BLUETOOTH SENSORS DATA VERSUS GPS-BASED DATA, MEASURING TRAVEL TIME RELIABILITY ON FREIGHT TRANSPORTATION CORRIDORS IN THE CITY OF CALGARY, ALBERTA, A COMPARATIVE STUDY



BLUETOOTH SENSORS DATA VERSUS GPS-BASED DATA, MEASURING TRAVEL TIME RELIABILITY ON FREIGHT TRANSPORTATION CORRIDORS IN THE CITY OF CALGARY, ALBERTA, A COMPARATIVE STUDY

Authors

Dr. Shahram Tahmasseby, P.Eng., The City of Calgary

Description

In this work we did a comparative study between two methodologies:traditional data collection via BluFax traffic data collecting devices vs. floating car data, for estimating travel time reliability along major goods movement corridors in Calgary.

Abstract

Presently most transportation departments use inductive loops, traffic cameras or stationary sensors to measure travel time and speeds, and thus to estimate travel time reliability. Although, these traditional systems are proven techniques of collecting traffic data, they each also have a couple of shortcomings incl. systems installation costs, applicable data processing fee, annual maintenance cost, data accuracy, calibration, and validation. Alternatively, Floating Car Data, known as FCD, has introduced an effortless method for traffic data collection and consequently traffic performance measurement since the past decade. In this work we did a comparative study between two techniques: Bluetooth sensors data vs. GPS-based data, for estimating travel time reliability along two major goods movement corridors in the city of Calgary, Alberta. As a trucking hub, Calgary plays a major role in providing a safe, efficient, and connected goods movement network in the province, and nationwide. On one hand, we used the output of BluFax units, which operate by monitoring Bluetooth signals at several points along a roadway, to calculate travel time reliability. On the other hand, TomTom historical traffic data was extracted by running a series of customised queries using TomTom self-service web portal, called Traffic Stats which eventually generates a report containing custom area analysis, travel times, and speeds. Accordingly, we estimated travel time reliability based on the generated TomTom report and compared it to the results obtained from the BluFax traffic data. The important goods movement corridors were identified according to the percentage of traffic consisting of trucks on the primary goods movement corridors. To calculate travel time reliability, we applied the travel time buffer index approach developed by FHWA. The methodology is somehow preferable since the calculated metrics are readily understandable by laypeople, including politician and the general public.
Our study results also demonstrated that the data provided by the Bluetooth technology meets the minimum sample size requirement and seems to be closest to the observed benchmarks. We concluded that applying the aforementioned technique could generate reliable travel time and speed data given the number of observations, and direct measurement of performance indicators from disaggregate data sources.
The study also showed the inadequacy in terms of the number of TomTom Historical Traffic Data records on Canadian freeways and arterial roads; nonetheless, this inadequate traffic data still demonstrated somehow a reasonable accuracy for the travel time reliability study on a heavily used arterial road. This can’t be interpreted as a general conclusion. Hence, a few more studies would need to be conducted to comprehensively verify the accuracy and the adequacy of TomTom historical traffic data for travel time and speed studies on Canadian roads.

Publisher

Association for European Transport