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Scientific Publications
Berge, S. H., Hagenzieker, M., Farah, H., & de Winter, J. C. F. (2021). Do cyclists need HMIs in future automated traffic? An interview study. Manuscript submitted for review. Preprint available at: https://www.researchgate.net/publication/351229876_Do_cyclists_need_HMIs_in_future_automated_traffic_An_interview_study
Figalová, N., Delp, A. L., Nick, A., Chuang, L. L., Baumann, M., Pollatos, O. (2021). Alpha and Theta Power in Repeated Take-over Requests. Neuroergonomics Conference 2021. https://neuroergonomicsconference.um.ifi.lmu.de/wp-content/uploads/submissions/197.pdf
Muhammad, A. P. (2021). Methods and Guidelines for Incorporating Human Factors Requirements in Automated Vehicles Development. In REFSQ Workshops. http://ceur-ws.org/Vol-2857/ds1.pdf
Peng, C., Merat, N., Romano, R., Hajiseyedjavadi, F., Paschalidis, E., Wei, C., Radhakrishnan, V., Solernou, A., Forster, D., Boer, E. (2021). Drivers’ Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural? [Manuscript submitted for publication]. preprint:https://www.researchgate.net/publication/351786327_Drivers’_Evaluation_of_Different_Automated_Driving_Styles_Is_It_both_Comfortable_and_Natural
Tabone, W., De Winter, J. C. F., Ackermann, C., Bärgman, J., Baumann, M., Deb, S., Emmenegger, C., Habibovic, A., Hagenzieker, M., Hancock, P. A., Happee, R., Krems, J., Lee, J. D., Martens, M., Merat, N., Norman, D. A., Sheridan, T. B., & Stanton, N. A. (2021). Vulnerable road users and the coming wave of automated vehicles: Expert perspectives. Transportation Research Interdisciplinary Perspectives, 9, 100293. https://doi.org/10.1016/j.trip.2020.100293
Tabone, W., Lee, Y.M., Merat, N., Happee, R., & De Winter J.C.F., (2021). Towards future pedestrian-vehicle interactions: Introducing theoretically-supported AR prototypes. Proceedings of the 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. n-n). Leeds, United Kingdom. https://doi.org/10.1145/3409118.3475149
Zhang, C., Berger, C., & Dozza, M. (2020). Towards Understanding Pedestrian Behavior Patterns from LiDAR Data. SAIS Workshop 2020. http://www.chalmers.se/SiteCollectionDocuments/Centrum/CHAIR/SAIS2020/SAIS_2020_Zhang_et_al.pdf
Zhang, C., Berger, C., & Dozza, M. (2020). An End-to-End Network for the Prediction of Pedestrian Behavior from LiDAR Data. L3Pilot Summer School 2020, Poster. https://i-sense.iccs.gr/images/documents/announcements/L3Pilot_summerschool2020_ChiZhang_final.pdf
Zhang, C., Berger, C., & Dozza, M. (2021). Social-IWSTCNN: A Social Interaction-Weighted Spatio-Temporal Convolutional Neural Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios. 2021 IEEE Intelligent Vehicle Symposium (IV). https://arxiv.org/abs/2105.12436 .
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Scientific Presentations
Text and links
SHAPE-IT Deliverables
D1.1 Methodological framework for the modelling and empirical approaches
D2.1 An overview of current AV interface strategies
Other material
Posters presented at AutoUI 2021
Introduction video to SHAPE-IT
