Building Reliable Datasets for Autonomous Vehicles: Data Factory for the Industry and Intelligent Trains

Autonomous vehicles have long been a worldwide research subject. For about a decade, the theme has known a growing attention. They promise to bring equity, liberty and flexibility to users, while being better optimized and less demanding in fuel and resources. On the last point however, many efforts must still be conducted. Indeed, to observe and react in its environment, the vehicle must embed many sensors. Each of them produces huge amount of data. To make sure algorithms and AI-based solutions are properly designed, training/validation/test data must answer some prerequisites. In particular, the industry has more constrains and requirements than academia. This paper proposes a concept of data factory for railway and industrial purposes. First of all, the conception of acquisition plans and data sanity checks are presented. Then storage and necessary volumes are discussed, followed by annotation and access.