CN116050189B - Traffic deduction simulation experiment method, system, terminal and storage medium - Google Patents
Traffic deduction simulation experiment method, system, terminal and storage medium Download PDFInfo
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Abstract
The application is applicable to the technical field of traffic simulation, and provides an experimental method, a system, a terminal and a storage medium for traffic deduction simulation, wherein the experimental method comprises the following steps: inputting initial triggering conditions and traffic simulation service types; the initial triggering condition is a system state variable which causes the actual condition of traffic to change; selecting a traffic simulation model from the traffic simulation model set based on the traffic simulation service type; the traffic simulation model set comprises a plurality of different types of traffic simulation models; based on the initial trigger condition and the selected traffic simulation model, calling a basic component for simulation; and outputting a simulation result of the traffic simulation model under the initial triggering condition. According to the traffic simulation modeling method and the traffic simulation modeling system, various traffic simulation models can be formulated according to the business characteristics of different fields, so that the self business requirements can be met.
Description
Technical Field
The application belongs to the technical field of traffic simulation, and particularly relates to an experimental method, system, terminal and storage medium for traffic deduction simulation.
Background
The traffic deduction simulation engine system consists of modules such as a model, an entity, a basic component, a rule specification, an API, a situation and the like, and different models can adapt to different deduction simulation types.
At present, the technology in the traffic field is rapidly developed, the requirements in the traffic simulation field are also more and more refined, and different simulation experiment models are needed to support different research topics. And further provides quantitative decision basis for traffic facility construction, traffic organization management, traffic event early warning and evaluation and traffic policy feasibility analysis research.
The various fields of traffic service have different targets and emphasis points for the simulation system, and the data requirements and algorithms of different models are also different, but at present, no simulation experiment method is available for making various traffic simulation models according to the service characteristics of different fields, so that an experiment method for traffic deduction simulation is needed, and various traffic simulation models can be made according to the service characteristics of different fields, so that the self-service requirement can be met.
Disclosure of Invention
In order to overcome the problems in the related art, the embodiment of the application provides an experimental method, a system, a terminal and a storage medium for traffic deduction simulation, and various traffic simulation models can be formulated according to the service characteristics of different fields, so that the application of self service requirements is realized.
The application is realized by the following technical scheme:
in a first aspect, an embodiment of the present application provides an experimental method for traffic deduction simulation, including:
inputting initial triggering conditions and traffic simulation service types; the initial triggering condition is a system state variable which causes the actual condition of traffic to change;
selecting a traffic simulation model from the traffic simulation model set based on the traffic simulation service type; the traffic simulation model set comprises a plurality of different types of traffic simulation models;
based on the initial trigger condition and the selected traffic simulation model, calling a basic component for simulation;
and outputting a simulation result of the traffic simulation model under the initial triggering condition.
In one possible implementation, the base component encapsulates predefined algorithmic data blocks that build the traffic simulation model.
In one possible implementation, the system state variables include attributes of the entity, the state of the activity, and the content of the event;
the entities are objects on the road, and the entities have a preset influence relationship with each other; the entity comprises a permanent entity and a temporary entity, wherein the permanent entity represents an object which exists on a road permanently in the simulation process, and the temporary entity represents an object which exists on a road temporarily in the simulation process;
an operation or process performed by the activity characterization entity over a period of time;
the event characterizes the operation or behavior that results in a change in the state of the traffic simulation model.
In one possible implementation, selecting a traffic simulation model from a set of traffic simulation models based on traffic simulation traffic types, includes:
based on the traffic simulation service type, a traffic simulation model corresponding to the traffic simulation service type is selected, and an initial state of a system state variable of the traffic simulation model is generated.
In one possible implementation, simulating based on the initial trigger condition and the selected traffic simulation model includes:
based on the initial trigger condition, changing the initial state of the system state variable of the traffic simulation model to generate new event arrangement; the new event arrangement includes an ordering and listing of new events;
based on the new event arrangement, event processing is carried out by utilizing time-pushing event occurrence, and system state variables are updated;
and comparing the state of the system state variable with a preset simulation ending condition, if the comparison result accords with the preset condition, ending the simulation, otherwise, generating a new event based on the state of the updated system state variable.
