Analysis of High-frequency Occurrence Areas of Beijing Taxis based on the K-means Method

Abstract

As the economy grows and of the pace of life accelerates, travelling by taxi has gradually become one of the most convenient and fastest choices for residents to go out. However, because of the randomness of people's travelling and the mobility of taxi driving, there exist an imbalance between the travelling demand of regional taxi users and the supply of taxis. In order to avoid the problem of uneven distribution of taxis and to achieve accurate prediction of taxi demand, this paper selects the vehicle number, latitude and longitude, and carrying status data of Beijing taxis as the basis of the study, and researches to explore the spatial distribution characteristics of the travelling demand of taxi users. The main contents of the paper are as follows. First of all, this paper initializes the GPS data of taxis, and obtains the boarding and alighting locations. The distribution of taxi regional travel demand is described by using K-means clustering method. Finally, the paper shows five high frequency locations. It is of great significance for taxi dispatching management, reducing empty rate, saving energy consumption and maximizing passenger travel demand.