Road network facility image-based management and control measure determination method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a road network facility image-based control measure determination method and device, electronic equipment and storage medium. The method determines a target facility corresponding to position information in a control instruction in response to a trigger control instruction. The method can determine a set of facilities to be controlled corresponding to the target facility based on a road network facility image knowledge base, thereby limiting the control measures to the set of facilities to be controlled related to the target facility, reducing the uncertainty caused by full network search and experience trial and error. Furthermore, based on the facility state parameters of the target facility and the facilities to be controlled within a preset time period, a set of initial executable control measures that match are quickly determined. Further, the initial executable control measure set with the best evaluation result is selected as the target control measure under the joint constraints of operation constraints and operation constraints, so that a fast risk-controllable control output can be achieved, the control consistency is improved, and the comprehensive operation and maintenance cost is reduced.

Description

Technical Field

[0001] This disclosure relates to the field of intelligent transportation technology, specifically to a method, apparatus, electronic device, and storage medium for determining control measures based on road network infrastructure profiling. Background Technology

[0002] Traffic control refers to comprehensive management measures taken for road network facilities to maintain traffic efficiency and safety and to respond to emergencies. In existing technologies, traffic control largely relies on manual experience or static rules, which are insufficiently aligned with actual road network operating conditions, demand structure, and facility constraints. This makes it difficult to measure traffic efficiency, safety, and operational impact in a timely and accurate manner, limiting the precision and effectiveness of control measures and severely hindering the improvement of traffic efficiency, operational safety, and operational revenue. Summary of the Invention

[0003] This disclosure presents a method, apparatus, electronic device, and storage medium for determining control measures based on road network infrastructure profiling.

[0004] The first aspect of this disclosure proposes a method for determining the target facility corresponding to the location information in a control command in response to a triggered control command; and for determining a set of facilities to be controlled corresponding to the target facility based on a preset road network facility profile knowledge base. Obtain the facility status parameters of the target facility and the set of facilities to be managed within a preset time period; determine the initial set of executable management measures corresponding to the facility status parameters of the set of facilities to be managed based on the road network facility profile knowledge base; Obtain preset constraints, and select the best evaluation result among the preset constraints from the initial set of executable control measures as the target control measure; preset constraints include operational constraints and management constraints.

[0005] A second aspect of this disclosure provides a device for determining control measures based on road network infrastructure profiling, comprising: The control trigger module is used to respond to the trigger control command, determine the target facility corresponding to the location information in the control command; and determine the set of facilities to be controlled corresponding to the target facility based on the preset road network facility profile knowledge base. The initial executable control measure set determination module is used to obtain the facility status parameters of the target facility and the set of facilities to be controlled within a preset time period; and to determine the initial executable control measure set corresponding to the facility status parameters of the set of facilities to be controlled based on the road network facility profile knowledge base. The target control measure determination module is used to obtain preset constraints and select the best evaluation result among the preset constraints from the initial set of executable control measures as the target control measure; the preset constraints include operational constraints and management constraints.

[0006] According to a third aspect of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is executed by the processor to cause the electronic device to perform the method as described in the first aspect.

[0007] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, on which a computer program is stored, the program being executed by a processor to implement the method of the first aspect.

[0008] The technical solutions provided in this disclosure have at least the following technical effects or advantages: By employing the method disclosed herein, in response to a triggered control command, the target facility corresponding to the location information in the control command is determined. Based on a road network facility profile knowledge base, a set of facilities to be controlled corresponding to the target facility can be identified, thereby limiting control measures to the set of facilities to be controlled related to the target facility, reducing the uncertainty caused by network-wide search and trial-and-error. Furthermore, based on the facility status parameters of the target facility and the facilities to be controlled within a preset time period, a matching set of initial executable control measures is quickly determined, avoiding strategies that are unimplementable or incompatible with facility capabilities. Under the joint constraints of operational and management constraints, the best evaluation result of the initial set of executable control measures is selected as the target control measure. Thus, control outputs that are rapidly generated, implementable, risk-controllable, and traceable can be achieved, improving control consistency and reducing overall operation and maintenance costs.

