Pictures of You, Pictures of Me

User Acceptance of Camera-technology in Intelligent Transport Systems

Teresa Brell, Ralf Philipsen and Martina Ziefle

Human-Computer Interaction Center, RWTH Aachen University, Campus-Boulevard 57, 52074 Aachen, Germany

Keywords: Camera-acceptance, Camera Design, User Diversity, Intelligent Transport Systems, Traffic Infrastructure.

Abstract: The integration of connected and smart technology is a key factor of our future traffic system development.

By integrating traffic participants into the technology development circle, possible trade-offs, obstacles and

advances can be identified and further, an understanding of technology acceptance can be evolved. This paper

will show, how camera-based technology in intelligent transport systems is evaluated from a user-centred

perspective. The focus of this work lies on the identification and evaluation of perceived benefits and barriers,

but also conditional and functional aspects are investigated as well as an overall acceptance picture. Results

show, that the need for technology is not denied, but privacy concerns and a feeling of surveillance still re-

strain users.

1 INTRODUCTION

Today, smart technologies are integrated in many

parts of our life: private, public and societal life as

well as business or working sector. The overarching

aim of integrating smart functions is functional by na-

ture: These processes, objects and functions direct to

optimize technology, increase the effectiveness and

efficiency of processes, and by this, decrease energy

consumption, enhancing safety, and minimizing hu-

man error. Adapted lighting, self-regulating thermo-

stats or virtual medical care are just small examples

of what can be connected to our homes and offices

(Asadullah, 2017). This shows just the surface of the

diverse scope of user-centred technology interaction

in many areas of application. Various technological

enhancements are used to develop seamless integra-

tion of those technical functions into our daily life and

further.

A very prototypical case for minimizing human

error are intelligent transport systems (ITS)

(Figueiredo et al., 2001). ITS or connected cars aim a

sustainable supply for all residents and moreover an

increase of traffic safety and providing maximum

comfort for travellers (Alam et al., 2016, Gora & Rüb,

2016). There are different technological approaches

on how intelligent transportation might work effi-

ciently. One way to support smart transportation tech-

nology could be camera-based traffic participant de-

tection (Datondji et al., 2016).

The idea behind the camera-based detection is

simple: A smart infrastructure, able to detect traffic

participants (type, number, and density of partici-

pants) could customize transportation functions or

traffic-relevant processes: e.g. the traffic light phases

to adapt to intense traffic. However, the technology

behind the idea is not simple: to ensure a complete

coverage, the detection of all street markings (Wang

et al., 2000), in real-time (Aly, 2008), multi-lane per-

ception (Abramov et al., 2016), based on accurate ge-

ometric lane estimation (Kang et al., 2014) is needed,

just to name a few.

Current research in this area focuses mainly on

technical issues, whereas integrating the users in the

technological development process is a key part for

societal acceptance (Rogers, 2003). Most studies in

traffic technology, which integrate the user focus on

usability issues, e.g. data visualization or transfer of

control (Rakotonirainy et al., 2014), but lack to iden-

tify user’ requirements on communication and infor-

mation on data exchange in traffic.

Especially when integrating cameras into public

places and streets, the trade-off between security and

safety on the one and the unwanted feeling of contin-

uous surveillance on the other hand is an intricate is-

sue for user acceptance (van Heek et al., 2016a,

2017). Even though residents value the increase of

public safety and security, the violation of public’s

privacy through recording, storage and processing of

(video) data is a serious barrier of using cameras in

Brell, T., Philipsen, R. and Zieﬂe, M.

Pictures of You, Pictures of Me.

DOI: 10.5220/0006700603710378

In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2018), pages 371-378

ISBN: 978-989-758-293-6

371

public spaces (Patton, 2000). A steadily growing dis-

trust to share data with a smart infrastructure, general

concerns and drawbacks could be identified in previ-

ous studies (Schmidt et al., 2015b). The identification

of perceptional obstacles in camera-based traffic

technology to understand the acceptance or willing-

ness to actively cooperate by sharing data is insuffi-

ciently explored so far. So, the question remains:

Would people accept a temporal (or permanent) in-

stallment of cameras in traffic?

