Reconstructed Roundabout Driving Dataset
This dataset is based on the ACFR Five Roundabouts Dataset. The original tracking data of over 23,000 traffic vehicles have been processed with an optimization-based filtering method to combat measurement noise and errors. Smooth velocity and acceleration signals are reconstructed. The processed recordings have then undergone a selection process using DBSCAN to remove the erroneous samples. The remaining samples contained in this dataset are considered representative of how average human drivers approach a roundabout scenario in daily driving.
We sincerely hope that sharing this dataset would help researchers in the relevant fields. Explanations on the dataset structure can be found in the README in the zip file. In case of any questions, please contact the authors via: firstname.lastname@example.org. Thank you!
The details of the processing method are presented in:
Y. Zheng, B. Shyrokau and T. Keviczky, "Comfort and Time Efficiency: A Roundabout Case Study," 2021 IEEE International Conference on Intelligent Transportation Systems (ITSC), 2021
(To be available online in Oct. 2021. Citation information will be updated.)
When using this dataset, please kindly cite our work above as well as the following:
A. Zyner, S. Worrall and E. M. Nebot, "ACFR Five Roundabouts Dataset: Naturalistic Driving at Unsignalized Intersections," in IEEE Intelligent Transportation Systems Magazine, vol. 11, no. 4, pp. 8-18, winter 2019, DOI: 10.1109/MITS.2019.2907676.
The original ACFR Five Roundabouts Dataset can be found via: