A method and system for automatically configuring temporary traffic facilities during highway construction period

Abstract

This invention discloses an automatic configuration method and system for temporary traffic facilities during highway construction. First, a bidirectional BFS breakpoint diagnosis is performed on each inaccessible origin-destination (OD) pair to obtain forward / reverse boundary node sets and identify blocked nodes and edges. Then, based on a predefined parametric temporary facility template library, candidate templates are automatically selected using the edge type at the breakpoint location as the matching condition. Next, a trial insertion operation is performed on a constraint graph depth copy, and BFS reachability verification is performed again. Finally, the verified schemes are scored using a normalized weighted average based on capacity assurance, construction cost, and scheme simplicity, and the optimal temporary facility configuration scheme is output in descending order. This invention achieves automatic and accurate location of traffic breakpoints, template-based selection of temporary facilities, and real-time on-graph verification, providing quantitative decision support for traffic organization during the construction of interchange reconstruction and expansion projects.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of traffic engineering and computer application technology, specifically relating to an automatic configuration method and system for temporary traffic facilities during highway construction. Furthermore, this invention focuses on intelligent traffic-assisted design technology based on parametric graph models, particularly addressing the problem of road network connectivity interruptions caused by interchange construction. It utilizes breakpoint diagnosis algorithms from graph theory and a predefined library of engineering experience templates to achieve automatic configuration and optimal scheme selection for temporary traffic facilities (such as temporary ramps, bypass lanes, and temporary at-grade intersections). Background Technology

[0002] During the construction phase of highway interchange reconstruction and expansion projects, the closure of some ramps or main road sections often leads to the interruption of traffic routes in specific origin-destination directions (OD directions). To ensure the continuity and safety of regional traffic flow during construction, in accordance with standards such as the "Technical Specification for Construction Safety of Highway Maintenance Engineering" (JTG / T 3392-2022), temporary traffic facilities such as temporary ramps, detours, or temporary at-grade intersections must be set up. Currently, in engineering practice, the identification of traffic interruption locations, the selection of temporary facility types, and the determination of their connection locations mainly rely on manual analysis by engineers based on two-dimensional drawings and personal experience. Whether the configuration scheme effectively restores traffic requires post-construction verification using traffic simulation software such as VISSIM. This approach is manageable in the construction organization of simple road sections, but in scenarios like interchanges with complex ramp topologies and multiple OD direction constraints, it suffers from inherent problems such as low efficiency, easy omission of feasible solutions, and inconsistent results.

[0003] For traffic organization during highway construction, existing technical literature mainly focuses on the layout of signs and markings in construction areas, traffic flow guidance systems, and optimization of traffic diversion schemes for ordinary road sections. For example, some patents disclose dynamic guidance methods for construction areas based on real-time traffic flow data, or signal timing adjustment strategies for at-grade intersections. However, these technologies do not involve the construction of parametric graphical models in interchange scenarios, nor can they automatically diagnose the specific breakpoint locations (i.e., blocking nodes or blocking edges) caused by construction closures. Furthermore, while commercial traffic simulation software can simulate and evaluate pre-designed temporary facility schemes, it is essentially a verification tool, lacking the autonomous reasoning and generation capabilities from "traffic interruption" to "automatic facility configuration," and cannot automatically recommend the types of temporary facilities and their connection locations with the existing road network. There is also no precedent in the existing technology for structurally expressing engineering experience as a computable template and selecting schemes through trial insertion and re-verification on a graph.

[0004] Therefore, there is an urgent need for a systematic method that can automatically diagnose the precise location of traffic breakpoints during construction based on the parametric model of interchanges, match suitable temporary facility templates according to the breakpoint characteristics, verify the configuration effect on the drawings, and quantitatively compare and rank multiple alternative schemes. Summary of the Invention

[0005] To address the above technical problems, this invention proposes an automatic configuration method for temporary traffic facilities during highway construction, comprising the following steps: S1: Input the construction constraint diagram and the list of unreachable OD direction pairs. For each unreachable OD direction pair in the list, execute a bidirectional breadth-first search breakpoint diagnosis algorithm to identify the blocking nodes and edges causing path interruption, and output the breakpoint diagnosis results. The construction constraint diagram is a graph data structure generated by overlaying construction-stage closure, reduction, or temporary addition of constraints on a parametric directed graph model of an interchange. Nodes and edges all have traffic status attributes. OD directions represent traffic flow from the origin to the destination. The list of unreachable OD direction pairs represents traffic direction pairs from the origin to the destination that cannot be reached. The breakpoint diagnosis results include: origin... ,end The OD direction, the set of forward boundary nodes, and the set of reverse boundary nodes; the set of forward boundary nodes represents the farthest boundary node that can be reached from the starting direction, and the set of reverse boundary nodes represents the nearest boundary node that can be traced back from the ending direction. S2: Retrieve the parameterized attributes of all candidate templates from the predefined temporary facility template library; the temporary facility template library contains multiple types of temporary facilities, and the parameterized attributes of each temporary facility template include template number, template type, new temporary edge type, new temporary node type, applicable breakpoint edge type, design speed range, lane number range, maximum allowable length, traffic capacity parameters, default engineering parameters, and cost parameters. Template types include temporary ramps, bypass traffic, and temporary at-grade intersections. The new temporary node type for temporary ramps and temporary at-grade intersections is ramp end node, while the new temporary node type for bypass traffic is no new temporary node. The new temporary edge type for temporary ramps and temporary at-grade intersections is ramp segment, while the new temporary edge type for bypass traffic is mainline segment. S3: Obtain a set of edge types for the associated edges of the forward boundary node set, and retain candidate templates whose applicable breakpoint edge types intersect with this set as initial candidate templates; perform topology rule checks based on the initial candidate template types. For temporary ramp templates, the starting point of the initial candidate template connecting to the forward boundary node must be a divergence point or the starting point of the weaving zone, and the ending point of the initial candidate template connecting to the reverse boundary node must be the end of the ramp; for bypass templates, the starting and ending points of the initial candidate template connecting to the forward and reverse boundary nodes must be mainline-related nodes and there must be opposing mainline edges in the construction constraint diagram; for temporary at-grade intersection templates, the starting and ending points of the initial candidate template connecting to the forward and reverse boundary nodes must not both be mainline control section nodes. S4: On the deep copy of the construction constraint diagram, try to insert the final candidate template in each combination of forward and reverse boundary nodes, and add temporary nodes and / or temporary edges. S5: Re-execute breadth-first search reachability verification for each copy of the construction constraint diagram after trial insertion. If there is a path from the start point to the end point, record it as a valid candidate solution. S6: Perform capacity bottleneck detection for each valid candidate solution that passes the accessibility verification, including calculating the bottleneck capacity of the path using the widest path algorithm, identifying the bottleneck edge, and determining the service level level based on the load ratio calculated by the OD traffic volume and the maximum flow. If the temporary facility is the bottleneck and the service level is poor, generate improvement suggestions. S7: Adaptively determine the scoring weights based on the engineering context, normalize and weight the valid candidate solutions that have passed the verification according to traffic capacity, construction cost and solution simplicity, and sort them after adding service level penalties; S8: Output a sorted list of temporary facility configuration schemes.