In one possible implementation, the ordering of events is determined by the random number generator generating random numbers of a prescribed distribution.
In a second aspect, an embodiment of the present application provides a system for traffic deduction simulation, including:
the input module is used for inputting initial triggering conditions and traffic simulation service types; the initial triggering condition is a system state variable which causes the actual condition of traffic to change;
the model version control module is used for selecting a traffic simulation model from the traffic simulation model set based on the traffic simulation service type; the traffic simulation model set comprises a plurality of different types of traffic simulation models;
the traffic simulation module is used for calling the basic component to simulate based on the initial triggering condition and the selected traffic simulation model;
and the traffic simulation result output module is used for outputting the simulation result of the traffic simulation model under the initial triggering condition.
In one possible implementation, the base components include an engine core component, a process control component, a database, communication middleware, a rule engine component; the base component is a predefined component;
the engine core component is used for performing task management, model analysis and node management;
the process control component is used for carrying out the period, step length and flow propulsion of the simulation process;
the database is used for storing simulation data and operation data, wherein the simulation data characterizes data related to the establishment of the traffic simulation model, and the operation data characterizes data generated in the simulation process of the traffic simulation model;
the communication middleware is used for simulating queuing in the data transmission process;
the rule engine component is used for simulating a service decision based on the simulation data and the rules of the traffic simulation service type; the business decisions are used to indicate predefined system state variables.
In a third aspect, an embodiment of the present application provides a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement an experimental method for traffic deduction simulation according to any one of the first aspects above.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program, where the computer program when executed by a processor implements an experimental method for traffic deduction simulation according to any one of the first aspects.
Compared with the prior art, the embodiment of the application has the beneficial effects that:
according to the embodiment of the application, the corresponding traffic simulation models are selected from the traffic simulation model set according to different traffic service requirements, so that various traffic simulation models can be formulated according to service characteristics in different fields under the condition that the system architecture is unchanged, and the application of self service requirements is realized.
The advantages of the second aspect to the fourth aspect are referred to as the advantages of the first aspect, and are not described here again.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an experimental method of traffic deduction simulation according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an event basic simulation mechanism provided in an embodiment of the present application;
FIG. 3 is a schematic diagram illustrating a change in system state of a traffic simulation model according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a simulation process of a traffic simulation model provided in an embodiment of the present application;
FIG. 5 is a schematic diagram of a system for traffic deduction simulation according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In order that those skilled in the art will better understand the present invention, a technical solution in the examples of the present application will be clearly and completely described in the following with reference to the accompanying drawings and detailed description, and it is apparent that the described examples are only some examples of the present invention, not all examples. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Based on the above problems, an experimental method for traffic deduction simulation is provided in the embodiments of the present application. Referring to fig. 1, the experimental method of the traffic deduction simulation is described in detail as follows:
Specifically, the system state variables include the attributes of the entity, the state of the activity, and the content of the event. The entities are objects on the road, and the entities have a preset influence relationship with each other. The entities include permanent entities that characterize objects that are permanently present on the road during the simulation process and temporary entities that characterize objects that are temporarily present on the road during the simulation process.
The activity characterizes an operation or process that an entity continues to perform over a period of time.
The event characterizes the operation or behavior that results in a change in the state of the traffic simulation model.
By way of example, the entity may be a vehicle on a road, a pedestrian, an intersection segment, an object on a road of a transportation facility, etc. The temporary entity may be a vehicle passing through an intersection, a temporary roadblock, a temporarily parked motor vehicle, etc., and the permanent entity may be a simulated road section, a signal lamp of an intersection, a toll station, etc.
By way of example, traffic simulation traffic types may include traffic event pre-warning traffic, traffic accident emergency handling traffic, road grooming analysis traffic, road traffic capacity analysis traffic, travel time analysis traffic, traffic management scheme assessment traffic, road maintenance policy assessment traffic, high speed toll booth handling capacity traffic, and the like.
In an embodiment, for traffic accident emergency processing service, the initial triggering condition may be set according to the occurrence cause of a specific traffic accident, for example, the initial triggering condition may be set as a rear-end collision or a collision of a vehicle.
102, selecting a traffic simulation model from a traffic simulation model set based on the traffic simulation service type; the traffic simulation model set includes a plurality of different types of traffic simulation models.
