Driverless cars don't change geometry

Via the Streetsblog Network, I came across this Salon piece from Michael Lind praising our future driverless car overlords.  Angie Schmidt at Streetsblog did a nice job to take down some of Lind’s loaded language, particularly the bits about “rigging markets” (which rings just as hollow as the cries about “social engineering” – as Timothy Lee notes, there’s no such thing as an intervention-free infrastructure policy).

Those issues aside, the biggest thing that Lind misses isn’t about technology at all – but rather about geometry, land use, and the relationship between transportation and the built environment. Lind writes:

As the white windmills fade from the picture of the future, so do the bullet trains speeding past them.  Even before the end of President Obama’s first four years, unrealistic fantasies about high-speed passenger rail had collapsed.  Federal funding for high-speed rail demonstration projects has been minuscule and symbolic.  State and local governments continue to conclude that the costs of high-speed passenger rail outweigh the alleged benefits.

In the longer run, robocars may be fatal for fixed-rail transportation, at least for passengers rather than freight.  Google has been test driving self-driving cars in California and Nevada has become the first state to legalize driverless vehicles.  No doubt it will take several decades for safety issues and legal arrangements to be worked out.  But high-speed trains might find competition in high-speed convoys of robot cars on smart highways, allowed higher speeds once human error has been eliminated.  And the price advantage of subway tickets over taxi fares in cities may vanish, when the taxis drive themselves.  Point-to-point travel, within cities or between them, is inherently more convenient than train or subway journeys which require changing modes of transit in the course of a journey.  Thanks to robocars, much cheaper point-to-point travel everywhere may eventually be cheap enough to relegate light rail and inter-city rail to the museum, along with the horse-drawn omnibus and the trans-atlantic blimp.

Paraphrasing Jarrett Walker (aside: his recently published book is an excellent read), technology does not change geometry.  A driverless car is still a car, the geometry that governs the car is the same regardless of who (or what) is at the controls.  Despite predictions about how this technology could change everything (see a whole series of GGW posts), I find the possibility for change to be marginal.  Driverless Johnny Cabs, Total Recall-style might decrease the cost of providing taxi service, but that won’t fundamentally change the inherent capacity limitations of taxis compared against a subway system.

The choice of the taxi as a demonstration for the technology is interesting. Most taxis operate in big cities, and big cities tend to be dense.  Density helps support high levels of transit service and ensures that lots of potential trip destinations are easily reached by foot or by transit, thereby diminishing the market for these automated taxis.  Cars, regardless of who’s driving, don’t have an advantage in point to point travel over pedestrians, transit, or other modes in cities.

The other point Lind makes is in investment priorities for government-funded infrastructure (hence the earlier comment about “rigging markets”).  Lind seems to view the built environment as static, rather than an evolving system that changes in concordance with the changes to the transportation infrastructure.  New York’s subways fueled its dense development, and that density in turn provides the market for high capacity rapid transit.  Given growing populations and constantly changing cityscapes, these infrastructure investments in transit are step along the process of letting out cities continue to grow.

(semi-related sidebar on growth patterns: check out this article in Scientific American on the patterns of growth among subway networks around the world.  The authors concluded ” that the geometries of large subway networks are guided by simple, universal rules.” – reminiscent of Geoffrey West et al)

5 comments to Driverless cars don’t change geometry

  • People inexplicably think that there’s some huge capacity gain to be had from driverless cars. For example, Tory Gattis when pressed spun a story on how driverless cars would reduce the need to change lanes. Of course on freeways where you’re driving for more than a couple exits this is all 100% irrelevant, and cars are already at the maximum capacity allowed by stopping distance considerations. It’s not like with trains, which have a huge amount of buffer room for station stops, fixed blocks, and such.

  • [...] car to be used productively by someone else.  A driverless taxi, otherwise (hence my choice for my previous post’s image of Total Recall’s Johnny Cab - I don’t know if the new version of the film this [...]

  • Agreed that there is still a limiting physical capacity, but there *is* a gain to be had in improvements to operational capacity: reduced headways, reduced startup loss time, reduced collisions, capabilities for system-wide over individual optimisation of routing, timing, etc. It’s certainly not the panacea some motorway idealists envision, but there are some significant gains to be had.

    (saying nothing of peds or bikes, of course)

  • Winston

    There is capacity gain possible from driverless cars, but only on freeways or dedicated roads. In those conditions, you can approximately double the number of cars that you can move past a point by reducing following distances. This, however isn’t true once you get into a low speed environment like a city with mixed traffic and tighter spacing between cars. In many ways, this makes the problems of integrating freeways into the city worse in that you can get more cars to already congested mixed-use streets.

  • Alex Block

    Bossi,

    Indeed, I think there would be some changes – I took a stab at that in a later post here: http://www.alexblock.net/blog/?p=2292

    Winston,

    Great point on the differences of mixed-traffic versus segregated traffic environments and boosting capacity. Same logic applies to automation in rail transit, too.

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