关键词: 智能交通, IC卡数据, 出行链, 出行模式, 出行周期, 出行特征

Abstract:

Public transit services carry the majority travel demand of urban residents. There is an urgent need for transit authorities to make a better understanding of the travel characteristics of transit riders. Recently, data from smart cards have become a new source of travel survey data, providing more comprehensive spatial-temporal information about urban public transport trips. In this paper, a methodology considering travel patterns and periodicity is developed to analyze the travel characteristics of residents. The individual trip information is firstly obtained based on smart card data and transit riders’trip chains are identified. The DBSCAN clustering algorithm is applied to examine transit riders’historical travel patterns. And a methodology is then proposed for analyzing the travel periodicity based on travel patterns. Finally Kmeans++ algorithm is applied to cluster and evaluate the travel regularities of transit riders. In case study, focused on the transit riders of Guangzhou City, the analysis of travel characteristics are conducted. The results proved the effectiveness of the proposed method. The information mined through the method is of great significant for improving transit service strategies.

Key words: intelligent transportation, smart card data, trip chain, travel pattern, travel periodicity, travel characteristics