CN110930705B - Intersection traffic decision system, method and equipment - Google Patents
Intersection traffic decision system, method and equipment Download PDFInfo
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- CN110930705B CN110930705B CN201911194692.7A CN201911194692A CN110930705B CN 110930705 B CN110930705 B CN 110930705B CN 201911194692 A CN201911194692 A CN 201911194692A CN 110930705 B CN110930705 B CN 110930705B
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Abstract
The invention discloses a system, a method and equipment for making a traffic decision at a crossing, wherein the system comprises: the user information processing device is used for receiving intersection traffic decision request information input by a user; the decision analysis device is used for generating an intersection traffic decision scheme according to the intersection traffic decision request information, judging whether each intersection traffic index in the intersection traffic decision scheme conforms to the corresponding preset threshold range or not, and determining the intersection traffic index which does not conform to the corresponding preset threshold range in the intersection traffic decision scheme; and the decision screening device is used for carrying out weight sorting on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme and selecting the intersection traffic optimal decision scheme according to the result of the weight sorting. By implementing the invention, the optimal decision scheme of the intersection traffic is automatically obtained by combining the intersection traffic decision request information input by the user, and the labor cost is reduced.
Description
Technical Field
The invention relates to the field of traffic decision support, in particular to a system, a method and equipment for intersection traffic decision.
Background
With the gradual improvement of the living standard of residents, the automobile holding capacity of the residents is increased with the gradual improvement of the economic standard, and under the condition, the efficient operation of urban traffic becomes an important factor for the rapid development of urban economy and the improvement of the living style of people; the key point is the traffic capacity of the nodes of the roads, namely the intersections.
The related technologies are continuously developed and innovated, and at present, the related technologies mainly focus on the application of a knowledge-based expert system in intersection signal design, establish an optimization timing model through the expert system based on pre-made knowledge and rules, and output a better decision solution, that is, an optimization decision of a traffic jam problem is obtained based on simple statistical analysis and visual display of various detection data, and the defect that learning data content cannot be automatically updated based on the obtained data content and knowledge exists, so that the intersection traffic signal optimization especially depends on manual optimization, the labor cost is increased, and a corresponding optimization solution proposal cannot be provided according to long-term dynamic data in different time periods.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defects that the prior art depends on manual optimization during intersection traffic signal optimization, increases labor cost and cannot provide corresponding optimization solution suggestions according to long-term dynamic data at different time intervals, thereby providing an intersection traffic decision system, a method and equipment.
According to a first aspect, an embodiment of the present invention discloses an intersection traffic decision system, including: the user information processing device is used for receiving intersection traffic decision request information input by a user; the decision analysis device is used for generating an intersection traffic decision scheme according to the intersection traffic decision request information, judging whether each intersection traffic index in the intersection traffic decision scheme accords with a corresponding preset threshold range, and determining intersection traffic indexes which do not accord with the corresponding preset threshold range in the intersection traffic decision scheme; and the decision screening device is used for carrying out weight sorting on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme and selecting the intersection traffic optimal decision scheme according to the weight sorting result.
With reference to the first aspect, in a first implementation manner of the first aspect, the traffic optimization system further includes a knowledge base device, configured to collect optimization decision scheme data information, traffic data directory data information, traffic optimization knowledge data information, traffic evaluation index data information, and traffic optimization case data information, and establish a traffic optimization knowledge graph according to the collected information.
With reference to the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the decision analysis apparatus includes: the intersection traffic decision generating unit is used for generating an intersection traffic decision scheme according to the intersection traffic decision request information and a preset intersection traffic decision obtaining model; and the judging unit is used for respectively judging whether the queuing length index, the average delay time index and the light waiting frequency index in the intersection traffic decision scheme accord with the corresponding preset threshold range or not according to the intersection traffic decision scheme, and determining the intersection traffic index which does not accord with the preset threshold range.
