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Proceedings of the Eastern Asia Society for Transportation Studies, Vol.12,2019
Autonomous Vehicle as a Future Mode of Transport in India: Analyzing the
Perception, Opportunities and Hurdles
Arnab JANA a, Ahana SARKAR b, Jagannath Venkobarao KALLAKURCHI c,
Satish KUMAR d
a,b,c Centre for Urban Science and Engineering, Indian Institute of Technology
Bombay, 400076
a E-mail: arnab.jana@iitb.ac.in
b E-mail: ahana.sarkar@iitb.ac.in
c E-mail: 184424001@iitb.ac.in
d Department of Humanities and Social Sciences, Indian Institute of Technology
Bombay, 400076
d E-mail: 178080008@iitb.ac.in
Abstract: This empirical research investigates into perception of Autonomous Vehicles’
(AV) acceptance among forth-coming probable users in India. Multinomial Logistic
regression (MNL) and exploratory analysis were undertaken to interpret the users’ degree of
interest regarding AVs in relation to socio-economic variables like users’ education and
employment standards and other variables like cost and expenses incurred, overall safety
issues, obstacles and benefits concerning AV. 91.1percent respondents had knowledge of AV
but 50 percent expressed concern regarding AVs’ reliability and 40percent showed interest in
AVs. MNL results highlighted that expressing high order of interest towards AV increases
with education and employment standards. Respondents expressing higher concern for AVs
reliability, had the maximum probability of exhibiting least interest in adopting AV majorly
due to dearth of consumer readiness and fear of accepting advanced technology. This study
can aid in adding new layers to the epistemology of the emerging field of AV in Indian
scenario.
Keywords: Autonomous Vehicles, User perception, Challenges and benefits, Safety concern,
Interest
1. INTRODUCTION
World has witnessed a rapid advancement in autonomous technology integrated with artificial
intelligence based approaches which has further boosted self-driving vehicles to arrive at the
forefront of public interest. The Autonomous Vehicle (AV) also connoted as ‘self-driving’ or
‘automated’ vehicle, a recent advancement in automotive industry can steer driver less in all
predetermined situations. AVs have gained importance since 2010s when several countries
allowed the use of these vehicles in road traffic. Several car manufacturers like NVidia, Audi,
Ford, BMW and Volvo would be launching high level automated vehicles or even Level 4
AVs by 2021 (Liljamo, Liimatainen, & Pöllänen, 2018).
In 2004, Defense Advanced Research Projects Agency’s (DARPA), US great challenge
was launched with the intention of elucidating the viability of autonomous technology by
traversing approximately 150 miles path. Subsequently, with the launching of self-driving car
Corresponding author.
in 2007, Google successfully performed a 14 miles on-road test of their AVs in 2012. Till
April 2014, Google’s self-driving cars have traversed more than 700,000 miles in California,
Texas, Washington, Arizona in US in collaboration with well-established car manufacturing
enterprises like Audi, BMW, Ford, GM, Nissan, Toyota etc. (Fagnant & Kockelman, 2015).
Other internationally recognized auto manufacturers have scheduled to emerge with varying
types of AVs like Ford and BMW by 2021 and Daimler trucks by 2025. According to Victoria
Transport Policy, world will experience the emergence of AVs at a mass-scale by 2045s. On
the same note, Europe’s CityMobil2 project is lately testing low speed AV application in five
cities (Fagnant & Kockelman, 2015).
With National Highway Traffic Safety Administration (NHTSA) releasing the initial
policies and guidelines on AVs in 2015, 33 states in US have come up with AV related
legislations (X. Xu & Fan, 2018). California, Michigan, Washington DC, Florida, and Nevada
have ratified notices and bills to control AV licensing and operation. Especially, California has
already directed its department of motor vehicles (DMV) to provide AV certification
requirements by 2015 (Fagnant & Kockelman, 2015).
AVs are expected to deliver notable benefits to the transportation system, including enhanced
traffic safety and efficiency by avoiding deadly crashes, offering hassle less mobility to young,
elderly and disabled, increasing road capacity, reducing fuel consumption and trimming down
carbon emissions (Liljamo et al., 2018). Moreover adoption of automotive technology in
car-sharing system would change the notion of vehicles from an owned product to an
on-demand service. Other possible sectors where AV would impact include parking services,
parking demands, infrastructure and operational cost modification, freight transportation
systems, land use patterns etc.
However, the process of advancement of AV technology has not been smooth till date.
Previously several significant innovations have collapsed immediately after their market
launch owing to failure in achieving user requirements and satisfaction. Apart from
technological challenges, the major impediment in new technology innovations includes
psychological concerns such as negative user perception and lack of acceptance towards
contemporary concepts. Recently a significant amount of research has showcased users’
perception towards acceptance of autonomous vehicle technology from different countries (Z.
Xu et al., 2018). Studies conducted on people’s attitude towards AVs elucidate how they
accept the new technology and how equipped they would be to begin adopting them
(Kyriakidis, Happee, & De Winter, 2015). Jourdes, Mol, Cedex, & Appliqu, (2018) predicted
that by 2050s, automated driving will be comprised as a typical feature of forthcoming
vehicles and AVs would comprise of 50-80 percent of vehicle travels and 40-60 percent of
vehicle fleets. Bansal & Kockelman, (2017) concluded that AVs would be adopted by
24.8-87.2 percent of vehicle fleets by 2045. Market penetration of AV technology was also
estimated by Nieuwenhuijsen, Correia, Milakis, van Arem, & van Daalen, (2018). Previous
studies mostly comprise of online surveys with non-representative samples (Becker &
Axhausen, 2017). Peoples’ attitude towards implementing an advanced technology without
any uncertainties and skepticism influence how fast a technology will be accepted and how
well the possible benefits from AVs can be recognized (Hemant & Regina, 2007).