[0009] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0010] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this disclosure. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart of a method for determining road control measures based on road network infrastructure profiling, provided in an embodiment of this disclosure, is shown. Figure 2 A schematic diagram of a method for determining road control measures based on road network infrastructure profiling, provided in an embodiment of this disclosure, is shown. Figure 3 A schematic diagram of the structure of a control measure determination device based on road network infrastructure profiling provided in another embodiment of this disclosure is shown; Figure 4A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure is shown; Figure 5 A schematic diagram of a storage medium provided according to an embodiment of the present disclosure is shown. Detailed Implementation

[0011] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0012] It should be noted that, unless otherwise stated, the technical or scientific terms used in this disclosure shall have the ordinary meaning as understood by one of ordinary skill in the art to which this disclosure pertains.

[0013] This disclosure proposes a method for determining road control measures based on road network infrastructure profiling. For example... Figure 1 As shown in the figure, the method for determining road control measures based on road network infrastructure profiling in this disclosure may include the following steps: In step S11, in response to triggering a control command, the target facility corresponding to the location information in the control command is determined; and the set of facilities to be controlled corresponding to the target facility is determined based on a preset road network facility profile knowledge base.

[0014] In step S12, the facility status parameters of the target facility and the set of facilities to be managed within a preset time period are obtained; the initial set of executable management measures corresponding to the facility status parameters of the set of facilities to be managed is determined based on the road network facility profile knowledge base.

[0015] In step S13, preset constraints are obtained, and the best evaluation result among the preset constraints is selected from the initial set of executable control measures as the target control measure; the preset constraints include operational constraints and management constraints.

[0016] For example, the conditions for triggering a control command can be that at least one of the following events occurs at the corresponding facility: speed / occupancy / queueing exceeds the corresponding threshold, related event is reported, or there is a sudden surge in demand. The facility where the control command is triggered is the target facility. After the control command is triggered, based on the target facility, a set of facilities to be controlled that affect the traffic flow of that target facility is determined. The target facility and its corresponding set of facilities to be controlled can be retrieved from a pre-built road network facility profile knowledge base.

[0017] The road network facility profiling knowledge base is constructed according to the granularity of road network facilities. Each road network target facility corresponds to a functional constraint profile. The functional constraint profile includes functional description parameters, operational constraint parameters, management constraint parameters, candidate measures and triggering conditions, cold start seed measures and priorities. The cold start seeds include strategies when various parameters are unknown during the initial startup.

[0018] After identifying the target facility, a set of facilities to be managed corresponding to the target facility can be selected from the road network facility profile knowledge base. Based on operational and management constraints, the optimal management measures for the set of facilities to be managed can then be determined.

[0019] In some embodiments, the road network facility profile knowledge base can be constructed as follows: a road network facility profile knowledge base is pre-constructed; wherein, the road network facility profile knowledge base includes a functional constraint profile of each target facility; the functional constraint profile includes a first mapping relationship and a second mapping relationship; the first mapping relationship refers to the mapping relationship between the target facility and the corresponding facility to be managed; the second mapping relationship refers to the mapping relationship between the facility status parameters corresponding to the target facility, the facility status parameters corresponding to the facility to be managed, and the set of executable control measures.

[0020] The first mapping relationship is constructed as follows: Obtain the OD set carried by the target facility; find facilities in the facility set whose OD set is equivalent to that carried by the target facility, and use these facilities as the initial set of facilities to be managed; for any initial facility to be managed, calculate the management score of the initial facility to be managed based on the traffic flow overlap parameter and traffic flow diversion parameter between the initial facility to be managed and the target facility; sort the initial facilities to be managed from high to low based on their management scores, and determine the top... The initial set of facilities to be managed is the target facility's set of facilities to be managed. The value is an integer greater than or equal to 1. The second mapping relationship is constructed in the following way: obtain the control measures of each facility to be controlled, and construct a set of candidate control measures; perform simulation evaluation based on the facility status parameters of the target facility and each candidate control facility, and take the candidate control measures that meet the preset constraints as the set of executable control measures; associate the target facility, the facility status parameters of each facility to be controlled and the corresponding set of executable control measures to obtain the second mapping relationship.

