CADC

The CADC dataset aims to promote research to improve self-driving in adverse weather conditions. This is the first public dataset to focus on real world driving data in snowy weather conditions. It features: For this dataset, routes were chosen with various levels of traffic, a variety of vehicles and always with snowfall. Sequences were selected from data collected within the Region of Waterloo, Canada. We collected data using the Autonomoose, a Lincoln MKZ Hybrid mounted with a full suite of LiDAR, inertial and vision sensors. Please refer to the figure below for the sensor configuration of the Autonomoose.

CADC数据集旨在推动恶劣天气条件下自动驾驶技术优化的相关研究。这是首个聚焦真实世界降雪天气下驾驶数据的公开数据集。该数据集具备如下特点：选取的行驶路线覆盖不同交通流量等级、多种车型，且全程均伴有降雪。数据序列采集自加拿大滑铁卢地区。我们使用搭载了全套激光雷达（LiDAR）、惯性传感器与视觉传感器的林肯MKZ混合动力自动驾驶测试平台Autonomoose完成了数据采集。有关Autonomoose的传感器配置，请参阅下图。

搜集汇总

背景与挑战

背景概述

CADC数据集是一个专注于恶劣天气条件下自动驾驶研究的公开数据集，包含56,000张相机图像和7,000次LiDAR扫描，覆盖多种复杂驾驶场景。数据集提供了完整的传感器套件数据，包括LiDAR、相机和GPS/IMU，特别强调雪天驾驶条件的研究。