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Eye tracking measures of bicyclists' behavior and perception: A systematic review.
- Source :
-
Transportation Research: Part F . Nov2024, Vol. 107, p52-68. 17p. - Publication Year :
- 2024
-
Abstract
- • Systematic literature review of 35 articles using eye-tracking in cycling experiments. • Gaze metrics offer insights into factors influencing cycling behavior and assess mental workload/stress from a cyclist-centered perspective. • Examination of eye-tracking device selection and gaze metric adoption/interpretation in relation to research objectives. • The diversity in gaze metrics design and interpretation highlights the need for standardization to facilitate cross-study comparisons. With improved portability and affordability, eye tracking devices have facilitated an expanding range of cycling experiments aimed at understanding cycling behavior and potential risks. Given the complexity of cyclists' visual behavior and gaze measurements, we provide a comprehensive review with three key focuses: 1) the adoption and interpretation of various gaze metrics derived from cycling experiments, 2) a summary of the findings of those experiments, and 3) identifying areas for future research. A systematic review of three databases yielded thirty-five articles that met our inclusion criteria. Our review results show that cycling experiments with eye tracking allow analysis of the viewpoint of the cyclist and reactions to the built environment, road conditions, navigation behavior, and mental workload and/or stress levels. Our review suggests substantial variation in research objectives and the consequent selection of eye-tracking devices, experimental design, and which gaze metrics are used and interpreted. A variety of general gaze metrics and gaze measurements related to Areas of Interest (AOI) are applied to infer cyclists' mental workload/stress levels and attention allocation respectively. The diversity of gaze metrics reported in the literature makes cross-study comparisons difficult. Areas for future research, especially potential integration with computer vision are also discussed. [ABSTRACT FROM AUTHOR]
- Subjects :
- *EYE tracking
*COMPUTER vision
*CYCLING
*BUILT environment
*AREA measurement
*GAZE
Subjects
Details
- Language :
- English
- ISSN :
- 13698478
- Volume :
- 107
- Database :
- Academic Search Index
- Journal :
- Transportation Research: Part F
- Publication Type :
- Academic Journal
- Accession number :
- 181091147
- Full Text :
- https://doi.org/10.1016/j.trf.2024.08.026