[0021] For example, target facilities include mainline sections, ramps, interchanges, toll / gantry structures, service areas, bridges, tunnels, and other road network transportation facilities. For a given OD (Origin-Destination), each transportation facility undertakes a different traffic flow transport function; some are core carrying units, while others are regulating and serving units. Different transportation facilities constitute competition or cooperation in fulfilling the given OD demand. Here, OD represents the path trajectory from the origin to the destination in the road network topology, and this path trajectory includes multiple different types of transportation facilities.

[0022] The target facility's OD set refers to all ODs passing through the target facility. This OD set can be obtained from the corresponding road network topology in the road network facility profile knowledge base. The target facility's supporting role for each OD in terms of accessibility, passability, and substitutability collectively constitutes the functional definition of the target facility. Based on the multiple optional paths between ODs and the multidimensional coupling relationships between the facilities contained in those paths, we can quantify the functional value and criticality of the facility for a specific OD or OD set. Furthermore, while ensuring the road network functionality corresponding to key OD sets, we can identify the complementary, substitutive, and competitive relationships between different facilities.

[0023] For example, the functional value of facilities to the OD set can be categorized into three types: traversal, dependence, and substitutability. Crossing OD Subset : Characterizes the OD that must pass through the facility in all optimal or acceptable generalized cost paths; Dependency on OD subset This characterizes the relative increase in the generalized cost of the optimal acceptable path for an OD (Original Development Path) exceeding a threshold once the facility's capacity is weakened or becomes unavailable. OD; Alternative OD subsets There is an acceptable alternative route that does not involve this facility, and the relative cost increase does not exceed a threshold. OD.

[0024] Among them, the generalized cost can be composed of a weighted average of factors such as time, toll fees, and reliability; Set thresholds for business operations; Characterization facilities.

[0025] The functional value of a facility depends on the importance of OD (Original Design Site), and this disclosure introduces a weighting factor. To define the importance of OD. The definition considers the OD's traffic (or demand share) and business-side weights (strategic importance, freight share, time period importance, etc.): (1) in, Characterizes the initial weighting coefficients corresponding to OD. Parameters are set by the user.

[0026] Let the set of OD be To normalize formula (1), we get: (2) Defining the importance weight of any OD Based on this, this disclosure defines facilities from several dimensions, including coverage, dependence intensity, irreplaceability, and substitutability. Functional attributes: Coverage representation The importance of service OD: (3) Dependency strength characterizes the importance of OD to this Degree of dependence: (4) Exclusivity / non-substitutability rate characterization after this And OD that is difficult to replace: (5) in is the numerical stability constant.

[0027] Substitutability characterization and this Equivalent facilities' capacity to absorb the OD (Original Demand) they undertake: (6) in, Defined The equivalent set of facilities, Facilities in the equivalent facility set The remaining capacity share (available margin under the same caliber). Consistency / reliability weights are applied (considering vehicle type / traffic restrictions / toll consistency, etc.).

[0028] In summary, four functional attributes corresponding to facilities have been defined, and facilities can be further divided into three types of functional tags: Core bearing unit: meets the requirements High value High value Low value, and A high value indicates that the unit carries a large number of irreplaceable critical ODs and is the "backbone that cannot be damaged by mistake"; Typical load-bearing unit: The value is moderate. value, Value and Value in the middle; Adjustment unit: Low value or High value, and Low or medium value.

[0029] like Figure 2 As shown, let For high-volume OD, For secondary ODs with relatively small flow rates, the definition of facility function labels can be used to determine: It belongs to the core carrying unit. It carries a large amount of weight. Main passage and All are high. It is also high and has high substitutability. Low, and once weakened, will significantly increase the generalized cost of key OD.

[0030] It belongs to a general bearing unit and mainly serves For a portion of the traffic, there are acceptable alternative paths and a certain margin, exhibiting a moderate level of performance. and and medium .