With reference to the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the process of the decision analysis device for building the preset intersection traffic decision obtaining model includes: acquiring traffic optimization knowledge map information in the knowledge base device; acquiring an intersection traffic decision request and an intersection traffic decision scheme within a preset time period according to the traffic optimization knowledge map information; and training a deep learning neural network model according to the intersection traffic decision request and the intersection traffic decision scheme in the preset time period, and generating the preset intersection traffic decision obtaining model.
With reference to the first aspect, in a fourth implementation manner of the first aspect, the decision screening apparatus includes: the sorting unit is used for sorting the intersection traffic indexes which do not accord with the corresponding preset threshold value according to the weight; and the optimal decision scheme obtaining unit is used for determining the influence degree of each intersection traffic index which does not accord with the corresponding preset threshold value on the intersection traffic decision scheme according to the weight sorting result, and selecting the intersection traffic decision scheme corresponding to the intersection traffic index with the minimum influence degree as the intersection traffic optimal decision scheme.
With reference to the first aspect, in a fifth implementation manner of the first aspect, the user information processing apparatus is further configured to: and feeding back the optimal decision scheme of the intersection traffic to the user.
With reference to the fifth embodiment of the first aspect, in the sixth embodiment of the first aspect, the user information processing apparatus includes: the first receiving unit is used for receiving the intersection traffic decision request information; the first conversion unit is used for converting the intersection traffic decision request information into a preset first interactive language; a first transmission unit, configured to transmit the first interactive language to the decision analysis apparatus; the second receiving unit is used for receiving the optimal intersection traffic decision scheme output by the decision screening device; the second conversion unit is used for converting the optimal intersection traffic decision scheme into a preset second interactive language; and the second transmission unit is used for transmitting the second interactive language to the user.
With reference to the sixth implementation manner of the first aspect, in the seventh implementation manner of the first aspect, the first interaction language is in the form of a computer language; the second interactive language includes a text form that has an actual meaning and that a user can make a decision directly.
According to a second aspect, the embodiment of the invention discloses an intersection traffic decision method, which comprises the following steps: receiving intersection traffic decision request information input by a user; generating an intersection traffic decision scheme according to the intersection traffic decision request information; judging whether each intersection traffic index in the intersection traffic decision scheme conforms to a corresponding preset threshold range or not, and determining intersection traffic indexes which do not conform to the corresponding preset threshold range in the intersection traffic decision scheme; and carrying out weight sequencing on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme, and selecting an intersection traffic optimal decision scheme according to the weight sequencing result.
With reference to the second aspect, in a first embodiment of the second aspect, the method further includes: collecting optimization decision scheme data information, traffic data directory data information, traffic optimization knowledge data information, traffic evaluation index data information and traffic optimization case data information; and establishing a traffic optimization knowledge graph according to the collected information.
According to a third aspect, an embodiment of the present invention discloses an intersection traffic decision device, including: at least one controller, configured to execute the intersection traffic decision support method according to the second aspect or any embodiment of the second aspect, and analyze and process the decision request information initiated by the user.
According to a fourth aspect, the embodiment of the present invention discloses a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the intersection traffic decision support method as described in the second aspect or any one of the embodiments of the second aspect.
