# FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains

arXiv: https://arxiv.org/abs/2002.05665 · HTML: https://mlsanity.com/paper/2002.05665/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Feb 2020.

## Built on by (most cited first, 10 of 10)

- [Confident Object Detection via Conformal Prediction and Conformal Risk Control: an Application to Railway Signaling](https://mlsanity.com/paper/2304.06052/) (2023)
- [OSDaR23: Open Sensor Data for Rail 2023](https://mlsanity.com/paper/2305.03001/) (2023)
- [Conformal Prediction for Trustworthy Detection of Railway Signals](https://mlsanity.com/paper/2301.11136/) (2023)
- [RailGoerl24: G"orlitz Rail Test Center CV Dataset 2024](https://mlsanity.com/paper/2504.00204/) (2025)
- [Forging Spatial Intelligence: A Roadmap of Multi-Modal Data Pre-Training for Autonomous Systems](https://mlsanity.com/paper/2512.24385/) (2025)
- [A Comparative Analysis of Visual Odometry in Virtual and Real-World Railways Environments](https://mlsanity.com/paper/2403.17084/) (2024)
- [Railway LiDAR semantic segmentation based on intelligent semi-automated data annotation](https://mlsanity.com/paper/2410.13383/) (2024)
- [LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring](https://mlsanity.com/paper/2504.18203/) (2025)
- [Railway Artificial Intelligence Learning Benchmark (RAIL-BENCH): A Benchmark Suite for Perception in the Railway Domain](https://mlsanity.com/paper/2604.22507/) (2026)
- [A Multi-Sensor Dataset for Monitoring the Operational Environment of Rail Vehicles](https://mlsanity.com/paper/2608.04704/) (2026)

## Abstract (arXiv)

In the realm of autonomous transportation, there have been many initiatives for open-sourcing self-driving cars datasets, but much less for alternative methods of transportation such as trains. In this paper, we aim to bridge the gap by introducing FRSign, a large-scale and accurate dataset for vision-based railway traffic light detection and recognition. Our recordings were made on selected running trains in France and benefited from carefully hand-labeled annotations. An illustrative dataset which corresponds to ten percent of the acquired data to date is published in open source with the paper. It contains more than 100,000 images illustrating six types of French railway traffic lights and their possible color combinations, together with the relevant information regarding their acquisition such as date, time, sensor parameters, and bounding boxes. This dataset is published in open-source at the address urlhttps://frsign.irt-systemx.fr. We compare, analyze various properties of the dataset and provide metrics to express its variability. We also discuss specific challenges and particularities related to autonomous trains in comparison to autonomous cars.