[0006] Furthermore, the breakpoint diagnosis results also include: a set of blocked nodes, a set of blocked edges, the breakpoint level, and a diagnostic text description; the bidirectional breadth-first search breakpoint diagnosis algorithm includes: S2.1: Forward Breadth-First Search: Starting from the starting point, traverse the construction constraint graph and search for the adjacent nodes of the current node. When the passage state of the edge connecting the current node and the adjacent node is not closed and the passage state of the adjacent node itself is not closed, the adjacent node is added to the queue to be visited, and the set of forward reachable nodes and the set of forward boundary nodes are obtained. S2.2: Reverse Breadth-First Search: Starting from the endpoint, traverse the construction constraint graph in reverse order, search for the adjacent nodes of the current node. When the passage state of the edge connecting the current node and the adjacent node is not closed and the passage state of the adjacent node itself is not closed, the adjacent node is added to the queue to be visited, and the set of reverse reachable nodes and the set of reverse boundary nodes are obtained. S2.3: Blocking Element Identification: Check the outgoing edges of the forward boundary nodes. If the subsequent adjacent node pointed to by the outgoing edge is closed, then the subsequent adjacent node is recorded as a blocking node; if the outgoing edge itself is closed, then the outgoing edge is recorded as a blocking edge. S2.4: Fault gap region calculation: The fault gap region is obtained by taking the difference between the reverse reachable set and the forward reachable set. The number of nodes in the fault gap region reflects the size of the topological range affected by the fault.

[0007] Furthermore, the breakpoint level is obtained using multi-breakpoint extended diagnosis: when construction constraints cause multiple paths to be closed simultaneously, path enumeration, blocking set analysis, and breakpoint classification are performed to obtain classification results of single breakpoint, double breakpoint, or multiple breakpoint; the breakpoint classification is based on the minimum blocking set size, where a minimum blocking set of 1 indicates a single breakpoint, 2 indicates a double breakpoint, and 3 or more indicates multiple breakpoints; the minimum blocking set size is the minimum number of closed edges in all enumerated paths.

[0008] Furthermore, in step S6, the bottleneck edge is the edge with the minimum capacity in the set of path edges; the service level is divided into four levels according to the load ratio: overloaded, near saturation, acceptable, and sufficient. The widest path algorithm aims to maximize the minimum edge throughput of a path, and uses a path bottleneck search algorithm to search for the bottleneck throughput of the path from the starting point to the ending point. Path bottleneck search algorithms include: Initialization: Create a maximum bottleneck capacity record table, recording data from the starting point O to the constraint graph replica. The maximum bottleneck capacity among the discovered paths at each node, constraint graph replica. It includes the nodes and / or temporary edges added after the trial insertion in step S4; the maximum bottleneck capacity corresponding to the starting point O is initialized to positive infinity, indicating that the starting point itself does not limit the path's traversal capacity; other nodes whose maximum bottleneck capacity is not recorded are treated as 0. A path predecessor record table is established to record path backtracking information. Records in the path predecessor record table are binary tuples containing the reached nodes. The predecessor node u and the path from the predecessor node u to the reached node The identifiers of the edges traversed are used, and the predecessor record table of the initial path is empty; Establish a priority queue, add the starting point O and its maximum bottleneck capacity to the priority queue, store the maximum bottleneck capacity of each node added to the priority queue in negative form, and establish a set of confirmed nodes to record the nodes whose maximum bottleneck capacity has been determined. When the priority queue is not empty, the node with the largest current bottleneck capacity is popped from the priority queue and designated as the reached node. If the set of nodes has been confirmed to already exist, the node has been reached. If the node is reached, skip it; otherwise, proceed to the next node. Add to the set of confirmed nodes, if the node has been reached. If the endpoint is D, then the process ends. Search reached node For each adjacent outgoing edge, if an adjacent node is found, determine whether the adjacent outgoing edge and the adjacent node satisfy any of the following skip conditions: the confirmed node set already contains an adjacent node; the state attribute of the adjacent node or the adjacent outgoing edge is closed. If any of the above conditions are met, skip the adjacent outgoing edge. For any passable adjacent outgoing edges that have not been skipped, calculate the number of nodes reached. The candidate bottleneck capacity is determined by the number of adjacent nodes and recorded in the maximum bottleneck capacity table. The candidate bottleneck capacity is the capacity of the nodes that have been reached. The minimum value of the maximum bottleneck capacity and the passage capacity of the adjacent passable outgoing edges; If the candidate bottleneck capacity is better than the maximum bottleneck capacity of other adjacent nodes already recorded in the maximum bottleneck capacity record table, then update the maximum bottleneck capacity record table and the predecessor node record table, recording the candidate bottleneck capacity as the maximum bottleneck passage capacity from the starting point O to the adjacent node, and recording the already reached nodes before the adjacent node. Record the adjacent outgoing edges in the predecessor node record table and add the adjacent nodes to the priority queue; When repeatedly searching the outward edges of adjacent nodes, the node with the largest bottleneck capacity (stored in negative form) is continuously retrieved from the priority queue. If the endpoint D is not retrieved even after the priority queue is emptied, it indicates that the node is still in the current constraint graph replica. If no feasible path exists from O to D given a passable edge, return an empty path with a capacity of 0; otherwise, if the endpoint D is removed, return a path from the endpoint D. Starting from the predecessor node u in the path predecessor record table, we backtrack step by step to the starting point. During the backtracking process, the edge identifiers of the traversed edges are obtained sequentially to form a reverse path edge list. Then, this reverse path edge list is reversed to obtain the edge list starting from the origin. To the finish line The path edge identifier sequence; Output the path edge identifier sequence and the maximum bottleneck capacity corresponding to the endpoint D in the current constraint graph copy. In the middle, from the starting point To the finish line Among all passable paths, the path bottleneck passability is maximized by minimizing the passability of the path with the smallest edge.

