Identifying Key Factors to Affect Taxi Travel Considering Spatial Dependence: A Case Study for Seoul

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips accordin...

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Bibliographic Details
Published inThe Journal of The Korea Institute of Intelligent Transport Systems Vol. 18; no. 5; pp. 64 - 78
Main Authors Lee, Hyangsook, Kim, Ji yoon, Choo, Sangho, Jang, Jin young, Choi, Sung taek
Format Journal Article
LanguageEnglish
Published 한국ITS학회 31.10.2019
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Summary:This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran’s I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips. KCI Citation Count: 1
Bibliography:http://journal.kits.or.kr/
ISSN:1738-0774
2384-1729
DOI:10.12815/kits.2019.18.5.64