Area entrance and exit dynamic extraction method based on taxi drop-off points

Abstract

The invention discloses an area entrance and exit dynamic extraction method based on taxi drop-off points, and belongs to the technical field of intelligent transportation. The method comprises the following steps of extracting and preprocessing POI data and taxi drop-off point data; then, subjecting the POI data to clustering analysis according to the position information and the name information; determining regions of interest and setting a peripheral road buffer area of each region of interest; acquiring taxi drop-off point information of a corresponding buffer area, clustering according to the information, determining a taxi drop-off point clustering area of each region of interest, and determining an entrance and exit of the region of interest according to the boundary of the regionof interest, the area center of the region of interest and each taxi drop-off point clustering center corresponding to the region of interest. The entrances and exits of the common regions of interestare extracted and realized through the passenger drop-off point heat associated with the entrances and exits, dynamic monitoring of the entrances and exits of the common regions of interest is realized, and new entrances and exits and distribution rules of existing entrances and exits can be discovered in time.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, in particular to a method for dynamically extracting regional entrances and exits based on taxi drop-off points. Background technique [0002] In recent years, with the rapid development of urbanization, the entrances and exits of AOI (Area of ​​Interests, such as schools, scenic spots, and hospitals) change frequently. In order to guide residents’ daily travel, the network map needs to update the map elements in time. Now With map data, the real-time data of AOI's entrance and exit cannot be updated in time. [0003] In urban environments, taxis are an extremely important part of the urban computing landscape. At present, GPS devices have been installed on taxis in most cities, and the current location information is sent to the data center in real time. Distribution of resources and traffic demands, even road and traffic route planning information. Contents of the inventi...

AI Technical Summary

Problems solved by technology

[0002] In recent years, with the rapid development of urbanization, the entrances and exits of AOI (Area of ​​Interests, such as schools, scenic spots, and hospitals) change frequently. In order to guide residents’ daily travel, the network map needs to update the map elements in time. Now With map data, it is not possible to update the real-time data of the entrance and exit of AOI in time

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