable scale, provided in an embodiment of this application;
[0020] Figure 2 A schematic diagram of a traffic network provided for another embodiment of this application;
[0021] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0024] Currently, while the Dial rule used to control the number of effective paths is theoretically instructive, it has limitations in practical applications, particularly regarding computational efficiency and the realism of path allocation in large-scale networks. The Dial rule determines path validity by comparing travel costs between nodes, but its strict conditions can sometimes lead to unrealistic path allocations, such as no traffic allocation on some paths when these paths might actually carry many vehicles. To address this issue, subsequent research has proposed more relaxed rules to define effective paths. These rules consider not only the origin and destination of the path but also the travel time and length to more realistically reflect driver behavior. For example, Tong relaxes the definition of an effective path to "far from the origin or near the destination." However, with this relaxation, the number of effective paths can sometimes become difficult to control. For instance, the maximum number of effective paths for the c1 condition in the Barcelona and Chicago-Sketch OD pairs reaches 69,988 and 72,618 respectively, which is impossible in reality because even in large-scale networks, an average traveler cannot consider so many "effective paths."
[0025] In view of this, in order to control the number of effective paths during the relaxation process, or to find a specific relaxation rule that has upper and lower limits, as exemplified in one embodiment, such as Figure 1 As shown, a method for generating an efficient path set with controllable scale is provided, including the following steps 101 to 107. Wherein:
[0026] Step 101: Create a family of Dial rules for filtering valid paths; the family of Dial rules includes at least: rules that move further away from the starting point and rules that move closer to the ending point.
[0027] Step 102: Select a rule from the Dial rule family as a compression rule, and filter road segments in the traffic network that satisfy the compression rule.
[0028] Step 103: Form a sub-network from the selected road segments that meet the compression rules.
[0029] Step 104: Use the maximum flow algorithm in graph theory to determine the minimum edge cut from the start point to the end point in the subnetwork.
[0030] Step 105: Determine the set of valid preceding paths from the starting point to the preceding node of the minimum edge cut that satisfy the rule of getting further and further away from the starting point.
[0031] Step 106: Determine the set of valid paths from the end node of the minimum edge cut to the end point that satisfy the rule of getting closer and closer to the end point.
[0032] Step 107: Combine the previous valid paths in the previous valid path set, the minimum edge cut, and the subsequent valid paths in the subsequent valid path set to obtain the set of valid paths from the starting point to the ending point.
[0033] By implementing steps 101 to 107 above, road segments that meet the compression rules are selected in the traffic network, and then the selected road segments that meet the compression rules are formed into a sub-network. Valid paths are determined in the sub-network of this method, ensuring that the number of valid paths has an upper bound, controlling the output scale of the set of valid paths from the starting point to the end point, and realizing the control of the number of valid paths.
[0034] In another exemplary embodiment of this application, the following parameters are given their meanings:
[0035] c1 condition: The distance from the starting point is getting further and further away.
[0036] c2 condition: getting closer and closer to the finish line.
[0037] Dial condition: Simultaneously satisfying "getting further away from the starting point" and "getting closer to the ending point", i.e., c1 & c2.
[0038] Tong condition: satisfying "getting farther and farther away from the starting point" or "getting closer and closer to the ending point", i.e., c1||c2.
[0039] The Dial rule family: a set of valid path rules. Valid paths derived from the valid path rules in this set include valid paths derived from the Dial condition. The Dial rule family includes: the Dial condition, the Tong condition, c1, and c2. The complete definition of the Dial rule family is as follows: where i and j are OD pairs, P... r ij Let R represent the set of valid paths derived using rule r. G(V,E) is a traffic network, where V and E are the vertex set and edge set, respectively. The edge set corresponds to the set of all road segments in the traffic network. The vertex set is the set of all intersections of road segments in the traffic network. R represents the family of Dial rules. This represents the set of all valid paths between vertex i and vertex j calculated using the Dial condition.
[0040]
[0041] st cut: Let G = (V, E) be a transportation network. Let S and T form a partition of V such that s belongs to S and t belongs to T. Then the set of links from S to T is called the st cut of graph G. The set of cut edges is represented as (S, T). In a real-world context, s-tcut represents the bottleneck region of the entire transportation network.
[0042] The join operator is a Cartesian join operator for paths.
[0043] In another exemplary embodiment of this application, four types of valid path rules are added to set R to obtain the Dial rule family. The specific rules in R are as follows:
[0044] 1. The path must move further and further away from the starting point. This rule ensures that the path starts from the starting point and expands outwards, avoiding the path lingering near the starting point.
[0045] 2. The path must get closer and closer to the destination. This rule ensures that the path moves towards the destination and avoids the path straying far from it.
[0046] 3. The path either moves further away from the starting point or closer to the ending point. This rule allows the path to expand without directly heading towards the ending point and does not restrict exploration near the starting point.
[0047] 4. The path is simultaneously moving further away from the starting point and closer to the ending point. This rule is used to identify paths that are both far from the starting point and close to the ending point; these paths are often candidates for the optimal path.
[0048] In another exemplary embodiment of this application, a rule r (e.g., rule 3 in step 1) is selected from the four types of rules in R as the compression rule. This rule r is used to reduce the complexity of the traffic network by excluding road segments that do not satisfy rule r. The number of effective paths that rule r can calculate is the upper bound of the effective path calculation method proposed in this paper. In practical applications, the upper bound, i.e., rule r, can be selected according to the actual situation. Then, step 102 above, which filters road segments in the traffic network that satisfy the compression rule, can be replaced by the following steps 201 to 204:
[0049] Step 201: Traverse every road segment in the transportation network.
[0050] Step 202: Check whether each road segment meets the compression rules.
[0051] Step 203: If a road segment does not meet the compression rules, it is excluded from the traffic network.
[0052] Step 204: If the road segment meets the compression rules, then retain it.
[0053] In another exemplary embodiment of this application, a new subnetwork is constructed using the remaining valid road segments. This subnetwork contains only those road segments that satisfy the compression rule. Therefore, step 103 can be replaced by steps 301 to 303:
[0054] Step 301: Copy the traffic network to obtain a new traffic network.
[0055] Step 302: Delete road segments that do not meet the compression rules in the new traffic network.
[0056] If the traffic network is defined as G(V,E) and the new traffic network is defined as G_new(V,E), then the invalid road segments that do not meet the compression rules in step 203 can be deleted from G_new(V,E).
[0057] Step 303: Update the vertex and edge information in the traffic network after deleting the road segment to obtain the subnetwork.
[0058] In another exemplary embodiment of this application, a maximum flow algorithm in graph theory, such as the Ford-Fulkerson algorithm, is used to determine the minimum edge cut. Then, step 104 above can be replaced by steps 401 to 405:
[0059] Step 401: Use the Ford-Fulkerson algorithm to solve for the maximum flow from the starting point to the ending point in the subnetwork.
[0060] Step 402: Distribute the maximum flow value to each segment in the sub-network.
[0061] Using Ford-Fulkerson's flow increase results for all augmenting paths, the maximum flow value is decomposed into each segment in G_new.
[0062] Step 403: Construct the residual network using the sub-network.
[0063] Step 404: Perform a breadth-first search in the remaining network starting from the starting point, and mark the visited nodes as visited nodes.
[0064] Step 405: After the breadth-first search is completed, the set of edges in the remaining network that point from visited nodes to unvisited nodes is determined as the minimum edge cut.
[0065] In another exemplary embodiment of this application, step 403 described above can be replaced by steps 501 to 503:
[0066] Step 501: Copy all vertices in the sub-network to the remaining network.
[0067] Step 502: Set each edge from the starting point to the ending point in the sub-network to an edge with the same flow from the ending point to the starting point in the residual network.
[0068] Step 503: If the flow value from the starting point to the ending point is less than the preset capacity, add another edge with a flow value of cf from the starting point to the ending point in the residual network to obtain the final residual network; where c is the preset capacity and f is the flow value from the starting point to the ending point.
[0069] In another exemplary embodiment of this application, step 105 above uses the rule of "further away from the starting point" to calculate all valid paths from the starting point to the predecessor node of the minimum edge cut. The minimum edge cut consists of edges connecting visited nodes to unvisited nodes. The set of vertices of visited nodes in each edge of the minimum edge cut constitutes the set of predecessor nodes. Paths from the starting point that can reach the predecessor node of the minimum edge cut are identified. Specific operations include:
[0070] ① Use the breadth-first search algorithm for pathfinding. The algorithm takes the starting point *s* as input and the set of predecessor nodes of the minimum edge cut as input. Each path stops when it finds a predecessor node in the minimum edge cut set. The algorithm outputs all paths from the starting point *s* to the predecessor nodes.
