Public Opinion on Automated Driving: Results of an International Questionnaire Among 5,000 Respondents

TL;DR: In this paper, the authors investigated user acceptance, worries, and willingness to buy partially, highly, and fully automated vehicles by means of a 63-question Internet-based survey, collected 5,000 responses from 109 countries (40 countries with at least 25 respondents).

Abstract: This study investigated user acceptance, worries, and willingness to buy partially, highly, and fully automated vehicles. By means of a 63-question Internet-based survey, we collected 5,000 responses from 109 countries (40 countries with at least 25 respondents). We determined cross-national differences, and assessed correlations with personal variables, such as age, gender, and personality traits as measured with a short version of the Big Five Inventory. Results showed that respondents, on average, found manual driving the most enjoyable mode of driving. Responses were diverse: 22% of the respondents did not want to pay more than $0 for a fully automated driving system, whereas 5% indicated they would be willing to pay more than $30,000 for it, and 33% indicated that fully automated driving would be highly enjoyable. 69% of respondents estimated that fully automated driving will reach a 50% market share between now and 2050. Respondents were found to be most concerned about software hacking/misuse, and were also concerned about legal issues and safety. More neurotic people were slightly less comfortable about data transmitting, whereas agreeable persons were slightly more comfortable with that. The more developed countries (in terms of accident statistics, education, and income) were less comfortable with their vehicle transmitting data, with cross-national correlations between ρ= -0.80 and ρ= -0.90. The present results indicate the major areas of promise and concern among the international public, and could be useful for vehicle developers and other stakeholders.

Summary

1. Introduction

• Road transport is an essential service in society, but the burden of traffic crashes and pollution is immense.
• In 2012, the US petroleum use for road transportation was about 11 million barrels per day, which corresponds to approximately 60% of the total US petroleum consumption (Davis, Diegel, & Boundy, 2014) .
• Current trends indicate that road traffic injuries will become the fifth leading cause of death by 2030, with the difference between high-and low-income countries further magnified (World Health Organization, 2013) .
• Automated driving systems have the potential to resolve these problems by increasing safety on public roads while decreasing traffic congestion, gas emissions, and fuel consumption (Anderson et al., 2014) .
• All three classifications start from the manual driving mode, where the driver executes all driving tasks, and each moves toward the fully automated driving mode, where no manual interaction is involved.

1.1. Previous surveys on automated driving

• The experts expressed the opinion that the ACC would be installed in 5% of the vehicles by 2004, while it would reach 50% of market penetration by 2015.
• The positive responses dropped to 20% after the respondents were informed about the estimated market price of $3000.
• Results of these two surveys were in close agreement with the original survey.

Levels of automation

• A survey carried out by Continental AG (Sommer, 2013) in Germany, China, Japan, and US pointed out that 59% of the respondents considered automated driving a useful advancement.
• Furthermore, the study suggested that half of the older respondents (aged 55+) believed that driverless technology is not important compared to under a third of the respondents between 16 and 24 years old.
• Casley et al. (2013) carried out a survey on the public opinion of fully automated vehicles among 467 students at Worcester Polytechnic Institute.
• 28% of the respondents indicated that the Level-3 automated vehicles will be commonplace on UK roads not earlier than 2040, while the number of those believed that this would never happen increased to 20%.
• A recent study by Schoettle and Sivak (2014a) investigated the public opinion (N = 1533) about autonomous and self-driving vehicles in the US, the UK, and Australia.

1.2. The aim of our survey study

• As described above, experts and the public are often positive about automated driving, but also exhibit essential concerns.
• The authors used the CrowdFlower crowdsourcing service, a tool which has been used for previous traffic psychology survey research as well (De Winter, Kyriakidis, Dodou, & Happee, 2015) .
• Third, since the previous survey studies on automated driving did not investigate how personality traits associate with the opinion of people on automated driving, this study explores associations with a well-known personality test, the Big Five Inventory (John & Srivastava, 1999) .

