Autonomous Vehicles and Public Health

Abstract

Autonomous vehicles (AVs) have the potential to shape urban life and significantly modify travel behaviors. “Autonomous technology” means technology that can drive a vehicle without active physical control or monitoring by a human operator. The first AV fleets are already in service in US cities. AVs offer a variety of automation, vehicle ownership, and vehicle use options. AVs could increase some health risks (such as air pollution, noise, and sedentarism); however, if proper regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments. Healthy models of AV use include fully electric vehicles in a system of ridesharing and ridesplitting. Public health will benefit if proper policies and regulatory frameworks are implemented before the complete introduction of AVs into the market.
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Annual Review of Public Health
Autonomous Vehicles and
Public Health
David Rojas-Rueda,1,2 Mark J. Nieuwenhuijsen,2,3,4,5
Haneen Khreis,2,3,4,6 and Howard Frumkin7
1Department of Environmental and Radiological Health Sciences, Colorado State University,
Fort Collins, Colorado 80523, USA; email: david.rojas@colostate.edu
2ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona 08003,
Spain; email: mark.nieuwenhuijsen@isglobal.org
3Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
4CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
5Municipal Institute of Medical Research (IMIM), Hospital del Mar, Barcelona 08003, Spain
6Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH),
Texas A&M Transportation Institute (TTI), Texas 77843, USA; email: H-Khreis@tti.tamu.edu
7Department of Environmental and Occupational Health Sciences, University of Washington,
Seattle, Washington 98195, USA; email: frumkin@uw.edu
Annu. Rev. Public Health 2020. 41:18.1–18.17
The Annual Review of Public Health is online at
publhealth.annualreviews.org
https://doi.org/10.1146/annurev-publhealth-
040119-094035
Copyright © 2020 by Annual Reviews.
All rights reserved
Keywords
autonomous vehicles, self-driving cars, public health, environmental health,
transportation, built environment
Abstract
Autonomous vehicles (AVs) have the potential to shape urban life and signif-
icantly modify travel behaviors. “Autonomous technology” means technol-
ogy that can drive a vehicle without active physical control or monitoring
by a human operator. The rst AV eets are already in service in US cities.
AVs offer a variety of automation, vehicle ownership, and vehicle use op-
tions. AVs could increase some health risks (such as air pollution, noise, and
sedentarism); however, if proper regulated, AVs will likely reduce morbidity
and mortality from motor vehicle crashes and may help reshape cities to pro-
mote healthy urban environments. Healthy models of AV use include fully
electric vehicles in a system of ridesharing and ridesplitting. Public health
will benet if proper policies and regulatory frameworks are implemented
before the complete introduction of AVs into the market.
.
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1. INTRODUCTION
Globally, more people are living in urban than in rural areas, with 55% of the world’s population
residing in urban areas in 2018 (77). The urban environment shapes populations through mul-
tiple health pathways, such as physical activity, air pollution, green spaces, social capital, access
to health services, and transport, among others (60, 89). Urban transportation policies, in partic-
ular, have been suggested as a principal pathway through which urban environments can either
impair or promote health (23, 60). This eld is dynamic and rapidly evolving; recent advances in
technology have led to transportation innovations such as multimodal integration via online appli-
cations, on-demand digitally enabled transportation, electrication of motorized transportation,
and connected autonomous vehicles (AVs) (26).
AVs are considered a major disruptive technology in the transportation sector, with the po-
tential to produce signicant changes in travel behaviors and the built environment (42). “Au-
tonomous technology” refers to technology that has the capability to drive a vehicle without active
physical control or monitoring by a human operator (74). There are six levels of vehicle auton-
omy, as dened by the Society of Automotive Engineers (SAE): Levels 0–2 are those where the
human driver needs to monitor the driving environment, and levels 3–5 are those where an auto-
mated driving system monitors the driving environment (also referred to in the US federal policy
guidance as highly automated vehicles) (69, 92). A fully autonomous vehicle is a vehicle that has a
full-time automated driving system that undertakes all aspects of driving that would otherwise be
undertaken by a human, under all roadway and environmental conditions (64). This article focuses
on the role of higher levels of AVs in public health.