2 METHODOLOGICAL

APPROACH & QUESTIONS

ADDRESSED

A user-focused technology design addresses the iden-

tification of influential acceptance factors as a major

process step. Subsequently, the user should be part of

the technology development in an iterative process.

To understand, which (perceived) obstacles and ad-

vantages come with the use of camera-based technol-

ogy in traffic, we followed a two-tiered empirical re-

search approach.

Qualitative (expert-) interviews, in which the pos-

sible usage scenarios were discussed, helped us to

identify benefits and barriers of the technology along-

side questioned functions, conditions and acceptance

patterns of/for the camera-technology.

Further, the results of the qualitative studies were

integrated into the quantitative questionnaire study to

follow the methodological approach of our research

model. The present work focuses on an understanding

of the acceptance of camera-based technology in traf-

fic.

Figure 1: Methodological concept of research model.

As can be seen from Fig. 1, the research perspec-

tive is user-centred. The methodological approach

shows three main research branches, which are ad-

dressed by the empirical procedure:

I. the overall perception of benefits and

barriers of the camera-technology,

II. the overall evaluation of functions and

conditions of the camera-technology,

III. a user-diverse look on acceptance pat-

terns.

2.1 The Survey: Development of the

Questionnaire Instrument

The used questionnaire survey was divided in several

parts. First, an informational text introduced the topic

of camera-based traffic technology to the participants.

2.1.1 Demographics and Traffic Behaviour

The first thematic section addressed demographic

data and questioned, if the participants own a driver’s

licence. Further, a self-assessment of the driving

skills and driving type was queried along the fre-

quency of vehicle usage. Also, the technical affinity

(Karrer, 2009) and the technical self-efficacy was

measured (Beier, 1999), the individual confidence in

one’s capability to use technical devices.

2.1.2 Camera Technology

In the second section, two sets of eight items (6-point

Likert scale, 6=full agreement) questioned the ad-

vantages (cf. Table 1) and disadvantages (cf. Table 2)

of camera-based technology in traffic environment.

Here, we could fall back on previously identified ar-

guments of qualitative studies, to help the participant

to evaluate the technology.

Table 1: Items of technology advantages.

I see the use of this technology positively, be-

cause…

…it increases traffic safety for all participants.

…it increases personal perceived traffic safety.

…it helps to prevent accidents.

…it helps to reduce traffic jams.

…it organizes the traffic more efficiently, so I save

travel time.

…traffic offender can be found more easily.

…the intelligent infrastructure and daily traffic situa-

tions will be optimized.

…exonerates the traffic for all traffic participants.

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372

Reliability analysis revealed high internal consist-

encies for the scales with Cronbach’s  = .892 for the

technology advantages and Cronbach’s  = .891 for

the technology disadvantages.

Table 2: Items of technology disadvantages.

I see the use of this technology negatively,

because…

…cameras transport a surveillance feeling.

…it bothers me that my data can be collected.

…the use of cameras compromises my privacy.

…I fear to lose my anonymity in traffic.

…I think the cameras do not function properly.

…I don’t want the traffic infrastructure to be digital

and connected.

…there is no need for technology in traffic.

…cameras are a distraction in traffic.

2.1.3 Camera Scenarios

The third section was divided into two possible cam-

era-scenarios. First, a bird-eye view picture of an in-

tersection was shown as location example followed

by in informative text to help the participants envision

the possibilities of camera-based technology usage in

traffic. A visualization of the camera type (internal vs.

external) was shown (see Figure 2) next along an al-

location of characteristics in form of a semantic dif-

ferential (Osgood, 1952, Bradley & Lang 1994) to-

wards the technology (categorized results from the in-

terview studies). The used attributes were derived

from previous (expert-)interviews.

