| EXPLORING DRIVING FACTORS OF HIGHER PAID TAXI TRIPS USING ORIGIN-DESTINATION GPS DATA (CASE STUDY: GREEN TAXIS OF NEW YORK CITY) |
| Paper ID : 1293-SMPR |
| Authors: |
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Pooya Mojtabaee *, Moein Molavi, Mohammad Taleai Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, Iran |
| Abstract: |
| Investigating the influential factors on where people use taxis is a crucial step in understanding the taxi demand dynamics. In this study, we intend to analyze higher paying taxi trips by putting forward an approach to explore a dataset of green taxi trips completed in New York City in Jan 2015 together with some demographic, housing, social and economic data. The final goal is to find out whether the chosen factors are statistically significant to be considered as demand location driving forces for trips with higher fare paid. Since airports are major attracting sources for taxi travels, all the steps are taken separately for three scenarios that the trip drop-offs are in 1) LaGuardia Airport, 2) John F Kennedy Airport or 3) other areas. First, the pickup spatial distribution of these higher paying trips is mapped to visually compare and explore the urban movement patterns. Then taking into account the pickup density as the response variable, the density of foreign-born population, the density of number of houses with no vehicles, the density of private wage and salary workers population, the density of government workers population and the density of self-employed workers in own not incorporate business population were examined to find important factors affecting the demand in each neighborhood and different results in each of the three scenarios were discussed. This study gives a better insight into discovering driving factors of higher paid taxi trips when considering airports as destinations which attract travels with potentially different characteristics. |
| Keywords: |
| GPS Trip Data, NYC Green Taxi, Spatial Patterns, Cost and Fare, Driving Factors, Socioeconomic |
| Status : Conditional Accept (Oral Presentation) |
