ABSTRACT
With self-driving vehicles (SDVs), pedestrians cannot rely on communication with the driver anymore. Industry experts and policymakers are proposing an external Human-Machine Interface (eHMI) communicating the automated status. We investigated whether additionally communicating SDVs' intent to give right of way further improves pedestrians' street crossing. To evaluate the stability of these eHMI effects, we conducted a three-session video study with N=34 pedestrians where we assessed subjective evaluations and crossing onset times. This is the first work capturing long-term effects of eHMIs. Our findings add credibility to prior studies by showing that eHMI effects last (acceptance, user experience) or even increase (crossing onset, perceived safety, trust, learnability, reliance) with time. We found that pedestrians benefit from an eHMI communicating SDVs' status, and that additionally communicating SDVs' intent adds further value. We conclude that SDVs should be equipped with an eHMI communicating both status and intent.
Supplemental Material
- Claudia Ackermann, Matthias Beggiato, Sarah Schubert, and Josef F. Krems. 2019. An experimental study to investigate design and assessment criteria: What is important for communication between pedestrians and automated vehicles? Applied Ergonomics 75, 272--282. DOI: https://doi.org/10.1016/j.apergo.2018.11.002.Google ScholarCross Ref
- American Association of Motor Vehicle Administrators. 2018. Jurisdictional guidelines for the safe testing and deployment of highly automated vehicles (2018). Retrieved July 29, 2019 from https://www.aamva.org/ GuidelinesTestingDeploymentHAVs-May2018/.Google Scholar
- Jonas Andersson, Azra Habibovic, Maria Klingegård, Cristofer Englund, and Victor M. Lundgren. 2017. Hello Human, can you read my mind? ERCIM News: Autonomous Vehicles, 109, 36--37.Google Scholar
- Ovidiu Antonescu. 2012. Front stop lamps for a safer traffic. In Proceedings of the FISITA 2012 World Automotive Congress, 311--314. DOI: https://doi.org/10.1007/978--3--642--33805--2_25.Google ScholarCross Ref
- Aaron Bangor, Philip Kortum, and James Miller. 2009. Determining what individual SUS scores mean: Adding an adjective rating scale. Journal of Usability Studies, 4, 114--123.Google ScholarDigital Library
- Christoph Bartneck, Dana Kulic, Elizabeth Croft, and Susana Zoghbi. 2009. Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. of Soc Robotics, 1, 71--81. DOI: https://doi.org/10.1007/s12369-008-0001--3.Google ScholarCross Ref
- Matthias Beggiato, Claudia Witzlack, Sabine Springer, and Josef Krems. 2017. The right moment for braking as informal communication signal between automated vehicles and pedestrians in crossing situations. In Proceedings of the 8th International Conference on Applied Human Factors and Ergonomics (AHFE '17), 1072--1081. DOI: https://doi.org/10.1007/978--3--319--604411_101.Google ScholarCross Ref
- Marc-Philipp Böckle, Anna P. Brenden, Maria Klingegård, Azra Habibovic, and Martijn Bout. 2017. SAV2P: Exploring the impact of an interface for shared automated vehicles on pedestrians' experience. In Adjunct Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI'17), 136--140. DOI: https://doi.org/10.1145/3131726.3131765.Google ScholarDigital Library
- John Brooke. 1996. SUS: A quick and dirty usability scale. In Usability Evaluation in Industry, Jordan, P. W., B. Thomas, B. A. Weerdmeester and I. L. McClelland, Eds. Taylor and Francis, London, 189-- 194.Google Scholar
- Koen de Clercq, Andre Dietrich, Juan P. Núñez Velasco, Joost de Winter, and Riender Happee. 2019. External human-machine interfaces on automated vehicles: Effects on pedestrian crossing decisions. Hum Factors. DOI: https://doi.org/10.1177/0018720819836343.Google ScholarCross Ref
