Econ_June_09

66 Finance and economics

The Economist

June 9th 2018

HE race to bring driverless cars to market is fierce and crowd-

ed. All the leading carmakers are in the field: onMay 31st Soft-

Bank’s Vision Fund said that it would invest $2.25bn in the auton-

omous vehicle (

) arm of General Motors. So are tech upstarts,

fromUber to Tesla toWaymo, Alphabet’s self-drive division and

the leader in driverless technology, which recently announced

plans to add 62,000minivans to the fleet ofcars thatwillmake up

its autonomous ride-hailing service. Intense competition has

both benefits and costs, but will probably prove short-lived.

Thanks to powerful economies of scale, the roads may soon be

ruled by nomore than a handful of firms.

The advantages of scale begin with data. Like humans, the

computers which power driverless cars improve with experi-

ence. The computers sitting in

s are essentially in the business

of learning and improving on what a good human driver would

do, write Ajay Agrawal, Joshua Gans and Avi Goldfarb in their

new book, “Prediction Machines”. The more data they have, the

better they become at predictingwhether that blur ahead is a pe-

destrian or sunlight reflecting off the road, and reacting accord-

ingly. And themoremiles under an

project’s belt, themore un-

usual events—amoose in the road, say—the system faces.

Fortunately such lessons, once learned by computers, are not

forgotten, and can be drawn upon by every vehicle using the

same software. This, and the fact that

s never fall asleep at the

wheel or pull their eyes from the road to check their phone, sug-

gests that driverless cars should ultimately be far safer than the

human-driven sort, which contribute to the roughly 1.25m road

deaths each year worldwide, a bigger body-count than malaria.

But some

systems will be safer than others. Those that beat

competitors on safety and general reliability will attract more

drivers and corporate partners, allowing them to gather more

data still.

Regulators might further thin the field, by forcing firms with

poor safety records to curtail testing or by setting standards that

only the best can meet. Indeed, performance gaps could create

ethical quandaries for governments: should the safest firms be

forced to share their technology; should they be given exclusive

rights to the roads; should policymakers tolerate preventable

deaths in cars using inferior software? Such questions might not

remain academic for long. Between December 2016 and Novem-

ber 2017 Waymo reported three collisions in 350,000 miles

(560,000km) of driving in California;

, the nearest American

competitor, had 22 in132,000. Neither has been involved in a fatal

accident, as Tesla andUber have.

Scale will yield still other benefits. Though some people will

want their own driverless cars, the market is likely to favour

based ride-hailing services. Driverless cars will not come cheap.

But cars used in ride-sharing services will cost less per mile than

personal vehicles, which spend much of their time sitting idle.

Maintenance and other costs should be lower for fleets of hail-

able

s, because centralised facilities ought to enjoy productivi-

tyadvantages overdistributedmechanics’ shops, andbecause in-

dividual owners are at an informational disadvantage to their

mechanics, which creates opportunities for overcharging.

Individual owners might nonetheless shell out for the conve-

nience of a car at their personal beck and call. Yet car-hailing ser-

vices, like bike-sharing businesses, become more useful as their

user-base grows. The more riders there are in an area, the more

vehicles it pays to operate, and the more likely a user is to find an

open ride nearby. Ifwaiting times fall to almost nothing—as clev-

s learn to roll up at the time you usually leave home or

work—the extra value of having your own carwill fade.

Convenient, safe

s, which allow riders to nap rather than

mind the wheel, should reduce the hassle of travelling by car.

That creates a potential snag: people may travel more, making

congestionworse. Ironically, though, scale could fix this too. Con-

gestion occurs because individual drivers do not take into ac-

count the inconvenience they cause to others. One way to solve

this is to force drivers to bear those costs, by charging them a fee.

But governments’ plans to introduce congestion tolling are un-

popular—and charging is consequently rarer than chronically

jammed highways.

But a ride-hailing servicewhich grewto account for a substan-

tial share of traffic would face a different set of incentives. Con-

gestion costs imposed by one of its cars on another would be in-

ternal to that firm, which would have both the reason and the

ability to do something about it—by varying priceswith demand,

perhaps, or by offering reduced rates to customers willing to

share a car. Other cars or services couldattempt to free-ride on the

free-flowing traffic created by dominant firms. But concentrated

control over roadways could make the politics of road fees more

tractable: as the winning firms’ bargaining power rose, as fewer

middle-income households owned their own cars, and especial-

ly if, asDaniel RauchandDavid Schleicher ofYaleUniversity sug-

gest,

firms join with governments to provide public transport

andmobility services.

Waymo regulation

Assuming, that is, that governments do not take a much larger

role in the market. Historically, scale economies in transport,

from railways to public transit, pushed systems towards monop-

oly and eventual government interference. Economies of scale

will likewise thin the ranks of driverless contenders and create

pressure for government involvement. Driverless cars might not

be much faster than those controlled by humans. But the market

could go from cut-throat competition to oligopoly to state control

with extraordinary speed.

Road hogs

Economies of scalewill push themarket fordriverless vehicles towardsmonopoly

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