WiFi Sensing-Based Real-Time Bus Tracking and Arrival Time Prediction in Urban Environments

Abstract

Offering the services of real-time tracking and arrival time prediction is a common welfare for bus riders and transit agencies, especially in urban environments. On the down side, the traditional GPS-based solutions work poorly in urban areas due to urban canyons, while the location systems based on cellular signal also suffer from inherent limitations. In this paper, we present a powerful tool named signal Voronoi diagram (SVD) to partition the radio-frequency signal space of WiFi access points (APs), distributed, where a bus travels, into signal cells, and then into fine-grained signal tiles, tackling the problem of noisy received signal strength readings and possible AP dynamics. On top of SVD, we present a novel framework so-called WiLocator, to track an urban bus based on the surrounding WiFi information collected by the commodity off-the-shelf smartphones of bus riders and the mobility constraint of a bus. To predict the bus arrival time, we incorporate the computed location information and the temporal consistency of travel time of buses on the overlapped road segments. We then present WiLocator(p) which utilizes the historical data of bus locations to compute dominated road sub-segments of WiFi APs, such that we do not necessarily locate a bus from scratch, and show that the proposed framework can be applied for locating unknown WiFi APs surrounding the bus roads, and indoor localization as well. We implement the prototype of WiLocator and WiLocator(p), and conduct the in-situ experiments to show their efficiency in bus tracking.