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. 2020 Oct 16;11:575151. doi: 10.3389/fpsyg.2020.575151

Corrigendum: External Human–Machine Interfaces for Autonomous Vehicle-to-Pedestrian Communication: A Review of Empirical Work

Alexandros Rouchitsas 1,*, Håkan Alm 1
PMCID: PMC7640756  PMID: 33192878

In the original article, there were five errors.

1. The word “only” was used instead of “mainly.”

A correction has been made to section External Human–Machine Interfaces Evaluated Via Empirical Studies, sub-section Studies Employing Physical Prototypes. The corrected sentence reads as follows:

“While the aforementioned studies have used mainly subjective measures to assess interface effectiveness, Clamann et al. (2017) evaluated a communication interface by using an objective measure, namely decision time, alongside ratings and interviews.”

2. The word “reaction” was used instead of “decision”.

A correction has been made to External Human–Machine Interfaces Evaluated Via Empirical Studies, sub-section VR-Based Studies. The corrected sentence reads as follows:

“All designs proved to be efficient, as evidenced by shorter decision times when compared to the baseline condition (autonomous vehicle without interface).”

3. The word “experimental” was used instead of “behavioral”.

A correction has been made to Discussion section. The corrected sentence reads as follows:

“Interestingly, the most convincing evidence were obtained largely from studies conducted in laboratory settings, namely monitor-based and VR-based studies, that utilized mainly objective measures, like reaction time, duration, and accuracy, in the context of behavioral tasks.”

Additionally, there was an error in Table 1 as published. The second-to-final version of Table 1 was included in the original article. The final version of the table appears below.

Table 1.

Empirical studies in the field of external human–machine interfaces for autonomous vehicle-to-pedestrian communication.

Studies Stimulus delivery Interface parameters Evaluation procedures Measures
Physical Prototype Monitor-based VR-based Technology Location Content type Information type Message coding Modality Behavioral task Online survey Questionnaire Objective Subjective
Hensch et al. (2019) Display Roof Information Mode, intention Lights Visual Intention identification Comprehensibility, trust, safety, usefulness Likert scales, interview
Costa (2017) Cardboard, speaker Hood, bumper Advice Textual, pictorial, sounds Visual, auditory Street-crossing Frequency
Mahadevan et al. (2018) Light strip, display, LEDs, printed hand, mobile phone, speaker Windshield, hood, roof, street surface, pedestrian's mobile phone Information Pedestrian acknowledgment, intention Lights, speech, vibration,gesture, pictorial Visual, auditory, haptic Crossing intention Effectiveness, confidence Likert scales, interview
Habibovic (2018) Light strip Windshield Information Mode, intention Lights Visual Street-crossing Safety Likert scales, interview
Clamann et al. (2017) Display Radiator grille Information, advice Speed Textual, pictorial Visual Street-crossing Effectiveness Decision time Interview
Li et al. (2018) Display Windshield, radiator grille, vehicle sides Advice Lights Visual Situational urgency, crossing intention Numeric scales, interview
Zhang et al. (2017) Light strip Front doors, hood Information Intention Lights Visual Intention identification, effectiveness Interview
Song et al. (2018) Display Radiator grille Advice Textual, pictorial Visual Crossing intention, preference Reaction time, frequency Interview
Fridman et al. (2017) Light strip, display, projection, vehicle lights and signals Windshield, headlights, fog lights, directional signals, radiator grille, bumper, street surface Information advice Intention Textual, pictorial, lights Visual Crossing intention Error rates, reaction time
Ackermann et al. (2019) Light strip, display, projection Windshield, radiator grille, street surface Information, advice Mode Lights, textual, pictorial Visual Comprehensibility, recognizability, ambiguousness, comfort Numeric scales, interview
Petzoldt et al. (2018) Light strip Above license plate Information Deceleration Lights Visual Deceleration detection Usefulness, safety Error rates, reaction time Likert scales
Chang et al. (2018) Light strip, display, projection, rotating vehicle lights Windshield, radiator grille, street surface, headlights Information Intention Lights, textual, pictorial, anthropomorphism Visual Intention identification Intelligibility Error rates Likert scales
Charisi et al. (2017) Display, light strip, projection, vehicle lights and signals Windshield, headlights, directional signals, street surface Information Intention Lights, textual, pictorial, anthropomorphism Visual Intention identification Intention identification Error rates Interview
de Clercq et al. (2019) Display, vehicle lights and signals Radiator grille, frontal brake lights Information advice Intention Textual, lights, pictorial Visual Safety-reporting Safety, preference Duration Interview
Hudson et al. (2018) Display, speaker Hood Advice Textual, pictorial, speech, music Visual, auditory Street-crossing Preference Interview
Deb et al. (2018) Display, speaker Hood Information advice Intention Lights, pictorial, speech, sounds, music Visual, auditory Street-crossing Safety, acceptance Decision time, duration Likert scales, interview
Stadler et al. (2019) Display Radiator grille Advice Lights, textual, pictorial Visual Street-crossing Satisfaction Error rates, decision time Numeric scales, interview
Othersen et al. (2018) Display Radiator grille Information Pedestrian detection, intention Lights, pictorial Visual Street-crossing Effectiveness, understandability, perceptibility, safety, appeal Decision time Interview
Chang et al. (2017) Rotating vehicle lights Headlights Information Pedestrian acknowledgment, intention Anthropomorphism Visual Crossing intention Effectiveness, safety Error rates, reaction time Likert scales, interview
Böckle et al. (2017) Light strip, speaker Vehicle corners Information Intention Lights, sounds Visual, auditory Street-crossing Safety, comfort, effectiveness Decision time Likert scales, interview

The authors apologize for these errors and state that they do not change the scientific conclusions of the article in any way. The original article has been updated.

