QML for Argoverse 2 Motion Forecasting Challenge
Su, Tong, Wang, Xishun, Yang, Xiaodong
–arXiv.org Artificial Intelligence
To safely navigate in various complex traffic scenarios, autonomous driving systems are generally equipped with a motion forecasting module to provide vital information for the downstream planning module. For the real-world onboard applications, both accuracy and latency of a motion forecasting model are essential. In this report, we present an effective and efficient solution, which ranks the 3rd place [1] in the Argoverse 2 Motion Forecasting Challenge 2022.
arXiv.org Artificial Intelligence
Jul-13-2022