[0009] Further, the adaptive determination of scoring weights in step S7 includes: preset default weights of capacity 0.4, construction cost 0.35, and scheme simplicity 0.25; when the traffic load is greater than 0.8, the capacity weight is adjusted to 0.55; when the budget is tight, the cost weight is adjusted to 0.50; when the construction period is tight, the simplicity weight is adjusted to 0.40; the normalized weighted score is: comprehensive score = capacity weight × (effective scheme capacity / maximum capacity) + cost weight × (1 - effective scheme cost coefficient / maximum cost coefficient) + simplicity weight × (1 - effective scheme operation number / maximum operation number), and then a service level penalty is added: deduct 0.1 when close to saturation, and deduct 0.3 when overloaded.

[0010] This invention also relates to an automatic configuration system for temporary traffic facilities during highway construction, comprising: The input module is used to receive construction constraint drawings and a list of unreachable OD (Original Design Location) pairs; The breakpoint diagnosis module is used to perform a bidirectional breadth-first search on unreachable OD pairs to locate forward reachable boundaries, reverse reachable boundaries and blocking elements, and to perform multi-breakpoint classification. The template library module is used to store predefined parametric temporary facility templates, including the drawing operation methods and engineering parameters for temporary ramps, bypasses, and temporary at-grade intersections; The filtering and matching module is used to filter candidate templates suitable for the current breakpoint from the template library based on the edge type and topological context at the breakpoint. The trial insertion verification module is used to trial insert candidate templates on a copy of the construction constraint drawing and verify the reachability of the path; The bottleneck detection module is used to calculate the maximum bottleneck capacity of the path after trial insertion and to determine whether the temporary facility becomes a bottleneck in capacity. The scoring and ranking module is used to rank the effective solutions based on a weighted score of accessibility, cost, and simplicity, and to output the final configuration solution list by adding service level penalties. Each configuration scheme in the list must include at least: ranking, facility type, connection start node, connection end node, number of lanes, design speed, traffic capacity, cost level, engineering operation description, overall score, service level level, and traffic capacity upgrade recommendations.

[0011] Furthermore, the breakpoint diagnosis module further includes a multi-breakpoint extended diagnosis unit, which, based on conventional breakpoint diagnosis, enumerates all simple paths from the breakpoint to the endpoint, evaluates the repair complexity by statistically analyzing the minimum blockage set size, and classifies breakpoints into single breakpoints, double breakpoints, or multiple breakpoints.

[0012] Furthermore, the adaptive weighting unit in the scoring and ranking module is specifically used to dynamically adjust the weight ratios of traffic capacity, construction cost, and scheme simplicity based on traffic flow, budget, and schedule requirements during the construction phase.

[0013] Furthermore, the bottleneck detection module uses the widest path algorithm to calculate the bottleneck capacity of the path from the starting point to the end point, and determines the service level based on the ratio of this capacity to the traffic volume. If the service level is overloaded or close to saturation and the bottleneck is located at a temporary facility, an upgrade template or improvement suggestion to adjust the cross-sectional utilization level is generated.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention employs a bidirectional breadth-first search for breakpoint diagnosis, accurately outputting forward reachable boundaries (near the break), reverse reachable boundaries (far the break), and blocking nodes / edges, thus providing a precise location description of the break. This diagnostic result directly provides reasonable connection pairings (start and end points) for subsequent template matching, avoiding the excessive computational complexity caused by exhaustively trying all node pairs in the graph in traditional methods, as well as the potential engineering inconsistencies of connecting temporary facilities to nodes unrelated to the break. This significantly improves the efficiency of temporary transportation facility configuration and the effectiveness of the solution.

[0015] This invention predefines engineering experience into 3 categories and 5 types of parameterized templates (temporary ramps, lane borrowing, and temporary at-grade intersections), and automatically selects applicable templates based on the edge type and topological context at the breakpoint, transforming facility selection from subjective judgment to repeatable and traceable automated decision-making.

[0016] This invention performs trial insertion operations on a deep copy of the constraint graph and immediately re-verifies reachability via BFS. The entire process can be completed in milliseconds and supports batch exploration and screening of multiple candidate templates and boundary node combinations.

[0017] This invention uses a normalized weighted scoring system based on three dimensions: traffic capacity assurance, construction cost, and scheme simplicity. It adaptively adjusts the weights according to the project context (traffic load, budget level, construction urgency) and adds service level penalties. The output is a list of configuration schemes sorted in descending order of comprehensive score, providing engineers with clear decision support.

[0018] This invention is based on a parametric directed graph model of interchanges (node ​​types V1~V8, edge types E1~E5), which can cover a variety of scenarios such as ramp breakage, main line breakage, and breakage at ramp ends and in the weaving zone, filling the technical gap in the automatic configuration of temporary traffic facilities during the construction period of interchanges.

[0019] This invention uses bottleneck detection to automatically identify whether a temporary facility itself becomes a bottleneck in the accessibility of an OD path, rather than simply verifying "accessibility". This avoids the deterioration of service levels caused by configuring temporary facilities with low accessibility. Attached Figure Description

[0020] Figure 1 This is a flowchart of the overall process of the present invention; Figure 2 This is a schematic diagram of bidirectional BFS breakpoint diagnosis; Figure 3 This is a sample diagram for inserting the template. Figure 4 This is a diagram illustrating the ranking of multiple objectives in an evaluation. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] Example The core process of this invention is as follows: Figure 1 As shown, an automatic configuration method for temporary traffic facilities during highway construction includes the following steps: S1, Receive construction constraint drawings Given a list of unreachable OD direction pairs, perform a bidirectional breadth-first search breakpoint diagnosis algorithm on each unreachable OD direction pair in the list to identify blocking nodes and blocking edges that cause path interruption, and output the breakpoint diagnosis results. This construction constraint diagram is generated by overlaying constraints such as closure, reduction, or temporary addition during the construction phase onto a parametric directed graph model of the interchange. The node set... This includes all functional points within the interchange, including but not limited to: mainline divergence point (V1), mainline merging point (V2), ramp divergence point (V3), ramp merging point (V4), weaving zone start point (V5), weaving zone end point (V6), ramp end (V7), and mainline control section (V8). (Edge set) This includes directed road segments connecting the aforementioned nodes, including but not limited to: mainline segments (E1), ramp segments (E2), deceleration lane segments (E4), and acceleration lane segments (E5). Each node and edge has a traffic status attribute, with selectable values ​​being normal traffic, closed, reduced capacity, and temporary new facilities. The unreachable OD (Original Direction) pair list represents traffic direction pairs that cannot be reached from the origin to the destination.

