Users’ Propensity to Use Self-Driving Systems of SAE Automation
Level 1 and 2 Cars: Results of an Italian Survey
MARIAROSARIA PICONE*
Department of Engineering,
University of Campania “Luigi Vanvitelli”,
via Roma 29, 81031 Aversa (Caserta),
ITALY
ARMANDO CARTENI
Department of Engineering,
University of Campania “Luigi Vanvitelli”,
via Roma 29, 81031 Aversa (Caserta),
http://orcid.org/0000-0003-4181-6631
ITALY
*Corresponding Author
Abstract: - The automotive sector is currently developing advanced autonomous functionalities which are
expected to be soon integrated into the vehicles. These vehicles can help to reduce road accidents, ease traffic
congestion, improve fuel consumption, and reduce pollutant emissions. By contrast, there are still
technological, normative, ethical, and social obstacles to the widespread adoption of self-driving cars, among
which users’ acceptance covers a relevant issue. The aim of the paper was to investigate the users’ propensity
to use self-driving systems of SAE automation Levels 1 and 2. To do this, an hoc mobility survey was
performed in Italy among car drivers, investigating both the presence of these autonomous devices on board the
vehicles currently used and their frequency of usage. Survey results show that 41% of the respondents currently
have a Level 1 and/or 2 system on-board their car: 54% have only the Cruise Control (Level 1 car), while 46%
have both of them (Level 2 car). Furthermore, about 85% of the respondent frequently (medium-high) use the
Cruise Control and/or Lane Keeping Assist. More than 86% of the drivers stated that these devices significantly
improve both road safety and driving stress (improve the travel experience). The highways are the roads where
these self-driving systems are mainly used (more than 70% of the time). These results underline the relevant
effort that the automotive industry has performed in the last decades about self-driving. In the last five years
within the Italian market was observed an increase of more than 200% of the car standard equipment (no
optional) with SAE automation Level 1 or 2 systems.
Key-words: - Self-driving vehicles; driverless; Autonomous Vehicles (AVs); Automated Driving (AD);
Artificial Intelligence (AI); Advanced Driver Assistance Systems (ADAS); travel experience;
Society of Automotive Engineers (SAE)
Received: December 11, 2022. Revised: April 9, 2023. Accepted: May 1, 2023. Published: May 17, 2023.
1 Introduction
Europe faces unprecedented environmental,
economic, and social challenges. In this context of
profound uncertainty, self-driving vehicles, also
known as "driverless" or Autonomous Vehicles
(AVs), or Automated Driving (AD), represent a
significant opportunity and challenge for
sustainable mobility. They have the potential to
reduce road accidents, alleviate traffic congestion,
abate pollutant emissions, reduce fuel consumption,
[1], [2], [3], potentially decrease land use, and
profoundly modify the scope and boundaries of
mobility services (e.g., [4], [5]).
Studies have shown that AVs can have a
positive impact on mobility, productivity, and
leisure time, [6], [7], as well as on aesthetics with
more cutting-edge vehicle design distinct from the
current ones. For example, AVs could enhance
mobility for individuals who are unable to guide
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
479
Volume 19, 2023
vehicles due to youthfulness, advanced age,
physical disabilities, or other incapacities (e.g., [8],
[9], [10], [11], [12]). In addition, AVs offer also a
significant opportunity to advance sustainability
goals and address current and future challenges in
the environmental transition; the adoption of AV
technology will lead to optimized driving and
technology, through the so-called eco-driving, [2];
with smooth and gradual accelerations and
decelerations and lower peak speeds (improving
fuel efficiency). The Artificial Intelligence (AI),
governing AVs operation, will be capable of
ensuring a reduction in pollutant emissions, both in
terms of greenhouse gas emissions and particulate
matter.
The automotive sector is currently developing
advanced autonomous functionalities which are
expected to be soon integrated into the vehicles.
