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@Inproceedings { AugJourneyCHI25,
    author = {Schramm, Robin Connor and Fedrizzi, Ginevra and Sasalovici, Markus and Freiwald, Jann Philipp and Schwanecke, Ulrich},
    title = {Augmented Journeys: Interactive Points of Interest for In-Car Augmented Reality},
    abstract = {As passengers spend more time in vehicles, the demand for non-driving related tasks (NDRTs) increases. In-car Augmented Reality (AR) has the potential to enhance passenger experiences by enabling interaction with the environment through NDRTs using world-fixed Points of Interest (POIs). However, the effectiveness of existing interaction techniques and visualization methods for in-car AR remains unclear. Based on a survey (N=110) and a pre-study (N=10), we developed an interactive in-car AR system using a video see-through head-mounted display to engage with POIs via eye-gaze and pinch. Users could explore passed and upcoming POIs using three visualization techniques: List, Timeline, and Minimap. We evaluated the system's feasibility in a field study (N=21). Our findings indicate general acceptance of the system, with the List visualization being the preferred method for exploring POIs. Additionally, the study highlights limitations of current AR hardware, particularly the impact of vehicle movement on 3D interaction.},
    status = {1},
    year = {2025},
    month = {4},
    DOI = {10.1145/3706598.3714323},
    booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (conditionally accepted)},
    publisher = {ACM},
    series = {CHI '25}
}

@Inproceedings { BlendingWorldsCHI25,
    author = {Schramm, Robin Connor and Sasalovici, Markus and Freiwald, Jann Philipp and Otto, Michael and Reinelt, Melissa and Schwanecke, Ulrich},
    title = {Blending the Worlds: World-Fixed Visual Appearances in Automotive Augmented Reality},
    abstract = {With the transition to fully autonomous vehicles, non-driving related tasks (NDRTs) become increasingly important, allowing passengers to use their driving time more efficiently. In-car Augmented Reality (AR) gives the possibility to engage in NDRTs while also allowing passengers to engage with their surroundings, for example, by displaying world-fixed points of interest (POIs). This can lead to new discoveries, provide information about the environment, and improve locational awareness. To explore the optimal visualization of POIs using in-car AR, we conducted a field study (N = 38) examining six parameters: positioning, scaling, rotation, render distance, information density, and appearance. We also asked for intention of use, preferred seat positions and preferred automation level for the AR function in a post-study questionnaire. Our findings reveal user preferences and general acceptance of the AR functionality. Based on these results, we derived UX-guidelines for the visual appearance and behavior of location-based POIs in in-car AR.},
    status = {1},
    year = {2025},
    month = {4},
    DOI = {10.1145/3706598.3713185},
    booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (conditionally accepted)},
    publisher = {ACM},
    series = {CHI '25}
}

@Inproceedings { BumpyRideCHI25,
    author = {Sasalovici, Markus and Zeqiri, Albin and Schramm, Robin Connor and Ariza Nu\~{n}ez, Oscar Javier and Jansen, Pascal and Freiwald, Jann Philipp and Colley, Mark and Winkler, Christian and Rukzio, Enrico},
    title = {Bumpy Ride? Understanding the Effects of External Forces on Spatial Interactions in Moving Vehicles},
    abstract = {As the use of Head-Mounted Displays in moving vehicles increases, passengers can immerse themselves in visual experiences independent of their physical environment. However, interaction methods are susceptible to physical motion, leading to input errors and reduced task performance. This work investigates the impact of G-forces, vibrations, and unpredictable maneuvers on 3D interaction methods. We conducted a field study with 24 participants in both stationary and moving vehicles to examine the effects of vehicle motion on four interaction methods: (1) Gaze\\&Pinch, (2) DirectTouch, (3) Handray, and (4) HeadGaze. Participants performed selections in a Fitts' Law task. Our findings reveal a significant effect of vehicle motion on interaction accuracy and duration across the tested combinations of Interaction Method x Road Type x Curve Type. We found a significant impact of movement on throughput, error rate, and perceived workload. Finally, we propose future research considerations and recommendations on interaction methods during vehicle movement.},
    status = {1},
    year = {2025},
    month = {4},
    DOI = {10.1145/3706598.3714077},
    booktitle = {Proceedings of the CHI 2025 (SIGCHI Conference on Human Factors in Computing Systems)},
    publisher = {ACM},
    series = {CHI '25},
    file_url = {t3://file?uid=525741}
}

@Article { 842835642096_2024,
    author = {Stampf, Annika and Sasalovici, Markus and Meinhardt, Luca-Maxim and Colley, Mark and Giss, Marcel and Rukzio, Enrico},
    title = {Move, Connect, Interact: Introducing a Design Space for Cross-Traffic Interaction},
    year = {2024},
    month = {9},
    DOI = {10.1145/3678580},
    journal = {Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (IMWUT)},
    publisher = {ACM},
    address = {New York, NY, USA},
    file_url = {t3://file?uid=495723}
}

@Inbook { sasalovici22ki,
    author = {Sasalovici, Markus},
    title = {Algorithmisch automatisierte Artwork Generation im Netflix Empfehlungssystem},
    abstract = {Das Unternehmen Netflix stellt heutzutage eine bekannte Gr\"{o}\"{s}e im Bereich der Produktion, B\"{u}ndelung und Distribution von Medieninhalten dar. Der 1997 gegr\"{u}ndete Videostreaming-Dienst hat sich als wandlungsf\"{a}higes Unternehmen erwiesen, welches sich unter Anwendung neuer Technologien stetig weiterentwickelt. Dabei sieht sich das Unternehmen mittlerweile einem starken Wettbewerb anderer Anbieter, wie beispielsweise Disney+ oder Amazon Prime Video, ausgesetzt. Die Zielsetzung liegt deswegen darin, Kunden f\"{u}r einen m\"{o}glichst langen Zeitraum an die eigene Plattform zu binden und deren dauerhafte Zufriedenheit sicherzustellen. In diesem Zusammenhang werden in diesem Kapitel drei \"{o}konomische Herausforderungen f\"{u}r Netflix, sowie L\"{o}sungsans\"{a}tze f\"{u}r diese \"{o}konomischen Bezugsprobleme mittels automatisch generierter und personalisierter Thumbnails, thematisiert.},
    year = {2022},
    month = {11},
    day = {01},
    language = {deutsch},
    isbn = {978-3-658-37404-4},
    DOI = {10.1007/978-3-658-37404-4\_3},
    booktitle = {Algorithmisch automatisierte Artwork Generation im Netflix Empfehlungssystem},
    edition = {1},
    publisher = {Springer Fachmedien},
    address = {Wiesbaden},
    editor = {Zydorek, Christoph},
    pages = {57-85},
    keywords = {sasalovici22ki},
    web_url = {https://doi.org/10.1007/978-3-658-37404-4\_3 \_blank - \dqLink zu DOI\dq}
}