In developing nations like India, maximum population suffer from unemployment, poor
education access, inferior environmental conditions and mass death-toll owing to road crashes.
Hence, in this context queries might upsurge about the challenges entrenched in peoples’ mind,
their behaviorism and skepticism regarding AVs’ safety issues and finally whether driverless
vehicles would create or displace jobs. The novelty of this study lies in exploring peoples’
attitude towards AV and their concerns regarding challenges of AV technology in Indian
scenario with a special focus on forward section of the society. According to Roger Everett’s
classic model, the ‘Diffusion of Innovations’, among the five categories of Innovators, Early
Adopters, Early Majority, late Majority and Laggards, the Early Adopters adopt the
technology faster (Sullivan, 2015). Because the forward section of the society with high
positions and managerial skills possess the unique characteristic of technological fluency, or
because they harbor positive views towards cutting-edge AV technology, we hypothesize that
the respondents considered in this survey will be within the early adopters (Woldeamanuel &
Nguyen, 2018). This study, through adoption of online survey, objectively intends to analyze
the peoples’ mindset, attitudes as well as impressions on smart car technologies and strategies.
Owing to lack of adequate literature regarding AV technology emergence in India and its
acknowledgement, this study would be of its initial kind to probe into the forward-section
user perception towards AVs in Indian scenario.
2. LITERATURE REVIEW
2.1 Potential Benefits and Applications of Autonomous Vehicles
The perceived efficacy, reliability, ease of use and cost of a technology, as well as general
attitudes towards it, are emphasized as significant factors in models elucidating how new
technologies become more conventional (Hemant & Regina, 2007). AVs, inherently different
from human-driven vehicles have certain unique potential factors to be considered which
include smooth functioning, reliability of vehicle related services, cost of technology etc.
(Fagnant & Kockelman, 2015).
AV technology is heralded for several positive and negative effects across multiple
sectors. AVs can be proved effective in reducing on road traffic crashes specifically owing to
human related causes (Woldeamanuel & Nguyen, 2018). NHTSA has reported driver error to
be the foremost reason behind 90 percent of road crashes (NHTSA, 2008). Over 40 percent of
the fatal crashes involve reasons like alcohol consumption, distraction, drug involvement and
fatigue other than inattention, distraction, or speeding caused by drivers. Adeel, Frank, & Ify,
(2014) had predicted a possible reduction of around 1.86 million less injurious crashes,
including up to 27,000 less fatalities per year with advent of AV technology. While driver less
AVs can reduce the chances of crashes owing to driver error, the challenges regarding AVs’
performance in a safe environment cannot be ignored or eradicated completely at this moment.
Designing a system for AV, with object recognition power on the road is critical. Different
objects with varying activity recognition make the AV sensor complex with advanced artificial
intelligence strategies. However, AVs often connoted as ‘crash-less cars’ would prove safer in
future with forthcoming advanced sensor installation.
Experts predict that AVs also have huge impact over traffic congestion (Silberg, 2012).
AV’s ability of sensing and anticipating lead vehicles’ braking and other decisions makes it
also efficient in reducing fuel consumption as well. AVs with advanced braking and speed
regulating technologies lead to fuel savings, and reductions in traffic-destabilizing shockwave
propagation of platooning vehicles (Sullivan, 2015). Profound use of existing lanes and
efficient intersections, coordinated platoons, and route choices are some of the estimated
benefits of AVs. Research cites that AVs’ advantages like congestion reduction, lesser fuel
consumption and improved safety concerns would also impact travel behavior. Furthermore,
driver-less AVs can be utilized by youngsters as well as elderly and differently abled.
Other benefits include smart parking decisions like self-parking capabilities in less
expensive zones and independence and mobility, avoiding human-driven physical limitations
like unfamiliar roads, night-time driving, poor weather, heavy traffic etc. Delays during peak
period can also be reduced with advent of AV by introducing smart routing coupled with
advanced infrastructure, quicker reaction times, and closer spacing between vehicles to
counter increased demand.
Moreover, efficiency in use of travel time while riding in AVs might encourage people
to shift their home locations to more remote areas and enjoy lower land prices, and bigger
properties. Paradoxically, urban core may turn even denser with the integration of AV
technology (Anderson et al., 2016). With major land shifts being the key constraints, studies
have also explored the residential shifts as motivated by AV access (Bansal, Kockelman, &
Singh, 2016).
Thus, AVs once extensive are likely to deduct human errors, optimize traffic flow, and
enhance safety and experience of on-road travelers by enabling enhanced communication with
other vehicles, infrastructure and pedestrians. Literature cites increased safety and fuel
efficiency (Adeel et al., 2014), reduced travel time, decreased needs for right-of-way,
independent mobility, increased efficiency through multitasking, lower private vehicle
ownership, less traffic congestion and lower insurance rates as key benefits of AV technology.
Berry (2010) had estimated that AVs would reduce 20-30percent acceleration and deceleration
rates which would further reduce 5percent fuel consumption. Researchers have also identified
lesser stress levels and increased productivity as potential benefits of AVs.
Semi-autonomous features such as adaptive cruise control, lane departure cautions,
parking support arrangements, crash evading technologies, and on-board navigation are now
commercially available in market. Furthermore, AVs have a wide range application in fields
of military, mining and agricultural sectors.
