A Stereoscopic Garage Scheduling Control Method

Abstract

A stereo garage scheduling control method is disclosed. The invention relates to the stereo garage intelligence control technology field and discloses a matrix-type stereo garage scheduling control method based on an ACP method. The method comprises the following steps of 101, data information acquisition; 102, request event acquisition; 103, information chain determination; 104, parking slot state acquisition and weight distribution; 105, scheduling scheme determination; and 106, scheduling scheme execution. Through combining large data analysis, complete request event information is acquired. The weight distribution, the complete request event information and the parking slot state information are combined. Through the ACP method, an optimal path scheme is acquired. A purpose that a data fusion analysis and scheduling system adapts to a garage vehicle flowrate is reached. An existing parking resource can be used maximumly and a parking infrastructure construction budget is reduced. A parking process is intelligent and convenient, trip efficiency is increased and operation efficiency of a city is improved. Usability is high, the method can be widely popularized and applied, and a problem that parking is difficult in a population and building density area is alleviated.

Description

Technical field:

[0001] The present invention relates to the technical field of three-dimensional garage intelligent control, in particular to a matrix-type three-dimensional garage scheduling control device based on the ACP method and its method, which combines big data analysis to obtain perfect request event information, and assigns weights, perfect request event information and The combination of garage state information and the optimal path scheme are obtained through the ACP method, so as to achieve the purpose of data fusion analysis and dispatching system's self-adaptation to the garage traffic flow. Background technique:

[0002] At present, with the rapid development of economy and society, the rapid increase of urban motor vehicle ownership has brought enormous pressure to the existing parking infrastructure, and the phenomena of difficult parking and random parking are repeated, especially in densely built areas. , the difficulty of parking is even more serious. ...

Examples

Embodiment 1

[0038] The three-dimensional garage scheduling control device involved in this embodiment, its main structure includes a user demand module 1, a data module 2, a garage information module 3, an intelligent control module 4 and an intelligent scheduling module 5; the user demand module 1 is used to obtain user access The car requests an event and transmits the request event to the intelligent control module 4, receives the garage status data output by the garage information module 3, and receives the waiting time and suggestions for the user event scheduling scheme fed back by the smart scheduling module 5, and sends the garage status data, waiting time Time and suggestions are fed back to the user; the user demand module 1 can be an interactive platform set in the mobile phone terminal APP, vehicle terminal, network platform and garage site; the data module 2 includes a data acquisition unit 13, a database 14 and a data preprocessing unit 15 Three functional parts, the data col...

Embodiment 2

[0061] The experimental design process involved in this embodiment adopts the breadth-first algorithm. First, the 5*5 parking spaces are numbered, and two decimal numbers are used. Tens represent rows, and ones represent columns, as shown in Table 1:

[0062] Table 1 Schematic diagram of the number of parking spaces

[0063]

[0064] In order to represent each state of the dispatching process, the parking space occupancy is coded in the binary form of the data. The information included in the data includes: whether each parking space is occupied and the parking space number of the target vehicle (main vehicle).

[0065] Table 2 Status Code Meaning Table

[0066]

[0067] The maximum value of the data max=2 27 =134,217,728

[0068] The long data type ranges from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807, which is sufficient for encoding, so the long data type is used to encode the state.

[0069] Storage of search information

[0070] Storage of the sear...

Technical field:

[0001] The present invention relates to the technical field of three-dimensional garage intelligent control, in particular to a matrix-type three-dimensional garage scheduling control device based on the ACP method and its method, which combines big data analysis to obtain perfect request event information, and assigns weights, perfect request event information and The combination of garage state information and the optimal path scheme are obtained through the ACP method, so as to achieve the purpose of data fusion analysis and dispatching system's self-adaptation to the garage traffic flow. Background technique:

[0002] At present, with the rapid development of economy and society, the rapid increase of urban motor vehicle ownership has brought enormous pressure to the existing parking infrastructure, and the phenomena of difficult parking and random parking are repeated, especially in densely built areas. , the difficulty of parking is even more serious. ...

Examples

Embodiment 1

[0038] The three-dimensional garage scheduling control device involved in this embodiment, its main structure includes a user demand module 1, a data module 2, a garage information module 3, an intelligent control module 4 and an intelligent scheduling module 5; the user demand module 1 is used to obtain user access The car requests an event and transmits the request event to the intelligent control module 4, receives the garage status data output by the garage information module 3, and receives the waiting time and suggestions for the user event scheduling scheme fed back by the smart scheduling module 5, and sends the garage status data, waiting time Time and suggestions are fed back to the user; the user demand module 1 can be an interactive platform set in the mobile phone terminal APP, vehicle terminal, network platform and garage site; the data module 2 includes a data acquisition unit 13, a database 14 and a data preprocessing unit 15 Three functional parts, the data col...

Embodiment 2

[0061] The experimental design process involved in this embodiment adopts the breadth-first algorithm. First, the 5*5 parking spaces are numbered, and two decimal numbers are used. Tens represent rows, and ones represent columns, as shown in Table 1:

[0062] Table 1 Schematic diagram of the number of parking spaces

[0063]

[0064] In order to represent each state of the dispatching process, the parking space occupancy is coded in the binary form of the data. The information included in the data includes: whether each parking space is occupied and the parking space number of the target vehicle (main vehicle).

[0065] Table 2 Status Code Meaning Table

[0066]

[0067] The maximum value of the data max=2 27 =134,217,728

[0068] The long data type ranges from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807, which is sufficient for encoding, so the long data type is used to encode the state.

[0069] Storage of search information

[0070] Storage of the sear...

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