- Nils Dahlbäck, Arne Jönsson, and Lars Ahrenberg. 1993. Wizard of Oz studies: why and how. In Proceedings of the 1st International Conference on Intelligent User Interfaces (IUI '93), 193--200. DOI: https://doi.org/10.1145/169891.169968.Google ScholarDigital Library
- Debargha Dey, Marieke Martens, Berry Eggen, and Jacques Terken. 2017. The impact of vehicle appearance and vehicle behavior on pedestrian interaction with autonomous vehicles. In Adjunct Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '17), 158-- 162. DOI: https://doi.org/10.1145/3131726.3131750.Google ScholarDigital Library
- André Dietrich, Jan-Henning Willrodt, Karolin Wagner, and Klaus Bengler. 2018. Projection-based external human machine interfaces: Enabling interaction between automated vehicles and pedestrians. In Proceedings of the 17th European VR, Driving Simulation & Virtual Reality Conference & Exhibition (DSC '18), 43--50.Google Scholar
- Nicola Döring and Jürgen Bortz. 2016. Forschungsmethoden und Evaluation. Springer, Wiesbaden.Google Scholar
- Kai Eckoldt, Marc Hassenzahl, Matthias Laschke, Thies Schneider, Josef Schumann, and Stefan Könsgen. 2016. The Gentleman: A prosocial assistance system to promote considerate driving. In Proceedings on the 10th Conference on Design and Emotion, 307--314.Google Scholar
- Mica R. Endsley. 1995. Toward a theory of situation awareness in dynamic systems. Hum Factors, 37, 32--64.Google ScholarCross Ref
- Stefanie M. Faas and Martin Baumann. 2019. Lightbased external human machine interface: Color evaluation for self-driving vehicle and pedestrian interaction. In Proceedings of the 63rd Human Factors and Ergonomics Society Annual Meeting (HFES '19), 1232--1236. DOI: https://doi.org/10.1177/1071181319631049.Google ScholarCross Ref
- Stefanie M. Faas and Martin Baumann. 2019. Yielding light signal evaluation for self-driving vehicle and pedestrian interaction. In Proceedings of the 2nd International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED '19), 189--194. DOI: https://doi.org/10.1007/978--3-030--27928--8_29.Google ScholarCross Ref
- 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, 167--181. DOI: https://doi.org/10.1016/j.tra.2015.04.003.Google ScholarCross Ref
- Berthold Färber. 2016. Communication and communication problems between autonomous vehicles and human drivers. In Autonomous Driving, Markus Maurer, J. C. Gerdes, Barbara Lenz and Hermann Winner, Eds. Springer, Berlin, Heidelberg, 125--144. DOI: https://doi.org/10.1007/978--3--66248847--8_7.Google ScholarCross Ref
- Federal Ministry of Transport and Digital Infrastructure. 2017. Ethics commission: Automated and connected driving (2017). Retrieved July 29, 2019 from https://www.bmvi.de/SharedDocs/EN/publications/report-ethics-commission.html.Google Scholar
- Andy Field. 2018. Discovering statistics using IBM SPSS statistics (5th edition). SAGE Publications Ltd., London.Google Scholar
- Anna-Katharina Frison, Philipp Wintersberger, Andreas Riener, Clemens Schartmüller, Linda N. Boyle, Erika Miller, and Klemens Weigl. 2019. In UX we trust. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '19). DOI: https://doi.org/10.1145/3290605.3300374.Google ScholarDigital Library
- Frederick J. Gravetter and Lori-Ann B. Forzano. 2018. Research Methods for the Behavioral Sciences. Cengage Learning.Google Scholar
- Nicolas Guéguen, Sébastien Meineri, and Chloé Eyssartier. 2015. A pedestrian's stare and drivers' stopping behavior: A field experiment at the pedestrian crossing. Safety Science, 75, 87--89. DOI: https://doi.org/10.1016/j.ssci.2015.01.018.Google ScholarCross Ref
- Azra Habibovic, Jonas Andersson, Victor Malmsten Lundgren, Maria Klingegård, Cristofer Englund, and Sofia Larsson. 2019. External vehicle interfaces for communication with other road users? In Road Vehicle Automation 5, Gereon Meyer and Sven Beiker, Eds. Springer, Cham, 91--102. DOI: https://doi.org/10.1007/978--3--319--94896--6_9.Google ScholarCross Ref
