Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM

Sustainability

Yong Qi¹  Jinjun Tang²  Fan Gao²  Fang Liu³  Wenhui Zhang⁴ 

[1] School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China;School of Transportation Engineering, Changsha University of Science and Technology, Changsha 410205, China;Traffic School, Northeast Forestry University, Harbin 150040, China;

关键词: travel demand;    geographically weighted regression;    generalized linear model;    spatial heterogeneity;   

DOI  :  10.3390/su11195525

来源: DOAJ

【 摘 要 】

Taxis are an important part of the urban public transit system. Understanding the spatio-temporal variations of taxi travel demand is essential for exploring urban mobility and patterns. The purpose of this study is to use the taxi Global Positioning System (GPS) trajectories collected in New York City to investigate the spatio-temporal characteristic of travel demand and the underlying affecting variables. We analyze the spatial distribution of travel demand in different areas by extracting the locations of pick-ups. The geographically weighted regression (GWR) method is used to capture the spatial heterogeneity in travel demand in different zones, and the generalized linear model (GLM) is applied to further identify key factors affecting travel demand. The results suggest that most taxi trips are concentrated in a fraction of the geographical area. Variables including road density, subway accessibility, Uber vehicle, point of interests (POIs), commercial area, taxi-related accident and commuting time have significant effects on travel demand, but the effects vary from positive to negative across the different zones of the city on weekdays and the weekend. The findings will be helpful to analyze the patterns of urban travel demand, improve efficiency of taxi companies and provide valuable strategies for related polices and managements.

【 授权许可】

Unknown