Exploring Taxi Demand Distribution of Comprehensive Land-Use Patterns Using Online Car-Hailing Data and Points of Interest in Chengdu, China

Abstract

With the rapid advance of urbanization, land-use intensity is increasing, and various land-use forms gather to form comprehensive land-use patterns. Traffic demand shows variability and complexity under comprehensive land-use patterns. Accurate analysis of traffic demand in urban transportation is the key to active traffic control and road guidance. Researchers have widely studied the relationship between traffic demand and land-use patterns, while land-use intensity is ignored when classifying land-use patterns, and the traffic demand distribution in each land-use pattern is not studied specifically. Taxi is a flexible public mode in urban areas, and taxi demand is an important component in analyzing traffic demand and identifying traffic hotspots in cities. This paper explores taxi demand distribution of comprehensive land-use patterns using online car-hailing data and points of interest (POI) in Chengdu, China. The demand-driven traffic analysis zones are developed by clustering origin–destination points of online car-hailing services. Using POI data, comprehensive land-use patterns are classified with land-use forms and land-use intensity. The K-shape algorithm is adopted to extract the typical taxi demand distribution in each comprehensive land-use pattern. Finally, two indicators, total taxi demand (TTD) and taxi demand difference (TDD), are computed and further analyzed. Results show that taxi demand distribution is still differential even under the same land-use pattern. Three land-use patterns whose average hourly taxi demand reaches about 300 vehicles per square kilometer have the largest TTD and most uneven TDD. The findings can support traffic management, land-use combination, and land-use adjustment to avoid concentrated taxi demand and mismatched TDD.