Speed profiles and GPS Trajectories for Traffic Rule Recognition (6 Junctions, Hannover, Germany)

This dataset is a subset of a much larger data collection and used for the analysis of speed- and time-profiles of trajectories crossing different selected intersections. Resulting findings can be used for the intersection categorization according to traffic regulation types.

The six selected intersections (A - F) and the crossing trajectory samples (green) can be seen in the subsequent figure: Intersections

Data Acquisition

The trajectory samples were recorded using an android smartphone while driving a car in and around the city of Hannover, Germany. The acquisition period was from December 2017 to March 2019 by only a single person. The recording of the trajectories has taken place without restrictions in order to reflect a normal behavior of everyday car journeys. The sampling rate is approximately 1 sample per second.

Related Publications:

  • Zourlidou, S., Sester, M. and Hu, S. (2022): Recognition of Intersection Traffic Regulations From Crowdsourced Data. Preprints 2022, 2022070012. DOI: https://doi.org/10.20944/preprints202207.0012.v1

  • Zourlidou, S., Golze, J. and Sester, M. (2022): Traffic Regulation Recognition using Crowd-Sensed GPS and Map Data: a Hybrid Approach, AGILE GIScience Ser., 3, 22, 2022. https://doi.org/10.5194/agile-giss-3-22-2022

  • Cheng, H., Lei, H., Zourlidou, S., Sester, M. (2022): Traffic Control Recognition with an Attention Mechanism Using Speed-Profile and Satellite Imagery data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2022, S. 287–29. https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-287-2022

  • Wang, C., Zourlidou, S., Golze, J. and Sester, M. (2020): Trajectory analysis at intersections for traffic rule identification. Geo-spatial Information Science, 11(4):1-10. https://doi.org/10.1080/10095020.2020.1843374

  • Cheng, H., Zourlidou, S. and Sester, M. (2020): Traffic Control Recognition with Speed-Profiles: A Deep Learning Approach. ISPRS Int. J. Geo-Inf. 2020, 9, 652. https://doi.org/10.3390/ijgi9110652

  • Golze, J., Zourlidou, S. and Sester, M. (2020): Traffic Regulator Detection Using GPS Trajectories. KN J. Cartogr. Geogr. Inf. https://doi.org/10.1007/s42489-020-00048-x

  • Zourlidou, S., Fischer, C. and Sester, M. (2019): Classification of street junctions according to traffic regulators. In: Kyriakidis, P., Hadjimitsis, D., Skarlatos, D. and Mansourian, A., (eds) 2019. Accepted short papers and posters from the 22nd AGILE conference on geo-information science. Cyprus University of Technology 17–20 June 2019, Limassol, Cyprus.

Related Datasets:

  • Zourlidou, S., Golze, J. and Sester, M. (2022). Dataset: GPS Trajectory Dataset of the Region of Hannover, Germany. https://doi.org/10.25835/9bidqxvl

  • Zourlidou, S., Golze, J. and Sester, M. (2022). Dataset: Traffic Regulator Ground-truth Information for the Chicago Trajectory Dataset. https://doi.org/10.25835/0vifyzqi

  • Zourlidou, S., Golze, J. and Sester, M. (2022). Dataset: GPS Trajectory Dataset and Traffic Regulation Information of the Region of Edessa, Greece. https://doi.org/10.25835/v0mzwob3

  • Zourlidou, S., Golze, J. and Sester, M. (2022). Dataset: Traffic Regulator Ground-truth Information of the City of Hannover, Germany. https://doi.org/10.25835/cqg0x1el

Data and Resources

Cite this as

Zourlidou, Stefania, Golze, Jens, Sester, Monika (2020). Dataset: Speed profiles and GPS Trajectories for Traffic Rule Recognition (6 Junctions, Hannover, Germany). https://doi.org/10.25835/0043786

DOI retrieved: September 14, 2020

Additional Info

Field Value
Imported on October 14, 2021
Last update November 28, 2024
License CC-BY-NC-3.0
Source https://data.uni-hannover.de/dataset/trajectory-analysis-at-intersections-for-traffic-rule-identification
Author Zourlidou, Stefania
Given Name Stefania
Family Name Zourlidou
More Authors
Golze, Jens
Sester, Monika
Author Email Zourlidou, Stefania
Maintainer Jens Golze
Maintainer Email Jens Golze
Source Creation 10 September, 2020, 06:44 AM (UTC+0000)
Source Modified 05 April, 2024, 14:23 PM (UTC+0000)