Re-Programming Mobility: Four Scenarios of How Digital Technology Could Reshape Transportation and Planning in the U.S.

Re-Programming Mobility: Four Scenarios of How Digital Technology Could Reshape Transportation and Planning in the U.S.

February 19, 2015  | Carter Templeton

BY ANTHONY TOWNSEND
New York University

In late 2012, I spent a week in Israel on business. Over lunch one day, one of my clients – an experienced engineer in the tech industry – recounted a shocking story. The previous summer, he told me (I later surmised it was on or about August 7 or 8, 2011), there had been a thunderstorm in Northern Virginia. Wind blew a tree down, a tree fell on a wire, and one of Amazon’s massive data centers went offline. The incident occurred around the morning rush hour in Israel. Now, at the time, something like 20 percent of Israeli drivers were daily users of Waze, a crowd-sourced traffic reporting and way-finding service. But the fast-growing company, founded just two years earlier, relied on Amazon Web Services’ (AWS) shared cloud-computing infrastructure to run its software. When Amazon went down, so did Waze, and Israel’s drivers were blacked-out. Without the app’s turn-by-turn directions and jam-avoiding route planners, gridlock quickly set in across the tiny nation.

While AWS certainly did fail that day, and Waze reported service disruptions on its blog, no one will go on the record, and there are no English or Hebrew language media reports. So, I’ve never been able to verify the scope of what actually happened, if my colleague’s story of mass national gridlock really took place.

But the veracity of this anecdote is beside the point. Because it is totally plausible. And that plausibility speaks volumes about how Israel’s entire surface transportation system had literally been re-programmed by a startup, that had introduced a single critical point of failure thousands of miles away in another country, with apparently zero awareness on the part of the Israeli government’s transportation planners or defense strategists. (And no doubt, if the traffic was as bad as reported, this was certainly a national defense concern.)

Technological Disruption Across the Value Chain

But Waze is just one of thousands of new digital technologies and services have come to market in recent years that are turning transportation from a bricks-and-mortar business into an information-based and informatics-based activity. Disruption is happening throughout the value chain. Examples include:

  • Infrastructure networks: adaptive traffic signaling, dynamic electronic road pricing
  • Vehicles: autonomous motor vehicles, autonomous aircraft, programmable vehicle performance characteristics
  • Business Models: car sharing, peer-to-peer taxi services
  • Interfaces: Electronic taxi hailing, crowdsourced traffic reporting, integrated multi-modal services (route planning, booking, and payment)

After decades of anticipation, digital technologies are beginning to have a major impact on the way Americans travel – from deciding when and where to take trips, to selecting modes and planning routes, and coordinating with others while on the go. Behind the scenes, these technologies are also being used to rewire infrastructure and services that enable transportation networks to function.

Investments in these technologies dwarf spending on conventional transportation solutions – for instance, as much private capital has been poured into cellular networks as public capital was spent on the entire Interstate Highway System, about $500 billion in current dollars. But transportation planning is only beginning to grapple with the far-reaching impacts of these rapid shifts. How will services like e-hailing, autonomous vehicles, and electronic road pricing impact the way people travel, land use patterns, and the management and planning of transportation itself?

Using Scenarios to Forecast Technological and Social Change

With generous support from the Rockefeller Foundation, the Rudin Center for Transportation Policy and Management has developed a set of four alternative future scenarios set in a selection of representative U.S. metropolitan areas in 2030. Based on our synthesis of current and anticipated technological innovations and expert speculation on their impacts from over 150 source documents, these scenarios highlight:

  • likely and possible shifts in the market for mobility, public financing schemes, and the overall structure and function of the U.S. transportation system at a metropolitan level,
  • the kinds of organizational changes that transportation regulators, funding agencies, and public planning institutions need to begin preparing for now, and
  • the kinds of skills and practices that might be required of transportation planners in the future.

