Feasibility of Analyzing Wi-Fi Activity to Estimate Transit Passenger Population

Maximizing the quality of service experienced by passengers of public transportation systems is of great importance to service operators. Accurate and timely information about passenger load, both at stops and on board vehicles, can help in many ways to improve the quality of service. This information is currently not readily available using data collection techniques that are transparent to passengers. We describe a method and feasibility study for estimating transit passenger population at two bus stops by passively monitoring Wi-Fi network activity of mobile devices. The collected data is filtered and analyzed to distinguish passengers' mobile devices from non-passenger devices. Our experimental results show that filtered Wi-Fi activity correlates well with observed passenger population at bus stops and has the potential to provide near real-time information.