Figure 2: Visualization example of internal camera design

(on the left) and external camera design (on the right) as

used in online survey.

Further, the approval of several camera functions

was questioned (see Table 3).

Table 3: Items of camera functions.

What functions should camera technology

have in your opinion?

The camera should be able to / have …

…save pictures (data) up to 24h.

…permanently analyse data material.

…swivel (moving around).

…process the material directly (no data storage).

…a predetermined angle of recording.

(e.g. safety equipment).

…analyse pictures (data) only in a predetermined

time frame

(e.g. between 6 and 9 am).

…only one alignment.

…zoom.

…interact with smartphones.

The last part of this section queried the acceptance

of the technology in terms of consent to the user of

camera technology with eight items (6-point Likert

scale, 6=full agreement).

2.2 Data Acquisition and Analysis

The survey was conceived as an online study. Partic-

ipants were addressed through acquisition in the uni-

versity environment and in online forums focusing on

safety, road transport or mobility in general. Aban-

doners and speeders were excluded from the analysis

during the quality check of the data. Data was ana-

lyzed descriptively and, with respect to the effects of

user diversity, by ANOVA procedures and linear re-

gression. The level of significance was set to α=.05.

Cohen’s d is reported for effect sizes. The remaining

data was analysed with non-parametric procedures

(cross-checked by parametric statistical evaluation

methods for group comparisons). Non-parametric

procedures are reported when minor violations of the

procedural requirements, i.e. deviation from normal

distribution of data, could be expected to result in an

underestimation of the p-values. Spearman correla-

tion coefficients are reported for bivariate relation-

ships.

2.3 Participants

In total, N=143 responses were included in the analy-

sis. The age ranged from 18 to 66 years, with an av-

erage of 31.9 years (Standard Deviation=11.7). The

gender distribution was almost equally distributed

Pictures of You, Pictures of Me

373

with 67 men (46.9%) and 76 women (53.1%). The ed-

ucational level of the sample was rather high, with

60.1% holding a university degree (n=86), followed

by 25.2% with a general higher education entrance

qualification (n=93) and 7.7% have a secondary

school certificate (n=11) plus 7.0% stated another

level of education (n=10). All participants reported a

rather high technically self-confidence with 4.2 / 6

(SD=0.9). Here, men are slightly more technical self-

affine (M=4.6; SD=0.8) than women (M=3.8;

SD=0.9) with t(141)=-5.056, p<.001, d=0.847.

The majority (n=135, 94.4%) holds a driving licence.

The sample evaluated the overall driving style as ra-

ther bold (Mean=3.2 out of 5 points max.) and fast,

but cautious, defensive and comfortable (see Table

4):

Table 4: Self-evaluation of driving style with 0=left attrib-

ute and 5=right attribute (N=143).

Driving type attributes

0 | 5

Fearful

Bold

3.2

1.3

Slow

Fast

3.0

1.2

Cautious

Risky

1.9

1.2

Defensive

Offensive

2.2

1.3

Comfortable

Sportive

2.2

1.2

3 RESULTS

In the following section the obtained results will be

presented in detail. First, the general findings about

the acceptance of camera technology are presented.

We report the perceived benefits and barriers related

to camera technology use in traffic. First, the partici-

pants were invited to agree or disagree to different pro

and contra camera-technology based statements. The

statements were formulated on the base of the quali-

tative research carried out prior to this questionnaire

study. Further, they had to evaluate several functions

and conditions of the technology.

3.1 General Results

In a first step, we report an overview of the general

questions about the level of information the partici-

pants had about both, camera use in traffic today and

information about the topic connected driving. In to-

tal, 75,5% (n=108) of the participants stated that they

noticed camera use in traffic before. Further, 44,1%

stated that the have heard about the topic connected

driving – so 55,9% (n=80) are new to the develop-

ment.