The technical scheme of the invention has the following advantages:
the invention provides a system, a method and equipment for making a decision on intersection traffic. The system receives intersection traffic decision request information input by a user through a user information processing device; generating an intersection traffic decision scheme according to the intersection traffic decision request information through a decision analysis device, further judging whether each intersection traffic index in the intersection traffic decision scheme conforms to a corresponding preset threshold range, and determining intersection traffic indexes which do not conform to the corresponding preset threshold range in the intersection traffic decision scheme; finally, through the decision screening device, the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme are subjected to weight sorting, and the optimal decision scheme of intersection traffic can be selected according to the result of the weight sorting, so that the defect that in the prior art, intersection traffic signals depend on manual optimization during optimization, and corresponding optimization solution suggestions cannot be provided according to long-term dynamic data at different time intervals is overcome, and the labor cost is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a block diagram showing a specific example of an intersection traffic decision system according to embodiment 1 of the present invention;
fig. 2 is a block diagram showing another specific example of an intersection traffic decision system according to embodiment 1 of the present invention;
fig. 3 is a block diagram of a decision analysis device in an intersection traffic decision system according to embodiment 1 of the present invention;
fig. 4 is a flowchart illustrating a preset intersection traffic decision obtaining model established by a decision analysis device in an intersection traffic decision system according to embodiment 1 of the present invention;
fig. 5 is a block diagram of a decision screening device in an intersection traffic decision system according to embodiment 1 of the present invention;
fig. 6 is a block diagram of a user information processing device in an intersection traffic decision system according to embodiment 1 of the present invention;
fig. 7 is a block flow diagram of a specific example of an intersection traffic decision method in embodiment 2 of the present invention;
fig. 8 is a block diagram showing a specific example of an intersection traffic decision device in embodiment 3 of the present invention;
fig. 9 is a block diagram of a first controller in an intersection traffic decision device in embodiment 3 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "first", "second", and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the term "connected" is to be interpreted broadly, e.g. as a fixed connection, a detachable connection, or an integral connection; may be an electrical connection; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment of the present invention provides an intersection traffic decision system, which is applied to specific application scenarios of intelligent intersection research, intelligent intersection analysis, and intelligent intersection problem diagnosis and analysis in the intersection traffic field, and the intersection traffic decision system in this embodiment, as shown in fig. 1, includes:
and the user information processing device 10 is used for receiving intersection traffic decision request information input by a user. In the present embodiment, the user information processing device 10 is configured to receive decision request information input by a user, and output an intersection traffic optimal decision scheme obtained by analyzing and processing by the intersection traffic decision system. Specifically, the user information processing device 10 is a human-computer interaction device in the practical sense, connects the user with the intersection traffic decision system, converts the decision request information of the user into a computer language that can be understood by the system, and inputs the computer language into the decision analysis device 20, and also converts the intersection traffic optimal decision scheme obtained by the intersection traffic decision system through analysis and screening into a text or other forms that have practical meanings and can be directly utilized for decision making, and outputs the text or other forms to the user.
And the decision analysis device 20 is configured to generate an intersection traffic decision scheme according to the intersection traffic decision request information, determine whether each intersection traffic index in the intersection traffic decision scheme conforms to a corresponding preset threshold range, and determine an intersection traffic index which does not conform to the corresponding preset threshold range in the intersection traffic decision scheme. In this embodiment, the decision analysis system is a traffic optimization decision tree established based on a traffic optimization knowledge map and the traffic optimization knowledge map, and an intersection traffic decision obtaining model established by fusing knowledge related to decision requests, specifically, the model is a deep learning neural network model trained according to a plurality of intersection traffic decision requests and intersection traffic decision schemes in a preset time period, so as to generate a preset intersection traffic decision obtaining model, thereby forming an auxiliary technology of intersection traffic optimization decision driven by knowledge and data. By utilizing the auxiliary technology, the traffic optimization deep learning neural network, the intersection traffic knowledge and the intersection traffic data are fused, and then an intersection traffic decision scheme can be obtained according to the intersection traffic decision request.
Specifically, a plurality of intersection traffic decision schemes meeting decision requests are obtained through a trained deep learning neural network model, and the decision analysis device 20 analyzes the problems in each intersection traffic decision scheme, and actually, the problem symptoms are problem points and disease points fed back by the system, and are the diseases detected by the system according to the intersection traffic decision request, that is, intersection traffic evaluation indexes which do not reach preset thresholds in the detected intersection traffic decision schemes, such as queue length, traffic capacity, light number of waiting, space occupancy, time occupancy, parking time, average delay time, queue delay, phase saturation and phase green signal ratio.
