# Ford Multi-AV Seasonal Dataset

arXiv: https://arxiv.org/abs/2003.07969 · HTML: https://mlsanity.com/paper/2003.07969/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Mar 2020.

## Built on by (most cited first, 30 of 39)

- [Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey](https://mlsanity.com/paper/2307.04370/) (2023)
- [Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys](https://mlsanity.com/paper/2303.17220/) (2023)
- [SSCBench: A Large-Scale 3D Semantic Scene Completion Benchmark for Autonomous Driving](https://mlsanity.com/paper/2306.09001/) (2023)
- [Uncertainty-aware Vision-based Metric Cross-view Geolocalization](https://mlsanity.com/paper/2211.12145/) (2022)
- [Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization](https://mlsanity.com/paper/2309.15556/) (2023)
- [Satellite Image Based Cross-view Localization for Autonomous Vehicle](https://mlsanity.com/paper/2207.13506/) (2022)
- [View Consistent Purification for Accurate Cross-View Localization](https://mlsanity.com/paper/2308.08110/) (2023)
- [Dataset and Benchmark: Novel Sensors for Autonomous Vehicle Perception](https://mlsanity.com/paper/2401.13853/) (2024)
- [A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services](https://mlsanity.com/paper/2304.14271/) (2023)
- [Adapting Fine-Grained Cross-View Localization to Areas without Fine Ground Truth](https://mlsanity.com/paper/2406.00474/) (2024)
- [Asynchronous Multi-View SLAM](https://mlsanity.com/paper/2101.06562/) (2021)
- [Ad-datasets: a meta-collection of data sets for autonomous driving](https://mlsanity.com/paper/2202.01909/) (2022)
- [MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation](https://mlsanity.com/paper/2506.18678/) (2025)
- [Continuous Self-Localization on Aerial Images Using Visual and Lidar Sensors](https://mlsanity.com/paper/2203.03334/) (2022)
- [S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM](https://mlsanity.com/paper/2210.13723/) (2022)
- [Deep Transfer Learning for Intelligent Vehicle Perception: a Survey](https://mlsanity.com/paper/2306.15110/) (2023)
- [RSRD: A Road Surface Reconstruction Dataset and Benchmark for Safe and Comfortable Autonomous Driving](https://mlsanity.com/paper/2310.02262/) (2023)
- [Diverse Complexity Measures for Dataset Curation in Self-driving](https://mlsanity.com/paper/2101.06554/) (2021)
- [Improving Worst Case Visual Localization Coverage via Place-specific Sub-selection in Multi-camera Systems](https://mlsanity.com/paper/2206.13883/) (2022)
- [PIDLoc: Cross-View Pose Optimization Network Inspired by PID Controllers](https://mlsanity.com/paper/2503.02388/) (2025)
- [A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios](https://mlsanity.com/paper/2505.07622/) (2025)
- [S-BEV: Semantic Birds-Eye View Representation for Weather and Lighting Invariant 3-DoF Localization](https://mlsanity.com/paper/2101.09569/) (2021)
- [Stereo Visual Odometry with Deep Learning-Based Point and Line Feature Matching using an Attention Graph Neural Network](https://mlsanity.com/paper/2308.01125/) (2023)
- [Dynamically Modulating Visual Place Recognition Sequence Length For Minimum Acceptable Performance Scenarios](https://mlsanity.com/paper/2407.00863/) (2024)
- [Princeton365: A Diverse Dataset with Accurate Camera Pose](https://mlsanity.com/paper/2506.09035/) (2025)
- [Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images](https://mlsanity.com/paper/2102.13262/) (2021)
- [OCTraN: 3D Occupancy Convolutional Transformer Network in Unstructured Traffic Scenarios](https://mlsanity.com/paper/2307.10934/) (2023)
- [PointCompress3D: A Point Cloud Compression Framework for Roadside LiDARs in Intelligent Transportation Systems](https://mlsanity.com/paper/2405.01750/) (2024)
- [Evaluating Global Geo-alignment for Precision Learned Autonomous Vehicle Localization using Aerial Data](https://mlsanity.com/paper/2503.13896/) (2025)
- [Cross-View Localization via Redundant Sliced Observations and A-Contrario Validation](https://mlsanity.com/paper/2508.05369/) (2025)

## Abstract (arXiv)

This paper presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles at different days and times during 2017-18. The vehicles traversed an average route of 66 km in Michigan that included a mix of driving scenarios such as the Detroit Airport, freeways, city-centers, university campus and suburban neighbourhoods, etc. Each vehicle used in this data collection is a Ford Fusion outfitted with an Applanix POS-LV GNSS system, four HDL-32E Velodyne 3D-lidar scanners, 6 Point Grey 1.3 MP Cameras arranged on the rooftop for 360-degree coverage and 1 Pointgrey 5 MP camera mounted behind the windshield for the forward field of view. We present the seasonal variation in weather, lighting, construction and traffic conditions experienced in dynamic urban environments. This dataset can help design robust algorithms for autonomous vehicles and multi-agent systems. Each log in the dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground truth pose, and 3D maps. All data is available in Rosbag format that can be visualized, modified and applied using the open-source Robot Operating System (ROS). We also provide the output of state-of-the-art reflectivity-based localization for bench-marking purposes. The dataset can be freely downloaded at our website.