Abstract
Interactions among drivers and pedestrians especially in heavy urban traffic constitute a key issue that needs to be addressed in the future autonomous vehicles. There is little evidence, however, concerning the signals and cues used by the drivers to infer the future intention of a pedestrian and/or a pedestrian’s awareness of the driver’s vehicle. The paper reports preliminary findings of an instrumented observational study of naturally occurring vehicle – pedestrian interaction cases at high density un-signalized urban crossings. Specifically, 21 experienced drivers drove their own car in a predefined course while equipped with an eye-tracker. In total 321driver – pedestrian interaction cases were analysed based on driver’s eye-gaze analysis and video-assisted retrospective commentary. Several types of signals were identified. These were stratified according to their expressiveness/explicitness. A main finding is that cues with a medium level of expressiveness/explicitness (i.e. eye-gaze from pedestrians) seem to resolve a great number of interaction cases, therefore it is important to explicitly consider this type of cues in future autonomous vehicles. The paper ends with a working model depicting the possible states of mutual attentiveness between driver and pedestrian as identified from the observation data.
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Acknowledgement
This work is a part of the interACT project. interACT has received funding from the European Union’s Horizon 2020 research & innovation programme under grant agreement no 723395. Content reflects only the authors’ view and European Commission is not responsible for any use that may be made of the information it contains.
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Recruitment of participants and data collection was conducted in accordance with National Technical University of Athens ethics procedures concerning research involving human participants.
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Nathanael, D., Portouli, E., Papakostopoulos, V., Gkikas, K., Amditis, A. (2019). Naturalistic Observation of Interactions Between Car Drivers and Pedestrians in High Density Urban Settings. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 823. Springer, Cham. https://doi.org/10.1007/978-3-319-96074-6_42
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DOI: https://doi.org/10.1007/978-3-319-96074-6_42
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