Dataset : EU Long-term Dataset with Multiple Sensors for Autonomous Driving

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Quotation

Zhi Yan ; Li Sun ; Tomas Krajnik ; Yassine Ruichek (2018): EU Long-term Dataset with Multiple Sensors for Autonomous Driving. Connaissance et Intelligence Artificielle Distribuées. FR-13002091000019-2020-07-23

General metadata

Identifier : local : FR-13002091000019-2020-07-23
Description :
This dataset was collected with our robocar (in human driving mode of course), equipped with eleven heterogeneous sensors, in the downtown (for long-term data) and suburban (for roundabout data) areas of Montbéliard in France.
Disciplines :
computer science, artificial intelligence (engineering science), computer science, interdisciplinary applications (engineering science), computer science, software engineering (engineering science), robotics (engineering science)
Keywords :

Dates :
Data acquisition : from May 2018 to Apr 2019
Data provision : 1 Nov 2018
Metadata record :
Creation : 23 Jul 2020
Update : 18 Aug 2020

Update periodicity : as needed
Language : English (eng)
Additional information :
As we take privacy very seriously and handle personal data in line with the EU’s data protection law (i.e. the General Data Protection Regulation (GDPR)), we used deep learning-based methods to post-process the camera-recorded images in order to blur face and license plate information. The images have been released successively from the first quarter of 2020.
Audience : Research, Stakeholder

Administrative metadata

Data creatorsAffiliation
Zhi YanCIAD (FRA)
Li SunSheffield - Computer Sc. (GBR)
Tomas KrajnikCzTU (CZE)
Yassine RuichekCIAD (FRA)
Publisher : Connaissance et Intelligence Artificielle Distribuées
Science contact : Zhi Yan website e-mail
Project and funder :
Access : available

Technical metadata

Formats : application/x-ros-bag
Data acquisition methods :
  • Observational data :
    The vehicle speed was limited to 50 km/h following the French traffic rules. For the long-term data, the driving distance is about 5.0 km (containing a small and a big road loop for loop-closure purpose) and the length of recorded data is about 16 minutes for each collection round. For the roundabout data, the driving distance is about 4.2 km (containing 10 roundabouts with various sizes) and the length of recorded data is about 12 minutes for each collection round.
Datatype : Dataset

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