  Crash data of autonomous vehicles (AV) or vehicles equipped with advanced
driver assistance systems (ADAS) are the key information to understand the
crash nature and to enhance the automation systems. However, most of the
existing crash data sources are either limited by the sample size or suffer
from missing or unverified data. To contribute to the AV safety research
community, we introduce AVOID: an open AV crash dataset. Three types of
vehicles are considered: Advanced Driving System (ADS) vehicles, Advanced
Driver Assistance Systems (ADAS) vehicles, and low-speed autonomous shuttles.
The crash data are collected from the National Highway Traffic Safety
Administration (NHTSA), California Department of Motor Vehicles (CA DMV) and
incident news worldwide, and the data are manually verified and summarized in
ready-to-use format. In addition, land use, weather, and geometry information
are also provided. The dataset is expected to accelerate the research on AV
crash analysis and potential risk identification by providing the research
community with data of rich samples, diverse data sources, clear data
structure, and high data quality.