However, several major obstacles still hinder the
widespread adoption of autonomous vehicles (e.g.,
[13], [14], [15], [16], [17]), including
technological, normative, ethical, and social (public
acceptance) challenges (e.g., [18]), and other such
as high production costs, vehicle usage data
security and legal liability (e.g., [19], [20], [21],
[22]).
From a technological standpoint, both
governments and manufacturers follow the
autonomy level classification established by the
Society of Automotive Engineers, [23]. The SAE
has defined six different levels of automation,
ranging from Level 0 (no automation) to Level 5
(fully unrestricted automation). The automation of
vehicles occurs at different levels depending on the
balance between the role of the driver and that of
driving technologies or support. In this regard,
automated vehicles and autonomous vehicles are
not synonymous, according to the European
Commission, [24]: “automated vehicle is a motor
vehicle which has technology available to assist the
driver so that elements of the driving task can be
transferred to a computer system. While
autonomous vehicle is a fully automated vehicle
equipped with the technologies capable to perform
all driving functions without any human
intervention”.
Automated vehicles are fitted with advanced
driver assistance systems, known as ADAS, which
aid the drivers task and endeavor to avert accidents
by intervening when required. This feature
enhances road safety. On the other hand,
autonomous vehicles take over specific portions of
the dynamic driving task, which are ordinarily
executed by human drivers. Once engaged, the
hardware and software systems analyze the
environment and steer the vehicle accordingly. In
simpler terms, these vehicles are outfitted with
Artificial Intelligence (AI), which involves the
study of theoretical principles, methodologies, and
techniques for designing hardware systems and
software programs that can provide electronic
computers with abilities that appear to be the sole
domain of human intelligence to an ordinary
observer, [25]. As reported by the European
Parliament, [26]: “AI is the ability of a machine to
display human-like capabilities such as reasoning,
learning, planning and creativity. AI enables
technical systems to perceive their environment,
deal with what they perceive, solve problems and
act to achieve a specific goal. The computer
receives data - already prepared or gathered
through its own sensors such as a camera -
processes it and responds. AI systems are capable
of adapting their behaviour to a certain degree by
analyzing the effects of previous actions and
working autonomously”.
In 2021, SAE International redefined the levels
of automation based on the evolution and diffusion
of driving functions available in the market, in
order to specify when and under what operational
design domain (ODD) the dynamic driving task
(DDT) activities are performed by the driver and
when by the vehicle itself. The new SAE
classification highlights the automation progression
based on the driver's role in DDT: well-known and
now widely available advanced driver assistance
systems (ADAS) are functions from level 0 to up to
level 2, while automated driving (and the AI)
mainly comes in operation with level 3 functions,
where the driver must still be ready to intervene, up
to levels 4 and 5, where the AI has complete
control of the driving task. In other words,
according to the new classification, ADAS
contribute to automation, which, in addition,
leverages Artificial Intelligence to process
signals/data received from a combination of
sensors, cameras, radar, lidar, laser, GPS locators
(and many others), to comprehend the environment
and offer a response to challenges, thus ensuring
vehicle movement.
As reported in the “Road Safety Thematic
Report”, [27] the main difference between ADAS
and AD is the role of the driver. While ADAS only
support the driver with their driving task, AD can
take over the complete driving task for at least part
of the trip.
From a normative standpoint, numerous trials
are underway globally to accelerate the deployment
of autonomous vehicles, although fully autonomous
vehicles (Levels 4 and 5) are presently prohibited
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
480
Volume 19, 2023
from being sold in many Countries for legal
reasons. Until a few years ago, even experimental
testing of autonomous vehicles on public roads was
prohibited.