[0071] ② Within these paths, check if the rule of "getting further and further away from the starting point" is met.
[0072] ③ Collect all paths that satisfy the condition of "getting further and further away from the starting point" to form a set of valid paths.
[0073] In another exemplary embodiment of this application, step 106 above uses the rule of "getting closer to the destination" to calculate all valid paths from the post-node of the minimum edge cut to the destination t. The set of vertices of unvisited nodes in each edge of the minimum edge cut constitutes the set of post-nodes. Paths from the post-node of the minimum edge cut to the destination are identified. Specific operations include:
[0074] 1) Use a breadth-first search algorithm for pathfinding. The algorithm takes as input the set of suffixes of the minimum edge cut and the destination t. The search stops when the destination is reached for each path. The algorithm outputs all paths from the suffixes to the destination t.
[0075] 2) Within these paths, check if the rule of "getting closer to the destination" is met.
[0076] 3) Collect all paths that satisfy the condition of "getting closer and closer to the destination" to form a set of valid paths.
[0077] In another exemplary embodiment of this application, step 107 described above can be replaced by steps 601 to 604:
[0078] Step 601: Define a join operator to connect the preceding valid path, the minimum edge cut, and the following valid path.
[0079] Step 602: For each pair of valid paths in the set of valid preceding paths and valid paths in the set of valid following paths, check whether each pair of valid preceding paths and valid following paths can be connected by a minimum edge cut.
[0080] Step 603: If they can be connected by the minimum edge cut, use the join operator to combine the minimum edge cut and a pair of preceding and following valid paths into a complete valid path from the starting point to the ending point.
[0081] Step 604: Collect all complete valid paths from the origin to the destination, forming a set of valid paths from the origin to the destination.
[0082] For example, if the set of preceding paths is {1-2-3, 1-5-6}, the minimum edge cut is {3-7, 6-8}, and the set of following paths is {7-9-10, 8-11-10}, then the result of the connection is {1-2-3-7-9-10, 1-5-6-8-11-10}.
[0083] In another exemplary embodiment of this application, steps 105 and 106 are logically independent and can support parallel computing.
[0084] In another exemplary embodiment of this application, after obtaining a set of valid paths from the starting point to the destination, the driver can select one of the valid paths in the set for navigation.
[0085] In real-world transportation networks, the effective path set generation method proposed in this application can produce path sets of moderate size, allowing for manual control over the scale of path set generation. Figure 2 For example, the starting point is 0 and the ending point is 8.
[0086] The number on each edge represents the travel time for that road segment. The valid path set derived by the Dial rule is {0-3-4-5-8, 0-3-6-7-8}, and the valid path set derived by the c1 condition is {0-1-4-5-8, 0-1-4-7-8, 0-3-4-5-8, 0-3-4-7-8, 0-3-6-7-8}. The valid path set derived using the method proposed in this application is {0-1-4-5-8, 0-3-4-5-8, 0-3-6-7-8}. It can be observed that the path set generated by the method of this application is of moderate size. In practical scenarios, using the method of this application can avoid uncontrolled size of the valid path set.
[0087] At the theoretical level, the effective path set derived by the method proposed in this application can be mathematically proven to have upper and lower bounds. Steps 102-103 guarantee that the number of path sets derived by the method of this application has an upper bound. Steps 104-107 prove that the lower bound of the path set is the effective path set of the Dial rule. The proof process is as follows, where the cut edge set D = (S, T).
