Jörg Preißinger

Near Field Communication (NFC) in an Automotive Environment

Near Field Communication (NFC) offers intuitive interactions between humans and vehicles. In this paper we explore different NFC based use cases in an automotive context. Nearly all described use cases have been implemented in a BMW vehicle to get experiences of NFC in a real in-car environment. We describe the underlying soft- and hardware architecture and our experiences in setting up the prototype.

Enhancement of Consumer Support in Retail Scenarios by Utilization of Semantic Product Memories

In this chapter, the utilization of Digital Product Memories (DPMs) in the retail domain is discussed. We demonstrate a complete retail-related usage scenario from a consumer perspective that begins with the preparation of a shopping list before the physical in-store shopping activity. Throughout the entire shopping process in the retail store, the DPM infrastructure effectively supports the consumer with appropriate product recommendations. It provides explicit and implicit access to the consumer’s user profile with different interaction modalities, e.g., via a display on the shopping cart or the consumer’s cell phone, and supports the payment and checkout process based on digital user representations stored on the consumer’s physical items such as his car key. In order to fully close the circle, we then conclude the discussion of DPM-based consumer support by analyzing the way home by car, as a DPM infrastructure in a car provides ample opportunities for driver assistance, including but not limited to monitoring the temperature in the car or finding an optimal route home that avoids roadworks in order to address the extra need for a shock-free ride for bought items such as raw eggs or bottles of champagne.

Using the Default Option Bias to Influence Decision Making While Driving

Gaining a better understanding of human–computer interaction in multiple-goal environments, such as driving, is critical as people increasingly use information technology to accomplish multiple tasks simultaneously. Extensive research shows that decision biases can be utilized as effective cues to guide user interaction in single-goal environments. This article is a first step toward understanding the effect of decision biases in multiple-goal environments. This study analyzed data from a field experiment during which a comparison was made between drivers’ decisions on parking lots in a single-goal environment and drivers’ decisions in a multiple-goal environment when being exposed to the default option bias. The article shows that the default option bias is effective in multiple-goal environments. The results have important implications for the design of human–computer interaction in multiple-goal environments.

Towards Identifying Contextual Factors on Parking Lot Decisions

The relevance of contextual factors that adapt in-car recommendations to the driver’s current situation is not yet fully understood. This paper presents a field study that has been conducted in order to identify relevant contextual factors of in-car parking lot recommender systems. Surprisingly, most contextual factors examined, i.e., weather, luggage, and traffic conditions, did not have a significant effect on the parking lot decision in the conducted field study. Only the urgency of the trip and the willingness to walk have significant effects on the decision outcome. Therefore, automobile manufacturers should focus on understanding the relevance of different contextual factors when developing user models for in-car recommender systems.