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Insight: Esri's Terry Bills on the growing use of GIS technology to aid DOTs

Over the past 12 months, Traffic Technology Today has featured several stories concerning the increasing use of geographic information systems (GIS) by transportation agencies to improve their day-to-day operations.

As well as providing general mapping and location information, GIS technology also allows agencies to visualize, question, analyze, and interpret data, to better understand relationships, patterns, and trends.

Three of the projects covered by TTT have involved Esri, one of the leaders in GIS technology, with Departments of Transportation (DOTs) in Michigan (graffiti removal from road signs), Iowa (pavement management), and Massachusetts (pothole repair program), using the company’s services.

To find out more, TTT spoke to Esri’s global transportation industry manager, Terry Bills, to provide some additional insight into the potential uses of GIS.

What other types of highway improvement programs could benefit from the use of GIS applications? Do you have any recent examples?
In the USA, under the new transportation legislation, it stipulates that DOTs have to follow a data-driven process in determining how they will allocate their transportation dollars. This is essentially the planning process, which requires inputs from an agency’s asset management program (what is the condition of my assets and where do I need to do maintenance), their safety program (where do I have dangerous highways sections, and what countermeasures should I install to ameliorate these), and where do I need to build new projects to add capacity or deal with upcoming deficiencies.

Leading agencies have been moving to much more strategic processes to answer and optimize these questions, and it is really through GIS that much of this information can be systematically organized, analyzed, and when combined with other optimization tools, can help agencies ensure they are making the most strategic decisions, given constrained resources.

Iowa DOT in fact is a great example of using our technology very widely. They have created a special group that focuses exclusively on performance management: how are they doing in terms of meeting their agency goals and their performance targets. Their agency goals are focused quite extensively on optimizing their multimodal networks (goods movement), and to drive down transportation costs in the state, such that they can become quite attractive from a location perspective.

If I was going to locate a new manufacturing facility, they can show quite effectively the costs by mode, and in fact they invest in multimodal freights hubs and transfer stations to continually drive down costs associated with goods movement. All of this data is managed and analyzed by Esri software.

How can GIS-based platforms contribute to Smart City projects?
First off, I think any city which wants to be considered ‘smart’ has to solve their mobility issues. Worldwide I think this remains the number-one challenge facing most cities: how to deal with ever-increasing congestion, and solve the rapidly changing mobility patterns of their residents, all in the goal of being more sustainable, and more livable from their residents’ perspective.

Unfortunately, many cities are still thinking of these issues from a very traditional framework – their public transport agencies are still providing the same services and same thinking they have used for the past 40 years, and many have not adapted to the rapid changes in mobility. From my perspective, it requires a much different approach to mobility, and understanding how people would like to travel.

Fortunately, planners now have access to much richer data sources to help them understand changing mobility patterns. We work with several companies that are now mining cellular data to better understand mobility… three that I would point to include:
Citilabs Streetlytics Data, Teralytics and Safegraph. They can all provide a similar type of service, and can tell planners very detailed information about people traveling on every city street: their age, the trip purpose, their income, their mode, etc. These data sources, together with others (progressive transit agencies are installing wi-fi on their buses, because they can also mine the resultant data), give public transport and mobility planners much richer information to rethink how seamless mobility could occur in their cities.

The other main problem is that currently in most cities, you have multiple agencies each responsible for their own segments, and there is seldom an agency that is attempting to coordinate them. For example, I have a road agency which is responsible for the city streets, another agency that is responsible for the public busses, and another that manages the light rail or the metro, and now I have a proliferation of new TNCs and other mobility options. No one is looking at how these various components can work seamlessly together to optimize the choices and performance of these collective mobility options.

I think at heart, it is an institutional issue, but certainly for those cities who would like to solve these problems, we provide not only new data sources, but also a platform that allows multiple agencies to share and collaborate on solving these issues. We see the next-generation ‘geohubs’ as the foundation for such collaborative and coordinated effort, and would point to LA City GeoHub as a prime example. We are now taking this concept to the next level, and we think, provides the platform and foundation for smart city problem solving.

