research-article

The RRADS platform: a real road autonomous driving simulator

Authors:

Sonia Baltodano,

Nikolas Martelaro,

Wendy JuAuthors Info & Claims

AutomotiveUI '15: Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 281 - 288

https://doi.org/10.1145/2799250.2799288

Published: 01 September 2015 Publication History

Abstract

This platform paper introduces a methodology for simulating an autonomous vehicle on open public roads. The paper outlines the technology and protocol needed for running these simulations, and describes an instance where the Real Road Autonomous Driving Simulator (RRADS) was used to evaluate 3 prototypes in a between-participant study design. 35 participants were interviewed at length before and after entering the RRADS. Although our study did not use overt deception---the consent form clearly states that a licensed driver is operating the vehicle---the protocol was designed to support suspension of disbelief. Several participants who did not read the consent form clearly strongly believed that they were interacting with a fully autonomous vehicle.

The RRADS platform provides a lens onto the attitudes and concerns that people in real-world autonomous vehicles might have, and also points to ways that a protocol deliberately using misdirection can gain ecologically valid reactions from study participants.

References

[1]

Alpern, M., & Minardo, K. (2003). Developing a car gesture interface for use as a secondary task. In Extended abstracts on Human factors in computing systems (CHI'03), 932--933.

Digital Library

[2]

Baltodano, S., Sibi, S., Martelaro, N., Gowda, N., & Ju, W.(2015). RRADS: Real Road Autonomous Driving Simulation. In Extended Abstracts of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI'15), 283--284.

Digital Library

[3]

Baum, L. F. (1900). The wonderful wizard of Oz. Books of Wonder.

[4]

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3 (2), 77--101.

[5]

Burgess, M., King, N., Harris, M., & Lewis, E. (2013). Electric vehicle drivers' reported interactions with the public: Driving stereotype change? Transportation Research Pt F: Traffic Psychology, 17, 33--44.

[6]

Cross, N (1977). The Automated Architect. Pion Limited.

Digital Library

[7]

Dahlbäck, N., Jönsson, A., & Ahrenberg, L. (1993). Wizard of Oz studies---why and how. Knowledge-based systems, 6(4), 258--266.

[8]

Davies, A. (2015.) I Rode 500 Miles in a Self-Driving Car and Saw the Future. It's Delightfully Dull. Wired.com, January 7, 2025. Available at: http://www.wired.com/2015/01/rode-500-miles-self-driving-car-saw-future-boring/

[9]

Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. J. Advanced Nursing, 62(1), 107--115.

[10]

Fels, S., Hausch, R., & Tang, A. (2006). Investigation of haptic feedback in the driver seat. In IEEE Intelligent Transportation Systems Conference (ITSC'06), 584--589.

[11]

Fitch, G. M., Kiefer, R. J., Hankey, J. M., & Kleiner, B. M.(2007). Toward developing an approach for alerting drivers to the direction of a crash threat. Human Factors: The Journal of the Human Factors and Ergonomics Society, 49(4), 710--720.

[12]

Fitch, G. M., Hankey, J. M., Kleiner, B. M., & Dingus, T. A.(2011). Driver comprehension of multiple haptic seat alerts intended for use in an integrated collision avoidance system. Transportation Research part F: Traffic Psychology and Behaviour, 14(4), 278--290.

[13]

Geiger, M., Nieschulz, R., Zobl, M., Neuss, R., & Lang, M.(2001). Methods for Facilitation of Wizard-of-Oz Studies and Data Acquisition. In Proc. of the 9th Intl. Conf. on Human-Computer Interaction (HCI International 2001), New Orleans, Louisiana, USA, 5(10), 8--11.

[14]

Geutner, P., Steffens, F., & Manstetten, D. (2002). Design of the VICO Spoken Dialogue System: Evaluation of User Expectations by Wizard-of-Oz Experiments. In Proc. Third International Conference on Language Resources and Evaluation (LREC'02). 1588--1593.

[15]

Green, P., Boreczky, J., and Kim, S. (1990). Applications of Rapid Prototyping to Control and Display Design. SAE Technical Paper 900470..

[16]

Hogema, J. H., De Vries, S. C., Van Erp, J., & Kiefer, R. J.(2009). A tactile seat for direction coding in car driving: Field evaluation. In Proc. of IEEE Transactions on Haptics, 2(4), 181--188.

Digital Library

[17]

Kelley, J. F. (1983) An empirical methodology for writing user-friendly natural language computer applications. Proceedings of ACM Human Factors in Computing systems (CHI'83), 193--196.

Digital Library

[18]

Kelley, J. F. (1985). CAL -- A Natural Language program developed with the OZ Paradigm: Implications for Supercomputing Systems"." In Proceedings of ACM First International Conference on Supercomputing Systems. 238--248.