2.2 Challenges Regarding AVs
AVs are also assumed to harbor complex negative externalities, along with predicted benefits
(Woldeamanuel & Nguyen, 2018). Although AVs play a significant role in delivering safety of
transportation systems, they would face safety and security challenges as well. Uncertainty
prevails regarding the proper functioning of AV technology in its infancy with our existing
technological capabilities (Sullivan, 2015). In a catastrophic event or on failure of single
component of AV, the whole in-vehicle network might get disrupted. In other cases, if the
on-board computer system executes a wrong command, the traffic safety and passengers’ life
would be compromised. Failure or tampering of Global Position System (GPS) data would
affect the AV localization and might lead to traffic disturbance or crash hazard. The disruption
in connection through exchange of wrong information and miscommunication with nearby
AVs would also degrade the traffic situation and lead to hazardous crashes. Thus, adequate
safety and security countermeasures need to be implemented to mitigate failure attacks.
Furthermore, other than the technological issues, economical barriers stand up as major
hurdles in the way of proliferation of autonomous vehicles (Howard & Dai, 2013). High
manufacturing and operational costs might hinder mass-production and would not be
consumer friendly.
Other challenges regarding AV technology involves privacy and passenger safety
concerns, insurance regulations, licensing features, cyber security and legal and liability
issues and ethical and hacking issues. Gaps still persist in AV legislation and provision of
federal guidance to partial or full AVs for testing purpose on public roads.
2.3 User Behaviorism towards Autonomous Vehicles
People’s mind-set and attitudes exert a strong influence on how quickly a new technology is
adopted, thus also affecting how well the benefits incurred from AVs can be realized. A public
opinion based survey was conducted in China, India, Japan, the USA, the UK and Australia
on people’s perception towards AV taking approximately 500 samples per country. The survey
results indicated that people in China and India exhibited high interest towards automated
vehicles, with 85percent respondents delivering positive attitude. Japan observed 50percent
respondents with neutral views towards AVs. However, 16 percent respondents from USA
showed negative or somewhat negative attitude towards AVs (Schoettle & Sivak, 2014).
Another exhaustive online survey was conducted on the general opinion about autonomous
vehicles taking over 5000 samples from 109 countries worldwide (Kyriakidis et al., 2015).
The finding suggested that the primary apprehensions of the respondents were cyber security,
traffic safety, privacy issues and legal aspects. The overall survey clarified mixed reviews on
AV with some respondents expressing positively towards AV, while others were not willing to
pay for it and did not view AV to be enough assuring. Passenger data sharing with traffic and
insurance authorities were other reasons behind the dislike towards AV working principles.
An US based study proposed and validated a questionnaire based framework for
evaluating pedestrian receptivity towards AVs using safety, interaction and compatibility as
major surrogate measures. Gender was found to be a dominant factor with male showing
greater perception of safety towards AVs. Younger generation was found to be more interested
in interacting with AVs in traffic environment (Kyriakidis et al., 2015). Overall, the survey
results indicated that people showing positive behavior believed that AV’s introduction would
vehemently improve traffic safety. Several public opinion based research conducted in US has
focused on aspects like beliefs, confidence level, adoption decisions and benefits and
concerns related to attributes of AVs.
A survey based study from China investigated the risk perceptions of AVs to reveal that
AVs had highly positive impression in China and that 42.35percent of respondents expect
lower risk for AVs (X. Xu & Fan, 2018). Another survey conducted over vehicle owners in
Seoul, South Korea demonstrated that perceived usefulness and trust are the major
determinants of intention to use AVs (Choi & Ji, 2015). The study also concluded that system
transparency, situation management and technical competence have a positive effect on trust.
The major factors that affect the AV acceptance are driver related personality traits like locus
of control. Liu, Yang, & Xu, (2018) had conducted an interview of 452 individuals to assess
the acceptance, willingness-to-pay and intention to use AVs. The results indicated that social
trust has a direct effect on behavioral intention and willingness-to-pay. Jiang, Zhang, Wang, &
Wang, (2018) had conducted a study in Japan over 1000 samples to explore the ownership
behavior due to emergence of AVs. It was observed that respondents are willing to pay an
excess of 4-8, 00,000 JPY for buying AVs in future.
Public opinion based literature has also established men to express more interest
towards AV technology and usage than that of women (Alessandrini, Alfonsi, Site, & Stam,
2014). Furthermore, similar studies have noted that men with high education level, higher
income and those residing in compact metropolitan cities and those living in households
without a car had a tendency of showing keen interest towards AV than others (Bansal et al.,
2016, Liljamo et al., 2018). Additionally, younger generation was observed to have higher
preferences towards AV than older people (Kyriakidis et al., 2015). Few literature have
revealed distrust towards AV, loss of self-belonging and attachment towards own vehicle and
pleasure in driving to be foremost reasons behind lack of respondents’ interest towards AV
(Cohen, Jones, & Cavoli, 2017). Potential cyber-attacks and disruption in automation systems
are other revealed reasons why people refuse to hand vehicle controls over to automation. The
major obstructions in the path of mass adoption of AVs may be psychological and not
technological. In order to interpret the dominant factors that influence people’s acceptance
and perception of AVs a field experiment based study was conducted in China for 300
participants (Z. Xu et al., 2018). The model included behavioral intention, willingness to ride,
perceived usefulness and perceived ease of use, trust and safety as major determinants. In a
response to this context, the user perception based study in Indian scenario needs to be
ventured as well.
