SFB D02 Implicit Driving Cues

Partner

Professur für Arbeitswissenschaft und Innovationsmanagement (TU Chemnitz)

Förderung

Deutsche Forschungsgemeinschaft (DFG; Förderkennzeichen: 416228727 – SFB 1410)

Laufzeit

01/2020-06/2024

Beschreibung

Hauptziel des Projekts ist es, relevante Fahrsignale zu identifizieren und zu charakterisieren. Diese werden in verschiedenen Situationen als Grundlage für intuitives Fahrverhalten von automatisierten Fahrzeugen getestet, mit dem Ziel die Nutzerakzeptanz und den Nutzerkomfort zu unterstützen. Der Fokus des Projektes liegt in der Untersuchung der Fahrzeug-Fahrzeug-Kommunikation mit spezifischer Berücksichtigung impliziter Fahrsignale wie Fahrzeugbewegungen (z.B. Beschleunigung, Abbremsen). Die Forschungsfragen werden mittels verschiedener komplementärer Methoden, einer Sekundärdatenanalyse, einer naturalistischen Fahrstudie, Labor- und Onlinestudien mit Realfahrvideos, Fahrsimulatorstudien und einer Realfahrtstudie, untersucht. Die Forschungsergebnisse bilden die Grundlage für die technische Umsetzung intuitiven Fahrverhaltens in automatisierten Fahrzeugen, mit besonderem Fokus auf impliziten Fahrsignalen.

Publikationen, Vorträge, Poster

Hensch, A.-C., Beggiato, M., Hartwich, F., & Krems, J.F. (2024). Comparison of a test track and a video study on drivers’ gap acceptance as a basis for intuitive automated vehicle driving functions. Human Factors and Ergonomics Society Europe Chapter 2024 Annual Conference, April 16-19, Lübeck, Germany. https://www.hfes-europe.org/posters-2024/.

Hensch, A.-C., Beggiato, M., & Krems J. F. (2023). Drivers' gap acceptance during parking maneuvers as a basis for initiating driving actions in automated vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 92, 133–142. doi:10.1016/j.trf.2022.11.008.

Beggiato, M., Rauh, N., & Krems, J. (2022). Multi-camera Face Tracking for Estimating User’s Discomfort with Automated Vehicle Operations. In W. Karwowski, T. Ahram, M. Milicevic, D. Etinger, & K. Zubrinic (Eds.), Proceedings of the 4th International Conference on Human Systems Engineering and Design (IHSED2021), 23.-25. September 2021. doi:10.54941/ahfe1001104.

Dettmann, A., Hartwich, F., Roßner, P., Beggiato, M., Felbel, K., Krems, J., & Bullinger, A. C. (2021). Comfort or Not? Automated Driving Style and User Characteristics Causing Human Discomfort in Automated Driving. International Journal of Human–Computer Interaction, 37:4, 331-339, doi:10.1080/10447318.2020.1860518.

Dommel, P., Pichler, A., & Beggiato, M. (2021). Comparison of a Logistic and SVM Model to Detect Discomfort in Automated Driving. In D. Russo et al. (Eds.), Intelligent Human Systems Integration 2021, AISC 1322, pp. 44-49. Cham: Springer. doi:10.1007/978-3-030-68017-6_7.

Hensch, A.-C., Beggiato, M., & Krems J. F. (2022). Should I wait or should I go? - Deciphering Implicit Communication Cues for Cooperative Interactions in Left-Turn Scenarios. In 2022 IEEE International Conference on Computational Intelligence & Virtual Environments for Measurement Systems and Applications (CIVEMSA), ISBN 78-1-6654-3445-4.

Hensch, A.-C., Beggiato, M., & Krems, J. F. (2021). Predicting Lane Changes by Identifying Sequence Patterns of Implicit Communication Cues. In N. Stanton (Ed.), Advances in Human Aspects of Transportation. AHFE 2021. LNNS 270. pp. 3-10. Cham: Springer. doi:10.1007/978-3-030-80012-3_1.

Hensch, A.-C., Beggiato, M., & Krems J. F. (2021). Drive safely and comfortably – Gap Acceptance as a Basis for a user-centred Design of Driving Styles in Automated Vehicles. Proceedings of the 7th HUMANIST Conference, Greece, 26-27 October 2021. ISBN 978-2-9531712-6-6. Link Download.

Hensch, A.-C., Beggiato, M., Mandl, S., Strobel, A., & Krems, J. (2022). The interplay of personality traits with drivers' gap acceptance. In K. Plant & G. Praetorius (eds), Human Factors in Transportation. AHFE (2022) International Conference. AHFE Open Access, vol 60 (pp. 329–337). USA: AHFE International. doi:10.54941/ahfe10024641.

Hensch, A.-C., Beggiato, M., Schömann, M. X., & Krems, J. F. (2021). Different Types, Different Speeds – The Effect of Interaction Partners and Encountering Speeds at Intersections on Drivers’ Gap Acceptance as an Implicit Communication Signal in Automated Driving. In H. Krömker (Ed.), HCI in Mobility, Transport, and Automotive Systems. HCII 2021. LNCS 12791. pp. 517-528. Cham: Springer. doi:10.1007/978-3-030-78358-7_36.

Hensch, A.-C., Kreißig, I., Beggiato, M., & Krems, J. (2022). The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians’ Trust and Acceptance of Automated Vehicle Communication Signals. Frontiers in Psychology, 13, 272. doi:10.3389/fpsyg.2022.866475.

Hensch, A.-C., Kreißig, I., Beggiato, M., & Krems, J. (2022). The Effects of eHMI Failures on Elderly Participants’ Assessment of Automated Vehicle Communication Signals. In Ahram T. & Taiar R. (Eds.), Human Interaction, Emerging Technologies and Future Systems V. IHIET 2021. LNNS 319. (pp. 355-363). Cham: Springer. doi:10.1007/978-3-030-85540-6_45.

Kretzschmar, F., Beggiato, M., & Pichler, A. (2022). Detection of Discomfort in Autonomous Driving via Stochastic Approximation. In K. Plant & G. Praetorius (eds), Human Factors in Transportation. AHFE (2022) International Conference. AHFE Open Access, vol 60 (pp. 87–92). USA: AHFE International. doi:10.54941/ahfe1002437.

Schuler, K., Quante, L., Schießl, C., Beggiato, M., & Jahn, G. (2022). Communication between drivers in a road bottleneck scenario. In K. Plant & G. Praetorius (eds), Human Factors in Transportation. AHFE (2022) International Conference. AHFE Open Access, vol 60 (pp. 306–312). USA: AHFE International. doi:10.54941/ahfe1002461.

Todorovikj, S., Kettner, F., Brand, D., Beggiato, M., & Ragni, M. (2022). Predicting Individual Discomfort in Autonomous Driving. In J. Culbertson, A. Perfors, H. Rabagliati & V. Ramenzoni (eds.), Proceedings of the Annual Meeting of the Cognitive Science Society, 44. Retrieved from https://escholarship.org/uc/item/71n4f4cr