[19]

Lathrop, B., Cheng, H., Weng, F., Mishra, R., Chen, J., Bratt, H., & Shriberg, L. (2005). A Wizard of Oz framework for collecting spoken human-computer dialogs: An experiment procedure for the design and testing of natural language in-vehicle technology systems. In Proc. 12^th World Congress on Intelligent Transportation Systems (ITS'05), 12(6) 3298--307.

[20]

Morrell, J., & Wasilewski, K. (2010). Design and evaluation of a vibrotactile seat to improve spatial awareness while driving. In Proc. IEEE Haptics Symposium, 281--288.

Digital Library

[21]

Schmidt, G., Kiss, M., Babbel, E., & Galla, A. (2008). The Wizard on Wheels: Rapid Prototyping and User Testing of Future Driver Assistance Using Wizard of Oz Technique in a Vehicle. In Proceedings of the FISITA 2008 World Automotive Congress, Munich. F2008-02-001

[22]

Schuller, B., Lang, M., & Rigoll, G. (2006). Recognition of spontaneous emotions by speech within automotive environment. Fortschritte der Akustik (DAGA'06), 32(1), 57--8.

[23]

Talone, A., Fincannon, T., Schuster, D., Jentsch, F. and Hudson, I. (2013). Comparing Physical and Virtual Simulation Use in UGV Research. Proc. of the Human Factors and Ergonomics Society (HFES'13), 57(1), 2017--202.

Cited By

Kim GHwang SSeong MYeo DRus DKim S(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
https://dl.acm.org/doi/10.1145/3678544
Ma ZSchroeter RGomez R(2024)Designing HMI for BVI Users in Fully Automated Vehicles: A Participatory and In-the-field ApproachProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3688507(1-5)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3688507
Dong HKainth SFranssen MBruns MMartens M(2024)Understanding Automation Surprise in Non-Critical Highly Automated Driving: An Initial On-Road Probing StudyAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685019(33-38)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3641308.3685019
Show More Cited By

Index Terms

The RRADS platform: a real road autonomous driving simulator
1. Human-centered computing
  1. Interaction design
    1. Interaction design process and methods
      1. Interface design prototyping

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cover image ACM Other conferences

AutomotiveUI '15: Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 2015

338 pages

ISBN:9781450337366

DOI:10.1145/2799250

General Chair:
Gary Burnett
University of Nottingham, UK
,
Program Chairs:
Joe Gabbard
Virginia Tech
,
Paul Green
University of Michigan Transportation Research Institute (UMTRI)
,
Sebastian Osswald
Technische Universitat Munchen (TUM), Germany
,
Publications Chairs:
Ayse Eren,
Vicki Antrobus

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 01 September 2015

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AutomotiveUI '15

AutomotiveUI '15: The 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 1 - 3, 2015

Nottingham, United Kingdom

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AutomotiveUI '15 Paper Acceptance Rate 38 of 80 submissions, 48%;

Overall Acceptance Rate 248 of 566 submissions, 44%

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Cited By

Kim GHwang SSeong MYeo DRus DKim S(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
https://dl.acm.org/doi/10.1145/3678544
Ma ZSchroeter RGomez R(2024)Designing HMI for BVI Users in Fully Automated Vehicles: A Participatory and In-the-field ApproachProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3688507(1-5)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3688507
Dong HKainth SFranssen MBruns MMartens M(2024)Understanding Automation Surprise in Non-Critical Highly Automated Driving: An Initial On-Road Probing StudyAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685019(33-38)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3641308.3685019
Dey DGoedicke DYang CSirkin DCurrano RJu W(2024)GrokWalks: A Portable Virtual Reality Platform to Facilitate Studying Driver-Pedestrian InteractionsAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685013(284-288)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3641308.3685013
Bremers AFriedman NLee SWu TLaurier EJung MOrtiz JJu W(2024)(Social) Trouble on the Road: Understanding and Addressing Social Discomfort in Shared Car TripsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665580(1-13)Online publication date: 8-Jul-2024
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Bu FLi SGoedicke DColley MSharma GJu W(2024)Portobello: Extending Driving Simulation from the Lab to the RoadProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642341(1-13)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642341
Dai JGao BLuo MHuang ZLi ZZhang YYang MRoychoudhury APaiva AAbreu RStorey M(2024)SCTrans: Constructing a Large Public Scenario Dataset for Simulation Testing of Autonomous Driving SystemsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623350(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3623350
Li GZhao KZhang SLyu XDusmanu MZhang YPollefeys MTang S(2024)EgoGen: An Egocentric Synthetic Data Generator2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01374(14497-14509)Online publication date: 16-Jun-2024
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Lin SChen FXi LWang GXi RSun YZhu H(2024)TM-fuzzer: fuzzing autonomous driving systems through traffic managementAutomated Software Engineering10.1007/s10515-024-00461-w31:2Online publication date: 27-Jul-2024
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Jeon HJo TYeo DAn EKang YKim S(2024)The way of water: exploring the role of interaction elements in usability challenges with in-car VR experienceVirtual Reality10.1007/s10055-024-01001-328:3Online publication date: 7-Jun-2024
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