Space and time-dependant bus accessibility: a case study in Rome

Abstract

The study of the accessibility in the city has always been appealing for urban planners and public transportation companies. Nowadays, thanks to the availability of tracking devices on public transportation devices, it is possible to evaluate such accessibility very accurately, and derive useful performance measures. In this paper, we propose a complete methodological process to analysize and measure the accessibility of a city using bus GPS traces. Firstly, the process involves the application of recent results in spatio-temporal data mining in order to detect bus lines and bus stops from the traces dataset. Then an agent-based algorithm is used to simulate human mobility in the network, in order to study how the accessibility of the city changes over time, and starting from different locations in the city. Finally, the methodology is applied to bus traces collected for the city of Rome and both the detection process and the accessibility study are deeply investigate.