[0023] Bidirectional breadth-first search breakpoint diagnosis algorithms include: The first step is a forward breadth-first search: add the starting point O to the queue to be visited, and traverse the constraint graph starting from the current node in the queue to search for the adjacent nodes of the current node. If the accessibility property of the edge connecting the current node and the adjacent node is not closed, and the accessibility property of the adjacent node itself is not closed, then add the adjacent node to the queue to be visited, and continue to traverse the constraint graph to search starting from the next node in the queue.

[0024] After the search is completed, the set of forward reachable nodes is obtained. (i.e., all nodes reachable from the starting point) and the set of nodes on the positive boundary. (refer to Those that have at least one outgoing edge pointing to not The nodes in the diagram, or nodes whose outgoing edges are closed, represent the farthest positions that can be reached from the starting point, i.e., the "near end of the break"); where outgoing edges refer to edges that start from a node and point to other nodes, and other nodes do not include nodes that the node points to in the opposite direction from the starting point.

[0025] The second step is a reverse breadth-first search: add the endpoint D to the queue to be visited, start from the current node in the queue to traverse the constraint graph, and search for the adjacent nodes of the current node. If the accessibility property of the edge connecting the current node and the adjacent node is not closed, and the accessibility property of the adjacent node itself is not closed, then add the adjacent node to the queue to be visited, and continue to traverse the constraint graph from the next node in the queue to search.

[0026] After the search is completed, the set of nodes that can be reached in reverse is obtained. (i.e., all nodes that can be reached by traversing backwards) and the set of reverse boundary nodes. ( Those that have at least one entry point from outside The nodes in the equation, or nodes whose incoming edges are closed, represent the nearest position that can be traced back from the endpoint, i.e., the "far end of the break".

[0027] The third step is to identify blocking elements: This involves identifying the set of forward boundary nodes. For each node in the process, check the outgoing edges. If the subsequent adjacent node pointed to by the outgoing edge has a closed passage status, then the subsequent adjacent node is recorded as a blocked node; if the outgoing edge has a closed passage status, then the outgoing edge is recorded as a blocked edge.

[0028] Among them, the forward boundary node is the farthest position that can be reached from the starting point, and it is also the starting side (near end) of the fracture gap region; the reverse boundary node is the closest position that can be reached by tracing back from the end point, and it is also the ending side (far end) of the fracture gap region; the fracture gap is the gap between the two blocked by the closing element.

[0029] Step 4, Calculation of the fracture gap region: Take the difference between the reverse reachable set and the forward reachable set (here, the difference is the standard set subtraction operation AB = elements that belong to A but not to B, i.e., nodes that belong to the reverse reachable set but not to the forward reachable set), to obtain the fracture gap region:

[0030] The difference operation does not require the reverse reachable set to contain the forward reachable set. The two sets can be completely disjoint, partially overlapping, or one can contain the other; the difference operation is meaningful in all cases. When the two sets are disjoint, the difference result is the entire reverse set. The number of nodes in the fracture gap region reflects the size of the topological extent of the fracture's influence. The more nodes in the set, the larger the area affected by the break. Combining the breakpoint classification (single breakpoint / double breakpoint / multiple breakpoints) can help assess the complexity of the repair.

[0031] When construction constraints cause multiple paths to be closed simultaneously, a single bidirectional search can only locate the nearest breakpoint. To support multi-breakpoint scenarios, this method performs the following extended multi-breakpoint diagnosis on top of conventional breakpoint diagnosis: Path enumeration: Ignore closed state constraints and enumerate all simple paths from the starting point to the destination. The maximum number of simple paths is set to 50 to avoid combinatorial explosion. If no simple path exists, it is considered structurally unreachable.

[0032] Blocking set analysis: Count the number of edges with the closed state attribute that each simple path passes through, find the simple path with the fewest edges with the closed state attribute, and the number of edges with the closed state attribute of the selected simple path is the minimum blocking set size.

[0033] Breakpoints are classified based on the minimum blocking set size: if the minimum blocking set size is 1, the breakpoint level from the start to the end is a single breakpoint (only one temporary facility is needed to restore passage); if the minimum blocking set size is 2, the breakpoint level from the start to the end is a double breakpoint (two temporary facilities are required for restoration); if the minimum blocking set size is not less than 3, the breakpoint level from the start to the end is a multiple breakpoint (repair is complex and may require a re-evaluation of the construction plan). This breakpoint classification information provides engineers with a quick prediction of the repair complexity.

[0034] Step S2 ultimately outputs the breakpoint diagnosis results, including the starting point. ,end OD direction, set of positive boundary nodes Reverse boundary node set The set of blocked nodes, the set of blocked edges, the breakpoint level, and the diagnostic text description.

[0035] This bidirectional breadth-first search can not only determine unreachable locations, but also accurately locate the break points. The gap between the forward and reverse boundary nodes is the two ends that the temporary facility should connect, directly providing accurate start and end point node pairs for subsequent template matching.

[0036] S2. Retrieve all candidate templates from the predefined temporary facility template library. Each temporary facility template is represented by parametric attributes, used to quickly generate feasible temporary facility structures under different construction constraints. These parametric attributes include at least: template number, template type, new temporary edge type, new temporary node type, applicable breakpoint edge type, design speed range, lane number range, maximum allowable length, traffic capacity parameters, default engineering parameters, and cost parameters. Template types include temporary ramps, lane borrowing, and temporary at-grade intersections. For temporary ramps and temporary at-grade intersections, the preferred new temporary node type is the ramp end node; lane borrowing does not require a new temporary node. For temporary ramps and temporary at-grade intersections, the preferred new temporary edge type is the ramp segment; for lane borrowing, the preferred new temporary edge type is the mainline segment.

[0037] Each temporary facility template carries the following parameterized attributes (see Table 1): Table 1

[0038] The design speed range, lane number range, maximum allowable length, traffic capacity parameters, default engineering parameters, and cost parameters for different template types are shown in Table 2.

[0039] Table 2 Five Specific Templates

[0040] The engineering basis for the parameterized attributes in Table 2 is as follows: Design speed: The design speed of temporary ramps (Category A) is 40-60 km / h, referring to the minimum design speed requirement for ramps in Article 8.3.2 "Design Speed ​​of Ramps" of JTG D20-2017; the design speed of temporary ramps (Category B) is 80 km / h, referring to the main line construction speed limit standard.