In 2018, Waymo, the Google subsidiary developing AVs, introduced the rst shared AV eet
to the market (Waymo-One) (https://waymo.com/). More than 1,400 self-driving cars, trucks,
and other vehicles are currently being tested by more than 80 companies across 36 US states and
the District of Columbia (25). Recent estimates suggest that by 2020, 5% of car sales will be AVs,
representing 2% of the vehicle eet and 4% of the miles traveled in the United States (42). The
same estimates predict that by 2030, AVs will cover 40% of the car market sales, representing 20%
of the vehicle eet and 30% of the miles traveled in the United States (42).
The potential impacts of AVs on public health could vary depending on the level of automa-
tion, type of use and ownership, and type of engine (internal combustion, hybrid, electric, etc.).
In terms of automation, this review refers mostly to those AVs with full automation (where an
automated driving system performs all aspects of the dynamic driving task under all roadway and
environmental conditions). Various patterns of AV ownership and use have been suggested; for
instance, private AVs imply private vehicle ownership and private use, and shared autonomous ve-
hicles (SAVs) imply shared uses, with or without vehicle ownership. Variants include carsharing,
personal vehicle sharing, ridesharing, and on-demand services (Figure 1). Carsharing is a model of
shared transportation in which several people use the same vehicle at a different time without car
ownership. Carsharing may be station based, where the car is picked up and returned to the same
location, and free oating, where the car is picked up at one location and left near the user’s des-
tination. Personal vehicle sharing is a system in which car owners convert their personal vehicles
into shared cars and rent them to others on a short-term basis; this arrangement could be be-
tween peers (peer-to-peer) or through shared vehicle ownership (fractional ownership). Rideshar-
ing pools multiple travelers with similar or overlapping paths (origins/destinations) and departure
times in the same vehicle (carpooling or vanpooling). On-demand services refer to vehicle shar-
ing with door-to-door services and are classied as ridesourcing or ridesplitting. Ridesourcing is
a door-to-door service that uses private vehicles for paid on-demand rides (such as Uber or Lyft).
Ridesplitting is a variant of the ridesourcing model, in which passengers with similar or overlap-
ping routes split a fare and ride in a ridesourcing vehicle (such as an Uber pool).
. Rojas-Rueda et al.
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INDIVIDUAL
Carsharing Personal vehicle
sharing
Station
based
Free
oating
Peer-to-peer
carsharing
Fractional
ownership Carpooling Vanpooling Ridesourcing
(Uber or Lyft)
Ridesplitting
(Uber pool)
Ridesharing On-demand
ride services
SHARING
Figure 1
Autonomous vehicles by type of use and ownership (green indicates options with greatest expected health benets and fewest health
risks).
AV use and ownership could translate meaningfully into health impacts. AV use and ownership
variations could increase health risks, by increasing overall vehicle miles traveled (VMTs) per per-
son, increasing emissions, and promoting sedentarism, or yield health benets, by reducing vehicle
crashes and reducing the number of vehicles on the streets, freeing urban space for recreational
use or vegetation.
2. POTENTIAL IMPACTS OF AVs ON PUBLIC HEALTH
We have developed a framework on autonomous vehicles and health determinants (Figure 2). In
this framework, we summarize the main health determinants related to AVs,consider two different
levels of impacts, direct and indirect, and highlight the expected changes in such determinants
(increments or reductions). “Direct impacts” refer to those impacts affecting travelers who use
AVs. “Indirect impacts” refer to those impacts that occur after widespread implementation of AVs
and that affect the larger community. The following sections describe the health determinants
presented in this framework and their interrelation with AVs.
2.1. Direct Impacts
AV direct impacts are those health determinants that affect travelers using AVs and are the most
common impacts associated with AVs.