2.1. Survey

• A 63-question survey was created on http://www.crowdflower.com.
• The research was approved by the Human Research Ethics Committee (HREC) of the Delft University of Technology (TU Delft).
• The system cannot handle all possible situations.
• The system takes over speed and steering control completely and permanently, on all roads and in all situations.
• The survey asked for age, gender, driving frequency, mileage, accident involvement, and preferences/worries regarding manual driving, partially automated driving, highly automated driving, and fully automated driving.

2.2. CrowdFlower settings

• In the instructions, the respondents were informed that they would need approximately 15 min to complete the survey.
• The task expiration time was set at 60 min.
• In order to collect data from an as large and diverse as possible population, no requirements regarding the respondents' country of residence were set.
• Furthermore, the authors opted for 'Level 1 contributors', which is the lowest of the three available levels, accounting for 60% of CrowdFlower's monthly completed work.
• For the completion of the survey a payment of $0.30 was offered, and 5000 responses were collected.

2.3. Analyses at the individual level

• Descriptive statistics (i.e., means, medians, standard deviations, and frequencies) were calculated for each of the variables, as shown in the Supplementary Materials (Table S1 ).
• In turn, Spearman correlation coefficients were calculated (criterion for statistical significance at p < 0.001) between age, gender, mileage, driving frequency, computer use, education, income, accidents, disability, ACC use, and personality, on the one hand, and the level of enjoyment, comfort, willingness to pay, and worries about automated driving, on the other.

3.1. Number of respondents and respondent satisfaction

• In total, 5000 people completed the survey.
• CrowdFlower allows respondents to provide satisfaction ratings regarding the completed job.
• Table 2 shows that the respondents were generally satisfied with both the overall survey and its specifics.

3.2. Data filtering

• The respondents who did not indicate that they had read the instructions (N = 102) were excluded from the analyses.
• Those who indicated they were under 18 (N = 13), thereby not adhering to the survey instructions, were also excluded.
• In addition, one person whose responses were not stored correctly in the CrowdFlower database had to be discarded.
• Accordingly, 114 unique respondents were removed, leaving 4886 respondents for further analysis.
• An internal validity check revealed good correlation between self-reported age and self-reported birth date (Spearman's q = À0.99; after excluding 3 people who reported they were over 115 years old, and 49 people who reported they were born before 1900 or after 2010).

3.3. Analyses at the individual level: responses

• Descriptive statistics for the 4886 respondents are listed in Table S1 .
• Considering the large sample size, virtually all of the differences in means between pairs of questions were statistically significant.
• A majority of the respondents (2505 people, 51%) indicated that automated driving would be so advanced in 30 years that they would not even be allowed to drive manually (Q31).
• Privacy was their smallest concern, yet people were still quite concerned about it.
• The results reveal a substantial increase in the number of the people who would intend to rest/sleep, watch movies, or read, while driving in fully automated mode compared to the highly automated driving mode.

3.4. Correlational analyses at the individual level

• Table 3 summarises the correlation matrix of the variables.
• Neither clear age effects (Q7) nor gender effects (Q8) were identified (absolute correlation coefficients were mostly smaller than 0.10).
• These findings mirror the literature, as presented in the introduction.
• Additionally, the respondents who drive more (Q10, Q11) were also willing to pay more (Q42-45), for both their next vehicle and for automated driving vehicles.
• Nonetheless, it was found that respondents who scored higher on neuroticism were less comfortable with data transmitting (Q32-36), while respondents who scored higher on agreeableness were more comfortable with that, and believed that automation is less silly (Q30).

3.5. Correlational analyses at the national level

• The 4886 respondents were from 109 different countries.
• Overall, the developmental status of a country (either expressed in accident statistics, educational performance, or GDP per person) is predictive of various automation-related results (Table 4 ).
• There are no statistically significant relationships between the countries' income level and the respondents' willingness to pay for partially, highly, or fully automated vehicles (Q43-45).
• Further cross-national correlations indicate that in countries with higher educational performance and income, there were more female respondents (Q8) and respondents of greater age (Q7).
• A further validation of CrowdFlower results is obtained by the correlations between registered accidents and self-reported accidents (q = 0.54/0.52, Q22).

4. Discussion

• Various recent studies have documented the public opinion on automated driving technology.
• Specifically, the authors found that people who drive more, would be willing to pay more for automated vehicles.
• In conclusion, there appears to be a market for automated driving technologies, but one has to acknowledge that a part of the population is reluctant against such technology.
• That is, citizens of high-income countries may realistically believe that the threat of data misuse exists and is harmful for them.
• Other limitations of cross-national correlations include their relatively small sample size (only 40 countries with at least 25 of respondents per country) and possible non-independence of data points (e.g., adjacent countries may be similar and dependent on each other), according to which the notion of statistical significance can be misleading (Pollet, Tybur, Frankenhuis, & Rickard, 2014) .

Figures

Fig. 5. Number of respondents who indicated that they would engage in secondary tasks, for different driving modes (Q59–62). People could select multiple secondary tasks per question in a checkbox question.

Fig. 6. Number of respondents for the question: ‘‘In which year do you think that most cars will be able to drive fully automatically on the roads in your country?’’ (Q24). Years were divided into 5-year-wide bins.

Table 2 CrowdFlower respondents satisfaction ratings completed by a subset of respondents (N = 2861).

Fig. 4. Number of responses regarding the question how much money (in US $) people were willing to pay for automated driving technology installed in their next vehicle, on top of the base price of that vehicle (Q43–45).

Fig. 3. Mean response on a scale from 1 = Disagree strongly to 5 = Agree strongly regarding respondents worries about fully automated driving (Q37–41).

Fig. 7. National average in comfort in transmitting data to tax authorities (Q36) vs. gross domestic product (GDP) per purchasing power parities (PPP).

Table 4 Spearman correlation matrix at the national level (N = 40 countries; correlations were multiplied by 100).

Fig. 1. Number of respondents regarding the statement that driving is/would be enjoyable, per response option and per driving mode (Q16–19).

Table 1 Alignment among BASt, NHTSA and SAE levels of automation (Smith, 2013b; Wending, 2014).

Table 3 Spearman correlation matrix at the individual level (N = 4886; correlations were multiplied by 100).

Fig. 2. Mean response on a scale from 1 = Disagree strongly to 5 = Agree strongly, regarding respondents’ comfort in transmitting data to automotive stakeholders (Q33–36).

Full text

Delft University of Technology
Public opinion on automated driving
Results of an international questionnaire among 5000 respondents
Kyriakidis, M; Happee, R; de Winter, JCF
DOI
10.1016/j.trf.2015.04.014
Publication date
2015
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Final published version
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Transportation Research. Part F: Traffic Psychology and Behaviour
Citation (APA)
Kyriakidis, M., Happee, R., & de Winter, JCF. (2015). Public opinion on automated driving: Results of an
international questionnaire among 5000 respondents.
Transportation Research. Part F: Traffic Psychology
and Behaviour
,
32
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Public opinion on automated driving: Results of an international
questionnaire among 5000 respondents
M. Kyriakidis
⇑
, R. Happee, J.C.F. de Winter
Department Biomechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands
article info
Article history:
Received 22 September 2014
Received in revised form 29 January 2015
Accepted 30 April 2015
Available online 15 June 2015
Keywords:
Driverless car
Questionnaire
Personality traits
Cross-national differences
Intent to purchase
abstract
This study investigated user acceptance, concerns, and willingness to buy partially, highly,
and fully automated vehicles. By means of a 63-question Internet-based survey, we col-
lected 5000 responses from 109 countries (40 countries with at least 25 respondents).
We determined cross-national differences, and assessed correlations with personal vari-
ables, such as age, gender, and personality traits as measured with a short version of the
Big Five Inventory. Results showed that respondents, on average, found manual driving
the most enjoyable mode of driving. Responses were diverse: 22% of the respondents did
not want to pay more than $0 for a fully automated driving system, whereas 5% indicated
they would be willing to pay more than $30,000, and 33% indicated that fully automated
driving would be highly enjoyable. 69% of respondents estimated that fully automated
driving will reach a 50% market share between now and 2050. Respondents were found
to be most concerned about software hacking/misuse, and were also concerned about legal
issues and safety. Respondents scoring higher on neuroticism were slightly less comfort-
able about data transmitting, whereas respondents scoring higher on agreeableness were
slightly more comfortable with this. Respondents from more developed countries (in terms
of lower accident statistics, higher education, and higher income) were less comfortable
with their vehicle transmitting data, with cross-national correlations between
q
= 0.80
and
q
= 0.90. The present results indicate the major areas of promise and concern among
the international public, and could be useful for vehicle developers and other stakeholders.
Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction
Road transport is an essential service in society, but the burden of traffic crashes and pollution is immense. US data show
that automobile crashes led to 34,080 fatalities in 2012 (NHTSA, 2013a), where about 90% of the cases were attributed at
least in part to driver error (Smith, 2013a). In 2012, the US petroleum use for road transportation was about 11 million bar-
rels per day, which corresponds to approximately 60% of the total US petroleum consumption (Davis, Diegel, & Boundy,
2014). Moreover, the average commuter gets delayed 38 h per year due to traffic congestion (Schrank, Eisele, & Lomax,
2012). European data (European Commission, 2014) show that more than 28,000 people died on EU roads in 2012, and that
four times as many people were permanently disabled. The fatality rates in high-income countries have been declining for
the past decades, but the fatality rates in the low- and middle-income countries are actually increasing (World Health
http://dx.doi.org/10.1016/j.trf.2015.04.014
1369-8478/Ó 2015 Elsevier Ltd. All rights reserved.
⇑
Corresponding author. Tel.: +31 15 27 83573.
E-mail address: m.kyriakidis@tudelft.nl (M. Kyriakidis).
Transportation Research Part F 32 (2015) 127–140
Contents lists available at ScienceDirect
Transportation Research Part F
journal homepage: www.elsevier.com/locate/trf

