Data-driven Analysis of Taxi and Ride-hailing Services: Case Study in Chengdu, China

Abstract

Both taxi and Internet-based ride-hailing services are important public transportation options. While these services provide a similar functionality, their quantitative patterns are difficult to describe and analyze without a big data approach. In this study, we present a data-driven analysis for taxi and ride-hailing services with a case study in Chengdu, China. Both a taxi GPS dataset and an Internet-based ride-hailing trip dataset provided by Didi Chuxing, the largest transportation network company in China, are used in this study. Our analysis is based on four aspects, i.e., temporal patterns, spatial patterns, spatio-temporal patterns, and traveling distance patterns. It is found that both taxi and ride-hailing services exhibit the densification power law with a space-time graph model. The ride-hailing service has a preference for more concentrated pickup and dropoff hotspots and trips with a longer distance. The observed results indicate that the ride-hailing service partially plays the role of taxis, but it also has its own characteristics as a new transport option. The findings in this study would be helpful for the government to better regulate the operation of both taxi and ride-hailing services.