Parameters affecting the early adoption has been studied in segments such as influence
of trust on the technology, behavioral aspects of the users, life style factors and the supply
adoption policies of the respective country or region.
It has been pointed out that trust an ‘anthropomorphic factor’, can be captured through
behavioral, physiological, and self-report measures (Waytz, A., Heafner, J., & Epley, N.,
2014). Parameters affecting the environment such as carbon dioxide emission has also been
discussed in various studies, however, studies also pointed out probable negative effects of
longer distance travels and increased travel speed (Brown, A., Gonder, J., & Repac, B., 2014).
Further, Lavieri, P. S., et al (2017), argued that lifestyle factors play an important role in
shaping AV usage. Further suggesting that younger, educated and more technological savvy
groups may be the early adopters. Wadud, Z. (2017), argued that commercial use (taxis and
trucks) might have higher return than personal use. Based on the above mentioned factors, the
survey was designed to capture factors that might influence early adoptions of AV in India.
3. DATA AND METHODOLOGY
3.1 Data Collection
In October-November 2018, a preliminary survey was conducted in India on the user
perception towards automated vehicles and their degree of interest in using AVs among high
professionals of India. The exploratory survey was mainly given to extremely reputed
university students and other senior officials of global service organizations. Majority of the
respondents, other than university students possess high education standards and are holding
top positions of managing directors (MDs), chief executing officers (CEOs) in internationally
renowned information technology (IT) sectors, Information Technology Enabled Services
(ITES) companies, financial and management consultant companies. Some of them include
Choice Solutions Ltd, Macaws Infotech, Meta Infotech, EPMS Global Enterprise etc. The
main intention of the survey was to explore into the public perception and their opinion
regarding emerging AVs with a focus on the top class citizens with high management skills.
Table 1 represents the general characteristics of the respondents.
Table 1. Characteristics of respondents (number of respondents=123)
Category
Sub-category
Percent
Gender
Male
86.2 percent
Female
13.8 percent
Age
19-30 years
43.9 percent
31-45 years
38.2 percent
46-60 years
17.9 percent
Education level
Less than graduate
8.9 percent
Graduate
46.3 percent
Post Graduate
44.7 percent
Monthly income (INR)
Unemployed (no salary)
35.8 percent
Less than 30,000
6.5 percent
30,000-50,000
3.3 percent
50,000-100,000
8.9 percent
More than 100,000
45.5 percent
Owning vehicle
89.4 percent
Mode choice for daily travel
Own vehicle
60.2 percent
Public transport (Bus, Train, Auto)
28.5 percent
App based (Uber/Ola)
11.4 percent
The survey was created in order to answer questions aiming to investigate general
perceptions regarding various elements of AV. The survey questionnaire was divided into
categories, Part I- socio-economic status of respondents, Part II- Knowledge and general
opinion regarding AVs, Part-III: potential benefits and barriers of AV growth and most
importantly Part IV: Perception and acceptance of respondents. The online survey form
consisting of 60 questions took around 20-30 minutes to complete. The questions consisted of
propositions with Likert scale 1-5, multiple choices, option ranking and open ended
preference and feedback related. SP (Stated Preference) was used for some questions, utilizing
hypothetical options. Few questions in our survey were adapted from a research done by
Woldeamanuel & Nguyen, (2018). Firstly, the survey mapped the respondents’ background
information, such as age, gender, education level and employment status and whether they
had a driving license, to help categorize the respondents. Concerning AV specific
investigations, questions focused on degree of concern and interest, opinions relating to issues
and perceived benefits entailing from complete AV implementation.
The survey was conducted in English and was made comparable with international
studies. In the questionnaire, the general individual level data was followed by general
opinion towards automated vehicles. This question was placed first so that the respondents
could answer it immediately, without the questionnaire affecting the answers. All people who
were selected for the survey were sent a Google online form on October 12, 2018. The sample
population was identified through their email id which acted as unique identification code.
The last responses were received on November 30, 2018. Post data collection process
involved a detailed descriptive analysis in order to inspect probable inter-linkages between
user interests and selected input variables.
The selected controlled-group consisted of respondents within the range of 19-60 year
old population. A total of 123 respondents participated in the survey out of which 106 were
male and 17 were female participants. 43.9 percent belonged to the age group of 19-30 years,
38.2 percent in the middle age group of 31-45 years while remaining 17.9percent belonged to
the age working category of 46-60 years. 46.3 percent of the respondents was graduate and
44.7 percent held a post graduate or more. 91 percent of the respondents was either graduate
or post graduate. 59.3 percent of the respondents was employed with 36.6percent students and
39 percent fully employed. 45.5 percent had a monthly income of more than INR 1, 00,000.
89.4percent report that they own personal vehicle, while 60.2 percent use their own can for
daily travel.
3.2 Exploratory Findings and Discussion
3.2.1 Knowledge, general concern and interest
A closer assessment of the data demonstrated the difference in user perception regarding
knowledge, general opinion and interest concerning AV when gender and age of respondents
was taken into account (see Figure 1).