2.1.1. Trafc safety. The AV industry and authorities claim that improved trafc safety would
be one of the signicant benecial impacts of AV use (30, 59). In 2017, 37,133 people were killed
in motor vehicle crashes in the United States (including nearly 7,000 pedestrians and cyclists)
(54, 78). Of all serious motor vehicle crashes, 94% involve driver-related factors, such as impaired
driving, distraction, and speeding or illegal maneuvers (78). Globally, road trafc incidents are one
of the leading causes of mortality,with 1.3 million people killed each year (86),and almost 90% of
those road trafc deaths are concentrated in low- and middle-income countries (44), despite that
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D
I
R
E
C
T
I
M
P
A
C
T
S
Noise
Non-exhaust
emissions
Economy and
employ-
ment
Economy and
employment
Substance
use
Access to
services
Social equity
Social equity
Stress
Work
conditions
Exhaust
emissions
Physical
activity
Electromagnetic
elds
Disabled people
autonomy and
inclusion
Trac
congestion
Land
use mix
Healthy
urban
design
Energy
consumption
Climate
change
Social
interactions
Children/elderly
autonomy and
inclusion
SHARED-ELECTRIC
AUTONOMOUS
VEHICLE
Trac
incidents
I
N
D
I
R
E
C
T
I
M
P
A
C
T
S
Expected increment
Expected reduction
Expected increment or reduction
Figure 2
A framework of autonomous vehicles and health determinants.
these countries have 48% of the world’s registered vehicles (86). A relevant health consideration
on trafc safety is that the majority of trafc injuries and fatalities in the United States happened
in individuals between ages 16 and 40 years old, where the number of years lived with disability
or years of life lost are greater (12, 49).
Fully automated vehicles could lead to reductions in the number of driver-related crashes (44).
Luttrell et al. (44) in 2015 modeled the expected impacts of AVs on motor vehicle crash injuries and
fatalities. They estimated that if 90% of the automobiles in the United States became autonomous,
an estimated 25,000 lives could be saved each year,with annual economic savings estimated at more
than $200 billion in the United States (44). These impacts are highly dependent on the market
penetration of AVs and are expected to be small initially but to grow as AVs are more widely
adopted. The safety benets of AVs are expected to emerge more rapidly in wealthy countries,
which will adopt AVs sooner, than in low- and middle-income countries, where adoption will
lag—a paradox given the higher risk in low- and middle-income settings. A barrier to the rapid
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adoption of AVs is public reluctance due to high-prole news coverage of AV crashes in recent
years (28).
Improved road safety related to AV use may lead to a decline in organ donations (1). In 2018 in
the United States, organ donations from motor vehicle crashes represented 13% of all donations
(81). The implementation of AVs should, therefore, trigger efforts to promote and strengthen
organ donation systems (36).
Finally, ethical issues involving the decisions made by AVs in the case of trafc incidents are
a relevant factor to consider (47). An imminent crash may pose instantaneous decisions about
who will die: a passenger or pedestrian, an older person or a child? The moral elements of such
decisions must be programmed into the algorithms used by AVs. A recent multinational survey on
moral decisions related to AV and road safety found that these moral decisions vary considerably
by gender, social status, and nation and appear to reect underlying societal-level preferences for
egalitarianism (47).
2.1.2. Physical activity. Transport-related physical activity (walking, cycling, or walking to and
from public transport) has been suggested as a strategy for increasing daily levels of physical activ-
ity (24, 65, 67). The benets of active transportation have been quantied in several cities around
the world and have shown both direct benets for pedestrians and cyclists and broader indirect
benets through improved air quality and reduced trafc noise (51). The impact of AVs on travel
behavior (and their corresponding impact on transport-related physical activity) is difcult to pre-
dict. But recent modeling studies suggest that AVs could increase VMTs by between 15% and 59%
and reduce the use of public and active transportation (73). In these transportation models, pri-
vate AVs also led to a more dispersed urban growth pattern (sprawl), which could increase trip
distances, making walking and cycling less attractive (66). However, some studies also suggest that
SAVs could decrease VMTs (in the range of 10–25%) if a large share of the travelers are willing to
rideshare (73). SAVs, especially when utilized through ridesharing or ridesplitting, are likely to re-
duce transport-related physical activity less than private AVs, as this approach is more compatible
with being complemented by walking, cycling, or using public transportation.
2.1.3. Air pollution emissions. Ninety-ve percent of the world’s population lives in areas ex-
ceeding the World Health Organization (WHO) guideline for healthy air (34). Air pollution is a
global leading risk factor for mortality and morbidity (34). Motorized vehicles are a major source
of air pollution in urban areas (3, 68). In 2015, estimates indicate that, globally, the attributable
number of deaths related to road transport air pollution was ∼250,000 deaths (4). Moreover, ex-
posure to air pollution tends to be greater for people within automobiles than for those who are
walking, cycling, or riding buses (22). Transport-related air pollution emissions can be classied
as exhaust and nonexhaust emissions.
