Analysis of Urban Bicycles’ Trip Behavior and Efficiency Optimization

Abstract

Bicycle sharing systems are becoming more and more prevalent in urban environments. They provide a low environmental friendly transportation alternative city. The management of these systems brings many optimization problems. The most important of these problems is the individual maintenance of bicycle rebalancing and shared facilities, and the use of systems by creating requirements in asymmetrical patterns. In order to solve the problem of unbalanced use of bicycles, based on real data sets, a series of data mining is developed around these issues. By analyzing the characteristics of each site, the site is modeled from the perspective of individuals and clusters, through different models. The evaluation indicators to detect the accuracy of the results provide an effective method for predicting shared bicycles.