Method for optimizing public bicycle station layout by applying GPS data of mobile phone
A technology of public bicycles and GPS data, which is applied to the station layout design of urban public bicycles and the optimization field of existing public bicycle stations. It can solve the problem of lack of OD matrix, no detection of passenger traffic mode, uncertain construction conditions of bicycle stations, etc. question
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2020-11-13
Smart Images

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Abstract
Description
technical field
[0001] The invention relates to a site layout design method for urban public bicycles, in particular to the optimization of existing public bicycle sites, and belongs to the field of traffic planning. Background technique
[0002] As a representative of smart and sustainable urban development, the public bicycle system is a hot spot in transportation, public health, and urban planning. Public bicycles not only bring convenience to short-distance travel, but also expand the influence of public transport stations, especially subways, improve the travel structure for medium and long distances, and save road resources. However, due to the unreasonable setting of bicycle stations, the public bicycle has been greatly affected to play its due role. In the past practical layout optimization, demand forecasting was the first difficulty. It was necessary to estimate potential traffic demand according to the location (such as shopping malls, hospitals, subway stations,...
Examples
Embodiment
[0053] Example: see figure 1 , figure 2 , a method of applying GPS data to optimize the layout of a public bike station, the method comprising the following steps:
[0054] (1) In order to more accurately identify the starting and ending points of bicycle users, this paper collects GPS trajectory data of some representative citizens for a period of time through operators;
[0055] (2) Divide the collected trajectory data into stay trajectories and moving trajectories, and divide the moving trajectories into 5 types of trajectories such as train, subway, car, bicycle, and walking through the random forest model;
[0056] (3) Extract the OD of all bicycle trips, and apply the geometric probability model to establish the probability and model of all OD trajectories;
[0057] (4) According to the actual situation, set the planned number of public bicycle stations in the area and the radius of each probability area, and apply the predator-prey particle swarm algorithm (PP-PSO) t...