Adapted from Levinson, D. and Krizek, K. (2017) The End of Traffic and the Future of Access. Network Design Lab. Cross-posted on the ITLS Thinking Outside the Box blog.
Each technological advance in mobility over the past 200 years increased the size of metropolitan areas. The ability to go faster, either owing to new technologies or more completely deployed and deeply connected networks, allowed people to reach more things in less time. The Underground drove the expansion of London, streetcars did the same for many American cities,[a] while trams and trains made Sydney, Melbourne, and Brisbane among others, and highways have exploded the size of cities everywhere. Historically, the time saved from mobility gains was reflected mostly in additional distance between home and the workplace, maintaining a stable commuting (home to work) time.
Will autonomous vehicles follow the path well worn by earlier technologies?
Fast, driverless cars that allow their passenger to do things other than steer and brake and find parking impose fewer requirements on the traveler than actively driving the same distance. Decreases in the cost of traveling (i.e., the availability of safe in-vehicle multitasking) makes travel easier. Faster roads arise because of capacity gains from vehicle automation (due both to closer following distances and narrower lanes, even more practical with narrower vehicles fit to serve the single passenger they usually carry). Easier travel means increases in accessibility and subsequently increases in the spread of development and a greater separation between home and work, (pejoratively, `sprawl’), just as commuter trains today enable exurban living or living in a different city.[b] Autonomous automobility reinforces the disconnected, dendritic suburban street grid and makes transit service that much more difficult (as if low density suburbs weren’t hard enough). People will live farther ‘Out.’
However, concomitant with automation is the emergence of the sharing economy, with at least some people transitioning from today, where the typical Australian owns their own car, to mobility-as-a-service (MaaS) — automated taxis. This is more likely in larger, central cities where taxis are common, auto ownership is already difficult, and parking scarce and expensive. In this world, while the total cost of travel drops as vehicle ownership costs disappear, the cost per trip might rise, as the cost of ownership is allocated to each trip. This reduces travel demand.
Driverless cars which can be summoned on-demand allow people to avoid vehicle ownership altogether. This reduces vehicle travel, as people will pay more to rent by the minute than exploit the sunk costs of vehicular ownership. By saving total expenditures on transport, more funds are available to pay for rent in cities, and more trips are by walk, bike, and transit. People who seek the set of urban amenities (entertainment, restaurants, a larger dating pool) will find these amenities increasing in response to the population. The greater value in cities with the new more convenient technology leads to more and taller development. (Hence the use of the word ‘Up.’)
At first blush, ‘Up’ and ‘Out’ appear to be contrasting scenarios; they are not exclusive, however. More people living in the outer suburbs or exurbs does not mean fewer people live in cities, because the overall size increases (with more people overall). Sydney for instance, is expected to grow from just over 5 million to about 8 million people over the next four decades.
Similarly, as the cost of travel decreases, people will be more willing to live in locations far from where they work. At safe speeds of 160 km/h on freeway lanes exclusively dedicated to automated vehicles, the commuting range expands widely. From Sydney in this new world, Newcastle can be reached an hour on road, and Kiama and Katoomba are even nearer.
Sydney planners have recently proposed the benchmark of the “30-minute city“, the idea that most people can find work, school, or daily shopping within 30 minutes of their homes by walk, bike, or transit. The threshold of 30-minutes is roughly equal to today’s one-way commute in Sydney (actually 35 minutes), shorter by car (26 minutes), longer by train (62 minutes) according to BITRE. The long times by train are because trains are designed to serve longer distance trips, and focus on the Central Business District.
The 30-minute city can be achieved through a combination of transport and land use strategies. On the transport side is the question of how fast and how direct the transport network is. On the land use side is the question of where desired activities are located relative to each other.
If the 30-minute city is defined for walk, bike, and transit as the relevant modes, with mobility-as-a-service easily available on-demand, the Up Scenario works best, though getting one-way commuting times for train users down from 60 to 30 minutes is a large ask. In contrast, the Out Scenario can continue to enable a 30-minute city for privately owned autonomous vehicles so long as jobs don’t centralize further in downtowns.
The interplay of AVs and road pricing is especially important. While autonomous vehicles may eventually double or quadruple road capacity, total demand will rise as well due to population growth, so long as people continue to work, shop, and play outside-the-home at today’s rates, even more if traditional patterns of induced demand hold.
It is quite possible that sharing remains a niche while most people choose to own their own cars — the ‘Out’ scenario dominates. Thus, exurbanization and AVs better leverage newly available capacity. But, in the absence of pricing, and with cheap energy, there is little to discourage tomorrow’s privately owned AVs from circulating empty on the road network rather than pay for high prices of parking, and thereby slow travel for everyone else. This possible outcome is so obviously bad, it suggests road pricing or similarly effective regulation in some form is likely.
[a] See Levinson, D. (2008). Density and dispersion: the co-development of land use and rail in London. Journal of Economic Geography, 8(1), 55-77 and Xie, F., & Levinson, D. (2009). How streetcars shaped suburbanization: a Granger causality analysis of land use and transit in the Twin Cities. Journal of Economic Geography, lbp031.
[b] For more on this reasoning, see Chapter 11 in Levinson, D. and Krizek, K (2008) Planning for Place and Plexus: Metropolitan Land Use and Transport. Routledge.
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