User Diverse Privacy Requirements for V2X-Technology

Quantitative Research on Context-Based Privacy Aspects

Teresa Schmidt, Ralf Philipsen and Martina Ziefle

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

Keywords: Mobility, V2X-Communication, User Diversity, Privacy, Intelligent Transportation System.

Abstract: The paper will show, how different types of users are evaluating privacy and data security differently

according to contextual differentiating traffic situations. The focus is hereby on an analysis of user types to

see, if general attributes towards data capture can be identified. User requirements are investigated in age,

gender, experience with driver assistance systems and technical affinity. Several significant effects like the

influence of prior experience increasing the willingness to share data in an traffic optimizing scenario could

be revealed. But results show also an undeniable reluctance towards sharing private data with other traffic

participants or companies. Traffic management such as police or the infrastructure itself are however entrusted

with various personal information and data.

1 INTRODUCTION

Integrating smart mobility in metropolitan areas and

urban city parts is an important step for a sustainable

supply of all residents, no matter age, health status or

distance to a city centre. With intelligent

transportation systems, not only the quality of life

would enhance, but also the feeling of care which is

taken to support and optimize the current situation of

urbanisation.

A large part of lived mobility takes place on the

street, more precisely in motorized personal transport

(MIV). On the MIV accounts for just over 80% of

passenger kilometers (PKM) measured in motorized

passenger transport performance (BMVI, 2014). In

2012 were the 914.6 billion passenger kilometers. In

the future, this type of transport should continue to

rise: Despite the stagnating population development

predicts the BMVI, among others due to increasing

travel distances, an increase in performance of the

MIV from 8.44% to 2030 compared to 2012.

Further, the number of traffic accident fatalities

(in Germany) increased – reportedly 335 people died

in road accidents in August 2015 (Destatis, 2015)

which shows an increase of 18.4% compared to

August 2014. A main goal is therefore to offer people

a safe and intelligent technology, which helps to

lower the number of traffic crashes by using it. By

implementing new, smart technologies like the

electronic stability control could be confirmed, that

this technology can be used to decrease car crashes

(Farmer, 2004, Breuer et al., 2007). In addition, the

integration of intelligent communication systems into

vehicles has the potential to further increase traffic

safety by exchanging sensor data between road users

and road infrastructure to broaden the information

base for decision making of drivers and autonomous

vehicles in safety critical situations (Picone et al.,

2015, Endsley and Garland, 2000). Moreover, the so-

called V2X-technology that make collaborative road

environments possible could lead to a more efficient

and more comfortable individual mobility.

While current research mainly focusses on

technical issues, for example the development of

specialised network technology (Ma et al., 2009,

Trivisonno et al., 2015, Wedel et al., 2009), there is

still little known about users’ demands on V2X-

technology. Most studies that take the user into

account concentrate on usability issues, e.g., data

visualization or transfer of control (simTD, 2013,

Rakotonirainy et al., 2014), but neglect the users’

requirements on the information exchange in traffic

conditions in general. The acceptance or willingness

to actively use V2X-technology or cooperate by

sharing (personal) data within transport systems is

incompletely explored so far.

Previous studies (Schmidt et al., 2015b) could

identify general concerns and drawbacks such as a

steadily growing distrust to share data. The more

personal data gets; the less willing are users to share

it with an intelligent traffic network.

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

User Diverse Privacy Requirements for V2X-Technology - Quantitative Research on Context-based Privacy Aspects.

In Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2016), pages 60-67

ISBN: 978-989-758-185-4

However, the influence of user diversity on the

acceptance of V2X-technology in general and the

information exchange in particular is still

insufficiently explored. The effect of user factors like

age or gender on technology acceptance in different

mobility contexts has been shown in previous studies

(Ziefle et al., 2014) and is expected to influence the

requirements for V2X-technology as well. In

addition, there might be context dependent

acceptance patterns, which should be taken into

account during technology development to increase

users’ acceptance.

