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Effects of Uncertain Trajectory Prediction Visualization in Highly Automated Vehicles on Trust, Situation Awareness, and Cognitive Load

Published: 12 January 2024 Publication History

Abstract

Automated vehicles are expected to improve safety, mobility, and inclusion. User acceptance is required for the successful introduction of this technology. One essential prerequisite for acceptance is appropriately trusting the vehicle's capabilities. System transparency via visualizing internal information could calibrate this trust by enabling the surveillance of the vehicle's detection and prediction capabilities, including its failures. Additionally, concurrently increased situation awareness could improve take-overs in case of emergency. This work reports the results of two online comparative video-based studies on visualizing prediction and maneuver-planning information. Effects on trust, cognitive load, and situation awareness were measured using a simulation (N=280) and state-of-the-art road user prediction and maneuver planning on a pre-recorded real-world video using a real prototype (N=238). Results show that color conveys uncertainty best, that the planned trajectory increased trust, and that the visualization of other predicted trajectories improved perceived safety.

References

[1]
Volkswagen AG. 2020. Head-up-Display. https://www.volkswagen-newsroom.com/de/head-up-display-3957. [Online; accessed: 07-AUGUST-2021].
[2]
Jason Antic. 2021. DeOldify. https://github.com/jantic/DeOldify. [Online; accessed: 05-AUGUST-2021].
[3]
Tirthankar Bandyopadhyay, Kok Sung Won, Emilio Frazzoli, David Hsu, Wee Sun Lee, and Daniela Rus. 2013. Intention-Aware Motion Planning. In Algorithmic Foundations of Robotics X, Emilio Frazzoli, Tomas Lozano-Perez, Nicholas Roy, and Daniela Rus (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 475--491.
[4]
Johannes Beller, Matthias Heesen, and Mark Vollrath. 2013. Improving the Driver--Automation Interaction: An Approach Using Automation Uncertainty. Human Factors 55, 6 (2013), 1130--1141. https://doi.org/10.1177/0018720813482327 arXiv:https://doi.org/10.1177/0018720813482327 24745204.
[5]
Mattan S. Ben-Shachar, Daniel Lüdecke, and Dominique Makowski. 2020. effectsize: Estimation of Effect Size Indices and Standardized Parameters. Journal of Open Source Software 5, 56 (2020), 2815. https://doi.org/10.21105/joss.02815
[6]
S. Brandenburg and E. M. Skottke. 2014. Switching from manual to automated driving and reverse: Are drivers behaving more risky after highly automated driving?. In 17th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE, New York, NY, USA, 2978--2983. https://doi.org/10.1109/ITSC.2014.6958168
[7]
Kelly Caine. 2016. Local Standards for Sample Size at CHI. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '16). Association for Computing Machinery, New York, NY, USA, 981--992. https://doi.org/10.1145/2858036.2858498
[8]
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, et al. 2019. Argoverse: 3d tracking and forecasting with rich maps. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, New York, NY, USA, 8748--8757.
[9]
Bike Chen, Chen Gong, and Jian Yang. 2018. Importance-aware semantic segmentation for autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems 20, 1 (2018), 137--148. https://doi.org/10.1109/TITS.2018.2801309
[10]
Fang Chen. 2013. Effects of cognitive load on trust. Technical Report. NATIONAL INFORMATION COMMUNICATION TECHNOLOGY AUSTRALIA LTD EVELEIGH.