[0031] It belongs to the adjustment unit. Its main functions are shaping and sharing, with a relatively small weight. It flows, and has good substitutability. Low, high, Low, suitable for prioritizing speed-limiting / guidance and other regulatory measures.

[0032] The above functional labels describe the importance of the facilities corresponding to each OD in the OD set. Based on the importance, non-core units and units with operability are selected as the initial set of facilities to be managed. For any initial facility to be managed, the management score of the initial facility to be managed is calculated based on the traffic flow overlap parameter and traffic flow diversion parameter between the initial facility to be managed and the target facility.

[0033] Traffic overlap parameters are calculated in the following way: (7) in, The threshold for determining the degree of overlap; Characterizing facilities to be controlled The set of ODs that can be directly affected.

[0034] Traffic flow can be diverted using the following parameters: (8) in, To and A set of equivalent facilities that undertake the same / similar origin-destination (OD); for facilities Let its time-varying margin be denoted as Its consistency / reliability weight is .

[0035] Control rating: (9) Select from highest to lowest score, satisfying rules such as mutual exclusion and minimum interval, and take at most [number of items]. One group entered the facility to be controlled, among which It is an integer greater than or equal to 1; , This is a weighting coefficient, which can be set according to the actual situation.

[0036] Let the target facility be Pre-set up to a maximum number from its collection of facilities to be managed. One facility to be managed is designated as... The system will acquire control measures for each facility to be controlled and construct a set of candidate control measures. Next, simulation evaluation will be conducted based on the facility status parameters of the target facility and each candidate control facility. Candidate control measures that meet preset constraints will be selected as the set of executable control measures.

[0037] set up Target facility A corresponding executable control measure combination strategy is defined, along with the strategy overview: (10) in This refers to a combination of different measures (such as traffic restriction / interception, toll station access restriction / closure, traffic diversion, and parallel / serial combinations of opposite lanes). The adjustment level of the control parameters corresponding to the control measures (taken from the allowable range of each measure). (discrete values); The timing encoding of the measures (parallel / serial relationship, start time, duration, etc.).

[0038] Set a uniform evaluation time window for measuring operational effectiveness. (e.g., 30 / 45 / 60 minutes), and an overview of the initial state of the simulation experiment: (11) In essence, it defines the abstract working conditions and external conditions corresponding to this simulation test (peak / off-peak, event / non-event, vehicle-to-cargo ratio range, weather category, toll rate / traffic restriction level, etc.). for It includes a collection of facilities to be managed.

[0039] Computer simulations are used to predict the effectiveness of each candidate control measure combination under specific traffic conditions, and feasible combinations are selected. The state parameters of the target facility over a set time period can be used as the initial conditions for the simulation model. Next, the corresponding candidate control measure combinations are input into the simulation model as intervention strategies, and evaluation time window parameters are set (e.g., simulation duration is 45 minutes into the future). The dynamic evolution of traffic flow is simulated, and relevant performance indicators are output, such as travel time, queue length, traffic safety risk proxy index, key origin-destination (OD) demand satisfaction, and toll revenue changes. Finally, the simulation output results are compared with preset operational constraints. Only candidate combinations whose simulation results fully meet the constraints are marked as executable control measure combinations.

[0040] To store the combination of executable control measures selected through simulation to the database, a mapping relationship between the target facility, facility status parameters, and the set of executable control measures can be constructed during storage, and the data can be persistently stored in the road network facility profile knowledge base.

[0041] During the simulation, meso / micro traffic simulation or an equivalent rapid estimator can be used, ensuring consistency with actual measurements (speed, flow rate, queueing, gantry tolling flow). Calibration during the simulation is based on real historical data to calibrate key parameters (basic flow-speed relationship, car-following / lane-changing parameters, saturation flow rate, vehicle composition, entrance / exit allocation, etc.); historical event replays are used to evaluate queue growth rate, speed profile, and obstacle clearance. The response undergoes cross-calibration until the error is within acceptable limits. The baseline reproduction error (velocity / queue / capacity) for uninterrupted scenarios should be below a set threshold (e.g., ...). Perform a validity check.

[0042] The simulation output should include both operational and management dimensions.

