Which Visual Cues do Drivers Use to Anticipate and Slow Down in Freeway Curve Approach? An Eye-Tracking and Think-Aloud On-road Study - Dataset

An on road experiment was conducted in which 31 participants drove through six freeway curves in their own car. During the experiment, look-ahead fixations and speed were recorded using an eye-tracker and a GPS tracker, respectively. In addition to these measurements, the participants verbalised their reasons for changing speed.  The collected data is shared here: - GPS data of the researched sections - Filtered Eye-tracking data, containing the fixations, timestamps and AoI labels - Verbalisations - 6 muted video’s of the HD-camera from the eye-tracker, containing fixation data (a video for each curve, from a single participant) - Output from the questionnaires More backgrounds can be read in: Vos, J., de Winter, J., Farah, H., & Hagenzieker, M. (2023). Which Visual Cues do Drivers Use to Anticipate and Slow Down in Freeway Curve Approach?  - An Eye-Tracking and Think-Aloud On-road Study. Transportation Research Part F: Traffic Psychology and Behaviour</p

Which Visual Cues do Drivers Use to Anticipate and Slow Down in Freeway Curve Approach? An Eye-Tracking and Think-Aloud On-road Study - Dataset

An on road experiment was conducted in which 31 participants drove through six freeway curves in their own car. During the experiment, look-ahead fixations and speed were recorded using an eye-tracker and a GPS tracker, respectively. In addition to these measurements, the participants verbalised their reasons for changing speed.  The collected data is shared here: - GPS data of the researched sections - Filtered Eye-tracking data, containing the fixations, timestamps and AoI labels - Verbalisations - 6 muted video’s of the HD-camera from the eye-tracker, containing fixation data (a video for each curve, from a single participant) - Output from the questionnaires More backgrounds can be read in: Vos, J., de Winter, J., Farah, H., & Hagenzieker, M. (2023). Which Visual Cues do Drivers Use to Anticipate and Slow Down in Freeway Curve Approach?  - An Eye-Tracking and Think-Aloud On-road Study. Transportation Research Part F: Traffic Psychology and Behaviour</p

Supplementary data for the article: What will the car driver do? A video-based questionnaire study on cyclists’ anticipation during safety-critical situations

This data set includes data for figures and statistical analyses, an online questionnaire, and supplementary materials (including an overview of the video clips, links to the exact locations of the intersection situations, and supplementary data analyses) for the paper: Kovácsová, N., De Winter, J. C. F., & Hagenzieker, M. (2019). What will the car driver do? A video-based questionnaire study on cyclists’ anticipation during safety-critical situations. Journal of Safety Research, 69, 11–21

Supplementary data for the article: Cycling Skill Inventory: Assessment of motor-tactical skills and safety motives

Raw data and scripts belonging to the article: De Winter, J. C. F., Kovácsová, N., & Hagenzieker, M. P. (2018). Cycling Skill Inventory: Assessment of motor-tactical skills and safety motives

Support systems for cyclists in automated traffic: A review and future outlook

Research data for the paper Berge, S. H., de Winter, J., & Hagenzieker, M. (2022). Support systems for cyclists in automated traffic: A review and future outlook. This paper provides a synthesis of the current literature on communication technologies, systems, and devices available to cyclists and discusses the outlook of technology-driven solutions in future automated traffic. We have analysed and coded 92 support systems using a taxonomy of 13 variables based on the physical, communicational, and functional attributes of the systems.  The data set contains a spreadsheet with the literature sample and the analysis. </p

Support systems for cyclists in automated traffic: A review and future outlook

Research data for the paper Berge, S. H., de Winter, J., & Hagenzieker, M. (2022). Support systems for cyclists in automated traffic: A review and future outlook. This paper provides a synthesis of the current literature on communication technologies, systems, and devices available to cyclists and discusses the outlook of technology-driven solutions in future automated traffic. We have analysed and coded 92 support systems using a taxonomy of 13 variables based on the physical, communicational, and functional attributes of the systems.  The data set contains a spreadsheet with the literature sample and the analysis. </p

Which Visual Cues do Drivers Use to Anticipate and Slow Down in Freeway Curve Approach? An Eye-Tracking and Think-Aloud On-road Study - Dataset

An on road experiment was conducted in which 31 participants drove through six freeway curves in their own car. During the experiment, look-ahead fixations and speed were recorded using an eye-tracker and a GPS tracker, respectively. In addition to these measurements, the participants verbalised their reasons for changing speed.  The collected data is shared here: - GPS data of the researched sections - Filtered Eye-tracking data, containing the fixations, timestamps and AoI labels - Verbalisations - 6 muted video’s of the HD-camera from the eye-tracker, containing fixation data (a video for each curve, from a single participant) - Output from the questionnaires More backgrounds can be read in: Vos, J., de Winter, J., Farah, H., & Hagenzieker, M. (2023). Which Visual Cues do Drivers Use to Anticipate and Slow Down in Freeway Curve Approach?  - An Eye-Tracking and Think-Aloud On-road Study. Transportation Research Part F: Traffic Psychology and Behaviour</p

Data underlying the publication: Speed behaviour upon approaching freeway curves

High Frequency Floating Car Data was collected to analyse circa 1 million individual speed profiles on 153 Dutch freeway curves. By defining the positions where the acceleration approaches 0 m/s2 before and after a curve starts, the positions when the driver started and stopped decelerating upon curve entry were defined.&nbsp;These positions and speeds are put in a database, combined with detailed reconstruction of the curves and their surroundings, as well as three dimensional sight distance analysis. This aggregated database is shared here, along a file explaining the different variables in the database.More backgrounds can be read in:Vos, J., Farah, H., &amp; Hagenzieker, M. (2021). Speed behaviour upon approaching freeway curves. Accident Analysis &amp; Prevention, 159, 106276. doi: https://doi.org/10.1016/j.aap.2021.106276</p

Data underlying the publication: Speed behaviour upon approaching freeway curves

High Frequency Floating Car Data was collected to analyse circa 1 million individual speed profiles on 153 Dutch freeway curves. By defining the positions where the acceleration approaches 0 m/s2 before and after a curve starts, the positions when the driver started and stopped decelerating upon curve entry were defined.&nbsp;These positions and speeds are put in a database, combined with detailed reconstruction of the curves and their surroundings, as well as three dimensional sight distance analysis. This aggregated database is shared here, along a file explaining the different variables in the database.More backgrounds can be read in:Vos, J., Farah, H., &amp; Hagenzieker, M. (2021). Speed behaviour upon approaching freeway curves. Accident Analysis &amp; Prevention, 159, 106276. doi: https://doi.org/10.1016/j.aap.2021.106276</p

Data underlying the publication: How do Dutch drivers perceive horizontal curves on freeway interchanges and which cues influence their speed choice?

An online survey was designed with 28 sets of curve comparisons. In each set illustrations of two different curves out of a total of 8 curves were shown, and the participants were asked in which curve they would drive faster. After this comparison task, the participants were asked for their reasons to drive faster in an open question. In total 819 participants in the age range of 18 and 78 (mean= 41.3; Std.=11.9) completed the survey. The output from the survey is shared here, and is in Dutch. A seperate sheet explaining the variables is added.More backgrounds can be read in:Vos, J., Farah, H., &amp; Hagenzieker, M. (2020). How do dutch drivers perceive horizontal curves on freeway interchanges and which cues influence their speed choice? IATSS Research. doi: https://doi.org/10.1016/j.iatssr.2020.11.004</p