From an ethical perspective, the deployment of
autonomous vehicles, as examined in [13], will
necessitate ethical deliberations that could engender
various quandaries for designers, manufacturers,
regulators, and governments. There is a vast
scientific literature that addresses the social issue of
user acceptance of this new technology, which
translates into the level of usage that drivers make
of driving aid devices. For example, according to a
report by the American Automobile Association in
2017, [28], approximately 75% of Americans
expressed apprehension towards utilizing and
operating fully autonomous vehicles, corroborating
the findings of a previous survey conducted in
2016. Simultaneously, it emerges that 59% of
Americans are also eager to have autonomous
features on board their next vehicle, demonstrating
a strong propensity among Americans to accept this
new technology. This result underscores the
potential for widespread adoption of autonomous
vehicles in the near future, despite existing
concerns regarding user acceptance. Research has
shown that the acceptance of self-driving vehicles
varies across cultures. For instance, [19],
discovered that American respondents exhibited
greater apprehension towards utilizing autonomous
vehicles in comparison to their UK counterparts.
According to [29], a significant proportion of UK
users (60%) believe that driverless vehicles will
enhance the safety of all road users. Similarly, [30],
conducted an online survey targeting a large sample
of French drivers, revealing that more than half of
the respondents expressed an interest in utilizing
fully automated vehicles. Surveys conducted in
Australia yielded different results. In [31], [32], the
authors found that over 70% of respondents in
Australia and New Zealand were concerned about
riding in a car without a driver. The findings of
[19], were also noteworthy. They administered a
questionnaire in multiple countries (China, India,
Japan, USA, UK, and Australia) and discovered
that, regardless of location, 87-95% of respondents
were concerned (to varying degrees) about driving
or riding in a fully self-driving vehicle.
Starting from these considerations, the paper
aimed to investigate the users’ propensity to use
self-driving systems of SAE automation Levels 1
and 2. To do this, an hoc mobility survey was
performed in Italy among car drivers, investigating
both the presence of these autonomous devices on
board the vehicles and their frequency of usage.
The paper is structured as follows: Section 2
reports the experimental method, Section 3 it is
investigated the users’ propensity to use self-
driving devices of SAE automation Levels 1 and 2
and Section 4 reports the main conclusions,
limitations, and future directions.
2 Method
To perform the aim of the research an hoc mobility
survey was performed in Italy among the car
drivers. A CAWI (Computer-Assisted Web
Interviewing) survey was carried out between
January and February 2023 among car drivers
living in the Provinces of Naples and Caserta in
southern Italy.
The questionnaire submitted consisted of two
sub-sections:
1. socio-economic background (e.g., age,
gender, occupation) and mobility habits
(trip frequency, average travel time);
2. presence and level of usage of self-driving
systems of SAE automation Levels 1 and 2
with the aim of:
investigate the on-board presence of
the cruise control and the lane-
keeping assist by transmission type
(i.e., automatic vs. manual);
investigate the frequency of usage of
these two autonomous devices by road
type (urban, suburban, highway);
investigate the users opinion about
the role of the autonomous system
(SAE levels 1 and 2) in improving
road safety also mitigating driving
stress (improving the travel
experience).
3 Result and Discussion
Overall, 243 car drivers were interviewed, and
Table 1 reports the main survey results: 65% of the
sample was male; 65% were 18-40 years old; 71%
were employed.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
481
Volume 19, 2023
Table 1. Survey results: socio-economic characteristics
number
%
Gender
male
157
64.61%
female
86
35.39%
Age
18-30
90
37.04%
30-40
69
28.40%
40-50
48
19.75%
Over 50
36
14.81%
Profession
Employed
174
71.60%
Not employed
12
4.94%
Student
57
23.46%
Total sample size
243
100.00%
Results in terms of the presence of SAE Level 1
(Cruise Control or Lane Keeping Assist) and Level
2 (Cruise Control and Lane Keeping Assist) devices
on-board the vehicles are reported in Figure 1. 41%
of the respondents currently have a Level 1 and/or 2
system on-board their car. Precisely, among those
who have them, 54% of the respondents have only
the Cruise Control (Level 1 car), while 46% have
both the Cruise Control and the Lane keeping assist
(Level 2 car).