Failure to address these issues head-on risks confronting a crisis in transportation planning. And in fact, we could make the case that the business opportunity now being exploited by startups and tech giants alike is the result of 50 years of transportation planning failures.  As these new digital band-aids bridge gaps in our existing physical transportation networks, planners need to become more agile in anticipating and adapting to rapid technology-enabled shifts in mobility. Transportation planning is just as important as it has always been, if not more so – but the kinds of plans and areas of inquiry we make must adapt to this new reality.

We present these scenarios as a provocation to transportation policymakers, managers, and planners with the goal of stimulating a national debate about the potential impacts of these new technologies and services, and how government can accommodate their vast potential to improve transportation and anticipate and mitigate their unintended consequences.

The four scenarios represent archetypes that allow us to think about a broad set of possible future paths:

Growth: A future in which current key conditions persist, including continued historical exponential growth in certain domains (economics, science and technology, cultural complexity, etc.) Also known as PTE, or “present trends extended”.

In our scenario, set in Atlanta in 2028, we find tech giant Google assuming a major role in the surface transportation system of Atlanta, through a public-private partnership with the Georgia Department of Transportation. The company is exploiting synergies from its two decades of investment in residential energy management and solar power, autonomous vehicles, e-taxi services and fiber internet service to build new communities at the exurban fringe. While the region’s residential areas continue to sprawl, some of the same technologies are also used to consolidate commercial activity around edge cities, which are able to grow and densify by pushing parking to automated satellite facilities.

Collapse: A future in which some conditions deteriorate from their present favorable levels, and some critical systems fail, due to a confluence of probable, possible, and wildcard factors.

In our scenario, set in Los Angeles in 2030, the rapid and uncoordinated deployment of semi- and fully-autonomous vehicles by dozens of manufacturers has put millions of new vehicles on the road without effective schemes for vehicles to coordinate traffic flows. Aggravating the situation is the increase in vehicle miles travelled due to a growing number of zero-occupant uses, as people send cars to pick up deliveries, or simply drive in holding patterns to avoid parking fees. With its transit system left to wither during the initial excitement over vehicle automation, the region has a long journey to rebuild its mobility system, but promising innovations in informal transit are starting to leverage some of the same technology to create ultra-low cost, flexible transportation options drawing on business models from the developing world.

Constraint: A future in which we encounter resource-based limits to growth. A sustainability regime emerges, slowing previous growth and organizing around values that are ancient, traditional, natural, ideologically-correct, or God-given.

What if the costs of maintaining a region’s road network in the face of severe weather caused by climate change finally pushed local government finances to the brink?

This scenario, set in northern New Jersey in 2029, envisions a world in which that nation’s first fully suburbanized region starts grappling with the unsustainability of its transportation system, and develops strong planning powers to implement a resilient network of local and regional express bus rapid transit, in record time and at a fraction of the cost of heavy rail.

Transformation: A future of disruptive emergence, “high tech,” with the end of some current patterns/values, and the development of new ones, rather than the return to older traditional ones. This is a transition to an innovation-based regime of new and even steeper GROWTH.

Our final scenario, set in Boston in the 2030s, looks at the role of automation in light electric vehicles and urban freight and express delivery. With residential use of the urban core shifting rapidly as young people are drawn to smaller, less expensive, and heavily tele-serviced micro-apartments, the city is becoming more walkable and vibrant, but the volume of e-commerce deliveries creates conflicts with pedestrians, e-bikes and other novel forms of sustainable personal mobility. The inevitable shift? The city shifts the bulk of freight movements to overnight, through the use of autonomous delivery vehicles and robots.

These are mere highlights of the rich, multi-faceted worlds described in these scenarios of how we are re-programming mobility in the United States. We present these scenarios as a provocation to transportation policymakers, managers, and planners with the goal of stimulating a national debate about the potential impacts of these new technologies and services, and how government can accommodate their vast potential to improve transportation and anticipate and mitigate their unintended consequences.

* Dr. Anthony Townsend is Senior Research Scientist at New York University’s Rudin Center for Transportation Policy and Management. This research was supported by a grant from the Rockefeller Foundation.

The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of The Eno Center for Transportation.

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