2.1.3.1. Exhaust emissions. The impact of AVs on air pollution exposure relates to three fac-
tors: whether AV use increases the overall amount of VMTs, the extent to which AVs pollute
(gasoline and diesel engines pollute more than electric vehicles do), and the extent of integration
between AVs and active and public transport. AV implementation could increase air pollution ex-
posure if it increases overall VMTs (65), which is a possibility if AVs continue to rely on internal
combustion engines (73) and/or if AV use patterns do not facilitate walking, cycling, and tran-
sit use. If AVs are not fully electric, future higher exposure periods to air pollution may affect
AV travelers, and higher air pollution exhaust emissions would then affect the general public. AV
regulations could account for these issues to reduce the negative externalities of motorized trans-
port, not only in air pollution exposure but also through contributions to CO2and black carbon
emissions associated with climate change.
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2.1.3.2. Nonexhaust emissions. Air pollution from motor vehicles is not limited to exhaust
emissions. Other sources include brake and tire wear, road surface wear, and resuspension of road
dust. Together these may exceed tailpipe emissions, at least with regard to particulate matter (3).
Moreover, brake and tire wear particles may have higher oxidative potential than other trafc-
related sources, which could translate to worse health impacts (3). Electric vehicles also have been
suggested to emit more nonexhaust emissions because they weigh more than nonelectric vehicles
(76). If AV use increases VMTs, even with a shift to electric vehicles, nonexhaust emissions will be
an issue for air quality.Potential strategies to reduce these emissions include source minimization
by improving the wear properties of materials, reducing the wear potential of trafc (e.g., studded
tires), and minimizing dust suspension to air by removing dust from road surfaces (road cleaning),
immobilizing dust (binding dust to road surfaces), and adjusting trafc (less trafc, lower speeds,
lighter weight vehicles) (3).
2.1.4. Noise. Another important aspect of AVs is the impact on road trafc noise. Road trafc
noise has been associated with multiple health outcomes, including sleep disturbance, annoyance,
cardiovascular disease, and hypertension (6, 10, 14, 32, 50, 61). In Europe, for instance, environ-
mental noise causes an estimated 10,000 premature deaths per year (9, 88). AVs using internal com-
bustion engines could continue to contribute to road trafc noise. As in the case of air pollution,
if AV use results in increased VMTs, then noise exposure would increase commensurately (73). In
contrast, electrication of the vehicle eet would reduce noise exposure [although at speeds above
50 km per hour, electric and hybrid cars are not quieter than conventional cars (82)]. A Dutch
study projected that a fully electric car eet would reduce average urban noise levels by 3–4 dB
and reduce annoyance effects by more than 30% (82). At low speeds, electric cars may also pose a
safety risk, owing to the lack of noise, especially for pedestrians with visual impairments who rely
on auditory cues (9, 15). In some countries such as the United States and Japan, regulators are con-
sidering requiring manufacturers of hybrid and electric cars to install an articial warning sound
(21). This intervention, if implemented for electric AVs, would lead to road safety improvements.
2.1.5. Electromagnetic elds. Electric and magnetic elds (EMFs) are invisible areas of energy
(also called radiation) that are produced by electricity (53). Low- to mid-frequency EMFs are in
the nonionizing radiation part of the electromagnetic spectrum and are not known to damage
DNA or cells directly (53). Numerous epidemiologic studies have evaluated possible associations
between exposure to nonionizing EMFs and the risk of cancer, without conclusive results (53). But
a recent study of the US National Toxicology Program concluded that there is clear evidence that
male rats exposed to high levels of radiofrequency, such as that used in 2G and 3G cell phones,
developed heart tumors (56). AVs use multiple technologies that would entail exposure to a range
of EMFs. Owing to the current lack of evidence on the health impacts of EMFs, it is difcult to
draw conclusions or offer recommendations on this issue. Further research is needed to clarify the
potential health implications of EMFs.