What role do you see GIS playing in the future roll-out of connected and autonomous vehicles (CAVs)?
That’s the 64,000-dollar question as we say in the USA…. There are multiple points where we play a role, and I think we, just like everyone else, are still trying to figure out where we can play the biggest role. We have worked with a number of the high-definition data providers who are collecting the core data that will be required for autonomous navigation, and looking into how that data is managed, and more importantly, how the data is continuously updated. The huge question that I think the vehicle manufacturers are looking at is: how does the first car in, when it detects a change, update the network and the rest of the users right behind, who are expecting something different when they approach a workzone or a change in the network?

We have partnerships with any number of the larger players who are looking at where they can play a role: Cisco, OSI Soft, Mobileye among others, and I think there is still a great deal of uncertainty about the mix of technologies that will be required. From my perspective, the large piece that no one is focusing on that will still be required to make this all work, is the next generation of traffic control systems…. When everyone gets into their autonomous vehicle in the morning, and punches in their coordinates of where they want to go, how is that mass of vehicles going to be optimized through the network, so they don’t all flood onto the same roadways? And what about the non-autonomous vehicles on the roadway? Everyone is approaching this as atomized individual vehicles, each navigating itself to its destination, without looking at the overall consequences. I think the emergent properties and externalities of the overall system are going to be huge. We all are still focused on the happy part of that overall equation, and I suspect we may have problems on the horizon.

As cities consider the introduction of congestion charging and clean air zones, how can GIS assist in their planning, and help communicate the benefits to the general public?
We have developed technology that allows our users to integrate very large live streams of data into systems of location intelligence. Since we know that the next generation of tolling and congestion charging will all be based on GPS technology (Singapore’s ERP II as an example), we are working with a number of the system integrators on some of these emerging projects, in a variety of roles. We think it will ultimately be not just congestion charging, but also parking, insurance, and road user fees that will all be driven by GPS. In fact, cities are increasingly becoming digitized with a wide range of sensors, all designed to help them better manage their infrastructure, with real-time sensor inputs, and increasingly with sophisticated algorithms derived from AI and machine learning that will be running much of our urban infrastructure.

In terms of how we can communicate those advantages to the public, we have given that question a great deal of thought. Let me point you to a recent example that uses our technology very effectively. 

This is from a regional transportation planning agency, the Regional Transportation Alliance of Southwestern Pennsylvania. Normally they produce a written document of their long-range plans, that almost no one reads, and much of what these agencies do is poorly understood by the public. This agency instead used our StoryMap framework to very effectively guide the reader through the principles they used to design the region’s transportation future, and then invited them to explore the maps to understand how they made their respective decisions. It combines multimedia, videos, text and maps to very effectively communicate with their citizens in an intelligent and sophisticated way. I think they did a great job, and have shown a great path for others to build upon and even improve.

How will GIS technologies be used in Mobility as a Service (MaaS) or on-demand transportation programs?
From my perspective, this represents the future of urban mobility. And by that, I mean the concept as applied by MaaS Global in Helsinki. I pay one flat monthly fee for unlimited mobility, on any mode that I choose. So I can take the train in the morning, then an Uber to dinner and drinks, and the bus back home. Because a car on the weekend if I need it is part of the deal, I really do not need to have a car at all. I think this will be the future for many in modern cities.

A key part of making such systems work is having access to the best and latest information on modal travel options. We do work with several companies in that space, including Trafi.com, Kisio and others who are trying to provide the best multimodal data and options. In terms of basic journey planners, there are literally hundreds of these little applications around, and the barriers to entry are nil. We are not really in that business, but do want to help some of the larger data providers better collect and manage the information they are providing. I think the key to success is being able to coordinate the information from all of those various options, and present them in an easy to understand way to the end user, the consumer. I think that is still a work in progress for many of these companies.

 

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