Traffic Data: Bluetooth Sensors vs. Crowdsourcing—A Comparative Study to Calculate Travel Time Reliability in Calgary, Alberta, Canada

Abstract

The City of Calgary did a comparative study between two techniques of traffic data collection: Bluetooth sensors and crowdsourcing, for measuring travel time reliability on two goods movement corridors in Calgary, Alberta. To estimate travel time and speed, we used the output of BluFAX sensors, which were operated by monitoring Bluetooth signals at several points along a roadway. On the other hand, TomTom historical traffic data were extracted from the TomTom Traffic Stats portal. To calculate travel time reliability, we applied the buffer index, and the planning time index recommended by FHWA (Federal Highway Administration). The Bluetooth traffic data were presumed as the benchmark in this study. Unlike the TomTom traffic data, the data provided by the Bluetooth technology met the minimum recommended sample size requirement, although data processing was time consuming and impractical for long study periods. Our study results showed that crowdsourcing technique can be a viable alternative and provide travel time reliability estimates with a reasonable accuracy, when there are adequate numbers of records registered. However, the TomTom sample sizes in Calgary were not large enough to provide a statistically reliable method of providing travel time indices. Further researches may verify the accuracy of crowdsourcing technologies for travel time studies.