CaRINA Dataset: Benchmark for Road Detection in Challenging Urban Scenarios

Detection of the road surface is a key capability for both path planning and object detection for Autonomous Vehicles. Current road datasets and benchmarks only depict European and North American scenarios, while emerging countries have higher projected consumer acceptance of AV and DAS technologies. This page presents selected Brazilian urban scenarios datasets and road detection benchmark s consisting of annotate RADAR, LIDAR and camera data. The main focus of this work is to provide challenging scenarios for road detection algorithms evaluation.

Map of collected data log.
Collected data coverage (blue) from a neighborhood surrounding the university campus of São Carlos; Select segments (red); and regions without RTK correction on GPS signal (yellow).


All datasets on this page are copyright by us and published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.



  author={P. Y. Shinzato and T. C. dos Santos and L. A. Rosero and 

D. A. Ridel and C. M. Massera and F. Alencar and M. P. Batista and A. Y. Hata and F. S. Osório and D. F. Wolf},

  booktitle={2016 IEEE 19th International Conference on Intelligent Transportation 
  Systems (ITSC)}, 
  title={CaRINA dataset: An emerging-country urban scenario benchmark for road 

detection systems},