Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
129 tokens/sec
GPT-4o
28 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Exploring the Impact of Interconnected External Interfaces in Autonomous Vehicleson Pedestrian Safety and Experience (2403.05725v2)

Published 8 Mar 2024 in cs.HC

Abstract: Policymakers advocate for the use of external Human-Machine Interfaces (eHMIs) to allow autonomous vehicles (AVs) to communicate their intentions or status. Nonetheless, scalability concerns in complex traffic scenarios arise, such as potentially increasing pedestrian cognitive load or conveying contradictory signals. Building upon precursory works, our study explores 'interconnected eHMIs,' where multiple AV interfaces are interconnected to provide pedestrians with clear and unified information. In a virtual reality study (N=32), we assessed the effectiveness of this concept in improving pedestrian safety and their crossing experience. We compared these results against two conditions: no eHMIs and unconnected eHMIs. Results indicated interconnected eHMIs enhanced safety feelings and encouraged cautious crossings. However, certain design elements, such as the use of the colour red, led to confusion and discomfort. Prior knowledge slightly influenced perceptions of interconnected eHMIs, underscoring the need for refined user education. We conclude with practical implications and future eHMI design research directions.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (74)
  1. Hello human, can you read my mind? ERCIM News 109 (2017), 36–37.
  2. Driving Test Australia. 2017. What you need to know about red painted areas on some Australian roads? https://emudrivingschool.com.au/Blog/What-you-need-to-know-about-red-painted-areas-on-some-Australian-roads Accessed: 6 Feb 2024.
  3. External Human-Machine Interfaces: Which of 729 Colors Is Best for Signaling ‘Please (Do not) Cross’?. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, Toronto, ON, Canada, 3721–3728. https://doi.org/10.1109/SMC42975.2020.9282998
  4. SAV2P: Exploring the Impact of an Interface for Shared Automated Vehicles on Pedestrians’ Experience. In Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications Adjunct (Oldenburg, Germany) (AutomotiveUI ’17). Association for Computing Machinery, New York, NY, USA, 136–140. https://doi.org/10.1145/3131726.3131765
  5. The effect of internal and external fields of view on visually induced motion sickness. Applied ergonomics 41, 4 (2010), 516–521.
  6. Eyes on a Car: An Interface Design for Communication between an Autonomous Car and a Pedestrian. 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, 65–73. https://doi.org/10.1145/3122986.3122989
  7. Effects of Pedestrian Behavior, Time Pressure, and Repeated Exposure on Crossing Decisions in Front of Automated Vehicles Equipped with External Communication. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 367, 11 pages. https://doi.org/10.1145/3491102.3517571
  8. Towards Inclusive External Communication of Autonomous Vehicles for Pedestrians with Vision Impairments. 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/10.1145/3313831.3376472
  9. Unveiling the Lack of Scalability in Research on External Communication of Autonomous Vehicles. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI EA ’20). Association for Computing Machinery, New York, NY, USA, 1–9. https://doi.org/10.1145/3334480.3382865
  10. Ford Motor Corporation. 2017. Ford, Virginia Tech Go Undercover to Develop Signals That Enable Autonomous Vehicles to Communicate with People. https://media.ford.com/content/fordmedia/fna/us/en/news/2017/09/13/ford-virginia-tech-autonomous-vehicle-human-testing.html
  11. External Human-Machine Interfaces on Automated Vehicles: Effects on Pedestrian Crossing Decisions. Human Factors 61, 8 (2019), 1353–1370. https://doi.org/10.1177/0018720819836343 arXiv:https://doi.org/10.1177/0018720819836343
  12. How Communicating Features can Help Pedestrian Safety in the Presence of Self-Driving Vehicles: Virtual Reality Experiment. IEEE Transactions on Human-Machine Systems 50, 2 (2020), 176–186. https://doi.org/10.1109/THMS.2019.2960517
  13. Investigating pedestrian suggestions for external features on fully autonomous vehicles: A virtual reality experiment. Transportation Research Part F: Traffic Psychology and Behaviour 59 (2018), 135–149. https://doi.org/10.1016/j.trf.2018.08.016
  14. Department of Transport and Main Roads. 2022. Township Entry Treatments. https://www.tmr.qld.gov.au/Safety/Road-safety/Targeted-Road-Safety-Program/Township-Entry-Treatments Accessed: 6 Feb 2024.
  15. Robert F. DeVellis. 1991. Scale Development: Theory and Applications. Applied Social Research Methods Series, Vol. 26. Sage Publications, Newbury Park, CA.