[0041] Number of lanes: determined based on ramp traffic volume level. A1 single lane is applicable to ramps with a design hourly traffic volume ≤ 900 pcu / h, and A2 double lane is applicable to ramps with a design hourly traffic volume > 900 pcu / h.

[0042] Traffic capacity: 900 pcu / h for single-lane ramps (JTG D20-2017 basic traffic capacity for ramps), and 1800 pcu / h for two-lane ramps; for shared lanes, the basic traffic capacity corresponding to the design speed of 80 km / h on the main line is taken as 1600 pcu / h per lane.

[0043] Default length: 450-600m for temporary ramps (to meet the minimum length requirement for ramps), and 800m for shared lanes (to meet the minimum combined length of transition section + transition section + shared lane section).

[0044] Cost coefficient: a relative value, with 1.0 as the baseline for the B1 lane-borrowing passage (the simplest: only requiring an opening in the central median strip and the installation of signs and markings), and the others increasing according to the complexity of construction.

[0045] The above parameters are all default values ​​and can be adjusted according to specific project conditions.

[0046] S3. Temporary Facility Template Filtering (Two-Level Filtering) Level 1: Edge type matching Traverse the set of forward boundary nodes For each node, extract the types of all associated edges (including incoming and outgoing edges) to form a set of breakpoint boundary edge types. For each candidate template in the temporary facility template library, check its applicable list of breakpoint edge types. Does an intersection exist? If an intersection exists, retain the candidate template as a preliminary candidate template; otherwise, discard it.

[0047] Level 2: Topology Context Compatibility Filtering For the initial screening of candidate templates, perform the following topology rule checks according to their template type: Rule 1 (Temporary Ramp Type): The starting point type of the candidate template connected to the forward boundary node is a branch point (V1 or V3) or a weaving zone starting point (V5); the ending point type of the candidate template connected to the reverse boundary node is a ramp end (V7). If the conditions are not met, the template is filtered.

[0048] Rule 2 (Borrowing Lanes): The starting point of the candidate template connecting to the forward boundary node and the ending point of the candidate template connecting to the reverse boundary node are both of type mainline related nodes (V1, V2, or V8); and in the construction constraint drawing, there is a corresponding opposing mainline edge (i.e., opposing mainline segment type edge E1) between the starting and ending points of the candidate template connecting to the forward and reverse boundary nodes respectively. This condition ensures that there is an opposing lane available for borrowing. If this condition is not met, the lane is filtered.

[0049] Rule 3 (Temporary Level Crossing): The starting point of the candidate template connecting the forward boundary node and the ending point of the candidate template connecting the reverse boundary node should not both be mainline control section nodes (V8). If both are mainline control section nodes V8, they should be filtered out because the area between the two mainline control section nodes V8 is a high-speed mainline segment, and setting up a level crossing there would pose a serious safety hazard and have mismatched traffic capacity.

[0050] After two levels of filtering, the final set of candidate templates is obtained.

[0051] S4, Trial Insertion Construct a deep copy of the construction constraint diagram and find the set of forward boundary nodes. With the set of reverse boundary nodes Each pair of candidate boundary node combinations ,in , ,and In candidate boundary node combination Perform trial insertion operations between each candidate template in the candidate template set, that is, for each candidate template and each pair of boundary node combinations. Try inserting temporary nodes and / or temporary edges on the constraint graph copy.

[0052] Specifically, firstly, the original construction constraint drawings... Perform a deep copy to obtain the candidate configuration diagram (i.e., a copy of the construction constraint diagram). Subsequently, based on the template type of the candidate template, [the following is executed / selected]... Insert the corresponding temporary nodes and / or temporary edges. When the template type is Temporary Plane Intersection (C1), in Add a temporary intermediate connection node The node type is set to V7 (ramp end); in and between, and A temporary edge is added between each section, both of type E2 (ramp section). The length of each temporary edge is half of the default template length (200m), i.e., 100m. The number of lanes, design speed, and traffic capacity use the default template values. When the template type is a temporary ramp (A1 / A2) or a lane-sharing section (B1 / B2), it is directly added... and A temporary edge is added between them, with edge types of E2 (temporary ramp) or E1 (passing through the other lane). The length, number of lanes, design speed, and traffic capacity all use the default template values.

[0053] All temporarily added elements are marked as "temporarily added facilities" in their attributes to distinguish them from existing normal or closed elements. Through step S5, multiple different candidate configuration diagrams can be constructed without modifying the original construction constraint diagram for subsequent verification.

[0054] S5, Reachability Revalidation For each copy of the construction constraint drawing after trial insertion Re-execute from the starting point To the finish line A breadth-first search is performed to verify reachability (the closure markers of temporary facilities are not considered, as temporary facilities are designed to restore access). If the search is successful (i.e., a path consisting entirely of non-closed edges exists), the solution (template ID, connected node pairs, graph structure after insertion, accessibility, etc.) is recorded as a valid candidate solution; if it is still unreachable, the solution is discarded. All valid candidate solutions are initially sorted in descending order of accessibility and ascending order of cost coefficient.

[0055] S6. Traffic Capacity Bottleneck Detection For each valid candidate solution that passes the accessibility verification in step S5, a capacity bottleneck detection is performed before the comprehensive scoring is executed to assess whether the solution meets the target traffic demand, including the following steps: Step 1, Path Bottleneck Search: The widest path algorithm (a variant of Dijkstra's algorithm that maximizes the minimum edge capacity of a path) is used to calculate the optimal path from the starting point O to the ending point D. This yields the set of path edges and the path bottleneck capacity for each edge. The path bottleneck capacity is the minimum capacity of all edges on the path.

