Low-Cost Data Collection with Big Results

April 19, 2009

Devices so common to modern life – cell phones, MP3 players, and other electronics –have a unique identifier known as a media access control (MAC) address. Think of it as a digital fingerprint. The address is broadcast from a device, allowing it to interact with other digital devices.

Now imagine measuring the speed and start and end points of a sample of vehicles on a road, in real time, using this automated, low-cost yet accurate technology. KAI is doing just that, capturing the time and location of these devices to determine traffic performance in real-time or near real-time.

With multiple sensor locations, travel times, speeds and origin-destinations between fixed points can be gauged, which is particularly useful to measure fluctuations in traffic patterns and more accurately measure the impacts of transportation system changes, such as new signal timing, new roadway lanes or even traffic accidents. Considering personal privacy, KAI has developed a data filter to protect the privacy of individual MAC addresses, to not infringe upon personal information of users, while retaining enough precision to evaluate them along a roadway.

Surveys completed using labor-intensive license plate studies can now be performed in an automated, low-cost fashion and produce far more data samples than manual origin-destination studies. This technology has a myriad of applications - from businesses that want to learn where customers come from to communities seeking to retime traffic signals.

KAI, in partnership with the City of Portland and the Oregon Department of Transportation (ODOT), has a demonstration project for Powell Boulevard, a local arterial in Portland, to further test and develop recommended data collection procedures, as well as data aggregation and destruction policies. The project also represents the first known permanent application of the technology along a signalized arterial to produce a wealth of historic data for engineers and planners. One day, this technology may contribute to traffic forecasts, in a similar fashion to weather forecasts, informing drivers how long a trip may take and which route is preferable given the time of year, weather conditions, events or other variables. This technology can equip transportation professionals with better information, resulting in more informed decisions and investments. Ultimately, that will create a better traveling experience for the public.

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