Fig. 1: Survey results: the presence of autonomous devices of SAE automation Levels 1 and 2 on board the
vehicles
Figure 2 reports the result in terms of both levels
of usage of these self-driving systems and users’
perception of their impact on road safety and driving
stress. About 85% of the respondent frequently
(medium-high) use the Cruise Control and/or Lane
Keeping Assist. More than 86% of the driver stated
that these devices significantly improve both on-
road safety and driving stress. Interestingly is to
observe that no differences in usage and/or opinions
have been found between Cruise Control and Lane
54%
46%
Does the vehicle that you habitually operate
feature Cruise Control and/or Lane Keeping
Assist (SAE level 1 or 2)?
Only Cruise Control Yes, both of them
59%
22%
19%
Do the vehicle that you habitually guide have Cruise
Control and/or Lane Keeping Assist (SAE
automation Level 1 or 2)?
No, neither of them Yes, only Cruise Control Yes, both of them
54%
46%
If Yes, do you have only the Cruise Control or
also the Lane Keeping Assist ?
Only Cruise Control Both of them
59%
22%
19%
Do the vehicle that you habitually guide have Cruise
Control and/or Lane Keeping Assist (SAE
automation Level 1 or 2)?
No, neither of them Yes, only Cruise Control Yes, both of them
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
482
Volume 19, 2023
Keeping Assist users. In addition, Figure 3 shows
that the highways are the roads where these self-
driving devices are mainly used (more than 70% of
the time).
Fig. 2: Survey results: frequency of usage and users opinion about the role of the autonomous system (SAE
level 1 and 2) in improving road safety, also mitigating driving stress (improving the travel experience).
Fig. 3: Survey results: frequency of usage autonomous devices (SAE Level 1 and 2) on board the vehicles by
road type (urban, suburban, highway)
Further analysis was conducted to examine possible
differences in habits between manual and automatic
car transmission users. From the survey emerges
that (Figure 4) the presence of Cruise Control (Lane
Keeping Assist) in vehicles with automatic
transmission is 35 (49) percentage points higher
than in a vehicle with a manual transmission. This
result is probably related to the circumstance that
the car with automatic transmissions has a greater
tendency to own more on-board options (such as
Cruise Control or Lane Keeping Assist), as the
automatic transmission is itself an (expensive)
option for the Italian market.
41%
59%
Does the vehicle that you habitually
operate feature Cruise Control?
Yes No
86%
14%
Does utilizing Cruise Control contribute
to enhanced driving safety and/or
reduced driving stress?
High Low
19%
81%
Does the vehicle that you habitually
operate feature Lane Keeping Assist?
Yes No
87%
13%
Does utilizing Lane Keeping Assist
contribute to enhanced driving safety
and/or reduced driving stress?
High Low
86%
14%
Do the use of Cruise Control contribute
to enhanced road safety and/or
reduced driving stress?
High Low
41%
59%
Do the vehicle that you habitually guide
have Cruise Control?
Yes No
19%
81%
Do the vehicle that you habitually
guide have Lane Keeping Assist?
Yes No
87%
13%
Do the use of Lane Keeping Assist
contribute to enhanced road safety
and/or reduced driving stress?
High Low
47%
38%
14%
How frequently do you use Cruise
Control?
High Medium None
63%
22%
15%
How frequently do you utilize Lane
Keeping Assist?
High Medium None
63%
22%
15%
How frequently do you use Lane
Keeping Assist?
High Medium None
9%
22%
69%
URBAN EXTRAURBAN HIGHWAY
On which type of road do you primarily utilize
Cruise Control?
74%
5% 2%
19%
SYSTEM ALWAYS
ACTIVE
URBAN EXTRAURBAN HIGHWAY
On which type of road do you primarily utilize Lane
Keeping Assist?
