27 datasets found

The dataset used in the paper is a collection of autonomous vehicle scenarios, where each scenario is represented as a 3x3 grid encoding. The scenarios are encoded using Pauli-X...

AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles

The dataset used for testing the OctoPath network in the real-world navigation environment.

The dataset used for testing the OctoPath network in the GridSim simulator.

A new large ‘water on road’ dataset spanning approximately 2 km of driving in various on-road and off-road conditions.

The dataset used for road slope estimation and vehicle dynamics control.

The dataset used in the paper is a set of logical scenarios for testing autonomous vehicles, including 5 different scenarios with various parameters such as weather, lighting,...

The dataset used in the paper is the Lyft Motion Prediction Dataset, which contains samples of real-world driving on a complex, urban route in Palo Alto, California.

KITTI and Ford Multi-AV Seasonal datasets are used for training and evaluation of the proposed method.

Two cross-view localization datasets, KITTI-CVL and FordAV-CVL, are constructed by collecting spatial-consistent satellite counterparts from Google Map according to the provided...

The dataset used in this paper is a diverse dataset created with real and synthetic images demonstrating that by exploiting spatio-temporal information combined with...

The dataset used in the paper is a collection of images and corresponding affordances (pedestrian hazard, vehicle hazard, red traffic light, and relative heading angle) for...

The A2D2 dataset is a driving dataset containing front-facing camera images and their corresponding steering angles.

The Waymo dataset is a LiDAR-based semantic segmentation dataset, which consists of 798 sequences for training and 202 for validation.

The SullyChen dataset is a driving dataset containing front-facing camera images and their corresponding steering angles.

The Honda, Waymo, A2D2, and SullyChen datasets are used for developing machine learning models for driving-related tasks.

The dataset used in this paper is a set of racing-based references provided by an external planner.

The dataset used in this paper is a set of vehicle states and inputs that represents a set of particular driving maneuvers guaranteeing rich enough data.

A self-driving car dataset that captures real-world urban driving in the center of Las Vegas.

The WoodScape dataset consists of 10,000 annotated images captured from four different view angles: Front View (FV), Mirror-View Right (MVR), Mirror-View Left (MVL), and Rear...