[11]
Mark Colley, Ali Askari, Marcel Walch, Marcel Woide, and Enrico Rukzio. 2021. ORIAS: On-The-Fly Object Identification and Action Selection for Highly Automated Vehicles. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. Association for Computing Machinery, New York, NY, USA, 79--89. https://doi.org/10.1145/3409118.3475134
[12]
Mark Colley, Christian Bräuner, Mirjam Lanzer, Marcel Walch, Martin Baumann, and Enrico Rukzio. 2020. Effect of Visualization of Pedestrian Intention Recognition on Trust and Cognitive Load. In 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Virtual Event, DC, USA) (AutomotiveUI '20). ACM, Association for Computing Machinery, New York, NY, USA, 181--191. https://doi.org/10.1145/3409120.3410648
[13]
Mark Colley, Julian Britten, Simon Demharter, Tolga Hisir, and Enrico Rukzio. 2022. Feedback Strategies for Crowded Intersections in Automated Traffic --- A Desirable Future?. In Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Seoul, Republic of Korea) (AutomotiveUI '22). Association for Computing Machinery, New York, NY, USA, 243--252. https://doi.org/10.1145/3543174.3545255
[14]
Mark Colley, Benjamin Eder, Jan Ole Rixen, and Enrico Rukzio. 2021. Effects of Semantic Segmentation Visualization on Trust, Situation Awareness, and Cognitive Load in Highly Automated Vehicles. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI '21). Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3411764.3445351
[15]
Mark Colley, Pascal Jansen, Enrico Rukzio, and Jan Gugenheimer. 2022. SwiVR-Car-Seat: Exploring Vehicle Motion Effects on Interaction Quality in Virtual Reality Automated Driving Using a Motorized Swivel Seat. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 4, Article 150 (dec 2022), 26 pages. https://doi.org/10.1145/3494968
[16]
Mark Colley, Svenja Krauß, Mirjam Lanzer, and Enrico Rukzio. 2021. How Should Automated Vehicles Communicate Critical Situations? A Comparative Analysis of Visualization Concepts. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 3, Article 94 (2021), 23 pages. https://doi.org/10.1145/3478111
[17]
Mark Colley, Max Rädler, Jonas Glimmann, and Enrico Rukzio. 2022. Effects of Scene Detection, Scene Prediction, and Maneuver Planning Visualizations on Trust, Situation Awareness, and Cognitive Load in Highly Automated Vehicles. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 2, Article 49 (jul 2022), 21 pages. https://doi.org/10.1145/3534609
[18]
Mark Colley and Enrico Rukzio. 2020. A Design Space for External Communication of Autonomous Vehicles. In Proceedings of the 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '20). ACM, Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3409120.3410646
[19]
Mark Colley, Marcel Walch, Jan Gugenheimer, and Enrico Rukzio. 2019. Including People with Impairments from the Start: External Communication of Autonomous Vehicles. In Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings (Utrecht, Netherlands) (AutomotiveUI '19). Association for Computing Machinery, New York, NY, USA, 307--314. https://doi.org/10.1145/3349263.3351521
[20]
Mark Colley, Dennis Wolf, Sabrina Böhm, Tobias Lahmann, Luca Porta, and Enrico Rukzio. 2021. Resync: Towards Transferring Somnolent Passengers to Consciousness. In Adjunct Publication of the 23rd International Conference on Mobile Human-Computer Interaction (Toulouse & Virtual, France) (MobileHCI '21). Association for Computing Machinery, New York, NY, USA, Article 1, 6 pages. https://doi.org/10.1145/3447527.3474847
[21]
Michael Correll, Dominik Moritz, and Jeffrey Heer. 2018. Value-Suppressing Uncertainty Palettes. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1--11. https://doi.org/10.1145/3173574.3174216
[22]
Henrik Detjen, Sarah Faltaous, Bastian Pfleging, Stefan Geisler, and Stefan Schneegass. 2021. How to increase automated vehicles' acceptance through in-vehicle interaction design: A review. International Journal of Human--Computer Interaction 37, 4 (2021), 308--330. https://doi.org/10.1080/10447318.2020.1860517 arXiv:https://doi.org/10.1080/10447318.2020.1860517
[23]
Debargha Dey, Marieke Martens, Chao Wang, Felix Ros, and Jacques Terken. 2018. Interface Concepts for Intent Communication from Autonomous Vehicles to Vulnerable Road Users. In Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Toronto, ON, Canada) (AutomotiveUI '18). Association for Computing Machinery, New York, NY, USA, 82--86. https://doi.org/10.1145/3239092.3265946
[24]
Frederik Diederichs, Tobias Schüttke, and Dieter Spath. 2015. Driver intention algorithm for pedestrian protection and automated emergency braking systems. In 2015 IEEE 18th International Conference on Intelligent Transportation Systems. IEEE, IEEE, New York, NY, USA, 1049--1054.
[25]
Liza Dixon. 2020. Autonowashing: The greenwashing of vehicle automation. Transportation research interdisciplinary perspectives 5 (2020), 100113.