3.1.1 Perceived Benefits

All beforehand identified benefits were accepted (cf.

Table 5). In summary, the most anticipated benefit for

the participants was to identify traffic offenders with

an average approval rating of 4.8 (SD=1.0). Follow-

ing accepted benefits address the optimization of traf-

fic flow: optimizing the traffic infrastructure (M=4.4,

SD=1.0) and reducing traffic jams (M=4.2, SD=1.2).

The increase of personal safety (M=3.7, SD=1.2) and

preventing accidents (M=3.7, SD=1.3) had compara-

bly lower ratings.

3.1.2 Perceived Barriers

Regarding the possible barriers to the use of camera-

technology especially statements dealing with pri-

vacy and data protection provoked serious concerns

(high approval ratings). On average, the participants

Table 5: Perceived benefits and barriers of camera-technology (mean agreement and standard deviations, 1 = no agreement,

6 = full agreement).

Camera-technology evaluation

Benefits

Barriers

Increase personal traffic safety

3,7

1,2

143

1,3

2,6

Cameras distract in traffic

Prevent accidents

3,7

1,3

143

1,2

2,9

No need for technology

Save travel time

3,8

1,2

143

1,3

3,3

Not wanting digital & connected traffic

Exonerate traffic

3,9

1,1

143

1,3

3,5

Camera not functioning properly

Increase overall traffic safety

4,1

1,1

143

1,5

3,6

Loss of anonymity in traffic

Reduce traffic jams

4,2

1,2

143

1,5

3,8

Compromise of own privacy

Optimize infrastructure

4,4

1,0

143

1,5

4,0

Feeling of data collection

Find traffic offender

4,8

1,0

143

1,4

4,2

Surveillance feeling

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374

agreed that cameras convey a feeling of surveillance

(M=4.2, SD=1.4) and the possible collection of (my)

data is also perceived negatively (M=4.0, SD=1.5).

The participants did rather not agree on the statement,

that cameras are a distraction in traffic (M=2.6,

SD=1.3).

When comparing the extent to which benefits, and

barriers were confirmed, it becomes apparent that the

confirmation of the benefits is much more pro-

nounced (with the highest evaluation of 4.8 points and

the lowest evaluation of 3.7 points) in comparison to

the barriers (max: 4.2 points and 2.6 points as lowest

evaluation). This shows that participants tend to tol-

erate the barriers while clearly valuing the benefits of

having cameras on public traffic routes.

3.1.3 Functions and Conditions

The functions and conditions of the questioned cam-

era-technology were taken from a beforehand taken

expert interview.

The most anticipated camera functions are the

data storage time of 24h max. (M=3.9, SD=1.3), pro-

cessing the material directly (no data storage)

(M=3.9, SD=1.1) and the possibility to swivel (move

around) (M=3.7, SD=1.2). The permanent analysis of

data material (M=3.3, SD=1.3) and the possibility to

interact with the camera (M=2.6, SD=1.3) are (rather)

not agreed upon. As for the conditions, almost all of

them were perceived as highly important (see Figure

3). Here, especially the condition to enhance safety in

traffic (M=5.1, SD=1.2), a functioning technology

(M=5.0, SD=1.1) and the condition of data security

(M=5.0, SD=1.2) are perceived most important.

Figure 3: Mean importance of different conditions for cam-

era use (0=min. importance, 6=max. importance).

3.2 User Diversity in the Evaluation of

Camera Technology

Looking at the influence of user factors on the per-

ception of advantages and disadvantages as well as on

the general acceptance of the use of camera technol-

ogy in traffic context, it becomes apparent that some

of the user characteristics considered have a signifi-

cant effect, but can only explain the user evaluations

to a minor degree.