Organization, 2013). Current trends indicate that road traffic injuries will become the fifth leading cause of death by 2030,
with the difference between high- and low-income countries further magnified (World Health Organization, 2013).
Automated driving systems have the potential to resolve these problems by increasing safety on public roads while
decreasing traffic congestion, gas emissions, and fuel consumption (Anderson et al., 2014). Different levels of automation
have been proposed with different definitions of the technological capabilities and human involvement. The most
well-known are provided by BASt (Gasser & Westhoff, 2012), National Highway Traffic Safety Administration (NHTSA,
2013b) and SAE (On-Road Automated Vehicle Standards Committee, 2014), as shown in Table 1.
All three classifications start from the manual driving mode, where the driver executes all driving tasks, and each moves
toward the fully automated driving mode, where no manual interaction is involved. In theory, fully automated driving
(assuming ‘‘perfect’’ sensing of the environment, ‘‘perfect’’ decision-making algorithms, and ‘‘perfect’’ actuators) is the opti-
mal solution in terms of safety, congestion, and emissions.
While automated driving systems have great potential to improve safety and efficiency of road transportation, many chal-
lenges have yet to be addressed, including the public perception, legal liability issues, and the security and control of the
systems (Howard & Dai, 2014). The public opinion on automated driving determines the extent to which people will accept
and purchase such systems, and it will define the way that car manufacturers will have to develop and market automated
vehicles, as well as the necessary tax and insurance policies, and any investments in infrastructure.
1.1. Previous surveys on automated driving
Various researchers have previously conducted surveys on automated driving systems (Begg, 2014; Casley, Jardim, &
Quartulli, 2013; Howard & Dai, 2014; KPMG., 2013; Payre, Cestac, & Delhomme, 2014; Power, 2012; Power, 2013;
Schoettle & Sivak, 2014a, 2014b; Sommer, 2013). An early study by Underwood (1992) explored which intelligent vehicle
technology would likely be deployed in North America. Results among 55 experts in the field indicated that, among the listed
control systems, adaptive cruise control (ACC) would be the most popular feature. The experts expressed the opinion that the
ACC would be installed in 5% of the vehicles by 2004, while it would reach 50% of market penetration by 2015. Automated
braking would follow with a lag of 6 to 10 years, while lane-keeping assist would be introduced at an even later date. In addi-
tion, it was projected that by 2002 both frontal collision warning systems and back-up warning systems (e.g., blind spot
detection) would reach 5% market penetration. Comparing those predictions with today’s status, it can be claimed that
the predictions were fairly accurate: ACC has been introduced in 1995 and is now available as an option by most car man-
ufacturers (yet it has not reached the predicted 50% market share; Kyriakidis, van de Weijer, van Arem, & Happee, 2015).
Advanced Emergency Braking (AEB), Forward Collision Warning Systems (FCWS) and Lane Keeping Systems (LKS) are also
currently available on the market. Underwood (1992) found that the experts also believed that fully automated driving (‘‘au-
tomatic chauffeuring with auto lane changing & merging’’) would achieve a 5% market share only between 2040 and 2075,
and would never achieve a 50% market share.
Also before the turn of the twenty-first century, Bekiaris et al. (1996) studied user needs and their acceptance of techno-
logical systems that could assist drivers who are in an impaired state. A questionnaire was distributed to 407 people in nine
European countries, and results showed that although most users would welcome being warned by a supportive assistance
system, they expressed ‘‘a definite rejection of automatic driving’’.
Recent studies (Begg, 2014; Casley et al., 2013; Howard & Dai, 2014; KPMG, 2013; Missel, 2014; Payre et al., 2014; Power,
2012; Power, 2013; Schoettle & Sivak, 2014a, 2014b; Sommer, 2013; Youngs, 2014) display a somewhat more positive pic-
ture of the public opinion on fully automated driving. Nevertheless, people also indicate a non-negligible level of reluctance.
Specifically, the global market research company Power and Associates have recently conducted various surveys on the will-
ingness of US vehicle owners to purchase automotive emerging technologies. Their first study (Power, 2012), conducted in
March 2012, surveyed 17,400 vehicle owners regarding their intention to purchase an autonomous driving mode, defined as
‘‘a feature that allows the vehicle to take control of acceleration, braking and steering, without any human interaction’’. 37%
of the respondents answered that they ‘‘would definitely’’ or ‘‘would probably’’ be interested in purchasing such technology.
However, the positive responses dropped to 20% after the respondents were informed about the estimated market price of
$3000. The study also revealed that those vehicle owners with the highest interest in fully autonomous driving at market
price were males (25%), those between the ages of 18 and 37 (30%), and those living in urban areas (30%). The second
Table 1
Alignment among BASt, NHTSA and SAE levels of automation (Smith, 2013b; Wending, 2014).
Source Levels of automation
BASt Driver only Assisted Partly automated Highly automated Fully automated Not addressed
NHTSA No Automation
(Level 0)
Function-Specific
Automation (Level 1)
Combined Function
Automation (Level 2)
Limited Self-Driving
Automation (Level 3)
Full Self-Driving Automation
(Level 4)
SAE No Automation
(Level 0)
Driver Assistance
(Level 1)
Partial Automation
(Level 2)
Conditional Automation
(Level 3)
High
Automation
(Level 4)
Full
Automation
(Level 5)
128 M. Kyriakidis et al. / Transportation Research Part F 32 (2015) 127–140