2 METHOD

Based on a set of prior focus group studies, we

identified possible user scenarios to test the

appreciation of technical support in form V2X-

supported driving. The further empirical approach

reported here is the outcome of two surveys, which

were constructed to look closely into different types

of users in order to find acceptance patterns

dependent on specific traffic situations. Therefore,

aspects of privacy and data security were questioned.

2.1 The Survey

The online survey was divided into four main parts.

Demographics. The first section addressed

demographic data as well as information about the

previous experience (due to a job) with different

vehicles. Following a question about the driver’s

licence(s), the frequency of vehicle usage was

questioned. Then, the experience with smart vehicle

technology (brake assistant, lane assistant, automatic

parking, distance control and cruise control). Also,

the technical self-efficiency was measured (Beier,

1999), the individual confidence in one’s capability

to use technical devices.

Roadside Scenarios. In the second section, two

V2X traffic scenarios were introduced to help the

participants envision the possibilities of V2X-

technology actively. Here, we were able to fall back

on previous qualitative studies (cf. Schmidt et al.,

2015a) to differentiate between making driving more

comfortable via information visualization and make

driving more efficient by optimizing routes (e.g.

smart traffic light, re-arranging of order).

V2X-technology. A set of seven items (6-point

Likert scale, 5=full agreement) questioned the usage

of V2X-technology in form of which data would be

shared (see Table 1).

Table 1: Item example of approval of data collection.

What information about you or your

vehicle may be collected / would be shared?

- Current motion data

(e.g. position).

- Intention to move

(e.g. planned route in navigation system).

- Information of past trips

(e.g. average speed, preferred routes).

Type of road user (e.g. bus, pedestrian).

Vehicle specifications

(e.g. safety equipment).

- Demographic data of driver

(e.g. age, gender).

- Physiological data of driver

(e.g. reaction rate, emotional state).

- Other personal data of driver

(e.g. driving experience).

And a set of four items which questioned from

whom and how long the data may be stored (see Table

2).

Table 2: Item example of data handling and storage.

Who may collect information about you

(and your vehicle) and how long may the

collected information be used / stored?

- Local road users.

Capturing and

processing

Short-term

storage

Long-

term/permanent

storage

- Local road infrastructure

(e.g. traffic light system).

- Central servers of traffic

management

and public authorities.

- Central servers of

companies

(e.g. car manufacturer or

insurance companies).

Ranking. The last part of the survey conveyed a

ranking of six different factors due to their own

perception of importance: control, cost, comfort,

safety, privacy and time (saving).

2.2 Scenarios

Infotainment. The first scenario invited the

participants to envision a situation in which they are

the driver of a car in an unknown city. In need of

information about a place to eat or where the next

ATM is positioned.

This scenario includes the integration of all, most

of personalized value-added services that increase the

comfort, entertain or inform. The spectrum of

User Diverse Privacy Requirements for V2X-Technology - Quantitative Research on Context-based Privacy Aspects

possible applications is very versatile and ranges from

automated payment systems, the integration of games

and multimedia, information on local attractions to

personalized advertising. Manufacturing and

maintenance-oriented applications, such as automatic

software updates or the transmission of data on

vehicle condition to the favored workshop, are in the

literature partly its own category (Dressler et al.,

2014).

Figure 1: Infotainment. A car drives through an unknown

city and gets information via V2X-technology.

Traffic Optimization. Participants had to

envision the scenario in which they are again the

driver of a car. In this situation, they are driving on a

Figure 2: Traffic optimization. A car drives through an

unknown city and gets information via V2X-technology.

highway with a building site. Here, they need to

rearrange to another line with the zipper method.

Here, the smart vehicles or infrastructure use

applications that improve the flow of traffic. This

prevents traffic jams and environmental pollution can

be reduced by a reduced fuel consumption. Through

local networking of vehicles and infrastructure an

optimal, environmentally friendly driving behavior

can be recommended to the driver or warning signals

and traffic lights are switched according to the current

volume of traffic. The central processing of traffic

data allows an intelligent traffic and redirect

management.

