Towards proximity-based passenger sensing on public transport buses

While substantial research on intelligent transportation systems has focused on the development of novel wireless communication technologies and protocols, relatively little work has sought to fully exploit proximity-based wireless technologies that passengers actually carry with them today. This paper presents the real-world deployment of a system that exploits public transit bus passengers’ Bluetooth-capable devices to capture and reconstruct micro- and macro-passenger behavior. We present supporting evidence that approximately 12% of passengers already carry Bluetooth-enabled devices and that the data collected on these passengers captures with almost 80 % accuracy the daily fluctuation of actual passengers flows. The paper makes three contributions in terms of understanding passenger behavior: We verify that the length of passenger trips is exponentially bounded, the frequency of passenger trips follows a power law distribution, and the microstructure of the network of passenger movements is polycentric.