and third studies were conducted in March 2013 (Power, 2013) and March 2014 (Youngs, 2014) respectively, both with over
15,000 respondents. Results of these two surveys were in close agreement with the original survey.
A survey carried out by Continental AG (Sommer, 2013) in Germany, China, Japan, and US pointed out that 59% of the
respondents considered automated driving a useful advancement. However, respondents were rather scared about driving
in an automated vehicle: 31% of the respondents stated that they are unnerved by the development of automated vehicles,
and 54% claimed that they do not believe that such vehicles will function reliably. The results by Continental AG also suggest
that the concept of automated driving is not equally known in all countries. Specifically, people in Germany (67%) and China
(64%) were more aware of automated driving developments compared to those in Japan (29%). About 40% of the respondents
expected automated vehicles to be on public roads within the next 10 to 15 years, while most of the respondents expressed
the intention to use such technology more on long freeway journeys (67%) and in traffic jams (52%), and less on rural roads
(36%) and in city traffic (34%).
Ipsos MORI (Missel, 2014) recently published the results of their study on peoples’ opinion on the importance of driver-
less cars for the car industry. The study was conducted in June 2014 among 1001 British people between 16 and 75 years old.
The results showed that only 18% of the British public found it important that car manufacturers focus on driverless tech-
nologies, whereas 41% found this unimportant. The study also explored the public opinion in relation to the gender and
age of the respondents. Findings showed that men are more likely to deem driverless vehicles important than women
(23% of men vs. 13% of women). Nearly half of the women (47%) found driverless vehicles unimportant compared to just over
a third (36%) of men. Furthermore, the study suggested that half of the older respondents (aged 55+) believed that driverless
technology is not important compared to under a third of the respondents between 16 and 24 years old. Results also indi-
cated that people who live in congested cities (e.g., London) found automated driving technology more important than those
who live in a non-urban environment.
In June 2013, the advisory services company KPMG (2013) carried out a 10 focus-group study with 32 people from Los
Angeles (CA), Chicago (IL), and Iselin (NJ). All participants were at least 21 years of age and owned at least one vehicle,
and all had completed high school and college or vocational school. Results showed that women (median = 8.5 on a scale
from 1 to 10) were more willing to use self-driving vehicles than men (median 7.5), while Californians were more open
(median = 9) to such vehicles than others (Chicago median = 4; Iselin median = 6). The KPMG report also showed that the
public opinion on automated driving cars is different from that of regular cars, where the discussion topics for fully auto-
mated cars are more on handling, safety, innovation, and trust and less on the engine, transmission, and styling.
Howard and Dai (2014) explored peoples’ (N = 107) opinion on self-driving cars in Berkeley (CA) using a questionnaire
and a video. Results showed that safety (75%) and convenience (61%) were the most attractive features about automated
driving, whereas 70% and 69% of the respondents indicated liability and cost respectively, as the least attractive elements.