  16. Investigating the Need for Explicit Communication of Non-Yielding Intent through a Slow-Pulsing Light Band (SPLB) EHMI in AV-Pedestrian Interaction. 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, 307–318. https://doi.org/10.1145/3543174.3546086
  17. Taming the eHMI jungle: A classification taxonomy to guide, compare, and assess the design principles of automated vehicles’ external human-machine interfaces. Transportation Research Interdisciplinary Perspectives 7 (2020), 100174. https://doi.org/10.1016/j.trip.2020.100174
  18. Color and Animation Preferences for a Light Band EHMI in Interactions Between Automated Vehicles and Pedestrians. 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, 1–13. https://doi.org/10.1145/3313831.3376325
  19. Debargha Dey and Jacques Terken. 2017. Pedestrian Interaction with Vehicles: Roles of Explicit and Implicit Communication. 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, 109–113. https://doi.org/10.1145/3122986.3123009
  20. Towards Scalable EHMIs: Designing for AV-VRU Communication Beyond One Pedestrian. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Leeds, United Kingdom) (AutomotiveUI ’21). Association for Computing Machinery, New York, NY, USA, 274–286. https://doi.org/10.1145/3409118.3475129
  21. Effects of User Instruction on Acceptance and Trust in Automated Driving. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC). IEEE, Rhodes, Greece, 1–6. https://doi.org/10.1109/ITSC45102.2020.9294511
  22. Calibrating Pedestrians’ Trust in Automated Vehicles: Does an Intent Display in an External HMI Support Trust Calibration and Safe Crossing Behavior?. 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 157, 17 pages. https://doi.org/10.1145/3411764.3445738
  23. Stefanie M. Faas and Martin Baumann. 2019. Light-Based External Human Machine Interface: Color Evaluation for Self-Driving Vehicle and Pedestrian Interaction. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, 1 (2019), 1232–1236. https://doi.org/10.1177/1071181319631049 arXiv:https://doi.org/10.1177/1071181319631049
  24. 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
  25. External HMI for self-driving vehicles: Which information shall be displayed? Transportation Research Part F: Traffic Psychology and Behaviour 68 (2020), 171–186. https://doi.org/10.1016/j.trf.2019.12.009
  26. Pedestrian Notification Methods in Autonomous Vehicles for Multi-Class Mobility-on-Demand Service. In Proceedings of the Fourth International Conference on Human Agent Interaction (Biopolis, Singapore) (HAI ’16). Association for Computing Machinery, New York, NY, USA, 387–392. https://doi.org/10.1145/2974804.2974833
  27. User Education in Automated Driving: Owner’s Manual and Interactive Tutorial Support Mental Model Formation and Human-Automation Interaction. Information 10, 4 (2019), 22 pages. https://doi.org/10.3390/info10040143
  28. Queensland Government. 2023. Stopping Distances. https://www.qld.gov.au/transport/safety/road-safety/driving-safely/stopping-distances Accessed: 2023-08-15.
  29. “I Am Going This Way”: Gazing Eyes on Self-Driving Car Show Multiple Driving Directions. 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, 319–329. https://doi.org/10.1145/3543174.3545251
  30. A pedestrian’s stare and drivers’ stopping behavior: A field experiment at the pedestrian crossing. Safety Science 75 (2015), 87–89. https://doi.org/10.1016/j.ssci.2015.01.018
  31. Communicating Intent of Automated Vehicles to Pedestrians. Frontiers in Psychology 9 (2018), 17 pages. https://doi.org/10.3389/fpsyg.2018.01336
  32. Sandra G. Hart and Lowell E. Staveland. 1988. Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. In Human Mental Workload, Peter A. Hancock and Najmedin Meshkati (Eds.). Advances in Psychology, Vol. 52. Elsevier, North-Holland, 139–183. https://doi.org/10.1016/S0166-4115(08)62386-9
  33. Don’t Panic! Guiding Pedestrians in Autonomous Traffic with Augmented Reality. In Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (Barcelona, Spain) (MobileHCI ’18). Association for Computing Machinery, New York, NY, USA, 261–268. https://doi.org/10.1145/3236112.3236148
