In the fifth of his six-part blog series on “melting the glacier” of traffic technology adoption, which outlines the five major ways transportation agencies are increasingly embracing so many of the life-saving, mobility-improving strategies that are available today, Iteris’ Mark Nogaki argues that, like in the financial services industry, data analysis is essential to identifying key opportunities for optimization.
I mentioned in my first blog entry the banking executive who said: “Banking isn’t about money anymore, it’s about the data.” To someone who at that point was only just entering the banking world from the high-tech space, the statement was provocative. But as I became more accustomed to banks’ back offices, it became increasingly clear to me that while the results were financially expressed, in dollars, cents and rates of return, the business of banking was knitted together by streams of data transactions.
The bulk of customers were data components in massive customer relationship management, or CRM, systems to which behavioral and risk models were assigned, and/or they were tied in as members of cluster models, around which decisions were made to make them offers for new financial vehicles.
Remember the subprime mortgage lending meltdown that led to the Great Recession? I was in the middle of it, heavily mired in data analytics and dealing with quantitative analysts, or quants, as we called them, on a daily basis. And while the banks were reeling from the upheaval and working to stave off bankruptcies, in the background there were firms trying to profit handsomely from the collapse.
How would they do that?
It all came down to math and data. At that time, if you had a pile of cash, you would take a portfolio of loans – all non-performing – and use models to gage the future value of the portfolio. For all intents and purposes, these portfolios were technically worth nothing. But were they? As it turns out, there were ways of curing some of those loans through various means and – long story short – some less-scrupulous firms were making off with 1,000% profits.
This is all to say that while the manifestation is in dollars and cents, the basis for it all is in the data.
“Traffic isn’t about cars and trucks any more, it’s about the data.”
Okay, so I’ll concede that traffic is mostly about vehicles and the people that operate them, but we’ve moved into a time where it really is about analyzing the data, and everywhere within the traffic ecosystem, there’s a plethora of data that we are learning to corral to make traffic management into something that we can optimize for improved safety and mobility.
Adaptive traffic control has been around for a long time and the use of traffic-responsive and ACS-lite type of traffic control have been used extensively. But now we’re moving way past minor pushing and pulling on years-old signal timing plans. Most modern traffic controllers are able to output high-resolution data, and traffic engineers are increasingly using signal performance measures, or SPM, tools and advanced models to corral the data and build better timing plans. Traffic detectors – through video, radar and other detection modalities are classifying objects, and generating presence, speed and trajectory data that, when used with SPM and crowd-sourced data, provide a rich and robust view of what’s actually taking place in our streets and highways.
In the end, we do all of this to improve safety and mobility for all users of our streets and highways: cars, trucks, pedestrians, bicyclists and so forth. We all need to co-exist in a manner that is efficient and safe.
Traffic is definitely about the data.
ICYMI: You can read earlier articles in Mark Nogaki's Melting the Glacier blog series at the following links:
About the Author:
Mark Nogaki is vice president, sales and customer success, Roadway Sensors at Iteris.
Connect with Mark on LinkedIn.