[0056] The path bottleneck search algorithm process is as follows: Initialization: Create a maximum bottleneck capacity record table, recording data from the starting point O to the constraint graph replica. The maximum bottleneck capacity among the discovered paths at each node, constraint graph replica. It includes the nodes and / or temporary edges added after the trial insertion in step S4; the maximum bottleneck capacity corresponding to the starting point O is initialized to positive infinity, indicating that the starting point itself does not limit the path's traversal capacity; other nodes whose maximum bottleneck capacity is not recorded are treated as 0. A path predecessor record table is established to record path backtracking information. Records in the path predecessor record table are binary tuples containing the reached nodes. The predecessor node u and the path from the predecessor node u to the reached node The identifiers of the edges traversed are used, and the predecessor record table of the initial path is empty; Establish a priority queue, add the starting point O and its maximum bottleneck capacity to the priority queue, store the maximum bottleneck capacity of each node added to the priority queue in negative form, and establish a set of confirmed nodes to record the nodes whose maximum bottleneck capacity has been determined. When the priority queue is not empty, the node with the largest current bottleneck capacity is popped from the priority queue and designated as the reached node. If the set of nodes has been confirmed to already exist, the node has been reached. If the node is reached, skip it; otherwise, proceed to the next node. Add to the set of confirmed nodes, if the node has been reached. If the endpoint is D, then the process ends. Search reached node For each adjacent outgoing edge, if an adjacent node is found, determine whether the adjacent outgoing edge and the adjacent node satisfy any of the following skip conditions: the confirmed node set already contains an adjacent node; the state attribute of the adjacent node or the adjacent outgoing edge is closed. If any of the above conditions are met, skip the adjacent outgoing edge. For any passable adjacent outgoing edges that have not been skipped, calculate the number of nodes reached. The candidate bottleneck capacity is determined by the number of adjacent nodes and recorded in the maximum bottleneck capacity table. The candidate bottleneck capacity is the capacity of the nodes that have been reached. The minimum value of the maximum bottleneck capacity and the passage capacity of the adjacent passable outgoing edges; If the candidate bottleneck capacity is better than the maximum bottleneck capacity of other adjacent nodes already recorded in the maximum bottleneck capacity record table, then update the maximum bottleneck capacity record table and the predecessor node record table, recording the candidate bottleneck capacity as the maximum bottleneck passage capacity from the starting point O to the adjacent node, and recording the already reached nodes before the adjacent node. Record the adjacent outgoing edges in the predecessor node record table and add the adjacent nodes to the priority queue; When repeatedly searching the outward edges of adjacent nodes, the node with the largest bottleneck capacity (stored in negative form) is continuously retrieved from the priority queue. If the endpoint D is not retrieved even after the priority queue is emptied, it indicates that the node is still in the current constraint graph replica. If no feasible path exists from O to D given a passable edge, return an empty path with a capacity of 0; otherwise, if the endpoint D is removed, return a path from the endpoint D. Starting from the predecessor node u in the path predecessor record table, we backtrack step by step to the starting point. During the backtracking process, the edge identifiers of the traversed edges are obtained sequentially to form a reverse path edge list. Then, this reverse path edge list is reversed to obtain the edge list starting from the origin. To the finish line The path edge identifier sequence; Output the path edge identifier sequence and the maximum bottleneck capacity corresponding to the endpoint D in the current constraint graph copy. In the middle, from the starting point To the finish line Among all passable paths, the path bottleneck passability is maximized by minimizing the passability of the path with the smallest edge.

[0057] Step 2, Bottleneck Edge Identification: Find the edge with the minimum throughput in the path edge identifier sequence. As a bottleneck edge. If the bottleneck edge is a temporary traffic facility added in step S5, then mark the temporary facility as a path bottleneck; otherwise, mark it as an existing road network bottleneck.

[0058] Step 3, Level of Service Determination: If the traffic volume in the OD direction is known... (Unit: pcu / h), then calculate the load ratio:

[0059] It is the maximum flow rate that the entire path from the starting point to the end point can carry.

[0060] The service level will be determined according to the following rules: when At that time, the service level is recorded as overloaded; when At that time, the service level is recorded as near saturation; when At that time, the service level was recorded as acceptable; when At that time, the service level was recorded as adequate.

[0061] Step 4, capacity recommendation generation: If the temporary facility is the bottleneck and the service level is overloaded or close to saturation, improvement recommendations are generated. For example, if the temporary facility constitutes a capacity bottleneck, it is recommended to upgrade to a template with a higher capacity (such as upgrading from A1 to A2), or increase the number of lanes, increase the design speed, or improve the cross-sectional utilization level.

[0062] Cross-sectional utilization level refers to the proportion of effective width in a road cross-section actually used for traffic. Under normal circumstances, only the driving lanes are used for traffic in a road cross-section, while the shoulders (hard shoulders and unpaved shoulders) are only used for emergency parking. Therefore, the normal cross-sectional utilization level is approximately 60-70% (driving lane width / total cross-sectional width). Specific engineering measures to improve cross-sectional utilization include: 1. Using hard shoulders as temporary driving lanes. JTG / T 3392-2022 "Highway Maintenance Safety Operation Regulations" clearly stipulates that hard shoulders can be converted into temporary driving lanes during construction, equivalent to adding one lane; 2. Narrowing lane widths to add more lanes, such as narrowing the standard lane width from 3.75m to 3.25m, adding one more lane within the same total cross-sectional width; 3. Using tidal flow lanes, dynamically adjusting lane direction allocation according to different morning and evening peak directions. These measures do not change the total road width but increase the number of effective lanes used for traffic, thereby improving traffic capacity.

[0063] The final bottleneck detection output includes: Bottleneck location, whether it is a temporary bottleneck, load ratio, service level, and improvement suggestions.

[0064] S7. Context-Adaptive Multi-Objective Scoring Ranking Valid candidate solutions that pass the validation process are scored using a normalized weighted average. The weights are adaptively adjusted based on the project context.

[0065] The first step is to determine the adaptive weights: Preset default weights are: traffic capacity 0.4, construction cost 0.35, and scheme simplicity 0.25. Based on the project context parameters, the weights are adaptively adjusted according to the following rules: In high-traffic scenarios (traffic load factor greater than 0.8): the capacity weight is increased to 0.55, cost is reduced to 0.25, and simplicity is reduced to 0.20. Reason: Prioritize ensuring traffic capacity.

[0066] In budget-constrained scenarios: the cost weighting is increased to 0.50, traffic capacity is reduced to 0.30, and simplicity is 0.20. Reason: cost control takes precedence.

[0067] In scenarios with tight deadlines: the weight of simplicity is increased to 0.40, traffic capacity to 0.35, and cost to 0.25. Reason: Rapid implementation is prioritized.

[0068] The weight adjustment logic can be preset by engineers or automatically identified by the system based on construction phase information (estimated flow, budget, and schedule requirements).

[0069] The second step is normalized scoring: This involves calculating the maximum possible accessibility, the maximum cost coefficient, and the maximum number of operations among all valid candidate solutions. For each valid candidate solution, the scores for these three components are calculated as follows: Capacity score = Capacity of the effective route ÷ Maximum capacity; Cost score = 1 - (cost coefficient of the effective solution ÷ maximum cost coefficient); Simplicity score = 1 - (number of operands in the effective solution ÷ maximum number of operands); if all solutions have 1 operand, the simplicity score is uniformly 1.0; Overall score = Traffic capacity weight × Traffic capacity score + Cost weight × Cost score + Simplicity weight × Simplicity score.