[26]
Na Du, Jacob Haspiel, Qiaoning Zhang, Dawn Tilbury, Anuj K. Pradhan, X. Jessie Yang, and Lionel P. Robert. 2019. Look who's talking now: Implications of AV's explanations on driver's trust, AV preference, anxiety and mental workload. Transportation Research Part C: Emerging Technologies 104 (2019), 428--442. https://doi.org/10.1016/j.trc.2019.05.025 ID: 271729.
[27]
Fredrick Ekman, Mikael Johansson, and Jana Sochor. 2018. Creating Appropriate Trust in Automated Vehicle Systems: A Framework for HMI Design. IEEE Transactions on Human-Machine Systems 48, 1 (2018), 95--101. https://doi.org/10.1109/THMS.2017.2776209
[28]
Mica R Endsley. 1995. Measurement of situation awareness in dynamic systems. Human factors 37, 1 (1995), 65--84.
[29]
Mica R Endsley, Stephen J Selcon, Thomas D Hardiman, and Darryl G Croft. 1998. A comparative analysis of SAGAT and SART for evaluations of situation awareness. In Proceedings of the human factors and ergonomics society annual meeting, Vol. 42. SAGE Publications Sage CA: Los Angeles, CA, SAGE Publications, Los Angeles, CA, USA, 82--86.
[30]
Stefanie M. Faas, Andrea C. Kao, and Martin Baumann. 2020. A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle -- Pedestrian Interaction. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI '20). Association for Computing Machinery, New York, NY, USA, 1--14. https://doi.org/10.1145/3313831.3376484
[31]
Daniel J Fagnant and Kara Kockelman. 2015. Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transportation Research Part A: Policy and Practice 77 (2015), 167--181.
[32]
Franz Faul, Edgar Erdfelder, Axel Buchner, and Albert-Georg Lang. 2009. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior research methods 41, 4 (2009), 1149--1160.
[33]
Anna-Katharina Frison, Philipp Wintersberger, Andreas Riener, Clemens Schartmüller, Linda Ng Boyle, Erika Miller, and Klemens Weigl. 2019. In UX We Trust: Investigation of Aesthetics and Usability of Driver-Vehicle Interfaces and Their Impact on the Perception of Automated Driving. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19). Association for Computing Machinery, New York, NY, USA, 1--13. https://doi.org/10.1145/3290605.3300374
[34]
David C. Funder and Daniel J. Ozer. 2019. Evaluating Effect Size in Psychological Research: Sense and Nonsense. Advances in Methods and Practices in Psychological Science 2, 2 (2019), 156--168. https://doi.org/10.1177/2515245919847202 arXiv:https://doi.org/10.1177/2515245919847202
[35]
J. L. Gabbard, G. M. Fitch, and H. Kim. 2014. Behind the Glass: Driver Challenges and Opportunities for AR Automotive Applications. Proc. IEEE 102, 2 (2014), 124--136.
[36]
Maximilian Josef Graf, Oliver Michael Speidel, Jona Ruof, and Klaus Dietmayer. 2021. On-Road Motion Planning for Automated Vehicles at Ulm University. 2--12 pages. https://doi.org/10.1109/MITS.2021.3084534
[37]
Kunal Gupta, Ryo Hajika, Yun Suen Pai, Andreas Duenser, Martin Lochner, and Mark Billinghurst. 2019. In AI We Trust: Investigating the Relationship between Biosignals, Trust and Cognitive Load in VR. In Proceedings of the 25th ACM Symposium on Virtual Reality Software and Technology (Parramatta, NSW, Australia) (VRST '19). Association for Computing Machinery, New York, NY, USA, Article 33, 10 pages. https://doi.org/10.1145/3359996.3364276
[38]
Renate Haeuslschmid, Yixin Shou, John O'Donovan, Gary Burnett, and Andreas Butz. 2016. First Steps towards a View Management Concept for Large-Sized Head-up Displays with Continuous Depth. In Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Ann Arbor, MI, USA) (Automotive'UI 16). Association for Computing Machinery, New York, NY, USA, 1--8. https://doi.org/10.1145/3003715.3005418
[39]
Sandra G Hart and Lowell E Staveland. 1988. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In Advances in psychology. Vol. 52. Elsevier, Amsterdam, The Netherlands, 139--183.