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
483
Volume 19, 2023
Fig. 4: Survey results: the presence of autonomous devices of SAE automation Level 1 and 2 on board the
vehicles by different car transmission (manual vs. automatic) users
In terms of frequency of usage, a significant
difference was observed between drivers of
automatic transmission cars and those of manual
ones (Figure 5); specifically, the former uses Cruise
Control and/or Lane Keeping Assist more frequently
than the latter (about 7-10 percentage points more).
Finally, both these categories of drivers agree that
SAE Level 1 and 2 systems significantly reduce
driving stress and increase road safety (Figure 6).
32%
68%
Does the vehicle that you habitually
operate feature Cruise Control?
Yes No
67%
33%
Does the vehicle that you habitually
operate feature Cruise Control?
Yes No
8%
92%
Does the vehicle that you habitually
operate feature Lane Keeping Assist?
Yes No
57%
43%
Does the vehicle that you habitually
operate feature Lane Keeping Assist?
Yes No
Drivers who drive a vehicle with a manual transmission Drivers who drive a vehicle with an automatic transmission
41%
59%
Do the vehicle that you habitually guide
have Cruise Control?
Yes No
41%
59%
Do the vehicle that you habitually guide
have Cruise Control?
Yes No
19%
81%
Do the vehicle that you habitually
guide have Lane Keeping Assist?
Yes No
19%
81%
Do the vehicle that you habitually
guide have Lane Keeping Assist?
Yes No
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
484
Volume 19, 2023
Fig. 5: Survey results: frequency of usage of autonomous system (SAE level 1 and 2) by car transmission type
(manual and automatic)
Fig. 6: Survey results: users opinion about the role of the autonomous system (SAE Level 1 and 2) in
improving road safety, also mitigating driving stress (improving the travel experience) by car transmission type
(manual and automatic)
50%
42%
8%
How frequently do you utilize Cruise
Control?
High Medium/low None
Drivers who drive a vehicle with a manual transmission Drivers who drive a vehicle with an automatic transmission
46%
36%
18%
How frequently do you utilize Cruise
Control?
High Medium/low None
53%
27%
20%
How frequently do you utilize Lane
Keeping Assist?
High Medium/low None
68%
19%
13%
How frequently do you utilize Lane
Keeping Assist?
High Medium/low None
46%
36%
18%
How frequently do you utilize Cruise
Control?
High Medium None
46%
36%
18%
How frequently do you utilize Cruise
Control?
High Medium None
46%
36%
18%
How frequently do you utilize Cruise
Control?
High Medium None
46%
36%
18%
How frequently do you utilize Cruise
Control?
High Medium None
47%
38%
14%
How frequently do you use Cruise
Control?
High Medium None
47%
38%
14%
How frequently do you use Cruise
Control?
High Medium None
63%
22%
15%
How frequently do you use Lane
Keeping Assist?
High Medium None
63%
22%
15%
How frequently do you use Lane
Keeping Assist?
High Medium None
Drivers who drive a vehicle with a manual transmission Drivers who drive a vehicle with an automatic transmission
80%
20%
Does utilizing Cruise Control contribute
to enhanced driving safety and/or
reduced driving stress?
High Low
94%
6%
Does utilizing Cruise Control contribute
to enhanced driving safety and/or
reduced driving stress?
High Low
83%
17%
Does utilizing Lane Keeping Assist
contribute to enhanced driving safety
and/or reduced driving stress?
High Low
89%
11%
Does utilizing Lane Keeping Assist
contribute to enhanced driving safety
and/or reduced driving stress?
High Low
86%
14%
Do the use of Cruise Control contribute
to enhanced road safety and/or
reduced driving stress?
High Low
86%
14%
Do the use of Cruise Control contribute
to enhanced road safety and/or
reduced driving stress?
High Low
87%
13%
Do the use of Lane Keeping Assist
contribute to enhanced road safety
and/or reduced driving stress?
High Low
87%
13%
Do the use of Lane Keeping Assist
contribute to enhanced road safety
and/or reduced driving stress?