[0070] The third step is to add service level penalties: using the results of bottleneck detection (S7), score penalties are applied to effective solutions with poor service levels: 0.1 points are deducted when approaching saturation and 0.3 points are deducted when overloaded.

[0071] Step 4, Sorting Output: Sort all valid candidate solutions from highest to lowest according to the final comprehensive score, and the one with the highest score is the preferred solution. The cost level is divided according to the cost coefficient: not more than 1.0 is "low", 1.0 to 2.0 is "medium", and more than 2.0 is "high".

[0072] S8, Output Temporary Facility Configuration Scheme List Each plan includes the following information items (see Table 3): Table 3

[0073] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatically configuring temporary traffic facilities during highway construction, characterized in that, Includes the following steps: S1: Input the construction constraint diagram and the list of unreachable OD direction pairs. For each unreachable OD direction pair in the list, execute a bidirectional breadth-first search breakpoint diagnosis algorithm to identify the blocking nodes and blocking edges that cause path interruption, and output the breakpoint diagnosis results. The construction constraint diagram is a graph data structure generated by superimposing the construction stage closure, reduction or temporary addition of constraints on the parametric directed graph model of the interchange. The nodes and edges are all attached with traffic status attributes. OD direction represents the direction of traffic flow from the origin to the destination; The unreachable OD (Original Direction) pair list represents traffic direction pairs that cannot be reached from the origin to the destination; breakpoint diagnosis results include: origin. ,end The OD direction, the set of forward boundary nodes, and the set of reverse boundary nodes; the set of forward boundary nodes represents the farthest boundary node that can be reached from the starting direction, and the set of reverse boundary nodes represents the nearest boundary node that can be traced back from the ending direction. S2: Retrieve the parameterized attributes of all candidate templates from the predefined temporary facility template library; the temporary facility template library contains multiple types of temporary facilities, and the parameterized attributes of each temporary facility template include template number, template type, new temporary edge type, new temporary node type, applicable breakpoint edge type, design speed range, lane number range, maximum allowable length, traffic capacity parameters, default engineering parameters, and cost parameters. Template types include temporary ramps, bypass traffic, and temporary at-grade intersections. The new temporary node type for temporary ramps and temporary at-grade intersections is ramp end node, while the new temporary node type for bypass traffic is no new temporary node. The new temporary edge type for temporary ramps and temporary at-grade intersections is ramp segment, while the new temporary edge type for bypass traffic is mainline segment. S3: Obtain a set of edge types for the associated edges of the forward boundary node set, and retain candidate templates whose applicable breakpoint edge types intersect with this set as initial candidate templates; perform topology rule checks based on the initial candidate template types. For temporary ramp templates, the starting point of the initial candidate template connecting to the forward boundary node must be a divergence point or the starting point of the weaving zone, and the ending point of the initial candidate template connecting to the reverse boundary node must be the end of the ramp; for bypass templates, the starting and ending points of the initial candidate template connecting to the forward and reverse boundary nodes must be mainline-related nodes and there must be opposing mainline edges in the construction constraint diagram; for temporary at-grade intersection templates, the starting and ending points of the initial candidate template connecting to the forward and reverse boundary nodes must not both be mainline control section nodes. S4: On the deep copy of the construction constraint diagram, try to insert the final candidate template in each pair of positive and negative boundary node combinations, and add temporary nodes and / or temporary edges. S5: Re-execute breadth-first search reachability verification for each copy of the construction constraint diagram after trial insertion. If there is a path from the starting point to the end point, record it as a valid candidate solution. S6: Perform capacity bottleneck detection for each valid candidate solution that passes the accessibility verification, including calculating the bottleneck capacity of the path using the widest path algorithm, identifying the bottleneck edge, and determining the service level level based on the load ratio calculated by the OD traffic volume and the maximum flow. If the temporary facility is the bottleneck and the service level is poor, generate improvement suggestions. S7: Adaptively determine the scoring weights based on the engineering context, normalize and weight the valid candidate solutions that have passed the verification according to traffic capacity, construction cost and solution simplicity, and sort them after adding service level penalties; S8: Output a sorted list of temporary facility configuration schemes.

2. The method according to claim 1, characterized in that, The breakpoint diagnosis results also include: a set of blocked nodes, a set of blocked edges, the breakpoint level, and a diagnostic text description; the bidirectional breadth-first search breakpoint diagnosis algorithm includes: S2.1: Forward Breadth-First Search: Starting from the starting point, traverse the construction constraint graph and search for the adjacent nodes of the current node. When the passage state of the edge connecting the current node and the adjacent node is not closed and the passage state of the adjacent node itself is not closed, the adjacent node is added to the queue to be visited, and the set of forward reachable nodes and the set of forward boundary nodes are obtained. S2.2: Reverse Breadth-First Search: Starting from the endpoint, traverse the construction constraint graph in reverse order, search for the adjacent nodes of the current node. When the passage state of the edge connecting the current node and the adjacent node is not closed and the passage state of the adjacent node itself is not closed, the adjacent node is added to the queue to be visited, and the set of reverse reachable nodes and the set of reverse boundary nodes are obtained. S2.3: Blocking Element Identification: Check the outgoing edges of the forward boundary nodes. If the subsequent adjacent node pointed to by the outgoing edge is closed, then the subsequent adjacent node is recorded as a blocking node; if the outgoing edge itself is closed, then the outgoing edge is recorded as a blocking edge. S2.4: Fault gap region calculation: The fault gap region is obtained by taking the difference between the reverse reachable set and the forward reachable set. The number of nodes in the fault gap region reflects the size of the topological range affected by the fault.

3. The method according to claim 2, characterized in that, The breakpoint level is obtained through multi-breakpoint extended diagnosis: when construction constraints cause multiple paths to be closed simultaneously, path enumeration, blocking set analysis, and breakpoint classification are performed to obtain the classification results of single breakpoint, double breakpoint, or multiple breakpoint; the breakpoint classification is based on the minimum blocking set size, where a minimum blocking set of 1 indicates a single breakpoint, 2 indicates a double breakpoint, and 3 or more indicates multiple breakpoints; the minimum blocking set size is the minimum number of closed edges in all enumerated paths.

