12: Adjunct Proceedings - Automotive User Interfaces and ...

term for systems which support collaborative activities inside the
car. It differs from current ADAS (Advanced Driver Assistance
Systems) which supports the driver in the driving process (e.g.,
lane departure warning system or adaptive cruise control).
Contrary, we define ACDAS as a system which permits
collaborative activities between driver, front-seat passengers or
other passengers. The aim of such systems is to support the codriver
in a way that he is able to assist the driver in a collaborative
way and to let him get back into his loop (i.e., be able to have full
concentration on the driving task).
In order to develop a deeper understanding of human assistance
and collaborative activities in cars, we conducted a two-month
participatory, ethnographic study of nine driver-passenger-pairs
recruited through an online car-sharing community from February
to March 2011 [16]. In this paper, we present specific findings for
the collaboration between driver and passenger, concentrating on
two of the most prominent technologies in modern cars, the GPS
system and the speedometer.
2. BACKGROUND
This chapter discusses the scientific foundations on which we
base our investigation of social and collaborative behavior within
the automotive context. It also gives a short overview of
ethnographic fieldwork in the automotive domain.
2.1 Social Assistance and Collaboration in the
Car
Forefront approaches [e.g., 12] in the field of technical automation
deal with the advantages of human behavior in relation to the
performance of machines. Thus, it has become important to
understand which kind of tasks should be operated by humans and
which tasks could be automated and handled by machines [e.g.,
21]. Wandke [21] proposes to define assistance as access to
machine functions and provides a taxonomy based on action
stages to be assisted. These stages are: (1) motivation, activation
and goal setting (2) perception (3) information integration or
generating situation awareness (4) decision-making or action
selection (5) action execution, and (6) processing feedback of
action results. Such social assistance episodes are triggered by
contextual cues [8]. A contextual cue signals to a person that an
action or event may occur. An example within the car context is in
how the front-seat passenger experiences the traffic situation as
dangerous and assumes that the driver is not able to solve the
problem without assistance. Then it could be, that the front-seat
passenger supports the driver by, for example, operating the
navigation system. In such situations, collaboration between
drivers and front-seat passengers is of high relevance as
highlighted by Forlizzi and colleagues [7]. Their results indicate
the importance of accessibility and flexibility of information
based on the intervention of front-seat passenger assistance. What
we propose in this paper is not just assistance but more of
collaborative usage of these systems.
2.2 Ethnographic Approaches in the
Automotive Domain
There have been several ethnographic studies investigating the
relationship between the city and the car [19], the family and the
car [20], and the pleasures of listening to music in the car [3].
Studies such as [1,4,5,11,14] encourage the benefits of studying
interior related aspects with an ethnographic approach. One
example is the ethnographic study conducted in 2007 by
Esbjörnson and colleagues that focused on the usage of mobile
phones in vehicles [5]. Oskar Juhlin and colleagues [4] take a
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Adjunct Proceedings of the 4th International Conference on Automotive User Interfaces and
Interactive Vehicular Applications (AutomotiveUI '12), October 17–19, 2012, Portsmouth, NH, USA
broader engagement on driving and design and has designed a
series of games and systems for the social experiences of driving
(e.g., pervasive games). Their fieldwork underlines the ways in
which driving is a process whereby road users “solve coordination
problems with other road users and try to influence each other”
[11, p.49]. The use of GPS was discussed in [1,15]. Leshed and
colleagues [15] present an ethnographically informed study with
GPS users, showing evidence for practices of disengagement as
well as new opportunities for engagement. Brown and Laurier [1]
identify five types of troubles where GPS systems cause issues
and confusion for drivers. Bubb [2] emphasizes that it may be
helpful for developing future ADAS to learn more about human
assistance during real driving conditions. Our paper argues how in
order to design future ADAS, we need to go back to the routes
and nature of human assistance.
3. STUDY
Our study took place from January to March, 2011. Nine driverpassenger
pairs were recruited from an online car-sharing
community. We looked for routes at the car-sharing platform that
started and ended in our vicinity. Based on the information of the
car-sharing platform, we called participants that regularly drove
those routes with other passengers. Participants were aged
between 20 and 32 years (27,9 in average); 7 male and 2 female
drivers. The nature of the car-sharing community enabled us to
observe collaboration on various topics and between people with
different relationships. Four of the nine driver-passenger pairs met
each other through the community. Two of them were either
friends or students fellow. The rest of them (three) had a solid
relationship.
To investigate human assistance, a researcher joined participants
by sitting in in the backseat. The researcher observed and
conversed with the driver-passenger pair. Paper and pencil was
used to log situations. Although we acknowledge the advantages
of technical support such as video, we wanted to observe realinteraction
without additional technical artifacts. Thus, the
researcher gets more involved and has no social distance to
participants. Technical devices could cause artificial behavior of
the driver-passenger pair and could also distract the driver. In
addition, we wanted the trips to be as natural as possible without
delaying departure by installing any equipment. We wished to use
the car-sharing platform as unobtrusive as possible.
All drivers were registered on the car-sharing website. One of
them tested a car-sharing platform for the first time. The
participants drove different cars such as Audi A3, BMW1,
Peugeot 207, Volkswagen Polo, or Mercedes Vito. Four out of
nine drivers used a mobile navigation device. In one specific case
the driver had a laptop mounted on the center stack with Google
Earth running.
4. RESULTS
The observed episodes collected in our study were analyzed using
an interaction analysis approach [9]. Two researchers classified
each observation into three categories: highway assistance (127
assistance episodes), assistance on rural roads (28 assistance
episodes), and assistance on urban streets (41 assistance episodes).
They clustered the noted assistance episodes and actions for
comparison in terms of similarities. The recorded material
represented patterns of behavior, triggers, and context factors that
influenced the human assistance and level of collaboration while
driving. Finally, we reflected on the results and triangulated them
to confirm ideas. This resulted in four categories: types of frontseat
passenger assistance, user experience related to human
assistance, context factors and triggers for supporting the driver,