Shared automobile parking network point determining method based on automobile using behaviors

Abstract

The invention discloses a shared automobile parking network point determining method based on automobile using behaviors in the field of shared trips. The method comprises the following steps: acquiring GPS position data of each vehicle during temporary parking from a vehicle management system; obtaining parking network points within a set range of the GPS position data and taking the parking network points as candidate parking network points; hierarchical analysis, setting weights for all the first-level indexes of the candidate parking network points respectively, and calculating scores of all the first-level indexes; according to the weight and the score of each first-level index, obtaining a second-level index; calculating a comprehensive score of each candidate parking network point; inputting the comprehensive score into a pre-created parking network point evaluation model; acquiring, the grade of each parking network point in the candidate parking network points generating the grade list and selecting a certain number of parking network points from the candidate parking network points as the parking network points according to the grade list, so that the site selection of the supplementary parking network points in the later period is effectively realized, the user consumption experience is improved, and the urban traffic resource configuration is optimized.

Description

Technical field [0001] The invention belongs to the field of shared travel, and specifically relates to a method for determining a shared car parking network based on car usage behavior. Background technique [0002] Although the car-sharing industry has a good prospect, it is restricted by the layout and quantity of parking sites and parking spaces, which has led to the inability of consumers to fully satisfy their car needs and experience. Therefore, formulating a reasonable and effective location plan will drive the entire investment in shared vehicles and increase the utilization rate of shared vehicles. At the same time, it is of great significance for improving the overall user experience and optimizing the allocation of urban transportation resources. [0003] The existing parking network location methods mainly include the location method based on the third party's morning and evening peak travel heat map data and the circle layer location method. [0004] The location metho...

AI Technical Summary

Problems solved by technology

[0004] The site selection method based on the third-party morning and evening peak travel heat map data is based on the general data of the public, not the precise user group data of the car-sharing industry. It can only provide extensive auxiliary location decision-making data in the early stage, and cannot provide refined consumer data. People's travel car data, so it is impossible to provide effective data support for later optimization and supplementary parking outlets

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