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Autonomous Vehicles and the Urban Economic Environment

Current discourse on autonomous vehicles (AVs) generally assume that their development

towards mainstream adoption is inevitable (Standage, 2018). AV technology is still relatively

nascent (Cameron, 2018), therefore we must look towards how other paradigm-shifting

technologies have been adopted in order to understand how autonomous vehicles - with

respect to classical urban economic theory - will change the face of the modern urban

environment.

AVs are a technological factor exogenous to the Real Estate System (Geltner et al, 2007).

They are touted to reduce congestion (The new autopia, 2018), transport costs (Henderson

& Spencer, 2016), air pollution (A different world, 2018) while increasing urban sprawl (The

new autopia, 2018), city densities (The new autopia, 2018) and productive consumer time (A

different world, 2018).

The potential for increased urban sprawl as a result of reduced transport costs and

congestion; city densities as a function of spaces allocated for cars being redeveloped for

urban use (The new autopia, 2018); and consumer income as a function of more free time

afforded by AVs may result in the Development Industry ramping up activities to meet these

new Space Market needs. Should this occur, the Asset Market will receive an influx of

greater cash flows; thus increasing property values by virtue of improved perceptions about

real estate assets as an investment. Capital markets will thus pour more capital into the

Asset Market should the market-required cap rate be acceptable for investors until

equilibrium is reached in the Real Estate System.

Of course, the level of urban sprawl will ultimately be determined by governments and city

councils who control and regulate the medium and long-term supply of land (Balchin &

Kieve, 1988) coupled with the ability of a city to attract migration. The regulatory bodies will

identify the most socially beneficial trade-off between increasing city sprawl and density;

adjusting city limits and land use restrictions accordingly. Should AVs be adopted widely, the

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bid-rent curve will flatten and lengthen as accessibility is intrinsically tied to productivity,

and thus rents (Balchin & Kieve, 1988). On the other hand, the increased opportunities and

profitability offered by an AV-friendly city will attract more firms and workers, who will in

turn maintain the relative demand for space. This will keep the bid-rents for central

locations at pre-AV-levels, potentially increasing them as the population of the city rises.

An interesting by-product of AV adoption will be the reduction of harmful emissions

produced by road-users. This will largely be due to the lower operating costs associated with

electric cars (A different world, 2018). What this will do of course is negate the air-pollution

factor in Hoyt’s Radial Sector Theory as well as Harris and Ullman’s Multiple Nuclei Theory

(Harvey & Jowsey, 2003); potentially blending the low, middle and high income housing

areas more seamlessly.

The benefits of lower operating costs as a function of distance and reduced number

employees resultant from transport automation (Henderson & Spencer, 2016) will mean

that firms have greater flexibility in where they can locate as they are subject to lower

production and transport costs. However, agglomeration economies may mitigate this

factor as the workforce will be similarly flexible in the advent of AV technology. A more

likely scenario will be the addition of another hexagonal layer in Christaller’s Central Place

Theory mesh; denoting a new accessible trade area for businesses because of AVs impact on

the range in which consumers will be willing to travel to purchase goods (Balchin & Kieve,

1988).

There are multiple criticisms, rebuttals and limitations of the claims above which include

how far away we are from accessing true AV technology (Cameron, 2018); the rate of AV

adoption (Clewlow & Mishra, 2017); and whether or not AVs are a viable product to begin

with (Wolmar, 2018).

Current AV technology is still some time away from achieving fully autonomous status as

classified by SAE International, with the latest offerings only having the ability to go

driverless in limited environments like freeways (Cameron, 2018). If the technology and

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infrastructure fails to achieve a significant level of unsupervised travel, the impact of the

scenarios above will not be as pronounced.

Similarly, there is no guarantee that AVs will be adopted en masse. Some households may

prefer to complement traditional vehicle ownership with a ride-sharing service. Ride-hailing

utilization rates are not as game-changing as some make the service out to be and gives an

ominous outlook for AV adoption (Clewlow & Mishra, 2017). On the other hand, AVs could

become the next smartphone-type item that the majority of individuals in the developed

world sought after upon release (Henderson & Spencer, 2016).

Perhaps the biggest elephant in the room is whether or not AVs are viable products to begin

with. Massive multinationals such as Google and Microsoft are investing heavily in AV

research and development in the face of Uber’s three-billion-dollar loss in 2016 (Wolmar,

2018). As with any innovative venture, no business model blueprint exists for a successful

AV company, potentially rendering forecasts of the future commercial and real estate

landscape as moot. Regulatory hurdles in the form of inconsistent AV legislation will have to

be met by AV manufacturers, thereby slowing the R&D process even further (Henderson

and Spencer, 2016).

Autonomous vehicles are a very exciting area of interest for the future of mobility. We

envision AV technology will bring a game-changing leap in productivity, quality of life and

subsequent developments in the urban economic environment. However, much like the real

estate industry, the risks and uncertainties involved in realising these benefits will take time,

prudent regulatory action and a true understanding of the wants, needs and perceptions of

the market.

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References:

A different world. (2018, 3rd March). The Economist.

Balchin, Paul N. and Kieve, J.L. (1988) Urban Land Economics and Public Policy. 4th edition,

pp.38-67. Macmillan Education.

Cameron, M. (2018) Chapters 2 & 3 of Realising the Potential of Driverless Vehicles.

Wellington, NZ: The Law Foundation.

Clewlow, R.R and Mishra, G.S. (2017) Disruptive Transportation: The Adoption, Utilization,

and Impacts of Ride-Hailing in the United States. Research Report UCD-ITS-RR-17-07. Davis,

CA: University of California.

Geltner, D.; Geltner, David M. (2007) Commercial Real Estate Analysis and Investments. pp.

21-35. Thompson South-Western.

Harvey, J. and Jowsey, E. (2003) Urban Land Economics. 6th edition. pp. 235-238, 247-265.

Palgrave Macmillan.

Henderson, J. and Spencer, J. (2016) Autonomous Vehicles and Commercial Real Estate.

Cornell Real Estate Review 14(1), pp. 44-55.

Selling rides, not cars. (2018, 3rd March). The Economist.

Standage, T. (2018, 3rd March) Reinventing wheels. The Economist special report on

autonomous vehicles from 3 March 2018 and 4 August 2018.

The new autopia. (2018, 3

rd March). The Economist.

Wolmar, C. (2018) Chapter 6 of Driverless Cars: On a Road to Nowhere. London, London

Publishing Partnership.