High Low
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
485
Volume 19, 2023
4 Conclusion
Autonomous mobility, together with e-mobility
(e.g., [33], [34], [35]) and smart roads (e.g., [36],
[37], [38]), can significantly contribute to
sustainable mobility and decarbonization of the
transport sector. AVs offer an important opportunity
to advance sustainability goals and address current
and future challenges in the environmental
transition, as they have the potential to ensure a
reduction in pollutant emissions, both in terms of
greenhouse gas emissions and particulate matter,
reduce road accidents, alleviate traffic congestion,
and reduce fuel consumption.
The automation of vehicles occurs at different
levels depending on the balance between the role of
the driver and that of driving technologies that
support the guide. In the last five years, a massive
penetration into the market of advanced autonomous
functionalities have occurred. Their market
penetration is dependent on both technological
innovation and user acceptance, which is contingent
upon their willingness to utilize and trust this
emerging technology.
Starting from these considerations, the paper
investigated the users’ propensity to use self-driving
systems of SAE automation Levels 1 and 2.
Estimation results show that 41% of the respondents
currently have a Level 1 and/or 2 system on-board
their car: 54% have only the Cruise Control (Level 1
car), while 46% have both of them (Level 2 car).
Furthermore, about 85% of the respondent
frequently (medium-high) use the Cruise Control
and/or Lane Keeping Assist. More than 86% of the
drivers stated that these devices significantly
improve both on road safety and driving stress.
Finally, the highways are the roads where these self-
driving devices are mainly used (more than the 70%
of the times).
These results underline the relevant effort that
the automotive industry has performed in the last
decades to integrate advanced autonomous
functionalities on-board the vehicles. On this issue,
within the Italian market, in the last five years, an
increase of 209% of the car with SAE automation
Level 1 and 2 (Cruise Control and/or Lane Keeping
Assist) as standard equipment (not optional) was
observed.
Future perspectives will be to evaluate the
sustainability of self-driving mobility in terms of
possible market penetration scenarios through, for
example, cost-benefit or multi-criteria analysis (e.g.,
[39], [40]), also within rational transportation
planning decision-making processes (e.g., [41],
[42]).
References:
[1] European Commission, White paper:
roadmap to a single European transport
area-towards a competitive and resource
efficient transport system, COM, 2011, 144.
[2] Bagloee, S. A., Tavana, M., Asadi, M., &
Oliver, T., Autonomous vehicles: challenges,
opportunities, and future implications for
transportation policies. Journal of modern
transportation, 24, 2016, pp. 284-303.
[3] Morrison, G., and Van Belle, J. P., Customer
intentions towards autonomous vehicles in
South Africa: an extended UTAUT Model.
In 2020 10th International Conference on
Cloud Computing, Data Science &
Engineering (Confluence), IEEE, 2020, pp.
525-531.
[4] Akar, G., and Erhardt, G. D., User response
to autonomous vehicles and emerging
mobility systems. Transportation, 45, 2018,
pp. 1603-1605.
[5] Fagnant, D. J., and Kockelman, K. M.,
Dynamic ride-sharing and fleet sizing for a
system of shared autonomous vehicles in
Austin, Texas. Transportation, 45, 2018, pp.
143-158.
[6] Eugensson, A., Brännström, M., Frasher, D.,
Rothoff, M., Solyom, S., & Robertsson, A.,
Environmental, safety legal and societal
implications of autonomous driving systems.
In International Technical Conference on the
Enhanced Safety of Vehicles (ESV). Seoul,
South Korea, 2013, Vol. 334.
[7] Krueger, R., Rashidi, T. H., & Rose, J. M.,
Preferences for shared autonomous
vehicles. Transportation research part C:
emerging technologies, 69, 2016, pp. 343-
355.
[8] Harper, C. D., Hendrickson, C. T.,
Mangones, S., & Samaras, C., Estimating
potential increases in travel with autonomous
vehicles for the non-driving, elderly and
people with travel-restrictive medical
conditions. Transportation research part C:
emerging technologies, 72, 2016, pp. 1-9.