Specifically, selecting a traffic simulation model from a traffic simulation model set based on the traffic simulation service type, including: based on the traffic simulation service type, a traffic simulation model corresponding to the traffic simulation service type is selected, and an initial state of a system state variable of the traffic simulation model is generated.
By way of example, under the unified specification requirements, corresponding traffic simulation models are established for different service requirements, and the established traffic simulation models are stored in a traffic simulation model set, so that the corresponding traffic simulation models are selected according to traffic simulation service types.
The traffic simulation model set can comprise a traffic event early warning model, a traffic accident emergency treatment model, a road dredging analysis model, a road traffic capacity analysis model, a travel time analysis model, a traffic management scheme evaluation model, a road maintenance strategy evaluation model, a high-speed toll booth processing capacity model and the like.
Illustratively, once any one of the traffic simulation models is selected, the initial state of the system state variables of the traffic simulation model. For example, selecting a high speed toll booth throughput service, the initial state of the system state variables of the traffic simulation model, including the high speed road segments of the set area, the high speed toll booth on the road segments, and the initial traffic volume, etc., are displayed.
The user interface can take the entity as a component, and defines a logic connection interface in the model, the main work of the user is to drag the corresponding entity from the component library according to the processing sequence of the entity, and connect the entities according to the logic relationship to form a situation, and meanwhile, the sensor and the AI system can be connected to enable the system to have situation sensing capability, and the situation can be constructed and perfected according to the sensed information. The model determines state variables and circulation modes in the system according to rules, determines the influence of the events on the state and entity attributes according to different events, and determines the mutual influence among the events.
And step 103, based on the initial trigger condition and the selected traffic simulation model, calling a basic component to simulate.
Specifically, the base component encapsulates predefined algorithmic data blocks that build the traffic simulation model.
Illustratively, a plurality of algorithmic data blocks of different types of traffic simulation models are packaged to form a base component. The algorithm data block comprises a predefined basic algorithm for building a traffic simulation model and general characteristic data of the traffic simulation model.
Illustratively, the base component encapsulates algorithms including engine core algorithms, algorithms for process control, databases, communication intermediate algorithms, rule engines.
The engine core algorithm comprises methods for task management, model analysis and node management. The algorithm for performing the process control can control the period, step size and flow advancement for performing the simulation process. The database is used for storing simulation data and operation data, the simulation data characterize the data related to the establishment of the traffic simulation model, and the operation data characterize the data generated in the simulation process of the traffic simulation model. The communication middleware algorithm comprises a queuing method in the simulation data transmission process. The rule engine algorithm simulates a business decision based on the simulation data and the rules of the traffic simulation business type; the business decisions are used to indicate predefined system state variables, i.e., changing the initial state of the system state variables of the corresponding traffic simulation model according to the business decisions.
Specifically, as shown in fig. 2, the simulation is performed based on the initial trigger condition and the selected traffic simulation model, including: based on the initial trigger condition, calling a basic component to change the initial state of a system state variable of the traffic simulation model, and generating new event arrangement; the new event schedule includes an ordering and list of new events. Based on the new event arrangement, event processing is performed by utilizing the time-advance event occurrence, and the system state variables are updated. And comparing the state of the system state variable with a preset simulation ending condition, if the comparison result accords with the preset condition, ending the simulation, otherwise, generating a new event based on the state of the updated system state variable.
Wherein the ordering of the events is determined by the random number generator generating random numbers of a prescribed distribution. In addition, because of various conditions of generating new events, selecting time or processing event in actual traffic conditions and changing the event processing modes, the generated random numbers with specified distribution have influence on generating new event arrangement, utilizing time to advance events and processing events.
For example, when the time advance event occurs, the current event table is scanned, and the time is set as the current event occurrence time.
In one embodiment, to better understand the present solution, a simple process of the high-speed toll booth throughput model is taken as an example:
this embodiment contemplates operation of a single toll booth. The initial state of the model is defined as the set number of vehicles in the system, such as waiting vehicles parked at a toll booth or in a queuing queue. The initial event includes the arrival of a vehicle, the entry of a vehicle into a toll booth, and the exit of a vehicle from a toll booth. The time-step logic is event driven, involving discrete steps of various lengths. The three events are: joining the tail of the queue, waiting in the queue for service and leaving the toll booth.
