Analysis Of Human And Bicycle Movement Law Based On Mobike

With the rapid development of urbanization,we are faced with many challenges in environment,energy,transportation and so on.Therefore,a greener and more sustainable transport system is crucial to the future development of cities,and shared transport is an important part of that.In recent years,shared bikes have become very popular and become one of the most frequently used transportation tools in People’s Daily life.Previous researches in this field are mostly based on pile-type shared bikes,while researches on pile-less shared bikes are relatively few.Therefore,this topic is mainly based on the pile-less bike-sharing system.Institute of the original data set is to get to Beijing and Shanghai are the city’s bike ride related data,the data set each cycling records all contains the order number,customer number,cycle number,cycling track coordinates longitude and latitude,the origin coordinate latitude and longitude,end coordinates longitude and latitude and their corresponding time stamp and other relevant information.The main research contents and conclusions are summarized as follows:1.To explore the distribution of cycling activities in Beijing and Shanghai and the spatial scale relationship between the cumulative amount of cycling activities and the distance between urban centers.The spatial distribution of cycling initiation and termination activities was examined,and the activity accumulation and distance distribution from the city center were quantitatively analyzed.It was found that the spatial distribution was consistent with the spatial scale theory.2.To explore the distribution of traffic volume within Beijing and Shanghai,and the distribution of the relationship between traffic volume and distance between regions.Rasterize the interior space of the city,that is,divide the area.The statistical results show that the regional traffic volume conforms to the power-law distribution under the relatively fine spatial resolution(500m).The relationship between the traffic volume and the distance from the regional center accords with the fat-tail distribution.3.Verify the validity of the general gravity model in different spatial scales in the city interior,and carry on the variation of the general gravity model,and make a comparative analysis of the results.Based on the above idea of urban interior rasterization,the general gravity model is obtained to be effective according to different spatial resolutions,and the influence of population on inter-regional single vehicle traffic volume is relatively more important.4.Based on fine spatial resolution,the distribution of the relationship between the weighted average distance and the traffic flow of bicycles in different areas was explored.The visualization results show that the distribution of the two cities is similar.The weighted average distance of the cycling area is relatively small,but the spatial distribution of the corresponding area is slightly different.Shanghai is basically distributed in the urban fringe areas,while Beijing will have part relatively close to the city center.5.The cycling patterns at some special locations(sources and sinks)that cannot be fully explained by gravity models at different spatial scales are studied,as well as the distribution of inbound and outbound traffic in each area.The number of source and sink regions(only outlet or only inlet)can not be ignored,and decreases with the increase of spatial scale,and the matching quantity of the two regions is relatively small.There is a good linear relationship between the distribution of inbound and outbound traffic in each region,that is,the inbound and outbound traffic in each region is basically the same.6.Groups were made with bicycles and users as the main body,that is,the cycling records of the same user(bicycle)were divided into a group.By looking at the visualization results of the spatial distribution of movement tracks after grouping,it is found that the movement characteristics of users(bikes)are different:for a single user,the movement tracks are relatively concentrated,while for a single bike,the movement tracks are relatively scattered.Then,based on the above grouping,the distribution relationship between the distance and times of movement of users(bikes)is obtained.It can be seen that users have a certain preference for the choice of bikes and tend to choose the bikes with newer and better functions.