# ROCO: A Roundabout Traffic Conflict Dataset

arXiv: https://arxiv.org/abs/2303.00563 · HTML: https://mlsanity.com/paper/2303.00563/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 41 references that are in the map.
- First posted on arXiv 1 Mar 2023.

## Builds on (most cited first, 7 of 7)

- [SlowFast Networks for Video Recognition](https://mlsanity.com/paper/1812.03982/) (2018)
- [V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction](https://mlsanity.com/paper/2008.07519/) (2020)
- [DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection](https://mlsanity.com/paper/2204.05575/) (2022)
- [Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds](https://mlsanity.com/paper/1905.05265/) (2019)
- [Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task](https://mlsanity.com/paper/2203.13608/) (2022)
- ["Curse of rarity" for autonomous vehicles](https://mlsanity.com/paper/2207.02749/) (2022)
- [Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras](https://mlsanity.com/paper/2206.09770/) (2022)

## Built on by (most cited first, 1 of 1)

- [MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles](https://mlsanity.com/paper/2310.05290/) (2023)

## Abstract (arXiv)

Traffic conflicts have been studied by the transportation research community as a surrogate safety measure for decades. However, due to the rarity of traffic conflicts, collecting large-scale real-world traffic conflict data becomes extremely challenging. In this paper, we introduce and analyze ROCO - a real-world roundabout traffic conflict dataset. The data is collected at a two-lane roundabout at the intersection of State St. and W. Ellsworth Rd. in Ann Arbor, Michigan. We use raw video dataflow captured from four fisheye cameras installed at the roundabout as our input data source. We adopt a learning-based conflict identification algorithm from video to find potential traffic conflicts, and then manually label them for dataset collection and annotation. In total 557 traffic conflicts and 17 traffic crashes are collected from August 2021 to October 2021. We provide trajectory data of the traffic conflict scenes extracted using our roadside perception system. Taxonomy based on traffic conflict severity, reason for the traffic conflict, and its effect on the traffic flow is provided. With the traffic conflict data collected, we discover that failure to yield to circulating vehicles when entering the roundabout is the largest contributing reason for traffic conflicts. ROCO dataset will be made public in the short future.