As can be seen in Fig. 4, there is no significant

correlation between age on the one hand and other

user factors and the evaluation of camera use on the

other hand. In contrast, there is a weak, positive cor-

relation between gender and both technical affinity

and self-confidence. Male participants stated higher

values for both attributes. There is a medium positive

correlation between both attributes themselves. In ad-

dition, gender was positively correlated with the driv-

ing style: Men agreed more strongly that they drive

Figure 4: Significant relations (Spearman correlation coefficients) between user characteristics, perceived benefits and barri-

ers as well as general acceptance of camera use.

Pictures of You, Pictures of Me

375

courageous (r

=.399), faster (r

=.397), offensive

=.280), and risky (r

=.246) than women.

Looking at the evaluation of camera use, it was

obvious and expected that the agreements to benefits

and barriers were negatively correlated. Participants

who agreed to the benefits showed less concerns

about barriers and vice versa. However, the correla-

tion was only weak. Unsurprisingly, there is a con-

nection between the general acceptance of the tech-

nology and the approval to both benefits and barriers

(contrary).

More central for the research question than the

correlations among each other within a factor group

are the correlations between user factors on the one

hand and the camera evaluation on the other. Fig. 4

indicates that age, gender and the individual driving

style have no effect on the perception of the technol-

ogy. Apparently, we see a quite homogeneous attitude

towards camera usage across participants that is not

modulated by individual factors.

As one exception, the technical affinity was posi-

tively correlated with both the agreement to benefits

and the general acceptance. Interestingly, there was

no relationship between the affinity and the percep-

tion of barriers. The technical self-confidence was

even only correlated with the acceptance measure-

ment. However, all correlations between user charac-

teristics and technology evaluation were only of mi-

nor degree (see Fig. 4) and cannot fully explain the

small but existing variance at the participants’ atti-

tudes. A linear regression analysis confirmed the

emerging picture and identified the technical affinity

as most explaining factor. However, with R

=.179 the

explained share of variance was rather low.

3.3 Attributions to Camera Designs

By looking at the attribution of the descriptive adjec-

tives to the two presented camera designs, almost all

pairs of terms with a more positive adjective were

predominantly attributed to both camera designs. The

cameras were attributed as "useful", "safe", "pro-

tected", "controllable", "elegant", and "modern" (see

Fig. 5). The only exception is the "observing prop-

erty" that has been assigned to both designs and the

"unfamiliarity" that was mentioned for the integrated

cameras. However, the participants made a few sig-

nificant distinctions based on the design for a few at-

tributes (where Wilcoxon Tests showed p<=.002).

At first, integrated cameras where perceived as

"cheaper" than external cameras. Looking at the func-

tionality, it became clear that the participants consid

ered integrated cameras as more "protected" than ex-

ternal ones. Most interestingly, the visibility of the

Figure 5: Attribution of descriptive adjectives to different camera designs

VEHITS 2018 - 4th International Conference on Vehicle Technology and Intelligent Transport Systems

376

camera led to a stronger attribution of an "observing

characteristics" in comparison to internal cameras,

which are usually hidden from sight.

The biggest differences in the users’ attributions

were found for design and innovation. Internal cam-

eras were perceived as significantly more "modern",

"elegant", "beautiful", and "friendly", whereas exter-

nal cameras were considered as more "familiar".

4 DISCUSSION & CONCLUSION

The current study was directed to the user’s view on

the possible use of camera-based technology in smart

infrastructure environments with the aim to identify

and integrate users’ requirements and concerns dur-

ing the technology development and roll-out.

It is noticeable that the utilization of camera tech-

nology was rated mainly positively. The participants

both attributed usefulness to the camera systems and

predominantly agreed to the benefits of it. A general

rejection could not be determined. While the installa-

tion of cameras in public places in Germany to pre-

vent crime is generally discussed controversially (cf.

van Heek et al., 2016a, b), the perception of camera

use in traffic and transportations systems seems to be

more homogeneous and positive. It is remarkable,

however, that the cameras’ capability to find traffic

offenders was considered as most important. This lo-

calizes the technology in the traditional context of

surveillance of criminal prosecution, while functions

that include optimization goals (e.g. saving travel

time or exonerating traffic) were perceived as less im-

portant. Also, these two functionalities support intel-

ligent transport systems to optimize specifically en-

ergy-saving and safety. This might indicate that the

participants’ mental concepts of a camera technology

somehow are still similar to conventional CCTV sys-

tems, and not yet fully adapted to the specificity of

intelligent transportation. Public communication pol-

icy as well as a sensible information strategy will

have to address this by explaining the new intelligent

functionalities to cope with the barriers, which were

perceived despite the majority approval of the tech-

nology.