References

  1. Ackermann C., Beggiato M., Schubert S., Krems J. F. (2019). An experimental study to investigate design and assessment criteria: what is important for communication between pedestrians and automated vehicles? Appl. Ergon. 75, 272–282. 10.1016/j.apergo.2018.11.002 [DOI] [PubMed] [Google Scholar]
  2. Böckle M. P., Brenden A. P., Klingegård M., Habibovic A., Bout M. (2017). 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 (New York, NY: ACM; ), 136–140. [Google Scholar]
  3. Chang C. M., Toda K., Igarashi T., Miyata M., Kobayashi Y. (2018). A video-based study comparing communication modalities between an autonomous car and a pedestrian, in Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (New York, NY: ACM; ), 104–109. [Google Scholar]
  4. Chang C. M., Toda K., Sakamoto D., Igarashi T. (2017). 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 (New York, NY: ACM; ), 65–73. [Google Scholar]
  5. Charisi V., Habibovic A., Andersson J., Li J., Evers V. (2017). Children's views on identification and intention communication of self-driving vehicles, in Proceedings of the 2017 Conference on Interaction Design and Children (New York, NY: ACM; ), 399–404. [Google Scholar]
  6. Clamann M., Aubert M., Cummings M. L. (2017). Evaluation of vehicle-to-pedestrian communication displays for autonomous vehicles, in Proceedings of the 96th Annual Transportation Research Board Meeting (Washington, DC: ). [Google Scholar]
  7. Costa G. (2017). Designing Framework for Human-Autonomous Vehicle Interaction. Master's thesis, Designing Framework for Human-Autonomous Vehicle Interaction, Minato. [Google Scholar]
  8. de Clercq K., Dietrich A., Núñez Velasco J. P., de Winter J., Happee R. (2019). External human-machine interfaces on automated vehicles: effects on pedestrian crossing decisions. Hum. Factors 61, 1353–1370. 10.1177/0018720819836343 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Deb S., Strawderman L. J., Carruth D. W. (2018). Investigating pedestrian suggestions for external features on fully autonomous vehicles: a virtual reality experiment. Transp. Res. Part F Traffic Psychol. Behav. 59, 135–149. 10.1016/j.trf.2018.08.016 [DOI] [Google Scholar]
  10. Fridman L., Mehler B., Xia L., Yang Y., Facusse L. Y., Reimer B. (2017). To walk or not to walk: crowdsourced assessment of external vehicle-to-pedestrian displays. arXiv [Preprint]. [Google Scholar]
  11. Habibovic A. (2018). Communicating intent of automated vehicles to pedestrians. Front. Psychol. 9:1336. 10.3389/fpsyg.2018.01336 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hensch A. C., Neumann I., Beggiato M., Halama J., Krems J. F. (2019). How should automated vehicles communicate? effects of a light-based communication approach in a wizard-of-oz study, In Proceedings of the International Conference on Applied Human Factors and Ergonomics. (Cham: Springer; ), 79–91. 10.1007/978-3-030-20503-4_8 [DOI] [Google Scholar]
  13. Hudson C. R., Deb S., Carruth D. W., McGinley J., Frey D. (2018). Pedestrian perception of autonomous vehicles with external interacting features, in Proceedings of the International Conference on Applied Human Factors and Ergonomics. (Cham: Springer; ), 33–39. 10.1007/978-3-319-94334-3_5 [DOI] [Google Scholar]
  14. Li Y., Dikmen M., Hussein T. G., Wang Y., Burns C. (2018). To cross or not to cross: urgency-based external warning displays on autonomous vehicles to improve pedestrian crossing safety, in Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (New York, NY: ACM; ), 188–197. [Google Scholar]
  15. Mahadevan K., Somanath S., Sharlin E. (2018). Communicating awareness and intent in autonomous vehicle-pedestrian interaction, in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (New York, NY: ACM; ), 429. [Google Scholar]
  16. Othersen I., Conti-Kufner A., Dietrich A., Maruhn P., Bengler K. (2018). Designing for automated vehicle and pedestrian communication, in Proceedings of the Perspectives on eHMIs from Older and Younger Persons (Netherlands: HFES Europe Annual Meeting; ). [Google Scholar]
  17. Petzoldt T., Schleinitz K., Banse R. (2018). Potential safety effects of a frontal brake light for motor vehicles. IEEE Intell. Trans. Sys. 12, 449–453. 10.1049/iet-its.2017.0321 [DOI] [Google Scholar]
  18. Song Y. E., Lehsing C., Fuest T., Bengler K. (2018). External HMIs and their Effect on the Interaction Between Pedestrians and Automated Vehicles, in Proceedings of the International Conference on Intelligent Human Systems Integration (Cham: Springer; ), 13–18. 10.1007/978-3-319-73888-8_3 [DOI] [Google Scholar]
  19. Stadler S., Cornet H., Theoto T. N., Frenkler F. (2019). A tool, not a toy: using virtual reality to evaluate the communication between autonomous vehicles and pedestrians, in Augmented Reality and Virtual Reality, eds tom Dieck M., Jung T. (Cham: Springer; ), 203–216. 10.1007/978-3-030-06246-0_15 [DOI] [Google Scholar]
  20. Zhang J., Vinkhuyzen E., Cefkin M. (2017). Evaluation of an autonomous vehicle external communication system concept: a survey study, in Proceedings of the International Conference on Applied Human Factors and Ergonomics. (Cham: Springer; ), 650–661. 10.1007/978-3-319-60441-1_63 [DOI] [Google Scholar]

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