2.1.6. Substance abuse. Alcohol and cannabis are the most frequently detected drugs in US
drivers (55). In 2013, 9.9 million people in the United States reported driving under the inuence
of illicit drugs (55, 58). Trafc laws prohibit driving under the inuence of alcohol or drugs. Such
policies, together with associated shifts in social norms, have increased public awareness and have
discouraged abuse of these substances while driving (62). It is conceivable that widespread AV use
would contribute to laxity in public attitudes toward alcohol and drugs. Australia’s National Trans-
port Commission, in a 2017 discussion paper, likened occupants of fully autonomous vehicles to
taxi passengers and suggested that they may be exempted from legal restrictions on drunk- and
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drug-impaired driving (57). A clear denition of the capabilities and requirements of AV passen-
gers will need to be aligned with future drink-driving and drug-impaired driving policies. Also,
broader efforts to discourage alcohol and drug abuse should be maintained so that any relaxation
of restrictions in the context of road travel does not undermine social norms against alcohol and
drug abuse.
2.1.7. Work conditions. A growing body of evidence suggests that long working hours ad-
versely affect the health and well-being of workers, increasing their risk of hypertension, cardio-
vascular disease, fatigue, stress, depression, musculoskeletal disorders, chronic infections, diabetes,
general health complaints, and all-cause mortality (72). Because 15% of daily trips in the United
States are taken for commuting (11), changes in travel patterns have an impact on work. Fully
AVs will not require passenger attention to driving tasks, which could result in the dedication of
commute time to work-related activities (as now occurs with some bus and train commuters). No
studies have considered the impact of AVs on work schedules and activities. But we have consid-
ered two main scenarios: (a) Commuting time in AVs extends unpaid and unofcial working times,
resulting in long working hours, and (b) commuting time in AVs comes to be considered ofcial
work time. Considerations of work regulations related to commuting by AVs will be needed to
avoid excessive working hours and associated negative health impacts.
2.1.8. Stress. The experience of driving has been suggested to be potentially detrimental to
health (5). A recent review provided evidence to suggest that driving for long hours elicits a stress
response over an extended period of time (5). Stress, in turn, has adverse impacts on the immune,
cardiovascular, and nervous systems, among others (45). Evidence indicates that automation is
likely to decrease mental workload and stress, thereby producing a more positive set of emotional
responses (18). The use of AVs could reduce the stress of driving, yielding health benets.
2.1.9. Social interactions. AVs could have either positive or negative impacts on social inter-
actions. On the positive side, AVs could facilitate increased access to venues for social interactions
and social support that help promote good mental health (73), and shared AVs could offer oppor-
tunities for social interactions among passengers during rides. On the negative side, AVs could
increase commuting time (if commuting by AV is seen as more painless than driving, and people,
therefore, choose to live farther from work), and longer commute times are associated with re-
duced community involvement, reduced time with friends and family, and reduced levels of social
capital (8, 13, 46).
2.2. Indirect Impacts
AV indirect impacts are those impacts that occur after widespread implementation of AVs and
that affect the larger community. These impacts could be less commonly associated with AVs but
could have important health implications.
2.2.1. Trafc congestion. Vehicles that are highly but not fully automated would probably
not behave signicantly differently from normal vehicles with respect to their contribution to
congestion. For fully automated AVs (driverless vehicles), some factors seem likely to operate both
to increase and to decrease congestion (48). A study of a theoretical grid-based urban area indicated
that one shared-ownership AV could replace 11 conventional vehicles (27). The International
Transport Forum estimated that the travel needs of the city of Lisbon could be met without the use
of private cars in the urban core area and hence without congestion if eets of SAVs replaced all car
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and bus trips in the city of Lisbon, in addition to existing rail and subway services (37). Reduction
in trafc congestion related to SAVs could have benecial impacts on travel time, reducing travel
sitting time, air pollution, and noise.
2.2.2. Impact on public transportation. Public transportation has been associated with a lower
risk of trafc incidents, compared with other modes of transportation (41, 66, 67). Public trans-
portation has also been suggested as a promoter of physical activity, owing to the inclusion of
walking trips to and from public transport stations (63, 66, 70, 90). Furthermore, if public trans-
portation substituted car trips, the shift could lead to a reduction in air pollution emissions, specif-
ically if the public transportation eet relies on electricity (e.g., light transit rail), hybrid energy,
or natural gas (buses) (7, 33, 67).
While AV implementation could lead to various impacts on public transportation use, not all
impacts are positive. If public transportation were to be fully supplanted by private AV alternatives
such as ridesharing offering door-to-door services, this change may lead to physical activity reduc-
tions and socioeconomic inequities, removing affordable transportation options for low-income
citizens (35). A possible path to mitigate this scenario is the integration of AVs in the public trans-
port system. Recent projects in the European Union have successfully tested autonomous transit in
7 European cities, carrying more than 60,000 passengers and sharing the infrastructure with other
road users (2). Other types of public transit, such as bus rapid transit (BRT) using autonomous pla-
tooning with precision docking, will produce a BRT-type service that can offer the same capacity
and service as rail transit with signicantly less cost (43).
Transit planners must nd ways to characterize autonomous vehicles accurately and include
them in the spectrum of mode choices available to travelers when confronted with alternative
choices. Possible disruptive impacts on public transportation should be considered an equity
issue owing to the impacts on the transit-dependent population. Finally, another possible con-
sequence of AV integration with public transportation would be the disappearance of driving jobs,
which in European Union countries account for 4.8 million employees (38). However, some re-
search predicts that the replacement of professional drivers by technology will be gradual, with
software initially taking over some elements of driving but with people still being required for
tasks such as close maneuvering (38).
2.2.3. Land use and healthy urban design. SAV eets could have positive impacts on urban
land use. Urban parking space may be reduced as much as 90% if AVs are implemented in rideshar-
ing mode (73). Moreover, AVs could also permit the relocation of public space from automobile
infrastructure to other activities, such as green and blue spaces that support physical activity and
social interaction (52, 83). However, modeling results on parking space related to AVs are very
sensitive to model assumptions, which are still very uncertain (e.g., the perception of time in AVs
or operational costs) (73).
AVs will also increase accessibility to multiple destinations, which could be more relevant for
populations living in suburbs and rural regions. Increasing access to destinations by reducing the
opportunity cost of travel time, increasing road capacity, and reducing travel time could result
in increased urban sprawl (19, 39, 40, 73). One modeling study of private AVs in Melbourne,
Australia, with a scenario for the year 2046 projected a 4% reduction in the population living in
inner parts of the city and a 3% increase in the population living in the far outer suburbs (75).
In the same study,a scenario considering ridesharing SAVs in Melbourne reported a 4% increase
in population in inner parts of the city,while far outer suburbs experienced a 3% reduction in the
population (75). Another modeling study, in Atlanta, concluded that SAV use would not induce
residential sprawl into exurban areas but would accelerate urban deindustrialization (91).
. Rojas-Rueda et al.
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2.2.4. Clean energy, energy consumption, and climate change. Climate change is a leading
threat to human health in the present era (84). Climate change impacts health through multiple
pathways, from food access and quality to air pollution to extreme weather (29, 87). The combus-
tion of fossil fuels as energy sources releases greenhouse gases, a principal contributor to climate
change. The transportation sector is an important contributor, representing about 14% of green-
house gas emissions globally and twice that amount in the United States (80). In 2017, on-road
vehicles in the United States, including light-duty passenger cars and trucks, buses, and commer-
cial and freight trucks, consumed 11.6 million barrels per day (b/d) oil equivalent, which accounted
for 80% of all transportation energy use and 31% of all delivered end-use energy in the United
States (79).
The impact of AVs on climate change will depend on several factors: the impact on VMTs
(with more VMTs, ceteris paribus, requiring more energy), the energy usage per vehicle, and the
source of energy used. If AV use increases overall VMTs, then the overall transportation energy
demand would increase. An increase in traveler population could increase empty miles driven, as
well as travel demand, and may shift travel from other modes to AVs (79). On the other hand,
AV use could reduce energy consumption through reductions in parking hunting, ridesharing,
eco-driving, congestion mitigation, collision avoidance, and vehicle/power resizing (79).
