The Future of Traffic Data

Michael Ostrom, CEO of Mygistics, Inc., reveals how advancements in traffic modeling will improve personal and commercial travel.

As if life isn’t stressful enough, the simple task of efficiently getting to work, home and recreation has become equally problematic. Greater traffic volumes, deteriorating infrastructure, overburdened mass transit and volatile energy costs conspire against us.

Longer rush hours, more time spent in traffic and more disposable income spent on fuel affect our quality of life. Building our way out of these problems is not the answer. According to TRIP, a Washington, DC non-profit research group that evaluates and distributes economic and technical data on highway transportation issues, “the current level of national transportation investment needs to double in order to significantly improve the country’s highway, transit, passenger rail and freight systems.”

Given the current economic climate, relief may not come soon to all the places that need it. Transportation officials understand their users need better ways to deal with the system as it currently exists.

Guessing the present
Today’s traffic information providers rely almost exclusively on real-time data and historic information. Little or no information is given on arterial and secondary roadways. No adjustments are easily made for wild-card factors – crashes, construction zones, special events, adverse weather – that account for over half of congestion problems.

The best data can be of little use to the average motorist embarking on a local trip. The usual twenty-minute drive may take thirty, or turn into a one-hour nightmare. Freight shippers feel the pinch more keenly. A study by HLB Decision-Economics indicates that, on average, freight carriers lose about $200 per hour in traffic; this loss almost doubles if the delay is unexpected.
The answer lies in predictive traffic information, a system that considers future traffic conditions along the route, allowing for much more precise calculations of arrival times and providing much better tools for managing travel.

A crystal ball on your dashboard?
Early efforts at creating predictive models were based on a statistical approach using Bayesian analytic techniques. Though these models gave some good short-term information, their predictive limitations could not process those unexpected delays or react to changes in traffic management strategies. Most crucially, they could not propagate these effects throughout a travel network. Bayesian models really only provide extrapolations of historical conduct, and do not model or understand human behavior – more Farmer’s Almanac than a National Weather Service forecast model.

Mygistics’ methodology is based on travel demand models that explain volumes and travel times by simulating all travelers on a network. Demand is generated using socioeconomic data such as household size, automobile availability and employment data, the root of why people travel from A to B. This knowledge applied to a network model can simulate how traffic conditions propagate throughout all roadways in a network, not just freeways, and how vehicles react to impedances such as accidents or road closures. The Mygistics model requires only the application of limited, live traffic sensor data, which serves to constantly calibrate system calculations.

Because this approach has its origin in both traffic engineering and transportation planning, it’s also useful for improving utilization of existing and planned infrastructure, predicting vehicle emissions, assessing environmental impacts and investigating topics in transportation safety and market research. Our partner, PTV AG, has applied this methodology in several European metropolitan areas and on a national scale in both Germany and the UK with great success. Mygistics is working to deliver data across the US with the Chicago metro as our first covered region.

With advances in the science of traffic engineering and increases in computing power, we can truly begin to get a handle on network complexity and solve transportation issues on a system wide level.

As Robert Frost wrote, “Two roads diverged in a wood, and I – I took the one less traveled by, and that has made all the difference.” Technology is moving in a direction that could afford this luxury to all of us.

Michael Ostrom was an early pioneer in the use of 3D visualization for transportation engineering and served as a technology director at two top AEC firms. As CEO of Mygistics he is working to leverage Web 2.0 technologies with Traffic Engineering and ITS to improve mobility on a national scale.