Understanding Taxi Driving Behaviors from Movement Data

Abstract. Understanding taxi mobility has significant social and economic impacts on the urban areas. The goal of this paper is to visualize and analyze the spatiotemporal driving patterns for two income-level groups, i.e. high-income and low-income taxis, when they are not occupied. Specifically, we differentiate the cruising and stationary states of non-occupied taxis and focus on the analysis of the mobility patterns of these two states. This work introduces an approach to detect the stationary spots from a large amount of non-occupied trajectory data. The visualization and analysis procedure comprises of mainly the visual analysis of the cruising trips and the stationary spots by integrating data mining and visualization techniques. Temporal patterns of the cruising trips and stationary spots of the two groups are compared based on the line charts and time graphs. A density-based spatial clustering approach is applied to cluster and aggregate the stationary spots. A variety of visu...

• Type: Journal
• Year: 2015
• Where: AGILE
• Authors: Linfang Ding, Hongchao Fan, Liqiu Meng
• Keywords: AGILE 2015, GIS