[0043] The output results of the running dimension include: This indicates the predicted average speed (or quantile speed) between the facility and its upstream location within the assessment window. This indicates the predicted peak and length of the facility's queues; This indicates the change in the total travel time of the system; This indicates a change in safety indicators (such as sudden deceleration / collision).

[0044] The output results of the operational dimension include: weighted satisfaction of key ODs. and revenue / expense estimates The calculation methods are as follows: Key OD weighted satisfaction : First, the satisfaction level of OD is assessed using the time-achievement metric, i.e., within the assessment time window. Within this framework, satisfaction is defined based on the proportion of arrival times not exceeding a baseline threshold. (12) in, This refers to the historical percentile threshold or the service commitment threshold.

[0045] The satisfaction levels of each OD are assigned according to their weights. polymerization: (13) The higher the value, the better. A lower limit is usually set in the acceptability determination, such as... .

[0046] Revenue / Expense Estimation : Using gantry / toll station billing flow as the metric, in the simulation system, the total revenue of the strategy scenario and the baseline scenario within the evaluation window is compared: (14) Positive values ​​indicate a decrease in revenue ("loss"); negative values ​​indicate an increase in revenue. An upper limit can be set in the acceptability assessment: .

[0047] For each combination of control measures (including parameters and timing), if the following hard constraints are met simultaneously: , , and When indicators meet set thresholds; hard operational constraints: , If certain indicators meet the set thresholds, the operation is marked as executable; otherwise, it is marked as inexecutable and removed. The set of executable control operations is then marked as... .

[0048] (15) To support rapid screening and online optimization in practical applications, this disclosure establishes a unified effect evaluation mapping model when determining the acceptability of the aforementioned strategy and state profiles through simulation experiments. . This is used to characterize the running and operational evaluation results of candidate strategies under a given state and evaluation time window, and is exemplified as follows: (16) in, This is a general overview of the situation. For an overview of the strategy, For the assessment of the time window. , , and For operational indicators; and For operational metrics.

[0049] The above describes the construction process of the aforementioned knowledge base for road network infrastructure profiling.

[0050] The corresponding road network infrastructure profiling knowledge base also includes a cost function for control measures, so as to track and evaluate the corresponding control measures after their implementation. Specifically, the cost function for control measures is constructed in the following way: a cost function for control measures is constructed with facility status parameters and combinations of control measures as independent variables, wherein the evaluation result parameters of the cost function for control measures include key OD weighted satisfaction parameters, operational constraint parameters, and benefit parameters; based on the cost function for control measures, the evaluation results of each control measure are generated. This application embodiment does not limit the specific form of the above cost function; those skilled in the art can set it according to actual conditions.

[0051] In some embodiments, determining the set of facilities to be managed corresponding to the target facility based on a preset road network facility profile knowledge base includes: determining the functional constraint profile corresponding to the target facility from the preset road network facility profile knowledge base; and searching for the set of facilities to be managed corresponding to the target facility based on the functional constraint profile corresponding to the target facility.

[0052] For example, after the target facility is determined, the corresponding functional constraint profile can be found in the preset road network facility profile knowledge base based on the identification and other information of the target facility. As mentioned above, the functional constraint profile includes a first mapping relationship and a second mapping relationship. The set of facilities to be controlled is determined according to the corresponding first mapping relationship, and the set of executable control measures is found according to the second mapping relationship.

[0053] In some embodiments, determining the initial set of executable control facilities also requires satisfying relevant constraints, including: obtaining a set of all executable control measures corresponding to the facility status parameters of the facility to be controlled from the road network facility profile knowledge base; and filtering control measures that satisfy preset constraints from the set of all executable control measures to obtain the initial set of executable control measures. The preset constraints include operational constraints and management constraints; the preset constraints also include at least one of the following: consistency constraints, traffic margin constraints, and interval and smoothing constraints; wherein the operational constraints indicate that the corresponding control measures meet preset traffic operation boundary thresholds; and the management constraints indicate that the corresponding control measures meet preset revenue boundary thresholds.