[40]
Renate Häuslschmid, Max von Bülow, Bastian Pfleging, and Andreas Butz. 2017. Supporting Trust in Autonomous Driving. In Proceedings of the 22nd International Conference on Intelligent User Interfaces (Limassol, Cyprus) (IUI '17). Association for Computing Machinery, New York, NY, USA, 319--329. https://doi.org/10.1145/3025171.3025198
[41]
Tove Helldin, Göran Falkman, Maria Riveiro, and Staffan Davidsson. 2013. Presenting System Uncertainty in Automotive UIs for Supporting Trust Calibration in Autonomous Driving. In Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Eindhoven, Netherlands) (AutomotiveUI '13). Association for Computing Machinery, New York, NY, USA, 210--217. https://doi.org/10.1145/2516540.2516554
[42]
Philipp Hock, Mark Colley, Ali Askari, Tobias Wagner, Martin Baumann, and Enrico Rukzio. 2022. Introducing VAMPIRE -- Using Kinaesthetic Feedback in Virtual Reality for Automated Driving Experiments. In Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Seoul, Republic of Korea) (AutomotiveUI '22). Association for Computing Machinery, New York, NY, USA, 204--214. https://doi.org/10.1145/3543174.3545252
[43]
Kevin Anthony Hoff and Masooda Bashir. 2015. Trust in automation: Integrating empirical evidence on factors that influence trust. Human factors 57, 3 (2015), 407--434.
[44]
Kai Holländer, Mark Colley, Enrico Rukzio, and Andreas Butz. 2021. A Taxonomy of Vulnerable Road Users for HCI Based On A Systematic Literature Review. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI '21). Association for Computing Machinery, New York, NY, USA, Article 158, 13 pages. https://doi.org/10.1145/3411764.3445480
[45]
Kai Holländer, Philipp Wintersberger, and Andreas Butz. 2019. Overtrust in External Cues of Automated Vehicles: An Experimental Investigation. In Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Utrecht, Netherlands) (AutomotiveUI '19). Association for Computing Machinery, New York, NY, USA, 211--221. https://doi.org/10.1145/3342197.3344528
[46]
Brittany E. Holthausen, Philipp Wintersberger, Bruce N. Walker, and Andreas Riener. 2020. Situational Trust Scale for Automated Driving (STS-AD): Development and Initial Validation. In 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Virtual Event, DC, USA) (AutomotiveUI '20). Association for Computing Machinery, New York, NY, USA, 40--47. https://doi.org/10.1145/3409120.3410637
[47]
Markus Jordan. 2020. DAS MBUX AUGMENTED REALITY HEAD-UP DISPLAY DER S-KLASSE. https://mbpassion.de/2020/09/das-mbux-augmented-reality-head-up-display/. [Online; accessed 01-APRIL-2022].
[48]
Christina Kaß, Stefanie Schoch, Frederik Naujoks, Sebastian Hergeth, Andreas Keinath, and Alexandra Neukum. 2020. Standardized Test Procedure for External Human--Machine Interfaces of Automated Vehicles. Information 11, 3 (2020), 173.
[49]
Matthew Kay. 2019. How Much Value Should an Uncertainty Palette Suppress if an Uncertainty Palette Should Suppress Value? Statistical and Perceptual Perspectives. 4 pages.
[50]
Jeamin Koo, Jungsuk Kwac, Wendy Ju, Martin Steinert, Larry Leifer, and Clifford Nass. 2015. Why did my car just do that? Explaining semi-autonomous driving actions to improve driver understanding, trust, and performance. International Journal on Interactive Design and Manufacturing (IJIDeM) 9, 4 (2015), 269--275.
[51]
Moritz Körber. 2019. Theoretical Considerations and Development of a Questionnaire to Measure Trust in Automation. In Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Sebastiano Bagnara, Riccardo Tartaglia, Sara Albolino, Thomas Alexander, and Yushi Fujita (Eds.). Springer International Publishing, Cham, 13--30.
[52]
Johannes Kraus, David Scholz, Dina Stiegemeier, and Martin Baumann. 2020. The More You Know: Trust Dynamics and Calibration in Highly Automated Driving and the Effects of Take-Overs, System Malfunction, and System Transparency. Human Factors 62, 5 (2020), 0018720819853686. https://doi.org/10.1177/0018720819853686 arXiv:https://doi.org/10.1177/0018720819853686 31233695.