[9] N. H. T. S., Automated driving systems 2.0:
A vision for safety. Washington, DC: US
Department of Transportation, DOT
HS, 812, 2017, 442.
[10] Bennett, R., Vijaygopal, R., & Kottasz, R.,
Attitudes towards autonomous vehicles
among people with physical
disabilities. Transportation research part A:
policy and practice, 127, 2019, pp. 1-17.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
486
Volume 19, 2023
[11] Hwang, J., Li, W., Stough, L., Lee, C., &
Turnbull, K., A focus group study on the
potential of autonomous vehicles as a viable
transportation option: Perspectives from
people with disabilities and public transit
agencies. Transportation research part F:
traffic psychology and behaviour, 70, 2020,
pp. 260-274.
[12] Lee, Y. C., & Mirman, J. H., Parents’
perspectives on using autonomous vehicles
to enhance children’s
mobility. Transportation research part C:
emerging technologies, 96, 2018, pp. 415-
431.
[13] Bonnefon, J. F., Shariff, A., & Rahwan, I.,
The social dilemma of autonomous
vehicles. Science, 352(6293), 2016, pp.
1573-1576.
[14] Cascetta, E., Cartenì, A., Di Francesco, L.,
Do autonomous vehicles drive like humans?
A Turing approach and an application to
SAE automation Level 2 cars.
Transportation Research Part C: Emerging
Technologies, 2022, 134.
[15] European Transport Safety Council,
Prioritising the safety potential of automated
driving in Europe, 2016.
[16] Fagnant, D. J., & Kockelman, K., Preparing
a nation for autonomous vehicles:
opportunities, barriers and policy
recommendations. Transportation Research
Part A: Policy and Practice, 77, 2015, pp.
167-181.
[17] Shariff, A., Bonnefon, J. F., & Rahwan, I.,
Psychological roadblocks to the adoption of
self-driving vehicles. Nature Human
Behaviour, 1(10), 2017, pp. 694-696.
[18] Cartenì, A., The acceptability value of
autonomous vehicles: A quantitative analysis
of the willingness to pay for shared
autonomous vehicles (SAVs) mobility
services. Transportation Research
Interdisciplinary Perspectives, 8, 2020,
100224.
[19] Schoettle, B., and Sivak, M., Public opinion
about self-driving vehicles in China, India,
Japan, the US, the UK, and Australia.
University of Michigan, Ann Arbor,
Transportation Research Institute, 2014
[20] KPMG, 2013. Self-Driving Cars: Are we
ready? Retrieved from
<http://www.kpmg.com/US/en/IssuesAndIns
ights/ArticlesPublications/Documents/selfdri
ving-cars-are-we-ready.pdf>.
[21] Howard, D., & Dai, D., Public perceptions of
self-driving cars: The case of Berkeley,
California. In Transportation research board
93rd annual meeting, Washington, DC: The
National Academies of Sciences,
Engineering, and Medicine, 2014, Vol. 14,
No. 4502, pp. 1-16.
[22] Haboucha, C. J., Ishaq, R., & Shiftan, Y.,
User preferences regarding autonomous
vehicles. Transportation Research Part C:
Emerging Technologies, 78, 2017, pp. 37-49.
[23] SAE, 2014. On-Road Automated Vehicle
Standards Committee (Taxonomy and
Definitions for Terms Related to On-road
Motor Vehicle Automated Driving Systems).
[24] European Commission, Automated vehicles
in the EU, https://www.europarl.europa.eu
[25] Somalvico, Artificial Intelligence, Hewlett-
Packard, 1987
[26] European Parliament, what is artificial
intelligence and how is it used?,
https://www.europarl.europa.eu/
[27] European Road Safety Observatory, Road
Safety Thematic Report, Advanced driver
assistant system, December 2021
[28] American Automobile Association, 2017.
