Driving Datasets Literature Review

Abstract

This report is a survey of the different autonomous driving datasets which have been published up to date. The first section introduces the many sensor types used in autonomous driving datasets. The second section investigates the calibration and synchronization procedure required to generate accurate data. The third section describes the diverse driving tasks explored by the datasets. Finally, the fourth section provides comprehensive lists of datasets, mainly in the form of tables.

References in corpus (8)

• Hand-Eye Calibration
• Learning a Driving Simulator
• CityPersons: A Diverse Dataset for Pedestrian Detection
• A Commute in Data: The comma2k19 Dataset
• The StreetLearn Environment and Dataset
• LiDAR point clouds correction acquired from a moving car based on CAN-bus data
• Highway Driving Dataset for Semantic Video Segmentation
• BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous Driving

Cited by in corpus (1)

• Ad-datasets: a meta-collection of data sets for autonomous driving