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arXiv · 2308.01369

An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems

Ni Dong·Shuming Chen·Yina Wu·Yiheng Feng·Xiaobo Liu
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Abstract

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.

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Ni Dong, Shuming Chen, Yina Wu, Yiheng Feng, Xiaobo Liu. 2023-08-02. An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems. https://arxiv.org/abs/2308.01369

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