[53]
Alexander Kunze, Stephen J. Summerskill, Russell Marshall, and Ashleigh J. Filtness. 2018. Augmented Reality Displays for Communicating Uncertainty Information in Automated Driving. In Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Toronto, ON, Canada) (AutomotiveUI '18). Association for Computing Machinery, New York, NY, USA, 164--175. https://doi.org/10.1145/3239060.3239074
[54]
Alexander Kunze, Stephen J. Summerskill, Russell Marshall, and Ashleigh J. Filtness. 2019. Conveying Uncertainties Using Peripheral Awareness Displays in the Context of Automated Driving. In Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Utrecht, Netherlands) (AutomotiveUI 19). Association for Computing Machinery, New York, NY, USA, 329--341. https://doi.org/10.1145/3342197.3344537
[55]
John D Lee and Katrina A See. 2004. Trust in automation: Designing for appropriate reliance. Human factors 46, 1 (2004), 50--80.
[56]
Patrick Lindemann, Tae-Young Lee, and Gerhard Rigoll. 2018. Catch my drift: Elevating situation awareness for highly automated driving with an explanatory windshield display user interface. Multimodal Technologies and Interaction 2, 4 (2018), 71.
[57]
Andreas Löcken, Anna-Katharina Frison, Vanessa Fahn, Dominik Kreppold, Maximilian Götz, and Andreas Riener. 2020. Increasing User Experience and Trust in Automated Vehicles via an Ambient Light Display. In 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services (Oldenburg, Germany) (MobileHCI '20). Association for Computing Machinery, New York, NY, USA, Article 38, 10 pages. https://doi.org/10.1145/3379503.3403567
[58]
Andreas Löcken, Wilko Heuten, and Susanne Boll. 2016. AutoAmbiCar: Using Ambient Light to Inform Drivers About Intentions of Their Automated Cars. In Adjunct Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Ann Arbor, MI, USA) (AutomotiveUI '16 Adjunct). Association for Computing Machinery, New York, NY, USA, 57--62. https://doi.org/10.1145/3004323.3004329
[59]
Alan M MacEachren, Robert E Roth, James O'Brien, Bonan Li, Derek Swingley, and Mark Gahegan. 2012. Visual semiotics & uncertainty visualization: An empirical study. IEEE transactions on visualization and computer graphics 18, 12 (2012), 2496--2505.
[60]
Roger C Mayer, James H Davis, and F David Schoorman. 1995. An integrative model of organizational trust. Academy of management review 20, 3 (1995), 709--734.
[61]
Natasha Merat, A. Hamish Jamson, Frank C.H. Lai, Michael Daly, and Oliver M.J. Carsten. 2014. Transition to manual: Driver behaviour when resuming control from a highly automated vehicle. Transportation Research Part F: Traffic Psychology and Behaviour 27 (2014), 274--282. https://doi.org/10.1016/j.trf.2014.09.005
[62]
Jean Mercat, Thomas Gilles, Nicole El Zoghby, Guillaume Sandou, Dominique Beauvois, and Guillermo Pita Gil. 2020. Multi-head attention for multi-modal joint vehicle motion forecasting. In 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, IEEE, New York, NY, USA, 9638--9644.
[63]
Bonnie M Muir and Neville Moray. 1996. Trust in automation. Part II. Experimental studies of trust and human intervention in a process control simulation. Ergonomics 39, 3 (1996), 429--460.
[64]
Tobias Müller, Mark Colley, Gülsemin Dogru, and Enrico Rukzio. 2022. AR4CAD: Creation and Exploration of a Taxonomy of Augmented Reality Visualization for Connected Automated Driving. Proc. ACM Hum.-Comput. Interact. 6, MHCI, Article 177 (sep 2022), 27 pages. https://doi.org/10.1145/3546712
[65]
Lace Padilla, Matthew Kay, and Jessica Hullman. 2022. Uncertainty visualization. Wiley, Hoboken, NJ, USA, Chapter 22, 405--421.
