Alexander Meschtscherjakov

Towards Autonomous Cars: The Effect of Autonomy Levels on Acceptance and User Experience

Surveys [8] show that people generally have a positive attitude towards autonomous cars. However, these studies neglect that cars have different levels of autonomy and that User Acceptance (UA) and User Experience (UX) with autonomous systems differ with regard to the degree of system autonomy. The National Highway Traffic Safety Administration (NHTSA) defines five degrees of car autonomy which vary in the penetration of cars with Advanced Driver Assistance Systems (ADAS) and the extent to which a car is taken over by autonomous systems. Based on these levels, we conducted an online-questionnaire study (N = 336), in which we investigated how UA and UX factors, such as Perceived Ease of Use, Attitude Towards using the system, Perceived Behavioral Control, Behavioral Intention to use a system, Trust and Fun, differ with regard to the degree of autonomy in cars. We show that UA and UX are highest in levels of autonomy that already have been deployed in modern cars. More specifically, perceived control and fun decrease continuously with higher autonomy. Furthermore, our results indicate that pre-experience with ADAS and demographics, such as age and gender, have an influence on UA and UX.

Enhanced shopping: a dynamic map in a retail store

This article investigates the prototypical implementation of a dynamic map of a retail store and the results of an empirical study in the shopping environment. Due to the distinct characteristics of the context of shopping (e.g. openness to the public, preexisting technologies), this context is particularly fruitful for UbiComp technologies. The prototype consists of a display showing an enhanced store map, which combines the dynamic visualization of customer activity (e.g. hot-spots, sales ranks) with conventional map elements (e.g. product locations, promotions). The results of our three-day in-situ study indicate the relevance and the usefulness of UbiComp technologies for shopping environments.

Capture the car!: qualitative in-situ methods to grasp the automotive context

In terms of human computer interaction (HCI), the car interior is a space, which can be divided into three areas: the drivers area, the front seat area, and the back seat area. So far HCI researchers have primary focused on the driver, and how in-car electronic devices can be designed to assist the driver in order to increase safety and comfort. We propose that for investigating interactive technology in the car in a holistic way, all three areas have to be taken into account. For that purpose we argue for an increased usage of qualitative in-situ studies, which have been hardly applied in automotive user interface research. So far the HCI community has mainly focused on laboratory studies utilizing driving simulators. Despite the broad range of available field study methods, such as ethnographic and self-reporting studies, the adaption of these methods for the automotive context is challenging due to the specific characteristics of this environment. For instance, cars provide only very limited space, the environment is constantly changing while driving and the driver must not be distracted from driving safely. As a consequence, a lack of experience exists, on how in-situ methods should be applied to cars. In this paper we describe three qualitative in-situ studies, we conducted to research the driver, the front seat passenger, and the rear seat passenger spaces. All three studies used a different method tailored to fit these three areas best. To share our experiences and insights we discuss the strengths and pitfalls of each method.

Enhancing the shopping experience with ambient displays: a field study in a retail store

This paper discusses the prototypical implementation of an ambient display and the results of an empirical study in a retail store. It presents the context of shopping as an application area for Ambient Intelligence (AmI) technologies. The prototype consists of an ambient store map that enhances the awareness of customer activity. The results of our study indicate potentials and challenges for an improvement of the shopping experience with AmI technologies. Based on our findings we discuss challenges and future developments for applying AmI technologies to shopping environments.

Come drive with me: an ethnographic study of driver-passenger pairs to inform future in-car assistance

There is today a large number of ADAS used while driving. These systems are mainly technology driven and most often fail to make use of the social nature and the collaborative mechanisms between driver-passenger pairs. To inform the development of future automotive user interface designs we need to develop a deeper understanding of collaboration in general. In addition, we need to develop an understanding of how, and in what way, other platforms (e.g., the mobile phones) are and will be used in combination with these systems while driving. This paper presents the results of a participative ethnographic study with nine driver-passenger pairs recruited from two online car-sharing portals. Results are categorized in three areas: common ground as a base for successful in-car communication, types and strategies of front-seat passenger assistance, and lastly the impact of technology on collaboration.

Mobile attachment: emotional attachment towards mobile devices and services

In my thesis I address the topic of mobile attachment. I provide a theoretical framework for mobile attachment together with influencing factors that indicate users emotional attachment (EA) to mobile devices and services. I investigate how the concept of user experience (UX) and EA are linked together and I outline how user behavior driven experience sampling can be exploited to measure mobile attachment. My research will result in design suggestions how the creation of EA to mobile devices and services can be facilitated.

I need help!: exploring collaboration in the car

Today a huge number of different driving assistance and navigation systems are available on the market. Often these systems fail to take into account the social nature and collaborative mechanism of driving. This paper presents a two-month ethnographic study of drivers and passengers, with the goal of understanding social and collaborative in-car activities while driving to inform in-car navigation design. We found that human assistance and collaborative behavior varied among different contextual situations. Above that User Experience (UX) factors such as trust and perceived safety have a main influence on the type of front-seat passenger assistance and level of collaboration. Based on these observations we present a design approach for collaborative navigation devices that can be used to inform future research and practical applications in automobile collaboration.

Are we there yet? a probing study to inform design for the rear seat of family cars

When researching interactive systems in the car, the design space can be divided into the following areas: driver, front seat passenger and rear seat. The latter has so far not been sufficiently addressed in HCI research, which results in an absence of implications for interaction designs in that space. This work presents a cultural probing study investigating the activities and the technology usage in the rear seat as social and physical space. The study was conducted with 20 families over a period of four weeks and unveiled aspects relevant for HCI research: aspects of diversion, educational motivation, togetherness, food as activity, physical space, perception of safety, and mobile computing. In relation to these areas, implications for the design and integration of interactive technology in the rear seat area are deduced. We show that cultural probing in the car is a promising and fruitful approach to get insights on passenger behavior and requirements for interactive systems. To improve the rear seat area and to show the potential of probing results to inform design, a design proposal for an interactive rear seat game called RiddleRide is introduced.

ChaseLight: ambient LED stripes to control driving speed

In order to support drivers to maintain a predefined driving speed, we introduce ChaseLight, an in-car system that uses a programmable LED stripe mounted along the A-pillar of a car. The chase light (i.e., stripes of adjacent LEDs that are turned on and off frequently to give the illusion of lights moving along the stripe) provides ambient feedback to the driver about speed. We present a simulator based user study that uses three different types of feedback: (1) chase light with constant speed, (2) with proportional speed (i.e., chase light speed correlates with vehicle speed), and (3) with adaptive speed (i.e., chase light speed adapts to a target speed of the vehicle). Our results show that the adaptive condition is suited best to help a driver to control driving speed. The proportional speed condition resulted in a significantly slower mean speed than the baseline condition (no chase light).

Experiencing Autonomous Vehicles: Crossing the Boundaries between a Drive and a Ride

Autonomous vehicles have gained attention recently since research organizations and companies have presented (semi-) autonomous vehicles driving in public traffic. This workshop covers the crossover between driving/riding in (semi-) autonomous vehicles and user experience (UX) research. The focus lies in an in-depth discussion on challenges and potentials for UX in autonomous vehicles. We will explore various areas such as, user experience factors, interaction design issues, entertainment potentials, social driving, and methodological issues. Additionally, we envision building a bridge between the automotive community and the human-robot-interaction community, since we believe autonomous vehicles can be regarded as a very specific kind of a robot. The overall aim of the workshop is to discuss the future landscape for research within and across each of these areas.