WiFi Sensing System for Monitoring Public Transportation Ridership: A Case Study

Abstract

Public transportation system as an essential mode of travel has been investigated by local governments and transportation agencies to capture passengers’ travel behaviors. Despite their efforts, agencies especially in small to medium sized cities could not afford to collect such behaviors data due to significant costs associated with the data collection system. In this study, we presented a WiFi sensing system which makes such data collection feasible with low-cost devices. We demonstrated the WiFi sensing system’s applicability in estimating passengers’ origin-destination (O/D) travel and passengers’ bus stop waiting times via video validation. In addition, WiFi signal strength was analyzed to further improve accuracy of the system. To this end, sliding window algorithm was adopted to mitigate the randomness of mobile devices’ signals. Our small-scale proof of concept experiment was conducted at four bus stops along the main transit corridor in Charlottesville, Virginia. Results indicated that the system was able to re-identify 91% of bus passengers and passengers bus stop waiting time error was as small as 7 seconds. It is expected that the system can be a viable low-cost Internet of Things (IoT) solution for monitoring public transit system performance.

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