- Darren K. Hall. 2004. Front safety light for alerting braking conditions of a vehicle. (Feb. 2004). Patent No. 6,690,272, Filed March 11th, 2002, Issued February 10th, 2004.Google Scholar
- Veli Himanen and Risto Kulmala. 1998. An application of logit models in analyzing the behavior of pedestrians and car drivers on pedestrian crossings. Accident Analysis & Prevention, 20, 187-- 197.Google ScholarCross Ref
- Andreas Hinderks, Martin Schrepp, and Jörg Thomaschewski. 2019. UEQ Data Analysis Tool (2019). Retrieved June 22, 2019 from https:// www.ueq-online.org/Material/ Short_UEQ_Data_Analysis_Tool.xlsx.Google Scholar
- Christopher R. Hudson, Shuchisnigdha Deb, Daniel W. Carruth, John McGinley, and Darren Frey. 2019. Pedestrian perception of autonomous vehicles with external interacting features. In Proceedings of the 9th International Conference on Applied Human Factors and Ergonomics (AHFE '18), 33--39. DOI: https://doi.org/10.1007/978--3--319--94334--3_5.Google ScholarCross Ref
- International Organization for Standardization. 2018. Road vehicles: Ergonomic aspects of external visual communication from automated vehicles to other road users (ISO/TR 23049:2018) (2018). Retrieved March 7, 2019 from https://www.iso.org/standard/ 74397.html.Google Scholar
- Gary D. Jandron. 1998. Vehicle side/front brake lights. (Jun. 1998). Patent No. 5,758,944, Filed December 26th, 1995, Issued June 2nd, 1998.Google Scholar
- Jiun-Yin Jian, Ann M. Bisantz, Colin G. Drury, and James Llinas. 2000. Foundations for an empirically determined scale of trust in automated systems. International Journal of Cognitive Ergonomics, 4, 53--71.Google ScholarCross Ref
- Neal K. Katyal. 2014. Disruptive technologies and the law. Georgetown Law Journal, 102, 1685--1689.Google Scholar
- Theresa T. Kessler, Cintya Larios, Tiffani Walker, Valarie Yerdon, and P. A. Hancock. 2017. A comparison of trust measures in human--robot interaction scenarios. In Proceedings of the 7th International Conference on Applied Human Factors and Ergonomics (AHFE '16), 353--364. DOI: https://doi.org/10.1007/978--3--319--419596_29.Google ScholarCross Ref
- Tobias Lagström and Victor M. Lundgren. 2015. Automated vehicle's interaction with pedestrians (2015). Retrieved April 20, 2019 from http://publications.lib.chalmers.se/records/fulltext/238401/238401.pdf.Google Scholar
- James R. Lewis and Jeff Sauro. 2009. The factor structure of the system usability scale. In Proceedings of the International Conference on Human Centered Design, 94--103.Google Scholar
- Yung-Ching Liu and Ying-Chan Tung. 2014. Risk analysis of pedestrians' road-crossing decisions: Effects of age, time gap, time of day, and vehicle speed. Safety Science, 63, 77--82. DOI: https://doi.org/10.1016/j.ssci.2013.11.002.Google ScholarCross Ref
- Victor M. Lundgren, Azra Habibovic, Jonas Andersson, Tobias Lagström, Maria Nilsson, Anna Sirkka, Johan Fagerlönn, Rikard Fredriksson, Claes Edgren, Stas Krupenia, and Dennis Saluäär. 2017. Will there be new communication needs when introducing automated vehicles to the urban context? In Proceedings of the 7th International Conference on Applied Human Factors and Ergonomics (AHFE '16), 485--497. DOI: https://doi.org/10.1007/978--3319--41682--3_41.Google ScholarCross Ref
- Karthik Mahadevan, Sowmya Somanath, and Ehud Sharlin. 2018. Communicating awareness and intent in autonomous vehicle-pedestrian interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '18), 1--12. DOI: https://doi.org/10.1145/3173574.3174003.Google ScholarDigital Library