2.3 Participants

In total 274 participants took part with an age range

of 17 to 70 years (Mean=33.02; Standard

Deviation=12.51). The gender distribution is

symmetrical with 137 men (50%) and 137 women

(50%). All participants hold a driving licence (age 17

holds a driving licence class B17, which corresponds

accompanied driving). The sample contains 45.4%

with a university degree (n=124), followed by 34.1%

with a technical college degree (n=93) and 12.1% did

vocational training (n=33) plus 4.4% stated another

level of education (n=12).

All participants reported a rather high technical

self-confidence with 3.70 / 5 (SD=1.16). Here, men

are slightly more technical affine (M=4.12; SD=0.98)

than women (M=3.29; SD=1.18).

For further research, users had to classify if they

used technical support systems (brake assistant, lane

assistant, automatic parking, distance control and

cruise control) in vehicles before. Here, the overall

sample has rather little experience M=1.82 (scale

form 0 = no experience to 5). Men have slightly more

experience (M=2.25; SD=1.61) than women

(M=1.39; SD=1.50).

3 RESULTS

In the following section the obtained results will be

presented in detail. First, the findings for both

scenarios based on the complete sample will be

reported. Afterwards, the effects of age, gender,

technical affinity and prior experience will be

introduced extensively.

3.1 General Findings

In a first step, we report a general evaluation about

which information of the user may be collected or in

VEHITS 2016 - International Conference on Vehicle Technology and Intelligent Transport Systems

other words which information the user is willing to

share with regard to the two scenarios introduced

above.

Infotainment. Among the more uncritical data,

which participants would mostly agree on sharing in

the context of gaining information while driving, is

type of road user (M=2,89, SD=2,10), current motion

data (M=2.76, SD=2.04) and intention to move

(M=2.50, SD=2.05). There is overall a lower

propensity to share information about past trips

(M=1.33, SD=1.75) and vehicle specifications

(M=1.16, SD=1.69). Most critical are demographic

data (M=0.86, SD=1.35), other personal data

(M=0.48, SD=1.05) or the physiological state of the

user (M=0.45, SD=1.01).

Traffic Optimization. In the second scenario are

similar findings identified. Here, current motion data

(M=3.49, SD=1.70) and type of road user (M=3.44,

SD=1.87) would be shared immediately, but the

intention to move is not perceived as uncritical data

(M=2.25, SD=2.01). Further, information about past

trips (M=1.50, SD=1.83) and vehicle specifications

(M=1.47, SD=1.85) would not be shared without

hesitation. The most critical data is again

demographic data (M=0.59, SD=1.21), physiological

data (M=0.58, SD=1.22) and other personal

information (M=0.54, SD=1.15) like driving

experience.

Storage and Duration. All participants had to

identify the tolerated duration of data storage and the

recipients, which should be allowed to store it. Figure

3 shows the findings.

As can be seen the most tolerated time span is

capture and process the data in the very moment of

the traffic situation (in all cases above 59.0%

agreement of all participants). The agreement scores

lower tremendously when asking about a short-term

storage (max. storage of one week), with scores from

16.1% to 26.6 %. Generally disliked is the long term

/ permanent storage of the data, here, the scores are in

all cases the lowest of the storage duration

possibilities.

Ranking. We asked participants to prioritize six

criterions according to perceived importance. The

results show that safety is the most important factor

(M=1.87, SD=1.10), followed by privacy (M=2.93,

SD=1.71) and control (M=3.10, SD=1.65). Saving

time (M=4.28, SD=1.41), cost (M=4.30, SD=1.22)

and comfort (M=4.49, SD=1.35) are evaluated with

less importance.

3.2 Age

In the following section age will be considered in

detail as the first of the examined user factors.

