Big Data and ITS

By Daniel Benhammou, President & CEO of Acyclica

Intelligent Transportation Systems (ITS) is the present and future of transportation management in the U.S. and around the world. With spending expected to exceed $72 billion annually by 2022, the ITS market is well-established and on the verge of a significant expansion.

Data is the lifeblood of ITS. The more accurate, timely, and complete the data, the more precisely ITS-based management technologies function. While ITS itself is not new, we are at the dawn of an exciting era where the full capability of ITS devices is being explored. The emergence of cloud computing and the shift in thinking about the Internet of Things has led to a data revolution in ITS where legacy devices are being transformed from a single function device to a real-time data stream yielding new possibilities which were never imagined when the products were conceived.

As public agencies grapple with the petabytes of data, smart city initiatives have been taking shape, in large part fueled by the explosion of data from ITS. Why does ITS have such a disproportionate impact on the ideas of Smart Cities? The answer is quite simple: cities are the fabric of our modern civilization, woven by the threads of commerce and human interaction. ITS is about moving people and things more efficiently and safely.

An encouraging trend of collaboration has emerged when considering the massive amounts of data which are now flooding traffic operation centers. The collaborative nature has already started paying dividends with regards to quantifying the performance of traffic networks. The next step has even more promise with the ability to reduce congestion, improve safety, and, ultimately, save lives.

One specific application demonstrating the above case can be found in the data fusion of combining stop bar detection information together with signal phasing data. In a recent study, data was examined at a series of intersections to determine, to the millisecond, when vehicles were arriving and departing the stop bar. Combining this data with the signal phasing information, it was possible to determine if queues were being adequately cleared or if platoons (or individual) vehicles were traversing the intersection as the signal changed from green to yellow and, in some cases, yellow to red. A disturbing realization was captured by recognizing the high degree of vehicles which were running red lights as evidenced by the data. Prior to the deployment of advanced data collection technology, quantifying the number of red light running events at an intersection was not possible without a manual survey or a red light running camera which may not be legal in all jurisdictions. Collecting this information highlighted a clear issue impacting traffic and public safety.

In order to determine possible means of mitigating the risk to public safety, high-resolution travel-time data was compiled on an intersection-to-intersection level. The travel-time distribution provided ample evidence of offsets which did not account for the actual flow of traffic but had been calculated solely based on traffic models. Adjusting the offsets based on real-world conditions, provided a simple means of optimizing the traffic flow so that a majority of vehicles could maintain progression. Furthermore, the city was able to determine exactly when and the duration of various traffic patterns due to the continuous data collection thereby reducing congestion and improving public safety.

As ITS technology becomes more ubiquitous, the applications are limitless. The technology which is currently being developed and implemented by technology leaders is laying a foundation for the connected and autonomous world of the future. While a fully-autonomous society holds promise for a future vision-zero Smart City, the ITS investments that are being made today pay immediate dividends.

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