In addition, 46% of the respondents believed that self-driving cars should operate with normal traffic, 38% in separate lanes,
while 11% expressed no opinion. More than 40% of the respondents were positive to either purchasing self-driving technol-
ogy in their next vehicle or equipping their current vehicle with such technology. Finally, 35% of the respondents were in
favor of a subsidized scheme for self-driving cars, whereas 22% expressed being against it.
Casley et al. (2013) carried out a survey on the public opinion of fully automated vehicles among 467 students at
Worcester Polytechnic Institute. When the students were asked to rank the most influential feature determining their desir-
ability of fully automated vehicles, 82% choose safety, 12% legislation and 7% cost. In addition, although most of the students
(40%) expected that a fully automated car would cost $5000–9999 on top of a regular car, more than 71% would not be will-
ing to spend more than $4999 to purchase it. Casley et al. (2013) showed that about 58% of people were not familiar with
current laws regarding the testing and operation of automated cars. Nonetheless, a large share of respondents (57%)
expressed concern about legislation. Finally, men were more likely to adopt and enjoy self-driving cars than women.
Begg (2014), conducted a survey of London transport professionals to ascertain their perceptions of whether, and how
soon, they expected driverless transport to become a reality. The study targeted over 3500 people, incorporating a broad
cross-section of transport experts. The key findings indicated that about 35% of the respondents believed that Level-2 auto-
mated vehicles (resembling the NHTSA definition) will be commonplace on UK roads by 2025, while 10% believed that this
would never happen. 28% of the respondents indicated that the Level-3 automated vehicles will be commonplace on UK
roads not earlier than 2040, while the number of those believed that this would never happen increased to 20%. In addition,
20% of the respondents believed that the Level-4 automated vehicles would be commonplace on UK roads by 2040, while
30% expressed the belief that this would never be the case. Finally, the respondents were asked to indicate their opinion
regarding the increase in safety of all road users due to automated vehicles. Results revealed that 36% and 24% of respondents
agreed and strongly agreed, respectively, that automated vehicles would improve safety for all road users.
A recent study by Schoettle and Sivak (2014a) investigated the public opinion (N = 1533) about autonomous and
self-driving vehicles in the US, the UK, and Australia. The study showed that 60–70% of people had heard of autonomous
or self-driving vehicles before, while 57% of the respondents had an overall positive (on a 5-point Likert scale from ‘‘very
negative’’ to ‘‘very positive’’) opinion on those vehicles. The main expected benefits of self-driving vehicles included crash
reduction (70% of responses), reduction of emissions (64%), and reduced fuel consumption (72%). People did not seem to
believe that such technology would improve traffic congestion (48%) and travel time (43%). A large number of respondents
expressed concerns about the technology of self-driving vehicles. In particular, 26% of the US respondents were ‘‘very con-
cerned’’ about system/equipment failure and vehicle performance in unexpected situations, while the corresponding per-
centages for UK and Australia were 15% and 16% respectively. However, this number increased to 75% for all the
M. Kyriakidis et al. / Transportation Research Part F 32 (2015) 127–140
129