[0088]
[0089] in, Using the Dial rule, the valid path from the starting point o to the ending point d is calculated. Given a starting point of o and an ending point of d, the set of valid paths calculated using the Dial rule includes all sub-paths from the starting point o to a certain internal node u. (u, v): The edge connecting u and v in the minimum edge cut. Given a starting point of o and an ending point of d, the set of valid paths calculated using the Dial rule includes all sub-paths from an internal node v to the ending point d. The set of valid paths from vertex o to vertex u calculated using condition c1. The set of valid paths from vertex v to vertex d calculated using condition c2. The Special Rule (SR) is a set of valid paths from vertex o to vertex d calculated using the SR rule. The SR is defined as follows: Using the maximum flow algorithm to find the minimum edge cut of the graph, the SR calculates valid paths from the starting point to the preceding node of the minimum edge cut based on the principle of "further from the starting point," and the SR calculates valid paths from the following node of the minimum edge cut to the ending point based on the principle of "closer to the ending point." These two sets of paths are then combined with the minimum edge cut to obtain the set of valid paths. This method of generating valid paths is called the Special Rule, or SR for short.
[0090] The method of this application mainly includes: deleting ineffective road segments from the road network using existing effective path rules to obtain a subnetwork; calculating a minimum edge cut between the start and end points in the subnetwork; calculating effective paths from the start point to the preceding node and from the following node to the end point around the minimum edge cut; and combining these three paths to obtain a set of effective paths from the start point to the end point.
[0091] Based on the same inventive concept, this application also provides a scale-controllable effective path set generation apparatus for implementing the above-described method for generating scale-controllable effective path sets. The solution provided by this apparatus is similar to the implementation described in the above-described method. Therefore, the specific limitations in one or more embodiments of the scale-controllable effective path set generation apparatus provided below can be found in the limitations of the scale-controllable effective path set generation method described above, and will not be repeated here.
[0092] In one exemplary embodiment, a scalable effective path set generation device is provided, comprising: a rule family creation module, a road segment filtering module, a sub-network construction module, a minimum edge cut determination module, a pre-path determination module, a post-path determination module, and an effective path combination module.
[0093] The rule family creation module is used to create Dial rule families for filtering valid paths; the Dial rule family includes at least: rules that move further away from the starting point and rules that move closer to the ending point.
[0094] The road segment filtering module is used to select a rule from the Dial rule family as a compression rule and filter road segments in the traffic network that satisfy the compression rule.
[0095] The subnetwork construction module is used to form a subnetwork from the selected road segments that meet the compression rules.
[0096] The minimum edge cut determination module is used to determine the minimum edge cut from the start point to the end point in the subnetwork using the maximum flow algorithm in graph theory.
[0097] The preceding path determination module is used to determine the set of valid preceding paths from the starting point to the preceding node with the minimum edge cut that satisfy the rule of getting further and further away from the starting point.
[0098] The post-path determination module is used to determine the set of valid post-paths from the post-node of the minimum edge cut to the endpoint that satisfy the rule of getting closer and closer to the endpoint.
[0099] The effective path combination module is used to combine the previous effective paths and the minimum edge cut from the previous effective path set and the subsequent effective paths from the subsequent effective path set to obtain the effective path set from the starting point to the ending point.
[0100] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores a set of valid paths from a starting point to an end point. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a method for generating a scalable set of valid paths.
[0101] Those skilled in the art will understand that Figure 3 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.
