OSM対HDマップ：軌道予測のための地図表現
OSM vs HD Maps: Map Representations for Trajectory Prediction
自動運転の軌道予測において、高精細地図の代わりにOpenStreetMapを用いる手法を提案し、予測時間を2倍に延ばしつつ競争力のある性能を達成した。
著者: Jing-Yan Liao, Parth Doshi, Zihan Zhang, David Paz, Henrik Christensen
分類: cs.CV, cs.AI, cs.RO
原文アブストラクト
While High Definition (HD) Maps have long been favored for their precise depictions of static road elements, their accessibility constraints and susceptibility to rapid environmental changes impede the widespread deployment of autonomous driving, especially in the motion forecasting task. In this context, we propose to leverage OpenStreetMap (OSM) as a promising alternative to HD Maps for long-term motion forecasting. The contributions of this work are threefold: firstly, we extend the application of OSM to long-horizon forecasting, doubling the forecasting horizon compared to previous studies. Secondly, through an expanded receptive field and the integration of intersection priors, our OSM-based approach exhibits competitive performance, narrowing the gap with HD Map-based models. Lastly, we conduct an exhaustive context-aware analysis, providing deeper insights in motion forecasting across diverse scenarios as well as conducting class-aware comparisons. This research not only advances long-term motion forecasting with coarse map representations but additionally offers a potential scalable solution within the domain of autonomous driving.
