André Dahlinger

Preventing Traffic Accidents with In-Vehicle Decision Support Systems – The Impact of Accident Hotspot Warnings on Driver Behaviour

Despite continuous investment in road and vehicle safety, as well as improvements in technology standards, the total amount of road traffic accidents has been increasing over the last decades. Consequently, identifying ways of effectively reducing the frequency and severity of traffic accidents is of utmost importance. In light of the depicted challenge, latest studies provide promising evidence that in-vehicle decision support systems (DSSs) can have significant positive effects on driving behaviour and collision avoidance. Going beyond existing research, we developed a comprehensive in-vehicle DSS, which provides accident hotspot warnings to drivers based on location analytics applied to a national historical accident dataset, composed of over 266,000 accidents. As such, we depict the design and field evaluation of an in-vehicle DSS, bridging the gap between real world location analytics and in-vehicle warnings. The system was tested in a country-wide field test of 57 professional drivers, with over 170,000km driven during a four-week period, where vehicle data were gathered via a connected car prototype system. Ultimately, we demonstrate that in-vehicle warnings of accident hotspots have a significant improvement on driver behaviour over time. In addition, we provide first evidence that an individuals personality plays a key role in the effectiveness of in-vehicle DSSs. However, in contrast to existing lab experiments with very promising results, we were unable to find an immediate effect on driver behaviour. Hence, we see a strong need for further field experiments with high resolution car data to confirm that in-vehicle DSSs can deliver in diverse field situations.

A Crowd Sensing Approach to Video Classification of Traffic Accident Hotspots

Despite various initiatives over the recent years, the number of traffic accidents has been steadily increasing and has reached over 1.2 million fatalities per year world wide. Recent research has highlighted the positive effects that come from educating drivers about accident hotspots, for example, through in-vehicle warnings of upcoming dangerous areas. Further, it has been shown that there exists a spatial correlation between to locations of heavy braking events and historical accidents. This indicates that emerging accident hotspots can be identified from a high rate of heavy braking, and countermeasures deployed in order to prevent accidents before they appear. In order to contextualize and classify historic accident hotspots and locations of current dangerous driving maneuvers, the research at hand introduces a crowd sensing system collecting vehicle and video data. This system was tested in a naturalistic driving study of 40 vehicles for two months, collecting over 140,000 km of driving data and 36,000 videos of various traffic situations. The exploratory results show that through applying data mining approaches it is possible to describe these situations and determine information regarding the involved traffic participants, main causes and location features. This enables accurate insights into the road network, and can help inform both drivers and authorities.

The Impact of Abstract vs. Concrete Feedback Design on Behavior Insights from a Large Eco-Driving Field Experiment

About 17% of the worldwide CO2-emissions can be ascribed to road transportation. Using information systems (IS)-enabled feedback has shown to be very efficient in promoting a less fuel-consuming driving style. Today, in-car IS that provide feedback on driving behavior are in the midst of a fundamental change. Increasing digitalization of in-car IS enables virtually any kind of feedback. Still, we see a gap in the empirical evidence on how to leverage this potential, raising questions on future HCI-based feedback design. To address this knowledge gap, we designed an eco-driving feedback IS and, building upon construal level theory, hypothesize that abstract feedback is more effective in reducing fuel consumption than concrete feedback. Deployed in a large field experiment with 56 participants covering over 297,000km, we provide first empirical evidence that supports this hypothesis. Despite its limitations, this research may have general implications for the design of real-time feedback.

Smile or Cry?: The Impact of a Victim's Facial Expression on Helping Behavior in Emergency Applications

Todays wide spread of smartphones bares high potential for the effectiveness of emergency or helping applications. But helping is a complex psycho-social process. This has important implications for the UI design of such applications. In our research, we tested the effect of a victims facial expression (sad vs. happy) on a potential helpers willingness to help in an online scenario. We further investigated, how the facial expression interacts with another well researched social phenomenon: the bystander effect. The results of this early research were mostly not as expected, but reveal interesting insights that are discussed and that open an exciting research avenue with important practical implications when it comes to the design of digital helping systems.

Design Science in Practice: Design and Evaluation of an Art Based Information System to Improve Indoor Air Quality at Schools

Indoor air quality has a significant effect on human performance. In addition, many health issues can be traced back to bad indoor room-climate. However, especially in Europe, pupils spend a majority of their learning life in school classes affected by poor room climate. Without an automatic heating, ventilation and air conditioning system these pupils and their teachers have to rely on manual ventilation by opening windows. Thereby, they often lack fundamental room climate quality information to effectively guide their behavior. Information systems IS and sensor technology can be a remedy to these challenges. Existing room climate monitoring systems regularly reveal major shortcomings, e.g. in respect to user interfaces, presentation of data, and systematic engagement. We want to address the aforementioned shortcomings and present an art IS, which reflects room conditions in real time through modifications of depicted art. The artifact is evaluated in a field experiment, conducted in an Austrian grammar school. The evaluation reveals that room climate measured in CO2 can indeed be improved significantly. In addition, pupils also perceive a significant room climate improvement.