[0102] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0103] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for generating a set of effective paths with controllable size, characterized in that, The application relates to a method for searching an effective path in a traffic network. The method comprises the following steps: creating a Dial rule family for screening an effective path; the Dial rule family at least comprises a rule of getting farther and farther away from a starting point and a rule of getting closer and closer to an ending point; selecting a rule from the Dial rule family as a compression rule and screening road sections in the traffic network which satisfy the compression rule; constructing a sub-network by using the screened road sections which satisfy the compression rule; determining a minimum cut from the starting point to the ending point in the sub-network by using a maximum flow algorithm in graph theory; determining a set of pre-effective paths which satisfy the rule of getting farther and farther away from the starting point between pre-nodes from the starting point to the minimum cut; determining a set of post-effective paths which satisfy the rule of getting closer and closer to the ending point between post-nodes from the minimum cut to the ending point; combining the pre-effective paths in the set of pre-effective paths, the minimum cut and the post-effective paths in the set of post-effective paths to obtain a set of effective paths from the starting point to the ending point; determining a minimum cut from the starting point to the ending point in the sub-network by using a maximum flow algorithm in graph theory, and the method comprises the following steps: solving a maximum flow from the starting point to the ending point in the sub-network by using a Ford-Fulkerson algorithm; allocating a flow value of the maximum flow to each road section in the sub-network; constructing a residual network by using the sub-network; performing a breadth-first search in the residual network from the starting point and marking visited nodes as visited nodes; after the breadth-first search is completed, a set of edges from the visited nodes to unvisited nodes in the residual network is determined as the minimum cut; constructing a residual network by using the sub-network, and the method comprises the following steps: copying all vertices in the sub-network to the residual network; setting each edge from the starting point to the ending point in the sub-network as an edge with the same flow from the ending point to the starting point in the residual network; 2. The scalable effective path set generation method of claim 1, wherein, if a flow value from the starting point to the ending point is smaller than a preset capacity, adding an edge with a flow value of c-f from the starting point to the ending point in the residual network to obtain a final residual network; wherein c is the preset capacity, and f is the flow value from the starting point to the ending point. the Dial rule family further comprises a Dial condition and a Tong condition; the Dial condition is a rule of simultaneously satisfying the rule of getting farther and farther away from the starting point and the rule of getting closer and closer to the ending point; 3. The scalable effective path set generation method of claim 1, wherein, the Tong condition is a rule of satisfying the rule of getting farther and farther away from the starting point or the rule of getting closer and closer to the ending point. screening road sections in the traffic network which satisfy the compression rule, and the method comprises the following steps: traversing each road section in the traffic network; checking whether each road section satisfies the compression rule; if a road section does not satisfy the compression rule, the road section is excluded from the traffic network; 4. The scalable effective path set generation method of claim 1, wherein, if a road section satisfies the compression rule, the road section is retained. constructing a sub-network by using the screened road sections which satisfy the compression rule, and the method comprises the following steps: copying the traffic network to obtain a new traffic network; deleting road sections which do not satisfy the compression rule in the new traffic network; updating vertex and edge information in the traffic network after the road sections are deleted to obtain the sub-network.
5. The scalable effective path set generation method of claim 1, wherein, The vertex set of the accessed nodes in each edge of the minimum cut forms a pre-node set, and the vertex set of the unaccessed nodes in each edge of the minimum cut forms a post-node set.
6. The scalable effective path set generation method of claim 1, wherein, The pre-effective path in the pre-effective path set, the minimum cut, and the post-effective path in the post-effective path set are combined to obtain an effective path set from the start point to the end point, specifically including: a join operator for connecting the pre-effective path, the minimum cut, and the post-effective path is defined; for each pair of the pre-effective path in the pre-effective path set and the post-effective path in the post-effective path set, it is checked whether the pair of the pre-effective path and the post-effective path can be connected by the minimum cut; if the pair of the pre-effective path and the post-effective path can be connected by the minimum cut, the minimum cut and the pair of the pre-effective path and the post-effective path are combined into a complete effective path from the start point to the end point by using the join operator; all the complete effective paths from the start point to the end point are collected to form an effective path set from the start point to the end point.
7. A scalable effective path set generation apparatus, characterized by comprising: The scale-controllable effective path set generation device is used to implement the scale-controllable effective path set generation method in any one of claims 1-6, and the scale-controllable effective path set generation device includes: a rule family creation module configured to create a Dial rule family for screening effective paths, wherein the Dial rule family at least includes a rule of getting farther and farther away from a start point and a rule of getting closer and closer to an end point; a road segment screening module configured to select a rule from the Dial rule family as a compression rule and screen road segments meeting the compression rule in a traffic network; a sub-network construction module configured to construct a sub-network from the screened road segments meeting the compression rule; a minimum cut determination module configured to determine a minimum cut from a start point to an end point in the sub-network by using a maximum flow algorithm in graph theory; a pre-path determination module configured to determine a pre-effective path set meeting the rule of getting farther and farther away from the start point between pre-nodes from the start point to the minimum cut; a post-path determination module configured to determine a post-effective path set meeting the rule of getting closer and closer to the end point between effective paths from post-nodes of the minimum cut to the end point; an effective path combination module configured to combine the pre-effective path in the pre-effective path set, the minimum cut, and the post-effective path in the post-effective path set to obtain an effective path set from the start point to the end point.
8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the scale-controllable effective path set generation method in any one of claims 1-6.