  Recognition of the surrounding environment using a camera is an important
technology in Advanced Driver-Assistance Systems and Autonomous Driving, and
recognition technology is often solved by machine learning approaches such as
deep learning in recent years. Machine learning requires datasets for learning
and evaluation. To develop robust recognition technology in the real world, in
addition to normal driving environment, data in environments that are difficult
for cameras such as rainy weather or nighttime are essential. We have
constructed a dataset that one can benchmark the technology, targeting the
velocity recognition of the leading vehicle. This task is an important one for
the Advanced Driver-Assistance Systems and Autonomous Driving. The dataset is
available at https://signate.jp/competitions/657