- Philipp Mayring. 2014. Qualitative content analysis: Theoretical foundation, basic procedures and software solution (2014). Retrieved April 18, 2019 from https://nbn-resolving.org/urn:nbn:de:0168ssoar-395173.Google Scholar
- Terence J. McDonnell. 2019. Emerging law enforcement roles supporting safe testing and deployment (2019). Retrieved July 22, 2019 from https://lifesaversconference.ord/wp-content/uploads/ 2019/03/McDonnell-VT-01.pdf.Google Scholar
- Brittany E. Noah, Philipp Wintersberger, Alexander G. Mirnig, Shailie Thakkar, Fei Yan, Thomas M. Gable, Johannes Kraus, and Roderick McCall. 2017. First workshop on trust in the age of automated driving. In Adjunct Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '17), 15--21. DOI: https://doi.org/10.1145/3131726.3131733.Google ScholarDigital Library
- Alan L. O'Sullivan. 1994. Front-mounted vehicle brake light. (Dec. 1994). Patent No. 5,373,426, Filed September 24th, 1993, Issued December 13th, 1994.Google Scholar
- Partners for Automated Vehicle Education. 2019. About (2019). Retrieved July 22, 2019 from https://pavecampaign.org/about/.Google Scholar
- Tibor Petzoldt, Katja Schleinitz, and Rainer Banse. 2018. The potential safety effects of a frontal brake light for motor vehicles. IET Intelligent Transport Systems, 12, 449--453. DOI: https://doi.org/10.1049/iet-its.2017.0321.Google ScholarCross Ref
- Zeheng Ren, Xiaobei Jiang, and Wuhong Wang. 2016. Analysis of the influence of pedestrians' eye contact on drivers' comfort boundary during the crossing conflict. Procedia Engineering, 137, 399-- 406. DOI: https://doi.org/10.1016/j.proeng.2016.01.274.Google ScholarCross Ref
- Malte Risto, Colleen Emmenegger, Erik Vinkhuyzen, Melissa Cefkin, and Jim Hollan. 2017. Human-vehicle interfaces: The power of vehicle movement gestures in human road user coordination. In Proceedings of the 9th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, 186--192. DOI: https://doi.org/10.17077/drivingassessment.1633.Google ScholarCross Ref
- Paola Rodríguez. 2017. Safety of pedestrians and cyclists when interacting with automated vehicles: A case study of the WEpods (2017). Retrieved April 19, 2019 from https://www.raddelft.nl/wp-content/uploads/2017/06/Paola-Rodriguez-Safety-ofPedestrians-and-Cyclists-when-Interactingwith?pdf.Google Scholar
- Dirk Rothenbücher, Jamy Li, David Sirkin, Brian Mok, and Wendy Ju. 2016. Ghost driver: A field study investigating the interaction between pedestrians and driverless vehicles. In Proceedings of the 25th IEEE International Symposium on Robot and Human Interactive Communication (IEEE RoMan '16), 795--802. DOI: https://doi.org/10.1109/ROMAN.2016.7745210.Google ScholarDigital Library
- SAE International. 2019. Autonomous vehicle lighting (J3134) https://www.sae.org/standards/ content/j3134/. Retrieved from.Google Scholar
- Anna Schieben, Marc Wilbrink, Carmen Kettwich, Ruth Madigan, Tyron Louw, and Natasha Merat. 2019. Designing the interaction of automated vehicles with other traffic participants: Design considerations based on human needs and expectations. Cogn Tech Work 2019, 21, 69--85. DOI: https://doi.org/10.1007/s10111-018-0521-z.Google ScholarDigital Library
- Sabrina Schmidt and Berthold Färber. 2009. Pedestrians at the kerb: Recognising the action intentions of humans. Transportation Research Part F: Traffic Psychology and Behaviour, 12, 300--310. DOI: https://doi.org/10.1016/j.trf.2009.02.003.Google ScholarCross Ref
- Friederike Schneemann and Irene Gohl. 2016. Analyzing driver-pedestrian interaction at crosswalks: A contribution to autonomous driving in urban environments. In 2016 IEEE Intelligent Vehicle Symposium (IV), 38--43. DOI: https://doi.org/10.1109/IVS.2016.7535361.Google ScholarDigital Library
- Martin Schrepp, Andreas Hinderks, and Jörg Thomaschewski. 2017. Design and evaluation of a short version of the user experience questionnaire (UEQ-S). IJIMAI, 4, 103--108. DOI: https://doi.org/10.9781/ijimai.2017.09.001.Google ScholarCross Ref