Americans Feel Unsafe Sharing the Road
With Fully Self-driving Vehicles. Retrieved
from. http://go.nature.com/2i296OW
[29] Begg, D. A 2050 vision for London: what are
the implications of driverless transport? 2014
[30] Payre, W., Cestac, J., & Delhomme, P.,
Intention to use a fully automated car:
Attitudes and a priori
acceptability. Transportation research part
F: traffic psychology and behaviour, 27,
2014, pp. 252-263.
[31] Cunningham, M. L., Ledger, S. A., & Regan,
M., A survey of public opinion on automated
vehicles in Australia and New Zealand.
In 28th ARRB International Conference
Next Generation Connectivity, Brisbane,
Queensland, 2018.
[32] Regan, M.A., Cunningham, M., Dixit, V.,
Horberry, T., Bender, A., Weeratunga, K.,
Cratchley, S., Dalwood, L., Muzorewa, D.,
Hassan, A., Preliminary Findings fromthe
First Australian National Survey of Public
Opinion about Automated and Driverless
Vehicles. Australian and New Zealand
Driverless Vehicle Initiative, Adelaide,
Australia (987-1-876592-85-1), 2017.
[33] Carteni, A., Henke, I. , Molitierno, C.,
Errico, A., Towards E-mobility: Strengths
and Weaknesses of Electric Vehicle;
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
487
Volume 19, 2023
Advances in Intelligent Systems and
Computing Volume 1150 AISC, Workshops
of the 34th International Conference on
Advanced Information Networking and
Applications, WAINA, 2020; Caserta, Italy;
pp. 1383-1393.
[34] Ruggieri, R., Ruggeri, M., Vinci, G., &
Poponi, S., Electric mobility in a smart city:
European overview. Energies, 14(2), 2021,
315.
[35] Babar, A. H. K., Ali, Y., & Khan, A. U.,
Moving toward green mobility: overview and
analysis of electric vehicle selection,
Pakistan a case in point. Environment,
Development and Sustainability, 23, 2021,
10994-11011.
[36] Henke I., Bifulco G.N., Carteni A., Di
Francesco L., Di Stasio A., A Smart Road
Application: The A2 Mediterranean
Highway Project in Italy. In Barolli L.,
Woungang I., Enokido T. (eds), 35th
International Conference on Advanced
Information Networking and Applications,
AINA, 2021. Lecture Notes in Networks and
Systems, 227, pp. 690 700.
[37] Zawieska, J., and Pieriegud, J., Smart city as
a tool for sustainable mobility and transport
decarbonisation. Transport policy, 63, 2018,
pp. 39-50.
[38] Torrisi, V., Ignaccolo, M., & Inturri, G.,
Innovative transport systems to promote
sustainable mobility: Developing the model
architecture of a traffic control and
supervisor system. In Computational Science
and Its ApplicationsICCSA 2018: 18th
International Conference, Melbourne, VIC,
Australia, July 25, 2018, Proceedings, Part
III 18, 2018, (pp. 622-638). Springer
International Publishing.
[39] Carteni’, A., Henke, I., Molitierno, C., A
cost-benefit analysis of the metro line 1 in
Naples, Italy; WSEAS Transactions on
Business and Economics, 15, 2018, pp. 529-
538.
[40] Cartenì A., Henke, I. Di Francesco L., A
sustainable evaluation processes for
investments in the transport sector: A
combined multi-criteria and costbenefit
analysis for a new highway in Italy.
Sustainability, Vol 12, Issue 23, 9854, 2020,
pp. 1-27.
[41] Cartenì, A., Marzano, V., Henke, I.,
Cascetta, E., A cognitive and participative
decision-making model for transportation
planning under different uncertainty levels.
Transport Policy, 116, 2022, pp. 386-398.
[42] Cartenì, A., Updating demand vectors using
traffic counts on congested networks: A real
case application, WIT Transactions on the
Built Environment 96, 2007, pp. 211-221.
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflict of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, Armando Carteni
E-ISSN: 2224-3496
488
Volume 19, 2023