First, age had effects on the willingness to share

information in both scenarios: There was a significant

correlation between age and the agreement on

revealing demographic data in infotainment use cases

(p=.002, r=-.145). The older the participants were, the

more consent to limit the exchange of demographic

information could be observed. With regard to traffic

optimization scenarios, age influenced the

willingness to disclosure both the intention to move

(p=.006, r=.126) and the vehicle specifications

(p=.000, r=-167). Older participants tended to state

slightly higher agreement levels concerning the

sharing of intended movements than younger

participants and vice versa in regard to technical

information of the vehicle.

Second, age influenced the consent to long-term

data storage by infrastructure. This effect was

significant for traffic optimization scenarios with

F(2.243)=4.183, p=.016. The older the participants

were, the more willingness to accept longer storage

periods could be determined.



Table 3: Overall results of storage (who may keep the data) and duration time (how long may it be stored) in %.

Infotainment Optimization

Capturing

and

processing

Short-

term

storage

Long-

term

storage

Capturing

and

processin

Short-

term

storage

Long-

term

storage

Road user

78.9 16.1 4.9 223 76.9 18.7 4.4 251

Infrastructure

70.0 22.9 7.0 227 59.7 26.2 14.1 248

Traffic management

62.5 25.0 12.5 208 59.0 26.6 14.4 229

Companies

77.9 16.1 6.0 199 77.1 17.1 5.9 205

User Diverse Privacy Requirements for V2X-Technology - Quantitative Research on Context-based Privacy Aspects

Figure 3: Average ranks of V2X-evaluation criteria based on gender (1 = most important criteria, 6 = least important criteria).

Finally, several effects of age on the ranking of V2X

evaluation criteria could be determined: Age correlated

with the items control (p=.001, r=.123), comfort

(p=.001, r=-.150) and saving time (p=.000, r=-.183).

Therefore, comfort and the economy of time were more

important for older participants, while younger people

tended to attach higher importance to control aspects.

3.3 Gender

With regard to gender, only a few significant effects

were found. The willingness to disclosure which type of

road user someone is was higher in women (M=3.23,

SD=1.97) than in men (M=2.56, SD=2.19). This effect

was significant but small with t(274)=-2.640, p=.009,

d=.319 and limited to the infotainment scenario.

Moreover, there was no influence of gender on both the

willingness to share any other type of data and the

question who is allowed to store the information.

In view of the evaluation criteria a quite uniform

picture emerged. Both men and women rated safety,

privacy and control as the most important criteria for

evaluating V2X-technology. However, the ranking of

safety was more important for women (Mdn=1) than

for men (Mdn=2) with U=7664.5, Z=-2.831, p=.005,

r=-.174. A complete overview of gender-based

rankings can be found in Figure 3.

3.4 Technical Affinity

Infotainment. With regard to technical affinity, two

significant effects were found. The willingness to

share technical data decreases with a lower level of

technical affinity (r=.-105, p<.028). Also other

personal data about the driver decreases with a lower

technical affinity (r=.158, p<. 001).

Traffic Optimization. A close evaluation of the

results of the second scenario showed critical

significant differences in willingness to share data. A

lower level of technical affinity indicates on the one

hand a smaller propensity to share the current motion

data (r=.105, p<.024) and type of road user (r=.093,

p<.047). On the other hand, this group is more willing

to share physiological data about the driver (r=-.118,

p<.016) and other personal data (e.g. driving

experience) (r=-.128, p<.010).

Storage and Ranking. There were no significant

differences in the storage and duration of data with

regard to technical affinity. There were also no

significant differences in the ranking of the important

criteria.

3.5 Prior Experience

Infotainment. In this scenario, the group without any

prior experience denies to share any kind of data

except the information about what type of road user

they are (M=2,73, SD=2,11). The group with prior

experience however would share the type of road user

(M=3,09, SD=2,10), current motion data (M=3,04,

SD=2,05) and the intention to move (M=2,84,

4.20

4.63

4.26

3.11

3.03

1.75

4.41

4.35

4.29

3.08

2.84

1.99

123456

Cost

Comfort

Saving Time

Control

Privacy

Safety

Ranking

Women

Men

VEHITS 2016 - International Conference on Vehicle Technology and Intelligent Transport Systems

SD=2,11). The other types of data are denied by both

groups, which individually answered below an

arithmetic mean of 1,60 (below 2,50 = rejection).

