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A shared electric vehicle station user demand prediction method

A technology for electric vehicles and user needs, applied in the field of urban transportation, to achieve the effect of simple data acquisition

Pending Publication Date: 2019-06-04
SOUTHEAST UNIV
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

Few relevant studies consider the impact of site external factors on site user needs and establish models for analysis

Method used

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  • A shared electric vehicle station user demand prediction method
  • A shared electric vehicle station user demand prediction method
  • A shared electric vehicle station user demand prediction method

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Embodiment Construction

[0048] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0049] Such as figure 1 As shown, the present invention proposes a method for forecasting user demand at a shared electric vehicle site, comprising the following steps:

[0050] (1) Obtain real-time information of shared electric vehicle sites in continuous time. Each sample information extracted includes time, site number, site coordinates, number of berths at the site and real-time information of existing parked vehicles in the site. Vehicle real-time information includes vehicle License plate ...

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Abstract

The invention discloses a shared electric vehicle station user demand prediction method. According to the method, a station is selected as a circle center, two data acquisition subsystems are established by taking a buffer area within a range of square and round one kilometer as a research object, wherein one system acquires characteristic data such as population economic characteristics, employment, entertainment, medical service, traffic modes and road networks in the buffer area, and the other system acquires parking space number data of a station, and travel data of the shared electric vehicle in the continuous time; deep mining and fusion are performed on the two pieces of data to form input data, and finally a whole set of shared electric vehicle station user demand prediction technology is established based on semi-parametric spatial geographic weighting Poisson regression; The technology can provide user demand change prediction support for the design of a berth number change adjustment scheme in the existing site layout, the influence of site surrounding built-up environment change on site user demands and the like.

Description

technical field [0001] The invention belongs to the field of urban transportation, in particular to a method for predicting user demand at a shared electric vehicle site based on a semi-parametric spatial geographic weighted Poisson regression model. Background technique [0002] Shared electric vehicles are small and mini-buses that are priced in minutes or hours, and use mobile Internet, global positioning and other information technologies to build a network service platform to provide users with self-service electric vehicle reservations, vehicle pick-up and return, and fee settlement. Leasing service is an innovation in service mode, technology and management of traditional small and mini bus leasing. [0003] Previous studies have shown that the existing shared electric vehicle rental market share is extremely low, and there is a certain deviation between the site layout design and berth configuration of shared electric vehicles and user needs, but research on user dem...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/29G06Q10/06
Inventor 杜安业徐铖铖文雨昂李唯一许光瑞牛泽晖
Owner SOUTHEAST UNIV
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