And the decision screening device 30 is used for performing weight sorting on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme, and selecting the intersection traffic optimal decision scheme according to the weight sorting result. In this embodiment, the decision screening device 30 processes the "diagnosed" or checked problems of the decision analysis device 20, and is an interface of the user information processing device 10, and is a processing system based on the traffic optimization knowledge map and the traffic optimization decision tree, and the analyzed and processed symptoms and solutions are sorted according to the weight combination, and the preset traffic problem diagnosis and optimization scheme auxiliary decision model is used to obtain the optimal answers, so as to obtain the traffic problem diagnosis result and the optimization scheme decision suggestion.
In the embodiment, the intersection traffic decision system further comprises a traffic optimization knowledge graph based on the knowledge base device 40, which can deeply analyze the "question", collect information and knowledge related to the "question", identify, judge, and solve the "question", and then can input the "question" and the "solution" to the decision screening device 30.
The intersection traffic decision system provided by this embodiment performs weight sorting on intersection traffic indexes in an intersection traffic decision scheme output by the system according to a decision request of a user through the user information processing device 10, the decision analysis device 20, and the decision screening device 30, and selects an optimum intersection traffic decision scheme according to a result of the weight sorting. The problem of because of optimizing personnel's level is uneven, optimization cost is too high, optimization means is single, produce strong dependence to manual optimization is solved, reached can obtain the effect of optimum decision-making solution automatically, the cost is reduced.
As shown in fig. 2, the intersection traffic decision system further includes a knowledge base device 40, which is used for collecting data information of the optimization decision scheme, data information of the traffic data directory, data information of the traffic optimization knowledge, data information of the traffic evaluation index, and data information of the traffic optimization case, and establishing a traffic optimization knowledge map according to the collected information. Specifically, the data information of the optimization decision scheme may also be referred to as a traffic optimization decision scheme library, which includes various traffic optimization means based on timing adjustment, such as traffic channeling organization, release mode, and the like, and the data information of the traffic data directory may also be referred to as a traffic data directory library, which includes traffic data descriptions and directories for various traffic detection data, traffic channeling data, and the like, and similarly, the traffic optimization knowledge library includes storage of various traffic optimization professional knowledge, the traffic evaluation index library includes various macroscopic, mesoscopic, and microscopic traffic operation evaluation indexes, and the traffic optimization case library stores cases of solving actual traffic problems in preset time periods in various places. The knowledge base device 40 not only includes these 'libraries', but also includes formulas, models, rules, analysis tools, evaluation criteria, etc. in the intersection traffic decision process, and is an organized storage and management system with computing capability, which is a set of all knowledge that can support intersection traffic decisions.
In this embodiment, the knowledge base device 40 establishes a traffic optimization knowledge map through the above-mentioned various data information, and the traffic optimization knowledge map can be used as a basis of an intersection traffic decision system. Specifically, the traffic optimization knowledge map is a network map made based on the traffic optimization knowledge data information and some traffic rules, and the traffic optimization knowledge map in the knowledge base device 40 is used in both the decision analysis device 20 and the decision screening device 30, so that a corresponding intersection traffic decision solution can be obtained according to an intersection traffic decision request. For example, the intersection traffic decision obtaining model in the decision analysis device 20 is generated according to the traffic optimization knowledge map. For example, when the intersection traffic decision request is a timing optimization problem, the traffic optimization knowledge graph may be an optimization decision suggestion related to the timing decision request, including: the traffic canalization organization comprises a series of evaluation indexes such as a straight left vehicle proportion, a big vehicle proportion, a small vehicle proportion, a pedestrian crossing index, a lane width, a lane number, an intersection size and the like.
In the present embodiment, as shown in fig. 3, the decision analysis device 20 includes:
an intersection traffic decision generating unit 201, configured to generate an intersection traffic decision scheme according to the intersection traffic decision request information and a preset intersection traffic decision obtaining model;
the judging unit 202 is configured to respectively judge whether the queuing length index, the average delay time index, and the light waiting time index in the intersection traffic decision scheme meet the corresponding preset threshold range according to the intersection traffic decision scheme, and determine an intersection traffic index that does not meet the preset threshold range. Specifically, the intersection traffic index may be a queue length, a traffic capacity, a number of lights waiting, a space occupancy, a time occupancy, a parking time, an average delay time, a queue delay, a phase saturation, a phase split ratio, and the like.
Specifically, as shown in fig. 4, the process of establishing the preset intersection traffic decision obtaining model includes:
step S41: traffic optimization knowledge map information in the knowledge base device 40 is obtained. The knowledge base device 40 stores knowledge related to intersection traffic decision, and firstly obtains a traffic optimization knowledge map based on the knowledge, specifically, the traffic optimization knowledge map is based on end-to-end named entity recognition and relationship extraction of deep learning, improves the precision of named entity recognition and relationship extraction simultaneously by utilizing a multi-task mode, and constructs the traffic optimization knowledge map by utilizing a neural network technology, a knowledge map technology and artificial knowledge. The map shows contents such as related popular science knowledge, traffic flow symptoms, optimization means, evaluation indexes and the like around various traffic problems.
Step S42: and acquiring an intersection traffic decision request and an intersection traffic decision scheme in a preset time period according to the traffic optimization knowledge map information. In this embodiment, the system stores the intersection traffic decision request and the corresponding intersection traffic optimal decision scheme within a preset time period.
Step S43: and training a deep learning neural network model according to the intersection traffic decision request and the intersection traffic decision scheme in the preset time period, and generating a preset intersection traffic decision obtaining model. Specifically, the deep learning neural network is used for deeply learning the neural network through the neural network according to a sufficient number of inputs and preset outputs, namely, the deviation from an ideal value is reduced as much as possible, and when the system inputs detection data, intersection channelized data and control scheme data obtained for an intersection, control effect evaluation data is obtained after the intersection traffic decision system operates.
In this embodiment, the intersection traffic decision obtaining model has a deep learning neural network background, and a deep learning technique is used, so that when the intersection traffic decision system reaches the intersection traffic decision obtaining model learning time, for example, 24 hours, all-day operation data and values, that is, the input intersection traffic decision request and the corresponding intersection traffic optimal decision scheme, as well as the optimized decision scheme data information, the traffic optimized decision tree, and the like in the knowledge base device 40 are called to perform self-learning training, for example, when three angles are reached: the system automatically stores the decision request and the corresponding intersection traffic decision scheme when the output intersection traffic optimal decision scheme is adopted, can also be used as the intersection traffic decision to obtain suboptimal data under the model, and can also be stored if the output intersection traffic optimal decision scheme is rejected, but the output intersection traffic optimal decision scheme is used as the next corrected data of the intersection traffic decision to obtain the model, and becomes a skilled intersection traffic decision obtaining model after repeated iterative learning, thereby becoming a skilled and intelligent intersection traffic optimization decision support system.
In this embodiment, as shown in fig. 5, the decision screening apparatus 30 specifically includes:
the sorting unit 51 is used for sorting the intersection traffic indexes which do not accord with the corresponding preset threshold value according to the weight; for example, the two decision schemes for signal timing obtained through the above processing are respectively a first decision scheme and a second decision scheme, and the average delay time obtained through the decision analysis device 20 in the first decision scheme, that is, the time difference between the time when the vehicle actually passes through the intersection and the time when the vehicle passes through the intersection at the desired speed does not satisfy the preset threshold range; in the second decision scheme, the decision analysis device 20 obtains the stopping time, that is, the waiting time or the dead time of the vehicle before the intersection stop line does not meet the preset threshold range. The "average delay time" and "parking time" are weighted and ranked, that is, it is considered that in the decision request of signal timing, which of the two intersection traffic indexes of "average delay time" and "parking time" has less influence on signal timing, specifically, even if the index is not ideal, there is only a certain interference to the "signal timing" problem.
The optimal decision-making scheme obtaining unit 52 is configured to determine, according to the weight sorting result, the influence degree of each intersection traffic index that does not meet the corresponding preset threshold on the intersection traffic decision-making scheme, and select the intersection traffic decision-making scheme corresponding to the intersection traffic index with the smallest influence degree as the intersection traffic optimal decision-making scheme.
In the intersection traffic decision system of the present embodiment, specifically, as shown in fig. 6, the knowledge base device 40 includes:
the first receiving unit 61 is configured to receive intersection traffic decision request information.
And a first conversion unit 62, configured to convert the intersection traffic decision request information into a preset first interactive language. Specifically, the preset first interactive language may be a binary language that can be directly understood by the computer.
A first transmission unit 63, configured to transmit the first interactive language to the decision analysis apparatus 20.
And a second receiving unit 64, configured to receive the intersection traffic optimal decision scheme output by the decision screening device 30.
And a second conversion unit 65, configured to convert the intersection traffic optimal decision scheme into a preset second interactive language. In particular, the preset second interactive language may be in the form of text or the like having an actual meaning and/or a decision may be directly utilized by the decision maker.
A second transmission unit 66 for transmitting the second interactive language to the user.
The intersection traffic decision system in the embodiment of the invention comprises: the user information processing device 10 is used for receiving intersection traffic decision request information input by a user; a decision analysis device 20, configured to generate an intersection traffic decision scheme according to the intersection traffic decision request information, determine whether each intersection traffic index in the intersection traffic decision scheme meets a corresponding preset threshold range, and determine an intersection traffic index in the intersection traffic decision scheme that does not meet the corresponding preset threshold range; and the decision screening device 30 is used for performing weight sorting on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme, and selecting an intersection traffic optimal decision scheme according to the result of the weight sorting. By constructing a traffic optimization problem diagnosis and optimization scheme decision auxiliary model, the traffic symptom problem intelligent diagnosis and analysis aiming at the intersection traffic slow-blocking problem in the urban traffic process are realized, the follow-up traffic optimization is turned to intelligent technology optimization, the problems of high dependence on manual optimization caused by uneven optimization personnel level, overhigh optimization cost and single optimization means are avoided, and suggestions and solutions can be automatically obtained.
Example 2
The embodiment provides an intersection traffic decision method, which can be applied to specific application scenarios of intelligent intersection investigation, intelligent intersection analysis and intelligent intersection problem diagnosis and analysis in the intersection traffic field, as shown in fig. 7, the method includes:
step S71: and receiving intersection traffic decision request information input by a user. For detailed implementation, reference may be made to the related description of the user information processing device 10 of the above system embodiment.
Step S72: and generating an intersection traffic decision scheme according to the intersection traffic decision request information. For detailed implementation, reference may be made to the above description of the decision analysis device 20 of the system embodiment.
Step S73: and judging whether the traffic indexes of all roads in the road traffic decision scheme meet the corresponding preset threshold range. For detailed implementation, reference may be made to the above description of the decision analysis device 20 of the system embodiment.
Step S74: and determining intersection traffic indexes which do not accord with the corresponding preset threshold range in the intersection traffic decision scheme. For detailed implementation, reference may be made to the above description of the decision analysis device 20 of the system embodiment.
Step S75: and carrying out weight sorting on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme, and selecting an intersection traffic optimal decision scheme according to the weight sorting result. For detailed implementation, reference may be made to the related description of the decision screening device 30 of the above system embodiment.
The invention provides a crossing traffic decision method, which receives crossing traffic decision request information input by a user; generating an intersection traffic decision scheme according to the intersection traffic decision request information; judging whether each intersection traffic index in the intersection traffic decision scheme conforms to a corresponding preset threshold range or not, and determining intersection traffic indexes which do not conform to the corresponding preset threshold range in the intersection traffic decision scheme; and carrying out weight sequencing on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme, and selecting an intersection traffic optimal decision scheme according to the weight sequencing result. The defects that manual optimization is relied on during intersection traffic signal optimization, labor cost is increased, and corresponding optimized solution suggestions cannot be provided according to long-term dynamic data of different time periods in the prior art are overcome, so that the optimal solution can be automatically obtained, response speed and efficiency of determining intersection traffic decision requests are improved, and cost is reduced.
Example 3
The present embodiment provides an intersection traffic decision device, as shown in fig. 8, including:
the first communication module 811 is used for transmitting data information, receiving intersection traffic decision request information input by a user and sending an intersection traffic optimal decision scheme to the user;
a first controller 812, configured to analyze and process the intersection traffic decision request according to the information received by the first communication module 811, where the first controller 812 is connected to the first communication module 811, as shown in fig. 9, and includes: at least one processor 91; and a memory 92 communicatively coupled to the at least one processor 91; the memory 92 stores instructions executable by the at least one processor 91, and when receiving a decision request message from a user, the at least one processor 91 is configured to execute the intersection traffic decision method according to any implementation manner of embodiment 1, in fig. 9, the processor 91 and the memory 92 are connected by a bus 90, for example, in this embodiment, the first communication module may be a wireless communication module, for example, a bluetooth module, a Wi-Fi module, or the like, or may be a wired communication module.
The memory 92 is a non-transitory computer readable storage medium, and can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the intersection traffic decision method in the embodiment of the present application. The processor 91 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 92, so as to implement the intersection traffic decision method of the above method embodiment.
The memory 92 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of a processing device operated by the server, and the like. Further, memory 92 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 92 may optionally include memory located remotely from the processor 91, which may be connected to a network connection device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 92, which when executed by the one or more processors 91 perform the method described in any of the above embodiments.
The intersection traffic decision device 81 provided by the embodiment of the present invention obtains decision solutions corresponding to the intersection traffic decision request through the first controller 812 according to the decision request information of the first communication module 811 by the user, and analyzes and screens the solutions to obtain an optimum intersection traffic decision solution. By constructing a traffic optimization problem diagnosis and optimization scheme decision auxiliary model, the traffic symptom problem intelligent diagnosis and analysis aiming at the intersection traffic slow-blocking problem in the urban traffic process are realized, the follow-up traffic optimization is turned to intelligent technology optimization, the problems of high dependence on manual optimization caused by uneven optimization personnel level, overhigh optimization cost and single optimization means are avoided, and suggestions and solutions can be automatically obtained.
The embodiment of the present invention further provides a non-transitory computer readable medium, where the non-transitory computer readable storage medium stores a computer instruction, and the computer instruction is used to enable a computer to execute the intersection traffic decision method described in any one of the above embodiments, where the storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard disk (Hard disk Drive, abbreviated as HDD), or a Solid-State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (9)
1. An intersection traffic decision system, comprising:
the user information processing device is used for receiving intersection traffic decision request information input by a user;
the decision analysis device is used for generating an intersection traffic decision scheme according to the intersection traffic decision request information, judging whether each intersection traffic index in the intersection traffic decision scheme accords with a corresponding preset threshold range, and determining intersection traffic indexes which do not accord with the corresponding preset threshold range in the intersection traffic decision scheme;
the decision screening device is used for carrying out weight sorting on the intersection traffic indexes which do not accord with the corresponding preset threshold in the intersection traffic decision scheme and selecting an intersection traffic optimal decision scheme according to the result of the weight sorting;
the knowledge base device is used for collecting data information of an optimization decision scheme, traffic data catalogue data information, traffic optimization knowledge data information, traffic evaluation index data information and traffic optimization case data information, and establishing a traffic optimization knowledge map according to the collected information;
the decision analysis device specifically comprises an intersection traffic decision generation unit, a decision analysis unit and a decision analysis unit, wherein the intersection traffic decision generation unit is used for generating an intersection traffic decision scheme according to the intersection traffic decision request information and a preset intersection traffic decision acquisition model;
the process of establishing the preset intersection traffic decision obtaining model by the decision analysis device comprises the following steps:
acquiring traffic optimization knowledge map information in the knowledge base device;
acquiring an intersection traffic decision request and an intersection traffic decision scheme within a preset time period according to the traffic optimization knowledge map information;
and training a deep learning neural network model according to the intersection traffic decision request and the intersection traffic decision scheme in the preset time period, and generating the preset intersection traffic decision obtaining model.