Respondents were delivered a basic description of self-driving vehicles and then
were inquired for their general opinion and knowledge of AV. It was observed that 95.5
percent of respondents belonging to the age group of 45-60 years were aware of AV followed
by 93.6 percent of middle working age group and 87.0 percent of younger cohort. Although it
is expected that younger cohort would be more aware about emerging technology of AVs than
that of elder cohorts, it has to be observed that here most of the respondents belonging to the
middle and elder age cohorts (i.e. 31-45 and 46-60 years) are highly educated possessing
undergraduate and post graduate education degrees. Also, owing to their possession of higher
management positions in well-established industries, they are perceptibly more aware of the
state-of-the-art technological advancements trending globally. However, not much difference
(8.42percent) was observed between higher and younger cohort’s knowledge, as the younger
cohort comprised of selected students from reputed universities. But, when the concern about
AV was inquired, approximately 50 percent in each age cohort were moderately concerned
about AV. Similarly, 40 percent of young cohort, 44.6 percent of middle age professionals
and 36.6 percent of higher age cohort showed personal interest in owning AV.
0
10
20
30
40
50
60
19 to 30
years 31 to 45
years 46 to 60
years
Number of respondents
Knowledge of AV
Yes No
0
10
20
30
40
50
60
19 to 30
years 31 to 45
years 46 to 60
years
Number of respondents
Concerned about AV
Very Concerned Moderately concerned
Slightly Concerned
0
10
20
30
40
50
60
19 to 30 years 31 to 45 years46 to 60 years
Number of respondents
Interested in owining/ riding AV
Very interested Moderately interested
Slightly interested Not at all interested
0
20
40
60
80
100
120
Male Female
Number of respondents
Knowledge of AV
Yes No
0
20
40
60
80
100
120
Male Female
Number of respondents
Concerned about AV
Very Concerned Moderately concerned
Slightly Concerned
0
20
40
60
80
100
120
Male Female
Number of respondents
Interested in owining/ riding AV
Very interested Moderately interested
Slightly interested Not at all interested
Figure 1. General opinions, knowledge and corners regarding autonomous vehicles
Similarly, when gender was taken into consideration marginally more number of males
(92.4percent) had knowledge of AV than that of females (82.3percent). However, gender
neutral results were observed when males (49.0 percent) and females (52.9 percent) expressed
their common views regarding concern about AV. Surprisingly, women (47.0 percent) were
found to express slightly higher levels of interest than men (40.5percent). This explains that
although AV is well acknowledged in India, people are yet ready to accept it in reality
evading concerns and reservations. This phenomenon can be assumed to get transformed with
large-scale implementation of AV in reality.
3.2.2 Perceived notion of safety
Literature has established safety as a major issue in advancement of AV (Cui, Liew,
Sabaliauskaite, & Zhou, 2018); hence, all the respondents were distinctly asked about the
degree of safety they would perceive while riding AV. 89.4 percent of the respondents owned
a car, out of which 60.2 percent used their own car for daily travel purpose. Majority of the
respondents i.e. 91.1 percent had a positive attitude towards AVs and they were fully aware of
the technology, but the respondents did not feel safe at all when were inquired about solely
riding a fully autonomous vehicle in Indian road conditions (see Figure 2a). It was observed
that 44.4 percent of the younger cohort, 38.2 percent of the middle age professionals and 45.5
percent of the higher age cohort did not feel safe at all when asked to ride AV alone.
Figure 2. Perceived degree of safety (a) and perceived concerns (b) regarding autonomous
vehicles
3.2.3 Perceived concerns for the AV technology
AVs have the potential to bring huge positive changes in existing transportation systems by
formulating new urban planning elements; however like other technologies, AVs would also
face challenges in public adoption owing to certain perceived concerns of the users.
Respondents were hence asked to reveal the major concerns they might face regarding AV
integration.
Liljamo et al., (2018) had demonstrated in his study that gender and age hugely affect
attitude towards AV, where 30 percent male and 17 percent female had shown positive and
moderate interest towards AV in a Finnish survey. In this study, the major concern among both
male (66.03percent) and female (47.05percent) respondents was observed to be safety. When
age was taken into consideration, respondents in the higher age group of 46-60 years had
considered cost, lack of improved regulatory framework and consumer readiness to be major
concerns of AV other than safety issues. 64.81 percent of younger cohort, 61.70 percent of
middle age professionals and 63.63 percent of higher age group perceived safety issue as the
major concern (see Figure 2b). Thus, in contrary to the above mentioned inferences, age and
gender of the respondents delivered a similar results regarding concerns of AV technology in
this study.
3.2.4 Perceived activities in autonomous vehicles, while not driving
Initial researches considered travel time as negative utility; however currently, the Value of
Travel Time Savings (VTTS) have been empirically calculated by researchers to analyze the
importance of multi-tasking involvement during travel (Varghese & Jana, 2018), thus
increasing activity participation. The advanced technology of AVs are able to relegate a
person from being the vehicle’s driver with full control to transforming to a passenger within
the same driver-less vehicle. Thus, unlike previous scenarios, AV technology permits the
driver to participate in activities similar to other passengers while riding the vehicle. A
question in the survey investigated the likelihood towards participation in different activities
while riding AVs.
0
10
20
30
40
50
60
Work
Entertainment
Sleep
Social
Read
Watch road
Number of respondents
(Age group: 19 to 30)
yes no
0
5
10
15
20
25
30
35
40
45
50
Work
Entertainment
Sleep
Social
Read
Watch road
Number of respondents
(Age group: 31 to 45)
yes no
0
5
10
15
20
25
Work
Entertainment
Sleep
Social
Read
Watch road
Number of respondents
(Age group: 46 to 60)
yes no
0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00%
Work
Entertainment
Sleep
Social
Read
Watchroad
Percentage of respondents willing to perform desired activities
Desired activities
Figure 3. Responses on preferred participation of activities while riding AVs
60.2 percent of the respondents drive their own vehicle for daily travel. However,
with the advent of driver-less technology in AVs, the extra travel time can be used in
multi-tasking activities such working, sleeping, watching road etc. Figure 3 explicates that 30
percent respondents opted to work while riding AV. Younger age group of 19-30 years
preferred entertainment (20.03percent) as major desired activity after work (27.78percent).