[0054] Correspondingly, in practical applications, the initial set of executable control measures... The selection of the best evaluation result among the preset constraints as the target control measure also includes: ranking the evaluation results of each initial executable control measure and selecting the one with the largest evaluation result. These control measures are identified as control measures to be optimized. The value is an integer greater than or equal to 1. For any control measure to be optimized, the control parameters in the control measure to be optimized are adjusted according to the preset data change rules to obtain the evaluation results corresponding to the multiple control parameters of the control measure to be optimized. Based on the evaluation results corresponding to the multiple control parameters, the control parameter with the best evaluation result is determined as the target control parameter.

[0055] For example, for the initial set of executable control measures Any initial executable control measure in Construct the cost function of control measures as follows: (17) Among them, the above Various items are mapped by a unified effect evaluation model. Given; weights satisfy .

[0056] Based on cost function In the initial set of executable control measures We will construct an optimization method to find the most effective target control measures.

[0057] (18) Typically, the control parameters corresponding to the determined executable control measures are default values ​​or optimized parameters obtained from historical data. In this case, in order to further adapt to the current road conditions, in some embodiments, the control measures in the above combination of control measures can be further optimized and fine-tuned locally.

[0058] In some implementations, for any control measure to be optimized, the control parameters in the control measure to be optimized are adjusted according to preset data change rules to obtain the evaluation results corresponding to multiple control parameters of the control measure to be optimized; based on the evaluation results corresponding to multiple control parameters, the control parameter with the best evaluation result is determined as the target control parameter.

[0059] For example, for each control parameter in the combination of control measures to be optimized, its domain (minimum / maximum), precision (adjustment step size), and constraints (such as a speed limit not lower than 30 km / h) are analyzed, and a sequence of candidate parameter values ​​is generated based on preset data change rules. The preset data change rules can be a binary search strategy, a grid search, or a set of random numbers, etc.

[0060] For each candidate parameter value, a simulation is performed, taking the current road condition and control parameter configuration as input, and outputting the parameter evaluation results for the next 15-30 minutes.

[0061] For example, after implementing target control measures, various operational parameters of those measures, such as traffic flow speed and queue length, can be continuously acquired within an evaluation window. If these operational parameters do not meet the predicted parameters, the target control measures can be switched to a pre-set conservative plan.

[0062] The method disclosed herein, in response to a triggered control command, determines the target facility corresponding to the location information in the control command. Based on a road network facility profile knowledge base, it identifies a set of facilities to be controlled corresponding to the target facility, thereby limiting control measures to this set and reducing uncertainty caused by network-wide searches and trial-and-error. Furthermore, based on the facility status parameters of the target facility and the facilities to be controlled within a preset time period, it quickly determines a matching set of initial executable control measures, avoiding strategies that are unimplementable or incompatible with facility capabilities. Finally, under the combined constraints of operational and management constraints, it selects the best initial executable control measure set as the target control measure. Therefore, it enables rapid generation, implementation, risk control, and traceable control outputs, improving control consistency and reducing overall operation and maintenance costs.

[0063] Corresponding to the above implementation method for determining road control measures based on road network infrastructure profiling, this disclosure also provides a device for determining control measures based on road network infrastructure profiling, such as... Figure 3 As shown, the device for determining control measures based on road network infrastructure profiles includes: The control trigger module 301 is used to respond to the trigger control command, determine the target facility corresponding to the location information in the control command; and determine the set of facilities to be controlled corresponding to the target facility based on the preset road network facility profile knowledge base; The initial executable control measure set determination module 302 is used to obtain the facility status parameters of the target facility and the set of facilities to be controlled within a preset time period; and to determine the initial executable control measure set corresponding to the facility status parameters of the set of facilities to be controlled based on the road network facility profile knowledge base. The target control measure combination determination module 303 is used to obtain preset constraints and select the best evaluation result among the preset constraints from the initial set of executable control measures as the target control measure; the preset constraints include operational constraints and management constraints.

[0064] The control measure determination device based on road network facility profile provided in the above embodiments of this disclosure and the road control measure determination method based on road network facility profile provided in the embodiments of this disclosure are based on the same disclosed concept and have the same beneficial effects as the methods adopted, run or implemented by the applications stored therein.