[66]
Bastian Pfleging, Maurice Rang, and Nora Broy. 2016. Investigating User Needs for Non-Driving-Related Activities during Automated Driving. In Proceedings of the 15th International Conference on Mobile and Ubiquitous Multimedia (Rovaniemi, Finland) (MUM '16). Association for Computing Machinery, New York, NY, USA, 91--99. https://doi.org/10.1145/3012709.3012735
[67]
Amir Rasouli and John K Tsotsos. 2019. Autonomous vehicles that interact with pedestrians: A survey of theory and practice. IEEE Transactions on Intelligent Transportation Systems 21, 3 (2019), 900--918.
[68]
Stephan Reuter, Ba-Tuong Vo, Ba-Ngu Vo, and Klaus Dietmayer. 2014. The Labeled Multi-Bernoulli Filter. IEEE Transactions on Signal Processing 62, 12 (2014), 3246--3260. https://doi.org/10.1109/TSP.2014.2323064
[69]
Katarzyna Samson and Patrycjusz Kostyszyn. 2015. Effects of cognitive load on trusting behavior--an experiment using the trust game. PloS one 10, 5 (2015), e0127680.
[70]
Katarzyna Samson and Patrycjusz Kostyszyn. 2015. Effects of Cognitive Load on Trusting Behavior -- An Experiment Using the Trust Game. PLOS ONE 10, 5 (05 2015), 1--10. https://doi.org/10.1371/journal.pone.0127680
[71]
Sarah Schmidt and B Färber. 2009. Pedestrians at the kerb--Recognising the action intentions of humans. Transportation research part F: traffic psychology and behaviour 12, 4 (2009), 300--310.
[72]
Tobias Schneider, Joana Hois, Alischa Rosenstein, Sabiha Ghellal, Dimitra Theofanou-Fülbier, and Ansgar R.S. Gerlicher. 2021. ExplAIn Yourself! Transparency for Positive UX in Autonomous Driving. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 161, 12 pages. https://doi.org/10.1145/3411764.3446647
[73]
Brandon Schoettle and Michael Sivak. 2014. A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia. Technical Report. University of Michigan, Ann Arbor, Transportation Research Institute.
[74]
Andreas Th Schulz and Rainer Stiefelhagen. 2015. Pedestrian intention recognition using latent-dynamic conditional random fields. In 2015 IEEE Intelligent Vehicles Symposium (IV). IEEE, IEEE, New York, NY, USA, 622--627.
[75]
Santokh Singh. 2015. Critical reasons for crashes investigated in the national motor vehicle crash causation survey. Technical Report. National Highway Traffic Safety Administration.
[76]
Vanessa Stange, Anne Goralzik, Susanne Ernst, Markus Steimle, Markus Maurer, and Mark Vollrath. 2022. Please stop now, automated vehicle!--Passengers aim to avoid risk experiences in interactions with a crossing vulnerable road user at an urban junction. Transportation research part F: traffic psychology and behaviour 87 (2022), 164--188.
[77]
Jan Strohbeck, Vasileios Belagiannis, Johannes Müller, Marcel Schreiber, Martin Herrmann, Daniel Wolf, and Michael Buchholz. 2020. Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks. In Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, New York, NY, USA.
[78]
Richard M Taylor. 2017. Situational awareness rating technique (SART): The development of a tool for aircrew systems design. In Situational awareness. Routledge, Abingdon, UK, 111--128.
[79]
Henry Togwell, Mark McGill, Graham Wilson, Daniel Medeiros, and Stephen Anthony Brewster. 2022. In-CAR Gaming: Exploring the Use of AR Headsets to Leverage Passenger Travel Environments for Mixed Reality Gameplay. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22). Association for Computing Machinery, New York, NY, USA, Article 369, 7 pages. https://doi.org/10.1145/3491101.3519741
[80]
Robert Tscharn, Marc Erich Latoschik, Diana Löffler, and Jörn Hurtienne. 2017. "Stop over There": Natural Gesture and Speech Interaction for Non-Critical Spontaneous Intervention in Autonomous Driving. In Proceedings of the 19th ACM International Conference on Multimodal Interaction (Glasgow, UK) (ICMI '17). Association for Computing Machinery, New York, NY, USA, 91--100. https://doi.org/10.1145/3136755.3136787
[81]
Unity Technologies. 2020. Unity. Unity Technologies.
