  Estimated time of arrival (ETA) is a very important factor in the
transportation system. It has attracted increasing attentions and has been
widely used as a basic service in navigation systems and intelligent
transportation systems. In this paper, we propose a novel solution to the ETA
estimation problem, which is an ensemble on tree models and neural networks. We
proved the accuracy and robustness of the solution on the A/B list and finally
won first place in the SIGSPATIAL 2021 GISCUP competition.