  34. Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time. Frontiers in Psychology 11 (2020), 11 pages. https://doi.org/10.3389/fpsyg.2020.585280
  35. Context-Based Interface Prototyping: Understanding the Effect of Prototype Representation on User Feedback. 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 370, 14 pages. https://doi.org/10.1145/3411764.3445159
  36. Investigating the Influence of External Car Displays on Pedestrians’ Crossing Behavior in Virtual Reality. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (Taipei, Taiwan) (MobileHCI ’19). Association for Computing Machinery, New York, NY, USA, Article 27, 11 pages. https://doi.org/10.1145/3338286.3340138
  37. Take It to the Curb: Scalable Communication Between Autonomous Cars and Vulnerable Road Users Through Curbstone Displays. Frontiers Comput. Sci. 4 (2022), 844245. https://doi.org/10.3389/fcomp.2022.844245
  38. Save the Smombies: App-Assisted Street Crossing. 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 22, 11 pages. https://doi.org/10.1145/3379503.3403547
  39. 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
  40. External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation. Transportation research part F: traffic psychology and behaviour 87 (2022), 365–378. https://doi.org/10.1016/j.trf.2022.04.017
  41. SAE International. 2019. Automated Driving System (ADS) Marker Lamp. SAE Recommended Practice J3134_201905. Society of Automotive Engineers, Warrendale, PA. 10 pages. https://doi.org/10.4271/J3134_201905
  42. External Human–Machine Interfaces Can Be Misleading: An Examination of Trust Development and Misuse in a CAVE-Based Pedestrian Simulation Environment. Human Factors 64, 6 (2022), 1070–1085. https://doi.org/10.1177/0018720820970751 arXiv:https://doi.org/10.1177/0018720820970751
  43. Steve G. Young Karyn Pravossoudovitch, Francois Cury and Andrew J. Elliot. 2014. Is red the colour of danger? Testing an implicit red–danger association. Ergonomics 57, 4 (2014), 503–510. https://doi.org/10.1080/00140139.2014.889220 arXiv:https://doi.org/10.1080/00140139.2014.889220 PMID: 24588355.
  44. 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). Springer International Publishing, Cham, 13–30.
  45. Tobias Lagström and Victor Malmsten Lundgren. 2016. AVIP-Autonomous vehicles’ interaction with pedestrians-An investigation of pedestrian-driver communication and development of a vehicle external interface. Master’s thesis. Chalmers University of Technology.
  46. Interaction Effects of Pedestrian Behavior, Smartphone Distraction and External Communication of Automated Vehicles on Crossing and Gaze Behavior. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23). Association for Computing Machinery, New York, NY, USA, Article 768, 18 pages. https://doi.org/10.1145/3544548.3581303
  47. Road Users Rarely Use Explicit Communication When Interacting in Today’s Traffic: Implications for Automated Vehicles. Cognition, Technology and Work 23, 2 (2021), 367–380. https://doi.org/10.1007/s10111-020-00635-y
  48. How Should Automated Vehicles Interact with Pedestrians? A Comparative Analysis of Interaction Concepts in Virtual Reality. 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, 262–274. https://doi.org/10.1145/3342197.3344544
  49. Go Ahead, Please!—Evaluation of External Human—Machine Interfaces in a Real-World Crossing Scenario. Frontiers in Computer Science 4 (2022), 14 pages. https://doi.org/10.3389/fcomp.2022.863072
  50. AV-Pedestrian Interaction Design Using a Pedestrian Mixed Traffic Simulator. In Proceedings of the 2019 on Designing Interactive Systems Conference (San Diego, CA, USA) (DIS ’19). Association for Computing Machinery, New York, NY, USA, 475–486. https://doi.org/10.1145/3322276.3322328
  51. Communicating Awareness and Intent in Autonomous Vehicle-Pedestrian Interaction. 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, 1–12. https://doi.org/10.1145/3173574.3174003
  52. Main Roads Western Australia. 2016. Laterite Red Coloured Asphalt. https://www.mainroads.wa.gov.au/globalassets/technical-commercial/technical-library/materials-engineering/publications/engineering-road-notes/laterite-red-coloured-asphalt.pdf. Accessed: 2024-02-06.