First, generating an initial state of a system state variable of a traffic simulation model: assuming that the vehicle arrival interval is 10 seconds, the service time at the toll booth is 5 seconds. As shown in fig. 3, the system state of the traffic simulation model is changed, and it is known that the model has certainty and no randomness. One is that there is a car at the toll booth (1), and the other is that there is no car at the toll booth (0). At time t=0, the first vehicle arrives, which requires 5 seconds of processing, and then leaves the toll booth. At time t=10, the next vehicle arrives, the above-described processing is repeated, the delay of each of the 9 vehicles is zero, and the value of the system state is either 1 or 0, depending on whether the vehicle at the toll booth is being serviced.
The initial trigger condition is set to a range of 4 to 16 seconds for the vehicle inter-arrival distance and 3-7 seconds for the actual service time. The same 9 vehicles were simulated as passing through the toll gate.
The event is that 9 vehicles enter in sequence, the event list is that 9 vehicles enter a toll booth to be served and leave, and the simulation is finished after all vehicles leave. The vehicle inter-arrival and service time are determined based on the random numbers generated by the random number generator. And calling the pushing time of the basic component, wherein the first event occurs at the time t=0 (the first vehicle arrives), processing the event, sequentially processing the event that 9 vehicles enter the toll booth to receive service and leave according to an event table, and repeating the process for more accurate results after the simulation process is finished.
In one embodiment, taking a traffic accident emergency treatment model as an example, for a selected road section, the initial state includes a set traffic flow in the system, the accident occurrence position is the entrance of the selected road section, the accident occurrence time is 8 a.m., and the staff handling the accident is within 1 km from the accident scene. The event includes a vehicle driving into the selected road section, a vehicle driving out of the selected road section, and a vehicle occurrence of a traffic accident. The time-step logic is event driven, involving discrete steps of various lengths. The initial triggering condition is set to be that the traffic accident happens in the middle of the road section, the traffic flow is in a range, and the accident occurrence time is multiple. The time taken for the emergency handling of traffic accidents is simulated.
In one embodiment, taking a traffic accident emergency treatment model and a road traffic capacity analysis model as an example, for a selected road section, the initial state includes a set traffic flow in the system, the accident occurrence position is the entrance of the selected road section, the accident occurrence time is 8 a.m., and the staff for handling the accident is within 1 km from the accident scene. The event includes a vehicle driving into the selected road section, a vehicle driving out of the selected road section, and a vehicle occurrence of a traffic accident. The time-step logic is event driven, involving discrete steps of various lengths. The initial triggering condition is set to be that the traffic flow changes randomly within a range, the accident occurrence time is within a certain time period, or the number of times of accident occurrence is the like to simulate traffic conditions, and the road traffic capacity and the traffic accident emergency handling capacity are analyzed.
By predefining the basic components, the simulation process is completed by directly calling a plurality of basic components in the simulation process, so that the operation time is reduced, and the efficiency of traffic simulation is improved.
For example, if some characteristics of some models are the same, data of the same characteristic part can be encapsulated in the base component, and can be directly called when in use.
For example, corresponding models are established for different business requirements, the established various traffic simulation models are stored in a traffic simulation model set, all models follow the unified specification, and under the condition that basic components and system architecture are unchanged, different traffic simulation models are changed to meet different business requirements.
And 104, outputting a simulation result of the traffic simulation model under the initial triggering condition.
Illustratively, after the simulation is completed, the simulation result is output. The simulation result may be an analysis report corresponding to the traffic simulation service.
The following are the results of the simulation process for the high speed toll booth throughput model in the above embodiment, as shown in table 1. The simulation random numbers are different, so that the results are different, and table 1 only lists the results of one of them for explaining the event simulation process, and only for explaining the event simulation process.
TABLE 1 results of simulation procedure for high speed toll booth throughput model
Wherein "vehicle number" in table 1 gives the numerical index of the vehicle. The "arrival time interval random variable" lists random numbers that determine the arrival time interval of the vehicle. The "arrival time interval" gives the time interval between the current car and the preceding car: 4+ arrival time interval random variable x (16-4). The "arrival time" gives the arrival time based on the arrival time interval. The "service time random variable" gives a random number that determines the service time. The "service time" is: 3+ service time random variable x (7~3). The "service start time" is a service start time, i.e., a time when the vehicle enters the toll booth. The "service end time" is the service end time, i.e., the time when the vehicle leaves the toll booth. "delay" gives the delay time in seconds.
The information in table 1 describes the following system implementation. The first vehicle enters the system at t=14.4 seconds, based on an arrival time interval of 4+0.8672× (16-4) =14.4 seconds. 0.8672 is the arrival time interval random variable. The service time of the vehicle is 3+0.8871× (7~3) =6.5 seconds, 0.8871 is the service time random variable. The 2 nd to 4 th vehicles can be estimated according to the same method.
For the 5 th vehicle, the arrival time interval is 4+0.0012× (16 to 4) =4.0 seconds, so its arrival time is 41.8 seconds. But at t=41.8 seconds the toll booth is already occupied. The vehicle must wait until t=45.0 seconds for the toll booth to be idle to receive service. Waiting creates a delay of 3.3 seconds. Then at t=45.1 seconds the car receives service and after 3+0.8501× (7-3) =6.4 seconds the service ends. The car leaves the toll booth for t=51.5 seconds, after which the 6 th car will be allowed to enter. Similarly, the 6 th vehicle arrives at t=51.1 seconds and waits for service. Due to randomness, the 3 rd, 4 th, 5 th, 6 th and 7 th vehicles experience delay times of 2.5 th, 3.7 th, 3.3 th, 0.4 th and 1.4 th seconds, respectively. The total delay was 11.3 seconds and the average delay per vehicle was 1.25 seconds. The system state is also changed since the initial trigger condition is set to a range of 4 to 16 seconds for the vehicle arrival interval and 3 to 7 seconds for the actual service time. The results of the simulation were obtained with a total delay of 11.3 seconds and an average delay of 1.25 seconds per vehicle.
For example, as shown in fig. 4, before simulation, the system performs data fusion processing according to simulation parameter data, planning data, traffic flow data, event data, planning data and traffic volume data to form simulation deduction data, and provides an infrastructure for traffic simulation. On the basis of the infrastructure, an initial trigger condition is input, and one of n traffic simulation models is selected from the traffic simulation model set. And calling the basic component, and pushing the traffic simulation model to generate by utilizing the actions of a rule engine, task management, model analysis, node management and process control to perform traffic simulation. And finally obtaining simulation result data, and carrying out traffic simulation result release, traffic situation display and traffic simulation result evaluation according to the simulation result data.
Compared with the prior art, the traffic deduction simulation method has the beneficial effects that: by establishing corresponding traffic simulation models aiming at different service requirements and conforming to unified specifications, different service requirements are met by changing the traffic simulation models under the condition that basic components and system architecture are unchanged. Through predefining the basic components, most of the basic components are directly called in the simulation process to push the simulation process to be completed, so that the operation time is reduced, and the traffic simulation efficiency is improved. And stripping the business simulation model from the system foundation assembly and the situation system, and meeting the simulation experiment requirements of various businesses by establishing models in different business fields. The models can be combined at will, a single model can be used for verifying a single index, and multi-model combination can be used for meeting the combined deduction of multiple fields, so that the application range is wide.
In an embodiment, a system for traffic deduction simulation based on an experimental method of traffic deduction simulation, referring to fig. 5, is described in detail as follows:
the system for traffic deduction simulation comprises an input module 201, a model version control module 202, a traffic simulation module 203 and a traffic simulation result output module 204.
An input module 201, configured to input an initial trigger condition and a traffic simulation service type; the initial trigger condition is a system state variable that causes a change in the actual condition of traffic.
A model version control module 202 for selecting a traffic simulation model from a set of traffic simulation models based on traffic simulation service types; the traffic simulation model set includes a plurality of different types of traffic simulation models.
The traffic simulation module 203 is configured to invoke the base component to simulate based on the initial trigger condition and the selected traffic simulation model.
And the traffic simulation result output module 204 is used for outputting the simulation result of the traffic simulation model under the initial triggering condition.
Specifically, the basic components comprise an engine core component, a process control component, a database, a communication middleware and a rule engine component; the base component is a predefined component.
The engine core component is used for performing task management, model analysis and node management.
The process control component is used to perform the cycle, step size and flow advances of the simulation process.
The database is used for storing simulation data and operation data, the simulation data characterize the data related to the establishment of the traffic simulation model, and the operation data characterize the data generated in the simulation process of the traffic simulation model.
The communication middleware is used for simulating queuing of the data transmission process.
The rule engine component is used for simulating a service decision based on the simulation data and the rules of the traffic simulation service type; the business decisions are used to indicate predefined system state variables.
The beneficial effects of the system for traffic deduction simulation refer to the beneficial effects of the experimental method of traffic deduction simulation, and are not repeated here.
It should be understood that the sequence number of each step does not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
It should be noted that, because the content of information interaction and execution process between the devices is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
The embodiment of the present application further provides a terminal device, referring to fig. 6, the terminal device 300 may include: at least one processor 310 and a memory 320, the memory 320 storing a computer program 321 executable on the at least one processor 310, the processor 310 implementing the steps of any of the various method embodiments described above, such as steps 101 to 104 in the embodiment shown in fig. 1, and the functions of the modules 201 to 204 in the embodiment shown in fig. 5, when the computer program is executed.
By way of example, a computer program may be partitioned into one or more modules/units that are stored in memory 320 and executed by processor 310 to complete the present application. The one or more modules/units described above may be a series of computer program segments capable of performing specific functions for describing the execution of the computer program in the terminal device 300.
It will be appreciated by those skilled in the art that fig. 6 is merely an example of a terminal device and is not limiting of the terminal device and may include more or fewer components than shown, or may combine certain components, or different components, such as input-output devices, network access devices, buses, etc.
The processor 310 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 320 may be an internal storage unit of the terminal device, or may be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card), or the like. The memory 320 is used for storing the computer program and other programs and data required by the terminal device. The memory 320 may also be used to temporarily store data that has been output or is to be output.
The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or one type of bus.
The traffic deduction simulation method provided by the embodiment of the application can be applied to terminal equipment such as computers, tablet computers, notebook computers, netbooks, personal digital assistants (personal digital assistant, PDA) and the like, and the embodiment of the application does not limit the specific types of the terminal equipment.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (7)
1. The experimental method for traffic deduction simulation is characterized by comprising the following steps:
performing data fusion processing according to simulation parameter data, planning data, traffic flow data, event data, planning data and traffic volume data to form simulation deduction data, and forming a traffic simulation infrastructure based on the simulation deduction data;
inputting initial triggering conditions and traffic simulation service types on the basis of the basic framework; the initial triggering condition is a system state variable which causes the actual condition of traffic to change;
selecting a traffic simulation model from a traffic simulation model set based on the traffic simulation service type; the traffic simulation model set comprises a plurality of different types of traffic simulation models; the traffic simulation model set comprises a traffic event early warning model, a traffic accident emergency processing model, a road dredging analysis model, a road traffic capacity analysis model, a traffic management scheme evaluation model, a road maintenance strategy evaluation model and a high-speed toll booth processing capacity model;
based on the initial trigger condition and the selected traffic simulation model, calling a basic component to simulate;
based on the initial trigger condition and the selected traffic simulation model, calling a basic component to simulate, wherein the method comprises the following steps: based on the initial trigger condition, calling the basic component to change the initial state of a system state variable of a traffic simulation model, and generating new event arrangement; the new event arrangement includes an ordering and listing of new events; based on the new event arrangement, event processing is carried out by utilizing time-pushing event occurrence, and system state variables are updated; comparing the state of the system state variable with a preset simulation ending condition, if the comparison result accords with the preset condition, ending the simulation, otherwise, generating a new event based on the state of the updated system state variable;
the base component encapsulates a predefined algorithm data block for establishing the traffic simulation model; the algorithm data block comprises a predefined basic algorithm for establishing the traffic simulation model and general characteristic data of the traffic simulation model; the base component encapsulates algorithms including an engine core algorithm, an algorithm for performing process control, a database, a communication middleware algorithm, and a rules engine; the engine core algorithm comprises a method for performing task management, model analysis and node management; the algorithm for performing process control can control the period, step length and flow propulsion of the simulation process; the database is used for storing simulation data and operation data, wherein the simulation data characterizes data related to the establishment of a traffic simulation model, and the operation data characterizes data generated in the simulation process of the traffic simulation model; the communication middleware algorithm comprises a queuing method in the process of simulating data transmission; the rule engine algorithm simulates a service decision based on the simulation data and the rules of the traffic simulation service type; the business decision is used for indicating a predefined system state variable;
and outputting a simulation result of the traffic simulation model under the initial triggering condition.
2. The experimental method of traffic deduction simulation according to claim 1, wherein the system state variables include attributes of entities, states of activities, and contents of events;
the entities are objects on the road, and the entities have a preset influence relationship with each other; the entity comprises a permanent entity and a temporary entity, wherein the permanent entity represents an object which is permanently existing on a road in the simulation process, and the temporary entity represents an object which is temporarily existing on the road in the simulation process;
the activity characterizes an operation or process that the entity continues for a period of time;
the events characterize operations or behaviors that result in changes in the state of the traffic simulation model.
3. The experimental method of traffic deduction simulation according to claim 2, wherein the selecting a traffic simulation model from a traffic simulation model set based on the traffic simulation service type comprises:
and selecting a traffic simulation model corresponding to the traffic simulation service type based on the traffic simulation service type, and generating an initial state of a system state variable of the traffic simulation model.
4. The experimental method of traffic deduction simulation according to claim 3, wherein the ordering of the events is determined by a random number generator generating random numbers of a prescribed distribution.
5. A system for traffic deduction simulation, comprising:
the input module is used for inputting initial triggering conditions and traffic simulation service types on the basis of the basic framework; the initial triggering condition is a system state variable which causes the actual condition of traffic to change; before the basic framework is formed, carrying out data fusion processing according to simulation parameter data, planning data, traffic flow data, event data, planning data and traffic volume data to form simulation deduction data, and forming a basic framework of traffic simulation based on the simulation deduction data;
the model version control module is used for selecting a traffic simulation model from a traffic simulation model set based on the traffic simulation service type; the traffic simulation model set comprises a plurality of different types of traffic simulation models; the traffic simulation model set comprises a traffic event early warning model, a traffic accident emergency processing model, a road dredging analysis model, a road traffic capacity analysis model, a traffic management scheme evaluation model, a road maintenance strategy evaluation model and a high-speed toll booth processing capacity model;
the traffic simulation module is used for calling a basic component to simulate based on the initial trigger condition and the selected traffic simulation model; the simulating based on the initial triggering condition and the selected traffic simulation model comprises the following steps: based on the initial trigger condition, calling the basic component to change the initial state of a system state variable of a traffic simulation model, and generating new event arrangement; the new event arrangement includes an ordering and listing of new events; based on the new event arrangement, event processing is carried out by utilizing time-pushing event occurrence, and system state variables are updated; comparing the state of the system state variable with a preset simulation ending condition, if the comparison result accords with the preset condition, ending the simulation, otherwise, generating a new event based on the state of the updated system state variable; the base component encapsulates a predefined algorithm data block for establishing the traffic simulation model; the algorithm data block comprises a predefined basic algorithm for establishing the traffic simulation model and general characteristic data of the traffic simulation model; the base component encapsulates algorithms including an engine core algorithm, an algorithm for performing process control, a database, a communication middleware algorithm, and a rules engine; the engine core algorithm comprises a method for performing task management, model analysis and node management; the algorithm for performing process control can control the period, step length and flow propulsion of the simulation process; the database is used for storing simulation data and operation data, wherein the simulation data characterizes data related to the establishment of a traffic simulation model, and the operation data characterizes data generated in the simulation process of the traffic simulation model; the communication middleware algorithm comprises a queuing method in the process of simulating data transmission; the rule engine algorithm simulates a service decision based on the simulation data and the rules of the traffic simulation service type; the business decision is used for indicating a predefined system state variable;
and the traffic simulation result output module is used for outputting the simulation result of the traffic simulation model under the initial triggering condition.
6. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the experimental method of traffic deduction simulation according to any one of the preceding claims 1 to 4 when executing the computer program.
7. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the experimental method of traffic deduction simulation according to any one of claims 1 to 4.
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