- Michael Sivak and Brandon Schöttle. 2015. Road safety with self-driving vehicles: General limitations and road sharing with conventional vehicles (Report No. UMTRI-2015--2) (2015). Retrieved July 25, 2019 from https://deepblue.lib.umich.edu/bitstream/handle/2027.42/111735/103187.pdf'sequence=1&isAllowed=y.Google Scholar
- Ye E. Song, Christian Lehsing, Tanja Fuest, and Klaus Bengler. 2018. External HMIs and their effect on the interaction between pedestrians and automated vehicles. In Proceedings of the 1st International Conference on Intelligent Human Systems Integration (IHSI '18), 13--18. DOI: https://doi.org/10.1007/978--3--319--73888--8.Google ScholarCross Ref
- Sebastian Stadler, Henriette Cornet, Tatiana Novaes Theoto, and Fritz Frenkler. 2019. A tool, not a toy: Using virtual reality to evaluate the communication between autonomous vehicles and pedestrians. In Augmented Reality and Virtual Reality, M. C. tom Dieck and Timothy Jung, Eds. Springer, Cham, 203-- 216. DOI: https://doi.org/10.1007/978--3-030-062460_15.Google ScholarCross Ref
- Daniel Dostal, and Ralf Risser. 2017. Pedestrian-driver communication and decision strategies at marked crossings. Accident Analysis & Prevention, 102, 41--50. DOI: https://doi.org/10.1016/j.aap.2017.02.018.Google ScholarCross Ref
- United Nations Economic Commission for Europe (UNECE), Taskforce on Autonomous Vehicle Signalling Requirements. 2019. Draft report: 4rd meeting (Report AVSR-04-05) (2019). Retrieved March 7, 2019 from https://wiki.unece.org/download/attachments/78742442/AVSR-0405e.docx?api=v2.Google Scholar
- Jinke D. van der Laan, Adriaan Heino, and Dick de Waard. 1997. A simple procedure for the assessment of acceptance of advanced transport telematics. Transportation Research Part C: Emerging Technologies, 5, 1--10. DOI: https://doi.org/10.1016/S0968-090X(96)00025--3.Google ScholarCross Ref
- Sherri C. Veach. 2005. Front safety brake lights. (Mar. 2005). Patent No. 6,864,787, Filed December 5th, 2001, Issued March 8th, 2005.Google Scholar
- Annette Werner. 2018. New colors for autonomous driving: An evaluation of chromaticities for the external lighting equipment of autonomous vehicles. Colour Turn, 1, 1--15. DOI: https://doi.org/10.25538/tct.v0i1.692.Google ScholarCross Ref
Index Terms
- A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle Pedestrian Interaction
Recommendations
Calibrating Pedestrians' Trust in Automated Vehicles: Does an Intent Display in an External HMI Support Trust Calibration and Safe Crossing Behavior?
CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing SystemsPolicymakers recommend that automated vehicles (AVs) display their automated driving status using an external human-machine interface (eHMI). However, previous studies suggest that a status eHMI is associated with overtrust, which might be overcome by ...
Communicating Awareness and Intent in Autonomous Vehicle-Pedestrian Interaction
CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing SystemsDrivers use nonverbal cues such as vehicle speed, eye gaze, and hand gestures to communicate awareness and intent to pedestrians. Conversely, in autonomous vehicles, drivers can be distracted or absent, leaving pedestrians to infer awareness and intent ...
Ghost driver: a platform for investigating interactions between pedestrians and driverless vehicles
AutomotiveUI '15: Adjunct Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular ApplicationsHow will pedestrians and cyclists interact with self-driving cars when there is no human driver? To find answers to this question we need a secure experimental design in which pedestrians can interact with a car that appears to drive on its own. In ...
Comments