Apart from involving in productive activities like working (31.16percent), watching road
(27.6percent) and social activities (12.7percent) were also favored by the middle age group as
desired activities while riding AV. 31.8 percent of respondents belonging to higher age cohort
preferred to utilize their travel time by working. Therefore, respondents entrained by their
education and work-place position and associated stress, majorly preferred to maximize their
travel time by working and performing productive activities.
3.2.5 Perceived potential benefits
Another important aspect explored was the user perception towards potential benefits
resulting from AV integration. AV is foreshadowed for many positive as well as negative
implications across various sectors. The major benefits of AVs include cost savings other than
reduced vehicular accidents and its associated costs. AVs can also produce a positive effect on
traffic congestion and fuel savings as well (see Figure 4a).
Here, 83 out of 106 males strongly agreed reduced amount of vehicular crashes as a
major benefit of AV. Reduced severity of crashes and improved emergency response to
crashes are other benefits observed by male respondents. On the other hand, females
recognized better fuel economy and lower vehicular emissions as potential benefits of AV.
Figure 4. Perceived responses regarding potential benefits of AVs (top) and Percentage of
respondents regarding order of likelihood of potential benefits of AV (down)
Taking an overall perspective as demonstrated in Figure 4b, ‘improved emergency
response to crashes’ was strongly agreed (25.2percent) and agreed (47.2percent) as most
potential benefit of AVs. Owing to artificial intelligence based vehicular control system,
respondents perceived it to be the most beneficial aspect of AV integration. Reduced severity
of crashes was also recommended as another perceived benefit of AV. This explicates that the
respondents are aware of the fact that with complex sensor installations, AVs would be able to
sense the presence of neighboring obstacles (other vehicles, pedestrians etc.); hence, they
believed that severity of road accidents would reduce with AV technology. AVs leading to fuel
saving strategy is among the maximum benefit believed to occur by the respondents, and has
the highest response frequency for the respondents who agreed (48percent) and strongly
agreed (21.1percent) to this phenomenon.
Respondents were asked the degree of agreement regarding reduced vehicular emissions.
The results show that 26.8 percent and 35.8 percent of the respondents either strongly agreed
or agreed it to be the most feasible benefit. However, opposite to the spectrum, 24.3 percent of
respondents disagreed ‘shorter travel time’ as benefit incurred from AV technology integration,
as they believed that AV would not reduce travel time. The lowest frequency in context to the
‘Less traffic congestion’ is expressed by 21.1 percent, who disagree that traffic congestion is
likely to reduce owing to AV adoption. Since, traffic congestion is unlikely to reduce due to
AV integration, travel time would advertently remain same. Hence, maximum respondents
disagreed ‘reduced travel time’ and ‘less traffic congestion’ to be benefits incurred from AV
implementation.
3.2 Research Methodology
Theoretical evidences suggest that interest, attitude and concerns towards advanced
technology of AVs depends hugely on user perception, their socio-economic background, and
their preferences ( Casley, Jardim, & Quartulli, 2013; Haboucha, Ishaq, & Shiftan, 2017;
Anania et al., 2018; Nazari, Noruzoliaee, & Mohammadian, 2018; Bennett, Vijaygopal, &
Kottasz, 2019). To study this relationship, we estimated a Multinomial logistic (MNL) model
(McFadden, 1987; Wills, 1987; Society, 2017), where the user interest towards AV is the
outcome variable. The model predicts user’s attitude towards AV between four degrees of
interest: very interested, moderately interested, slightly interested and not at all interested and
draws its relationship with the socio-economic characters of users such as age, gender,
employment and education levels on one hand and their desired activities, perceived concerns
and benefits of AV etc. on other hand. The relationship between user characteristics and their
attitude towards AVs will deliver us a comprehensive image of the opinion of varying
categories of users towards forthcoming advanced technology of self-less automobiles within
the country.
The MNL model offered us a global statistic i.e. one single value explaining the
relationship between public interest levels and other independent variables considered in the
model. It explains how degrees of users’ interest towards AV depend on other input variables.
Since the aim was on exploring the attitudes towards AVs, our intention was not to estimate
the best fitting and most complex model. Therefore, we only estimated standard multinomial
logit regression model in this research.
4. RESULTS
A strong correlation was observed between the education, employment of the respondents and
their knowledge regarding AV technology (see Figure 5). As expected, people with higher
education and appropriate employment status had more knowledge about AV technology.
When desired activities while riding AV was taken into consideration, a positive
correlation was observed between employment, education variables and entertainment, while
the variables showed a negative correlation with reading. On taking AV related concerns into
account, people who had more knowledge regarding AV technology were relatively less
concerned about AV technology’s reliability; but considered cost and dearth of consumer
readiness as major concerns for AV growth in Indian scenario. Concern related to ‘Regulatory
framework’ was found to have a strong correlation with ‘cyber security’.