  53. Mercedes-Benz. 2015. The Mercedes-Benz F 015 Luxury in Motion. https://www.mercedes-benz.com.au/passengercars/mercedes-benz-cars/campaigns/mercedes-benz-f-015.html
  54. A field study investigating road safety effects of a front brake light. IET Intelligent Transport Systems 15, 8 (2021), 1043–1052. https://doi.org/10.1049/itr2.12080 arXiv:https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/itr2.12080
  55. The Case for Implicit External Human-Machine Interfaces for Autonomous Vehicles. 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, 295–307. https://doi.org/10.1145/3342197.3345320
  56. Designing for Projection-Based Communication between Autonomous Vehicles and Pedestrians. 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, 284–294. https://doi.org/10.1145/3342197.3344543
  57. Potential safety effects of a frontal brake light for motor vehicles. IET Intelligent Transport Systems 12, 6 (2018), 449–453. https://doi.org/10.1049/iet-its.2017.0321 arXiv:https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2017.0321
  58. Comparing State-of-the-Art and Emerging Augmented Reality Interfaces for Autonomous Vehicle-to-Pedestrian Communication. IEEE Transactions on Vehicular Technology 70, 2 (2021), 1157–1168.
  59. Agreeing to Cross: How Drivers and Pedestrians Communicate. In 2017 IEEE Intelligent Vehicles Symposium (IV). IEEE Press, Los Angeles, CA, USA, 264–269. https://doi.org/10.1109/IVS.2017.7995730
  60. Analysis of the Influence of Pedestrians’ eye Contact on Drivers’ Comfort Boundary During the Crossing Conflict. Procedia Engineering 137 (2016), 399–406. https://doi.org/10.1016/j.proeng.2016.01.274 Green Intelligent Transportation System and Safety.
  61. Lionel P. Robert. 2019. The Future of Pedestrian-Automated Vehicle Interactions. XRDS 25, 3 (apr 2019), 30–33. https://doi.org/10.1145/3313115
  62. Ghost driver: A field study investigating the interaction between pedestrians and driverless vehicles. In 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, New York, NY, USA, 795–802. https://doi.org/10.1109/ROMAN.2016.7745210
  63. Alexandros Rouchitsas and Håkan Alm. 2019. External Human–Machine Interfaces for Autonomous Vehicle-to-Pedestrian Communication: A Review of Empirical Work. Frontiers in Psychology 10 (2019), 12 pages. https://doi.org/10.3389/fpsyg.2019.02757
  64. Thomas W Schubert. 2003. The sense of presence in virtual environments: A three-component scale measuring spatial presence, involvement, and realness. Z. für Medienpsychologie 15, 2 (2003), 69–71.
  65. A Change of Perspective: Designing the Automated Vehicle as a New Social Actor in a Public Space. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI EA ’19). Association for Computing Machinery, New York, NY, USA, 1–8. https://doi.org/10.1145/3290607.3299044
  66. Pedestrian-driver communication and decision strategies at marked crossings. Accident Analysis & Prevention 102 (2017), 41–50. https://doi.org/10.1016/j.aap.2017.02.018
  67. Towards Future Pedestrian-Vehicle Interactions: Introducing Theoretically-Supported AR Prototypes. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Leeds, United Kingdom) (AutomotiveUI ’21). Association for Computing Machinery, New York, NY, USA, 209–218. https://doi.org/10.1145/3409118.3475149
  68. A Review of Virtual Reality Studies on Autonomous Vehicle–Pedestrian Interaction. IEEE Transactions on Human-Machine Systems 51, 6 (2021), 641–652. https://doi.org/10.1109/THMS.2021.3107517
  69. Scoping Out the Scalability Issues of Autonomous Vehicle-Pedestrian Interaction. In 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Ingolstadt, Germany) (AutomotiveUI ’23). Association for Computing Machinery, New York, NY, USA, 167–177. https://doi.org/10.1145/3580585.3607167
  70. Designing Wearable Augmented Reality Concepts to Support Scalability in Autonomous Vehicle-Pedestrian Interaction. Frontiers in Computer Science 4 (2022), 39. https://doi.org/10.3389/fcomp.2022.866516
  71. Umbrellium. 2017. Case study - make roads safer, more responsive & dynamic. https://umbrellium.co.uk/case-studies/south-london-starling-cv/
  72. Pedestrian-Vehicle Interaction in Shared Space: Insights for Autonomous Vehicles. 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, 330–339. https://doi.org/10.1145/3543174.3546838
  73. Scaling up Automated Vehicles’ EHMI Communication Designs to Interactions with Multiple Pedestrians – Putting EHMIs to the Test. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Leeds, United Kingdom) (AutomotiveUI ’21 Adjunct). Association for Computing Machinery, New York, NY, USA, 119–122. https://doi.org/10.1145/3473682.3480277
  74. Use of color in warnings. Cambridge University Press, Cambridge, 377–400. https://doi.org/10.1017/CBO9781107337930.019
Citations (2)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets