EMATO: エネルギー消費モデルを考慮した自動運転の軌道最適化
EMATO: Energy-Model-Aware Trajectory Optimization for Autonomous Driving
自動運転の軌道計画において、道路勾配予測と交通流を考慮しつつエネルギー消費モデルを組み込んだオンライン非線形計画法を提案し、セダンとトラックで有効性を検証した。
著者: Zhaofeng Tian, Lichen Xia, Weisong Shi
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Autonomous driving lacks strong proof of energy efficiency with the energy-model-agnostic trajectory planning. To achieve an energy consumption model-aware trajectory planning for autonomous driving, this study proposes an online nonlinear programming method that optimizes the polynomial trajectories generated by the Frenet polynomial method while considering both traffic trajectories and road slope prediction. This study further investigates how the energy model can be leveraged in different driving conditions to achieve higher energy efficiency. Case studies, quantitative studies, and ablation studies are conducted in a sedan and truck model to prove the effectiveness of the method.
関連論文
- 混雑交通における時空間安全制約を用いたリアルタイム並列軌道最適化自動運転/軌道最適化
- DL-IAPSとPJSO:経路・速度分離型軌道最適化と自動運転への応用自動運転/軌道最適化
