An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems
An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems
著者: Ni Dong, Shuming Chen, Yina Wu, Yiheng Feng, Xiaobo Liu
分類: cs.RO, cs.AI
原文アブストラクト
Navigating automated driving systems (ADSs) through complex driving environments is difficult. Predicting the driving behavior of surrounding human-driven vehicles (HDVs) is a critical component of an ADS. This paper proposes an enhanced motion-planning approach for an ADS in a highway-merging scenario. The proposed enhanced approach utilizes the results of two aspects: the driving behavior and long-term trajectory of surrounding HDVs, which are coupled using a hierarchical model that is used for the motion planning of an ADS to improve driving safety.