4. The method according to claim 1, characterized in that, In step S6, the bottleneck edge is the edge with the minimum capacity in the set of path edges; the service level is divided into four levels according to the load ratio: overloaded, near saturation, acceptable, and sufficient. The widest path algorithm aims to maximize the throughput of the path with the minimum edge, and uses a path bottleneck search algorithm to search for the throughput of the path bottleneck from the starting point to the ending point. Path bottleneck search algorithms include: Initialization: Create a maximum bottleneck capacity record table, recording data from the starting point O to the constraint graph replica. The maximum bottleneck capacity among the discovered paths at each node, constraint graph replica. It includes the nodes and / or temporary edges added after the trial insertion in step S4; the maximum bottleneck capacity corresponding to the starting point O is initialized to positive infinity, indicating that the starting point itself does not limit the path's traversal capacity; other nodes whose maximum bottleneck capacity is not recorded are treated as 0. A path predecessor record table is established to record path backtracking information. Records in the path predecessor record table are binary tuples containing the reached nodes. The predecessor node u and the path from the predecessor node u to the reached node The identifiers of the edges traversed are used, and the predecessor record table of the initial path is empty; Establish a priority queue, add the starting point O and its maximum bottleneck capacity to the priority queue, store the maximum bottleneck capacity of each node added to the priority queue in negative form, and establish a set of confirmed nodes to record the nodes whose maximum bottleneck capacity has been determined. When the priority queue is not empty, the node with the largest current bottleneck capacity is popped from the priority queue and designated as the reached node. If the node set has been confirmed to already have a reached node If the node is reached, skip it; otherwise, proceed to the next node. Add to the set of confirmed nodes, if the node has been reached. If the endpoint is D, then the process ends. Search reached node For each adjacent outgoing edge, if an adjacent node is found, determine whether the adjacent outgoing edge and the adjacent node satisfy any of the following skip conditions: the confirmed node set already contains an adjacent node; the state attribute of the adjacent node or the adjacent outgoing edge is closed. If any of the above conditions are met, skip the adjacent outgoing edge. For any passable adjacent outgoing edges that have not been skipped, calculate the number of nodes reached. The candidate bottleneck capacity is determined by the number of adjacent nodes and recorded in the maximum bottleneck capacity table. The candidate bottleneck capacity is the capacity of the nodes that have been reached. The minimum value of the maximum bottleneck capacity and the passage capacity of the adjacent passable outgoing edges; If the candidate bottleneck capacity is better than the maximum bottleneck capacity of other adjacent nodes already recorded in the maximum bottleneck capacity record table, then update the maximum bottleneck capacity record table and the predecessor node record table, recording the candidate bottleneck capacity as the maximum bottleneck passage capacity from the starting point O to the adjacent node, and recording the already reached nodes before the adjacent node. Record the adjacent outgoing edges in the predecessor node record table and add the adjacent nodes to the priority queue; When repeatedly searching the outward edges of adjacent nodes, the node with the largest bottleneck capacity (stored in negative form) is continuously retrieved from the priority queue. If the endpoint D is not retrieved even after the priority queue is emptied, it indicates that the node is still in the current constraint graph replica. If no feasible path exists from O to D given a passable edge, return an empty path with a capacity of 0; otherwise, if the endpoint D is removed, return a path from the endpoint D. Starting from the predecessor node u in the path predecessor record table, we backtrack step by step to the starting point. During the backtracking process, the edge identifiers of the traversed edges are obtained sequentially to form a reverse path edge list. Then, this reverse path edge list is reversed to obtain the edge list starting from the origin. To the finish line The path edge identifier sequence; Output the path edge identifier sequence and the maximum bottleneck capacity corresponding to the endpoint D in the current constraint graph copy. In the middle, from the starting point To the finish line Among all passable paths, the path bottleneck passability is maximized by minimizing the passability of the path with the smallest edge.

5. The method according to claim 1, characterized in that, The adaptive determination of scoring weights in step S7 includes: preset default weights of capacity 0.4, construction cost 0.35, and scheme simplicity 0.25; when the traffic load is greater than 0.8, the capacity weight is adjusted to 0.55; when the budget is tight, the cost weight is adjusted to 0.50; when the construction period is tight, the simplicity weight is adjusted to 0.40; the normalized weighted score is: comprehensive score = capacity weight × (effective scheme capacity / maximum capacity) + cost weight × (1 - effective scheme cost coefficient / maximum cost coefficient) + simplicity weight × (1 - effective scheme operation number / maximum operation number), and then a service level penalty is added: deduct 0.1 when close to saturation, and deduct 0.3 when overloaded.

6. An automatic configuration system for temporary traffic facilities during highway construction, characterized in that, include: The input module is used to receive construction constraint drawings and a list of unreachable OD (Original Design Location) pairs; The breakpoint diagnosis module is used to perform a bidirectional breadth-first search on unreachable OD pairs to locate forward reachable boundaries, reverse reachable boundaries and blocking elements, and to perform multi-breakpoint classification. The template library module is used to store predefined parametric temporary facility templates, including the drawing operation methods and engineering parameters for temporary ramps, bypasses, and temporary at-grade intersections; The filtering and matching module is used to filter candidate templates suitable for the current breakpoint from the template library based on the edge type and topological context at the breakpoint. The trial insertion verification module is used to trial insert candidate templates on a copy of the construction constraint drawing and verify the reachability of the path; The bottleneck detection module is used to calculate the maximum bottleneck capacity of the path after trial insertion and to determine whether the temporary facility becomes a bottleneck in capacity. The scoring and ranking module is used to rank the effective solutions based on a weighted score of accessibility, cost, and simplicity, and to output the final configuration solution list by adding service level penalties. Each configuration scheme in the list must include at least: ranking, facility type, connection start node, connection end node, number of lanes, design speed, traffic capacity, cost level, engineering operation description, overall score, service level level, and traffic capacity upgrade recommendations.

7. The system according to claim 6, characterized in that, The breakpoint diagnosis module further includes a multi-breakpoint extended diagnosis unit, which, based on conventional breakpoint diagnosis, enumerates all simple paths from the breakpoint to the endpoint, evaluates the repair complexity by statistically analyzing the minimum blockage set size, and classifies breakpoints into single breakpoints, double breakpoints, or multiple breakpoints.

8. The system according to claim 6, characterized in that, The adaptive weighting unit in the scoring and ranking module is specifically used to dynamically adjust the weight ratios of traffic capacity, construction cost, and scheme simplicity based on traffic flow, budget, and schedule requirements during the construction phase.

9. The system according to claim 6, characterized in that, The bottleneck detection module uses the widest path algorithm to calculate the bottleneck capacity of the path from the starting point to the end point, and determines the service level based on the ratio of this capacity to the traffic volume. If the service level is overloaded or close to saturation and the bottleneck is located at a temporary facility, an upgrade template or improvement suggestions for adjusting the cross-sectional utilization level are generated.

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