[0065] This disclosure also provides an electronic device for performing the above-described data transmission method. Please refer to... Figure 4 This illustrates a schematic diagram of an electronic device provided by some embodiments of the present disclosure. For example... Figure 4 As shown, the electronic device includes: a processor 400, a memory 401, a bus 402, and a communication interface 404. The processor 400, the communication interface 404, and the memory 401 are connected via the bus 402. The memory 401 stores a computer program that can run on the processor 400. When the processor 400 runs the computer program, it executes the aforementioned provisions of this disclosure. Figure 1 The method provided by any of the illustrated embodiments.

[0066] The memory 401 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 404 (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network.

[0067] Bus 402 can be an ISA bus, PCI bus, or EISA bus, etc. Buses can be divided into address buses, data buses, control buses, etc. Memory 401 is used to store programs; after receiving execution instructions, processor 400 executes the program, as described above. Figure 1 or Figure 3 The method disclosed in any of the illustrated embodiments can be applied to or implemented by the processor 400.

[0068] The processor 400 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 400 or by instructions in software form. The processor 400 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 401. The processor 400 reads the information in memory 401 and, in conjunction with its hardware, completes the steps of the above method.

[0069] The electronic devices and data transmission methods provided in this disclosure are based on the same disclosed concept and have the same beneficial effects as the methods they employ, operate, or implement.

[0070] This disclosure also provides a computer-readable storage medium corresponding to the data transmission method provided in the foregoing embodiments. Please refer to... Figure 5 The computer-readable storage medium shown is an optical disc 30, on which a computer program (i.e., a program product) is stored. When the computer program is run by the microprocessor, it executes the data transmission method provided in any of the aforementioned embodiments.

[0071] It should be noted that examples of computer-readable storage media may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media, which will not be elaborated here.

[0072] The computer-readable storage medium provided in the above embodiments of this disclosure and the data transmission method provided in the embodiments of this disclosure are based on the same disclosed concept and have the same beneficial effects as the methods adopted, run or implemented by the applications stored therein.

[0073] It should be noted that: Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this disclosure may be practiced without these specific details. In some instances, well-known structures and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0074] Similarly, it should be understood that, for the sake of brevity and to aid in understanding one or more of the various aspects of the disclosure, in the foregoing description of exemplary embodiments of the disclosure, various features of the disclosure are sometimes grouped together in a single embodiment, figure, or description thereof. However, this approach to disclosure should not be construed as reflecting a schematic diagram in which the claimed disclosure requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, the aspects of the disclosure consist of fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the disclosure.

[0075] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of this disclosure and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0076] The above are merely preferred embodiments of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for determining control measures based on road network infrastructure profiling, characterized in that, The method includes: In response to a triggered control command, the system determines the target facility corresponding to the location information in the control command; and determines the set of facilities to be controlled corresponding to the target facility based on a preset road network facility profile knowledge base. Obtain the facility status parameters of the target facility and the set of facilities to be managed within a preset time period; determine the initial set of executable management measures corresponding to the facility status parameters of the set of facilities to be managed based on the road network facility profile knowledge base; Obtain preset constraints, and select the best evaluation result among the preset constraints from the initial set of executable control measures as the target control measure; the preset constraints include operational constraints and management constraints.

2. The method according to claim 1, characterized in that, The method further includes: A road network facility profile knowledge base is pre-constructed; wherein, the road network facility profile knowledge base includes a functional constraint profile of each target facility; the functional constraint profile includes a first mapping relationship and a second mapping relationship; the first mapping relationship refers to the mapping relationship between the target facility and the corresponding facility to be managed; the second mapping relationship refers to the mapping relationship between the facility status parameters corresponding to the target facility, the facility status parameters corresponding to the facility to be managed, and the set of executable management measures.

3. The method according to claim 2, characterized in that, The set of facilities to be managed, determined based on a pre-set road network facility profiling knowledge base and corresponding to the target facility, includes: The functional constraint profile corresponding to the target facility is determined from the preset road network facility profile knowledge base; Based on the functional constraint profile corresponding to the target facility, find the set of facilities to be managed corresponding to the target facility.