Figure 5 Correlation matrix explaining the strength and direction of relationships within
variables considered in MNL: desired activities (left) and major concerns (right)
The MNL model represented an individual’s likelihood towards the degree of interest
for AV expressed in three major categories of ‘very interested’, ‘moderately interested’ and
‘slightly interested’ with ‘not at all interested’ as reference category (see Table 2). The model
estimates exhibited positive relation between education level and high degree of interest
towards AV, and showing mild increase in moderate level of interest. This explicates that the
respondents with higher education standards had more probability of showing higher degree
of interest towards AVs. The odds of showing higher interest also increased with the
employment status of the respondent. This is majorly due to the diffusion of innovation theory,
where early adopters exhibit more interest towards new technology (Sullivan, 2015). The
model also showcases that the concern for AV technology has a negative relation with
peoples’ interest towards AV i.e. respondents who are less concerned regarding AVs’
reliability had more likelihood towards higher interest intensities. If the impact of travel time
utilization while riding driver-less AV is investigated, it can be observed that people
expressing higher levels of interest were less preferring to use the time doing social activities
like texting, talking etc. This is attributable to the fact that the employed people with higher
education standards (maximum respondents) would prefer to maximize their travel time
performing productive activities like work rather than involving in social connections. If we
probe into the respondents’ perception about major obstacles that can hinder the AV growth
in Indian market, a positive relationship was observed between people who considered cost of
AV technology as major obstacle and their expression of interest towards AV. Furthermore,
when the major concerns regarding AV and how they relate to the odds of preferring high
interest level towards AV are explored, it can be noticed that safety concerns related
negatively with log odd choice preferences. Implying, people with higher safety concerns
were not at all interested towards using AVs.
These results represent an average value for the whole sample collected from major
cities of India, representing a holistic statistics. However, this fails to provide us the other
local variations existing amongst the socio-economic or other input variables that can be more
prevalent than the other. Higher sample size can provide us better relationships and can help
us to interpret the association user variables have with their attitude towards AV. Last but most
importantly, the aim of the study was to inspect the perception of a particular high educated
section of population who are occupying high service positions in different sectors; hence, the
results of this model might counter when a heterogeneous population sample is taken into
consideration.
Table 2. Model estimation results
Independent
Variables
Very interested
Moderately interested
Slightly interested
(B)
Std.
Error
T stat
(B)
Std.
Error
T stat
(B)
Std.
Error
T stat
Intercept
0.98
1.16
0.83
1.27
1.11
1.14
-0.22
1.22
-0.18
Education
level: Less
than Graduate
-2.74*
1.68
-1.63
-3.57**
1.63
-2.18
-2.24
1.58
-1.41
Education
level:
Graduate
0.51
1.06
0.48
0.51
1.01
0.50
0.07
1.13
0.06
Employed
1.89
1.43
1.32
2.24*
1.38
1.62
2.97**
1.45
2.04
Concern:
Slight
3.41**
1.47
2.31
1.61
1.45
1.10
1.67
1.48
1.12
Concern:
Moderate
1.09
0.90
1.21
1.08
0.83
1.30
0.93
0.89
1.04
Social activity
-3.56**
1.66
-2.14
-1.42
1.31
-1.08
-1.03
1.33
-0.77
Perceived
Cost
2.27**
1.19
1.91
2.36**
1.15
2.04
1.79
1.21
1.47
Perceived
Major
concern:
Safety
-1.98*
1.06
-1.86
-1.56*
1.04
-1.50
-0.69**
1.10
-0.62
Observations
123
Model fitting information
Initial
log-likelihood
204.992
Likelihood Ratio Test
Final
log-likelihood
154.283
Chi-square
df
Sig.
McFadden’s
Rho-squared
2
0.165
50.709
24
0.001
– Not relevant; *** Significant at 1percent level; ** Significant at 5percent level; * Significant at 10percent
level
a. The reference category is ‘not at all interested’.
5. DISCUSSIONS
This study utilized the public opinion data by performing online survey from major cities of
India including Mumbai, Hyderabad, Pune, Delhi and Chennai to analyze the user perceptions,
their attitude and concerns regarding the advanced technology of self-driving vehicles within
high level professionals. Majority of the respondents were post-graduate, and employed with
monthly salary above INR 150,000.
Descriptive statistics suggested that 91.9 percent of the respondents were pragmatically
aware of the forthcoming self-driving vehicle technology and showed positive attitude
towards AV, but half of the respondents exhibited moderate anxiety about AVs’ reliability (see
Figure 1). This explains that the highly educated group of sample, though are aware of the
state-of-the-art technological advancements, have exposure to the challenges, issues and
deficiencies of current technologies. It was also observed that the concern regarding AV was
gender unbiased, and the most perceived apprehensions for both male and female were safety
issues and dearth of consumer readiness. High cost of the system and existing regulatory
frameworks were also perceived as major barriers in the growth of AV in Indian market.
When we looked into the age category, younger age cohort mostly preferred entertainment as
the desired activity during time of travel, whereas middle and higher age group chose to work
(Figure 3). According to Figure 4, better emergency response to crashes was perceived as the
major benefit incurred from AV technology.
MNL regression model for determining user interest towards AV showed that the odds
of preferring AV technology increases with education level. This is because with higher
education standards, the awareness and acknowledgement of a forthcoming advanced
technology increases. It also showed that how employment of a person acted as a guiding
factor for choosing preferred levels of interest towards AV. This can be strongly explained as
an employed individual with decent earning would more easily be able to accept and afford
technologies like AV. Since age of the respondents was not distinctly investigated, it did not
show significance while conveying interest towards AV. However, it can be assumed that the
generation difference between non-millennials and digital natives can be another challenge
behind consumer adoption of relinquishing the vehicular control to artificial intelligence
(Woldeamanuel & Nguyen, 2018). It was also observed that people who expressed maximum
concern or anxiety for AVs’ reliability, had the probability of showing least interest in
adopting the forthcoming AV. Dearth of consumer readiness and fear of accepting advanced
technology can be apprehended as the major factors contributing to this phenomenon. Also,
India has not yet witnessed enough AV field testing which can also develop negative outlook.