The source of energy for AVs is a critical factor. In 2017, 99% of the energy used by light-duty
passenger cars and trucks came from gasoline and diesel (79). The AVs currently being tested
are gasoline dependent, with some hybrid vehicles in the mix. In the future, AVs are expected
to be fully electric (30, 85). AVs could be an opportunity to promote the sale of more energy-
efcient or clean-energy vehicles through a faster payback of the more expensive purchase price
(79). Shared-use mobility providers offer the greatest potential for a faster payback (79). AVs could
also promote the use of alternative fuels through refueling without the rider and by reducing the
anxiety related to plug-in electric vehicles by ensuring that consumers always have a sufciently
charged electric vehicle available (79). In general, AVs offer an opportunity to promote the tran-
sition from fossil fuels to renewable sources of energy if the AVs are implemented as fully electric
vehicles together with a supply chain based on renewable energy sources. In addition to electric
AVs based on renewable energy sources, shared-electric AVs represent the optimal strategy to in-
creasing energy efciency, reducing consumption, especially when integrated into healthy urban
and transport environments, and supporting active and public transport.
2.2.5. Access to services, autonomy and inclusion, social equity, employment, and econ-
omy. For some population groups, driving is not a feasible option. Barriers to driving include
the cost of full-time car ownership, the cost of learning to drive, difculties with licensing, or
factors related to health, disability, or age (20). For those affected communities, the difculty in
accessing transportation contributes to socioeconomic disadvantage (20). Some equity priorities
in transportation are related to transportation costs, access to destinations, services (such as health
services), and employment (16). A recent study modeled the equity impact of AVs in terms of
job accessibility in Washington, DC (17). The study found that in all the scenarios modeled, AVs
increased job accessibility, especially in more disadvantaged populations and in scenarios using
ridesharing SAVs (17). Two main recommendations to support social equity for AVs are (a)to
engage and include disadvantaged communities in transportation planning, especially regarding
SAVs; and (b) to reduce barriers to using SAVs, including nancial, technological, language, and
cultural barriers. In addition to these recommendations, a 2018 report related to the impact of AV
on US workers found that the introduction of autonomous cars and trucks could directly elimi-
nate 1.3–2.3 million workers’ jobs over the next 30 years; this issue also needs to be considered in
terms of workers’ health (31).
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3. RECOMMENDATIONS
At a high level, the optimal strategies for advancing public health through AVs appears to be
shifting from internal combustion to electric vehicles, ensuring support from a renewable energy
supply system, and favoring SAVs over individually owned vehicles. Policy and research recom-
mendations for policy makers, health practitioners, and researchers are summarized in Table 1,
with reference to specic health determinants and outcomes as discussed above. AV policies and
regulations should be analyzed, debated, and implemented in advance of the full introduction
of AVs to the market. A “health in all policies” approach will help minimize the health risks re-
lated to AVs and maximize their possible benets (71). Public health practitioners should lead in-
tersectoral groups to introduce health vision into the AV projections. Substantial research gaps
exist around AVs. More funding opportunities should be available to focus on understanding
the implication of AVs on travel behavior, trafc safety, land use, urban built environments, and
transportation-related costs. From the public health perspective, more understanding of the ethics
related to AVs and road safety, health equity, and environmental and urban health is required to
understand the health implications of AV technologies. In general, there are many uncertainties
about the direction of the impacts related to AVs. The range of impacts depends on the type
of model that the industry and governments promote. Substantial health gains are expected for
approaches that utilize fully electric AVs in a shared system with a ridesharing or ridesplitting
format.
Table 1 Autonomous vehicle (AV) recommendations for policy makers, health practitioners, and researchers
Health determinant
Recommendations
Road safety
Physical activity
Clean energy, energy consumption,
and climate change
Air pollution
Noise
Electromagnetic elds
Substance abuse
Work conditions
Social interaction
Land use
Social equity, autonomy, inclusion,
employment, and economy
Favor shared AVs over private AVs ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Favor rideshare and ridesplitting ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Integrate shared-electric AVs in the public
transport system
✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Integrate shared-electric AVs to promote (not to
compete with) active transportation
✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Prioritize shared-electric AVs on those vulnerable
and disadvantaged communities (in all
geographical areas), who will benet more
from trafc safety interventions
✓ ✓ ✓
Consider market penetrance of AVs when
designing and estimating the road safety
impacts
✓ ✓
(Continued)
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Table 1 (Continued)
Health determinant
Recommendations
Road safety
Physical activity
Clean energy, energy consumption,
and climate change
Air pollution
Noise
Electromagnetic elds
Substance abuse
Work conditions
Social interaction
Land use
Social equity, autonomy, inclusion,
employment, and economy
Promote research that provides a comprehensive
vision of moral and ethical issues related to AVs
and road safety
✓ ✓
Promote and strengthen organ donation national
systems
✓
Promote research on travel behavior related to
AVs and modal share
✓ ✓ ✓ ✓
Prioritize the implementation of fully electric AVs ✓ ✓ ✓ ✓
Prioritize the energy supply (in urban and rural
areas) based on renewable energy sources
✓ ✓ ✓ ✓ ✓
Improve AVs’ wear properties of materials and
reduce the wear potential of trafc sources
✓ ✓ ✓
Reduce road dust suspension by
removing/immobilizing dust from road
surfaces (road cleaning)
✓ ✓ ✓
Bind dust to the road surface and adjust trafc
(less trafc, lower speed, less heavy AVs)
✓ ✓ ✓
Engage with and include disadvantaged
communities in transportation planning,
especially regarding shared-electric AVs
✓ ✓ ✓ ✓ ✓
Reduce barriers to using shared-electric AVs,
including nancial, technological, language,
and cultural barriers
✓ ✓ ✓ ✓
Support research on exposure levels of
electromagnetic elds in AVs
✓
Support research on health implications of
electromagnetic elds in general and in
particular those related to AVs
✓
Dene the AV passenger/driver regulations on
alcohol and drug consumption
✓
Support drinking- and drug-oriented policies to
reduce substance abuse
✓
Clearly dene and regulate work-related activities
during commuting in AVs to avoid overtime or
long working hours
✓
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4. CONCLUSIONS
Autonomous vehicles are an innovative transport intervention that will impact public health. Main
health impacts (risks and/or benets) rely on the AV implementation model related to the type
of use, ownership, engine, fuel, and integration with other modes of transportation. Aside from
the expected benets associated with trafc safety, AVs could offer major opportunities for pub-
lic health when AVs are implemented as fully electric (depending on renewable sources), in a
ridesharing format, and integrated with public and active transportation modes. All these charac-
teristics could promote physical activity, improve the urban environment (air quality and noise),
and provide more public space to support a healthy urban design. On the other hand, major risks
can be present when AVs are implemented for individual use, depend on fossil fuels, lead to more
miles traveled, exacerbate trafc congestion, and increase occupancy of public spaces; all of these
factors result in more sedentarism, degradation of the urban environment (air quality and noise),
and reductions in the amount of public space available for social interaction and physical activity.
Prioritizing research to increase understanding related to AV market penetration, travel behavior,
safety,land use, and built environments will lead to improved current health frameworks and help
implement future health impact assessments on AVs. At this stage, general recommendations can
be generated to support policies and regulations prioritizing electric AVs in a format of ridesharing
or ridesplitting. The implementation of AVs should aim to support public and active transporta-
tion, prioritizing more disadvantaged communities and contributing to the evolution of urban and
transport planning toward a healthier urban environment.
SUMMARY POINTS
1. AVs could result in health risks and/or benets.
2. Proper policies and regulations prioritizing electric AVs in a format of ridesharing or
ridesplitting would optimize benets for health.
3. AVs should be designed to support public and active transportation.
4. AVs should be prioritized in disadvantageous communities.
5. AVs should contribute to an urban planning revolution with a vision for healthy urban
environments.
6. AV policies and regulatory frameworks should be implemented before the complete in-
troduction of AVs into the market.
FUTURE ISSUES
1. Future research should provide a comprehensive vision of moral and ethical issues re-
latedtoAVsandroadsafety.
2. Research is needed on travel behavior related to AVs and modal share.
3. Future research should investigate barriers to using shared-electric AVs, including -
nancial, technological, language, and cultural barriers.
4. Research on exposure and health impacts of electromagnetic elds in AVs is needed.
5. Health impact assessment of AVs is critical.
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DISCLOSURE STATEMENT
The authors are not aware of any afliations, memberships, funding, or nancial holdings that
might be perceived as affecting the objectivity of this review.
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