[82]
Anne Marthe Van Der Bles, Sander van der Linden, Alexandra LJ Freeman, and David J Spiegelhalter. 2020. The effects of communicating uncertainty on public trust in facts and numbers. Proceedings of the National Academy of Sciences 117, 14 (2020), 7672--7683.
[83]
Hanneke Hooft van Huysduynen, Jacques Terken, Alexander Meschtscherjakov, Berry Eggen, and Manfred Tscheligi. 2017. Ambient Light and Its Influence on Driving Experience. In Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Oldenburg, Germany) (AutomotiveUI '17). Association for Computing Machinery, New York, NY, USA, 293--301. https://doi.org/10.1145/3122986.3122992
[84]
Tamara von Sawitzky, Philipp Wintersberger, Andreas Riener, and Joseph L. Gabbard. 2019. Increasing Trust in Fully Automated Driving: Route Indication on an Augmented Reality Head-up Display. In Proceedings of the 8th ACM International Symposium on Pervasive Displays (Palermo, Italy) (PerDis '19). Association for Computing Machinery, New York, NY, USA, Article 6, 7 pages. https://doi.org/10.1145/3321335.3324947
[85]
Gesa Wiegand, Malin Eiband, Maximilian Haubelt, and Heinrich Hussmann. 2020. "I'd like an Explanation for That!"Exploring Reactions to Unexpected Autonomous Driving. In 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services (Oldenburg, Germany) (MobileHCI '20). Association for Computing Machinery, New York, NY, USA, Article 36, 11 pages. https://doi.org/10.1145/3379503.3403554
[86]
Marc Wilbrink, Anna Schieben, and Michael Oehl. 2020. Reflecting the Automated Vehicle's Perception and Intention: Light-Based Interaction Approaches for on-Board HMI in Highly Automated Vehicles. In Proceedings of the 25th International Conference on Intelligent User Interfaces Companion (Cagliari, Italy) (IUI '20). Association for Computing Machinery, New York, NY, USA, 105--107. https://doi.org/10.1145/3379336.3381502
[87]
Philipp Wintersberger, Anna-Katharina Frison, Andreas Riener, and Tamara von Sawitzky. 2019. Fostering User Acceptance and Trust in Fully Automated Vehicles: Evaluating the Potential of Augmented Reality. PRESENCE: Virtual and Augmented Reality 27, 1 (2019), 46--62. https://doi.org/10.1162/pres_a_00320 arXiv:https://doi.org/10.1162/pres_a_00320
[88]
Philipp Wintersberger, Hannah Nicklas, Thomas Martlbauer, Stephan Hammer, and Andreas Riener. 2020. Explainable Automation: Personalized and Adaptive UIs to Foster Trust and Understanding of Driving Automation Systems. In 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Virtual Event, DC, USA) (AutomotiveUI '20). Association for Computing Machinery, New York, NY, USA, 252--261. https://doi.org/10.1145/3409120.3410659
[89]
Jacob O. Wobbrock, Leah Findlater, Darren Gergle, and James J. Higgins. 2011. The Aligned Rank Transform for Nonparametric Factorial Analyses Using Only Anova Procedures. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, BC, Canada) (CHI '11). Association for Computing Machinery, New York, NY, USA, 143--146. https://doi.org/10.1145/1978942.1978963

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  • (2024)TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated VehiclesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785448:3(1-60)Online publication date: 9-Sep-2024
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  1. Effects of Uncertain Trajectory Prediction Visualization in Highly Automated Vehicles on Trust, Situation Awareness, and Cognitive Load

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    cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 7, Issue 4
    December 2023
    1613 pages
    EISSN:2474-9567
    DOI:10.1145/3640795
    Issue’s Table of Contents
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 12 January 2024
    Published in IMWUT Volume 7, Issue 4

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    1. Autonomous vehicles
    2. Uncertainty Information
    3. Visualization Design

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    • (2024)TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated VehiclesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785448:3(1-60)Online publication date: 9-Sep-2024
    • (2024)Hey, What's Going On?Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596188:2(1-24)Online publication date: 15-May-2024
    • (2024)Investigating the Effects of External Communication and Platoon Behavior on Manual Drivers at Highway AccessProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642365(1-15)Online publication date: 11-May-2024

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