Furthermore, with inferior road conditions in India, and maximum death toll rising due to
road crashes, driver-less AVs would advertently be a major concern of citizens. With
successful field test of AVs in India at a mass scale, the acceptance rate of AVs can be
increased. This broadens the need of further research to aware Indian citizens regarding
benefits of AV as well. Descriptive analysis of the data elucidated work to be most preferred
activity while riding AV; in similar trails, the regression model also showed that people who
least preferred to perform social activities during travel had the probability of expressing
maximum fascination towards AV (refer to Table 2). With travel time saving in a driver-less
vehicle, highly educated and employed passengers would maximize their time utilization in
multitasking by involving in productive activities like work, read etc. MNL also explored the
relationship, the perceived potential challenges of AVs have with preferring AVs with varying
interest levels. Surprisingly, it was observed that amongst cost, cybersecurity, dearth of
regulatory framework and consumer readiness, high cost of the forthcoming technology came
out as the only significant variable. The model results suggested that people who had reasoned
high cost of the technology as preferred difficulty in growth of AV, had expressed more
interest towards AVs. The major factor which can be contributed to this phenomenon is that it
is already well accepted globally as well in India, that AV with artificial intelligence strategies
would be the most recognizable forthcoming technology in automotive industries. However,
the only major challenge would be the cost and expenses incurred for manufacturing,
operating, and maintaining this heavy computation-based technology. However, cost
subsidization at a mass-scale can enormously increase the user acceptance of AVs. For
example, in China electrical vehicles (EVs) have been highly subsidized with its
implementation even in public fleets (Gandoman et al., 2019; Li & Ouyang, 2011). Based on
effective subsidization policies offered by government, AV might also be accepted in future as
a major mode of transportation in India. However, large scale infrastructure development
needs to be undertaken before such initiative can be practically applied on roads. Lastly, the
model results also demonstrated that people with higher safety concerns had the probability of
showing lesser interest in AVs. It has already been well-established in literature that safety is
of paramount importance for autonomous vehicles, where planned trajectory cannot be
assumed perfectly in presence of evasive maneuvers owing to tire slip, uncertain parameters,
indeterminate initial states, and other distractions and disturbances (Althoff, Althoff, Wollherr,
& Buss, 2010). Sets of variables like velocity, orientation, and slip angle through online safety
verification should be properly computed before large-scale implementation of this
technology. However, with AV technology verification, the behaviorism of users might alter.
6. CONCLUSION
Owing to the lack of adequate literature regarding AV emergence, usage and user perception
concerning AVs in Indian scenario, this is the initial study as per knowledge of authors, which
explores into the public opinion, their attitudes and concerns towards advanced technology of
self-driving vehicles in India. On one hand, advent of new technology like AV would facilitate
the users with improved level of service including smooth travel, better fuel economy, thus
increasing user satisfaction level, whereas the perceived challenges of AVs like safety
concerns, artificial intelligence system failures coupled with their adverse effects etc. is a sign
of gaps that impose great challenge in public adoption of AVs. However, the AV industry still
continues to advance the technology at a fast rate in preparation for introduction of AVs to the
public domain. This research broadly aims to capture the user perception in Indian scenario by
centering on public individualities, opinions and values held by respondents to answer few
primary questions:
i) How interested would you be in riding a completely self-driving vehicle?
ii) Do statistical relationships exist between demographic and socio-economic variables,
and specific opinions and sentiments?
iii) How does income and education standards affect level of interest for AVs?
The survey was majorly categorized into two sectors: perceived challenges and potential
benefits incurred from AV. The exploratory analysis divided the results between three age
cohorts which include young adults, people belonging to mid management and top
management of different industries. The perceptions of rural, suburban and low-income urban
population have not been considered in this study.
The findings from the surveys offered a generalized perspective regarding the user
attitude towards AV and whether certain age groups are more attracted to AV technology than
the others. Since, the AV adoption is in infant stage, this study can pave a way forward
towards formulation of user friendly transport policies and guidelines regarding upcoming AV
technology in India. Further, this study might provide valuable inputs to the automobile
companies indulging in development of AV.
The study finds that Indian citizens have a positive attitude towards AV, and have
optimistic views regarding AV benefits. The respondents shared gender-neutral views
regarding knowledge of AV and concerns related to safety issues on one hand and
gender-biased views on AV related benefits on other hand. Neutral views was observed when
selecting desired multi-tasking activities while riding driver-less cars; while dichotomy in user
perception was observed in expressing awareness, general concern and knowledge regarding
AV when age cohort came to play role. Cost was perceived to be a major hurdle towards the
growth of AV in India.
The reservations and unreliability intertwined to the forthcoming AVs’ technological
progressions especially in developing nation like India have been recognized here. However,
numerous queries in this field still remains under-explored, which can be speculated with the
real implementation of AVs at large-scale. Further research on globally accepted AV related
policies can enhance the depth of the epistemology of the evolving arena of AV addressing
macro-level matters regarding the effect of global AV adoption on urbanization etc. With aid
of these researches, the efficacy of AVs can be adjudicated rationally.
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