4. The method according to claim 2, characterized in that, The first mapping relationship is constructed in the following way: Obtain the OD set carried by the target facility; based on the OD set, find facilities in the facility set that have an equivalent OD set carried by the target facility, and use them as the initial set of facilities to be managed; For any initial facility to be managed, a management score is calculated based on the traffic overlap parameters between the initial facility to be managed and the target facility, and the traffic diversion parameters. Based on the initial control scores of the facilities to be controlled, ranked from high to low, the top [facilities] are determined. The initial set of facilities to be managed is the target facility's set of facilities to be managed. It is an integer greater than or equal to 1.

5. The method according to claim 2, characterized in that, The second mapping relationship is constructed in the following way: Obtain the control measures for each facility to be controlled, and construct a set of candidate control measures; Simulation evaluation is conducted based on the facility status parameters of the target facility and each candidate control facility, and the candidate control measures that meet the preset constraints are taken as the set of executable control measures. The second mapping relationship is obtained by associating the target facility, the facility status parameters of each facility to be managed, and the corresponding set of executable management measures.

6. The method according to claim 2, characterized in that, The initial set of executable control measures, determined based on the road network facility profiling knowledge base, for the facility status parameters corresponding to the set of facilities to be controlled, includes: Obtain a set of all executable control measures corresponding to the facility status parameters of the facility to be controlled from the road network facility profile knowledge base; The initial set of executable control measures is obtained by selecting control measures that meet preset constraints from the set of all executable control measures. The preset constraints include operational constraints and business constraints. The preset constraints also include at least one of the following: consistency constraints, flow margin constraints, and interval and smoothing constraints. The operational constraints described therein represent that the corresponding control measures meet the preset traffic operation boundary thresholds; The operational constraints indicate that the corresponding control measures meet the preset revenue boundary threshold.

7. The method according to claim 2, characterized in that, The road network infrastructure profiling knowledge base also includes cost functions for control measures. Construct a cost function for control measures with facility status parameters and combinations of control measures as independent variables. The evaluation result parameters of the cost function for control measures include key OD weighted satisfaction parameters, operational constraint parameters, and benefit parameters. Based on the cost function of the control measures, the evaluation results of each control measure are generated.

8. The method according to any one of claims 1-7, characterized in that, Selecting the control measure with the best evaluation result among the preset constraints from the initial set of executable control measures also includes: The assessment results of each initial executable control measure are ranked, and the measure with the highest assessment result is selected. These control measures are identified as control measures to be optimized. It is an integer greater than or equal to 1; For any control measure to be optimized, the control parameters in the control measure to be optimized are adjusted according to the preset data change rules to obtain the evaluation results corresponding to the multiple control parameters of the control measure to be optimized. Based on the evaluation results corresponding to the multiple control parameters, the control parameter with the best evaluation result is determined as the target control parameter.

9. A device for determining control measures based on road network infrastructure profiling, characterized in that, include: The control triggering module is used to respond to a control command and determine the target facility corresponding to the location information in the control command; And based on a pre-set road network facility profile knowledge base, determine the set of facilities to be managed corresponding to the target facilities; The initial executable control measure set determination module is used to obtain the facility status parameters of the target facility and the set of facilities to be controlled within a preset time period; and to determine the initial executable control measure set corresponding to the facility status parameters of the set of facilities to be controlled based on the road network facility profile knowledge base. The target control measure determination module is used to obtain preset constraints and select the best evaluation result among the preset constraints from the initial set of executable control measures as the target control measure; the preset constraints include operational constraints and management constraints.

10. An electronic device, characterized in that, The device includes a processor and a memory storing program instructions, the processor being configured to, when executing the program instructions, perform the method for determining road control measures based on a road network infrastructure profile as described in any one of claims 1 to 8.

11. A computer-readable medium, characterized in that, It stores computer-readable instructions, which are executed by a processor to implement a method for determining road control measures based on a road network infrastructure profile as described in any one of claims 1 to 8.

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