Further, the unexperienced group showed

significantly lower scores in the following data types:

current motion data (t(265)=-2.208; p<.028),

intention to move (M=2,19, SD=1,99) (t(265)=-

2.579; p<.010) and information of past trips (M=1,09,

SD=1,54) (t(264)=-2.062; p<.040).

Traffic Optimization. The group without prior

experience and the group with prior experience would

both share what type of road user they are (M=3,15,

SD=1,97; M=3,86, SD=1,63) and the current motion

data (M=3,26, SD=1,79; M=3,83, SD=1,48). The

experienced group would also share their intention to

move (M=2,52, SD=2,12). As we can see in figure 4

the experienced group has higher agreement scores

overall. The only exception is the vehicle

specification (M=1,45, SD=1,88), which data both

groups do not want to share, but the unexperienced

slightly more (M=1,48, SD=1,84).

Here again, the assent of participants without

prior experience was significantly lower in four

different types of data, namely type of road user

(t(264)=-3.177; p<.002), current motion data

(t(265)=-2.832; p<.005), intention to move (M=2,03,

SD=1,91) (t(264)=-1.982; p<.049) and information of

past trips (M=1,21, SD=1,62) (t(265)=-2.767;

p<.006).

Storage and Ranking. The critical issue of

storing data did not show any significant differences

between the experience groups. There were no

significant differences in the ranking of the important

criteria with regard to prior experience.

4 DISCUSSION AND

CONCLUSION

The current study was directed to the diversity of

future V2X-technology users and their manifold

privacy issues regarding context-based traffic

scenarios. V2X-technology is focused by an

increasing research community, often regarding

technical issues (Ardelt, 2012, Lefevre, 2013).

Nevertheless, the most important factor for the

success of V2X-technology concepts is the user

himself and the public perception and acceptance in

order to gain enough trust regarding the conscientious

handling of personal data and private information

needed.

Figure 4: Arithmetic means of data sharing agreement differentiated by roadside scenario and prior experience.

0,69

0,64

0,68

1,45

1,83

2,52

3,83

3,86

0,45

0,48

1,48

1,21

2,03

3,26

3,15

0,51

0,52

0,95

1,08

1,53

2,84

3,04

3,09

0,38

0,43

0,74

1,18

1,09

2,19

2,49

2,73

012345

Physiological data of driver

Other personal data of driver

Demographic data of driver

Vehicle specifications

Information of past trips

Intention to move

Current motion data

Type of road user

Willingness to share data - scenarios traffic optimization & infotainment

Infotainment

Without prior

experience

Infotainment

Prior experience

Traffic Optimization

Without prior

experience

Traffic Optimization

Prior experience

full rejection

full agreement

User Diverse Privacy Requirements for V2X-Technology - Quantitative Research on Context-based Privacy Aspects

In order to get a first impression on what

information would be shared with this novel

technology, we used a well-educated, but diverse

sample. With a wide age range and a symmetrical

gender distribution, it was possible to take a closer

look on both user specifications. Further, the

participants were questioned about general and traffic

addressing information about themselves in order to

characterize the sample into diverse user types such

as prior experienced with driver assistance systems or

technical affinity - which we believe are key factors

for the acceptance of new intelligent technologies.

An introduction to two different traffic scenarios

set the focus towards a distinguishing level of

efficiency for daily traffic situations. In the

infotainment scenario, no further benefit except more

information about a city or a region could be gained.

Here we could identify that women are more willing

to share what type of road user they are. This can

maybe be connected to the fact, that saving time and

cost was more important to women in comparison to

men. Overall, the most important factor for all

participants regardless the group specifications was

safety – which validates past research results of

Schmidt et al. (2015a).

Further, the results of the infotainment scenario

show that also prior experience has effects on the

propensity to share data. To sum up, without prior

experience with driver assistance systems, almost no

data would be shared in general. Here we can

conclude, that more experienced drivers do

understand or trust in the possibility of an increasing

information support. Or it is possible that non-

experienced drivers simply mistrust the technology.

Comparing the amount of shared data of non

experienced drivers to the data a simple navigation

system uses – which is at least the direction in which

the driver is moving, speed and route – this finding is

rather surprising. For a situation without further

benefit as information support, they are not willing to

share information with the infrastructure. This leads

to the question, if traffic participants are generally

aware of current privacy situations (e.g. privacy

settings of a navigation system or application) and if

they are aware of how detailed the information is,

which is already shared with that kind of technology.

The second scenario showed the ability of V2X-

technology to increase the driving efficiency by

optimizing the behavior of all traffic participants.

Here could be identified that younger people tend to

be more curious about the disclosure of technical

information about their vehicle, whilst older people

have less concerns about their intention to move

(direction or destination). Regarding an overall look

at the data, the intention to move would not be shared

by the overall sample. This finding is extremely

confusing, because the optimization of traffic cannot

work without knowledge of the theoretical next

position of all traffic participants. Not sharing that

information would immediately interfere with the

given scenario. Further, even common technologies

like navigation systems need and receive the drivers’

intention to move via destination input and these are

frequently used support systems (Yamashita, 2004).

In comparison can be seen that physiological data,

demographic data and other person data would not be

shared by either one of the prior experience groups.

This is interesting, because people are not willing to

give too many information about themselves as

drivers to the infrastructure – not even for more

efficiency in the overall traffic behaviour. Here we

can see that privacy is very important, which can be

seen in the ranking of the V2X-evaluation criteria.

Nevertheless, we can see, that experience seems

to be a crucible factor of willingness to share data –

even more if there is a benefit in traffic behaviour and

not only more information. Bringing V2X step by

step to the user or even integrating users in the

development of the technology is therefore an

inevitable step for further research.

Another fruitful research topic could relate to the

different cultural attitudes with respect to safety and

data privacy – as different countries show different

legal and societal etiquette to handle this trade-off.

A very different outcome could be identified for

the question how long which data may be stored and

which authority may be allowed to store it. Neither

gender, nor prior experience or technical affinity have

any influence here. Only older people were willing to

accept longer periods of storage in the traffic

optimization scenario, which is the only effect

detected so far. This result leads to the conclusion that

duration (short-term storage is preferred in all

scenarios and groups) and storage are kinds of

universal factors. Here, no user diverse influence

could be found. In the cases of long-term storage,

there is an undeniable reluctance towards sharing

private data with companies or other traffic

participants on the one hand. One the other hand,

traffic management, such as police or the

infrastructure itself are however increasingly

entrusted with private information. Also surprising is

the result, that companies are entrusted with

information in the shortest duration possibility

(capturing and processing). The results show no

explanation for this outcome. Therefore, a closer

research may be able to identify possible reasons.

VEHITS 2016 - International Conference on Vehicle Technology and Intelligent Transport Systems

Also, the understanding of privacy and data

sharing in general should be questioned as well as

possible trade-offs and drawbacks. This would lead to

a deeper understanding about the already shared data

in persons daily lives out of the user’s perspective.

Further future research should also compare more

fatal roadside scenarios in order to see, if traffic

participants are willing to share personal data to

protect themselves and others.

ACKNOWLEDGEMENTS

We owe gratitude to the reviewers for their profound

input in an earlier version of this study. Many thanks

go to Jonas Hemsen for research assistance. This

project was supported by the Center of European

Research on Mobility (CERM) – funded by both

strategy funds at RWTH Aachen University,

Germany and the Excellence Initiative of German

State and Federal Government. Further, thanks go to

the project I2EASE, funded by the German Federal

ministry of Research and Education [under the

reference number 16EMO012K].

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