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Public opinion on automated driving: results of an international questionnaire among 5000 respondents" ?

In this paper, different levels of automation have been proposed with different definitions of the technological capabilities and human involvement. 

Q2. What were the main expected benefits of self-driving vehicles?

The main expected benefits of self-driving vehicles included crash reduction (70% of responses), reduction of emissions (64%), and reduced fuel consumption (72%). 

Q3. How many responses could be included in the statistical analyses?

The authors implemented a 63-question survey via the CrowdFlower crowdsourcing service, and the authors collected 5000 responses, 4886 of which could be included in their statistical analyses. 

Q4. How many people were concerned about the safety of self-driving vehicles?

In particular, 26% of the US respondents were ‘‘very concerned’’ about system/equipment failure and vehicle performance in unexpected situations, while the corresponding percentages for UK and Australia were 15% and 16% respectively. 

Q5. What is the role of automated driving systems in solving traffic accidents?

Automated driving systems have the potential to resolve these problems by increasing safety on public roads while decreasing traffic congestion, gas emissions, and fuel consumption (Anderson et al., 2014). 

Q6. How many people were positive to self-driving cars?

More than 40% of the respondents were positive to either purchasing self-driving technology in their next vehicle or equipping their current vehicle with such technology. 

Q7. How many people believed that the Level-3 would never happen?

28% of the respondents indicated that the Level-3 automated vehicles will be commonplace on UK roads not earlier than 2040, while the number of those believed that this would never happen increased to 20%. 

Q8. How many respondents would be willing to pay more than $30,000 for fully automated driving?

240 respondents (4.9%) indicated they would be willing to pay more than $30,000 for fully automated driving, compared to only 117 and 154 respondents for partially and highly automated driving, respectively. 

Q9. What was the first study to examine the use of autonomous driving?

Their first study (Power, 2012), conducted in March 2012, surveyed 17,400 vehicle owners regarding their intention to purchase an autonomous driving mode, defined as ‘‘a feature that allows the vehicle to take control of acceleration, braking and steering, without any human interaction’’. 37% of the respondents answered that they ‘‘would definitely’’ or ‘‘would probably’’ be interested in purchasing such technology. 

Q10. How many Chinese and Indian respondents expressed interest in self-driving vehicles?

a large number of Chinese and Indian respondents (76% and 80% respectively) expressed interest in acquiring such technology on their personal vehicles, compared to only 41% of the Japanese respondents. 

Q11. How many people agreed that self-driving vehicles would improve safety for all road users?

Results revealed that 36% and 24% of respondents agreed and strongly agreed, respectively, that automated vehicles would improve safety for all road users. 

Q12. What are the limitations of cross-national correlations?

Other limitations of cross-national correlations include their relatively small sample size (only 40 countries with at least 25 of respondents per country) and possible non-independence of data points (e.g., adjacent countries may be similarand dependent on each other), according to which the notion of statistical significance can be misleading (Pollet, Tybur, Frankenhuis, & Rickard, 2014). 

Q13. How much would the population be willing to pay for a fully automated car?

At the same time, there is a fair part of the population who will enjoy fully automated driving, and about 5% would be willing to pay even more than $30,000 to purchase it. 

Q14. How many people believe fully automated driving will reach a 50% market share?

In conclusion, their survey showed that 69% of people believe that fully automated driving will reach a 50% market share between now and 2050 (cf. Fig. 6).