  Correctly identifying vulnerable road users (VRUs), e.g. cyclists and
pedestrians, remains one of the most challenging environment perception tasks
for autonomous vehicles (AVs). This work surveys the current state-of-the-art
in VRU detection, covering topics such as benchmarks and datasets, object
detection techniques and relevant machine learning algorithms. The article
concludes with a discussion of remaining open challenges and promising future
research directions for this domain.
