Characterization of Trip-Level Pace Variability Based on Taxi GPS Trajectory Data

Abstract

Travel behavior researchers have observed that the average and standard deviations of trip pace (the inverse of speed) are linearly related. This paper further studies this relationship by using taxi GPS trajectory data collected in the city of Shenzhen, China, in eight periods between early 2013 and late 2015. When tested against the original linear relationship, the data demonstrated heteroscedasticity. To address that issue, a distance- or time-corrected variable was introduced into the original linear model. The resulting two models, along with the original linear model, were tested and compared. The results showed that ( a) the new linear model with the time-corrected pace variable (TCPV) demonstrated the best fit to data compared with the other models, ( b) the parameters of the TCPV model showed strong consistency for trips originating from similar areas with similar land use patterns, and ( c) the parameters of the TCPV model were relatively stable across different time periods.