2. The intersection traffic decision system of claim 1, wherein the decision analysis device further comprises:
and the judging unit is used for respectively judging whether the queuing length index, the average delay time index and the light waiting frequency index in the intersection traffic decision scheme accord with the corresponding preset threshold range or not according to the intersection traffic decision scheme, and determining the intersection traffic index which does not accord with the preset threshold range.
3. The intersection traffic decision system of claim 1, wherein the decision screening device comprises:
the sorting unit is used for sorting the intersection traffic indexes which do not accord with the corresponding preset threshold value according to the weight;
and the optimal decision scheme obtaining unit is used for determining the influence degree of each intersection traffic index which does not accord with the corresponding preset threshold value on the intersection traffic decision scheme according to the weight sorting result, and selecting the intersection traffic decision scheme corresponding to the intersection traffic index with the minimum influence degree as the intersection traffic optimal decision scheme.
4. The intersection traffic decision system of claim 1, wherein the user information processing device is further configured to: and feeding back the optimal decision scheme of the intersection traffic to the user.
5. The intersection traffic decision system according to claim 4, characterized in that the user information processing means comprises:
the first receiving unit is used for receiving the intersection traffic decision request information;
the first conversion unit is used for converting the intersection traffic decision request information into a preset first interactive language;
a first transmission unit, configured to transmit the first interactive language to the decision analysis apparatus;
the second receiving unit is used for receiving the optimal intersection traffic decision scheme output by the decision screening device;
the second conversion unit is used for converting the optimal intersection traffic decision scheme into a preset second interactive language;
and the second transmission unit is used for transmitting the second interactive language to the user.
6. The intersection traffic decision system of claim 5, wherein the first interactive language is in the form of a computer language; the second interactive language includes a text form that has an actual meaning and that a user can make a decision directly.
7. An intersection traffic decision method, comprising:
receiving intersection traffic decision request information input by a user;
generating an intersection traffic decision scheme according to the intersection traffic decision request information;
judging whether each intersection traffic index in the intersection traffic decision scheme conforms to a corresponding preset threshold range or not, and determining intersection traffic indexes which do not conform to the corresponding preset threshold range in the intersection traffic decision scheme;
carrying out weight sorting on intersection traffic indexes which do not accord with corresponding preset threshold values in the intersection traffic decision scheme, and selecting an intersection traffic optimal decision scheme according to the weight sorting result;
collecting optimization decision scheme data information, traffic data directory data information, traffic optimization knowledge data information, traffic evaluation index data information and traffic optimization case data information;
establishing a traffic optimization knowledge graph according to the collected information;
the generating of the intersection traffic decision scheme according to the intersection traffic decision request information specifically comprises: generating the intersection traffic decision scheme according to the intersection traffic decision request information and a preset intersection traffic decision obtaining model;
the process of establishing the preset intersection traffic decision obtaining model comprises the following steps:
acquiring traffic optimization knowledge map information in the knowledge base device;
acquiring an intersection traffic decision request and an intersection traffic decision scheme within a preset time period according to the traffic optimization knowledge map information;
and training a deep learning neural network model according to the intersection traffic decision request and the intersection traffic decision scheme in the preset time period, and generating the preset intersection traffic decision obtaining model.
8. An intersection traffic decision device, comprising:
at least one controller for executing the intersection traffic decision support method of claim 7, analyzing and processing the decision request information initiated by the user.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the intersection traffic decision support method according to claim 7.
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