Looking at these possible impediments to public

acceptance of the integration of camera-technology in

traffic infrastructure, especially statements dealing

with privacy and data protection provoked serious

concerns. Here, a clear resemblance towards other

privacy concerns in V2X-technology usage can be

identified (cf. Schmidt et al., 2015a), which directs to

the suggestion that privacy is one of the most promi-

nent acceptance factors for connected traffic-technol-

ogy. At first glance, it appears inconsistent that the

participants named the feeling of being monitored as

the most important drawback, while surveying and

identifying traffic offenders was rated as the most rel-

evant benefit. This “wash me, but don’t make me

wet”- mentality among laypeople clarifies the prob-

lem of finding the optimal balance during technology

development and application: Surveillance as the

most central and powerful skill of the cameras in in-

telligent transport systems is at the same time also the

function that causes the most concern. Future work

should provide a deeper insight into user require-

ments in more specific usage contexts and regarding

technical parameters, i.e., motion and behaviour de-

tection and analysis, and data handling, to be able to

parameterize the technology more fine-grained.

To understand the influence of user factors on the

perception of camera technology in intelligent trans-

portation scenarios, the individual affinity for tech-

nology was identified as an explanatory factor for

general acceptance. In previous studies, this attitude

had been found to significantly influence the ac-

ceptance of novel technology in general (cf. Calero

Valdez et al., 2017), but also in vehicle technology in

particular (cf. Schmidt et al., 2015a,b). However, the

close connection of technical self-confidence with

technology acceptance is on the one hand hardly sur-

prising and on the other, it was found that 80% of the

variance in the user ratings of the technology cannot

yet be explained. Concluding, the perception of bar-

riers appears very homogeneous and independent of

individual user factors in the present study. This con-

tradicts previous results regarding the effects of age

on the evaluation of camera technology in non-traffic

surveillance scenarios (cf. van Heek et al., 2016b) and

indicates (again) that findings about camera ac-

ceptance cannot be generalized by disregarding the

application context.

Consequently, further research is needed for a

better understanding of the explanatory factors and

the reasoning behind the users’ evaluation of camera

technology in transportation. Therefore, additional

individual attitudes and personality traits, e.g., the

need for security, the need for privacy, or the surveil-

lance anxiety, should be considered in future work.

The habit of getting used to cameras and the safety

culture of society might also play a role, which could

not yet be considered in the present study with a sam-

ple limited to Germany. Therefore, cross-cultural

comparisons including countries that are already fo-

cusing more on camera use in the public area are nec-

essary.

Pictures of You, Pictures of Me

377

Finally, the comparison of camera designs re-

vealed that integrated cameras should be preferred

over external ones. The integrated camera design was

perceived as more modern, friendly, beautiful and el-

egant. Even the assumption that internal cameras are

perceived as more observing, because they are hidden

and not obvious, could not be confirmed. The increas-

ing miniaturization and concealment of sensor and

camera systems and related ubiquitous computing

seems to be unproblematic for the acceptance of the

systems, at least in the present study.

ACKNOWLEDGEMENTS

The authors thank Emine Deveci, Kevin Wegener and

Florian Groh for their research assistance. This re-

search was supported by the project I2EASE, funded

by the German Federal ministry of Research and Ed-

ucation [under the reference number 16EMO012K].

Special thanks go to project partner OSRAM for tech-

nical know-how and visual material.

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